From c3f2f84761f4e6005134cdbdece9ffa16bf64a15 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 10:49:11 +0100 Subject: [PATCH 01/33] Modifying stpredictions for py310 --- stpredictions/models/OK3/_criterion.c | 25521 +----------- stpredictions/models/OK3/_criterion.pxd | 91 - stpredictions/models/OK3/_splitter.c | 35305 ---------------- stpredictions/models/OK3/_tree.c | 48004 ---------------------- 4 files changed, 1 insertion(+), 108920 deletions(-) delete mode 100644 stpredictions/models/OK3/_criterion.pxd delete mode 100644 stpredictions/models/OK3/_splitter.c delete mode 100644 stpredictions/models/OK3/_tree.c diff --git a/stpredictions/models/OK3/_criterion.c b/stpredictions/models/OK3/_criterion.c index 18ca8e99e..06f2230dd 100644 --- a/stpredictions/models/OK3/_criterion.c +++ b/stpredictions/models/OK3/_criterion.c @@ -1,25520 +1 @@ -/* Generated by Cython 0.29.23 */ - -/* BEGIN: Cython Metadata -{ - "distutils": { - "depends": [ - "/home/asani/Documents/Hi_Paris_Code_Projects/Florence/venv_stpredictions/lib/python3.9/site-packages/numpy/core/include/numpy/arrayobject.h", - 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PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) -#else -#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) -#endif -#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) -#if PY_MAJOR_VERSION >= 3 -#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) -#else -#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) -#endif -#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) -#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII -static int __Pyx_sys_getdefaultencoding_not_ascii; -static int __Pyx_init_sys_getdefaultencoding_params(void) { - PyObject* sys; - PyObject* default_encoding = NULL; - PyObject* ascii_chars_u = NULL; - PyObject* ascii_chars_b = NULL; - const char* default_encoding_c; - sys = PyImport_ImportModule("sys"); - if (!sys) goto bad; - default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); - Py_DECREF(sys); - if (!default_encoding) goto bad; 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- -/* "sklearn/tree/_tree.pxd":19 - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - * - */ -typedef npy_int32 __pyx_t_7sklearn_4tree_5_tree_INT32_t; - -/* "sklearn/tree/_tree.pxd":20 - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< - * - * from ._splitter cimport Splitter - */ -typedef npy_uint32 __pyx_t_7sklearn_4tree_5_tree_UINT32_t; - -/* "neighbors/_quad_tree.pxd":13 - * cimport numpy as np - * - * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - */ -typedef npy_float32 __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t; 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- -/* "sklearn/tree/_utils.pxd":19 - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - * - */ -typedef npy_int32 __pyx_t_7sklearn_4tree_6_utils_INT32_t; - -/* "sklearn/tree/_utils.pxd":20 - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< - * - * - */ -typedef npy_uint32 __pyx_t_7sklearn_4tree_6_utils_UINT32_t; -/* Declarations.proto */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - typedef ::std::complex< float > __pyx_t_float_complex; - #else - typedef float _Complex __pyx_t_float_complex; - #endif -#else - typedef struct { float real, imag; } __pyx_t_float_complex; -#endif -static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); - -/* Declarations.proto */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - typedef ::std::complex< double > __pyx_t_double_complex; - #else - typedef double _Complex __pyx_t_double_complex; - #endif -#else - typedef struct { double real, imag; } __pyx_t_double_complex; -#endif -static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); - - -/*--- Type declarations ---*/ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion; -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter; -struct __pyx_obj_7sklearn_4tree_5_tree_Tree; -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder; -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree; -struct __pyx_obj_7sklearn_4tree_6_utils_Stack; -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator; 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-}; - -/* "sklearn/tree/_tree.pxd":78 - * cdef object _decision_path_sparse_csr(self, object X) - * - * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< - * - * - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances { - int __pyx_n; - PyObject *normalize; -}; - -/* "sklearn/tree/_tree.pxd":102 - * cdef double min_impurity_decrease # Impurity threshold for early stopping - * - * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< - * np.ndarray sample_weight=*) - * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build { - int __pyx_n; - PyArrayObject *sample_weight; -}; -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; - -/* "neighbors/_quad_tree.pxd":21 - * # It allows us to write printf debugging lines - * # and remove them at compile time - * cdef enum: # <<<<<<<<<<<<<< - * DEBUGFLAG = 0 - * - */ -enum { - __pyx_e_7sklearn_9neighbors_10_quad_tree_DEBUGFLAG = 0 -}; - -/* "neighbors/_quad_tree.pxd":29 - * # have is_leaf and max_width consecutive as it permits to avoid padding by - * # the compiler and keep the size coherent for both C and numpy data structures. - * cdef struct Cell: # <<<<<<<<<<<<<< - * # Base storage structure for cells in a QuadTree object - * - */ -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell { - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t parent; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t children[8]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t point_index; - int is_leaf; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t squared_max_width; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cumulative_size; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t center[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t barycenter[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t min_bounds[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t max_bounds[3]; -}; - -/* "neighbors/_quad_tree.pxd":75 - * - * # Point insertion methods - * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< - * SIZE_t cell_id=*) nogil except -1 - * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; -}; - -/* "neighbors/_quad_tree.pxd":77 - * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, - * SIZE_t cell_id=*) nogil except -1 - * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< - * SIZE_t point_index, SIZE_t size=* - * ) nogil - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t size; -}; - -/* "neighbors/_quad_tree.pxd":84 - * - * # Create a summary of the Tree compare to a query point - * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< - * float squared_theta=*, SIZE_t cell_id=*, long idx=* - * ) nogil - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize { - int __pyx_n; - float squared_theta; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; - long idx; -}; - -/* "neighbors/_quad_tree.pxd":99 - * # Private array manipulation to manage the ``cells`` array - * cdef int _resize(self, SIZE_t capacity) nogil except -1 - * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< - * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 - * cdef np.ndarray _get_cell_ndarray(self) - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; -}; - -/* "neighbors/_quad_tree.pxd":100 - * cdef int _resize(self, SIZE_t capacity) nogil except -1 - * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 - * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< - * cdef np.ndarray _get_cell_ndarray(self) - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; -}; -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord; -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord; -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; - -/* "sklearn/tree/_utils.pxd":23 - * - * - * cdef enum: # <<<<<<<<<<<<<< - * # Max value for our rand_r replacement (near the bottom). - * # We don't use RAND_MAX because it's different across platforms and - */ -enum { - __pyx_e_7sklearn_4tree_6_utils_RAND_R_MAX = 0x7FFFFFFF -}; - -/* "sklearn/tree/_utils.pxd":70 - * - * # A record on the stack for depth-first tree growing - * cdef struct StackRecord: # <<<<<<<<<<<<<< - * SIZE_t start - * SIZE_t end - */ -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t parent; - int is_left; - double impurity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t n_constant_features; -}; - -/* "sklearn/tree/_utils.pxd":96 - * - * # A record on the frontier for best-first tree growing - * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< - * SIZE_t node_id - * SIZE_t start - */ -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t node_id; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t pos; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; - int is_leaf; - double impurity; - double impurity_left; - double impurity_right; - double improvement; -}; - -/* "sklearn/tree/_utils.pxd":127 - * - * # A record stored in the WeightedPQueue - * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< - * DOUBLE_t data - * DOUBLE_t weight - */ -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord { - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t data; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t weight; -}; - -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtab; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - double weighted_n_samples; - double weighted_n_node_samples; - double weighted_n_left; - double weighted_n_right; - double *sum_total; - double *sum_left; - double *sum_right; -}; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t sum_stride; -}; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - double sq_sum_total; -}; - - -/* "_splitter.pxd":34 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *criterion; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - PyObject *random_state; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - double weighted_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; -}; - - -/* "sklearn/tree/_tree.pxd":37 - * - * - * cdef class Tree: # <<<<<<<<<<<<<< - * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and - */ -struct __pyx_obj_7sklearn_4tree_5_tree_Tree { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtab; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t node_count; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; - struct __pyx_t_7sklearn_4tree_5_tree_Node *nodes; - double *value; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t value_stride; -}; - - -/* "sklearn/tree/_tree.pxd":85 - * # ============================================================================= - * - * cdef class TreeBuilder: # <<<<<<<<<<<<<< - * # The TreeBuilder recursively builds a Tree object from training samples, - * # using a Splitter object for splitting internal nodes and assigning - */ -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *splitter; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_split; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; - double min_impurity_split; - double min_impurity_decrease; -}; - - -/* "neighbors/_quad_tree.pxd":55 - * - * - * cdef class _QuadTree: # <<<<<<<<<<<<<< - * # The QuadTree object is a quad tree structure constructed by inserting - * # recursively points in the tree and splitting cells in 4 so that each - */ -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtab; - int n_dimensions; - int verbose; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_cells_per_cell; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t max_depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_count; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_points; - struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *cells; -}; - - -/* "sklearn/tree/_utils.pxd":79 - * SIZE_t n_constant_features - * - * cdef class Stack: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t top - */ -struct __pyx_obj_7sklearn_4tree_6_utils_Stack { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t top; - struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *stack_; -}; - - -/* "sklearn/tree/_utils.pxd":108 - * double improvement - * - * cdef class PriorityHeap: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t heap_ptr - */ -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t heap_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *heap_; -}; - - -/* "sklearn/tree/_utils.pxd":131 - * DOUBLE_t weight - * - * cdef class WeightedPQueue: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t array_ptr - */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t array_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *array_; -}; - - -/* "sklearn/tree/_utils.pxd":151 - * # ============================================================================= - * - * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< - * cdef SIZE_t initial_capacity - * cdef WeightedPQueue samples - */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t initial_capacity; - struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *samples; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t total_weight; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t k; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t sum_w_0_k; -}; - - -/* "stpredictions/models/OK3/_criterion.pxd":12 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. - */ -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion { - PyObject_HEAD - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtab; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - double weighted_n_samples; - double weighted_n_node_samples; - double weighted_n_left; - double weighted_n_right; -}; - - -/* "stpredictions/models/OK3/_criterion.pxd":50 - * - * - * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract kernelized output regression criterion.""" - * - */ -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { - struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; - double sum_diag_Gramm; - double sum_total_Gramm; - double sum_diag_Gramm_left; - double sum_diag_Gramm_right; - double sum_total_Gramm_left; - double sum_total_Gramm_right; -}; - - -/* "stpredictions/models/OK3/_criterion.pyx":445 - * - * - * cdef class KernelizedMSE(KernelizedRegressionCriterion): # <<<<<<<<<<<<<< - * """Mean squared error impurity criterion. - * - */ -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE { - struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion __pyx_base; -}; - - -/* "View.MemoryView":105 - * - * @cname("__pyx_array") - * cdef class array: # <<<<<<<<<<<<<< - * - * cdef: - */ -struct __pyx_array_obj { - PyObject_HEAD - struct __pyx_vtabstruct_array *__pyx_vtab; - char *data; - Py_ssize_t len; - char *format; - int ndim; - Py_ssize_t *_shape; - Py_ssize_t *_strides; - Py_ssize_t itemsize; - PyObject *mode; - PyObject *_format; - void (*callback_free_data)(void *); - int free_data; - int dtype_is_object; -}; - - -/* "View.MemoryView":279 - * - * @cname('__pyx_MemviewEnum') - * cdef class Enum(object): # <<<<<<<<<<<<<< - * cdef object name - * def __init__(self, name): - */ -struct __pyx_MemviewEnum_obj { - PyObject_HEAD - PyObject *name; -}; - - -/* "View.MemoryView":330 - * - * @cname('__pyx_memoryview') - * cdef class memoryview(object): # <<<<<<<<<<<<<< - * - * cdef object obj - */ -struct __pyx_memoryview_obj { - PyObject_HEAD - struct __pyx_vtabstruct_memoryview *__pyx_vtab; - PyObject *obj; - PyObject *_size; - PyObject *_array_interface; - PyThread_type_lock lock; - __pyx_atomic_int acquisition_count[2]; - __pyx_atomic_int *acquisition_count_aligned_p; - Py_buffer view; - int flags; - int dtype_is_object; - __Pyx_TypeInfo *typeinfo; -}; - - -/* "View.MemoryView":965 - * - * @cname('__pyx_memoryviewslice') - * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< - * "Internal class for passing memoryview slices to Python" - * - */ -struct __pyx_memoryviewslice_obj { - struct __pyx_memoryview_obj __pyx_base; - __Pyx_memviewslice from_slice; - PyObject *from_object; - PyObject *(*to_object_func)(char *); - int (*to_dtype_func)(char *, PyObject *); -}; - - - -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion { - int (*init)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double, double, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_Criterion; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_ClassificationCriterion; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_RegressionCriterion; - - -/* "_splitter.pxd":34 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ - -struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter { - int (*init)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); - int (*node_reset)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); - int (*node_split)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double, struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double *); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtabptr_7sklearn_4tree_9_splitter_Splitter; - - -/* "sklearn/tree/_tree.pxd":37 - * - * - * cdef class Tree: # <<<<<<<<<<<<<< - * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and - */ - -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double); - int (*_resize)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args); - PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*predict)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*apply)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*_apply_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*decision_path)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyObject *(*_decision_path_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*compute_feature_importances)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklearn_4tree_5_tree_Tree; - - -/* "sklearn/tree/_tree.pxd":85 - * # ============================================================================= - * - * cdef class TreeBuilder: # <<<<<<<<<<<<<< - * # The TreeBuilder recursively builds a Tree object from training samples, - * # using a Splitter object for splitting internal nodes and assigning - */ - -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder { - PyObject *(*build)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args); - PyObject *(*_check_input)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder; - - -/* "neighbors/_quad_tree.pxd":55 - * - * - * cdef class _QuadTree: # <<<<<<<<<<<<<< - * # The QuadTree object is a quad tree structure constructed by inserting - * # recursively points in the tree and splitting cells in 4 so that each - */ - -struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree { - int (*insert_point)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_is_duplicate)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - long (*summarize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); - void (*_init_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - void (*_init_root)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - int (*_check_point_in_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_resize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); - int (*_get_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); - PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *); -}; -static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtabptr_7sklearn_9neighbors_10_quad_tree__QuadTree; - - -/* "sklearn/tree/_utils.pxd":79 - * SIZE_t n_constant_features - * - * cdef class Stack: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t top - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7sklearn_4tree_6_utils_Stack; - - -/* "sklearn/tree/_utils.pxd":108 - * double improvement - * - * cdef class PriorityHeap: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t heap_ptr - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); - void (*heapify_up)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - void (*heapify_down)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, double, double, double); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabptr_7sklearn_4tree_6_utils_PriorityHeap; - - -/* "sklearn/tree/_utils.pxd":131 - * DOUBLE_t weight - * - * cdef class WeightedPQueue: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t array_ptr - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*peek)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedPQueue; - - -/* "sklearn/tree/_utils.pxd":151 - * # ============================================================================= - * - * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< - * cdef SIZE_t initial_capacity - * cdef WeightedPQueue samples - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*update_median_parameters_post_push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*update_median_parameters_post_remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedMedianCalculator; - - -/* "stpredictions/models/OK3/_criterion.pyx":22 - * # from kernel import Kernel - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * """Interface for impurity criteria. - * - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion { - int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion; - - -/* "stpredictions/models/OK3/_criterion.pyx":209 - * - * - * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * r"""Abstract kernelized output regression criterion. - * - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; - - -/* "stpredictions/models/OK3/_criterion.pyx":445 - * - * - * cdef class KernelizedMSE(KernelizedRegressionCriterion): # <<<<<<<<<<<<<< - * """Mean squared error impurity criterion. - * - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE { - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion __pyx_base; -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE; - - -/* "View.MemoryView":105 - * - * @cname("__pyx_array") - * cdef class array: # <<<<<<<<<<<<<< - * - * cdef: - */ - -struct __pyx_vtabstruct_array { - PyObject *(*get_memview)(struct __pyx_array_obj *); -}; -static struct __pyx_vtabstruct_array *__pyx_vtabptr_array; - - -/* "View.MemoryView":330 - * - * @cname('__pyx_memoryview') - * cdef class memoryview(object): # <<<<<<<<<<<<<< - * - * cdef object obj - */ - -struct __pyx_vtabstruct_memoryview { - char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *); - PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *); - PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); - PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *); - PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); - PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *); - PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *); 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__Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\ - __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ -} -#define __Pyx_GetModuleGlobalNameUncached(var, name) {\ - PY_UINT64_T __pyx_dict_version;\ - PyObject *__pyx_dict_cached_value;\ - (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ -} -static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value); -#else -#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) -#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) -static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); -#endif - -/* RaiseTooManyValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); - -/* RaiseNeedMoreValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); - -/* RaiseNoneIterError.proto */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); - -/* ExtTypeTest.proto */ -static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); - -/* SwapException.proto */ -#if CYTHON_FAST_THREAD_STATE -#define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) -static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); -#else -static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); -#endif - -/* Import.proto */ -static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); - -/* FastTypeChecks.proto */ -#if CYTHON_COMPILING_IN_CPYTHON -#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) -static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); -static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); -static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); -#else -#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) -#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) -#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) -#endif -#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) - -static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ -/* ListCompAppend.proto */ -#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS -static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { - PyListObject* L = (PyListObject*) list; - Py_ssize_t len = Py_SIZE(list); - if (likely(L->allocated > len)) { - Py_INCREF(x); - PyList_SET_ITEM(list, len, x); - __Pyx_SET_SIZE(list, len + 1); - return 0; - } - return PyList_Append(list, x); -} -#else -#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) -#endif - -/* PyIntBinop.proto */ -#if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); -#else -#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ - (inplace ? 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- -/* ImportFrom.proto */ -static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); - -/* HasAttr.proto */ -static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *); - -/* PyObject_GenericGetAttrNoDict.proto */ -#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 -static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name); -#else -#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr -#endif - -/* PyObject_GenericGetAttr.proto */ -#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 -static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name); -#else -#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr -#endif - -/* SetVTable.proto */ -static int __Pyx_SetVtable(PyObject *dict, void *vtable); - -/* PyObjectGetAttrStrNoError.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); - -/* SetupReduce.proto */ -static int __Pyx_setup_reduce(PyObject* type_obj); - -/* TypeImport.proto */ -#ifndef __PYX_HAVE_RT_ImportType_proto -#define __PYX_HAVE_RT_ImportType_proto -enum __Pyx_ImportType_CheckSize { - __Pyx_ImportType_CheckSize_Error = 0, - __Pyx_ImportType_CheckSize_Warn = 1, - __Pyx_ImportType_CheckSize_Ignore = 2 -}; -static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); -#endif - -/* GetVTable.proto */ -static void* __Pyx_GetVtable(PyObject *dict); - -/* CLineInTraceback.proto */ -#ifdef CYTHON_CLINE_IN_TRACEBACK -#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) -#else -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); -#endif - -/* CodeObjectCache.proto */ -typedef struct { - PyCodeObject* code_object; - int code_line; -} __Pyx_CodeObjectCacheEntry; -struct __Pyx_CodeObjectCache { - int count; - int max_count; - __Pyx_CodeObjectCacheEntry* entries; -}; -static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; -static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); -static PyCodeObject *__pyx_find_code_object(int code_line); -static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); - -/* AddTraceback.proto */ -static void __Pyx_AddTraceback(const char *funcname, int c_line, - int py_line, const char *filename); - -#if PY_MAJOR_VERSION < 3 - static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); - static void __Pyx_ReleaseBuffer(Py_buffer *view); -#else - #define __Pyx_GetBuffer PyObject_GetBuffer - #define __Pyx_ReleaseBuffer PyBuffer_Release -#endif - - -/* BufferStructDeclare.proto */ -typedef struct { - Py_ssize_t shape, strides, suboffsets; -} __Pyx_Buf_DimInfo; -typedef struct { - size_t refcount; - Py_buffer pybuffer; -} __Pyx_Buffer; -typedef struct { - __Pyx_Buffer *rcbuffer; - char *data; - __Pyx_Buf_DimInfo diminfo[8]; -} __Pyx_LocalBuf_ND; - -/* MemviewSliceIsContig.proto */ -static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); - -/* OverlappingSlices.proto */ -static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, - __Pyx_memviewslice *slice2, - int ndim, size_t itemsize); - -/* Capsule.proto */ -static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); - -/* GCCDiagnostics.proto */ -#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) -#define __Pyx_HAS_GCC_DIAGNOSTIC -#endif - -/* RealImag.proto */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - #define __Pyx_CREAL(z) ((z).real()) - #define __Pyx_CIMAG(z) ((z).imag()) - #else - #define __Pyx_CREAL(z) (__real__(z)) - #define __Pyx_CIMAG(z) (__imag__(z)) - #endif -#else - #define __Pyx_CREAL(z) ((z).real) - #define __Pyx_CIMAG(z) ((z).imag) -#endif -#if defined(__cplusplus) && CYTHON_CCOMPLEX\ - && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) - #define __Pyx_SET_CREAL(z,x) ((z).real(x)) - #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) -#else - #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) - #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) -#endif - -/* Arithmetic.proto */ -#if CYTHON_CCOMPLEX - #define __Pyx_c_eq_float(a, b) ((a)==(b)) - #define __Pyx_c_sum_float(a, b) ((a)+(b)) - #define __Pyx_c_diff_float(a, b) ((a)-(b)) - #define __Pyx_c_prod_float(a, b) ((a)*(b)) - #define __Pyx_c_quot_float(a, b) ((a)/(b)) - #define __Pyx_c_neg_float(a) (-(a)) - #ifdef __cplusplus - #define __Pyx_c_is_zero_float(z) ((z)==(float)0) - #define __Pyx_c_conj_float(z) (::std::conj(z)) - #if 1 - #define __Pyx_c_abs_float(z) (::std::abs(z)) - #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) - #endif - #else - #define __Pyx_c_is_zero_float(z) ((z)==0) - #define __Pyx_c_conj_float(z) (conjf(z)) - #if 1 - #define __Pyx_c_abs_float(z) (cabsf(z)) - #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) - #endif - #endif -#else - static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); - static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); - #if 1 - static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); - #endif -#endif - -/* Arithmetic.proto */ -#if CYTHON_CCOMPLEX - #define __Pyx_c_eq_double(a, b) ((a)==(b)) - #define __Pyx_c_sum_double(a, b) ((a)+(b)) - #define __Pyx_c_diff_double(a, b) ((a)-(b)) - #define __Pyx_c_prod_double(a, b) ((a)*(b)) - #define __Pyx_c_quot_double(a, b) ((a)/(b)) - #define __Pyx_c_neg_double(a) (-(a)) - #ifdef __cplusplus - #define __Pyx_c_is_zero_double(z) ((z)==(double)0) - #define __Pyx_c_conj_double(z) (::std::conj(z)) - #if 1 - #define __Pyx_c_abs_double(z) (::std::abs(z)) - #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) - #endif - #else - #define __Pyx_c_is_zero_double(z) ((z)==0) - #define __Pyx_c_conj_double(z) (conj(z)) - #if 1 - #define __Pyx_c_abs_double(z) (cabs(z)) - #define __Pyx_c_pow_double(a, b) (cpow(a, b)) - #endif - #endif -#else - static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); - static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); - #if 1 - static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); - #endif -#endif - -/* MemviewSliceCopyTemplate.proto */ -static __Pyx_memviewslice -__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, - const char *mode, int ndim, - size_t sizeof_dtype, int contig_flag, - int dtype_is_object); - -/* CIntFromPy.proto */ -static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value); - -/* CIntFromPy.proto */ -static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); - -/* CIntFromPy.proto */ -static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); - -/* CIntFromPy.proto */ -static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); - -/* CheckBinaryVersion.proto */ -static int __Pyx_check_binary_version(void); - -/* VoidPtrImport.proto */ -static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig); - -/* FunctionImport.proto */ -static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig); - -/* InitStrings.proto */ -static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); - -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_init(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_y, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, CYTHON_UNUSED double __pyx_v_weighted_n_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_reset(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_reverse_reset(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_update(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos); /* proto*/ -static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right); /* proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_node_value(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_dest); /* proto*/ -static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_proxy_impurity_improvement(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto*/ -static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_impurity_improvement(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, double __pyx_v_impurity); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_init(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, double __pyx_v_weighted_n_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_reset(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_reverse_reset(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_update(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos); /* proto*/ -static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right); /* proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_node_value(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, double *__pyx_v_dest); /* proto*/ -static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self); /* proto*/ -static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_proxy_impurity_improvement(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self); /* proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right); /* proto*/ -static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ -static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ -static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ -static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ -static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ -static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ -static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ -static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ -static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ -static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ - -/* Module declarations from 'cpython.buffer' */ - -/* Module declarations from 'libc.string' */ - -/* Module declarations from 'libc.stdio' */ - -/* Module declarations from '__builtin__' */ - -/* Module declarations from 'cpython.type' */ -static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; 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/*proto*/ -static double (*__pyx_f_7sklearn_4tree_6_utils_log)(double); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DTYPE_t **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t **, size_t); /*proto*/ -static unsigned char *(*__pyx_fuse_2__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t ***, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_5_tree_Node *(*__pyx_fuse_6__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_5_tree_Node **(*__pyx_fuse_8__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node ***, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_StackRecord **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord **, size_t); /*proto*/ - -/* Module declarations from 'stpredictions.models.OK3._criterion' */ -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_Criterion = 0; -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion = 0; -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE = 0; -static PyTypeObject *__pyx_array_type = 0; -static PyTypeObject *__pyx_MemviewEnum_type = 0; -static PyTypeObject *__pyx_memoryview_type = 0; -static PyTypeObject *__pyx_memoryviewslice_type = 0; -static PyObject *generic = 0; -static PyObject *strided = 0; -static PyObject *indirect = 0; -static PyObject *contiguous = 0; -static PyObject *indirect_contiguous = 0; -static int __pyx_memoryview_thread_locks_used; -static PyThread_type_lock __pyx_memoryview_thread_locks[8]; -static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ -static void *__pyx_align_pointer(void *, size_t); /*proto*/ -static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ -static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ -static PyObject *_unellipsify(PyObject *, int); /*proto*/ -static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ -static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ -static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ -static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ -static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ -static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ -static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ -static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ -static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ -static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ -static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ -static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ -static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ -static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ -static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ -static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ -static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ -static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ -static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ -static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ -static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ -static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ -static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ -static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ -static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ -static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ -static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ -static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ -#define __Pyx_MODULE_NAME "stpredictions.models.OK3._criterion" -extern int __pyx_module_is_main_stpredictions__models__OK3___criterion; -int __pyx_module_is_main_stpredictions__models__OK3___criterion = 0; - -/* Implementation of 'stpredictions.models.OK3._criterion' */ -static PyObject *__pyx_builtin_TypeError; -static PyObject *__pyx_builtin_range; -static PyObject *__pyx_builtin_ImportError; -static PyObject *__pyx_builtin_ValueError; -static PyObject *__pyx_builtin_MemoryError; -static PyObject *__pyx_builtin_enumerate; -static PyObject *__pyx_builtin_Ellipsis; -static PyObject *__pyx_builtin_id; -static PyObject *__pyx_builtin_IndexError; -static const char __pyx_k_O[] = "O"; -static const char __pyx_k_c[] = "c"; -static const char __pyx_k_id[] = "id"; -static const char __pyx_k_np[] = "np"; -static const char __pyx_k_new[] = "__new__"; -static const char __pyx_k_obj[] = "obj"; -static const char __pyx_k_base[] = "base"; -static const char __pyx_k_dict[] = "__dict__"; -static const char __pyx_k_main[] = "__main__"; -static const char __pyx_k_mode[] = "mode"; -static const char __pyx_k_name[] = "name"; -static const char __pyx_k_ndim[] = "ndim"; -static const char __pyx_k_pack[] = "pack"; -static const char __pyx_k_size[] = "size"; -static const char __pyx_k_step[] = "step"; -static const char __pyx_k_stop[] = "stop"; -static const char __pyx_k_test[] = "__test__"; -static const char __pyx_k_ASCII[] = "ASCII"; -static const char __pyx_k_class[] = "__class__"; -static const char __pyx_k_error[] = "error"; -static const char __pyx_k_flags[] = "flags"; -static const char __pyx_k_numpy[] = "numpy"; -static const char __pyx_k_range[] = "range"; -static const char __pyx_k_shape[] = "shape"; -static const char __pyx_k_start[] = "start"; -static const char __pyx_k_encode[] = "encode"; -static const char __pyx_k_format[] = "format"; -static const char __pyx_k_import[] = "__import__"; -static const char __pyx_k_name_2[] = "__name__"; -static const char __pyx_k_pickle[] = "pickle"; -static const char __pyx_k_reduce[] = "__reduce__"; -static const char __pyx_k_struct[] = "struct"; -static const char __pyx_k_unpack[] = "unpack"; -static const char __pyx_k_update[] = "update"; 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/* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_9Criterion_6__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_9Criterion_8__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_samples); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_2__reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto */ -static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ -static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ -static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ -static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_12__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf___pyx_array___reduce_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_array_2__setstate_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ -static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_MemviewEnum___reduce_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_MemviewEnum_2__setstate_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); 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- if (__pyx_t_4) { - - /* "stpredictions/models/OK3/_criterion.pyx":301 - * - * if sample_weight != NULL: - * w_j = sample_weight[j] # <<<<<<<<<<<<<< - * - * self.sum_total_Gramm += w_i * w_j * self.y[i,j] - */ - __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]); - - /* "stpredictions/models/OK3/_criterion.pyx":300 - * j = samples[q] - * - * if sample_weight != NULL: # <<<<<<<<<<<<<< - * w_j = sample_weight[j] - * - */ - } - - /* "stpredictions/models/OK3/_criterion.pyx":303 - * w_j = sample_weight[j] - * - * self.sum_total_Gramm += w_i * w_j * self.y[i,j] # <<<<<<<<<<<<<< - * - * # Reset to pos=start - */ - if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 303, __pyx_L1_error)} - __pyx_t_6 = __pyx_v_i; - __pyx_t_5 = __pyx_v_j; - __pyx_v_self->sum_total_Gramm = (__pyx_v_self->sum_total_Gramm + ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_6 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_5)) ))))); - } - } - - /* "stpredictions/models/OK3/_criterion.pyx":306 - * - * # Reset to pos=start - * self.reset() # <<<<<<<<<<<<<< - * # with gil: - * # print("print sum diag :",self.sum_diag_Gramm) - */ - __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.reset(((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self)); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(1, 306, __pyx_L1_error) - - /* "stpredictions/models/OK3/_criterion.pyx":311 - * # print("print sum total :",self.sum_total_Gramm) - * # print("print weighted_n_node_samples :",self.weighted_n_node_samples) - * return 0 # <<<<<<<<<<<<<< - * - * cdef int reset(self) nogil except -1: - */ - __pyx_r = 0; - goto __pyx_L0; - - /* "stpredictions/models/OK3/_criterion.pyx":254 - * return (type(self), (self.n_samples,), self.__getstate__()) - * - * cdef int init(self, const DOUBLE_t[:, ::1] y, DOUBLE_t* sample_weight, # <<<<<<<<<<<<<< - * double weighted_n_samples, SIZE_t* samples, SIZE_t start, - * SIZE_t end) nogil except -1: - */ - - /* function exit code */ - __pyx_L1_error:; - { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); - #endif - __Pyx_AddTraceback("stpredictions.models.OK3._criterion.KernelizedRegressionCriterion.init", __pyx_clineno, __pyx_lineno, __pyx_filename); - #ifdef WITH_THREAD - __Pyx_PyGILState_Release(__pyx_gilstate_save); - #endif - } - __pyx_r = -1; - __pyx_L0:; - return __pyx_r; -} - -/* "stpredictions/models/OK3/_criterion.pyx":313 - * return 0 - * - * cdef int reset(self) nogil except -1: # <<<<<<<<<<<<<< - * """Reset the criterion at pos=start.""" - * - */ - -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_reset(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { - int __pyx_r; - double __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; - - /* "stpredictions/models/OK3/_criterion.pyx":316 - * """Reset the criterion at pos=start.""" - * - * self.sum_diag_Gramm_left = 0.0 # <<<<<<<<<<<<<< - * self.sum_diag_Gramm_right = self.sum_diag_Gramm - * - */ - __pyx_v_self->sum_diag_Gramm_left = 0.0; - - /* "stpredictions/models/OK3/_criterion.pyx":317 - * - * self.sum_diag_Gramm_left = 0.0 - * self.sum_diag_Gramm_right = self.sum_diag_Gramm # <<<<<<<<<<<<<< - * - * self.sum_total_Gramm_left = 0.0 - */ - __pyx_t_1 = __pyx_v_self->sum_diag_Gramm; - __pyx_v_self->sum_diag_Gramm_right = __pyx_t_1; - - /* "stpredictions/models/OK3/_criterion.pyx":319 - * self.sum_diag_Gramm_right = self.sum_diag_Gramm - * - * self.sum_total_Gramm_left = 0.0 # <<<<<<<<<<<<<< - * self.sum_total_Gramm_right = self.sum_total_Gramm - * - */ - __pyx_v_self->sum_total_Gramm_left = 0.0; - - /* "stpredictions/models/OK3/_criterion.pyx":320 - * - * self.sum_total_Gramm_left = 0.0 - * self.sum_total_Gramm_right = self.sum_total_Gramm # <<<<<<<<<<<<<< - * - * self.weighted_n_left = 0.0 - */ - __pyx_t_1 = __pyx_v_self->sum_total_Gramm; - __pyx_v_self->sum_total_Gramm_right = __pyx_t_1; - - /* "stpredictions/models/OK3/_criterion.pyx":322 - * self.sum_total_Gramm_right = self.sum_total_Gramm - * - * self.weighted_n_left = 0.0 # <<<<<<<<<<<<<< - * self.weighted_n_right = self.weighted_n_node_samples - * self.pos = self.start - */ - __pyx_v_self->__pyx_base.weighted_n_left = 0.0; - - /* "stpredictions/models/OK3/_criterion.pyx":323 - * - * self.weighted_n_left = 0.0 - * self.weighted_n_right = self.weighted_n_node_samples # <<<<<<<<<<<<<< - * self.pos = self.start - * return 0 - */ - __pyx_t_1 = __pyx_v_self->__pyx_base.weighted_n_node_samples; - __pyx_v_self->__pyx_base.weighted_n_right = __pyx_t_1; - - /* "stpredictions/models/OK3/_criterion.pyx":324 - * self.weighted_n_left = 0.0 - * self.weighted_n_right = self.weighted_n_node_samples - * self.pos = self.start # <<<<<<<<<<<<<< - * return 0 - * - */ - __pyx_t_2 = __pyx_v_self->__pyx_base.start; - __pyx_v_self->__pyx_base.pos = __pyx_t_2; - - /* "stpredictions/models/OK3/_criterion.pyx":325 - * self.weighted_n_right = self.weighted_n_node_samples - * self.pos = self.start - * return 0 # <<<<<<<<<<<<<< - * - * cdef int reverse_reset(self) nogil except -1: - */ - __pyx_r = 0; - goto __pyx_L0; - - /* "stpredictions/models/OK3/_criterion.pyx":313 - * return 0 - * - * cdef int reset(self) nogil except -1: # <<<<<<<<<<<<<< - * """Reset the criterion at pos=start.""" - * - */ - - /* function exit code */ - __pyx_L0:; - return __pyx_r; -} - -/* "stpredictions/models/OK3/_criterion.pyx":327 - * return 0 - * - * cdef int reverse_reset(self) nogil except -1: # <<<<<<<<<<<<<< - * """Reset the criterion at pos=end.""" - * - */ - -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_reverse_reset(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { - int __pyx_r; - double __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; - - /* "stpredictions/models/OK3/_criterion.pyx":330 - * """Reset the criterion at pos=end.""" - * - * self.sum_diag_Gramm_right = 0.0 # <<<<<<<<<<<<<< - * self.sum_diag_Gramm_left = self.sum_diag_Gramm - * - */ - __pyx_v_self->sum_diag_Gramm_right = 0.0; - - /* "stpredictions/models/OK3/_criterion.pyx":331 - * - * self.sum_diag_Gramm_right = 0.0 - * self.sum_diag_Gramm_left = self.sum_diag_Gramm # <<<<<<<<<<<<<< - * - * self.sum_total_Gramm_right = 0.0 - */ - __pyx_t_1 = __pyx_v_self->sum_diag_Gramm; - __pyx_v_self->sum_diag_Gramm_left = __pyx_t_1; - - /* "stpredictions/models/OK3/_criterion.pyx":333 - * self.sum_diag_Gramm_left = self.sum_diag_Gramm - * - * self.sum_total_Gramm_right = 0.0 # <<<<<<<<<<<<<< - * self.sum_total_Gramm_left = self.sum_total_Gramm - * - */ - __pyx_v_self->sum_total_Gramm_right = 0.0; - - /* "stpredictions/models/OK3/_criterion.pyx":334 - * - * self.sum_total_Gramm_right = 0.0 - * self.sum_total_Gramm_left = self.sum_total_Gramm # <<<<<<<<<<<<<< - * - * self.weighted_n_right = 0.0 - */ - __pyx_t_1 = __pyx_v_self->sum_total_Gramm; - __pyx_v_self->sum_total_Gramm_left = __pyx_t_1; - - /* "stpredictions/models/OK3/_criterion.pyx":336 - * self.sum_total_Gramm_left = self.sum_total_Gramm - * - * self.weighted_n_right = 0.0 # <<<<<<<<<<<<<< - * self.weighted_n_left = self.weighted_n_node_samples - * self.pos = self.end - */ - __pyx_v_self->__pyx_base.weighted_n_right = 0.0; - - /* "stpredictions/models/OK3/_criterion.pyx":337 - * - * self.weighted_n_right = 0.0 - * self.weighted_n_left = self.weighted_n_node_samples # <<<<<<<<<<<<<< - * self.pos = self.end - * return 0 - */ - __pyx_t_1 = __pyx_v_self->__pyx_base.weighted_n_node_samples; - __pyx_v_self->__pyx_base.weighted_n_left = __pyx_t_1; - - /* "stpredictions/models/OK3/_criterion.pyx":338 - * self.weighted_n_right = 0.0 - * self.weighted_n_left = self.weighted_n_node_samples - * self.pos = self.end # <<<<<<<<<<<<<< - * return 0 - * - */ - __pyx_t_2 = __pyx_v_self->__pyx_base.end; - __pyx_v_self->__pyx_base.pos = __pyx_t_2; - - /* "stpredictions/models/OK3/_criterion.pyx":339 - * self.weighted_n_left = self.weighted_n_node_samples - * self.pos = self.end - * return 0 # <<<<<<<<<<<<<< - * - * cdef int update(self, SIZE_t new_pos) nogil except -1: - */ - __pyx_r = 0; - goto __pyx_L0; - - /* "stpredictions/models/OK3/_criterion.pyx":327 - * return 0 - * - * cdef int reverse_reset(self) nogil except -1: # <<<<<<<<<<<<<< - * """Reset the criterion at pos=end.""" - * - */ - - /* function exit code */ - __pyx_L0:; - return __pyx_r; -} - -/* "stpredictions/models/OK3/_criterion.pyx":341 - * return 0 - * - * cdef int update(self, SIZE_t new_pos) nogil except -1: # <<<<<<<<<<<<<< - * """Updated statistics by moving samples[pos:new_pos] to the left.""" - * - */ - -static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_update(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos) { - double *__pyx_v_sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_q; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_i; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_j; - int __pyx_r; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_3; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_5; - int __pyx_t_6; - Py_ssize_t __pyx_t_7; - Py_ssize_t __pyx_t_8; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_9; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_10; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_11; - int __pyx_lineno = 0; - const char *__pyx_filename = NULL; - int __pyx_clineno = 0; - - /* "stpredictions/models/OK3/_criterion.pyx":344 - * """Updated statistics by moving samples[pos:new_pos] to the left.""" - * - * cdef double* sample_weight = self.sample_weight # <<<<<<<<<<<<<< - * cdef SIZE_t* samples = self.samples - * - */ - __pyx_t_1 = __pyx_v_self->__pyx_base.sample_weight; - __pyx_v_sample_weight = __pyx_t_1; - - /* "stpredictions/models/OK3/_criterion.pyx":345 - * - * cdef double* sample_weight = self.sample_weight - * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< - * - * cdef SIZE_t start = self.start - */ - __pyx_t_2 = __pyx_v_self->__pyx_base.samples; - __pyx_v_samples = __pyx_t_2; - - /* "stpredictions/models/OK3/_criterion.pyx":347 - * cdef SIZE_t* samples = self.samples - * - * cdef SIZE_t start = self.start # <<<<<<<<<<<<<< - * cdef SIZE_t pos = self.pos - * cdef SIZE_t end = self.end - */ - __pyx_t_3 = __pyx_v_self->__pyx_base.start; - __pyx_v_start = __pyx_t_3; - - /* "stpredictions/models/OK3/_criterion.pyx":348 - * - * cdef SIZE_t start = self.start - * cdef SIZE_t pos = self.pos # <<<<<<<<<<<<<< - * cdef SIZE_t end = self.end - * - */ - __pyx_t_3 = __pyx_v_self->__pyx_base.pos; - __pyx_v_pos = __pyx_t_3; - - /* "stpredictions/models/OK3/_criterion.pyx":349 - * cdef SIZE_t start = self.start - * cdef SIZE_t pos = self.pos - * cdef SIZE_t end = self.end # <<<<<<<<<<<<<< - * - * cdef SIZE_t i - */ - __pyx_t_3 = __pyx_v_self->__pyx_base.end; - __pyx_v_end = __pyx_t_3; - - /* "stpredictions/models/OK3/_criterion.pyx":355 - * cdef SIZE_t p - * cdef SIZE_t q - * cdef DOUBLE_t w_i = 1.0 # <<<<<<<<<<<<<< - * cdef DOUBLE_t w_j = 1.0 - * - */ - __pyx_v_w_i = 1.0; - - /* "stpredictions/models/OK3/_criterion.pyx":356 - * cdef SIZE_t q - * cdef DOUBLE_t w_i = 1.0 - * cdef DOUBLE_t w_j = 1.0 # <<<<<<<<<<<<<< - * - * # Update statistics up to new_pos - */ - __pyx_v_w_j = 1.0; - - /* "stpredictions/models/OK3/_criterion.pyx":360 - * # Update statistics up to new_pos - * - * for p in range(pos, new_pos): # <<<<<<<<<<<<<< - * i = samples[p] - * - */ - __pyx_t_3 = __pyx_v_new_pos; 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- __pyx_t_4 = __pyx_t_3; - for (__pyx_t_5 = __pyx_v_new_pos; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { - __pyx_v_p = __pyx_t_5; - - /* "stpredictions/models/OK3/_criterion.pyx":393 - * - * for p in range(new_pos, end): - * i = samples[p] # <<<<<<<<<<<<<< - * - * if sample_weight != NULL: - */ - __pyx_v_i = (__pyx_v_samples[__pyx_v_p]); - - /* "stpredictions/models/OK3/_criterion.pyx":395 - * i = samples[p] - * - * if sample_weight != NULL: # <<<<<<<<<<<<<< - * w_i = sample_weight[i] - * - */ - __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_criterion.pyx":396 - * - * if sample_weight != NULL: - * w_i = sample_weight[i] # <<<<<<<<<<<<<< - * - * for q in range(pos, new_pos): - */ - __pyx_v_w_i = (__pyx_v_sample_weight[__pyx_v_i]); - - /* "stpredictions/models/OK3/_criterion.pyx":395 - * i = samples[p] - * - * if sample_weight != NULL: # <<<<<<<<<<<<<< - * w_i = sample_weight[i] - * - */ - } - - /* "stpredictions/models/OK3/_criterion.pyx":398 - * w_i = sample_weight[i] - * - * for q in range(pos, new_pos): # <<<<<<<<<<<<<< - * j = samples[q] - * - */ - __pyx_t_9 = __pyx_v_new_pos; - __pyx_t_10 = __pyx_t_9; - for (__pyx_t_11 = __pyx_v_pos; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) { - __pyx_v_q = __pyx_t_11; - - /* "stpredictions/models/OK3/_criterion.pyx":399 - * - * for q in range(pos, new_pos): - * j = samples[q] # <<<<<<<<<<<<<< - * - * if sample_weight != NULL: - */ - __pyx_v_j = (__pyx_v_samples[__pyx_v_q]); - - /* "stpredictions/models/OK3/_criterion.pyx":401 - * j = samples[q] - * - * if sample_weight != NULL: # <<<<<<<<<<<<<< - * w_j = sample_weight[j] - * - */ - __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_criterion.pyx":402 - * - * if sample_weight != NULL: - * w_j = sample_weight[j] # <<<<<<<<<<<<<< - * - * self.sum_total_Gramm_right -= 2 * w_i * w_j * self.y[i,j] - */ - __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]); - - /* "stpredictions/models/OK3/_criterion.pyx":401 - * j = samples[q] - * - * if sample_weight != NULL: # <<<<<<<<<<<<<< - * w_j = sample_weight[j] - * - */ - } - - /* "stpredictions/models/OK3/_criterion.pyx":404 - * w_j = sample_weight[j] - * - * self.sum_total_Gramm_right -= 2 * w_i * w_j * self.y[i,j] # <<<<<<<<<<<<<< - * - * self.pos = new_pos - */ - if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 404, __pyx_L1_error)} - __pyx_t_8 = __pyx_v_i; - __pyx_t_7 = __pyx_v_j; - __pyx_v_self->sum_total_Gramm_right = (__pyx_v_self->sum_total_Gramm_right - (((2.0 * __pyx_v_w_i) * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) ))))); - } - } - - /* "stpredictions/models/OK3/_criterion.pyx":406 - * self.sum_total_Gramm_right -= 2 * w_i * w_j * self.y[i,j] - * - * self.pos = new_pos # <<<<<<<<<<<<<< - * return 0 - * - */ - __pyx_v_self->__pyx_base.pos = __pyx_v_new_pos; - - /* "stpredictions/models/OK3/_criterion.pyx":407 - * - * self.pos = new_pos - * return 0 # <<<<<<<<<<<<<< - * - * cdef double node_impurity(self) nogil: - */ - __pyx_r = 0; - goto __pyx_L0; - - /* "stpredictions/models/OK3/_criterion.pyx":341 - * return 0 - * - * cdef int update(self, SIZE_t new_pos) nogil except -1: # <<<<<<<<<<<<<< - * """Updated statistics by moving samples[pos:new_pos] to the left.""" - * - */ - - /* function exit code */ - __pyx_L1_error:; - { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); - #endif - __Pyx_AddTraceback("stpredictions.models.OK3._criterion.KernelizedRegressionCriterion.update", __pyx_clineno, __pyx_lineno, __pyx_filename); - #ifdef WITH_THREAD - __Pyx_PyGILState_Release(__pyx_gilstate_save); - #endif - } - __pyx_r = -1; - __pyx_L0:; - return __pyx_r; -} - -/* "stpredictions/models/OK3/_criterion.pyx":409 - * return 0 - * - * cdef double node_impurity(self) nogil: # <<<<<<<<<<<<<< - * pass - * - */ - -static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { - double __pyx_r; - - /* function exit code */ - __pyx_r = 0; - return __pyx_r; -} - -/* "stpredictions/models/OK3/_criterion.pyx":412 - * pass - * - * cdef void children_impurity(self, double* impurity_left, double* impurity_right) nogil: # <<<<<<<<<<<<<< - * pass - * - */ - -static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) { - - /* function exit code */ -} - -/* "stpredictions/models/OK3/_criterion.pyx":415 - * pass - * - * cdef void node_value(self, double* dest) nogil: # <<<<<<<<<<<<<< - * """Compute the node value of samples[start:end] into dest.""" - * - */ - -static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_node_value(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, double *__pyx_v_dest) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; 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- - /* "stpredictions/models/OK3/_criterion.pyx":426 - * k = self.samples[p] - * - * if self.sample_weight != NULL: # <<<<<<<<<<<<<< - * w = self.sample_weight[k] - * - */ - __pyx_t_4 = ((__pyx_v_self->__pyx_base.sample_weight != NULL) != 0); - if (__pyx_t_4) { - - /* "stpredictions/models/OK3/_criterion.pyx":427 - * - * if self.sample_weight != NULL: - * w = self.sample_weight[k] # <<<<<<<<<<<<<< - * - * dest[k] = w / self.weighted_n_node_samples - */ - __pyx_v_w = (__pyx_v_self->__pyx_base.sample_weight[__pyx_v_k]); - - /* "stpredictions/models/OK3/_criterion.pyx":426 - * k = self.samples[p] - * - * if self.sample_weight != NULL: # <<<<<<<<<<<<<< - * w = self.sample_weight[k] - * - */ - } - - /* "stpredictions/models/OK3/_criterion.pyx":429 - * w = self.sample_weight[k] - * - * dest[k] = w / self.weighted_n_node_samples # <<<<<<<<<<<<<< - * - * - */ - (__pyx_v_dest[__pyx_v_k]) = (__pyx_v_w / __pyx_v_self->__pyx_base.weighted_n_node_samples); - } - - /* "stpredictions/models/OK3/_criterion.pyx":415 - * pass - * - * cdef void node_value(self, double* dest) nogil: # <<<<<<<<<<<<<< - * """Compute the node value of samples[start:end] into dest.""" - * - */ - - /* function exit code */ -} - -/* "stpredictions/models/OK3/_criterion.pyx":454 - * """ - * - * cdef double node_impurity(self) nogil: # <<<<<<<<<<<<<< - * """Evaluate the impurity of the current node, i.e. the impurity of - * samples[start:end].""" - */ - -static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self) { - double __pyx_v_impurity; 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- CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; - Py_ssize_t __pyx_v_dst_extent; - Py_ssize_t __pyx_v_src_stride; - Py_ssize_t __pyx_v_dst_stride; - int __pyx_t_1; - int __pyx_t_2; - int __pyx_t_3; - Py_ssize_t __pyx_t_4; - Py_ssize_t __pyx_t_5; - Py_ssize_t __pyx_t_6; - - /* "View.MemoryView":1147 - * - * cdef Py_ssize_t i - * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< - * cdef Py_ssize_t dst_extent = dst_shape[0] - * cdef Py_ssize_t src_stride = src_strides[0] - */ - __pyx_v_src_extent = (__pyx_v_src_shape[0]); - - /* "View.MemoryView":1148 - * cdef Py_ssize_t i - * cdef Py_ssize_t src_extent = src_shape[0] - * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< - * cdef Py_ssize_t src_stride = src_strides[0] - * cdef Py_ssize_t dst_stride = dst_strides[0] - */ - __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); - - /* "View.MemoryView":1149 - * cdef Py_ssize_t src_extent = src_shape[0] - * cdef Py_ssize_t dst_extent = dst_shape[0] - * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< - * cdef Py_ssize_t dst_stride = dst_strides[0] - * - */ - __pyx_v_src_stride = (__pyx_v_src_strides[0]); - - /* "View.MemoryView":1150 - * cdef Py_ssize_t dst_extent = dst_shape[0] - * cdef Py_ssize_t src_stride = src_strides[0] - * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< - * - * if ndim == 1: - */ - __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); - - /* "View.MemoryView":1152 - * cdef Py_ssize_t dst_stride = dst_strides[0] - * - * if ndim == 1: # <<<<<<<<<<<<<< - * if (src_stride > 0 and dst_stride > 0 and - * src_stride == itemsize == dst_stride): - */ - __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); - if (__pyx_t_1) { - - /* "View.MemoryView":1153 - * - * if ndim == 1: - * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< - * src_stride == itemsize == dst_stride): - * memcpy(dst_data, src_data, itemsize * dst_extent) - */ - __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); - if (__pyx_t_2) { - } else { - __pyx_t_1 = __pyx_t_2; - goto __pyx_L5_bool_binop_done; - } - __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); - if (__pyx_t_2) { - } else { - __pyx_t_1 = __pyx_t_2; - goto __pyx_L5_bool_binop_done; - } - - /* "View.MemoryView":1154 - * if ndim == 1: - * if (src_stride > 0 and dst_stride > 0 and - * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< - * memcpy(dst_data, src_data, itemsize * dst_extent) - * else: - */ - __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); - if (__pyx_t_2) { - __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); - } - __pyx_t_3 = (__pyx_t_2 != 0); - __pyx_t_1 = __pyx_t_3; - __pyx_L5_bool_binop_done:; - - /* "View.MemoryView":1153 - * - * if ndim == 1: - * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< - * src_stride == itemsize == dst_stride): - * memcpy(dst_data, src_data, itemsize * dst_extent) - */ - if (__pyx_t_1) { - - /* "View.MemoryView":1155 - * if (src_stride > 0 and dst_stride > 0 and - * src_stride == itemsize == dst_stride): - * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< - * else: - * for i in range(dst_extent): - */ - (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); - - /* "View.MemoryView":1153 - * - * if ndim == 1: - * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< - * src_stride == itemsize == dst_stride): - * memcpy(dst_data, src_data, itemsize * dst_extent) - */ - goto __pyx_L4; - } - - /* "View.MemoryView":1157 - * memcpy(dst_data, src_data, itemsize * dst_extent) - * else: - * for i in range(dst_extent): # <<<<<<<<<<<<<< - * memcpy(dst_data, src_data, itemsize) - * src_data += src_stride - */ - /*else*/ { - __pyx_t_4 = __pyx_v_dst_extent; - __pyx_t_5 = __pyx_t_4; - for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { - __pyx_v_i = __pyx_t_6; - - /* "View.MemoryView":1158 - * else: - * for i in range(dst_extent): - * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< - * src_data += src_stride - * dst_data += dst_stride - */ - (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize)); - - /* "View.MemoryView":1159 - * for i in range(dst_extent): - * memcpy(dst_data, src_data, itemsize) - * src_data += src_stride # <<<<<<<<<<<<<< - * dst_data += dst_stride - * else: - */ - __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); - - /* "View.MemoryView":1160 - * memcpy(dst_data, src_data, itemsize) - * src_data += src_stride - * dst_data += dst_stride # <<<<<<<<<<<<<< - * else: - * for i in range(dst_extent): - */ - __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); - } - } - __pyx_L4:; - - /* "View.MemoryView":1152 - * cdef Py_ssize_t dst_stride = dst_strides[0] - * - * if ndim == 1: # <<<<<<<<<<<<<< - * if (src_stride > 0 and dst_stride > 0 and - * src_stride == itemsize == dst_stride): - */ - goto __pyx_L3; - } - - /* "View.MemoryView":1162 - * dst_data += dst_stride - * else: - * for i in range(dst_extent): # <<<<<<<<<<<<<< - * _copy_strided_to_strided(src_data, src_strides + 1, - * dst_data, dst_strides + 1, - */ - /*else*/ { - __pyx_t_4 = __pyx_v_dst_extent; - __pyx_t_5 = __pyx_t_4; - for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { - __pyx_v_i = __pyx_t_6; - - /* "View.MemoryView":1163 - * else: - * for i in range(dst_extent): - * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< - * dst_data, dst_strides + 1, - * src_shape + 1, dst_shape + 1, - */ - _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); - - /* "View.MemoryView":1167 - * src_shape + 1, dst_shape + 1, - * ndim - 1, itemsize) - * src_data += src_stride # <<<<<<<<<<<<<< - * dst_data += dst_stride - * - */ - __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); - - /* "View.MemoryView":1168 - * ndim - 1, itemsize) - * src_data += src_stride - * dst_data += dst_stride # <<<<<<<<<<<<<< - * - * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, - */ - __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); - } - } - __pyx_L3:; - - /* "View.MemoryView":1140 - * - * @cython.cdivision(True) - * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< - * char *dst_data, Py_ssize_t *dst_strides, - * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, - */ - - /* function exit code */ -} - -/* "View.MemoryView":1170 - * dst_data += dst_stride - * - * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< - * __Pyx_memviewslice *dst, - * int ndim, size_t itemsize) nogil: - */ - -static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { - - /* "View.MemoryView":1173 - * __Pyx_memviewslice *dst, - * int ndim, size_t itemsize) nogil: - * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< - * src.shape, dst.shape, ndim, itemsize) - * - */ - _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); - - /* "View.MemoryView":1170 - * dst_data += dst_stride - * - * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< - * __Pyx_memviewslice *dst, - * int ndim, size_t itemsize) nogil: - */ - - /* function exit code */ -} - -/* "View.MemoryView":1177 - * - * @cname('__pyx_memoryview_slice_get_size') - * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< - * "Return the size of the memory occupied by the slice in number of bytes" - * cdef Py_ssize_t shape, size = src.memview.view.itemsize - */ - -static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { - Py_ssize_t __pyx_v_shape; - Py_ssize_t __pyx_v_size; - Py_ssize_t __pyx_r; - Py_ssize_t __pyx_t_1; - Py_ssize_t *__pyx_t_2; - Py_ssize_t *__pyx_t_3; - Py_ssize_t *__pyx_t_4; - - /* "View.MemoryView":1179 - * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: - * "Return the size of the memory occupied by the slice in number of bytes" - * cdef Py_ssize_t shape, size = src.memview.view.itemsize # <<<<<<<<<<<<<< - * - * for shape in src.shape[:ndim]: - */ - __pyx_t_1 = __pyx_v_src->memview->view.itemsize; - __pyx_v_size = __pyx_t_1; - - /* "View.MemoryView":1181 - * cdef Py_ssize_t shape, size = src.memview.view.itemsize - * - * for shape in src.shape[:ndim]: # <<<<<<<<<<<<<< - * size *= shape - * - */ - __pyx_t_3 = (__pyx_v_src->shape + __pyx_v_ndim); - for (__pyx_t_4 = __pyx_v_src->shape; __pyx_t_4 < __pyx_t_3; __pyx_t_4++) { - __pyx_t_2 = __pyx_t_4; - __pyx_v_shape = (__pyx_t_2[0]); - - /* "View.MemoryView":1182 - * - * for shape in src.shape[:ndim]: - * size *= shape # <<<<<<<<<<<<<< - * - * return size - */ - __pyx_v_size = (__pyx_v_size * __pyx_v_shape); - } - - /* "View.MemoryView":1184 - * size *= shape - * - * return size # <<<<<<<<<<<<<< - * - * @cname('__pyx_fill_contig_strides_array') - */ - __pyx_r = __pyx_v_size; - goto __pyx_L0; - - /* "View.MemoryView":1177 - * - * @cname('__pyx_memoryview_slice_get_size') - * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< - * "Return the size of the memory occupied by the slice in number of bytes" - * cdef Py_ssize_t shape, size = src.memview.view.itemsize - */ - - /* function exit code */ - __pyx_L0:; - return __pyx_r; -} - -/* "View.MemoryView":1187 - * - * @cname('__pyx_fill_contig_strides_array') - * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< - * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, - * int ndim, char order) nogil: - */ - -static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { - int __pyx_v_idx; - Py_ssize_t __pyx_r; - int __pyx_t_1; - int __pyx_t_2; - int __pyx_t_3; - int __pyx_t_4; - - /* "View.MemoryView":1196 - * cdef int idx - * - * if order == 'F': # <<<<<<<<<<<<<< - * for idx in range(ndim): - * strides[idx] = stride - */ - __pyx_t_1 = ((__pyx_v_order == 'F') != 0); - if (__pyx_t_1) { - - /* "View.MemoryView":1197 - * - * if order == 'F': - * for idx in range(ndim): # <<<<<<<<<<<<<< - * strides[idx] = stride - * stride *= shape[idx] - */ - __pyx_t_2 = __pyx_v_ndim; - __pyx_t_3 = __pyx_t_2; - for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { - __pyx_v_idx = __pyx_t_4; - - /* "View.MemoryView":1198 - * if order == 'F': - * for idx in range(ndim): - * strides[idx] = stride # <<<<<<<<<<<<<< - * stride *= shape[idx] - * else: - */ - (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - - /* "View.MemoryView":1199 - * for idx in range(ndim): - * strides[idx] = stride - * stride *= shape[idx] # <<<<<<<<<<<<<< - * else: - * for idx in range(ndim - 1, -1, -1): - */ - __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); - } - - /* "View.MemoryView":1196 - * cdef int idx - * - * if order == 'F': # <<<<<<<<<<<<<< - * for idx in range(ndim): - * strides[idx] = stride - */ - goto __pyx_L3; - } - - /* "View.MemoryView":1201 - * stride *= shape[idx] - * else: - * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< - * strides[idx] = stride - * stride *= shape[idx] - */ - /*else*/ { - for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) { - __pyx_v_idx = __pyx_t_2; - - /* "View.MemoryView":1202 - * else: - * for idx in range(ndim - 1, -1, -1): - * strides[idx] = stride # <<<<<<<<<<<<<< - * stride *= shape[idx] - * - */ - (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - - /* "View.MemoryView":1203 - * for idx in range(ndim - 1, -1, -1): - * strides[idx] = stride - * stride *= shape[idx] # <<<<<<<<<<<<<< - * - * return stride - */ - __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); - } - } - __pyx_L3:; - - /* "View.MemoryView":1205 - * stride *= shape[idx] - * - * return stride # <<<<<<<<<<<<<< - * - * @cname('__pyx_memoryview_copy_data_to_temp') - */ - __pyx_r = __pyx_v_stride; - goto __pyx_L0; - - /* "View.MemoryView":1187 - * - * @cname('__pyx_fill_contig_strides_array') - * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< - * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, - * int ndim, char order) nogil: - */ - - /* function exit code */ - __pyx_L0:; - return __pyx_r; -} - -/* "View.MemoryView":1208 - * - * @cname('__pyx_memoryview_copy_data_to_temp') - * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< - * __Pyx_memviewslice *tmpslice, - * char order, - */ - -static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_tmpslice, char __pyx_v_order, int __pyx_v_ndim) { - int __pyx_v_i; - void *__pyx_v_result; - size_t __pyx_v_itemsize; - size_t __pyx_v_size; - void *__pyx_r; - Py_ssize_t __pyx_t_1; - int __pyx_t_2; - int __pyx_t_3; - struct __pyx_memoryview_obj *__pyx_t_4; - int __pyx_t_5; - int __pyx_t_6; - int __pyx_lineno = 0; - const char *__pyx_filename = NULL; - int __pyx_clineno = 0; - - /* "View.MemoryView":1219 - * cdef void *result - * - * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< - * cdef size_t size = slice_get_size(src, ndim) - * - */ - __pyx_t_1 = __pyx_v_src->memview->view.itemsize; - __pyx_v_itemsize = __pyx_t_1; - - /* "View.MemoryView":1220 - * - * cdef size_t itemsize = src.memview.view.itemsize - * cdef size_t size = slice_get_size(src, ndim) # <<<<<<<<<<<<<< - * - * result = malloc(size) - */ - __pyx_v_size = __pyx_memoryview_slice_get_size(__pyx_v_src, __pyx_v_ndim); - - /* "View.MemoryView":1222 - * cdef size_t size = slice_get_size(src, ndim) - * - * result = malloc(size) # <<<<<<<<<<<<<< - * if not result: - * _err(MemoryError, NULL) - */ - __pyx_v_result = malloc(__pyx_v_size); 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- - /* "View.MemoryView":1284 - * cdef __Pyx_memviewslice tmp - * - * if src_ndim < dst_ndim: # <<<<<<<<<<<<<< - * broadcast_leading(&src, src_ndim, dst_ndim) - * elif dst_ndim < src_ndim: - */ - goto __pyx_L3; - } - - /* "View.MemoryView":1286 - * if src_ndim < dst_ndim: - * broadcast_leading(&src, src_ndim, dst_ndim) - * elif dst_ndim < src_ndim: # <<<<<<<<<<<<<< - * broadcast_leading(&dst, dst_ndim, src_ndim) - * - */ - __pyx_t_2 = ((__pyx_v_dst_ndim < __pyx_v_src_ndim) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1287 - * broadcast_leading(&src, src_ndim, dst_ndim) - * elif dst_ndim < src_ndim: - * broadcast_leading(&dst, dst_ndim, src_ndim) # <<<<<<<<<<<<<< - * - * cdef int ndim = max(src_ndim, dst_ndim) - */ - __pyx_memoryview_broadcast_leading((&__pyx_v_dst), __pyx_v_dst_ndim, __pyx_v_src_ndim); - - /* "View.MemoryView":1286 - * if src_ndim < dst_ndim: - * broadcast_leading(&src, src_ndim, dst_ndim) - * elif dst_ndim < src_ndim: # <<<<<<<<<<<<<< - * broadcast_leading(&dst, dst_ndim, src_ndim) - * - */ - } - __pyx_L3:; - - /* "View.MemoryView":1289 - * broadcast_leading(&dst, dst_ndim, src_ndim) - * - * cdef int ndim = max(src_ndim, dst_ndim) # <<<<<<<<<<<<<< - * - * for i in range(ndim): - */ - __pyx_t_3 = __pyx_v_dst_ndim; - __pyx_t_4 = __pyx_v_src_ndim; - if (((__pyx_t_3 > __pyx_t_4) != 0)) { - __pyx_t_5 = __pyx_t_3; - } else { - __pyx_t_5 = __pyx_t_4; - } - __pyx_v_ndim = __pyx_t_5; - - /* "View.MemoryView":1291 - * cdef int ndim = max(src_ndim, dst_ndim) - * - * for i in range(ndim): # <<<<<<<<<<<<<< - * if src.shape[i] != dst.shape[i]: - * if src.shape[i] == 1: - */ - __pyx_t_5 = __pyx_v_ndim; - __pyx_t_3 = __pyx_t_5; - for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { - __pyx_v_i = __pyx_t_4; - - /* "View.MemoryView":1292 - * - * for i in range(ndim): - * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< - * if src.shape[i] == 1: - * broadcasting = True - */ - __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) != (__pyx_v_dst.shape[__pyx_v_i])) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1293 - * for i in range(ndim): - * if src.shape[i] != dst.shape[i]: - * if src.shape[i] == 1: # <<<<<<<<<<<<<< - * broadcasting = True - * src.strides[i] = 0 - */ - __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) == 1) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1294 - * if src.shape[i] != dst.shape[i]: - * if src.shape[i] == 1: - * broadcasting = True # <<<<<<<<<<<<<< - * src.strides[i] = 0 - * else: - */ - __pyx_v_broadcasting = 1; - - /* "View.MemoryView":1295 - * if src.shape[i] == 1: - * broadcasting = True - * src.strides[i] = 0 # <<<<<<<<<<<<<< - * else: - * _err_extents(i, dst.shape[i], src.shape[i]) - */ - (__pyx_v_src.strides[__pyx_v_i]) = 0; - - /* "View.MemoryView":1293 - * for i in range(ndim): - * if src.shape[i] != dst.shape[i]: - * if src.shape[i] == 1: # <<<<<<<<<<<<<< - * broadcasting = True - * src.strides[i] = 0 - */ - goto __pyx_L7; - } - - /* "View.MemoryView":1297 - * src.strides[i] = 0 - * else: - * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<< - * - * if src.suboffsets[i] >= 0: - */ - /*else*/ { - __pyx_t_6 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(0, 1297, __pyx_L1_error) - } - __pyx_L7:; - - /* "View.MemoryView":1292 - * - * for i in range(ndim): - * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< - * if src.shape[i] == 1: - * broadcasting = True - */ - } - - /* "View.MemoryView":1299 - * _err_extents(i, dst.shape[i], src.shape[i]) - * - * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< - * _err_dim(ValueError, "Dimension %d is not direct", i) - * - */ - __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1300 - * - * if src.suboffsets[i] >= 0: - * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<< - * - * if slices_overlap(&src, &dst, ndim, itemsize): - */ - __pyx_t_6 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Dimension %d is not direct"), __pyx_v_i); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(0, 1300, __pyx_L1_error) - - /* "View.MemoryView":1299 - * _err_extents(i, dst.shape[i], src.shape[i]) - * - * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< - * _err_dim(ValueError, "Dimension %d is not direct", i) - * - */ - } - } - - /* "View.MemoryView":1302 - * _err_dim(ValueError, "Dimension %d is not direct", i) - * - * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< - * - * if not slice_is_contig(src, order, ndim): - */ - __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1304 - * if slices_overlap(&src, &dst, ndim, itemsize): - * - * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< - * order = get_best_order(&dst, ndim) - * - */ - __pyx_t_2 = ((!(__pyx_memviewslice_is_contig(__pyx_v_src, __pyx_v_order, __pyx_v_ndim) != 0)) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1305 - * - * if not slice_is_contig(src, order, ndim): - * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< - * - * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) - */ - __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim); - - /* "View.MemoryView":1304 - * if slices_overlap(&src, &dst, ndim, itemsize): - * - * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< - * order = get_best_order(&dst, ndim) - * - */ - } - - /* "View.MemoryView":1307 - * order = get_best_order(&dst, ndim) - * - * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< - * src = tmp - * - */ - __pyx_t_7 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_7 == ((void *)NULL))) __PYX_ERR(0, 1307, __pyx_L1_error) - __pyx_v_tmpdata = __pyx_t_7; - - /* "View.MemoryView":1308 - * - * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) - * src = tmp # <<<<<<<<<<<<<< - * - * if not broadcasting: - */ - __pyx_v_src = __pyx_v_tmp; - - /* "View.MemoryView":1302 - * _err_dim(ValueError, "Dimension %d is not direct", i) - * - * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< - * - * if not slice_is_contig(src, order, ndim): - */ - } - - /* "View.MemoryView":1310 - * src = tmp - * - * if not broadcasting: # <<<<<<<<<<<<<< - * - * - */ - __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1313 - * - * - * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< - * direct_copy = slice_is_contig(dst, 'C', ndim) - * elif slice_is_contig(src, 'F', ndim): - */ - __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'C', __pyx_v_ndim) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1314 - * - * if slice_is_contig(src, 'C', ndim): - * direct_copy = slice_is_contig(dst, 'C', ndim) # <<<<<<<<<<<<<< - * elif slice_is_contig(src, 'F', ndim): - * direct_copy = slice_is_contig(dst, 'F', ndim) - */ - __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim); - - /* "View.MemoryView":1313 - * - * - * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< - * direct_copy = slice_is_contig(dst, 'C', ndim) - * elif slice_is_contig(src, 'F', ndim): - */ - goto __pyx_L12; - } - - /* "View.MemoryView":1315 - * if slice_is_contig(src, 'C', ndim): - * direct_copy = slice_is_contig(dst, 'C', ndim) - * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< - * direct_copy = slice_is_contig(dst, 'F', ndim) - * - */ - __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'F', __pyx_v_ndim) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1316 - * direct_copy = slice_is_contig(dst, 'C', ndim) - * elif slice_is_contig(src, 'F', ndim): - * direct_copy = slice_is_contig(dst, 'F', ndim) # <<<<<<<<<<<<<< - * - * if direct_copy: - */ - __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim); - - /* "View.MemoryView":1315 - * if slice_is_contig(src, 'C', ndim): - * direct_copy = slice_is_contig(dst, 'C', ndim) - * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< - * direct_copy = slice_is_contig(dst, 'F', ndim) - * - */ - } - __pyx_L12:; - - /* "View.MemoryView":1318 - * direct_copy = slice_is_contig(dst, 'F', ndim) - * - * if direct_copy: # <<<<<<<<<<<<<< - * - * refcount_copying(&dst, dtype_is_object, ndim, False) - */ - __pyx_t_2 = (__pyx_v_direct_copy != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1320 - * if direct_copy: - * - * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< - * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) - * refcount_copying(&dst, dtype_is_object, ndim, True) - */ - __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); - - /* "View.MemoryView":1321 - * - * refcount_copying(&dst, dtype_is_object, ndim, False) - * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< - * refcount_copying(&dst, dtype_is_object, ndim, True) - * free(tmpdata) - */ - (void)(memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim))); - - /* "View.MemoryView":1322 - * refcount_copying(&dst, dtype_is_object, ndim, False) - * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) - * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< - * free(tmpdata) - * return 0 - */ - __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); - - /* "View.MemoryView":1323 - * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) - * refcount_copying(&dst, dtype_is_object, ndim, True) - * free(tmpdata) # <<<<<<<<<<<<<< - * return 0 - * - */ - free(__pyx_v_tmpdata); - - /* "View.MemoryView":1324 - * refcount_copying(&dst, dtype_is_object, ndim, True) - * free(tmpdata) - * return 0 # <<<<<<<<<<<<<< - * - * if order == 'F' == get_best_order(&dst, ndim): - */ - __pyx_r = 0; - goto __pyx_L0; - - /* "View.MemoryView":1318 - * direct_copy = slice_is_contig(dst, 'F', ndim) - * - * if direct_copy: # <<<<<<<<<<<<<< - * - * refcount_copying(&dst, dtype_is_object, ndim, False) - */ - } - - /* "View.MemoryView":1310 - * src = tmp - * - * if not broadcasting: # <<<<<<<<<<<<<< - * - * - */ - } - - /* "View.MemoryView":1326 - * return 0 - * - * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< - * - * - */ - __pyx_t_2 = (__pyx_v_order == 'F'); - if (__pyx_t_2) { - __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim)); - } - __pyx_t_8 = (__pyx_t_2 != 0); - if (__pyx_t_8) { - - /* "View.MemoryView":1329 - * - * - * transpose_memslice(&src) # <<<<<<<<<<<<<< - * transpose_memslice(&dst) - * - */ - __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(0, 1329, __pyx_L1_error) - - /* "View.MemoryView":1330 - * - * transpose_memslice(&src) - * transpose_memslice(&dst) # <<<<<<<<<<<<<< - * - * refcount_copying(&dst, dtype_is_object, ndim, False) - */ - __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(0, 1330, __pyx_L1_error) - - /* "View.MemoryView":1326 - * return 0 - * - * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< - * - * - */ - } - - /* "View.MemoryView":1332 - * transpose_memslice(&dst) - * - * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< - * copy_strided_to_strided(&src, &dst, ndim, itemsize) - * refcount_copying(&dst, dtype_is_object, ndim, True) - */ - __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); - - /* "View.MemoryView":1333 - * - * refcount_copying(&dst, dtype_is_object, ndim, False) - * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< - * refcount_copying(&dst, dtype_is_object, ndim, True) - * - */ - copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); - - /* "View.MemoryView":1334 - * refcount_copying(&dst, dtype_is_object, ndim, False) - * copy_strided_to_strided(&src, &dst, ndim, itemsize) - * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< - * - * free(tmpdata) - */ - __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); - - /* "View.MemoryView":1336 - * refcount_copying(&dst, dtype_is_object, ndim, True) - * - * free(tmpdata) # <<<<<<<<<<<<<< - * return 0 - * - */ - free(__pyx_v_tmpdata); - - /* "View.MemoryView":1337 - * - * free(tmpdata) - * return 0 # <<<<<<<<<<<<<< - * - * @cname('__pyx_memoryview_broadcast_leading') - */ - __pyx_r = 0; - goto __pyx_L0; - - /* "View.MemoryView":1268 - * - * @cname('__pyx_memoryview_copy_contents') - * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< - * __Pyx_memviewslice dst, - * int src_ndim, int dst_ndim, - */ - - /* function exit code */ - __pyx_L1_error:; - { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); - #endif - __Pyx_AddTraceback("View.MemoryView.memoryview_copy_contents", __pyx_clineno, __pyx_lineno, __pyx_filename); - #ifdef WITH_THREAD - __Pyx_PyGILState_Release(__pyx_gilstate_save); - #endif - } - __pyx_r = -1; - __pyx_L0:; - return __pyx_r; -} - -/* "View.MemoryView":1340 - * - * @cname('__pyx_memoryview_broadcast_leading') - * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< - * int ndim, - * int ndim_other) nogil: - */ - -static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) { - int __pyx_v_i; - int __pyx_v_offset; - int __pyx_t_1; 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PyDict_Size(kwargs) : 0; - if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { - return NULL; - } - if ( -#if PY_MAJOR_VERSION >= 3 - co->co_kwonlyargcount == 0 && -#endif - likely(kwargs == NULL || nk == 0) && - co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { - if (argdefs == NULL && co->co_argcount == nargs) { - result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); - goto done; - } - else if (nargs == 0 && argdefs != NULL - && co->co_argcount == Py_SIZE(argdefs)) { - /* function called with no arguments, but all parameters have - a default value: use default values as arguments .*/ - args = &PyTuple_GET_ITEM(argdefs, 0); - result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); - goto done; - } - } - if (kwargs != NULL) { - Py_ssize_t pos, i; - kwtuple = PyTuple_New(2 * nk); - if (kwtuple == NULL) { - result = NULL; - goto done; - } - k = &PyTuple_GET_ITEM(kwtuple, 0); - pos = i = 0; - while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { - Py_INCREF(k[i]); - Py_INCREF(k[i+1]); - i += 2; - } - nk = i / 2; - } - else { - kwtuple = NULL; - k = NULL; - } - closure = PyFunction_GET_CLOSURE(func); -#if PY_MAJOR_VERSION >= 3 - kwdefs = PyFunction_GET_KW_DEFAULTS(func); -#endif - if (argdefs != NULL) { - d = &PyTuple_GET_ITEM(argdefs, 0); - nd = Py_SIZE(argdefs); - } - else { - d = NULL; - nd = 0; - } -#if PY_MAJOR_VERSION >= 3 - result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, - args, (int)nargs, - k, (int)nk, - d, (int)nd, kwdefs, closure); -#else - result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, - args, (int)nargs, - k, (int)nk, - d, (int)nd, closure); -#endif - Py_XDECREF(kwtuple); -done: - Py_LeaveRecursiveCall(); - return result; -} -#endif -#endif - -/* PyObjectCallMethO */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { - PyObject *self, *result; - PyCFunction cfunc; - cfunc = PyCFunction_GET_FUNCTION(func); - self = PyCFunction_GET_SELF(func); - if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) - return NULL; - result = cfunc(self, arg); - Py_LeaveRecursiveCall(); - if (unlikely(!result) && unlikely(!PyErr_Occurred())) { - PyErr_SetString( - PyExc_SystemError, - "NULL result without error in PyObject_Call"); - } - return result; -} -#endif - -/* PyObjectCallNoArg */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { -#if CYTHON_FAST_PYCALL - if (PyFunction_Check(func)) { - return __Pyx_PyFunction_FastCall(func, NULL, 0); - } -#endif -#ifdef __Pyx_CyFunction_USED - if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) -#else - if (likely(PyCFunction_Check(func))) -#endif - { - if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { - return __Pyx_PyObject_CallMethO(func, NULL); - } - } - return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); -} -#endif - -/* PyCFunctionFastCall */ -#if CYTHON_FAST_PYCCALL -static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { - PyCFunctionObject *func = (PyCFunctionObject*)func_obj; - PyCFunction meth = PyCFunction_GET_FUNCTION(func); - PyObject *self = PyCFunction_GET_SELF(func); - int flags = PyCFunction_GET_FLAGS(func); - assert(PyCFunction_Check(func)); - assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); - assert(nargs >= 0); - assert(nargs == 0 || args != NULL); - /* _PyCFunction_FastCallDict() must not be called with an exception set, - because it may clear it (directly or indirectly) and so the - caller loses its exception */ - assert(!PyErr_Occurred()); - if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { - return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); - } else { - return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); - } -} -#endif - -/* PyObjectCallOneArg */ -#if CYTHON_COMPILING_IN_CPYTHON -static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *result; - PyObject *args = PyTuple_New(1); - if (unlikely(!args)) return NULL; - Py_INCREF(arg); - PyTuple_SET_ITEM(args, 0, arg); - result = __Pyx_PyObject_Call(func, args, NULL); - Py_DECREF(args); - return result; -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { -#if CYTHON_FAST_PYCALL - if (PyFunction_Check(func)) { - return __Pyx_PyFunction_FastCall(func, &arg, 1); - } -#endif - if (likely(PyCFunction_Check(func))) { - if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { - return __Pyx_PyObject_CallMethO(func, arg); -#if CYTHON_FAST_PYCCALL - } else if (__Pyx_PyFastCFunction_Check(func)) { - return __Pyx_PyCFunction_FastCall(func, &arg, 1); -#endif - } - } - return __Pyx__PyObject_CallOneArg(func, arg); -} -#else -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *result; - PyObject *args = PyTuple_Pack(1, arg); - if (unlikely(!args)) return NULL; - result = __Pyx_PyObject_Call(func, args, NULL); - Py_DECREF(args); - return result; -} -#endif - -/* MemviewSliceInit */ -static int -__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, - int ndim, - __Pyx_memviewslice *memviewslice, - int memview_is_new_reference) -{ - __Pyx_RefNannyDeclarations - int i, retval=-1; - Py_buffer *buf = &memview->view; - __Pyx_RefNannySetupContext("init_memviewslice", 0); - if (unlikely(memviewslice->memview || memviewslice->data)) { - PyErr_SetString(PyExc_ValueError, - "memviewslice is already initialized!"); - goto fail; - } - if (buf->strides) { - for (i = 0; i < ndim; i++) { - memviewslice->strides[i] = buf->strides[i]; - } - } else { - Py_ssize_t stride = buf->itemsize; - for (i = ndim - 1; i >= 0; i--) { - memviewslice->strides[i] = stride; - stride *= buf->shape[i]; - } - } - for (i = 0; i < ndim; i++) { - memviewslice->shape[i] = buf->shape[i]; - if (buf->suboffsets) { - memviewslice->suboffsets[i] = buf->suboffsets[i]; - } else { - memviewslice->suboffsets[i] = -1; - } - } - memviewslice->memview = memview; - memviewslice->data = (char *)buf->buf; - if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { - Py_INCREF(memview); - } - retval = 0; - goto no_fail; -fail: - memviewslice->memview = 0; - memviewslice->data = 0; - retval = -1; -no_fail: - __Pyx_RefNannyFinishContext(); - return retval; -} -#ifndef Py_NO_RETURN -#define Py_NO_RETURN -#endif -static void __pyx_fatalerror(const char *fmt, ...) Py_NO_RETURN { - va_list vargs; - char msg[200]; -#ifdef HAVE_STDARG_PROTOTYPES - va_start(vargs, fmt); -#else - va_start(vargs); -#endif - vsnprintf(msg, 200, fmt, vargs); - va_end(vargs); - Py_FatalError(msg); -} -static CYTHON_INLINE int -__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, - PyThread_type_lock lock) -{ - int result; - PyThread_acquire_lock(lock, 1); - result = (*acquisition_count)++; - PyThread_release_lock(lock); - return result; -} -static CYTHON_INLINE int -__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, - PyThread_type_lock lock) -{ - int result; - PyThread_acquire_lock(lock, 1); - result = (*acquisition_count)--; - PyThread_release_lock(lock); - return result; -} -static CYTHON_INLINE void -__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) -{ - int first_time; - struct __pyx_memoryview_obj *memview = memslice->memview; - if (unlikely(!memview || (PyObject *) memview == Py_None)) - return; - if (unlikely(__pyx_get_slice_count(memview) < 0)) - __pyx_fatalerror("Acquisition count is %d (line %d)", - __pyx_get_slice_count(memview), lineno); - first_time = __pyx_add_acquisition_count(memview) == 0; - if (unlikely(first_time)) { - if (have_gil) { - Py_INCREF((PyObject *) memview); - } else { - PyGILState_STATE _gilstate = PyGILState_Ensure(); - Py_INCREF((PyObject *) memview); - PyGILState_Release(_gilstate); - } - } -} -static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, - int have_gil, int lineno) { - int last_time; - struct __pyx_memoryview_obj *memview = memslice->memview; - if (unlikely(!memview || (PyObject *) memview == Py_None)) { - memslice->memview = NULL; - return; - } - if (unlikely(__pyx_get_slice_count(memview) <= 0)) - __pyx_fatalerror("Acquisition count is %d (line %d)", - __pyx_get_slice_count(memview), lineno); - last_time = __pyx_sub_acquisition_count(memview) == 1; - memslice->data = NULL; - if (unlikely(last_time)) { - if (have_gil) { - Py_CLEAR(memslice->memview); - } else { - PyGILState_STATE _gilstate = PyGILState_Ensure(); - Py_CLEAR(memslice->memview); - PyGILState_Release(_gilstate); - } - } else { - memslice->memview = NULL; - } -} - -/* GetTopmostException */ -#if CYTHON_USE_EXC_INFO_STACK -static _PyErr_StackItem * -__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) -{ - _PyErr_StackItem *exc_info = tstate->exc_info; - while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && - exc_info->previous_item != NULL) - { - exc_info = exc_info->previous_item; - } - return exc_info; -} -#endif - -/* SaveResetException */ -#if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); - *type = exc_info->exc_type; - *value = exc_info->exc_value; - *tb = exc_info->exc_traceback; - #else - *type = tstate->exc_type; - *value = tstate->exc_value; - *tb = tstate->exc_traceback; - #endif - Py_XINCREF(*type); - Py_XINCREF(*value); - Py_XINCREF(*tb); -} -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = type; - exc_info->exc_value = value; - exc_info->exc_traceback = tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = type; - tstate->exc_value = value; - tstate->exc_traceback = tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -#endif - -/* PyErrExceptionMatches */ -#if CYTHON_FAST_THREAD_STATE -static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; icurexc_type; - if (exc_type == err) return 1; - if (unlikely(!exc_type)) return 0; - if (unlikely(PyTuple_Check(err))) - return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); - return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); -} -#endif - -/* GetException */ -#if CYTHON_FAST_THREAD_STATE -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) -#endif -{ - PyObject *local_type, *local_value, *local_tb; -#if CYTHON_FAST_THREAD_STATE - PyObject *tmp_type, *tmp_value, *tmp_tb; - local_type = tstate->curexc_type; - local_value = tstate->curexc_value; - local_tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -#else - PyErr_Fetch(&local_type, &local_value, &local_tb); -#endif - PyErr_NormalizeException(&local_type, &local_value, &local_tb); -#if CYTHON_FAST_THREAD_STATE - if (unlikely(tstate->curexc_type)) -#else - if (unlikely(PyErr_Occurred())) -#endif - goto bad; - #if PY_MAJOR_VERSION >= 3 - if (local_tb) { - if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) - goto bad; - } - #endif - Py_XINCREF(local_tb); - Py_XINCREF(local_type); - Py_XINCREF(local_value); - *type = local_type; - *value = local_value; - *tb = local_tb; -#if CYTHON_FAST_THREAD_STATE - #if CYTHON_USE_EXC_INFO_STACK - { - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = local_type; - exc_info->exc_value = local_value; - exc_info->exc_traceback = local_tb; - } - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = local_type; - tstate->exc_value = local_value; - tstate->exc_traceback = local_tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#else - PyErr_SetExcInfo(local_type, local_value, local_tb); -#endif - return 0; -bad: - *type = 0; - *value = 0; - *tb = 0; - Py_XDECREF(local_type); - Py_XDECREF(local_value); - Py_XDECREF(local_tb); - return -1; -} - -/* ArgTypeTest */ -static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) -{ - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - else if (exact) { - #if PY_MAJOR_VERSION == 2 - if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; - #endif - } - else { - if (likely(__Pyx_TypeCheck(obj, type))) return 1; - } - PyErr_Format(PyExc_TypeError, - "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", - name, type->tp_name, Py_TYPE(obj)->tp_name); - return 0; -} - -/* PyObjectCall2Args */ -static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { - PyObject *args, *result = NULL; - #if CYTHON_FAST_PYCALL - if (PyFunction_Check(function)) { - PyObject *args[2] = {arg1, arg2}; - return __Pyx_PyFunction_FastCall(function, args, 2); - } - #endif - #if CYTHON_FAST_PYCCALL - if (__Pyx_PyFastCFunction_Check(function)) { - PyObject *args[2] = {arg1, arg2}; - return __Pyx_PyCFunction_FastCall(function, args, 2); - } - #endif - args = PyTuple_New(2); - if (unlikely(!args)) goto done; - Py_INCREF(arg1); - PyTuple_SET_ITEM(args, 0, arg1); - Py_INCREF(arg2); - PyTuple_SET_ITEM(args, 1, arg2); - Py_INCREF(function); - result = __Pyx_PyObject_Call(function, args, NULL); - Py_DECREF(args); - Py_DECREF(function); -done: - return result; -} - -/* BytesEquals */ -static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { -#if CYTHON_COMPILING_IN_PYPY - return PyObject_RichCompareBool(s1, s2, equals); -#else - if (s1 == s2) { - return (equals == Py_EQ); - } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { - const char *ps1, *ps2; - Py_ssize_t length = PyBytes_GET_SIZE(s1); - if (length != PyBytes_GET_SIZE(s2)) - return (equals == Py_NE); - ps1 = PyBytes_AS_STRING(s1); - ps2 = PyBytes_AS_STRING(s2); - if (ps1[0] != ps2[0]) { - return (equals == Py_NE); - } else if (length == 1) { - return (equals == Py_EQ); - } else { - int result; -#if CYTHON_USE_UNICODE_INTERNALS - Py_hash_t hash1, hash2; - hash1 = ((PyBytesObject*)s1)->ob_shash; - hash2 = ((PyBytesObject*)s2)->ob_shash; - if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { - return (equals == Py_NE); - } -#endif - result = memcmp(ps1, ps2, (size_t)length); - return (equals == Py_EQ) ? (result == 0) : (result != 0); - } - } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { - return (equals == Py_NE); - } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { - return (equals == Py_NE); - } else { - int result; - PyObject* py_result = PyObject_RichCompare(s1, s2, equals); - if (!py_result) - return -1; - result = __Pyx_PyObject_IsTrue(py_result); - Py_DECREF(py_result); - return result; - } -#endif -} - -/* UnicodeEquals */ -static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { -#if CYTHON_COMPILING_IN_PYPY - return PyObject_RichCompareBool(s1, s2, equals); -#else -#if PY_MAJOR_VERSION < 3 - PyObject* owned_ref = NULL; -#endif - int s1_is_unicode, s2_is_unicode; - if (s1 == s2) { - goto return_eq; - } - s1_is_unicode = PyUnicode_CheckExact(s1); - s2_is_unicode = PyUnicode_CheckExact(s2); -#if PY_MAJOR_VERSION < 3 - if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { - owned_ref = PyUnicode_FromObject(s2); - if (unlikely(!owned_ref)) - return -1; - s2 = owned_ref; - s2_is_unicode = 1; - } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { - owned_ref = PyUnicode_FromObject(s1); - if (unlikely(!owned_ref)) - return -1; - s1 = owned_ref; - s1_is_unicode = 1; - } else if (((!s2_is_unicode) & (!s1_is_unicode))) { - return __Pyx_PyBytes_Equals(s1, s2, equals); - } -#endif - if (s1_is_unicode & s2_is_unicode) { - Py_ssize_t length; - int kind; - void *data1, *data2; - if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) - return -1; - length = __Pyx_PyUnicode_GET_LENGTH(s1); - if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { - goto return_ne; - } -#if CYTHON_USE_UNICODE_INTERNALS - { - Py_hash_t hash1, hash2; - #if CYTHON_PEP393_ENABLED - hash1 = ((PyASCIIObject*)s1)->hash; - hash2 = ((PyASCIIObject*)s2)->hash; - #else - hash1 = ((PyUnicodeObject*)s1)->hash; - hash2 = ((PyUnicodeObject*)s2)->hash; - #endif - if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { - goto return_ne; - } - } -#endif - kind = __Pyx_PyUnicode_KIND(s1); - if (kind != __Pyx_PyUnicode_KIND(s2)) { - goto return_ne; - } - data1 = __Pyx_PyUnicode_DATA(s1); - data2 = __Pyx_PyUnicode_DATA(s2); - if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { - goto return_ne; - } else if (length == 1) { - goto return_eq; - } else { - int result = memcmp(data1, data2, (size_t)(length * kind)); - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - return (equals == Py_EQ) ? (result == 0) : (result != 0); - } - } else if ((s1 == Py_None) & s2_is_unicode) { - goto return_ne; - } else if ((s2 == Py_None) & s1_is_unicode) { - goto return_ne; - } else { - int result; - PyObject* py_result = PyObject_RichCompare(s1, s2, equals); - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - if (!py_result) - return -1; - result = __Pyx_PyObject_IsTrue(py_result); - Py_DECREF(py_result); - return result; - } -return_eq: - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - return (equals == Py_EQ); -return_ne: - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - return (equals == Py_NE); -#endif -} - -/* GetAttr */ -static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { -#if CYTHON_USE_TYPE_SLOTS -#if PY_MAJOR_VERSION >= 3 - if (likely(PyUnicode_Check(n))) -#else - if (likely(PyString_Check(n))) -#endif - return __Pyx_PyObject_GetAttrStr(o, n); -#endif - return PyObject_GetAttr(o, n); -} - -/* GetItemInt */ -static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { - PyObject *r; - if (!j) return NULL; - r = PyObject_GetItem(o, j); - Py_DECREF(j); - return r; -} -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, - CYTHON_NCP_UNUSED int wraparound, - CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS - Py_ssize_t wrapped_i = i; - if (wraparound & unlikely(i < 0)) { - wrapped_i += PyList_GET_SIZE(o); - } - if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { - PyObject *r = PyList_GET_ITEM(o, wrapped_i); - Py_INCREF(r); - return r; - } - return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); -#else - return PySequence_GetItem(o, i); -#endif -} -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, - CYTHON_NCP_UNUSED int wraparound, - CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS - Py_ssize_t wrapped_i = i; - if (wraparound & unlikely(i < 0)) { - wrapped_i += PyTuple_GET_SIZE(o); - } - if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { - PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); - Py_INCREF(r); - return r; - } - return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); -#else - return PySequence_GetItem(o, i); -#endif -} -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, - CYTHON_NCP_UNUSED int wraparound, - CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS - if (is_list || PyList_CheckExact(o)) { - Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); - if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { - PyObject *r = PyList_GET_ITEM(o, n); - Py_INCREF(r); - return r; - } - } - else if (PyTuple_CheckExact(o)) { - Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); - if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { - PyObject *r = PyTuple_GET_ITEM(o, n); - Py_INCREF(r); - return r; - } - } else { - PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; - if (likely(m && m->sq_item)) { - if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { - Py_ssize_t l = m->sq_length(o); - if (likely(l >= 0)) { - i += l; - } else { - if (!PyErr_ExceptionMatches(PyExc_OverflowError)) - return NULL; - PyErr_Clear(); - } - } - return m->sq_item(o, i); - } - } -#else - if (is_list || PySequence_Check(o)) { - return PySequence_GetItem(o, i); - } -#endif - return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); -} - -/* ObjectGetItem */ -#if CYTHON_USE_TYPE_SLOTS -static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { - PyObject *runerr; - Py_ssize_t key_value; - PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; - if (unlikely(!(m && m->sq_item))) { - PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); - return NULL; - } - key_value = __Pyx_PyIndex_AsSsize_t(index); - if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { - return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); - } - if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { - PyErr_Clear(); - PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); - } - return NULL; -} -static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { - PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; - if (likely(m && m->mp_subscript)) { - return m->mp_subscript(obj, key); - } - return __Pyx_PyObject_GetIndex(obj, key); -} -#endif - -/* decode_c_string */ -static CYTHON_INLINE PyObject* __Pyx_decode_c_string( - const char* cstring, Py_ssize_t start, Py_ssize_t stop, - const char* encoding, const char* errors, - PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { - Py_ssize_t length; - if (unlikely((start < 0) | (stop < 0))) { - size_t slen = strlen(cstring); - if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { - PyErr_SetString(PyExc_OverflowError, - "c-string too long to convert to Python"); - return NULL; - } - length = (Py_ssize_t) slen; - if (start < 0) { - start += length; - if (start < 0) - start = 0; - } - if (stop < 0) - stop += length; - } - if (unlikely(stop <= start)) - return __Pyx_NewRef(__pyx_empty_unicode); - length = stop - start; - cstring += start; - if (decode_func) { - return decode_func(cstring, length, errors); - } else { - return PyUnicode_Decode(cstring, length, encoding, errors); - } -} - -/* GetAttr3 */ -static PyObject *__Pyx_GetAttr3Default(PyObject *d) { - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) - return NULL; - __Pyx_PyErr_Clear(); - Py_INCREF(d); - return d; -} -static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) { - PyObject *r = __Pyx_GetAttr(o, n); - return (likely(r)) ? r : __Pyx_GetAttr3Default(d); -} - -/* PyDictVersioning */ -#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS -static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { - PyObject *dict = Py_TYPE(obj)->tp_dict; - return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; -} -static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { - PyObject **dictptr = NULL; - Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; - if (offset) { -#if CYTHON_COMPILING_IN_CPYTHON - dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); -#else - dictptr = _PyObject_GetDictPtr(obj); -#endif - } - return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; -} -static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { - PyObject *dict = Py_TYPE(obj)->tp_dict; - if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) - return 0; - return obj_dict_version == __Pyx_get_object_dict_version(obj); -} -#endif - -/* GetModuleGlobalName */ -#if CYTHON_USE_DICT_VERSIONS -static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) -#else -static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) -#endif -{ - PyObject *result; -#if !CYTHON_AVOID_BORROWED_REFS -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 - result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); - __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return __Pyx_NewRef(result); - } else if (unlikely(PyErr_Occurred())) { - return NULL; - } -#else - result = PyDict_GetItem(__pyx_d, name); - __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return __Pyx_NewRef(result); - } -#endif -#else - result = PyObject_GetItem(__pyx_d, name); - __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return __Pyx_NewRef(result); - } - PyErr_Clear(); -#endif - return __Pyx_GetBuiltinName(name); -} - -/* RaiseTooManyValuesToUnpack */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { - PyErr_Format(PyExc_ValueError, - "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); -} - -/* RaiseNeedMoreValuesToUnpack */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { - PyErr_Format(PyExc_ValueError, - "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", - index, (index == 1) ? "" : "s"); -} - -/* RaiseNoneIterError */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { - PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); -} - -/* ExtTypeTest */ -static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - if (likely(__Pyx_TypeCheck(obj, type))) - return 1; - PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", - Py_TYPE(obj)->tp_name, type->tp_name); - return 0; -} - -/* SwapException */ -#if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = *type; - exc_info->exc_value = *value; - exc_info->exc_traceback = *tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = *type; - tstate->exc_value = *value; - tstate->exc_traceback = *tb; - #endif - *type = tmp_type; - *value = tmp_value; - *tb = tmp_tb; -} -#else -static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); - PyErr_SetExcInfo(*type, *value, *tb); - *type = tmp_type; - *value = tmp_value; - *tb = tmp_tb; -} -#endif - -/* Import */ -static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { - PyObject *empty_list = 0; - PyObject *module = 0; - PyObject *global_dict = 0; - PyObject *empty_dict = 0; - PyObject *list; - #if PY_MAJOR_VERSION < 3 - PyObject *py_import; - py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); - if (!py_import) - goto bad; - #endif - if (from_list) - list = from_list; - else { - empty_list = PyList_New(0); - if (!empty_list) - goto bad; - list = empty_list; - } - global_dict = PyModule_GetDict(__pyx_m); - if (!global_dict) - goto bad; - empty_dict = PyDict_New(); - if (!empty_dict) - goto bad; - { - #if PY_MAJOR_VERSION >= 3 - if (level == -1) { - if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, 1); - if (!module) { - if (!PyErr_ExceptionMatches(PyExc_ImportError)) - goto bad; - PyErr_Clear(); - } - } - level = 0; - } - #endif - if (!module) { - #if PY_MAJOR_VERSION < 3 - PyObject *py_level = PyInt_FromLong(level); - if (!py_level) - goto bad; - module = PyObject_CallFunctionObjArgs(py_import, - name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); - Py_DECREF(py_level); - #else - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, level); - #endif - } - } -bad: - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(py_import); - #endif - Py_XDECREF(empty_list); - Py_XDECREF(empty_dict); - return module; -} - -/* FastTypeChecks */ -#if CYTHON_COMPILING_IN_CPYTHON -static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { - while (a) { - a = a->tp_base; - if (a == b) - return 1; - } - return b == &PyBaseObject_Type; -} -static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { - PyObject *mro; - if (a == b) return 1; - mro = a->tp_mro; - if (likely(mro)) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(mro); - for (i = 0; i < n; i++) { - if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) - return 1; - } - return 0; - } - return __Pyx_InBases(a, b); -} -#if PY_MAJOR_VERSION == 2 -static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { - PyObject *exception, *value, *tb; - int res; - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - __Pyx_ErrFetch(&exception, &value, &tb); - res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; - if (unlikely(res == -1)) { - PyErr_WriteUnraisable(err); - res = 0; - } - if (!res) { - res = PyObject_IsSubclass(err, exc_type2); - if (unlikely(res == -1)) { - PyErr_WriteUnraisable(err); - res = 0; - } - } - __Pyx_ErrRestore(exception, value, tb); - return res; -} -#else -static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { - int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; - if (!res) { - res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); - } - return res; -} -#endif -static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - assert(PyExceptionClass_Check(exc_type)); - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; i= 0 || (x^b) >= 0)) - return PyInt_FromLong(x); - return PyLong_Type.tp_as_number->nb_add(op1, op2); - } - #endif - #if CYTHON_USE_PYLONG_INTERNALS - if (likely(PyLong_CheckExact(op1))) { - const long b = intval; - long a, x; -#ifdef HAVE_LONG_LONG - const PY_LONG_LONG llb = intval; - PY_LONG_LONG lla, llx; -#endif - const digit* digits = ((PyLongObject*)op1)->ob_digit; - const Py_ssize_t size = Py_SIZE(op1); - if (likely(__Pyx_sst_abs(size) <= 1)) { - a = likely(size) ? digits[0] : 0; - if (size == -1) a = -a; - } else { - switch (size) { - case -2: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case 2: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case -3: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case 3: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case -4: - if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case 4: - if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - default: return PyLong_Type.tp_as_number->nb_add(op1, op2); - } - } - x = a + b; - return PyLong_FromLong(x); -#ifdef HAVE_LONG_LONG - long_long: - llx = lla + llb; - return PyLong_FromLongLong(llx); -#endif - - - } - #endif - if (PyFloat_CheckExact(op1)) { - const long b = intval; - double a = PyFloat_AS_DOUBLE(op1); - double result; - PyFPE_START_PROTECT("add", return NULL) - result = ((double)a) + (double)b; - PyFPE_END_PROTECT(result) - return PyFloat_FromDouble(result); - } - return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); -} -#endif - -/* None */ -static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { - PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); -} - -/* ImportFrom */ -static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { - PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); - if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { - PyErr_Format(PyExc_ImportError, - #if PY_MAJOR_VERSION < 3 - "cannot import name %.230s", PyString_AS_STRING(name)); - #else - "cannot import name %S", name); - #endif - } - return value; -} - -/* HasAttr */ -static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) { - PyObject *r; - if (unlikely(!__Pyx_PyBaseString_Check(n))) { - PyErr_SetString(PyExc_TypeError, - "hasattr(): attribute name must be string"); - return -1; - } - r = __Pyx_GetAttr(o, n); - if (unlikely(!r)) { - PyErr_Clear(); - return 0; - } else { - Py_DECREF(r); - return 1; - } -} - -/* PyObject_GenericGetAttrNoDict */ -#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 -static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) { - PyErr_Format(PyExc_AttributeError, -#if PY_MAJOR_VERSION >= 3 - "'%.50s' object has no attribute '%U'", - tp->tp_name, attr_name); -#else - "'%.50s' object has no attribute '%.400s'", - tp->tp_name, PyString_AS_STRING(attr_name)); -#endif - return NULL; -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) { - PyObject *descr; - PyTypeObject *tp = Py_TYPE(obj); - if (unlikely(!PyString_Check(attr_name))) { - return PyObject_GenericGetAttr(obj, attr_name); - } - assert(!tp->tp_dictoffset); - descr = _PyType_Lookup(tp, attr_name); - if (unlikely(!descr)) { - return __Pyx_RaiseGenericGetAttributeError(tp, attr_name); - } - Py_INCREF(descr); - #if PY_MAJOR_VERSION < 3 - if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS))) - #endif - { - descrgetfunc f = Py_TYPE(descr)->tp_descr_get; - if (unlikely(f)) { - PyObject *res = f(descr, obj, (PyObject *)tp); - Py_DECREF(descr); - return res; - } - } - return descr; -} -#endif - -/* PyObject_GenericGetAttr */ -#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 -static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) { - if (unlikely(Py_TYPE(obj)->tp_dictoffset)) { - return PyObject_GenericGetAttr(obj, attr_name); - } - return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name); -} -#endif - -/* SetVTable */ -static int __Pyx_SetVtable(PyObject *dict, void *vtable) { -#if PY_VERSION_HEX >= 0x02070000 - PyObject *ob = PyCapsule_New(vtable, 0, 0); -#else - PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); -#endif - if (!ob) - goto bad; - if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) - goto bad; - Py_DECREF(ob); - return 0; -bad: - Py_XDECREF(ob); - return -1; -} - -/* PyObjectGetAttrStrNoError */ -static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) - __Pyx_PyErr_Clear(); -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { - PyObject *result; -#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 - PyTypeObject* tp = Py_TYPE(obj); - if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { - return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); - } -#endif - result = __Pyx_PyObject_GetAttrStr(obj, attr_name); - if (unlikely(!result)) { - __Pyx_PyObject_GetAttrStr_ClearAttributeError(); - } - return result; -} - -/* SetupReduce */ -static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { - int ret; - PyObject *name_attr; - name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2); - if (likely(name_attr)) { - ret = PyObject_RichCompareBool(name_attr, name, Py_EQ); - } else { - ret = -1; - } - if (unlikely(ret < 0)) { - PyErr_Clear(); - ret = 0; - } - Py_XDECREF(name_attr); - return ret; -} -static int __Pyx_setup_reduce(PyObject* type_obj) { - int ret = 0; - PyObject *object_reduce = NULL; - PyObject *object_reduce_ex = NULL; - PyObject *reduce = NULL; - PyObject *reduce_ex = NULL; - PyObject *reduce_cython = NULL; - PyObject *setstate = NULL; - PyObject *setstate_cython = NULL; -#if CYTHON_USE_PYTYPE_LOOKUP - if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; -#else - if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; -#endif -#if CYTHON_USE_PYTYPE_LOOKUP - object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; -#else - object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; -#endif - reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; - if (reduce_ex == object_reduce_ex) { -#if CYTHON_USE_PYTYPE_LOOKUP - object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; -#else - object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; -#endif - reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; - if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { - reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); - if (likely(reduce_cython)) { - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - } else if (reduce == object_reduce || PyErr_Occurred()) { - goto __PYX_BAD; - } - setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); - if (!setstate) PyErr_Clear(); - if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { - setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); - if (likely(setstate_cython)) { - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - } else if (!setstate || PyErr_Occurred()) { - goto __PYX_BAD; - } - } - PyType_Modified((PyTypeObject*)type_obj); - } - } - goto __PYX_GOOD; -__PYX_BAD: - if (!PyErr_Occurred()) - PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); - ret = -1; -__PYX_GOOD: -#if !CYTHON_USE_PYTYPE_LOOKUP - Py_XDECREF(object_reduce); - Py_XDECREF(object_reduce_ex); -#endif - Py_XDECREF(reduce); - Py_XDECREF(reduce_ex); - Py_XDECREF(reduce_cython); - Py_XDECREF(setstate); - Py_XDECREF(setstate_cython); - return ret; -} - -/* TypeImport */ -#ifndef __PYX_HAVE_RT_ImportType -#define __PYX_HAVE_RT_ImportType -static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, - size_t size, enum __Pyx_ImportType_CheckSize check_size) -{ - PyObject *result = 0; - char warning[200]; - Py_ssize_t basicsize; -#ifdef Py_LIMITED_API - PyObject *py_basicsize; -#endif - result = PyObject_GetAttrString(module, class_name); - if (!result) - goto bad; - if (!PyType_Check(result)) { - PyErr_Format(PyExc_TypeError, - "%.200s.%.200s is not a type object", - module_name, class_name); - goto bad; - } -#ifndef Py_LIMITED_API - basicsize = ((PyTypeObject *)result)->tp_basicsize; -#else - py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); - if (!py_basicsize) - goto bad; - basicsize = PyLong_AsSsize_t(py_basicsize); - Py_DECREF(py_basicsize); - py_basicsize = 0; - if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) - goto bad; -#endif - if ((size_t)basicsize < size) { - PyErr_Format(PyExc_ValueError, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - goto bad; - } - if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { - PyErr_Format(PyExc_ValueError, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - goto bad; - } - else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { - PyOS_snprintf(warning, sizeof(warning), - "%s.%s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; - } - return (PyTypeObject *)result; -bad: - Py_XDECREF(result); - return NULL; -} -#endif - -/* GetVTable */ -static void* __Pyx_GetVtable(PyObject *dict) { - void* ptr; - PyObject *ob = PyObject_GetItem(dict, __pyx_n_s_pyx_vtable); - if (!ob) - goto bad; -#if PY_VERSION_HEX >= 0x02070000 - ptr = PyCapsule_GetPointer(ob, 0); -#else - ptr = PyCObject_AsVoidPtr(ob); -#endif - if (!ptr && !PyErr_Occurred()) - PyErr_SetString(PyExc_RuntimeError, "invalid vtable found for imported type"); - Py_DECREF(ob); - return ptr; -bad: - Py_XDECREF(ob); - return NULL; -} - -/* CLineInTraceback */ -#ifndef CYTHON_CLINE_IN_TRACEBACK -static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { - PyObject *use_cline; - PyObject *ptype, *pvalue, *ptraceback; -#if CYTHON_COMPILING_IN_CPYTHON - PyObject **cython_runtime_dict; -#endif - if (unlikely(!__pyx_cython_runtime)) { - return c_line; - } - __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); -#if CYTHON_COMPILING_IN_CPYTHON - cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); - if (likely(cython_runtime_dict)) { - __PYX_PY_DICT_LOOKUP_IF_MODIFIED( - use_cline, *cython_runtime_dict, - __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) - } else -#endif - { - PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); - if (use_cline_obj) { - use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; - Py_DECREF(use_cline_obj); - } else { - PyErr_Clear(); - use_cline = NULL; - } - } - if (!use_cline) { - c_line = 0; - PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); - } - else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { - c_line = 0; - } - __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); - return c_line; -} -#endif - -/* CodeObjectCache */ -static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { - int start = 0, mid = 0, end = count - 1; - if (end >= 0 && code_line > entries[end].code_line) { - return count; - } - while (start < end) { - mid = start + (end - start) / 2; - if (code_line < entries[mid].code_line) { - end = mid; - } else if (code_line > entries[mid].code_line) { - start = mid + 1; - } else { - return mid; - } - } - if (code_line <= entries[mid].code_line) { - return mid; - } else { - return mid + 1; - } -} -static PyCodeObject *__pyx_find_code_object(int code_line) { - PyCodeObject* code_object; - int pos; - if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { - return NULL; - } - pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); - if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { - return NULL; - } - code_object = __pyx_code_cache.entries[pos].code_object; - Py_INCREF(code_object); - return code_object; -} -static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { - int pos, i; - __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; - if (unlikely(!code_line)) { - return; - } - if (unlikely(!entries)) { - entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); - if (likely(entries)) { - __pyx_code_cache.entries = entries; - __pyx_code_cache.max_count = 64; - __pyx_code_cache.count = 1; - entries[0].code_line = code_line; - entries[0].code_object = code_object; - Py_INCREF(code_object); - } - return; - } - pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); - if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { - PyCodeObject* tmp = entries[pos].code_object; - entries[pos].code_object = code_object; - Py_DECREF(tmp); - return; - } - if (__pyx_code_cache.count == __pyx_code_cache.max_count) { - int new_max = __pyx_code_cache.max_count + 64; - entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( - __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); - if (unlikely(!entries)) { - return; - } - __pyx_code_cache.entries = entries; - __pyx_code_cache.max_count = new_max; - } - for (i=__pyx_code_cache.count; i>pos; i--) { - entries[i] = entries[i-1]; - } - entries[pos].code_line = code_line; - entries[pos].code_object = code_object; - __pyx_code_cache.count++; - Py_INCREF(code_object); -} - -/* AddTraceback */ -#include "compile.h" -#include "frameobject.h" -#include "traceback.h" -static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( - const char *funcname, int c_line, - int py_line, const char *filename) { - PyCodeObject *py_code = 0; - PyObject *py_srcfile = 0; - PyObject *py_funcname = 0; - #if PY_MAJOR_VERSION < 3 - py_srcfile = PyString_FromString(filename); - #else - py_srcfile = PyUnicode_FromString(filename); - #endif - if (!py_srcfile) goto bad; - if (c_line) { - #if PY_MAJOR_VERSION < 3 - py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); - #else - py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); - #endif - } - else { - #if PY_MAJOR_VERSION < 3 - py_funcname = PyString_FromString(funcname); - #else - py_funcname = PyUnicode_FromString(funcname); - #endif - } - if (!py_funcname) goto bad; - py_code = __Pyx_PyCode_New( - 0, - 0, - 0, - 0, - 0, - __pyx_empty_bytes, /*PyObject *code,*/ - __pyx_empty_tuple, /*PyObject *consts,*/ - __pyx_empty_tuple, /*PyObject *names,*/ - __pyx_empty_tuple, /*PyObject *varnames,*/ - __pyx_empty_tuple, /*PyObject *freevars,*/ - __pyx_empty_tuple, /*PyObject *cellvars,*/ - py_srcfile, /*PyObject *filename,*/ - py_funcname, /*PyObject *name,*/ - py_line, - __pyx_empty_bytes /*PyObject *lnotab*/ - ); - Py_DECREF(py_srcfile); - Py_DECREF(py_funcname); - return py_code; -bad: - Py_XDECREF(py_srcfile); - Py_XDECREF(py_funcname); - return NULL; -} -static void __Pyx_AddTraceback(const char *funcname, int c_line, - int py_line, const char *filename) { - PyCodeObject *py_code = 0; - PyFrameObject *py_frame = 0; - PyThreadState *tstate = __Pyx_PyThreadState_Current; - if (c_line) { - c_line = __Pyx_CLineForTraceback(tstate, c_line); - } - py_code = __pyx_find_code_object(c_line ? -c_line : py_line); - if (!py_code) { - py_code = __Pyx_CreateCodeObjectForTraceback( - funcname, c_line, py_line, filename); - if (!py_code) goto bad; - __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); - } - py_frame = PyFrame_New( - tstate, /*PyThreadState *tstate,*/ - py_code, /*PyCodeObject *code,*/ - __pyx_d, /*PyObject *globals,*/ - 0 /*PyObject *locals*/ - ); - if (!py_frame) goto bad; - __Pyx_PyFrame_SetLineNumber(py_frame, py_line); - PyTraceBack_Here(py_frame); -bad: - Py_XDECREF(py_code); - Py_XDECREF(py_frame); -} - -#if PY_MAJOR_VERSION < 3 -static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { - if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); - PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); - return -1; -} -static void __Pyx_ReleaseBuffer(Py_buffer *view) { - PyObject *obj = view->obj; - if (!obj) return; - if (PyObject_CheckBuffer(obj)) { - PyBuffer_Release(view); - return; - } - if ((0)) {} - view->obj = NULL; - Py_DECREF(obj); -} -#endif - - -/* MemviewSliceIsContig */ -static int -__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) -{ - int i, index, step, start; - Py_ssize_t itemsize = mvs.memview->view.itemsize; - if (order == 'F') { - step = 1; - start = 0; - } else { - step = -1; - start = ndim - 1; - } - for (i = 0; i < ndim; i++) { - index = start + step * i; - if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) - return 0; - itemsize *= mvs.shape[index]; - } - return 1; -} - -/* OverlappingSlices */ -static void -__pyx_get_array_memory_extents(__Pyx_memviewslice *slice, - void **out_start, void **out_end, - int ndim, size_t itemsize) -{ - char *start, *end; - int i; - start = end = slice->data; - for (i = 0; i < ndim; i++) { - Py_ssize_t stride = slice->strides[i]; - Py_ssize_t extent = slice->shape[i]; - if (extent == 0) { - *out_start = *out_end = start; - return; - } else { - if (stride > 0) - end += stride * (extent - 1); - else - start += stride * (extent - 1); - } - } - *out_start = start; - *out_end = end + itemsize; -} -static int -__pyx_slices_overlap(__Pyx_memviewslice *slice1, - __Pyx_memviewslice *slice2, - int ndim, size_t itemsize) -{ - void *start1, *end1, *start2, *end2; - __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); - __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); - return (start1 < end2) && (start2 < end1); -} - -/* Capsule */ -static CYTHON_INLINE PyObject * -__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) -{ - PyObject *cobj; -#if PY_VERSION_HEX >= 0x02070000 - cobj = PyCapsule_New(p, sig, NULL); -#else - cobj = PyCObject_FromVoidPtr(p, NULL); -#endif - return cobj; -} - -/* CIntFromPyVerify */ -#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ - __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) -#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ - __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) -#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ - {\ - func_type value = func_value;\ - if (sizeof(target_type) < sizeof(func_type)) {\ - if (unlikely(value != (func_type) (target_type) value)) {\ - func_type zero = 0;\ - if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ - return (target_type) -1;\ - if (is_unsigned && unlikely(value < zero))\ - goto raise_neg_overflow;\ - else\ - goto raise_overflow;\ - }\ - }\ - return (target_type) value;\ - } - -/* Declarations */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - return ::std::complex< float >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - return x + y*(__pyx_t_float_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - __pyx_t_float_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ -#if CYTHON_CCOMPLEX -#else - static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - if (b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabsf(b.real) >= fabsf(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - float r = b.imag / b.real; - float s = (float)(1.0) / (b.real + b.imag * r); - return __pyx_t_float_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - float r = b.real / b.imag; - float s = (float)(1.0) / (b.imag + b.real * r); - return __pyx_t_float_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - if (b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - float denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_float_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { - __pyx_t_float_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { - __pyx_t_float_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrtf(z.real*z.real + z.imag*z.imag); - #else - return hypotf(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - float r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - float denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_float(a, a); - case 3: - z = __Pyx_c_prod_float(a, a); - return __Pyx_c_prod_float(z, a); - case 4: - z = __Pyx_c_prod_float(a, a); - return __Pyx_c_prod_float(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if (b.imag == 0) { - z.real = powf(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2f(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_float(a); - theta = atan2f(a.imag, a.real); - } - lnr = logf(r); - z_r = expf(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cosf(z_theta); - z.imag = z_r * sinf(z_theta); - return z; - } - #endif -#endif - -/* Declarations */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - return ::std::complex< double >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - return x + y*(__pyx_t_double_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - __pyx_t_double_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ -#if CYTHON_CCOMPLEX -#else - static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - if (b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabs(b.real) >= fabs(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - double r = b.imag / b.real; - double s = (double)(1.0) / (b.real + b.imag * r); - return __pyx_t_double_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - double r = b.real / b.imag; - double s = (double)(1.0) / (b.imag + b.real * r); - return __pyx_t_double_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - if (b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - double denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_double_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { - __pyx_t_double_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { - __pyx_t_double_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrt(z.real*z.real + z.imag*z.imag); - #else - return hypot(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - double r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - double denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_double(a, a); - case 3: - z = __Pyx_c_prod_double(a, a); - return __Pyx_c_prod_double(z, a); - case 4: - z = __Pyx_c_prod_double(a, a); - return __Pyx_c_prod_double(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if (b.imag == 0) { - z.real = pow(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_double(a); - theta = atan2(a.imag, a.real); - } - lnr = log(r); - z_r = exp(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cos(z_theta); - z.imag = z_r * sin(z_theta); - return z; - } - #endif -#endif - -/* MemviewSliceCopyTemplate */ -static __Pyx_memviewslice -__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, - const char *mode, int ndim, - size_t sizeof_dtype, int contig_flag, - int dtype_is_object) -{ - __Pyx_RefNannyDeclarations - int i; - __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; - struct __pyx_memoryview_obj *from_memview = from_mvs->memview; - Py_buffer *buf = &from_memview->view; - PyObject *shape_tuple = NULL; - PyObject *temp_int = NULL; - struct __pyx_array_obj *array_obj = NULL; - struct __pyx_memoryview_obj *memview_obj = NULL; - __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); - for (i = 0; i < ndim; i++) { - if (unlikely(from_mvs->suboffsets[i] >= 0)) { - PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " - "indirect dimensions (axis %d)", i); - goto fail; - } - } - shape_tuple = PyTuple_New(ndim); - if (unlikely(!shape_tuple)) { - goto fail; - } - __Pyx_GOTREF(shape_tuple); - for(i = 0; i < ndim; i++) { - temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); - if(unlikely(!temp_int)) { - goto fail; - } else { - PyTuple_SET_ITEM(shape_tuple, i, temp_int); - temp_int = NULL; - } - } - array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); - if (unlikely(!array_obj)) { - goto fail; - } - __Pyx_GOTREF(array_obj); - memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( - (PyObject *) array_obj, contig_flag, - dtype_is_object, - from_mvs->memview->typeinfo); - if (unlikely(!memview_obj)) - goto fail; - if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) - goto fail; - if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, - dtype_is_object) < 0)) - goto fail; - goto no_fail; -fail: - __Pyx_XDECREF(new_mvs.memview); - new_mvs.memview = NULL; - new_mvs.data = NULL; -no_fail: - __Pyx_XDECREF(shape_tuple); - __Pyx_XDECREF(temp_int); - __Pyx_XDECREF(array_obj); - __Pyx_RefNannyFinishContext(); - return new_mvs; -} - -/* CIntFromPy */ -static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(Py_intptr_t) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (Py_intptr_t) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (Py_intptr_t) 0; - case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, digits[0]) - case 2: - if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) >= 2 * PyLong_SHIFT) { - return (Py_intptr_t) (((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) >= 3 * PyLong_SHIFT) { - return (Py_intptr_t) (((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) >= 4 * PyLong_SHIFT) { - return (Py_intptr_t) (((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (Py_intptr_t) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (Py_intptr_t) 0; - case -1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, +digits[0]) - case -2: - if (8 * sizeof(Py_intptr_t) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { - return (Py_intptr_t) (((Py_intptr_t)-1)*(((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { - return (Py_intptr_t) ((((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { - return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { - return (Py_intptr_t) ((((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { - return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { - return (Py_intptr_t) ((((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - } -#endif - if (sizeof(Py_intptr_t) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - Py_intptr_t val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (Py_intptr_t) -1; - } - } else { - Py_intptr_t val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (Py_intptr_t) -1; - val = __Pyx_PyInt_As_Py_intptr_t(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to Py_intptr_t"); - return (Py_intptr_t) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to Py_intptr_t"); - return (Py_intptr_t) -1; -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(Py_intptr_t) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(Py_intptr_t) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(Py_intptr_t), - little, !is_unsigned); - } -} - -/* CIntFromPy */ -static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const int neg_one = (int) -1, const_zero = (int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(int) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (int) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (int) 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) - case 2: - if (8 * sizeof(int) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { - return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(int) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { - return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(int) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { - return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (int) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(int) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (int) 0; - case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) - case -2: - if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(int) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(int) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(int) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { - return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - } -#endif - if (sizeof(int) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - int val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (int) -1; - } - } else { - int val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (int) -1; - val = __Pyx_PyInt_As_int(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to int"); - return (int) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to int"); - return (int) -1; -} - -/* CIntFromPy */ -static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const long neg_one = (long) -1, const_zero = (long) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(long) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (long) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (long) 0; - case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) - case 2: - if (8 * sizeof(long) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { - return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(long) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { - return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(long) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { - return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (long) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(long) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (long) 0; - case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) - case -2: - if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(long) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(long) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(long) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - } -#endif - if (sizeof(long) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - long val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (long) -1; - } - } else { - long val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (long) -1; - val = __Pyx_PyInt_As_long(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to long"); - return (long) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to long"); - return (long) -1; -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const int neg_one = (int) -1, const_zero = (int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(int) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(int) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(int) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(int), - little, !is_unsigned); - } -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const long neg_one = (long) -1, const_zero = (long) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(long) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(long) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(long) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(long), - little, !is_unsigned); - } -} - -/* CIntFromPy */ -static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const char neg_one = (char) -1, const_zero = (char) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(char) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (char) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (char) 0; - case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) - case 2: - if (8 * sizeof(char) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { - return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(char) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { - return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(char) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { - return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (char) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(char) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (char) 0; - case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) - case -2: - if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { - return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(char) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { - return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { - return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(char) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { - return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { - return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(char) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { - return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - } -#endif - if (sizeof(char) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - char val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (char) -1; - } - } else { - char val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (char) -1; - val = __Pyx_PyInt_As_char(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to char"); - return (char) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to char"); - return (char) -1; -} - -/* CheckBinaryVersion */ -static int __Pyx_check_binary_version(void) { - char ctversion[4], rtversion[4]; - PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); - PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); - if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { - char message[200]; - PyOS_snprintf(message, sizeof(message), - "compiletime version %s of module '%.100s' " - "does not match runtime version %s", - ctversion, __Pyx_MODULE_NAME, rtversion); - return PyErr_WarnEx(NULL, message, 1); - } - return 0; -} - -/* VoidPtrImport */ -#ifndef __PYX_HAVE_RT_ImportVoidPtr -#define __PYX_HAVE_RT_ImportVoidPtr -static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig) { - PyObject *d = 0; - PyObject *cobj = 0; - d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); - if (!d) - goto bad; - cobj = PyDict_GetItemString(d, name); - if (!cobj) { - PyErr_Format(PyExc_ImportError, - "%.200s does not export expected C variable %.200s", - PyModule_GetName(module), name); - goto bad; - } -#if PY_VERSION_HEX >= 0x02070000 - if (!PyCapsule_IsValid(cobj, sig)) { - PyErr_Format(PyExc_TypeError, - "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), name, sig, PyCapsule_GetName(cobj)); - goto bad; - } - *p = PyCapsule_GetPointer(cobj, sig); -#else - {const char *desc, *s1, *s2; - desc = (const char *)PyCObject_GetDesc(cobj); - if (!desc) - goto bad; - s1 = desc; s2 = sig; - while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } - if (*s1 != *s2) { - PyErr_Format(PyExc_TypeError, - "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), name, sig, desc); - goto bad; - } - *p = PyCObject_AsVoidPtr(cobj);} -#endif - if (!(*p)) - goto bad; - Py_DECREF(d); - return 0; -bad: - Py_XDECREF(d); - return -1; -} -#endif - -/* FunctionImport */ -#ifndef __PYX_HAVE_RT_ImportFunction -#define __PYX_HAVE_RT_ImportFunction -static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig) { - PyObject *d = 0; - PyObject *cobj = 0; - union { - void (*fp)(void); - void *p; - } tmp; - d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); - if (!d) - goto bad; - cobj = PyDict_GetItemString(d, funcname); - if (!cobj) { - PyErr_Format(PyExc_ImportError, - "%.200s does not export expected C function %.200s", - PyModule_GetName(module), funcname); - goto bad; - } -#if PY_VERSION_HEX >= 0x02070000 - if (!PyCapsule_IsValid(cobj, sig)) { - PyErr_Format(PyExc_TypeError, - "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), funcname, sig, PyCapsule_GetName(cobj)); - goto bad; - } - tmp.p = PyCapsule_GetPointer(cobj, sig); -#else - {const char *desc, *s1, *s2; - desc = (const char *)PyCObject_GetDesc(cobj); - if (!desc) - goto bad; - s1 = desc; s2 = sig; - while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } - if (*s1 != *s2) { - PyErr_Format(PyExc_TypeError, - "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), funcname, sig, desc); - goto bad; - } - tmp.p = PyCObject_AsVoidPtr(cobj);} -#endif - *f = tmp.fp; - if (!(*f)) - goto bad; - Py_DECREF(d); - return 0; -bad: - Py_XDECREF(d); - return -1; -} -#endif - -/* InitStrings */ -static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { - while (t->p) { - #if PY_MAJOR_VERSION < 3 - if (t->is_unicode) { - *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); - } else if (t->intern) { - *t->p = PyString_InternFromString(t->s); - } else { - *t->p = PyString_FromStringAndSize(t->s, t->n - 1); - } - #else - if (t->is_unicode | t->is_str) { - if (t->intern) { - *t->p = PyUnicode_InternFromString(t->s); - } else if (t->encoding) { - *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); - } else { - *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); - } - } else { - *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); - } - #endif - if (!*t->p) - return -1; - if (PyObject_Hash(*t->p) == -1) - return -1; - ++t; - } - return 0; -} - -static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { - return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); -} -static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { - Py_ssize_t ignore; - return __Pyx_PyObject_AsStringAndSize(o, &ignore); -} -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT -#if !CYTHON_PEP393_ENABLED -static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { - char* defenc_c; - PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); - if (!defenc) return NULL; - defenc_c = PyBytes_AS_STRING(defenc); -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - { - char* end = defenc_c + PyBytes_GET_SIZE(defenc); - char* c; - for (c = defenc_c; c < end; c++) { - if ((unsigned char) (*c) >= 128) { - PyUnicode_AsASCIIString(o); - return NULL; - } - } - } -#endif - *length = PyBytes_GET_SIZE(defenc); - return defenc_c; -} -#else -static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { - if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - if (likely(PyUnicode_IS_ASCII(o))) { - *length = PyUnicode_GET_LENGTH(o); 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It also computes the output statistics - # such as the mean in regression and class probabilities in classification. - - # Internal structures - cdef const DOUBLE_t[:, ::1] y # Values of y - cdef const DOUBLE_t[:] sample_weight # Sample weights - - cdef const SIZE_t[:] sample_indices # Sample indices in X, y - cdef SIZE_t start # samples[start:pos] are the samples in the left node - cdef SIZE_t pos # samples[pos:end] are the samples in the right node - cdef SIZE_t end - - cdef SIZE_t n_outputs # Number of outputs - cdef SIZE_t n_samples # Number of samples - cdef SIZE_t n_node_samples # Number of samples in the node (end-start) - cdef double weighted_n_samples # Weighted number of samples (in total) - cdef double weighted_n_node_samples # Weighted number of samples in the node - cdef double weighted_n_left # Weighted number of samples in the left node - cdef double weighted_n_right # Weighted number of samples in the right node - - # The criterion object is maintained such that left and right collected - # statistics correspond to samples[start:pos] and samples[pos:end]. - - # Methods - cdef int init( - self, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight, - double weighted_n_samples, - const SIZE_t[:] sample_indices, - SIZE_t start, - SIZE_t end - ) except -1 nogil - cdef int reset(self) except -1 nogil - cdef int reverse_reset(self) except -1 nogil - cdef int update(self, SIZE_t new_pos) except -1 nogil - cdef double node_impurity(self) noexcept nogil - cdef void children_impurity( - self, - double* impurity_left, - double* impurity_right - ) noexcept nogil - cdef void node_value( - self, - double* dest - ) noexcept nogil - cdef double impurity_improvement( - self, - double impurity_parent, - double impurity_left, - double impurity_right - ) noexcept nogil - cdef double proxy_impurity_improvement(self) noexcept nogil - -cdef class ClassificationCriterion(Criterion): - """Abstract criterion for classification.""" - - cdef SIZE_t[::1] n_classes - cdef SIZE_t max_n_classes - 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- -/* "sklearn/tree/_tree.pxd":19 - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - * - */ -typedef npy_int32 __pyx_t_7sklearn_4tree_5_tree_INT32_t; - -/* "sklearn/tree/_tree.pxd":20 - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< - * - * from ._splitter cimport Splitter - */ -typedef npy_uint32 __pyx_t_7sklearn_4tree_5_tree_UINT32_t; - -/* "neighbors/_quad_tree.pxd":13 - * cimport numpy as np - * - * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - */ -typedef npy_float32 __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t; - -/* "neighbors/_quad_tree.pxd":14 - * - * ctypedef np.npy_float32 DTYPE_t # Type of X - * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - */ -typedef npy_intp __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t; - -/* "neighbors/_quad_tree.pxd":15 - * ctypedef np.npy_float32 DTYPE_t # Type of X - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - * - */ -typedef npy_int32 __pyx_t_7sklearn_9neighbors_10_quad_tree_INT32_t; - -/* "neighbors/_quad_tree.pxd":16 - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< - * - * # This is effectively an ifdef statement in Cython - */ -typedef npy_uint32 __pyx_t_7sklearn_9neighbors_10_quad_tree_UINT32_t; - -/* "sklearn/tree/_utils.pxd":16 - * from ..neighbors._quad_tree cimport Cell - * - * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - */ -typedef npy_float32 __pyx_t_7sklearn_4tree_6_utils_DTYPE_t; - -/* "sklearn/tree/_utils.pxd":17 - * - * ctypedef np.npy_float32 DTYPE_t # Type of X - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - */ -typedef npy_float64 __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t; - -/* "sklearn/tree/_utils.pxd":18 - * ctypedef np.npy_float32 DTYPE_t # Type of X - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - */ -typedef npy_intp __pyx_t_7sklearn_4tree_6_utils_SIZE_t; - -/* "sklearn/tree/_utils.pxd":19 - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - * - */ -typedef npy_int32 __pyx_t_7sklearn_4tree_6_utils_INT32_t; - -/* "sklearn/tree/_utils.pxd":20 - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< - * - * - */ -typedef npy_uint32 __pyx_t_7sklearn_4tree_6_utils_UINT32_t; -/* Declarations.proto */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - typedef ::std::complex< float > __pyx_t_float_complex; - #else - typedef float _Complex __pyx_t_float_complex; - #endif -#else - typedef struct { float real, imag; } __pyx_t_float_complex; -#endif -static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); - -/* Declarations.proto */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - typedef ::std::complex< double > __pyx_t_double_complex; - #else - typedef double _Complex __pyx_t_double_complex; - #endif -#else - typedef struct { double real, imag; } __pyx_t_double_complex; -#endif -static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); - - -/*--- Type declarations ---*/ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion; -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter; -struct __pyx_obj_7sklearn_4tree_5_tree_Tree; -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder; -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion; -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree; -struct __pyx_obj_7sklearn_4tree_6_utils_Stack; -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator; -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter; -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter; -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter; -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter; -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter; -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter; -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter; -struct __pyx_array_obj; -struct __pyx_MemviewEnum_obj; -struct __pyx_memoryview_obj; -struct __pyx_memoryviewslice_obj; - -/* "../venv_stpredictions/lib/python3.9/site-packages/numpy/__init__.pxd":728 - * ctypedef npy_longdouble longdouble_t - * - * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< - * ctypedef npy_cdouble cdouble_t - * ctypedef npy_clongdouble clongdouble_t - */ -typedef npy_cfloat __pyx_t_5numpy_cfloat_t; - -/* "../venv_stpredictions/lib/python3.9/site-packages/numpy/__init__.pxd":729 - * - * ctypedef npy_cfloat cfloat_t - * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< - * ctypedef npy_clongdouble clongdouble_t - * - */ -typedef npy_cdouble __pyx_t_5numpy_cdouble_t; - -/* "../venv_stpredictions/lib/python3.9/site-packages/numpy/__init__.pxd":730 - * ctypedef npy_cfloat cfloat_t - * ctypedef npy_cdouble cdouble_t - * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< - * - * ctypedef npy_cdouble complex_t - */ -typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; - -/* "../venv_stpredictions/lib/python3.9/site-packages/numpy/__init__.pxd":732 - * ctypedef npy_clongdouble clongdouble_t - * - * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< - * - * cdef inline object PyArray_MultiIterNew1(a): - */ -typedef npy_cdouble __pyx_t_5numpy_complex_t; -struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord; - -/* "_splitter.pxd":23 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef struct SplitRecord: # <<<<<<<<<<<<<< - * # Data to track sample split - * SIZE_t feature # Which feature to split on. - */ -struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - double threshold; - double improvement; - double impurity_left; - double impurity_right; -}; -struct __pyx_t_7sklearn_4tree_5_tree_Node; -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c; -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances; -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build; - -/* "sklearn/tree/_tree.pxd":25 - * from ._splitter cimport SplitRecord - * - * cdef struct Node: # <<<<<<<<<<<<<< - * # Base storage structure for the nodes in a Tree object - * - */ -struct __pyx_t_7sklearn_4tree_5_tree_Node { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t left_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t right_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t threshold; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t impurity; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t weighted_n_node_samples; -}; - -/* "sklearn/tree/_tree.pxd":63 - * double weighted_n_samples) nogil except -1 - * cdef int _resize(self, SIZE_t capacity) nogil except -1 - * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< - * - * cdef np.ndarray _get_value_ndarray(self) - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c { - int __pyx_n; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; -}; - -/* "sklearn/tree/_tree.pxd":78 - * cdef object _decision_path_sparse_csr(self, object X) - * - * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< - * - * - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances { - int __pyx_n; - PyObject *normalize; -}; - -/* "sklearn/tree/_tree.pxd":102 - * cdef double min_impurity_decrease # Impurity threshold for early stopping - * - * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< - * np.ndarray sample_weight=*) - * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build { - int __pyx_n; - PyArrayObject *sample_weight; -}; -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; - -/* "neighbors/_quad_tree.pxd":21 - * # It allows us to write printf debugging lines - * # and remove them at compile time - * cdef enum: # <<<<<<<<<<<<<< - * DEBUGFLAG = 0 - * - */ -enum { - __pyx_e_7sklearn_9neighbors_10_quad_tree_DEBUGFLAG = 0 -}; - -/* "neighbors/_quad_tree.pxd":29 - * # have is_leaf and max_width consecutive as it permits to avoid padding by - * # the compiler and keep the size coherent for both C and numpy data structures. - * cdef struct Cell: # <<<<<<<<<<<<<< - * # Base storage structure for cells in a QuadTree object - * - */ -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell { - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t parent; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t children[8]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t point_index; - int is_leaf; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t squared_max_width; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cumulative_size; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t center[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t barycenter[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t min_bounds[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t max_bounds[3]; -}; - -/* "neighbors/_quad_tree.pxd":75 - * - * # Point insertion methods - * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< - * SIZE_t cell_id=*) nogil except -1 - * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; -}; - -/* "neighbors/_quad_tree.pxd":77 - * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, - * SIZE_t cell_id=*) nogil except -1 - * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< - * SIZE_t point_index, SIZE_t size=* - * ) nogil - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t size; -}; - -/* "neighbors/_quad_tree.pxd":84 - * - * # Create a summary of the Tree compare to a query point - * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< - * float squared_theta=*, SIZE_t cell_id=*, long idx=* - * ) nogil - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize { - int __pyx_n; - float squared_theta; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; - long idx; -}; - -/* "neighbors/_quad_tree.pxd":99 - * # Private array manipulation to manage the ``cells`` array - * cdef int _resize(self, SIZE_t capacity) nogil except -1 - * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< - * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 - * cdef np.ndarray _get_cell_ndarray(self) - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; -}; - -/* "neighbors/_quad_tree.pxd":100 - * cdef int _resize(self, SIZE_t capacity) nogil except -1 - * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 - * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< - * cdef np.ndarray _get_cell_ndarray(self) - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; -}; -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord; -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord; -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; - -/* "sklearn/tree/_utils.pxd":23 - * - * - * cdef enum: # <<<<<<<<<<<<<< - * # Max value for our rand_r replacement (near the bottom). - * # We don't use RAND_MAX because it's different across platforms and - */ -enum { - __pyx_e_7sklearn_4tree_6_utils_RAND_R_MAX = 0x7FFFFFFF -}; - -/* "sklearn/tree/_utils.pxd":70 - * - * # A record on the stack for depth-first tree growing - * cdef struct StackRecord: # <<<<<<<<<<<<<< - * SIZE_t start - * SIZE_t end - */ -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t parent; - int is_left; - double impurity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t n_constant_features; -}; - -/* "sklearn/tree/_utils.pxd":96 - * - * # A record on the frontier for best-first tree growing - * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< - * SIZE_t node_id - * SIZE_t start - */ -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t node_id; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t pos; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; - int is_leaf; - double impurity; - double impurity_left; - double impurity_right; - double improvement; -}; - -/* "sklearn/tree/_utils.pxd":127 - * - * # A record stored in the WeightedPQueue - * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< - * DOUBLE_t data - * DOUBLE_t weight - */ -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord { - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t data; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t weight; -}; -struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord; - -/* "stpredictions/models/OK3/_splitter.pxd":14 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef struct SplitRecord: # <<<<<<<<<<<<<< - * # Data to track sample split - * SIZE_t feature # Which feature to split on. - */ -struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - double threshold; - double improvement; - double impurity_left; - double impurity_right; -}; - -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtab; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - double weighted_n_samples; - double weighted_n_node_samples; - double weighted_n_left; - double weighted_n_right; - double *sum_total; - double *sum_left; - double *sum_right; -}; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t sum_stride; -}; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - double sq_sum_total; -}; - - -/* "_splitter.pxd":34 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *criterion; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - PyObject *random_state; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - double weighted_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; -}; - - -/* "sklearn/tree/_tree.pxd":37 - * - * - * cdef class Tree: # <<<<<<<<<<<<<< - * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and - */ -struct __pyx_obj_7sklearn_4tree_5_tree_Tree { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtab; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t node_count; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; - struct __pyx_t_7sklearn_4tree_5_tree_Node *nodes; - double *value; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t value_stride; -}; - - -/* "sklearn/tree/_tree.pxd":85 - * # ============================================================================= - * - * cdef class TreeBuilder: # <<<<<<<<<<<<<< - * # The TreeBuilder recursively builds a Tree object from training samples, - * # using a Splitter object for splitting internal nodes and assigning - */ -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *splitter; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_split; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; - double min_impurity_split; - double min_impurity_decrease; -}; - - -/* "_criterion.pxd":12 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. - */ -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion { - PyObject_HEAD - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtab; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - double weighted_n_samples; - double weighted_n_node_samples; - double weighted_n_left; - double weighted_n_right; -}; - - -/* "_criterion.pxd":50 - * - * - * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract kernelized output regression criterion.""" - * - */ -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { - struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; - double sum_diag_Gramm; - double sum_total_Gramm; - double sum_diag_Gramm_left; - double sum_diag_Gramm_right; - double sum_total_Gramm_left; - double sum_total_Gramm_right; -}; - - -/* "neighbors/_quad_tree.pxd":55 - * - * - * cdef class _QuadTree: # <<<<<<<<<<<<<< - * # The QuadTree object is a quad tree structure constructed by inserting - * # recursively points in the tree and splitting cells in 4 so that each - */ -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtab; - int n_dimensions; - int verbose; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_cells_per_cell; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t max_depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_count; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_points; - struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *cells; -}; - - -/* "sklearn/tree/_utils.pxd":79 - * SIZE_t n_constant_features - * - * cdef class Stack: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t top - */ -struct __pyx_obj_7sklearn_4tree_6_utils_Stack { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t top; - struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *stack_; -}; - - -/* "sklearn/tree/_utils.pxd":108 - * double improvement - * - * cdef class PriorityHeap: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t heap_ptr - */ -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t heap_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *heap_; -}; - - -/* "sklearn/tree/_utils.pxd":131 - * DOUBLE_t weight - * - * cdef class WeightedPQueue: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t array_ptr - */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t array_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *array_; -}; - - -/* "sklearn/tree/_utils.pxd":151 - * # ============================================================================= - * - * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< - * cdef SIZE_t initial_capacity - * cdef WeightedPQueue samples - */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t initial_capacity; - struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *samples; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t total_weight; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t k; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t sum_w_0_k; -}; - - -/* "stpredictions/models/OK3/_splitter.pxd":25 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter { - PyObject_HEAD - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtab; - struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *criterion; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - PyObject *random_state; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - double weighted_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; -}; - - -/* "stpredictions/models/OK3/_splitter.pyx":223 - * - * - * cdef class BaseDenseSplitter(Splitter): # <<<<<<<<<<<<<< - * cdef const DTYPE_t[:, :] X - * - */ -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter { - struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter __pyx_base; - __Pyx_memviewslice X; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_total_samples; -}; - - -/* "stpredictions/models/OK3/_splitter.pyx":245 - * - * - * cdef class BestSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< - * """Splitter for finding the best split.""" - * def __reduce__(self): - */ -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter { - struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter __pyx_base; -}; - - -/* "stpredictions/models/OK3/_splitter.pyx":564 - * - * - * cdef class RandomSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< - * """Splitter for finding the best random split.""" - * def __reduce__(self): - */ -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter { - struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter __pyx_base; -}; - - -/* "stpredictions/models/OK3/_splitter.pyx":761 - * - * - * cdef class BaseSparseSplitter(Splitter): # <<<<<<<<<<<<<< - * # The sparse splitter works only with csc sparse matrix format - * cdef DTYPE_t* X_data - */ -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter { - struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter __pyx_base; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *X_data; - __pyx_t_7sklearn_4tree_5_tree_INT32_t *X_indices; - __pyx_t_7sklearn_4tree_5_tree_INT32_t *X_indptr; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_total_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *index_to_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *sorted_samples; -}; - - -/* "stpredictions/models/OK3/_splitter.pyx":1080 - * - * - * cdef class BestSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< - * """Splitter for finding the best split, using the sparse data.""" - * - */ -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter { - struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_base; -}; - - -/* "stpredictions/models/OK3/_splitter.pyx":1309 - * - * - * cdef class RandomSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< - * """Splitter for finding a random split, using the sparse data.""" - * - */ -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter { - struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_base; -}; - - -/* "View.MemoryView":105 - * - * @cname("__pyx_array") - * cdef class array: # <<<<<<<<<<<<<< - * - * cdef: - */ -struct __pyx_array_obj { - PyObject_HEAD - struct __pyx_vtabstruct_array *__pyx_vtab; - char *data; - Py_ssize_t len; - char *format; - int ndim; - Py_ssize_t *_shape; - Py_ssize_t *_strides; - Py_ssize_t itemsize; - PyObject *mode; - PyObject *_format; - void (*callback_free_data)(void *); - int free_data; - int dtype_is_object; -}; - - -/* "View.MemoryView":279 - * - * @cname('__pyx_MemviewEnum') - * cdef class Enum(object): # <<<<<<<<<<<<<< - * cdef object name - * def __init__(self, name): - */ -struct __pyx_MemviewEnum_obj { - PyObject_HEAD - PyObject *name; -}; - - -/* "View.MemoryView":330 - * - * @cname('__pyx_memoryview') - * cdef class memoryview(object): # <<<<<<<<<<<<<< - * - * cdef object obj - */ -struct __pyx_memoryview_obj { - PyObject_HEAD - struct __pyx_vtabstruct_memoryview *__pyx_vtab; - PyObject *obj; - PyObject *_size; - PyObject *_array_interface; - PyThread_type_lock lock; - __pyx_atomic_int acquisition_count[2]; - __pyx_atomic_int *acquisition_count_aligned_p; - Py_buffer view; - int flags; - int dtype_is_object; - __Pyx_TypeInfo *typeinfo; -}; - - -/* "View.MemoryView":965 - * - * @cname('__pyx_memoryviewslice') - * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< - * "Internal class for passing memoryview slices to Python" - * - */ -struct __pyx_memoryviewslice_obj { - struct __pyx_memoryview_obj __pyx_base; - __Pyx_memviewslice from_slice; - PyObject *from_object; - PyObject *(*to_object_func)(char *); - int (*to_dtype_func)(char *, PyObject *); -}; - - - -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion { - int (*init)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double, double, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_Criterion; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_ClassificationCriterion; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_RegressionCriterion; - - -/* "_splitter.pxd":34 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ - -struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter { - int (*init)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); - int (*node_reset)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); - int (*node_split)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double, struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double *); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtabptr_7sklearn_4tree_9_splitter_Splitter; - - -/* "sklearn/tree/_tree.pxd":37 - * - * - * cdef class Tree: # <<<<<<<<<<<<<< - * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and - */ - -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double); - int (*_resize)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args); - PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*predict)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*apply)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*_apply_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*decision_path)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyObject *(*_decision_path_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*compute_feature_importances)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklearn_4tree_5_tree_Tree; - - -/* "sklearn/tree/_tree.pxd":85 - * # ============================================================================= - * - * cdef class TreeBuilder: # <<<<<<<<<<<<<< - * # The TreeBuilder recursively builds a Tree object from training samples, - * # using a Splitter object for splitting internal nodes and assigning - */ - -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder { - PyObject *(*build)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args); - PyObject *(*_check_input)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder; - - -/* "_criterion.pxd":12 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion { - int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion; - - -/* "_criterion.pxd":50 - * - * - * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract kernelized output regression criterion.""" - * - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; - - -/* "neighbors/_quad_tree.pxd":55 - * - * - * cdef class _QuadTree: # <<<<<<<<<<<<<< - * # The QuadTree object is a quad tree structure constructed by inserting - * # recursively points in the tree and splitting cells in 4 so that each - */ - -struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree { - int (*insert_point)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_is_duplicate)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - long (*summarize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); - void (*_init_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - void (*_init_root)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - int (*_check_point_in_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_resize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); - int (*_get_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); - PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *); -}; -static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtabptr_7sklearn_9neighbors_10_quad_tree__QuadTree; - - -/* "sklearn/tree/_utils.pxd":79 - * SIZE_t n_constant_features - * - * cdef class Stack: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t top - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7sklearn_4tree_6_utils_Stack; - - -/* "sklearn/tree/_utils.pxd":108 - * double improvement - * - * cdef class PriorityHeap: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t heap_ptr - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); - void (*heapify_up)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - void (*heapify_down)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, double, double, double); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabptr_7sklearn_4tree_6_utils_PriorityHeap; - - -/* "sklearn/tree/_utils.pxd":131 - * DOUBLE_t weight - * - * cdef class WeightedPQueue: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t array_ptr - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*peek)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedPQueue; - - -/* "sklearn/tree/_utils.pxd":151 - * # ============================================================================= - * - * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< - * cdef SIZE_t initial_capacity - * cdef WeightedPQueue samples - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*update_median_parameters_post_push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*update_median_parameters_post_remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedMedianCalculator; - - -/* "stpredictions/models/OK3/_splitter.pyx":41 - * self.improvement = -INFINITY - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * """Abstract splitter class. - * - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter { - int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); - int (*node_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); - int (*node_split)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); - void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double *); - double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *); -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_Splitter; - - -/* "stpredictions/models/OK3/_splitter.pyx":223 - * - * - * cdef class BaseDenseSplitter(Splitter): # <<<<<<<<<<<<<< - * cdef const DTYPE_t[:, :] X - * - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter { - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter __pyx_base; -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter; - - -/* "stpredictions/models/OK3/_splitter.pyx":245 - * - * - * cdef class BestSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< - * """Splitter for finding the best split.""" - * def __reduce__(self): - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSplitter { - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter __pyx_base; -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BestSplitter; - - -/* "stpredictions/models/OK3/_splitter.pyx":564 - * - * - * cdef class RandomSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< - * """Splitter for finding the best random split.""" - * def __reduce__(self): - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSplitter { - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter __pyx_base; -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_RandomSplitter; - - -/* "stpredictions/models/OK3/_splitter.pyx":761 - * - * - * cdef class BaseSparseSplitter(Splitter): # <<<<<<<<<<<<<< - * # The sparse splitter works only with csc sparse matrix format - * cdef DTYPE_t* X_data - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter { - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter __pyx_base; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_partition)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - void (*extract_nnz)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, int *); -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter; -static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, int *); - - -/* "stpredictions/models/OK3/_splitter.pyx":1080 - * - * - * cdef class BestSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< - * """Splitter for finding the best split, using the sparse data.""" - * - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter { - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_base; -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter; - - -/* "stpredictions/models/OK3/_splitter.pyx":1309 - * - * - * cdef class RandomSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< - * """Splitter for finding a random split, using the sparse data.""" - * - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter { - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_base; -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter; - - -/* "View.MemoryView":105 - * - * @cname("__pyx_array") - * cdef class array: # <<<<<<<<<<<<<< - * - * cdef: - */ - -struct __pyx_vtabstruct_array { - PyObject *(*get_memview)(struct __pyx_array_obj *); -}; -static struct __pyx_vtabstruct_array *__pyx_vtabptr_array; - - -/* "View.MemoryView":330 - * - * @cname('__pyx_memoryview') - * cdef class memoryview(object): # <<<<<<<<<<<<<< - * - * cdef object obj - */ - -struct __pyx_vtabstruct_memoryview { - char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *); - PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *); - PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); - PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *); - PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); - PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *); - PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *); -}; -static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview; - - -/* "View.MemoryView":965 - * - * @cname('__pyx_memoryviewslice') - * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< - * "Internal class for passing memoryview slices to Python" - * - */ - -struct __pyx_vtabstruct__memoryviewslice { - struct __pyx_vtabstruct_memoryview __pyx_base; 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/*proto*/ -/* ListCompAppend.proto */ -#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS -static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { - PyListObject* L = (PyListObject*) list; - Py_ssize_t len = Py_SIZE(list); - if (likely(L->allocated > len)) { - Py_INCREF(x); - PyList_SET_ITEM(list, len, x); - __Pyx_SET_SIZE(list, len + 1); - return 0; - } - return PyList_Append(list, x); -} -#else -#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) -#endif - -/* PyIntBinop.proto */ -#if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); -#else -#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ - (inplace ? 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- -/* SetupReduce.proto */ -static int __Pyx_setup_reduce(PyObject* type_obj); - -/* TypeImport.proto */ -#ifndef __PYX_HAVE_RT_ImportType_proto -#define __PYX_HAVE_RT_ImportType_proto -enum __Pyx_ImportType_CheckSize { - __Pyx_ImportType_CheckSize_Error = 0, - __Pyx_ImportType_CheckSize_Warn = 1, - __Pyx_ImportType_CheckSize_Ignore = 2 -}; -static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); -#endif - -/* GetVTable.proto */ -static void* __Pyx_GetVtable(PyObject *dict); - -/* CLineInTraceback.proto */ -#ifdef CYTHON_CLINE_IN_TRACEBACK -#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) -#else -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); -#endif - -/* CodeObjectCache.proto */ -typedef struct { - PyCodeObject* code_object; - int code_line; -} __Pyx_CodeObjectCacheEntry; -struct __Pyx_CodeObjectCache { - int count; 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- char *data; - __Pyx_Buf_DimInfo diminfo[8]; -} __Pyx_LocalBuf_ND; - -/* MemviewSliceIsContig.proto */ -static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); - -/* OverlappingSlices.proto */ -static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, - __Pyx_memviewslice *slice2, - int ndim, size_t itemsize); - -/* Capsule.proto */ -static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); - -/* GCCDiagnostics.proto */ -#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) -#define __Pyx_HAS_GCC_DIAGNOSTIC -#endif - -/* RealImag.proto */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - #define __Pyx_CREAL(z) ((z).real()) - #define __Pyx_CIMAG(z) ((z).imag()) - #else - #define __Pyx_CREAL(z) (__real__(z)) - #define __Pyx_CIMAG(z) (__imag__(z)) - #endif -#else - #define __Pyx_CREAL(z) ((z).real) - #define __Pyx_CIMAG(z) ((z).imag) -#endif -#if defined(__cplusplus) && CYTHON_CCOMPLEX\ - && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) - #define __Pyx_SET_CREAL(z,x) ((z).real(x)) - #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) -#else - #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) - #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) -#endif - -/* Arithmetic.proto */ -#if CYTHON_CCOMPLEX - #define __Pyx_c_eq_float(a, b) ((a)==(b)) - #define __Pyx_c_sum_float(a, b) ((a)+(b)) - #define __Pyx_c_diff_float(a, b) ((a)-(b)) - #define __Pyx_c_prod_float(a, b) ((a)*(b)) - #define __Pyx_c_quot_float(a, b) ((a)/(b)) - #define __Pyx_c_neg_float(a) (-(a)) - #ifdef __cplusplus - #define __Pyx_c_is_zero_float(z) ((z)==(float)0) - #define __Pyx_c_conj_float(z) (::std::conj(z)) - #if 1 - #define __Pyx_c_abs_float(z) (::std::abs(z)) - #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) - #endif - #else - #define __Pyx_c_is_zero_float(z) ((z)==0) - #define __Pyx_c_conj_float(z) (conjf(z)) - #if 1 - #define __Pyx_c_abs_float(z) (cabsf(z)) - #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) - #endif - #endif -#else - static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); - static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); - #if 1 - static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); - #endif -#endif - -/* Arithmetic.proto */ -#if CYTHON_CCOMPLEX - #define __Pyx_c_eq_double(a, b) ((a)==(b)) - #define __Pyx_c_sum_double(a, b) ((a)+(b)) - #define __Pyx_c_diff_double(a, b) ((a)-(b)) - #define __Pyx_c_prod_double(a, b) ((a)*(b)) - #define __Pyx_c_quot_double(a, b) ((a)/(b)) - #define __Pyx_c_neg_double(a) (-(a)) - #ifdef __cplusplus - #define __Pyx_c_is_zero_double(z) ((z)==(double)0) - #define __Pyx_c_conj_double(z) (::std::conj(z)) - #if 1 - #define __Pyx_c_abs_double(z) (::std::abs(z)) - #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) - #endif - #else - #define __Pyx_c_is_zero_double(z) ((z)==0) - #define __Pyx_c_conj_double(z) (conj(z)) - #if 1 - #define __Pyx_c_abs_double(z) (cabs(z)) - #define __Pyx_c_pow_double(a, b) (cpow(a, b)) - #endif - #endif -#else - static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); - static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); - #if 1 - static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); - #endif -#endif - -/* MemviewSliceCopyTemplate.proto */ -static __Pyx_memviewslice -__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, - const char *mode, int ndim, - size_t sizeof_dtype, int contig_flag, - int dtype_is_object); - -/* CIntFromPy.proto */ -static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); - -/* CIntFromPy.proto */ -static CYTHON_INLINE npy_uint32 __Pyx_PyInt_As_npy_uint32(PyObject *); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_int32(npy_int32 value); - -/* CIntFromPy.proto */ -static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *); - -/* CIntFromPy.proto */ -static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); - -/* CIntFromPy.proto */ -static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); - -/* CIntFromPy.proto */ -static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); - -/* TypeInfoCompare.proto */ -static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); - -/* MemviewSliceValidateAndInit.proto */ -static int __Pyx_ValidateAndInit_memviewslice( - int *axes_specs, - int c_or_f_flag, - int buf_flags, - int ndim, - __Pyx_TypeInfo *dtype, - __Pyx_BufFmt_StackElem stack[], - __Pyx_memviewslice *memviewslice, - PyObject *original_obj); - -/* ObjectToMemviewSlice.proto */ -static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t__const__(PyObject *, int writable_flag); - -/* CheckBinaryVersion.proto */ -static int __Pyx_check_binary_version(void); - -/* VoidPtrImport.proto */ -static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig); - -/* FunctionImport.proto */ -static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig); - -/* InitStrings.proto */ -static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); - -static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_init(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_reset(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, double *__pyx_v_weighted_n_node_samples); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_split(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED double __pyx_v_impurity, CYTHON_UNUSED struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_value(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, double *__pyx_v_dest); /* proto*/ -static double __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter_init(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_12BestSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ -static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, double __pyx_v_threshold, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_zero_pos); /* proto*/ -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_feature, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive, int *__pyx_v_is_samples_sorted); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ -static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ -static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ -static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ -static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ -static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ -static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ -static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ -static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ -static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ -static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ - -/* Module declarations from 'cpython.buffer' */ - -/* Module declarations from 'libc.string' */ - -/* Module declarations from 'libc.stdio' */ - -/* Module declarations from '__builtin__' */ - -/* Module declarations from 'cpython.type' */ -static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; - -/* Module declarations from 'cpython' */ - -/* Module declarations from 'cpython.object' */ - -/* Module declarations from 'cpython.ref' */ - -/* Module declarations from 'cpython.mem' */ - -/* Module declarations from 'numpy' */ - -/* Module declarations from 'numpy' */ -static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; -static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; -static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; -static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; -static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; -static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ - -/* Module declarations from 'sklearn.tree._criterion' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_Criterion = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_ClassificationCriterion = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_RegressionCriterion = 0; - -/* Module declarations from 'sklearn.tree._splitter' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_9_splitter_Splitter = 0; - -/* Module declarations from 'sklearn.tree._tree' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_Tree = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_TreeBuilder = 0; - -/* Module declarations from 'stpredictions.models.OK3._criterion' */ -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_Criterion = 0; -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion = 0; - -/* Module declarations from 'libc.stdlib' */ - -/* Module declarations from 'sklearn.neighbors._quad_tree' */ -static PyTypeObject *__pyx_ptype_7sklearn_9neighbors_10_quad_tree__QuadTree = 0; -static float *__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON = 0; -#define __pyx_v_7sklearn_9neighbors_10_quad_tree_EPSILON (*__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON) - -/* Module declarations from 'sklearn.tree._utils' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_Stack = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_PriorityHeap = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedPQueue = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedMedianCalculator = 0; -static __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*__pyx_f_7sklearn_4tree_6_utils_rand_int)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_UINT32_t *); /*proto*/ -static double (*__pyx_f_7sklearn_4tree_6_utils_rand_uniform)(double, double, __pyx_t_7sklearn_4tree_6_utils_UINT32_t *); /*proto*/ -static double (*__pyx_f_7sklearn_4tree_6_utils_log)(double); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DTYPE_t **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t **, size_t); /*proto*/ -static unsigned char *(*__pyx_fuse_2__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t ***, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_5_tree_Node *(*__pyx_fuse_6__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_5_tree_Node **(*__pyx_fuse_8__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node ***, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_StackRecord **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord **, size_t); /*proto*/ - -/* Module declarations from 'stpredictions.models.OK3._splitter' */ -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_Splitter = 0; -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter = 0; -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_BestSplitter = 0; -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_RandomSplitter = 0; -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter = 0; -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter = 0; -static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter = 0; -static PyTypeObject *__pyx_array_type = 0; -static PyTypeObject *__pyx_MemviewEnum_type = 0; -static PyTypeObject *__pyx_memoryview_type = 0; -static PyTypeObject *__pyx_memoryviewslice_type = 0; -static double __pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY; -static __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD; -static __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_13stpredictions_6models_3OK3_9_splitter_EXTRACT_NNZ_SWITCH; -static PyObject *generic = 0; -static PyObject *strided = 0; -static PyObject *indirect = 0; -static PyObject *contiguous = 0; -static PyObject *indirect_contiguous = 0; -static int __pyx_memoryview_thread_locks_used; -static PyThread_type_lock __pyx_memoryview_thread_locks[8]; -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split(struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_median3(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int); /*proto*/ -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_compare_SIZE_t(void const *, void const *); /*proto*/ -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t *); /*proto*/ -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_index_to_samples(__pyx_t_7sklearn_4tree_5_tree_INT32_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); /*proto*/ -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, int *); /*proto*/ -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ -static void *__pyx_align_pointer(void *, size_t); /*proto*/ -static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ -static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ -static PyObject *_unellipsify(PyObject *, int); /*proto*/ -static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ -static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ -static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ -static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ -static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ -static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ -static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ -static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ -static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ -static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ -static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ -static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ -static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ -static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ -static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ -static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ -static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ -static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ -static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ -static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ -static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ -static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ -static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ -static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ -static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ -static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ -static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ -static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t = { "DTYPE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t), { 0 }, 0, 'R', 0, 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_INT32_t = { "INT32_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_INT32_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_7sklearn_4tree_5_tree_INT32_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_7sklearn_4tree_5_tree_INT32_t), 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t__const__ = { "const DTYPE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const ), { 0 }, 0, 'R', 0, 0 }; -#define __Pyx_MODULE_NAME "stpredictions.models.OK3._splitter" -extern int __pyx_module_is_main_stpredictions__models__OK3___splitter; -int __pyx_module_is_main_stpredictions__models__OK3___splitter = 0; - -/* Implementation of 'stpredictions.models.OK3._splitter' */ -static PyObject *__pyx_builtin_range; -static PyObject *__pyx_builtin_TypeError; -static PyObject *__pyx_builtin_ValueError; -static PyObject *__pyx_builtin_ImportError; -static PyObject *__pyx_builtin_MemoryError; -static PyObject *__pyx_builtin_enumerate; -static PyObject *__pyx_builtin_Ellipsis; -static PyObject *__pyx_builtin_id; -static PyObject *__pyx_builtin_IndexError; -static const char __pyx_k_O[] = "O"; -static const char __pyx_k_c[] = "c"; -static const char __pyx_k_id[] = "id"; -static const char __pyx_k_np[] = "np"; -static const char __pyx_k_inf[] = "inf"; -static const char __pyx_k_new[] = "__new__"; -static const char __pyx_k_obj[] = "obj"; -static const char __pyx_k_base[] = "base"; -static const char __pyx_k_data[] = "data"; -static const char __pyx_k_dict[] = "__dict__"; -static const char __pyx_k_main[] = "__main__"; -static const char __pyx_k_mode[] = "mode"; -static const char __pyx_k_name[] = "name"; -static const char __pyx_k_ndim[] = "ndim"; -static const char __pyx_k_pack[] = "pack"; -static const char __pyx_k_size[] = "size"; -static const char __pyx_k_step[] = "step"; -static const char __pyx_k_stop[] = "stop"; -static const char __pyx_k_test[] = "__test__"; -static const char __pyx_k_ASCII[] = "ASCII"; -static const char __pyx_k_class[] = "__class__"; -static const char __pyx_k_error[] = "error"; -static const char __pyx_k_flags[] = "flags"; -static const char __pyx_k_numpy[] = "numpy"; -static const char __pyx_k_range[] = "range"; -static const char __pyx_k_shape[] = "shape"; -static const char __pyx_k_start[] = "start"; -static const char __pyx_k_encode[] = "encode"; -static const char __pyx_k_format[] = "format"; -static const char __pyx_k_import[] = "__import__"; -static const char __pyx_k_indptr[] = "indptr"; -static const char __pyx_k_name_2[] = "__name__"; -static const char __pyx_k_pickle[] = "pickle"; -static const char __pyx_k_reduce[] = "__reduce__"; -static const char __pyx_k_struct[] = "struct"; -static const char __pyx_k_unpack[] = "unpack"; -static const char __pyx_k_update[] = "update"; -static const char __pyx_k_fortran[] = "fortran"; -static const char __pyx_k_indices[] = "indices"; -static const char __pyx_k_memview[] = "memview"; -static const char __pyx_k_randint[] = "randint"; -static const char __pyx_k_Ellipsis[] = "Ellipsis"; -static const char __pyx_k_Splitter[] = "Splitter"; -static const char __pyx_k_getstate[] = "__getstate__"; -static const char __pyx_k_itemsize[] = "itemsize"; -static const char __pyx_k_pyx_type[] = "__pyx_type"; -static const char __pyx_k_setstate[] = "__setstate__"; -static const char __pyx_k_TypeError[] = "TypeError"; -static const char __pyx_k_criterion[] = "criterion"; -static const char __pyx_k_enumerate[] = "enumerate"; -static const char __pyx_k_pyx_state[] = "__pyx_state"; -static const char __pyx_k_reduce_ex[] = "__reduce_ex__"; -static const char __pyx_k_IndexError[] = "IndexError"; -static const char __pyx_k_ValueError[] = "ValueError"; -static const char __pyx_k_csc_matrix[] = "csc_matrix"; -static const char __pyx_k_pyx_result[] = "__pyx_result"; -static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; -static const char __pyx_k_ImportError[] = "ImportError"; -static const char __pyx_k_MemoryError[] = "MemoryError"; -static const char __pyx_k_PickleError[] = "PickleError"; -static const char __pyx_k_BestSplitter[] = "BestSplitter"; -static const char __pyx_k_max_features[] = "max_features"; -static const char __pyx_k_pyx_checksum[] = "__pyx_checksum"; -static const char __pyx_k_random_state[] = "random_state"; -static const char __pyx_k_scipy_sparse[] = "scipy.sparse"; -static const char __pyx_k_stringsource[] = "stringsource"; -static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; -static const char __pyx_k_reduce_cython[] = "__reduce_cython__"; -static const char __pyx_k_RandomSplitter[] = "RandomSplitter"; -static const char __pyx_k_View_MemoryView[] = "View.MemoryView"; -static const char __pyx_k_allocate_buffer[] = "allocate_buffer"; -static const char __pyx_k_dtype_is_object[] = "dtype_is_object"; -static const char __pyx_k_min_weight_leaf[] = "min_weight_leaf"; -static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError"; -static const char __pyx_k_setstate_cython[] = "__setstate_cython__"; -static const char __pyx_k_min_samples_leaf[] = "min_samples_leaf"; -static const char __pyx_k_BaseDenseSplitter[] = "BaseDenseSplitter"; -static const char __pyx_k_pyx_unpickle_Enum[] = "__pyx_unpickle_Enum"; -static const char __pyx_k_BaseSparseSplitter[] = "BaseSparseSplitter"; -static const char __pyx_k_BestSparseSplitter[] = "BestSparseSplitter"; -static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; -static const char __pyx_k_strided_and_direct[] = ""; -static const char __pyx_k_RandomSparseSplitter[] = "RandomSparseSplitter"; -static const char __pyx_k_strided_and_indirect[] = ""; -static const char __pyx_k_contiguous_and_direct[] = ""; -static const char __pyx_k_MemoryView_of_r_object[] = ""; -static const char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; -static const char __pyx_k_contiguous_and_indirect[] = ""; -static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; -static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; -static const char __pyx_k_X_should_be_in_csc_format[] = "X should be in csc format"; -static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; -static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; -static const char __pyx_k_strided_and_direct_or_indirect[] = ""; -static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; -static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; -static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; -static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview"; -static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview"; -static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; -static const char __pyx_k_Incompatible_checksums_s_vs_0xb0[] = "Incompatible checksums (%s vs 0xb068931 = (name))"; -static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; -static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; -static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; -static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; -static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; -static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; -static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; -static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; -static PyObject *__pyx_n_s_ASCII; -static PyObject *__pyx_n_s_BaseDenseSplitter; -static PyObject *__pyx_n_s_BaseSparseSplitter; -static PyObject *__pyx_n_s_BestSparseSplitter; -static PyObject *__pyx_n_s_BestSplitter; -static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; -static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; -static PyObject *__pyx_kp_s_Cannot_assign_to_read_only_memor; -static PyObject *__pyx_kp_s_Cannot_create_writable_memory_vi; -static PyObject *__pyx_kp_s_Cannot_index_with_type_s; -static PyObject *__pyx_n_s_Ellipsis; -static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; -static PyObject *__pyx_n_s_ImportError; -static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xb0; -static PyObject *__pyx_n_s_IndexError; -static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; -static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; -static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; -static PyObject *__pyx_n_s_MemoryError; -static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; -static PyObject *__pyx_kp_s_MemoryView_of_r_object; -static PyObject *__pyx_n_b_O; -static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; -static PyObject *__pyx_n_s_PickleError; -static PyObject *__pyx_n_s_RandomSparseSplitter; -static PyObject *__pyx_n_s_RandomSplitter; -static PyObject *__pyx_n_s_Splitter; -static PyObject *__pyx_n_s_TypeError; -static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; -static PyObject *__pyx_n_s_ValueError; -static PyObject *__pyx_n_s_View_MemoryView; -static PyObject *__pyx_kp_s_X_should_be_in_csc_format; -static PyObject *__pyx_n_s_allocate_buffer; -static PyObject *__pyx_n_s_base; -static PyObject *__pyx_n_s_c; -static PyObject *__pyx_n_u_c; -static PyObject *__pyx_n_s_class; -static PyObject *__pyx_n_s_cline_in_traceback; -static PyObject *__pyx_kp_s_contiguous_and_direct; -static PyObject *__pyx_kp_s_contiguous_and_indirect; -static PyObject *__pyx_n_s_criterion; -static PyObject *__pyx_n_s_csc_matrix; -static PyObject *__pyx_n_s_data; -static PyObject *__pyx_n_s_dict; -static PyObject *__pyx_n_s_dtype_is_object; -static PyObject *__pyx_n_s_encode; -static PyObject *__pyx_n_s_enumerate; -static PyObject *__pyx_n_s_error; -static PyObject *__pyx_n_s_flags; -static PyObject *__pyx_n_s_format; -static PyObject *__pyx_n_s_fortran; -static PyObject *__pyx_n_u_fortran; -static PyObject *__pyx_n_s_getstate; -static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; -static PyObject *__pyx_n_s_id; -static PyObject *__pyx_n_s_import; -static PyObject *__pyx_n_s_indices; -static PyObject *__pyx_n_s_indptr; -static PyObject *__pyx_n_s_inf; -static PyObject *__pyx_n_s_itemsize; -static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; -static PyObject *__pyx_n_s_main; -static PyObject *__pyx_n_s_max_features; -static PyObject *__pyx_n_s_memview; -static PyObject *__pyx_n_s_min_samples_leaf; -static PyObject *__pyx_n_s_min_weight_leaf; -static PyObject *__pyx_n_s_mode; -static PyObject *__pyx_n_s_name; -static PyObject *__pyx_n_s_name_2; -static PyObject *__pyx_n_s_ndim; -static PyObject *__pyx_n_s_new; -static PyObject *__pyx_kp_s_no_default___reduce___due_to_non; -static PyObject *__pyx_n_s_np; -static PyObject *__pyx_n_s_numpy; -static PyObject *__pyx_kp_s_numpy_core_multiarray_failed_to; -static PyObject *__pyx_kp_s_numpy_core_umath_failed_to_impor; -static PyObject *__pyx_n_s_obj; -static PyObject *__pyx_n_s_pack; -static PyObject *__pyx_n_s_pickle; -static PyObject *__pyx_n_s_pyx_PickleError; -static PyObject *__pyx_n_s_pyx_checksum; -static PyObject *__pyx_n_s_pyx_getbuffer; -static PyObject *__pyx_n_s_pyx_result; -static PyObject *__pyx_n_s_pyx_state; -static PyObject *__pyx_n_s_pyx_type; -static PyObject *__pyx_n_s_pyx_unpickle_Enum; -static PyObject *__pyx_n_s_pyx_vtable; -static PyObject *__pyx_n_s_randint; -static PyObject *__pyx_n_s_random_state; -static PyObject *__pyx_n_s_range; -static PyObject *__pyx_n_s_reduce; -static PyObject *__pyx_n_s_reduce_cython; -static PyObject *__pyx_n_s_reduce_ex; -static PyObject *__pyx_n_s_scipy_sparse; -static PyObject *__pyx_n_s_setstate; -static PyObject *__pyx_n_s_setstate_cython; -static PyObject *__pyx_n_s_shape; -static PyObject *__pyx_n_s_size; -static PyObject *__pyx_n_s_start; -static PyObject *__pyx_n_s_step; -static PyObject *__pyx_n_s_stop; -static PyObject *__pyx_kp_s_strided_and_direct; -static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; -static PyObject *__pyx_kp_s_strided_and_indirect; -static PyObject *__pyx_kp_s_stringsource; -static PyObject *__pyx_n_s_struct; -static PyObject *__pyx_n_s_test; -static PyObject *__pyx_kp_s_unable_to_allocate_array_data; -static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; -static PyObject *__pyx_n_s_unpack; -static PyObject *__pyx_n_s_update; -static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_criterion, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, PyObject *__pyx_v_random_state); /* proto */ -static void __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_4__getstate__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_6__setstate__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion___get__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_4__del__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features___get__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_16min_samples_leaf___get__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_16min_samples_leaf_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_15min_weight_leaf___get__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_15min_weight_leaf_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_8__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_10__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter___reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter_2__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_12BestSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_criterion, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, CYTHON_UNUSED double __pyx_v_min_weight_leaf, CYTHON_UNUSED PyObject *__pyx_v_random_state); /* proto */ -static void __pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_v_self); /* proto */ -static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ -static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ -static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ -static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_12__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf___pyx_array___reduce_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_array_2__setstate_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ -static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_MemviewEnum___reduce_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_MemviewEnum_2__setstate_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ -static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); 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- __pyx_v_max_features = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":272 - * cdef DTYPE_t* Xf = self.feature_values - * cdef SIZE_t max_features = self.max_features - * cdef SIZE_t min_samples_leaf = self.min_samples_leaf # <<<<<<<<<<<<<< - * cdef double min_weight_leaf = self.min_weight_leaf - * cdef UINT32_t* random_state = &self.rand_r_state - */ - __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf; - __pyx_v_min_samples_leaf = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":273 - * cdef SIZE_t max_features = self.max_features - * cdef SIZE_t min_samples_leaf = self.min_samples_leaf - * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< - * cdef UINT32_t* random_state = &self.rand_r_state - * - */ - __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf; - __pyx_v_min_weight_leaf = __pyx_t_4; - - /* "stpredictions/models/OK3/_splitter.pyx":274 - * cdef SIZE_t min_samples_leaf = self.min_samples_leaf - * cdef double min_weight_leaf = self.min_weight_leaf - * cdef UINT32_t* random_state = &self.rand_r_state # <<<<<<<<<<<<<< - * - * cdef SplitRecord best, current - */ - __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state); - - /* "stpredictions/models/OK3/_splitter.pyx":277 - * - * cdef SplitRecord best, current - * cdef double current_proxy_improvement = -INFINITY # <<<<<<<<<<<<<< - * cdef double best_proxy_improvement = -INFINITY - * - */ - __pyx_v_current_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - - /* "stpredictions/models/OK3/_splitter.pyx":278 - * cdef SplitRecord best, current - * cdef double current_proxy_improvement = -INFINITY - * cdef double best_proxy_improvement = -INFINITY # <<<<<<<<<<<<<< - * - * cdef SIZE_t f_i = n_features - */ - __pyx_v_best_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - - /* "stpredictions/models/OK3/_splitter.pyx":280 - * cdef double best_proxy_improvement = -INFINITY - * - * cdef SIZE_t f_i = n_features # <<<<<<<<<<<<<< - * cdef SIZE_t f_j - * cdef SIZE_t p - */ - __pyx_v_f_i = __pyx_v_n_features; - - /* "stpredictions/models/OK3/_splitter.pyx":288 - * cdef SIZE_t j - * - * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< - * # Number of features discovered to be constant during the split search - * cdef SIZE_t n_found_constants = 0 - */ - __pyx_v_n_visited_features = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":290 - * cdef SIZE_t n_visited_features = 0 - * # Number of features discovered to be constant during the split search - * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 - */ - __pyx_v_n_found_constants = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":292 - * cdef SIZE_t n_found_constants = 0 - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< - * cdef SIZE_t n_known_constants = n_constant_features[0] - * # n_total_constants = n_known_constants + n_found_constants - */ - __pyx_v_n_drawn_constants = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":293 - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 - * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< - * # n_total_constants = n_known_constants + n_found_constants - * cdef SIZE_t n_total_constants = n_known_constants - */ - __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); - - /* "stpredictions/models/OK3/_splitter.pyx":295 - * cdef SIZE_t n_known_constants = n_constant_features[0] - * # n_total_constants = n_known_constants + n_found_constants - * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< - * cdef DTYPE_t current_feature_value - * cdef SIZE_t partition_end - */ - __pyx_v_n_total_constants = __pyx_v_n_known_constants; - - /* "stpredictions/models/OK3/_splitter.pyx":299 - * cdef SIZE_t partition_end - * - * _init_split(&best, end) # <<<<<<<<<<<<<< - * - * # Sample up to max_features without replacement using a - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); - - /* "stpredictions/models/OK3/_splitter.pyx":310 - * # newly discovered constant features to spare computation on descendant - * # nodes. - * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< - * # are constant - * (n_visited_features < max_features or - */ - while (1) { - __pyx_t_6 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0); - if (__pyx_t_6) { - } else { - __pyx_t_5 = __pyx_t_6; - goto __pyx_L5_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":312 - * while (f_i > n_total_constants and # Stop early if remaining features - * # are constant - * (n_visited_features < max_features or # <<<<<<<<<<<<<< - * # At least one drawn features must be non constant - * n_visited_features <= n_found_constants + n_drawn_constants)): - */ - __pyx_t_6 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0); - if (!__pyx_t_6) { - } else { - __pyx_t_5 = __pyx_t_6; - goto __pyx_L5_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":314 - * (n_visited_features < max_features or - * # At least one drawn features must be non constant - * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< - * - * n_visited_features += 1 - */ - __pyx_t_6 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0); - __pyx_t_5 = __pyx_t_6; - __pyx_L5_bool_binop_done:; - if (!__pyx_t_5) break; - - /* "stpredictions/models/OK3/_splitter.pyx":316 - * n_visited_features <= n_found_constants + n_drawn_constants)): - * - * n_visited_features += 1 # <<<<<<<<<<<<<< - * - * # Loop invariant: elements of features in - */ - __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":330 - * - * # Draw a feature at random - * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< - * random_state) - * - */ - __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); - - /* "stpredictions/models/OK3/_splitter.pyx":333 - * random_state) - * - * if f_j < n_known_constants: # <<<<<<<<<<<<<< - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] - */ - __pyx_t_5 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":335 - * if f_j < n_known_constants: - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] # <<<<<<<<<<<<<< - * - * n_drawn_constants += 1 - */ - __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); - __pyx_t_7 = (__pyx_v_features[__pyx_v_n_drawn_constants]); - (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_2; - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; - - /* "stpredictions/models/OK3/_splitter.pyx":337 - * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] - * - * n_drawn_constants += 1 # <<<<<<<<<<<<<< - * - * else: - */ - __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":333 - * random_state) - * - * if f_j < n_known_constants: # <<<<<<<<<<<<<< - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] - */ - goto __pyx_L8; - } - - /* "stpredictions/models/OK3/_splitter.pyx":341 - * else: - * # f_j in the interval [n_known_constants, f_i - n_found_constants[ - * f_j += n_found_constants # <<<<<<<<<<<<<< - * # f_j in the interval [n_total_constants, f_i[ - * current.feature = features[f_j] - */ - /*else*/ { - __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); - - /* "stpredictions/models/OK3/_splitter.pyx":343 - * f_j += n_found_constants - * # f_j in the interval [n_total_constants, f_i[ - * current.feature = features[f_j] # <<<<<<<<<<<<<< - * - * # Sort samples along that feature; by - */ - __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); - - /* "stpredictions/models/OK3/_splitter.pyx":349 - * # sorting the array in a manner which utilizes the cache more - * # effectively. - * for i in range(start, end): # <<<<<<<<<<<<<< - * Xf[i] = self.X[samples[i], current.feature] - * - */ - __pyx_t_7 = __pyx_v_end; - __pyx_t_2 = __pyx_t_7; - for (__pyx_t_8 = __pyx_v_start; __pyx_t_8 < __pyx_t_2; __pyx_t_8+=1) { - __pyx_v_i = __pyx_t_8; - - /* "stpredictions/models/OK3/_splitter.pyx":350 - * # effectively. - * for i in range(start, end): - * Xf[i] = self.X[samples[i], current.feature] # <<<<<<<<<<<<<< - * - * sort(Xf + start, samples + start, end - start) - */ - if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 350, __pyx_L1_error)} - __pyx_t_9 = (__pyx_v_samples[__pyx_v_i]); - __pyx_t_10 = __pyx_v_current.feature; - (__pyx_v_Xf[__pyx_v_i]) = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_10 * __pyx_v_self->__pyx_base.X.strides[1]) ))); - } - - /* "stpredictions/models/OK3/_splitter.pyx":352 - * Xf[i] = self.X[samples[i], current.feature] - * - * sort(Xf + start, samples + start, end - start) # <<<<<<<<<<<<<< - * - * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end - __pyx_v_start)); - - /* "stpredictions/models/OK3/_splitter.pyx":354 - * sort(Xf + start, samples + start, end - start) - * - * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< - * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] - * - */ - __pyx_t_5 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":355 - * - * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: - * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] # <<<<<<<<<<<<<< - * - * n_found_constants += 1 - */ - __pyx_t_7 = (__pyx_v_features[__pyx_v_n_total_constants]); - __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; - (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":357 - * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] - * - * n_found_constants += 1 # <<<<<<<<<<<<<< - * n_total_constants += 1 - * - */ - __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":358 - * - * n_found_constants += 1 - * n_total_constants += 1 # <<<<<<<<<<<<<< - * - * else: - */ - __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":354 - * sort(Xf + start, samples + start, end - start) - * - * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< - * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] - * - */ - goto __pyx_L11; - } - - /* "stpredictions/models/OK3/_splitter.pyx":361 - * - * else: - * f_i -= 1 # <<<<<<<<<<<<<< - * features[f_i], features[f_j] = features[f_j], features[f_i] - * - */ - /*else*/ { - __pyx_v_f_i = (__pyx_v_f_i - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":362 - * else: - * f_i -= 1 - * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< - * - * # Evaluate all splits - */ - __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); - __pyx_t_7 = (__pyx_v_features[__pyx_v_f_i]); - (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2; - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; - - /* "stpredictions/models/OK3/_splitter.pyx":365 - * - * # Evaluate all splits - * self.criterion.reset() # <<<<<<<<<<<<<< - * p = start - * - */ - __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 365, __pyx_L1_error) - - /* "stpredictions/models/OK3/_splitter.pyx":366 - * # Evaluate all splits - * self.criterion.reset() - * p = start # <<<<<<<<<<<<<< - * - * while p < end: - */ - __pyx_v_p = __pyx_v_start; - - /* "stpredictions/models/OK3/_splitter.pyx":368 - * p = start - * - * while p < end: # <<<<<<<<<<<<<< - * while (p + 1 < end and - * Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): - */ - while (1) { - __pyx_t_5 = ((__pyx_v_p < __pyx_v_end) != 0); - if (!__pyx_t_5) break; - - /* "stpredictions/models/OK3/_splitter.pyx":369 - * - * while p < end: - * while (p + 1 < end and # <<<<<<<<<<<<<< - * Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): - * p += 1 - */ - while (1) { - __pyx_t_6 = (((__pyx_v_p + 1) < __pyx_v_end) != 0); - if (__pyx_t_6) { - } else { - __pyx_t_5 = __pyx_t_6; - goto __pyx_L16_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":370 - * while p < end: - * while (p + 1 < end and - * Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): # <<<<<<<<<<<<<< - * p += 1 - * - */ - __pyx_t_6 = (((__pyx_v_Xf[(__pyx_v_p + 1)]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); - __pyx_t_5 = __pyx_t_6; - __pyx_L16_bool_binop_done:; - if (!__pyx_t_5) break; - - /* "stpredictions/models/OK3/_splitter.pyx":371 - * while (p + 1 < end and - * Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): - * p += 1 # <<<<<<<<<<<<<< - * - * # (p + 1 >= end) or (X[samples[p + 1], current.feature] > - */ - __pyx_v_p = (__pyx_v_p + 1); - } - - /* "stpredictions/models/OK3/_splitter.pyx":375 - * # (p + 1 >= end) or (X[samples[p + 1], current.feature] > - * # X[samples[p], current.feature]) - * p += 1 # <<<<<<<<<<<<<< - * # (p >= end) or (X[samples[p], current.feature] > - * # X[samples[p - 1], current.feature]) - */ - __pyx_v_p = (__pyx_v_p + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":379 - * # X[samples[p - 1], current.feature]) - * - * if p < end: # <<<<<<<<<<<<<< - * current.pos = p - * - */ - __pyx_t_5 = ((__pyx_v_p < __pyx_v_end) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":380 - * - * if p < end: - * current.pos = p # <<<<<<<<<<<<<< - * - * # Reject if min_samples_leaf is not guaranteed - */ - __pyx_v_current.pos = __pyx_v_p; - - /* "stpredictions/models/OK3/_splitter.pyx":383 - * - * # Reject if min_samples_leaf is not guaranteed - * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< - * ((end - current.pos) < min_samples_leaf)): - * continue - */ - __pyx_t_6 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0); - if (!__pyx_t_6) { - } else { - __pyx_t_5 = __pyx_t_6; - goto __pyx_L20_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":384 - * # Reject if min_samples_leaf is not guaranteed - * if (((current.pos - start) < min_samples_leaf) or - * ((end - current.pos) < min_samples_leaf)): # <<<<<<<<<<<<<< - * continue - * - */ - __pyx_t_6 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0); - __pyx_t_5 = __pyx_t_6; - __pyx_L20_bool_binop_done:; - - /* "stpredictions/models/OK3/_splitter.pyx":383 - * - * # Reject if min_samples_leaf is not guaranteed - * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< - * ((end - current.pos) < min_samples_leaf)): - * continue - */ - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":385 - * if (((current.pos - start) < min_samples_leaf) or - * ((end - current.pos) < min_samples_leaf)): - * continue # <<<<<<<<<<<<<< - * - * self.criterion.update(current.pos) - */ - goto __pyx_L12_continue; - - /* "stpredictions/models/OK3/_splitter.pyx":383 - * - * # Reject if min_samples_leaf is not guaranteed - * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< - * ((end - current.pos) < min_samples_leaf)): - * continue - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":387 - * continue - * - * self.criterion.update(current.pos) # <<<<<<<<<<<<<< - * - * # Reject if min_weight_leaf is not satisfied - */ - __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 387, __pyx_L1_error) - - /* "stpredictions/models/OK3/_splitter.pyx":390 - * - * # Reject if min_weight_leaf is not satisfied - * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< - * (self.criterion.weighted_n_right < min_weight_leaf)): - * continue - */ - __pyx_t_6 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_left < __pyx_v_min_weight_leaf) != 0); - if (!__pyx_t_6) { - } else { - __pyx_t_5 = __pyx_t_6; - goto __pyx_L23_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":391 - * # Reject if min_weight_leaf is not satisfied - * if ((self.criterion.weighted_n_left < min_weight_leaf) or - * (self.criterion.weighted_n_right < min_weight_leaf)): # <<<<<<<<<<<<<< - * continue - * - */ - __pyx_t_6 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_right < __pyx_v_min_weight_leaf) != 0); - __pyx_t_5 = __pyx_t_6; - __pyx_L23_bool_binop_done:; - - /* "stpredictions/models/OK3/_splitter.pyx":390 - * - * # Reject if min_weight_leaf is not satisfied - * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< - * (self.criterion.weighted_n_right < min_weight_leaf)): - * continue - */ - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":392 - * if ((self.criterion.weighted_n_left < min_weight_leaf) or - * (self.criterion.weighted_n_right < min_weight_leaf)): - * continue # <<<<<<<<<<<<<< - * - * current_proxy_improvement = self.criterion.proxy_impurity_improvement() - */ - goto __pyx_L12_continue; - - /* "stpredictions/models/OK3/_splitter.pyx":390 - * - * # Reject if min_weight_leaf is not satisfied - * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< - * (self.criterion.weighted_n_right < min_weight_leaf)): - * continue - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":394 - * continue - * - * current_proxy_improvement = self.criterion.proxy_impurity_improvement() # <<<<<<<<<<<<<< - * - * # with gil: - */ - __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); - - /* "stpredictions/models/OK3/_splitter.pyx":402 - * # print() - * - * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< - * best_proxy_improvement = current_proxy_improvement - * # sum of halves is used to avoid infinite value - */ - __pyx_t_5 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":403 - * - * if current_proxy_improvement > best_proxy_improvement: - * best_proxy_improvement = current_proxy_improvement # <<<<<<<<<<<<<< - * # sum of halves is used to avoid infinite value - * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 - */ - __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement; - - /* "stpredictions/models/OK3/_splitter.pyx":405 - * best_proxy_improvement = current_proxy_improvement - * # sum of halves is used to avoid infinite value - * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 # <<<<<<<<<<<<<< - * - * if ((current.threshold == Xf[p]) or - */ - __pyx_v_current.threshold = (((__pyx_v_Xf[(__pyx_v_p - 1)]) / 2.0) + ((__pyx_v_Xf[__pyx_v_p]) / 2.0)); - - /* "stpredictions/models/OK3/_splitter.pyx":407 - * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 - * - * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< - * (current.threshold == INFINITY) or - * (current.threshold == -INFINITY)): - */ - __pyx_t_6 = ((__pyx_v_current.threshold == (__pyx_v_Xf[__pyx_v_p])) != 0); - if (!__pyx_t_6) { - } else { - __pyx_t_5 = __pyx_t_6; - goto __pyx_L27_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":408 - * - * if ((current.threshold == Xf[p]) or - * (current.threshold == INFINITY) or # <<<<<<<<<<<<<< - * (current.threshold == -INFINITY)): - * current.threshold = Xf[p - 1] - */ - __pyx_t_6 = ((__pyx_v_current.threshold == __pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY) != 0); - if (!__pyx_t_6) { - } else { - __pyx_t_5 = __pyx_t_6; - goto __pyx_L27_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":409 - * if ((current.threshold == Xf[p]) or - * (current.threshold == INFINITY) or - * (current.threshold == -INFINITY)): # <<<<<<<<<<<<<< - * current.threshold = Xf[p - 1] - * - */ - __pyx_t_6 = ((__pyx_v_current.threshold == (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY)) != 0); - __pyx_t_5 = __pyx_t_6; - __pyx_L27_bool_binop_done:; - - /* "stpredictions/models/OK3/_splitter.pyx":407 - * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 - * - * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< - * (current.threshold == INFINITY) or - * (current.threshold == -INFINITY)): - */ - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":410 - * (current.threshold == INFINITY) or - * (current.threshold == -INFINITY)): - * current.threshold = Xf[p - 1] # <<<<<<<<<<<<<< - * - * best = current # copy - */ - __pyx_v_current.threshold = (__pyx_v_Xf[(__pyx_v_p - 1)]); - - /* "stpredictions/models/OK3/_splitter.pyx":407 - * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 - * - * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< - * (current.threshold == INFINITY) or - * (current.threshold == -INFINITY)): - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":412 - * current.threshold = Xf[p - 1] - * - * best = current # copy # <<<<<<<<<<<<<< - * - * # Reorganize into samples[start:best.pos] + samples[best.pos:end] - */ - __pyx_v_best = __pyx_v_current; - - /* "stpredictions/models/OK3/_splitter.pyx":402 - * # print() - * - * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< - * best_proxy_improvement = current_proxy_improvement - * # sum of halves is used to avoid infinite value - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":379 - * # X[samples[p - 1], current.feature]) - * - * if p < end: # <<<<<<<<<<<<<< - * current.pos = p - * - */ - } - __pyx_L12_continue:; - } - } - __pyx_L11:; - } - __pyx_L8:; - } - - /* "stpredictions/models/OK3/_splitter.pyx":415 - * - * # Reorganize into samples[start:best.pos] + samples[best.pos:end] - * if best.pos < end: # <<<<<<<<<<<<<< - * partition_end = end - * p = start - */ - __pyx_t_5 = ((__pyx_v_best.pos < __pyx_v_end) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":416 - * # Reorganize into samples[start:best.pos] + samples[best.pos:end] - * if best.pos < end: - * partition_end = end # <<<<<<<<<<<<<< - * p = start - * - */ - __pyx_v_partition_end = __pyx_v_end; - - /* "stpredictions/models/OK3/_splitter.pyx":417 - * if best.pos < end: - * partition_end = end - * p = start # <<<<<<<<<<<<<< - * - * while p < partition_end: - */ - __pyx_v_p = __pyx_v_start; - - /* "stpredictions/models/OK3/_splitter.pyx":419 - * p = start - * - * while p < partition_end: # <<<<<<<<<<<<<< - * if self.X[samples[p], best.feature] <= best.threshold: - * p += 1 - */ - while (1) { - __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0); - if (!__pyx_t_5) break; - - /* "stpredictions/models/OK3/_splitter.pyx":420 - * - * while p < partition_end: - * if self.X[samples[p], best.feature] <= best.threshold: # <<<<<<<<<<<<<< - * p += 1 - * - */ - if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 420, __pyx_L1_error)} - __pyx_t_10 = (__pyx_v_samples[__pyx_v_p]); - __pyx_t_9 = __pyx_v_best.feature; - __pyx_t_5 = (((*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_10 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))) <= __pyx_v_best.threshold) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":421 - * while p < partition_end: - * if self.X[samples[p], best.feature] <= best.threshold: - * p += 1 # <<<<<<<<<<<<<< - * - * else: - */ - __pyx_v_p = (__pyx_v_p + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":420 - * - * while p < partition_end: - * if self.X[samples[p], best.feature] <= best.threshold: # <<<<<<<<<<<<<< - * p += 1 - * - */ - goto __pyx_L33; - } - - /* "stpredictions/models/OK3/_splitter.pyx":424 - * - * else: - * partition_end -= 1 # <<<<<<<<<<<<<< - * - * samples[p], samples[partition_end] = samples[partition_end], samples[p] - */ - /*else*/ { - __pyx_v_partition_end = (__pyx_v_partition_end - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":426 - * partition_end -= 1 - * - * samples[p], samples[partition_end] = samples[partition_end], samples[p] # <<<<<<<<<<<<<< - * - * self.criterion.reset() - */ - __pyx_t_7 = (__pyx_v_samples[__pyx_v_partition_end]); - __pyx_t_2 = (__pyx_v_samples[__pyx_v_p]); - (__pyx_v_samples[__pyx_v_p]) = __pyx_t_7; - (__pyx_v_samples[__pyx_v_partition_end]) = __pyx_t_2; - } - __pyx_L33:; - } - - /* "stpredictions/models/OK3/_splitter.pyx":428 - * samples[p], samples[partition_end] = samples[partition_end], samples[p] - * - * self.criterion.reset() # <<<<<<<<<<<<<< - * self.criterion.update(best.pos) - * best.improvement = self.criterion.impurity_improvement(impurity) - */ - __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 428, __pyx_L1_error) - - /* "stpredictions/models/OK3/_splitter.pyx":429 - * - * self.criterion.reset() - * self.criterion.update(best.pos) # <<<<<<<<<<<<<< - * best.improvement = self.criterion.impurity_improvement(impurity) - * self.criterion.children_impurity(&best.impurity_left, - */ - __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 429, __pyx_L1_error) - - /* "stpredictions/models/OK3/_splitter.pyx":430 - * self.criterion.reset() - * self.criterion.update(best.pos) - * best.improvement = self.criterion.impurity_improvement(impurity) # <<<<<<<<<<<<<< - * self.criterion.children_impurity(&best.impurity_left, - * &best.impurity_right) - */ - __pyx_v_best.improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); - - /* "stpredictions/models/OK3/_splitter.pyx":431 - * self.criterion.update(best.pos) - * best.improvement = self.criterion.impurity_improvement(impurity) - * self.criterion.children_impurity(&best.impurity_left, # <<<<<<<<<<<<<< - * &best.impurity_right) - * - */ - ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); - - /* "stpredictions/models/OK3/_splitter.pyx":415 - * - * # Reorganize into samples[start:best.pos] + samples[best.pos:end] - * if best.pos < end: # <<<<<<<<<<<<<< - * partition_end = end - * p = start - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":437 - * # element in features[:n_known_constants] must be preserved for sibling - * # and child nodes - * memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) # <<<<<<<<<<<<<< - * - * # Copy newly found constant features - */ - (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants))); - - /* "stpredictions/models/OK3/_splitter.pyx":440 - * - * # Copy newly found constant features - * memcpy(constant_features + n_known_constants, # <<<<<<<<<<<<<< - * features + n_known_constants, - * sizeof(SIZE_t) * n_found_constants) - */ - (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants))); - - /* "stpredictions/models/OK3/_splitter.pyx":445 - * - * # Return values - * split[0] = best # <<<<<<<<<<<<<< - * n_constant_features[0] = n_total_constants - * return 0 - */ - (__pyx_v_split[0]) = __pyx_v_best; - - /* "stpredictions/models/OK3/_splitter.pyx":446 - * # Return values - * split[0] = best - * n_constant_features[0] = n_total_constants # <<<<<<<<<<<<<< - * return 0 - * - */ - (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants; - - /* "stpredictions/models/OK3/_splitter.pyx":447 - * split[0] = best - * n_constant_features[0] = n_total_constants - * return 0 # <<<<<<<<<<<<<< - * - * - */ - __pyx_r = 0; - goto __pyx_L0; - - /* "stpredictions/models/OK3/_splitter.pyx":254 - * self.random_state), self.__getstate__()) - * - * cdef int node_split(self, double impurity, SplitRecord* split, # <<<<<<<<<<<<<< - * SIZE_t* n_constant_features) nogil except -1: - * """Find the best split on node samples[start:end] - */ - - /* function exit code */ - __pyx_L1_error:; - { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); - #endif - __Pyx_AddTraceback("stpredictions.models.OK3._splitter.BestSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename); - #ifdef WITH_THREAD - __Pyx_PyGILState_Release(__pyx_gilstate_save); - #endif - } - __pyx_r = -1; - __pyx_L0:; - return __pyx_r; -} - -/* "stpredictions/models/OK3/_splitter.pyx":452 - * # Sort n-element arrays pointed to by Xf and samples, simultaneously, - * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). - * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: # <<<<<<<<<<<<<< - * if n == 0: - * return - */ - -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) { - int __pyx_v_maxd; - int __pyx_t_1; - - /* "stpredictions/models/OK3/_splitter.pyx":453 - * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). - * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: - * if n == 0: # <<<<<<<<<<<<<< - * return - * cdef int maxd = 2 * log(n) - */ - __pyx_t_1 = ((__pyx_v_n == 0) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":454 - * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: - * if n == 0: - * return # <<<<<<<<<<<<<< - * cdef int maxd = 2 * log(n) - * introsort(Xf, samples, n, maxd) - */ - goto __pyx_L0; - - /* "stpredictions/models/OK3/_splitter.pyx":453 - * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). - * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: - * if n == 0: # <<<<<<<<<<<<<< - * return - * cdef int maxd = 2 * log(n) - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":455 - * if n == 0: - * return - * cdef int maxd = 2 * log(n) # <<<<<<<<<<<<<< - * introsort(Xf, samples, n, maxd) - * - */ - __pyx_v_maxd = (2 * ((int)__pyx_f_7sklearn_4tree_6_utils_log(__pyx_v_n))); - - /* "stpredictions/models/OK3/_splitter.pyx":456 - * return - * cdef int maxd = 2 * log(n) - * introsort(Xf, samples, n, maxd) # <<<<<<<<<<<<<< - * - * - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n, __pyx_v_maxd); - - /* "stpredictions/models/OK3/_splitter.pyx":452 - * # Sort n-element arrays pointed to by Xf and samples, simultaneously, - * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). - * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: # <<<<<<<<<<<<<< - * if n == 0: - * return - */ - - /* function exit code */ - __pyx_L0:; -} - -/* "stpredictions/models/OK3/_splitter.pyx":459 - * - * - * cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< - * SIZE_t i, SIZE_t j) nogil: - * # Helper for sort - */ - -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j) { - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_3; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4; - - /* "stpredictions/models/OK3/_splitter.pyx":462 - * SIZE_t i, SIZE_t j) nogil: - * # Helper for sort - * Xf[i], Xf[j] = Xf[j], Xf[i] # <<<<<<<<<<<<<< - * samples[i], samples[j] = samples[j], samples[i] - * - */ - __pyx_t_1 = (__pyx_v_Xf[__pyx_v_j]); - __pyx_t_2 = (__pyx_v_Xf[__pyx_v_i]); - (__pyx_v_Xf[__pyx_v_i]) = __pyx_t_1; - (__pyx_v_Xf[__pyx_v_j]) = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":463 - * # Helper for sort - * Xf[i], Xf[j] = Xf[j], Xf[i] - * samples[i], samples[j] = samples[j], samples[i] # <<<<<<<<<<<<<< - * - * - */ - __pyx_t_3 = (__pyx_v_samples[__pyx_v_j]); - __pyx_t_4 = (__pyx_v_samples[__pyx_v_i]); - (__pyx_v_samples[__pyx_v_i]) = __pyx_t_3; - (__pyx_v_samples[__pyx_v_j]) = __pyx_t_4; - - /* "stpredictions/models/OK3/_splitter.pyx":459 - * - * - * cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< - * SIZE_t i, SIZE_t j) nogil: - * # Helper for sort - */ - - /* function exit code */ -} - -/* "stpredictions/models/OK3/_splitter.pyx":466 - * - * - * cdef inline DTYPE_t median3(DTYPE_t* Xf, SIZE_t n) nogil: # <<<<<<<<<<<<<< - * # Median of three pivot selection, after Bentley and McIlroy (1993). - * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. - */ - -static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_median3(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) { - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_a; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_b; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_c; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_r; - int __pyx_t_1; - - /* "stpredictions/models/OK3/_splitter.pyx":469 - * # Median of three pivot selection, after Bentley and McIlroy (1993). - * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. - * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] # <<<<<<<<<<<<<< - * if a < b: - * if b < c: - */ - __pyx_v_a = (__pyx_v_Xf[0]); - __pyx_v_b = (__pyx_v_Xf[(__pyx_v_n / 2)]); - __pyx_v_c = (__pyx_v_Xf[(__pyx_v_n - 1)]); - - /* "stpredictions/models/OK3/_splitter.pyx":470 - * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. - * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] - * if a < b: # <<<<<<<<<<<<<< - * if b < c: - * return b - */ - __pyx_t_1 = ((__pyx_v_a < __pyx_v_b) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":471 - * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] - * if a < b: - * if b < c: # <<<<<<<<<<<<<< - * return b - * elif a < c: - */ - __pyx_t_1 = ((__pyx_v_b < __pyx_v_c) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":472 - * if a < b: - * if b < c: - * return b # <<<<<<<<<<<<<< - * elif a < c: - * return c - */ - __pyx_r = __pyx_v_b; - goto __pyx_L0; - - /* "stpredictions/models/OK3/_splitter.pyx":471 - * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] - * if a < b: - * if b < c: # <<<<<<<<<<<<<< - * return b - * elif a < c: - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":473 - * if b < c: - * return b - * elif a < c: # <<<<<<<<<<<<<< - * return c - * else: - */ - __pyx_t_1 = ((__pyx_v_a < __pyx_v_c) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":474 - * return b - * elif a < c: - * return c # <<<<<<<<<<<<<< - * else: - * return a - */ - __pyx_r = __pyx_v_c; - goto __pyx_L0; - - /* "stpredictions/models/OK3/_splitter.pyx":473 - * if b < c: - * return b - * elif a < c: # <<<<<<<<<<<<<< - * return c - * else: - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":476 - * return c - * else: - * return a # <<<<<<<<<<<<<< - * elif b < c: - * if a < c: - */ - /*else*/ { - __pyx_r = __pyx_v_a; - goto __pyx_L0; - } - - /* "stpredictions/models/OK3/_splitter.pyx":470 - * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. - * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] - * if a < b: # <<<<<<<<<<<<<< - * if b < c: - * return b - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":477 - * else: - * return a - * elif b < c: # <<<<<<<<<<<<<< - * if a < c: - * return a - */ - __pyx_t_1 = ((__pyx_v_b < __pyx_v_c) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":478 - * return a - * elif b < c: - * if a < c: # <<<<<<<<<<<<<< - * return a - * else: - */ - __pyx_t_1 = ((__pyx_v_a < __pyx_v_c) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":479 - * elif b < c: - * if a < c: - * return a # <<<<<<<<<<<<<< - * else: - * return c - */ - __pyx_r = __pyx_v_a; - goto __pyx_L0; - - /* "stpredictions/models/OK3/_splitter.pyx":478 - * return a - * elif b < c: - * if a < c: # <<<<<<<<<<<<<< - * return a - * else: - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":481 - * return a - * else: - * return c # <<<<<<<<<<<<<< - * else: - * return b - */ - /*else*/ { - __pyx_r = __pyx_v_c; - goto __pyx_L0; - } - - /* "stpredictions/models/OK3/_splitter.pyx":477 - * else: - * return a - * elif b < c: # <<<<<<<<<<<<<< - * if a < c: - * return a - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":483 - * return c - * else: - * return b # <<<<<<<<<<<<<< - * - * - */ - /*else*/ { - __pyx_r = __pyx_v_b; - goto __pyx_L0; - } - - /* "stpredictions/models/OK3/_splitter.pyx":466 - * - * - * cdef inline DTYPE_t median3(DTYPE_t* Xf, SIZE_t n) nogil: # <<<<<<<<<<<<<< - * # Median of three pivot selection, after Bentley and McIlroy (1993). - * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. - */ - - /* function exit code */ - __pyx_L0:; - return __pyx_r; -} - -/* "stpredictions/models/OK3/_splitter.pyx":488 - * # Introsort with median of 3 pivot selection and 3-way partition function - * # (robust to repeated elements, e.g. lots of zero features). - * cdef void introsort(DTYPE_t* Xf, SIZE_t *samples, # <<<<<<<<<<<<<< - * SIZE_t n, int maxd) nogil: - * cdef DTYPE_t pivot - */ - -static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n, int __pyx_v_maxd) { - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_pivot; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_l; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_r; - int __pyx_t_1; - - /* "stpredictions/models/OK3/_splitter.pyx":493 - * cdef SIZE_t i, l, r - * - * while n > 1: # <<<<<<<<<<<<<< - * if maxd <= 0: # max depth limit exceeded ("gone quadratic") - * heapsort(Xf, samples, n) - */ - while (1) { - __pyx_t_1 = ((__pyx_v_n > 1) != 0); - if (!__pyx_t_1) break; - - /* "stpredictions/models/OK3/_splitter.pyx":494 - * - * while n > 1: - * if maxd <= 0: # max depth limit exceeded ("gone quadratic") # <<<<<<<<<<<<<< - * heapsort(Xf, samples, n) - * return - */ - __pyx_t_1 = ((__pyx_v_maxd <= 0) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":495 - * while n > 1: - * if maxd <= 0: # max depth limit exceeded ("gone quadratic") - * heapsort(Xf, samples, n) # <<<<<<<<<<<<<< - * return - * maxd -= 1 - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_heapsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n); - - /* "stpredictions/models/OK3/_splitter.pyx":496 - * if maxd <= 0: # max depth limit exceeded ("gone quadratic") - * heapsort(Xf, samples, n) - * return # <<<<<<<<<<<<<< - * maxd -= 1 - * - */ - goto __pyx_L0; - - /* "stpredictions/models/OK3/_splitter.pyx":494 - * - * while n > 1: - * if maxd <= 0: # max depth limit exceeded ("gone quadratic") # <<<<<<<<<<<<<< - * heapsort(Xf, samples, n) - * return - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":497 - * heapsort(Xf, samples, n) - * return - * maxd -= 1 # <<<<<<<<<<<<<< - * - * pivot = median3(Xf, n) - */ - __pyx_v_maxd = (__pyx_v_maxd - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":499 - * maxd -= 1 - * - * pivot = median3(Xf, n) # <<<<<<<<<<<<<< - * - * # Three-way partition. - */ - __pyx_v_pivot = __pyx_f_13stpredictions_6models_3OK3_9_splitter_median3(__pyx_v_Xf, __pyx_v_n); - - /* "stpredictions/models/OK3/_splitter.pyx":502 - * - * # Three-way partition. - * i = l = 0 # <<<<<<<<<<<<<< - * r = n - * while i < r: - */ - __pyx_v_i = 0; - __pyx_v_l = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":503 - * # Three-way partition. - * i = l = 0 - * r = n # <<<<<<<<<<<<<< - * while i < r: - * if Xf[i] < pivot: - */ - __pyx_v_r = __pyx_v_n; - - /* "stpredictions/models/OK3/_splitter.pyx":504 - * i = l = 0 - * r = n - * while i < r: # <<<<<<<<<<<<<< - * if Xf[i] < pivot: - * swap(Xf, samples, i, l) - */ - while (1) { - __pyx_t_1 = ((__pyx_v_i < __pyx_v_r) != 0); - if (!__pyx_t_1) break; - - /* "stpredictions/models/OK3/_splitter.pyx":505 - * r = n - * while i < r: - * if Xf[i] < pivot: # <<<<<<<<<<<<<< - * swap(Xf, samples, i, l) - * i += 1 - */ - __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_i]) < __pyx_v_pivot) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":506 - * while i < r: - * if Xf[i] < pivot: - * swap(Xf, samples, i, l) # <<<<<<<<<<<<<< - * i += 1 - * l += 1 - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_l); - - /* "stpredictions/models/OK3/_splitter.pyx":507 - * if Xf[i] < pivot: - * swap(Xf, samples, i, l) - * i += 1 # <<<<<<<<<<<<<< - * l += 1 - * elif Xf[i] > pivot: - */ - __pyx_v_i = (__pyx_v_i + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":508 - * swap(Xf, samples, i, l) - * i += 1 - * l += 1 # <<<<<<<<<<<<<< - * elif Xf[i] > pivot: - * r -= 1 - */ - __pyx_v_l = (__pyx_v_l + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":505 - * r = n - * while i < r: - * if Xf[i] < pivot: # <<<<<<<<<<<<<< - * swap(Xf, samples, i, l) - * i += 1 - */ - goto __pyx_L8; - } - - /* "stpredictions/models/OK3/_splitter.pyx":509 - * i += 1 - * l += 1 - * elif Xf[i] > pivot: # <<<<<<<<<<<<<< - * r -= 1 - * swap(Xf, samples, i, r) - */ - __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_i]) > __pyx_v_pivot) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":510 - * l += 1 - * elif Xf[i] > pivot: - * r -= 1 # <<<<<<<<<<<<<< - * swap(Xf, samples, i, r) - * else: - */ - __pyx_v_r = (__pyx_v_r - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":511 - * elif Xf[i] > pivot: - * r -= 1 - * swap(Xf, samples, i, r) # <<<<<<<<<<<<<< - * else: - * i += 1 - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_r); - - /* "stpredictions/models/OK3/_splitter.pyx":509 - * i += 1 - * l += 1 - * elif Xf[i] > pivot: # <<<<<<<<<<<<<< - * r -= 1 - * swap(Xf, samples, i, r) - */ - goto __pyx_L8; - } - - /* "stpredictions/models/OK3/_splitter.pyx":513 - * swap(Xf, samples, i, r) - * else: - * i += 1 # <<<<<<<<<<<<<< - * - * introsort(Xf, samples, l, maxd) - */ - /*else*/ { - __pyx_v_i = (__pyx_v_i + 1); - } - __pyx_L8:; - } - - /* "stpredictions/models/OK3/_splitter.pyx":515 - * i += 1 - * - * introsort(Xf, samples, l, maxd) # <<<<<<<<<<<<<< - * Xf += r - * samples += r - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_l, __pyx_v_maxd); - - /* "stpredictions/models/OK3/_splitter.pyx":516 - * - * introsort(Xf, samples, l, maxd) - * Xf += r # <<<<<<<<<<<<<< - * samples += r - * n -= r - */ - __pyx_v_Xf = (__pyx_v_Xf + __pyx_v_r); - - /* "stpredictions/models/OK3/_splitter.pyx":517 - * introsort(Xf, samples, l, maxd) - * Xf += r - * samples += r # <<<<<<<<<<<<<< - * n -= r - * - */ - __pyx_v_samples = (__pyx_v_samples + __pyx_v_r); - - /* "stpredictions/models/OK3/_splitter.pyx":518 - * Xf += r - * samples += r - * n -= r # <<<<<<<<<<<<<< - * - * - */ - __pyx_v_n = (__pyx_v_n - __pyx_v_r); - } - - /* "stpredictions/models/OK3/_splitter.pyx":488 - * # Introsort with median of 3 pivot selection and 3-way partition function - * # (robust to repeated elements, e.g. lots of zero features). - * cdef void introsort(DTYPE_t* Xf, SIZE_t *samples, # <<<<<<<<<<<<<< - * SIZE_t n, int maxd) nogil: - * cdef DTYPE_t pivot - */ - - /* function exit code */ - __pyx_L0:; -} - -/* "stpredictions/models/OK3/_splitter.pyx":521 - * - * - * cdef inline void sift_down(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< - * SIZE_t start, SIZE_t end) nogil: - * # Restore heap order in Xf[start:end] by moving the max element to start. - */ - -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_maxind; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_root; - int __pyx_t_1; - int __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":526 - * cdef SIZE_t child, maxind, root - * - * root = start # <<<<<<<<<<<<<< - * while True: - * child = root * 2 + 1 - */ - __pyx_v_root = __pyx_v_start; - - /* "stpredictions/models/OK3/_splitter.pyx":527 - * - * root = start - * while True: # <<<<<<<<<<<<<< - * child = root * 2 + 1 - * - */ - while (1) { - - /* "stpredictions/models/OK3/_splitter.pyx":528 - * root = start - * while True: - * child = root * 2 + 1 # <<<<<<<<<<<<<< - * - * # find max of root, left child, right child - */ - __pyx_v_child = ((__pyx_v_root * 2) + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":531 - * - * # find max of root, left child, right child - * maxind = root # <<<<<<<<<<<<<< - * if child < end and Xf[maxind] < Xf[child]: - * maxind = child - */ - __pyx_v_maxind = __pyx_v_root; - - /* "stpredictions/models/OK3/_splitter.pyx":532 - * # find max of root, left child, right child - * maxind = root - * if child < end and Xf[maxind] < Xf[child]: # <<<<<<<<<<<<<< - * maxind = child - * if child + 1 < end and Xf[maxind] < Xf[child + 1]: - */ - __pyx_t_2 = ((__pyx_v_child < __pyx_v_end) != 0); - if (__pyx_t_2) { - } else { - __pyx_t_1 = __pyx_t_2; - goto __pyx_L6_bool_binop_done; - } - __pyx_t_2 = (((__pyx_v_Xf[__pyx_v_maxind]) < (__pyx_v_Xf[__pyx_v_child])) != 0); - __pyx_t_1 = __pyx_t_2; - __pyx_L6_bool_binop_done:; - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":533 - * maxind = root - * if child < end and Xf[maxind] < Xf[child]: - * maxind = child # <<<<<<<<<<<<<< - * if child + 1 < end and Xf[maxind] < Xf[child + 1]: - * maxind = child + 1 - */ - __pyx_v_maxind = __pyx_v_child; - - /* "stpredictions/models/OK3/_splitter.pyx":532 - * # find max of root, left child, right child - * maxind = root - * if child < end and Xf[maxind] < Xf[child]: # <<<<<<<<<<<<<< - * maxind = child - * if child + 1 < end and Xf[maxind] < Xf[child + 1]: - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":534 - * if child < end and Xf[maxind] < Xf[child]: - * maxind = child - * if child + 1 < end and Xf[maxind] < Xf[child + 1]: # <<<<<<<<<<<<<< - * maxind = child + 1 - * - */ - __pyx_t_2 = (((__pyx_v_child + 1) < __pyx_v_end) != 0); - if (__pyx_t_2) { - } else { - __pyx_t_1 = __pyx_t_2; - goto __pyx_L9_bool_binop_done; - } - __pyx_t_2 = (((__pyx_v_Xf[__pyx_v_maxind]) < (__pyx_v_Xf[(__pyx_v_child + 1)])) != 0); - __pyx_t_1 = __pyx_t_2; - __pyx_L9_bool_binop_done:; - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":535 - * maxind = child - * if child + 1 < end and Xf[maxind] < Xf[child + 1]: - * maxind = child + 1 # <<<<<<<<<<<<<< - * - * if maxind == root: - */ - __pyx_v_maxind = (__pyx_v_child + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":534 - * if child < end and Xf[maxind] < Xf[child]: - * maxind = child - * if child + 1 < end and Xf[maxind] < Xf[child + 1]: # <<<<<<<<<<<<<< - * maxind = child + 1 - * - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":537 - * maxind = child + 1 - * - * if maxind == root: # <<<<<<<<<<<<<< - * break - * else: - */ - __pyx_t_1 = ((__pyx_v_maxind == __pyx_v_root) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":538 - * - * if maxind == root: - * break # <<<<<<<<<<<<<< - * else: - * swap(Xf, samples, root, maxind) - */ - goto __pyx_L4_break; - - /* "stpredictions/models/OK3/_splitter.pyx":537 - * maxind = child + 1 - * - * if maxind == root: # <<<<<<<<<<<<<< - * break - * else: - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":540 - * break - * else: - * swap(Xf, samples, root, maxind) # <<<<<<<<<<<<<< - * root = maxind - * - */ - /*else*/ { - __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_root, __pyx_v_maxind); - - /* "stpredictions/models/OK3/_splitter.pyx":541 - * else: - * swap(Xf, samples, root, maxind) - * root = maxind # <<<<<<<<<<<<<< - * - * - */ - __pyx_v_root = __pyx_v_maxind; - } - } - __pyx_L4_break:; - - /* "stpredictions/models/OK3/_splitter.pyx":521 - * - * - * cdef inline void sift_down(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< - * SIZE_t start, SIZE_t end) nogil: - * # Restore heap order in Xf[start:end] by moving the max element to start. - */ - - /* function exit code */ -} - -/* "stpredictions/models/OK3/_splitter.pyx":544 - * - * - * cdef void heapsort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: # <<<<<<<<<<<<<< - * cdef SIZE_t start, end - * - */ - -static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end; - int __pyx_t_1; - - /* "stpredictions/models/OK3/_splitter.pyx":548 - * - * # heapify - * start = (n - 2) / 2 # <<<<<<<<<<<<<< - * end = n - * while True: - */ - __pyx_v_start = ((__pyx_v_n - 2) / 2); - - /* "stpredictions/models/OK3/_splitter.pyx":549 - * # heapify - * start = (n - 2) / 2 - * end = n # <<<<<<<<<<<<<< - * while True: - * sift_down(Xf, samples, start, end) - */ - __pyx_v_end = __pyx_v_n; - - /* "stpredictions/models/OK3/_splitter.pyx":550 - * start = (n - 2) / 2 - * end = n - * while True: # <<<<<<<<<<<<<< - * sift_down(Xf, samples, start, end) - * if start == 0: - */ - while (1) { - - /* "stpredictions/models/OK3/_splitter.pyx":551 - * end = n - * while True: - * sift_down(Xf, samples, start, end) # <<<<<<<<<<<<<< - * if start == 0: - * break - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_sift_down(__pyx_v_Xf, __pyx_v_samples, __pyx_v_start, __pyx_v_end); - - /* "stpredictions/models/OK3/_splitter.pyx":552 - * while True: - * sift_down(Xf, samples, start, end) - * if start == 0: # <<<<<<<<<<<<<< - * break - * start -= 1 - */ - __pyx_t_1 = ((__pyx_v_start == 0) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":553 - 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* cdef double min_weight_leaf = self.min_weight_leaf - * cdef UINT32_t* random_state = &self.rand_r_state - */ - __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf; - __pyx_v_min_samples_leaf = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":592 - * cdef SIZE_t max_features = self.max_features - * cdef SIZE_t min_samples_leaf = self.min_samples_leaf - * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< - * cdef UINT32_t* random_state = &self.rand_r_state - * - */ - __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf; - __pyx_v_min_weight_leaf = __pyx_t_4; - - /* "stpredictions/models/OK3/_splitter.pyx":593 - * cdef SIZE_t min_samples_leaf = self.min_samples_leaf - * cdef double min_weight_leaf = self.min_weight_leaf - * cdef UINT32_t* random_state = &self.rand_r_state # <<<<<<<<<<<<<< - * - * cdef SplitRecord best, current - */ - __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state); - - /* "stpredictions/models/OK3/_splitter.pyx":596 - 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* cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 - */ - __pyx_v_n_found_constants = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":607 - * cdef SIZE_t n_found_constants = 0 - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< - * cdef SIZE_t n_known_constants = n_constant_features[0] - * # n_total_constants = n_known_constants + n_found_constants - */ - __pyx_v_n_drawn_constants = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":608 - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 - * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< - * # n_total_constants = n_known_constants + n_found_constants - * cdef SIZE_t n_total_constants = n_known_constants - */ - __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); - - /* "stpredictions/models/OK3/_splitter.pyx":610 - * cdef SIZE_t n_known_constants = n_constant_features[0] - * # n_total_constants = n_known_constants + n_found_constants - * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< - * cdef SIZE_t n_visited_features = 0 - * cdef DTYPE_t min_feature_value - */ - __pyx_v_n_total_constants = __pyx_v_n_known_constants; - - /* "stpredictions/models/OK3/_splitter.pyx":611 - * # n_total_constants = n_known_constants + n_found_constants - * cdef SIZE_t n_total_constants = n_known_constants - * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< - * cdef DTYPE_t min_feature_value - * cdef DTYPE_t max_feature_value - */ - __pyx_v_n_visited_features = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":616 - * cdef DTYPE_t current_feature_value - * - * _init_split(&best, end) # <<<<<<<<<<<<<< - * - * # Sample up to max_features without replacement using a - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); - - /* "stpredictions/models/OK3/_splitter.pyx":627 - * # newly discovered constant features to spare computation on descendant - * # nodes. - * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< - * # are constant - * (n_visited_features < max_features or - */ - while (1) { - __pyx_t_6 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0); - if (__pyx_t_6) { - } else { - __pyx_t_5 = __pyx_t_6; - goto __pyx_L5_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":629 - * while (f_i > n_total_constants and # Stop early if remaining features - * # are constant - * (n_visited_features < max_features or # <<<<<<<<<<<<<< - * # At least one drawn features must be non constant - * n_visited_features <= n_found_constants + n_drawn_constants)): - */ - __pyx_t_6 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0); - if (!__pyx_t_6) { - } else { - __pyx_t_5 = __pyx_t_6; - goto __pyx_L5_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":631 - * (n_visited_features < max_features or - * # At least one drawn features must be non constant - * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< - * n_visited_features += 1 - * - */ - __pyx_t_6 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0); - __pyx_t_5 = __pyx_t_6; - __pyx_L5_bool_binop_done:; - if (!__pyx_t_5) break; - - /* "stpredictions/models/OK3/_splitter.pyx":632 - * # At least one drawn features must be non constant - * n_visited_features <= n_found_constants + n_drawn_constants)): - * n_visited_features += 1 # <<<<<<<<<<<<<< - * - * # Loop invariant: elements of features in - */ - __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":646 - * - * # Draw a feature at random - * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< - * random_state) - * - */ - __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); - - /* "stpredictions/models/OK3/_splitter.pyx":649 - * random_state) - * - * if f_j < n_known_constants: # <<<<<<<<<<<<<< - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] - */ - __pyx_t_5 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":651 - * if f_j < n_known_constants: - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] # <<<<<<<<<<<<<< - * n_drawn_constants += 1 - * - */ - __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); - __pyx_t_7 = (__pyx_v_features[__pyx_v_n_drawn_constants]); - (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_2; - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; - - /* "stpredictions/models/OK3/_splitter.pyx":652 - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] - * n_drawn_constants += 1 # <<<<<<<<<<<<<< - * - * else: - */ - __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":649 - * random_state) - * - * if f_j < n_known_constants: # <<<<<<<<<<<<<< - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] - */ - goto __pyx_L8; - } - - /* "stpredictions/models/OK3/_splitter.pyx":656 - * else: - * # f_j in the interval [n_known_constants, f_i - n_found_constants[ - * f_j += n_found_constants # <<<<<<<<<<<<<< - * # f_j in the interval [n_total_constants, f_i[ - * - */ - /*else*/ { - __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); - - /* "stpredictions/models/OK3/_splitter.pyx":659 - * # f_j in the interval [n_total_constants, f_i[ - * - * current.feature = features[f_j] # <<<<<<<<<<<<<< - * - * # Find min, max - */ - __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); - - /* "stpredictions/models/OK3/_splitter.pyx":662 - * - * # Find min, max - * min_feature_value = self.X[samples[start], current.feature] # <<<<<<<<<<<<<< - * max_feature_value = min_feature_value - * Xf[start] = min_feature_value - */ - if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 662, __pyx_L1_error)} - __pyx_t_8 = (__pyx_v_samples[__pyx_v_start]); - __pyx_t_9 = __pyx_v_current.feature; - __pyx_v_min_feature_value = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))); - - /* "stpredictions/models/OK3/_splitter.pyx":663 - * # Find min, max - * min_feature_value = self.X[samples[start], current.feature] - * max_feature_value = min_feature_value # <<<<<<<<<<<<<< - * Xf[start] = min_feature_value - * - */ - __pyx_v_max_feature_value = __pyx_v_min_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":664 - * min_feature_value = self.X[samples[start], current.feature] - * max_feature_value = min_feature_value - * Xf[start] = min_feature_value # <<<<<<<<<<<<<< - * - * for p in range(start + 1, end): - */ - (__pyx_v_Xf[__pyx_v_start]) = __pyx_v_min_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":666 - * Xf[start] = min_feature_value - * - * for p in range(start + 1, end): # <<<<<<<<<<<<<< - * current_feature_value = self.X[samples[p], current.feature] - * Xf[p] = current_feature_value - */ - __pyx_t_7 = __pyx_v_end; - __pyx_t_2 = __pyx_t_7; - for (__pyx_t_10 = (__pyx_v_start + 1); __pyx_t_10 < __pyx_t_2; __pyx_t_10+=1) { - __pyx_v_p = __pyx_t_10; - - /* "stpredictions/models/OK3/_splitter.pyx":667 - * - * for p in range(start + 1, end): - * current_feature_value = self.X[samples[p], current.feature] # <<<<<<<<<<<<<< - * Xf[p] = current_feature_value - * - */ - if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 667, __pyx_L1_error)} - __pyx_t_9 = (__pyx_v_samples[__pyx_v_p]); - __pyx_t_8 = __pyx_v_current.feature; - __pyx_v_current_feature_value = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[1]) ))); - - /* "stpredictions/models/OK3/_splitter.pyx":668 - * for p in range(start + 1, end): - * current_feature_value = self.X[samples[p], current.feature] - * Xf[p] = current_feature_value # <<<<<<<<<<<<<< - * - * if current_feature_value < min_feature_value: - */ - (__pyx_v_Xf[__pyx_v_p]) = __pyx_v_current_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":670 - * Xf[p] = current_feature_value - * - * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: - */ - __pyx_t_5 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":671 - * - * if current_feature_value < min_feature_value: - * min_feature_value = current_feature_value # <<<<<<<<<<<<<< - * elif current_feature_value > max_feature_value: - * max_feature_value = current_feature_value - */ - __pyx_v_min_feature_value = __pyx_v_current_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":670 - * Xf[p] = current_feature_value - * - * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: - */ - goto __pyx_L11; - } - - /* "stpredictions/models/OK3/_splitter.pyx":672 - * if current_feature_value < min_feature_value: - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< - * max_feature_value = current_feature_value - * - */ - __pyx_t_5 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":673 - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: - * max_feature_value = current_feature_value # <<<<<<<<<<<<<< - * - * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: - */ - __pyx_v_max_feature_value = __pyx_v_current_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":672 - * if current_feature_value < min_feature_value: - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< - * max_feature_value = current_feature_value - * - */ - } - __pyx_L11:; - } - - /* "stpredictions/models/OK3/_splitter.pyx":675 - * max_feature_value = current_feature_value - * - * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< - * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature - * - */ - __pyx_t_5 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":676 - * - * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: - * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature # <<<<<<<<<<<<<< - * - * n_found_constants += 1 - */ - __pyx_t_7 = (__pyx_v_features[__pyx_v_n_total_constants]); - __pyx_t_2 = __pyx_v_current.feature; - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; - (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":678 - * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature - * - * n_found_constants += 1 # <<<<<<<<<<<<<< - * n_total_constants += 1 - * - */ - __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":679 - * - * n_found_constants += 1 - * n_total_constants += 1 # <<<<<<<<<<<<<< - * - * else: - */ - __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":675 - * max_feature_value = current_feature_value - * - * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< - * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature - * - */ - goto __pyx_L12; - } - - /* "stpredictions/models/OK3/_splitter.pyx":682 - * - * else: - * f_i -= 1 # <<<<<<<<<<<<<< - * features[f_i], features[f_j] = features[f_j], features[f_i] - * - */ - /*else*/ { - __pyx_v_f_i = (__pyx_v_f_i - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":683 - * else: - * f_i -= 1 - * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< - * - * # Draw a random threshold - */ - __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); - __pyx_t_7 = (__pyx_v_features[__pyx_v_f_i]); - (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2; - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; - - /* "stpredictions/models/OK3/_splitter.pyx":686 - * - * # Draw a random threshold - * current.threshold = rand_uniform(min_feature_value, # <<<<<<<<<<<<<< - * max_feature_value, - * random_state) - */ - __pyx_v_current.threshold = __pyx_f_7sklearn_4tree_6_utils_rand_uniform(__pyx_v_min_feature_value, __pyx_v_max_feature_value, __pyx_v_random_state); - - /* "stpredictions/models/OK3/_splitter.pyx":690 - * random_state) - * - * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< - * current.threshold = min_feature_value - * - */ - __pyx_t_5 = ((__pyx_v_current.threshold == __pyx_v_max_feature_value) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":691 - * - * if current.threshold == max_feature_value: - * current.threshold = min_feature_value # <<<<<<<<<<<<<< - * - * # Partition - */ - __pyx_v_current.threshold = __pyx_v_min_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":690 - * random_state) - * - * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< - * current.threshold = min_feature_value - * - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":694 - * - * # Partition - * p, partition_end = start, end # <<<<<<<<<<<<<< - * while p < partition_end: - * if Xf[p] <= current.threshold: - */ - __pyx_t_7 = __pyx_v_start; - __pyx_t_2 = __pyx_v_end; - __pyx_v_p = __pyx_t_7; - __pyx_v_partition_end = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":695 - * # Partition - * p, partition_end = start, end - * while p < partition_end: # <<<<<<<<<<<<<< - * if Xf[p] <= current.threshold: - * p += 1 - */ - while (1) { - __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0); - if (!__pyx_t_5) break; - - /* "stpredictions/models/OK3/_splitter.pyx":696 - * p, partition_end = start, end - * while p < partition_end: - * if Xf[p] <= current.threshold: # <<<<<<<<<<<<<< - * p += 1 - * else: - */ - __pyx_t_5 = (((__pyx_v_Xf[__pyx_v_p]) <= __pyx_v_current.threshold) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":697 - * while p < partition_end: - * if Xf[p] <= current.threshold: - * p += 1 # <<<<<<<<<<<<<< - * else: - * partition_end -= 1 - */ - __pyx_v_p = (__pyx_v_p + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":696 - * p, partition_end = start, end - * while p < partition_end: - * if Xf[p] <= current.threshold: # <<<<<<<<<<<<<< - * p += 1 - * else: - */ - goto __pyx_L16; - } - - /* "stpredictions/models/OK3/_splitter.pyx":699 - * p += 1 - * else: - * partition_end -= 1 # <<<<<<<<<<<<<< - * - * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] - */ - /*else*/ { - __pyx_v_partition_end = (__pyx_v_partition_end - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":701 - * partition_end -= 1 - * - * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] # <<<<<<<<<<<<<< - * samples[p], samples[partition_end] = samples[partition_end], samples[p] - * - */ - __pyx_t_11 = (__pyx_v_Xf[__pyx_v_partition_end]); - __pyx_t_12 = (__pyx_v_Xf[__pyx_v_p]); - (__pyx_v_Xf[__pyx_v_p]) = __pyx_t_11; - (__pyx_v_Xf[__pyx_v_partition_end]) = __pyx_t_12; - - /* "stpredictions/models/OK3/_splitter.pyx":702 - * - * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] - * samples[p], samples[partition_end] = samples[partition_end], samples[p] # <<<<<<<<<<<<<< - * - * current.pos = partition_end - */ - __pyx_t_2 = (__pyx_v_samples[__pyx_v_partition_end]); - __pyx_t_7 = (__pyx_v_samples[__pyx_v_p]); - (__pyx_v_samples[__pyx_v_p]) = __pyx_t_2; - (__pyx_v_samples[__pyx_v_partition_end]) = __pyx_t_7; - } - __pyx_L16:; - } - - /* "stpredictions/models/OK3/_splitter.pyx":704 - * samples[p], samples[partition_end] = samples[partition_end], samples[p] - * - * current.pos = partition_end # <<<<<<<<<<<<<< - * - * # Reject if min_samples_leaf is not guaranteed - */ - __pyx_v_current.pos = __pyx_v_partition_end; - - /* "stpredictions/models/OK3/_splitter.pyx":707 - * - * # Reject if min_samples_leaf is not guaranteed - * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< - 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* Xf[start_positive_] = X_data[k] - */ - __pyx_t_5 = (((__pyx_v_X_data[__pyx_v_k]) > 0.0) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":983 - * if start <= index_to_samples[X_indices[k]] < end: - * if X_data[k] > 0: - * start_positive_ -= 1 # <<<<<<<<<<<<<< - * Xf[start_positive_] = X_data[k] - * index = index_to_samples[X_indices[k]] - */ - __pyx_v_start_positive_ = (__pyx_v_start_positive_ - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":984 - * if X_data[k] > 0: - * start_positive_ -= 1 - * Xf[start_positive_] = X_data[k] # <<<<<<<<<<<<<< - * index = index_to_samples[X_indices[k]] - * sparse_swap(index_to_samples, samples, index, start_positive_) - */ - (__pyx_v_Xf[__pyx_v_start_positive_]) = (__pyx_v_X_data[__pyx_v_k]); - - /* "stpredictions/models/OK3/_splitter.pyx":985 - * start_positive_ -= 1 - * Xf[start_positive_] = X_data[k] - * index = index_to_samples[X_indices[k]] # <<<<<<<<<<<<<< - * sparse_swap(index_to_samples, samples, index, start_positive_) - * - */ - __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]); - - /* "stpredictions/models/OK3/_splitter.pyx":986 - * Xf[start_positive_] = X_data[k] - * index = index_to_samples[X_indices[k]] - * sparse_swap(index_to_samples, samples, index, start_positive_) # <<<<<<<<<<<<<< - * - * - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_start_positive_); - - /* "stpredictions/models/OK3/_splitter.pyx":982 - * for k in range(indptr_start, indptr_end): - * if start <= index_to_samples[X_indices[k]] < end: - * if X_data[k] > 0: # <<<<<<<<<<<<<< - * start_positive_ -= 1 - * Xf[start_positive_] = X_data[k] - */ - goto __pyx_L6; - } - - /* "stpredictions/models/OK3/_splitter.pyx":989 - * - * - * elif X_data[k] < 0: # <<<<<<<<<<<<<< - * Xf[end_negative_] = X_data[k] - * index = index_to_samples[X_indices[k]] - */ - __pyx_t_5 = (((__pyx_v_X_data[__pyx_v_k]) < 0.0) != 0); - if (__pyx_t_5) { - - /* "stpredictions/models/OK3/_splitter.pyx":990 - * - * elif X_data[k] < 0: - * Xf[end_negative_] = X_data[k] # <<<<<<<<<<<<<< - * index = index_to_samples[X_indices[k]] - * sparse_swap(index_to_samples, samples, index, end_negative_) - */ - (__pyx_v_Xf[__pyx_v_end_negative_]) = (__pyx_v_X_data[__pyx_v_k]); - - /* "stpredictions/models/OK3/_splitter.pyx":991 - * elif X_data[k] < 0: - * Xf[end_negative_] = X_data[k] - * index = index_to_samples[X_indices[k]] # <<<<<<<<<<<<<< - * sparse_swap(index_to_samples, samples, index, end_negative_) - * end_negative_ += 1 - */ - __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]); - - /* "stpredictions/models/OK3/_splitter.pyx":992 - * Xf[end_negative_] = X_data[k] - * index = index_to_samples[X_indices[k]] - * sparse_swap(index_to_samples, samples, index, end_negative_) # <<<<<<<<<<<<<< - * end_negative_ += 1 - * - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_end_negative_); - - /* "stpredictions/models/OK3/_splitter.pyx":993 - * index = index_to_samples[X_indices[k]] - * sparse_swap(index_to_samples, samples, index, end_negative_) - * end_negative_ += 1 # <<<<<<<<<<<<<< - * - * # Returned values - */ - __pyx_v_end_negative_ = (__pyx_v_end_negative_ + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":989 - * - * - * elif X_data[k] < 0: # <<<<<<<<<<<<<< - * Xf[end_negative_] = X_data[k] - * index = index_to_samples[X_indices[k]] - */ - } - __pyx_L6:; - - /* "stpredictions/models/OK3/_splitter.pyx":981 - * - * for k in range(indptr_start, indptr_end): - * if start <= index_to_samples[X_indices[k]] < end: # <<<<<<<<<<<<<< - * if X_data[k] > 0: - * start_positive_ -= 1 - */ - } - } - - /* "stpredictions/models/OK3/_splitter.pyx":996 - * - * # Returned values - * end_negative[0] = end_negative_ # <<<<<<<<<<<<<< - * start_positive[0] = start_positive_ - * - */ - (__pyx_v_end_negative[0]) = __pyx_v_end_negative_; - - /* "stpredictions/models/OK3/_splitter.pyx":997 - * # Returned values - * end_negative[0] = end_negative_ - * start_positive[0] = start_positive_ # <<<<<<<<<<<<<< - * - * - */ - (__pyx_v_start_positive[0]) = __pyx_v_start_positive_; - - /* "stpredictions/models/OK3/_splitter.pyx":960 - * - * - * cdef inline void extract_nnz_index_to_samples(INT32_t* X_indices, # <<<<<<<<<<<<<< - * DTYPE_t* X_data, - * INT32_t indptr_start, - */ - - /* function exit code */ -} - -/* "stpredictions/models/OK3/_splitter.pyx":1000 - * - * - * cdef inline void extract_nnz_binary_search(INT32_t* X_indices, # <<<<<<<<<<<<<< - * DTYPE_t* X_data, - * INT32_t indptr_start, - */ - -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indices, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X_data, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_start, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_sorted_samples, int *__pyx_v_is_samples_sorted) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_index; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative_; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive_; - int __pyx_t_1; - int __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":1023 - * cdef SIZE_t n_samples - * - * if not is_samples_sorted[0]: # <<<<<<<<<<<<<< - * n_samples = end - start - * memcpy(sorted_samples + start, samples + start, - */ - __pyx_t_1 = ((!((__pyx_v_is_samples_sorted[0]) != 0)) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":1024 - * - * if not is_samples_sorted[0]: - * n_samples = end - start # <<<<<<<<<<<<<< - * memcpy(sorted_samples + start, samples + start, - * n_samples * sizeof(SIZE_t)) - */ - __pyx_v_n_samples = (__pyx_v_end - __pyx_v_start); - - /* "stpredictions/models/OK3/_splitter.pyx":1025 - * if not is_samples_sorted[0]: - * n_samples = end - start - * memcpy(sorted_samples + start, samples + start, # <<<<<<<<<<<<<< - * n_samples * sizeof(SIZE_t)) - * qsort(sorted_samples + start, n_samples, sizeof(SIZE_t), - */ - (void)(memcpy((__pyx_v_sorted_samples + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_n_samples * (sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t))))); - - /* "stpredictions/models/OK3/_splitter.pyx":1027 - * memcpy(sorted_samples + start, samples + start, - * n_samples * sizeof(SIZE_t)) - * qsort(sorted_samples + start, n_samples, sizeof(SIZE_t), # <<<<<<<<<<<<<< - * compare_SIZE_t) - * is_samples_sorted[0] = 1 - */ - qsort((__pyx_v_sorted_samples + __pyx_v_start), __pyx_v_n_samples, (sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)), __pyx_f_13stpredictions_6models_3OK3_9_splitter_compare_SIZE_t); - - /* "stpredictions/models/OK3/_splitter.pyx":1029 - * qsort(sorted_samples + start, n_samples, sizeof(SIZE_t), - * compare_SIZE_t) - * is_samples_sorted[0] = 1 # <<<<<<<<<<<<<< - * - * while (indptr_start < indptr_end and - */ - (__pyx_v_is_samples_sorted[0]) = 1; - - /* "stpredictions/models/OK3/_splitter.pyx":1023 - * cdef SIZE_t n_samples - * - * if not is_samples_sorted[0]: # <<<<<<<<<<<<<< - * n_samples = end - start - * memcpy(sorted_samples + start, samples + start, - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":1031 - * is_samples_sorted[0] = 1 - * - * while (indptr_start < indptr_end and # <<<<<<<<<<<<<< - * sorted_samples[start] > X_indices[indptr_start]): - * indptr_start += 1 - */ - while (1) { - __pyx_t_2 = ((__pyx_v_indptr_start < __pyx_v_indptr_end) != 0); - if (__pyx_t_2) { - } else { - __pyx_t_1 = __pyx_t_2; - goto __pyx_L6_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1032 - * - * while (indptr_start < indptr_end and - * sorted_samples[start] > X_indices[indptr_start]): # <<<<<<<<<<<<<< - * indptr_start += 1 - * - */ - __pyx_t_2 = (((__pyx_v_sorted_samples[__pyx_v_start]) > (__pyx_v_X_indices[__pyx_v_indptr_start])) != 0); - __pyx_t_1 = __pyx_t_2; - __pyx_L6_bool_binop_done:; - if (!__pyx_t_1) break; - - /* "stpredictions/models/OK3/_splitter.pyx":1033 - * while (indptr_start < indptr_end and - * sorted_samples[start] > X_indices[indptr_start]): - * indptr_start += 1 # <<<<<<<<<<<<<< - * - * while (indptr_start < indptr_end and - */ - __pyx_v_indptr_start = (__pyx_v_indptr_start + 1); - } - - /* "stpredictions/models/OK3/_splitter.pyx":1035 - * indptr_start += 1 - * - * while (indptr_start < indptr_end and # <<<<<<<<<<<<<< - * sorted_samples[end - 1] < X_indices[indptr_end - 1]): - * indptr_end -= 1 - */ - while (1) { - __pyx_t_2 = ((__pyx_v_indptr_start < __pyx_v_indptr_end) != 0); - if (__pyx_t_2) { - } else { - __pyx_t_1 = __pyx_t_2; - goto __pyx_L10_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1036 - * - * while (indptr_start < indptr_end and - * sorted_samples[end - 1] < X_indices[indptr_end - 1]): # <<<<<<<<<<<<<< - * indptr_end -= 1 - * - */ - __pyx_t_2 = (((__pyx_v_sorted_samples[(__pyx_v_end - 1)]) < (__pyx_v_X_indices[(__pyx_v_indptr_end - 1)])) != 0); - __pyx_t_1 = __pyx_t_2; - __pyx_L10_bool_binop_done:; - if (!__pyx_t_1) break; - - /* "stpredictions/models/OK3/_splitter.pyx":1037 - * while (indptr_start < indptr_end and - * sorted_samples[end - 1] < X_indices[indptr_end - 1]): - * indptr_end -= 1 # <<<<<<<<<<<<<< - * - * cdef SIZE_t p = start - */ - __pyx_v_indptr_end = (__pyx_v_indptr_end - 1); - } - - /* "stpredictions/models/OK3/_splitter.pyx":1039 - * indptr_end -= 1 - * - * cdef SIZE_t p = start # <<<<<<<<<<<<<< - * cdef SIZE_t index - * cdef SIZE_t k - */ - __pyx_v_p = __pyx_v_start; - - /* "stpredictions/models/OK3/_splitter.pyx":1042 - * cdef SIZE_t index - * cdef SIZE_t k - * cdef SIZE_t end_negative_ = start # <<<<<<<<<<<<<< - * cdef SIZE_t start_positive_ = end - * - */ - __pyx_v_end_negative_ = __pyx_v_start; - - /* "stpredictions/models/OK3/_splitter.pyx":1043 - * cdef SIZE_t k - * cdef SIZE_t end_negative_ = start - * cdef SIZE_t start_positive_ = end # <<<<<<<<<<<<<< - * - * while (p < end and indptr_start < indptr_end): - */ - __pyx_v_start_positive_ = __pyx_v_end; - - /* "stpredictions/models/OK3/_splitter.pyx":1045 - * cdef SIZE_t start_positive_ = end - * - * while (p < end and indptr_start < indptr_end): # <<<<<<<<<<<<<< - * # Find index of sorted_samples[p] in X_indices - * binary_search(X_indices, indptr_start, indptr_end, - */ - while (1) { - __pyx_t_2 = ((__pyx_v_p < __pyx_v_end) != 0); - if (__pyx_t_2) { - } else { - __pyx_t_1 = __pyx_t_2; - goto __pyx_L14_bool_binop_done; - } - __pyx_t_2 = ((__pyx_v_indptr_start < __pyx_v_indptr_end) != 0); - __pyx_t_1 = __pyx_t_2; - __pyx_L14_bool_binop_done:; - if (!__pyx_t_1) break; - - /* "stpredictions/models/OK3/_splitter.pyx":1047 - * while (p < end and indptr_start < indptr_end): - * # Find index of sorted_samples[p] in X_indices - * binary_search(X_indices, indptr_start, indptr_end, # <<<<<<<<<<<<<< - * sorted_samples[p], &k, &indptr_start) - * - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_binary_search(__pyx_v_X_indices, __pyx_v_indptr_start, __pyx_v_indptr_end, (__pyx_v_sorted_samples[__pyx_v_p]), (&__pyx_v_k), (&__pyx_v_indptr_start)); - - /* "stpredictions/models/OK3/_splitter.pyx":1050 - * sorted_samples[p], &k, &indptr_start) - * - * if k != -1: # <<<<<<<<<<<<<< - * # If k != -1, we have found a non zero value - * - */ - __pyx_t_1 = ((__pyx_v_k != -1L) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":1053 - * # If k != -1, we have found a non zero value - * - * if X_data[k] > 0: # <<<<<<<<<<<<<< - * start_positive_ -= 1 - * Xf[start_positive_] = X_data[k] - */ - __pyx_t_1 = (((__pyx_v_X_data[__pyx_v_k]) > 0.0) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":1054 - * - * if X_data[k] > 0: - * start_positive_ -= 1 # <<<<<<<<<<<<<< - * Xf[start_positive_] = X_data[k] - * index = index_to_samples[X_indices[k]] - */ - __pyx_v_start_positive_ = (__pyx_v_start_positive_ - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1055 - * if X_data[k] > 0: - * start_positive_ -= 1 - * Xf[start_positive_] = X_data[k] # <<<<<<<<<<<<<< - * index = index_to_samples[X_indices[k]] - * sparse_swap(index_to_samples, samples, index, start_positive_) - */ - (__pyx_v_Xf[__pyx_v_start_positive_]) = (__pyx_v_X_data[__pyx_v_k]); - - /* "stpredictions/models/OK3/_splitter.pyx":1056 - * start_positive_ -= 1 - * Xf[start_positive_] = X_data[k] - * index = index_to_samples[X_indices[k]] # <<<<<<<<<<<<<< - * sparse_swap(index_to_samples, samples, index, start_positive_) - * - */ - __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]); - - /* "stpredictions/models/OK3/_splitter.pyx":1057 - * Xf[start_positive_] = X_data[k] - * index = index_to_samples[X_indices[k]] - * sparse_swap(index_to_samples, samples, index, start_positive_) # <<<<<<<<<<<<<< - * - * - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_start_positive_); - - /* "stpredictions/models/OK3/_splitter.pyx":1053 - * # If k != -1, we have found a non zero value - * - * if X_data[k] > 0: # <<<<<<<<<<<<<< - * start_positive_ -= 1 - * Xf[start_positive_] = X_data[k] - */ - goto __pyx_L17; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1060 - * - * - * elif X_data[k] < 0: # <<<<<<<<<<<<<< - * Xf[end_negative_] = X_data[k] - * index = index_to_samples[X_indices[k]] - */ - __pyx_t_1 = (((__pyx_v_X_data[__pyx_v_k]) < 0.0) != 0); - if (__pyx_t_1) { - - /* "stpredictions/models/OK3/_splitter.pyx":1061 - * - * elif X_data[k] < 0: - * Xf[end_negative_] = X_data[k] # <<<<<<<<<<<<<< - * index = index_to_samples[X_indices[k]] - * sparse_swap(index_to_samples, samples, index, end_negative_) - */ - (__pyx_v_Xf[__pyx_v_end_negative_]) = (__pyx_v_X_data[__pyx_v_k]); - - /* "stpredictions/models/OK3/_splitter.pyx":1062 - * elif X_data[k] < 0: - * Xf[end_negative_] = X_data[k] - * index = index_to_samples[X_indices[k]] # <<<<<<<<<<<<<< - * sparse_swap(index_to_samples, samples, index, end_negative_) - * end_negative_ += 1 - */ - __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]); - - /* "stpredictions/models/OK3/_splitter.pyx":1063 - * Xf[end_negative_] = X_data[k] - * index = index_to_samples[X_indices[k]] - * sparse_swap(index_to_samples, samples, index, end_negative_) # <<<<<<<<<<<<<< - * end_negative_ += 1 - * p += 1 - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_end_negative_); - - /* "stpredictions/models/OK3/_splitter.pyx":1064 - * index = index_to_samples[X_indices[k]] - * sparse_swap(index_to_samples, samples, index, end_negative_) - * end_negative_ += 1 # <<<<<<<<<<<<<< - * p += 1 - * - */ - __pyx_v_end_negative_ = (__pyx_v_end_negative_ + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1060 - * - * - * elif X_data[k] < 0: # <<<<<<<<<<<<<< - * Xf[end_negative_] = X_data[k] - * index = index_to_samples[X_indices[k]] - */ - } - __pyx_L17:; - - /* "stpredictions/models/OK3/_splitter.pyx":1050 - * sorted_samples[p], &k, &indptr_start) - * - * if k != -1: # <<<<<<<<<<<<<< - * # If k != -1, we have found a non zero value - * - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":1065 - * sparse_swap(index_to_samples, samples, index, end_negative_) - * end_negative_ += 1 - * p += 1 # <<<<<<<<<<<<<< - * - * # Returned values - */ - __pyx_v_p = (__pyx_v_p + 1); - } - - /* "stpredictions/models/OK3/_splitter.pyx":1068 - * - * # Returned values - * end_negative[0] = end_negative_ # <<<<<<<<<<<<<< - * start_positive[0] = start_positive_ - * - */ - (__pyx_v_end_negative[0]) = __pyx_v_end_negative_; - - /* "stpredictions/models/OK3/_splitter.pyx":1069 - * # Returned values - * end_negative[0] = end_negative_ - * start_positive[0] = start_positive_ # <<<<<<<<<<<<<< - * - * - */ - (__pyx_v_start_positive[0]) = __pyx_v_start_positive_; - - /* "stpredictions/models/OK3/_splitter.pyx":1000 - * - * - * cdef inline void extract_nnz_binary_search(INT32_t* X_indices, # <<<<<<<<<<<<<< - * DTYPE_t* X_data, - * INT32_t indptr_start, - */ - - /* function exit code */ -} - -/* "stpredictions/models/OK3/_splitter.pyx":1072 - * - * - * cdef inline void sparse_swap(SIZE_t* index_to_samples, SIZE_t* samples, # <<<<<<<<<<<<<< - * SIZE_t pos_1, SIZE_t pos_2) nogil: - * """Swap sample pos_1 and pos_2 preserving sparse invariant.""" - */ - -static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos_1, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos_2) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":1075 - * SIZE_t pos_1, SIZE_t pos_2) nogil: - * """Swap sample pos_1 and pos_2 preserving sparse invariant.""" - * samples[pos_1], samples[pos_2] = samples[pos_2], samples[pos_1] # <<<<<<<<<<<<<< - * index_to_samples[samples[pos_1]] = pos_1 - * index_to_samples[samples[pos_2]] = pos_2 - */ - __pyx_t_1 = (__pyx_v_samples[__pyx_v_pos_2]); - __pyx_t_2 = (__pyx_v_samples[__pyx_v_pos_1]); - (__pyx_v_samples[__pyx_v_pos_1]) = __pyx_t_1; - (__pyx_v_samples[__pyx_v_pos_2]) = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":1076 - * """Swap sample pos_1 and pos_2 preserving sparse invariant.""" - * samples[pos_1], samples[pos_2] = samples[pos_2], samples[pos_1] - * index_to_samples[samples[pos_1]] = pos_1 # <<<<<<<<<<<<<< - * index_to_samples[samples[pos_2]] = pos_2 - * - */ - (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_pos_1])]) = __pyx_v_pos_1; - - /* "stpredictions/models/OK3/_splitter.pyx":1077 - * samples[pos_1], samples[pos_2] = samples[pos_2], samples[pos_1] - * index_to_samples[samples[pos_1]] = pos_1 - * index_to_samples[samples[pos_2]] = pos_2 # <<<<<<<<<<<<<< - * - * - */ - (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_pos_2])]) = __pyx_v_pos_2; - - /* "stpredictions/models/OK3/_splitter.pyx":1072 - * - * - * cdef inline void sparse_swap(SIZE_t* index_to_samples, SIZE_t* samples, # <<<<<<<<<<<<<< - * SIZE_t pos_1, SIZE_t pos_2) nogil: - * """Swap sample pos_1 and pos_2 preserving sparse invariant.""" - 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* cdef double min_weight_leaf = self.min_weight_leaf - * cdef UINT32_t* random_state = &self.rand_r_state - */ - __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf; - __pyx_v_min_samples_leaf = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":1115 - * cdef SIZE_t max_features = self.max_features - * cdef SIZE_t min_samples_leaf = self.min_samples_leaf - * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< - * cdef UINT32_t* random_state = &self.rand_r_state - * - */ - __pyx_t_5 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf; - __pyx_v_min_weight_leaf = __pyx_t_5; - - /* "stpredictions/models/OK3/_splitter.pyx":1116 - * cdef SIZE_t min_samples_leaf = self.min_samples_leaf - * cdef double min_weight_leaf = self.min_weight_leaf - * cdef UINT32_t* random_state = &self.rand_r_state # <<<<<<<<<<<<<< - * - * cdef SplitRecord best, current - */ - __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state); - - /* "stpredictions/models/OK3/_splitter.pyx":1119 - * - * cdef SplitRecord best, current - * _init_split(&best, end) # <<<<<<<<<<<<<< - * cdef double current_proxy_improvement = - INFINITY - * cdef double best_proxy_improvement = - INFINITY - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); - - /* "stpredictions/models/OK3/_splitter.pyx":1120 - * cdef SplitRecord best, current - * _init_split(&best, end) - * cdef double current_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< - * cdef double best_proxy_improvement = - INFINITY - * - */ - __pyx_v_current_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - - /* "stpredictions/models/OK3/_splitter.pyx":1121 - * _init_split(&best, end) - * cdef double current_proxy_improvement = - INFINITY - * cdef double best_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< - * - * cdef SIZE_t f_i = n_features - */ - __pyx_v_best_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - - /* "stpredictions/models/OK3/_splitter.pyx":1123 - * cdef double best_proxy_improvement = - INFINITY - * - * cdef SIZE_t f_i = n_features # <<<<<<<<<<<<<< - * cdef SIZE_t f_j, p - * cdef SIZE_t n_visited_features = 0 - */ - __pyx_v_f_i = __pyx_v_n_features; - - /* "stpredictions/models/OK3/_splitter.pyx":1125 - * cdef SIZE_t f_i = n_features - * cdef SIZE_t f_j, p - * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< - * # Number of features discovered to be constant during the split search - * cdef SIZE_t n_found_constants = 0 - */ - __pyx_v_n_visited_features = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":1127 - * cdef SIZE_t n_visited_features = 0 - * # Number of features discovered to be constant during the split search - * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 - */ - __pyx_v_n_found_constants = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":1129 - * cdef SIZE_t n_found_constants = 0 - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< - * cdef SIZE_t n_known_constants = n_constant_features[0] - * # n_total_constants = n_known_constants + n_found_constants - */ - __pyx_v_n_drawn_constants = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":1130 - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 - * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< - * # n_total_constants = n_known_constants + n_found_constants - * cdef SIZE_t n_total_constants = n_known_constants - */ - __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); - - /* "stpredictions/models/OK3/_splitter.pyx":1132 - * cdef SIZE_t n_known_constants = n_constant_features[0] - * # n_total_constants = n_known_constants + n_found_constants - * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< - * cdef DTYPE_t current_feature_value - * - */ - __pyx_v_n_total_constants = __pyx_v_n_known_constants; - - /* "stpredictions/models/OK3/_splitter.pyx":1137 - * cdef SIZE_t p_next - * cdef SIZE_t p_prev - * cdef bint is_samples_sorted = 0 # indicate is sorted_samples is # <<<<<<<<<<<<<< - * # inititialized - * - */ - __pyx_v_is_samples_sorted = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":1154 - * # newly discovered constant features to spare computation on descendant - * # nodes. - * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< - * # are constant - * (n_visited_features < max_features or - */ - while (1) { - __pyx_t_7 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0); - if (__pyx_t_7) { - } else { - __pyx_t_6 = __pyx_t_7; - goto __pyx_L5_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1156 - * while (f_i > n_total_constants and # Stop early if remaining features - * # are constant - * (n_visited_features < max_features or # <<<<<<<<<<<<<< - * # At least one drawn features must be non constant - * n_visited_features <= n_found_constants + n_drawn_constants)): - */ - __pyx_t_7 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0); - if (!__pyx_t_7) { - } else { - __pyx_t_6 = __pyx_t_7; - goto __pyx_L5_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1158 - * (n_visited_features < max_features or - * # At least one drawn features must be non constant - * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< - * - * n_visited_features += 1 - */ - __pyx_t_7 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0); - __pyx_t_6 = __pyx_t_7; - __pyx_L5_bool_binop_done:; - if (!__pyx_t_6) break; - - /* "stpredictions/models/OK3/_splitter.pyx":1160 - * n_visited_features <= n_found_constants + n_drawn_constants)): - * - * n_visited_features += 1 # <<<<<<<<<<<<<< - * - * # Loop invariant: elements of features in - */ - __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1174 - * - * # Draw a feature at random - * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< - * random_state) - * - */ - __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); - - /* "stpredictions/models/OK3/_splitter.pyx":1177 - * random_state) - * - * if f_j < n_known_constants: # <<<<<<<<<<<<<< - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] - */ - __pyx_t_6 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1179 - * if f_j < n_known_constants: - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] # <<<<<<<<<<<<<< - * - * n_drawn_constants += 1 - */ - __pyx_t_2 = (__pyx_v_features[__pyx_v_n_drawn_constants]); - __pyx_t_8 = (__pyx_v_features[__pyx_v_f_j]); - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2; - (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_8; - - /* "stpredictions/models/OK3/_splitter.pyx":1181 - * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] - * - * n_drawn_constants += 1 # <<<<<<<<<<<<<< - * - * else: - */ - __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1177 - * random_state) - * - * if f_j < n_known_constants: # <<<<<<<<<<<<<< - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] - */ - goto __pyx_L8; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1185 - * else: - * # f_j in the interval [n_known_constants, f_i - n_found_constants[ - * f_j += n_found_constants # <<<<<<<<<<<<<< - * # f_j in the interval [n_total_constants, f_i[ - * - */ - /*else*/ { - __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); - - /* "stpredictions/models/OK3/_splitter.pyx":1188 - * # f_j in the interval [n_total_constants, f_i[ - * - * current.feature = features[f_j] # <<<<<<<<<<<<<< - * self.extract_nnz(current.feature, - * &end_negative, &start_positive, - */ - __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); - - /* "stpredictions/models/OK3/_splitter.pyx":1189 - * - * current.feature = features[f_j] - * self.extract_nnz(current.feature, # <<<<<<<<<<<<<< - * &end_negative, &start_positive, - * &is_samples_sorted) - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); - - /* "stpredictions/models/OK3/_splitter.pyx":1194 - * - * # Sort the positive and negative parts of `Xf` - * sort(Xf + start, samples + start, end_negative - start) # <<<<<<<<<<<<<< - * sort(Xf + start_positive, samples + start_positive, - * end - start_positive) - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end_negative - __pyx_v_start)); - - /* "stpredictions/models/OK3/_splitter.pyx":1195 - * # Sort the positive and negative parts of `Xf` - * sort(Xf + start, samples + start, end_negative - start) - * sort(Xf + start_positive, samples + start_positive, # <<<<<<<<<<<<<< - * end - start_positive) - * - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort((__pyx_v_Xf + __pyx_v_start_positive), (__pyx_v_samples + __pyx_v_start_positive), (__pyx_v_end - __pyx_v_start_positive)); - - /* "stpredictions/models/OK3/_splitter.pyx":1199 - * - * # Update index_to_samples to take into account the sort - * for p in range(start, end_negative): # <<<<<<<<<<<<<< - * index_to_samples[samples[p]] = p - * for p in range(start_positive, end): - */ - __pyx_t_8 = __pyx_v_end_negative; - __pyx_t_2 = __pyx_t_8; - for (__pyx_t_9 = __pyx_v_start; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { - __pyx_v_p = __pyx_t_9; - - /* "stpredictions/models/OK3/_splitter.pyx":1200 - * # Update index_to_samples to take into account the sort - * for p in range(start, end_negative): - * index_to_samples[samples[p]] = p # <<<<<<<<<<<<<< - * for p in range(start_positive, end): - * index_to_samples[samples[p]] = p - */ - (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_p])]) = __pyx_v_p; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1201 - * for p in range(start, end_negative): - * index_to_samples[samples[p]] = p - * for p in range(start_positive, end): # <<<<<<<<<<<<<< - * index_to_samples[samples[p]] = p - * - */ - __pyx_t_8 = __pyx_v_end; - __pyx_t_2 = __pyx_t_8; - for (__pyx_t_9 = __pyx_v_start_positive; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { - __pyx_v_p = __pyx_t_9; - - /* "stpredictions/models/OK3/_splitter.pyx":1202 - * index_to_samples[samples[p]] = p - * for p in range(start_positive, end): - * index_to_samples[samples[p]] = p # <<<<<<<<<<<<<< - * - * # Add one or two zeros in Xf, if there is any - */ - (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_p])]) = __pyx_v_p; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1205 - * - * # Add one or two zeros in Xf, if there is any - * if end_negative < start_positive: # <<<<<<<<<<<<<< - * start_positive -= 1 - * Xf[start_positive] = 0. - */ - __pyx_t_6 = ((__pyx_v_end_negative < __pyx_v_start_positive) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1206 - * # Add one or two zeros in Xf, if there is any - * if end_negative < start_positive: - * start_positive -= 1 # <<<<<<<<<<<<<< - * Xf[start_positive] = 0. - * - */ - __pyx_v_start_positive = (__pyx_v_start_positive - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1207 - * if end_negative < start_positive: - * start_positive -= 1 - * Xf[start_positive] = 0. # <<<<<<<<<<<<<< - * - * if end_negative != start_positive: - */ - (__pyx_v_Xf[__pyx_v_start_positive]) = 0.; - - /* "stpredictions/models/OK3/_splitter.pyx":1209 - * Xf[start_positive] = 0. - * - * if end_negative != start_positive: # <<<<<<<<<<<<<< - * Xf[end_negative] = 0. - * end_negative += 1 - */ - __pyx_t_6 = ((__pyx_v_end_negative != __pyx_v_start_positive) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1210 - * - * if end_negative != start_positive: - * Xf[end_negative] = 0. # <<<<<<<<<<<<<< - * end_negative += 1 - * - */ - (__pyx_v_Xf[__pyx_v_end_negative]) = 0.; - - /* "stpredictions/models/OK3/_splitter.pyx":1211 - * if end_negative != start_positive: - * Xf[end_negative] = 0. - * end_negative += 1 # <<<<<<<<<<<<<< - * - * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: - */ - __pyx_v_end_negative = (__pyx_v_end_negative + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1209 - * Xf[start_positive] = 0. - * - * if end_negative != start_positive: # <<<<<<<<<<<<<< - * Xf[end_negative] = 0. - * end_negative += 1 - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":1205 - * - * # Add one or two zeros in Xf, if there is any - * if end_negative < start_positive: # <<<<<<<<<<<<<< - * start_positive -= 1 - * Xf[start_positive] = 0. - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":1213 - * end_negative += 1 - * - * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< - * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] - * - */ - __pyx_t_6 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1214 - * - * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: - * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] # <<<<<<<<<<<<<< - * - * n_found_constants += 1 - */ - __pyx_t_8 = (__pyx_v_features[__pyx_v_n_total_constants]); - __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_8; - (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":1216 - * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] - * - * n_found_constants += 1 # <<<<<<<<<<<<<< - * n_total_constants += 1 - * - */ - __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1217 - * - * n_found_constants += 1 - * n_total_constants += 1 # <<<<<<<<<<<<<< - * - * else: - */ - __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1213 - * end_negative += 1 - * - * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< - * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] - * - */ - goto __pyx_L15; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1220 - * - * else: - * f_i -= 1 # <<<<<<<<<<<<<< - * features[f_i], features[f_j] = features[f_j], features[f_i] - * - */ - /*else*/ { - __pyx_v_f_i = (__pyx_v_f_i - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1221 - * else: - * f_i -= 1 - * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< - * - * # Evaluate all splits - */ - __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); - __pyx_t_8 = (__pyx_v_features[__pyx_v_f_i]); - (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2; - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_8; - - /* "stpredictions/models/OK3/_splitter.pyx":1224 - * - * # Evaluate all splits - * self.criterion.reset() # <<<<<<<<<<<<<< - * p = start - * - */ - __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1224, __pyx_L1_error) - - /* "stpredictions/models/OK3/_splitter.pyx":1225 - * # Evaluate all splits - * self.criterion.reset() - * p = start # <<<<<<<<<<<<<< - * - * while p < end: - */ - __pyx_v_p = __pyx_v_start; - - /* "stpredictions/models/OK3/_splitter.pyx":1227 - * p = start - * - * while p < end: # <<<<<<<<<<<<<< - * if p + 1 != end_negative: - * p_next = p + 1 - */ - while (1) { - __pyx_t_6 = ((__pyx_v_p < __pyx_v_end) != 0); - if (!__pyx_t_6) break; - - /* "stpredictions/models/OK3/_splitter.pyx":1228 - * - * while p < end: - * if p + 1 != end_negative: # <<<<<<<<<<<<<< - * p_next = p + 1 - * else: - */ - __pyx_t_6 = (((__pyx_v_p + 1) != __pyx_v_end_negative) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1229 - * while p < end: - * if p + 1 != end_negative: - * p_next = p + 1 # <<<<<<<<<<<<<< - * else: - * p_next = start_positive - */ - __pyx_v_p_next = (__pyx_v_p + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1228 - * - * while p < end: - * if p + 1 != end_negative: # <<<<<<<<<<<<<< - * p_next = p + 1 - * else: - */ - goto __pyx_L18; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1231 - * p_next = p + 1 - * else: - * p_next = start_positive # <<<<<<<<<<<<<< - * - * while (p_next < end and - */ - /*else*/ { - __pyx_v_p_next = __pyx_v_start_positive; - } - __pyx_L18:; - - /* "stpredictions/models/OK3/_splitter.pyx":1233 - * p_next = start_positive - * - * while (p_next < end and # <<<<<<<<<<<<<< - * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): - * p = p_next - */ - while (1) { - __pyx_t_7 = ((__pyx_v_p_next < __pyx_v_end) != 0); - if (__pyx_t_7) { - } else { - __pyx_t_6 = __pyx_t_7; - goto __pyx_L21_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1234 - * - * while (p_next < end and - * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): # <<<<<<<<<<<<<< - * p = p_next - * if p + 1 != end_negative: - */ - __pyx_t_7 = (((__pyx_v_Xf[__pyx_v_p_next]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); - __pyx_t_6 = __pyx_t_7; - __pyx_L21_bool_binop_done:; - if (!__pyx_t_6) break; - - /* "stpredictions/models/OK3/_splitter.pyx":1235 - * while (p_next < end and - * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): - * p = p_next # <<<<<<<<<<<<<< - * if p + 1 != end_negative: - * p_next = p + 1 - */ - __pyx_v_p = __pyx_v_p_next; - - /* "stpredictions/models/OK3/_splitter.pyx":1236 - * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): - * p = p_next - * if p + 1 != end_negative: # <<<<<<<<<<<<<< - * p_next = p + 1 - * else: - */ - __pyx_t_6 = (((__pyx_v_p + 1) != __pyx_v_end_negative) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1237 - * p = p_next - * if p + 1 != end_negative: - * p_next = p + 1 # <<<<<<<<<<<<<< - * else: - * p_next = start_positive - */ - __pyx_v_p_next = (__pyx_v_p + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1236 - * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): - * p = p_next - * if p + 1 != end_negative: # <<<<<<<<<<<<<< - * p_next = p + 1 - * else: - */ - goto __pyx_L23; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1239 - * p_next = p + 1 - * else: - * p_next = start_positive # <<<<<<<<<<<<<< - * - * - */ - /*else*/ { - __pyx_v_p_next = __pyx_v_start_positive; - } - __pyx_L23:; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1244 - * # (p_next >= end) or (X[samples[p_next], current.feature] > - * # X[samples[p], current.feature]) - * p_prev = p # <<<<<<<<<<<<<< - * p = p_next - 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* cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< - * # Number of features discovered to be constant during the split search - * cdef SIZE_t n_found_constants = 0 - */ - __pyx_v_n_visited_features = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":1358 - * cdef SIZE_t n_visited_features = 0 - * # Number of features discovered to be constant during the split search - * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 - */ - __pyx_v_n_found_constants = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":1360 - * cdef SIZE_t n_found_constants = 0 - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< - * cdef SIZE_t n_known_constants = n_constant_features[0] - * # n_total_constants = n_known_constants + n_found_constants - */ - __pyx_v_n_drawn_constants = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":1361 - * # Number of features known to be constant and drawn without replacement - * cdef SIZE_t n_drawn_constants = 0 - * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< - * # n_total_constants = n_known_constants + n_found_constants - * cdef SIZE_t n_total_constants = n_known_constants - */ - __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); - - /* "stpredictions/models/OK3/_splitter.pyx":1363 - * cdef SIZE_t n_known_constants = n_constant_features[0] - * # n_total_constants = n_known_constants + n_found_constants - * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< - * cdef SIZE_t partition_end - * - */ - __pyx_v_n_total_constants = __pyx_v_n_known_constants; - - /* "stpredictions/models/OK3/_splitter.pyx":1369 - * cdef DTYPE_t max_feature_value - * - * cdef bint is_samples_sorted = 0 # indicate that sorted_samples is # <<<<<<<<<<<<<< - * # inititialized - * - */ - __pyx_v_is_samples_sorted = 0; - - /* "stpredictions/models/OK3/_splitter.pyx":1386 - * # newly discovered constant features to spare computation on descendant - * # nodes. - * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< - * # are constant - * (n_visited_features < max_features or - */ - while (1) { - __pyx_t_7 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0); - if (__pyx_t_7) { - } else { - __pyx_t_6 = __pyx_t_7; - goto __pyx_L5_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1388 - * while (f_i > n_total_constants and # Stop early if remaining features - * # are constant - * (n_visited_features < max_features or # <<<<<<<<<<<<<< - * # At least one drawn features must be non constant - * n_visited_features <= n_found_constants + n_drawn_constants)): - */ - __pyx_t_7 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0); - if (!__pyx_t_7) { - } else { - __pyx_t_6 = __pyx_t_7; - goto __pyx_L5_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1390 - * (n_visited_features < max_features or - * # At least one drawn features must be non constant - * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< - * - * n_visited_features += 1 - */ - __pyx_t_7 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0); - __pyx_t_6 = __pyx_t_7; - __pyx_L5_bool_binop_done:; - if (!__pyx_t_6) break; - - /* "stpredictions/models/OK3/_splitter.pyx":1392 - * n_visited_features <= n_found_constants + n_drawn_constants)): - * - * n_visited_features += 1 # <<<<<<<<<<<<<< - * - * # Loop invariant: elements of features in - */ - __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1406 - * - * # Draw a feature at random - * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< - * random_state) - * - */ - __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); - - /* "stpredictions/models/OK3/_splitter.pyx":1409 - * random_state) - * - * if f_j < n_known_constants: # <<<<<<<<<<<<<< - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] - */ - __pyx_t_6 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1411 - * if f_j < n_known_constants: - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] # <<<<<<<<<<<<<< - * - * n_drawn_constants += 1 - */ - __pyx_t_2 = (__pyx_v_features[__pyx_v_n_drawn_constants]); - __pyx_t_8 = (__pyx_v_features[__pyx_v_f_j]); - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2; - (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_8; - - /* "stpredictions/models/OK3/_splitter.pyx":1413 - * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] - * - * n_drawn_constants += 1 # <<<<<<<<<<<<<< - * - * else: - */ - __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1409 - * random_state) - * - * if f_j < n_known_constants: # <<<<<<<<<<<<<< - * # f_j in the interval [n_drawn_constants, n_known_constants[ - * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] - */ - goto __pyx_L8; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1417 - * else: - * # f_j in the interval [n_known_constants, f_i - n_found_constants[ - * f_j += n_found_constants # <<<<<<<<<<<<<< - * # f_j in the interval [n_total_constants, f_i[ - * - */ - /*else*/ { - __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); - - /* "stpredictions/models/OK3/_splitter.pyx":1420 - * # f_j in the interval [n_total_constants, f_i[ - * - * current.feature = features[f_j] # <<<<<<<<<<<<<< - * - * self.extract_nnz(current.feature, - */ - __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); - - /* "stpredictions/models/OK3/_splitter.pyx":1422 - * current.feature = features[f_j] - * - * self.extract_nnz(current.feature, # <<<<<<<<<<<<<< - * &end_negative, &start_positive, - * &is_samples_sorted) - */ - __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); - - /* "stpredictions/models/OK3/_splitter.pyx":1427 - * - * # Add one or two zeros in Xf, if there is any - * if end_negative < start_positive: # <<<<<<<<<<<<<< - * start_positive -= 1 - * Xf[start_positive] = 0. - */ - __pyx_t_6 = ((__pyx_v_end_negative < __pyx_v_start_positive) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1428 - * # Add one or two zeros in Xf, if there is any - * if end_negative < start_positive: - * start_positive -= 1 # <<<<<<<<<<<<<< - * Xf[start_positive] = 0. - * - */ - __pyx_v_start_positive = (__pyx_v_start_positive - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1429 - * if end_negative < start_positive: - * start_positive -= 1 - * Xf[start_positive] = 0. # <<<<<<<<<<<<<< - * - * if end_negative != start_positive: - */ - (__pyx_v_Xf[__pyx_v_start_positive]) = 0.; - - /* "stpredictions/models/OK3/_splitter.pyx":1431 - * Xf[start_positive] = 0. - * - * if end_negative != start_positive: # <<<<<<<<<<<<<< - * Xf[end_negative] = 0. - * end_negative += 1 - */ - __pyx_t_6 = ((__pyx_v_end_negative != __pyx_v_start_positive) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1432 - * - * if end_negative != start_positive: - * Xf[end_negative] = 0. # <<<<<<<<<<<<<< - * end_negative += 1 - * - */ - (__pyx_v_Xf[__pyx_v_end_negative]) = 0.; - - /* "stpredictions/models/OK3/_splitter.pyx":1433 - * if end_negative != start_positive: - * Xf[end_negative] = 0. - * end_negative += 1 # <<<<<<<<<<<<<< - * - * # Find min, max in Xf[start:end_negative] - */ - __pyx_v_end_negative = (__pyx_v_end_negative + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1431 - * Xf[start_positive] = 0. - * - * if end_negative != start_positive: # <<<<<<<<<<<<<< - * Xf[end_negative] = 0. - * end_negative += 1 - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":1427 - * - * # Add one or two zeros in Xf, if there is any - * if end_negative < start_positive: # <<<<<<<<<<<<<< - * start_positive -= 1 - * Xf[start_positive] = 0. - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":1436 - * - * # Find min, max in Xf[start:end_negative] - * min_feature_value = Xf[start] # <<<<<<<<<<<<<< - * max_feature_value = min_feature_value - * - */ - __pyx_v_min_feature_value = (__pyx_v_Xf[__pyx_v_start]); - - /* "stpredictions/models/OK3/_splitter.pyx":1437 - * # Find min, max in Xf[start:end_negative] - * min_feature_value = Xf[start] - * max_feature_value = min_feature_value # <<<<<<<<<<<<<< - * - * for p in range(start, end_negative): - */ - __pyx_v_max_feature_value = __pyx_v_min_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":1439 - * max_feature_value = min_feature_value - * - * for p in range(start, end_negative): # <<<<<<<<<<<<<< - * current_feature_value = Xf[p] - * - */ - __pyx_t_8 = __pyx_v_end_negative; - __pyx_t_2 = __pyx_t_8; - for (__pyx_t_9 = __pyx_v_start; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { - __pyx_v_p = __pyx_t_9; - - /* "stpredictions/models/OK3/_splitter.pyx":1440 - * - * for p in range(start, end_negative): - * current_feature_value = Xf[p] # <<<<<<<<<<<<<< - * - * if current_feature_value < min_feature_value: - */ - __pyx_v_current_feature_value = (__pyx_v_Xf[__pyx_v_p]); - - /* "stpredictions/models/OK3/_splitter.pyx":1442 - * current_feature_value = Xf[p] - * - * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: - */ - __pyx_t_6 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1443 - * - * if current_feature_value < min_feature_value: - * min_feature_value = current_feature_value # <<<<<<<<<<<<<< - * elif current_feature_value > max_feature_value: - * max_feature_value = current_feature_value - */ - __pyx_v_min_feature_value = __pyx_v_current_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":1442 - * current_feature_value = Xf[p] - * - * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: - */ - goto __pyx_L13; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1444 - * if current_feature_value < min_feature_value: - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< - * max_feature_value = current_feature_value - * - */ - __pyx_t_6 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1445 - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: - * max_feature_value = current_feature_value # <<<<<<<<<<<<<< - * - * # Update min, max given Xf[start_positive:end] - */ - __pyx_v_max_feature_value = __pyx_v_current_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":1444 - * if current_feature_value < min_feature_value: - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< - * max_feature_value = current_feature_value - * - */ - } - __pyx_L13:; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1448 - * - * # Update min, max given Xf[start_positive:end] - * for p in range(start_positive, end): # <<<<<<<<<<<<<< - * current_feature_value = Xf[p] - * - */ - __pyx_t_8 = __pyx_v_end; - __pyx_t_2 = __pyx_t_8; - for (__pyx_t_9 = __pyx_v_start_positive; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { - __pyx_v_p = __pyx_t_9; - - /* "stpredictions/models/OK3/_splitter.pyx":1449 - * # Update min, max given Xf[start_positive:end] - * for p in range(start_positive, end): - * current_feature_value = Xf[p] # <<<<<<<<<<<<<< - * - * if current_feature_value < min_feature_value: - */ - __pyx_v_current_feature_value = (__pyx_v_Xf[__pyx_v_p]); - - /* "stpredictions/models/OK3/_splitter.pyx":1451 - * current_feature_value = Xf[p] - * - * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: - */ - __pyx_t_6 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1452 - * - * if current_feature_value < min_feature_value: - * min_feature_value = current_feature_value # <<<<<<<<<<<<<< - * elif current_feature_value > max_feature_value: - * max_feature_value = current_feature_value - */ - __pyx_v_min_feature_value = __pyx_v_current_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":1451 - * current_feature_value = Xf[p] - * - * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: - */ - goto __pyx_L16; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1453 - * if current_feature_value < min_feature_value: - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< - * max_feature_value = current_feature_value - * - */ - __pyx_t_6 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1454 - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: - * max_feature_value = current_feature_value # <<<<<<<<<<<<<< - * - * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: - */ - __pyx_v_max_feature_value = __pyx_v_current_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":1453 - * if current_feature_value < min_feature_value: - * min_feature_value = current_feature_value - * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< - * max_feature_value = current_feature_value - * - */ - } - __pyx_L16:; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1456 - * max_feature_value = current_feature_value - * - * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< - * features[f_j] = features[n_total_constants] - * features[n_total_constants] = current.feature - */ - __pyx_t_6 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1457 - * - * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: - * features[f_j] = features[n_total_constants] # <<<<<<<<<<<<<< - * features[n_total_constants] = current.feature - * - */ - (__pyx_v_features[__pyx_v_f_j]) = (__pyx_v_features[__pyx_v_n_total_constants]); - - /* "stpredictions/models/OK3/_splitter.pyx":1458 - * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: - * features[f_j] = features[n_total_constants] - * features[n_total_constants] = current.feature # <<<<<<<<<<<<<< - * - * n_found_constants += 1 - */ - __pyx_t_8 = __pyx_v_current.feature; - (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_8; - - /* "stpredictions/models/OK3/_splitter.pyx":1460 - * features[n_total_constants] = current.feature - * - * n_found_constants += 1 # <<<<<<<<<<<<<< - * n_total_constants += 1 - * - */ - __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1461 - * - * n_found_constants += 1 - * n_total_constants += 1 # <<<<<<<<<<<<<< - * - * else: - */ - __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1456 - * max_feature_value = current_feature_value - * - * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< - * features[f_j] = features[n_total_constants] - * features[n_total_constants] = current.feature - */ - goto __pyx_L17; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1464 - * - * else: - * f_i -= 1 # <<<<<<<<<<<<<< - * features[f_i], features[f_j] = features[f_j], features[f_i] - * - */ - /*else*/ { - __pyx_v_f_i = (__pyx_v_f_i - 1); - - /* "stpredictions/models/OK3/_splitter.pyx":1465 - * else: - * f_i -= 1 - * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< - * - * # Draw a random threshold - */ - __pyx_t_8 = (__pyx_v_features[__pyx_v_f_j]); - __pyx_t_2 = (__pyx_v_features[__pyx_v_f_i]); - (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_8; - (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2; - - /* "stpredictions/models/OK3/_splitter.pyx":1468 - * - * # Draw a random threshold - * current.threshold = rand_uniform(min_feature_value, # <<<<<<<<<<<<<< - * max_feature_value, - * random_state) - */ - __pyx_v_current.threshold = __pyx_f_7sklearn_4tree_6_utils_rand_uniform(__pyx_v_min_feature_value, __pyx_v_max_feature_value, __pyx_v_random_state); - - /* "stpredictions/models/OK3/_splitter.pyx":1472 - * random_state) - * - * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< - * current.threshold = min_feature_value - * - */ - __pyx_t_6 = ((__pyx_v_current.threshold == __pyx_v_max_feature_value) != 0); - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1473 - * - * if current.threshold == max_feature_value: - * current.threshold = min_feature_value # <<<<<<<<<<<<<< - * - * # Partition - */ - __pyx_v_current.threshold = __pyx_v_min_feature_value; - - /* "stpredictions/models/OK3/_splitter.pyx":1472 - * random_state) - * - * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< - * current.threshold = min_feature_value - * - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":1476 - * - * # Partition - * current.pos = self._partition(current.threshold, # <<<<<<<<<<<<<< - * end_negative, - * start_positive, - */ - __pyx_v_current.pos = __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.threshold, __pyx_v_end_negative, __pyx_v_start_positive, (__pyx_v_start_positive + ((__pyx_v_Xf[__pyx_v_start_positive]) == 0.))); - - /* "stpredictions/models/OK3/_splitter.pyx":1483 - * - * # Reject if min_samples_leaf is not guaranteed - * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< - * ((end - current.pos) < min_samples_leaf)): - * continue - */ - __pyx_t_7 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0); - if (!__pyx_t_7) { - } else { - __pyx_t_6 = __pyx_t_7; - goto __pyx_L20_bool_binop_done; - } - - /* "stpredictions/models/OK3/_splitter.pyx":1484 - * # Reject if min_samples_leaf is not guaranteed - * if (((current.pos - start) < min_samples_leaf) or - * ((end - current.pos) < min_samples_leaf)): # <<<<<<<<<<<<<< - * continue - * - */ - __pyx_t_7 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0); - __pyx_t_6 = __pyx_t_7; - __pyx_L20_bool_binop_done:; - - /* "stpredictions/models/OK3/_splitter.pyx":1483 - * - * # Reject if min_samples_leaf is not guaranteed - * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< - * ((end - current.pos) < min_samples_leaf)): - * continue - */ - if (__pyx_t_6) { - - /* "stpredictions/models/OK3/_splitter.pyx":1485 - * if (((current.pos - start) < min_samples_leaf) or - * ((end - current.pos) < min_samples_leaf)): - * continue # <<<<<<<<<<<<<< - * - * # Evaluate split - */ - goto __pyx_L3_continue; - - /* "stpredictions/models/OK3/_splitter.pyx":1483 - * - * # Reject if min_samples_leaf is not guaranteed - * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< - * ((end - current.pos) < min_samples_leaf)): - * continue - */ - } - - /* "stpredictions/models/OK3/_splitter.pyx":1488 - * - * # Evaluate split - * self.criterion.reset() # <<<<<<<<<<<<<< - * self.criterion.update(current.pos) - * - */ - __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1488, __pyx_L1_error) - 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* - * if have_step and step == 0: # <<<<<<<<<<<<<< - * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) - * - */ - } - - /* "View.MemoryView":841 - * - * - * if have_start: # <<<<<<<<<<<<<< - * if start < 0: - * start += shape - */ - __pyx_t_2 = (__pyx_v_have_start != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":842 - * - * if have_start: - * if start < 0: # <<<<<<<<<<<<<< - * start += shape - * if start < 0: - */ - __pyx_t_2 = ((__pyx_v_start < 0) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":843 - * if have_start: - * if start < 0: - * start += shape # <<<<<<<<<<<<<< - * if start < 0: - * start = 0 - */ - __pyx_v_start = (__pyx_v_start + __pyx_v_shape); - - /* "View.MemoryView":844 - * if start < 0: - * start += shape - * if start < 0: # <<<<<<<<<<<<<< - * start = 0 - * elif start >= shape: - */ - __pyx_t_2 = ((__pyx_v_start < 0) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":845 - * start += shape - * if start < 0: - * start = 0 # <<<<<<<<<<<<<< - * elif start >= shape: - * if negative_step: - */ - __pyx_v_start = 0; - - /* "View.MemoryView":844 - * if start < 0: - * start += shape - * if start < 0: # <<<<<<<<<<<<<< - * start = 0 - * elif start >= shape: - */ - } - - /* "View.MemoryView":842 - * - * if have_start: - * if start < 0: # <<<<<<<<<<<<<< - * start += shape - * if start < 0: - */ - goto __pyx_L12; - } - - /* "View.MemoryView":846 - * if start < 0: - * start = 0 - * elif start >= shape: # <<<<<<<<<<<<<< - * if negative_step: - * start = shape - 1 - */ - __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":847 - * start = 0 - * elif start >= shape: - * if negative_step: # <<<<<<<<<<<<<< - * start = shape - 1 - * else: - */ - __pyx_t_2 = (__pyx_v_negative_step != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":848 - * elif start >= shape: - * if negative_step: - * start = shape - 1 # <<<<<<<<<<<<<< - * else: - * start = shape - */ - __pyx_v_start = (__pyx_v_shape - 1); - - /* "View.MemoryView":847 - * start = 0 - * elif start >= shape: - * if negative_step: # <<<<<<<<<<<<<< - * start = shape - 1 - * else: - */ - goto __pyx_L14; - } - - /* "View.MemoryView":850 - * start = shape - 1 - * else: - * start = shape # <<<<<<<<<<<<<< - * else: - * if negative_step: - */ - /*else*/ { - __pyx_v_start = __pyx_v_shape; - } - __pyx_L14:; - - /* "View.MemoryView":846 - * if start < 0: - * start = 0 - * elif start >= shape: # <<<<<<<<<<<<<< - * if negative_step: - * start = shape - 1 - */ - } - __pyx_L12:; - - /* "View.MemoryView":841 - * - * - * if have_start: # <<<<<<<<<<<<<< - * if start < 0: - * start += shape - */ - goto __pyx_L11; - } - - /* "View.MemoryView":852 - * start = shape - * else: - * if negative_step: # <<<<<<<<<<<<<< - * start = shape - 1 - * else: - */ - /*else*/ { - __pyx_t_2 = (__pyx_v_negative_step != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":853 - * else: - * if negative_step: - * start = shape - 1 # <<<<<<<<<<<<<< - * else: - * start = 0 - */ - __pyx_v_start = (__pyx_v_shape - 1); - - /* "View.MemoryView":852 - * start = shape - * else: - * if negative_step: # <<<<<<<<<<<<<< - * start = shape - 1 - * else: - */ - goto __pyx_L15; - } - - /* "View.MemoryView":855 - * start = shape - 1 - * else: - * start = 0 # <<<<<<<<<<<<<< - * - * if have_stop: - */ - /*else*/ { - __pyx_v_start = 0; - } - __pyx_L15:; - } - __pyx_L11:; - - /* "View.MemoryView":857 - * start = 0 - * - * if have_stop: # <<<<<<<<<<<<<< - * if stop < 0: - * stop += shape - */ - __pyx_t_2 = (__pyx_v_have_stop != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":858 - * - * if have_stop: - * if stop < 0: # <<<<<<<<<<<<<< - * stop += shape - * if stop < 0: - */ - __pyx_t_2 = ((__pyx_v_stop < 0) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":859 - * if have_stop: - * if stop < 0: - * stop += shape # <<<<<<<<<<<<<< - * if stop < 0: - * stop = 0 - */ - __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape); - - /* "View.MemoryView":860 - * if stop < 0: - * stop += shape - * if stop < 0: # <<<<<<<<<<<<<< - * stop = 0 - * elif stop > shape: - */ - __pyx_t_2 = ((__pyx_v_stop < 0) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":861 - * stop += shape - * if stop < 0: - * stop = 0 # <<<<<<<<<<<<<< - * elif stop > shape: - * stop = shape - */ - __pyx_v_stop = 0; - - /* "View.MemoryView":860 - * if stop < 0: - * stop += shape - * if stop < 0: # <<<<<<<<<<<<<< - * stop = 0 - * elif stop > shape: - */ - } - - /* "View.MemoryView":858 - * - * if have_stop: - * if stop < 0: # <<<<<<<<<<<<<< - * stop += shape - * if stop < 0: - */ - goto __pyx_L17; - } - - /* "View.MemoryView":862 - * if stop < 0: - * stop = 0 - * elif stop > shape: # <<<<<<<<<<<<<< - * stop = shape - * else: - */ - __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":863 - * stop = 0 - * elif stop > shape: - * stop = shape # <<<<<<<<<<<<<< - * else: - * if negative_step: - */ - __pyx_v_stop = __pyx_v_shape; - - /* "View.MemoryView":862 - * if stop < 0: - * stop = 0 - * elif stop > shape: # <<<<<<<<<<<<<< - * stop = shape - * else: - */ - } - __pyx_L17:; - - /* "View.MemoryView":857 - * start = 0 - * - * if have_stop: # <<<<<<<<<<<<<< - * if stop < 0: - * stop += shape - */ - goto __pyx_L16; - } - - /* "View.MemoryView":865 - * stop = shape - * else: - * if negative_step: # <<<<<<<<<<<<<< - * stop = -1 - * else: - */ - /*else*/ { - __pyx_t_2 = (__pyx_v_negative_step != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":866 - * else: - * if negative_step: - * stop = -1 # <<<<<<<<<<<<<< - * else: - * stop = shape - */ - __pyx_v_stop = -1L; - - /* "View.MemoryView":865 - * stop = shape - * else: - * if negative_step: # <<<<<<<<<<<<<< - * stop = -1 - * else: - */ - goto __pyx_L19; - } - - /* "View.MemoryView":868 - * stop = -1 - * else: - * stop = shape # <<<<<<<<<<<<<< - * - * if not have_step: - */ - /*else*/ { - __pyx_v_stop = __pyx_v_shape; - } - __pyx_L19:; - } - __pyx_L16:; - - /* "View.MemoryView":870 - * stop = shape - * - * if not have_step: # <<<<<<<<<<<<<< - * step = 1 - * - */ - __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":871 - * - * if not have_step: - * step = 1 # <<<<<<<<<<<<<< - * - * - */ - __pyx_v_step = 1; - - /* "View.MemoryView":870 - * stop = shape - * - * if not have_step: # <<<<<<<<<<<<<< - * step = 1 - * - */ - } - - /* "View.MemoryView":875 - * - * with cython.cdivision(True): - * new_shape = (stop - start) // step # <<<<<<<<<<<<<< - * - * if (stop - start) - step * new_shape: - */ - __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step); - - /* "View.MemoryView":877 - * new_shape = (stop - start) // step - * - * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< - * new_shape += 1 - * - */ - __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":878 - * - * if (stop - start) - step * new_shape: - * new_shape += 1 # <<<<<<<<<<<<<< - * - * if new_shape < 0: - */ - __pyx_v_new_shape = (__pyx_v_new_shape + 1); - - /* "View.MemoryView":877 - * new_shape = (stop - 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- /* "View.MemoryView":886 - * dst.strides[new_ndim] = stride * step - * dst.shape[new_ndim] = new_shape - * dst.suboffsets[new_ndim] = suboffset # <<<<<<<<<<<<<< - * - * - */ - (__pyx_v_dst->suboffsets[__pyx_v_new_ndim]) = __pyx_v_suboffset; - } - __pyx_L3:; - - /* "View.MemoryView":889 - * - * - * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< - * dst.data += start * stride - * else: - */ - __pyx_t_2 = (((__pyx_v_suboffset_dim[0]) < 0) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":890 - * - * if suboffset_dim[0] < 0: - * dst.data += start * stride # <<<<<<<<<<<<<< - * else: - * dst.suboffsets[suboffset_dim[0]] += start * stride - */ - __pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride)); - - /* "View.MemoryView":889 - * - * - * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< - * dst.data += start * stride - * else: - */ - goto __pyx_L23; - } - - /* "View.MemoryView":892 - * dst.data += start * stride - * else: - * dst.suboffsets[suboffset_dim[0]] += start * stride # <<<<<<<<<<<<<< - 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} - __pyx_L26:; - - /* "View.MemoryView":895 - * - * if suboffset >= 0: - * if not is_slice: # <<<<<<<<<<<<<< - * if new_ndim == 0: - * dst.data = ( dst.data)[0] + suboffset - */ - goto __pyx_L25; - } - - /* "View.MemoryView":902 - * "must be indexed and not sliced", dim) - * else: - * suboffset_dim[0] = new_ndim # <<<<<<<<<<<<<< - * - * return 0 - */ - /*else*/ { - (__pyx_v_suboffset_dim[0]) = __pyx_v_new_ndim; - } - __pyx_L25:; - - /* "View.MemoryView":894 - * dst.suboffsets[suboffset_dim[0]] += start * stride - * - * if suboffset >= 0: # <<<<<<<<<<<<<< - * if not is_slice: - * if new_ndim == 0: - */ - } - - /* "View.MemoryView":904 - * suboffset_dim[0] = new_ndim - * - * return 0 # <<<<<<<<<<<<<< - * - * - */ - __pyx_r = 0; - goto __pyx_L0; - - /* "View.MemoryView":807 - * - * @cname('__pyx_memoryview_slice_memviewslice') - * cdef int slice_memviewslice( # <<<<<<<<<<<<<< - * __Pyx_memviewslice *dst, - * Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset, - */ - - /* function exit code */ - 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for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { - __pyx_v_i = __pyx_t_4; - - /* "View.MemoryView":1130 - * - * for i in range(ndim): - * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< - * f_stride = mslice.strides[i] - * break - */ - __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1131 - * for i in range(ndim): - * if mslice.shape[i] > 1: - * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< - * break - * - */ - __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); - - /* "View.MemoryView":1132 - * if mslice.shape[i] > 1: - * f_stride = mslice.strides[i] - * break # <<<<<<<<<<<<<< - * - * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): - */ - goto __pyx_L7_break; - - /* "View.MemoryView":1130 - * - * for i in range(ndim): - * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< - * f_stride = mslice.strides[i] - * break - */ - } - } - __pyx_L7_break:; - - /* "View.MemoryView":1134 - * break - * - * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< - * return 'C' - * else: - */ - __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":1135 - * - * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): - * return 'C' # <<<<<<<<<<<<<< - * else: - * return 'F' - */ - __pyx_r = 'C'; - goto __pyx_L0; - - /* "View.MemoryView":1134 - * break - * - * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< - * return 'C' - * else: - */ - } - - /* "View.MemoryView":1137 - * return 'C' - * else: - * return 'F' # <<<<<<<<<<<<<< - * - * @cython.cdivision(True) - */ - /*else*/ { - __pyx_r = 'F'; - goto __pyx_L0; - } - - /* "View.MemoryView":1116 - * - * @cname('__pyx_get_best_slice_order') - * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< - * """ - * Figure out the best memory access order for a given slice. - */ - - /* function exit code */ - __pyx_L0:; - return __pyx_r; -} - -/* "View.MemoryView":1140 - * - * @cython.cdivision(True) - * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< - * char *dst_data, Py_ssize_t *dst_strides, - * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, - */ - -static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) { - CYTHON_UNUSED Py_ssize_t __pyx_v_i; - CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; - Py_ssize_t __pyx_v_dst_extent; - Py_ssize_t __pyx_v_src_stride; - Py_ssize_t __pyx_v_dst_stride; - int __pyx_t_1; - int __pyx_t_2; - int __pyx_t_3; - Py_ssize_t __pyx_t_4; - Py_ssize_t __pyx_t_5; - Py_ssize_t __pyx_t_6; - - /* "View.MemoryView":1147 - * - * cdef Py_ssize_t i - * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< - * cdef Py_ssize_t dst_extent = dst_shape[0] - * cdef Py_ssize_t src_stride = src_strides[0] - */ - __pyx_v_src_extent = (__pyx_v_src_shape[0]); - - /* "View.MemoryView":1148 - * cdef Py_ssize_t i - * cdef Py_ssize_t src_extent = src_shape[0] - * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< - * cdef Py_ssize_t src_stride = src_strides[0] - * cdef Py_ssize_t dst_stride = dst_strides[0] - */ - __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); - - /* "View.MemoryView":1149 - * cdef Py_ssize_t src_extent = src_shape[0] - * cdef Py_ssize_t dst_extent = dst_shape[0] - * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< - * cdef Py_ssize_t dst_stride = dst_strides[0] - * - */ - __pyx_v_src_stride = (__pyx_v_src_strides[0]); - - /* "View.MemoryView":1150 - * cdef Py_ssize_t dst_extent = dst_shape[0] - * cdef Py_ssize_t src_stride = src_strides[0] - * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< - * - * if ndim == 1: - */ - __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); - - /* "View.MemoryView":1152 - * cdef Py_ssize_t dst_stride = dst_strides[0] - * - * if ndim == 1: # <<<<<<<<<<<<<< - * if (src_stride > 0 and dst_stride > 0 and - * src_stride == itemsize == dst_stride): - */ - __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); - if (__pyx_t_1) { - - /* "View.MemoryView":1153 - * - * if ndim == 1: - * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< - * src_stride == itemsize == dst_stride): - * memcpy(dst_data, src_data, itemsize * dst_extent) - */ - __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); - if (__pyx_t_2) { - } else { - __pyx_t_1 = __pyx_t_2; - goto __pyx_L5_bool_binop_done; - } - __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); - if (__pyx_t_2) { - } else { - __pyx_t_1 = __pyx_t_2; - goto __pyx_L5_bool_binop_done; - } - - /* "View.MemoryView":1154 - * if ndim == 1: - * if (src_stride > 0 and dst_stride > 0 and - * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< - * memcpy(dst_data, src_data, itemsize * dst_extent) - * else: - */ - __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); - if (__pyx_t_2) { - __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); - } - __pyx_t_3 = (__pyx_t_2 != 0); - __pyx_t_1 = __pyx_t_3; - __pyx_L5_bool_binop_done:; - - /* "View.MemoryView":1153 - * - * if ndim == 1: - * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< - * src_stride == itemsize == dst_stride): - * memcpy(dst_data, src_data, itemsize * dst_extent) - */ - if (__pyx_t_1) { - - /* "View.MemoryView":1155 - * if (src_stride > 0 and dst_stride > 0 and - * src_stride == itemsize == dst_stride): - * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< - * else: - * for i in range(dst_extent): - */ - (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); - - /* "View.MemoryView":1153 - * - * if ndim == 1: - * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< - * src_stride == itemsize == dst_stride): - * memcpy(dst_data, src_data, itemsize * dst_extent) - */ - goto __pyx_L4; - } - - /* "View.MemoryView":1157 - * memcpy(dst_data, src_data, itemsize * dst_extent) - * else: - * for i in range(dst_extent): # <<<<<<<<<<<<<< - * memcpy(dst_data, src_data, itemsize) - * src_data += src_stride - */ - /*else*/ { - __pyx_t_4 = __pyx_v_dst_extent; - __pyx_t_5 = __pyx_t_4; - for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { - __pyx_v_i = __pyx_t_6; - - /* "View.MemoryView":1158 - * else: - * for i in range(dst_extent): - * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< - * src_data += src_stride - * dst_data += dst_stride - */ - (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize)); - - /* "View.MemoryView":1159 - * for i in range(dst_extent): - * memcpy(dst_data, src_data, itemsize) - * src_data += src_stride # <<<<<<<<<<<<<< - * dst_data += dst_stride - * else: - */ - __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); - - /* "View.MemoryView":1160 - * memcpy(dst_data, src_data, itemsize) - * src_data += src_stride - * dst_data += dst_stride # <<<<<<<<<<<<<< - * else: - * for i in range(dst_extent): - */ - __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); - } - } - __pyx_L4:; - - /* "View.MemoryView":1152 - * cdef Py_ssize_t dst_stride = dst_strides[0] - * - * if ndim == 1: # <<<<<<<<<<<<<< - * if (src_stride > 0 and dst_stride > 0 and - * src_stride == itemsize == dst_stride): - */ - goto __pyx_L3; - } - - /* "View.MemoryView":1162 - * dst_data += dst_stride - * else: - * for i in range(dst_extent): # <<<<<<<<<<<<<< - * _copy_strided_to_strided(src_data, src_strides + 1, - * dst_data, dst_strides + 1, - */ - /*else*/ { - __pyx_t_4 = __pyx_v_dst_extent; - __pyx_t_5 = __pyx_t_4; - for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { - __pyx_v_i = __pyx_t_6; - - /* "View.MemoryView":1163 - * else: - * for i in range(dst_extent): - * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< - * dst_data, dst_strides + 1, - * src_shape + 1, dst_shape + 1, - */ - _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); - - /* "View.MemoryView":1167 - * src_shape + 1, dst_shape + 1, - * ndim - 1, itemsize) - * src_data += src_stride # <<<<<<<<<<<<<< - * dst_data += dst_stride - * - */ - __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); - - /* "View.MemoryView":1168 - * ndim - 1, itemsize) - * src_data += src_stride - * dst_data += dst_stride # <<<<<<<<<<<<<< - * - * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, - */ - __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); - } - } - __pyx_L3:; - - /* "View.MemoryView":1140 - * - * @cython.cdivision(True) - * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< - * char *dst_data, Py_ssize_t *dst_strides, - * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, - */ - - /* function exit code */ -} - -/* "View.MemoryView":1170 - * dst_data += dst_stride - * - * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< - * __Pyx_memviewslice *dst, - * int ndim, size_t itemsize) nogil: - */ - -static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { - - /* "View.MemoryView":1173 - * __Pyx_memviewslice *dst, - * int ndim, size_t itemsize) nogil: - * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< - * src.shape, dst.shape, ndim, itemsize) - * - */ - _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); - - /* "View.MemoryView":1170 - * dst_data += dst_stride - * - * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< - * __Pyx_memviewslice *dst, - * int ndim, size_t itemsize) nogil: - */ - - /* function exit code */ -} - -/* "View.MemoryView":1177 - * - * @cname('__pyx_memoryview_slice_get_size') - * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< - * "Return the size of the memory occupied by the slice in number of bytes" - * cdef Py_ssize_t shape, size = src.memview.view.itemsize - */ - -static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { - Py_ssize_t __pyx_v_shape; - Py_ssize_t __pyx_v_size; - Py_ssize_t __pyx_r; - Py_ssize_t __pyx_t_1; - Py_ssize_t *__pyx_t_2; - Py_ssize_t *__pyx_t_3; - Py_ssize_t *__pyx_t_4; - - /* "View.MemoryView":1179 - * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: - * "Return the size of the memory occupied by the slice in number of bytes" - * cdef Py_ssize_t shape, size = src.memview.view.itemsize # <<<<<<<<<<<<<< - * - * for shape in src.shape[:ndim]: - */ - __pyx_t_1 = __pyx_v_src->memview->view.itemsize; - __pyx_v_size = __pyx_t_1; - - /* "View.MemoryView":1181 - * cdef Py_ssize_t shape, size = src.memview.view.itemsize - * - * for shape in src.shape[:ndim]: # <<<<<<<<<<<<<< - * size *= shape - * - */ - __pyx_t_3 = (__pyx_v_src->shape + __pyx_v_ndim); - for (__pyx_t_4 = __pyx_v_src->shape; __pyx_t_4 < __pyx_t_3; __pyx_t_4++) { - __pyx_t_2 = __pyx_t_4; - __pyx_v_shape = (__pyx_t_2[0]); - - /* "View.MemoryView":1182 - * - * for shape in src.shape[:ndim]: - * size *= shape # <<<<<<<<<<<<<< - * - * return size - */ - __pyx_v_size = (__pyx_v_size * __pyx_v_shape); - } - - /* "View.MemoryView":1184 - * size *= shape - * - * return size # <<<<<<<<<<<<<< - * - * @cname('__pyx_fill_contig_strides_array') - */ - __pyx_r = __pyx_v_size; - goto __pyx_L0; - - /* "View.MemoryView":1177 - * - * @cname('__pyx_memoryview_slice_get_size') - * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< - * "Return the size of the memory occupied by the slice in number of bytes" - * cdef Py_ssize_t shape, size = src.memview.view.itemsize - */ - - /* function exit code */ - __pyx_L0:; - return __pyx_r; -} - -/* "View.MemoryView":1187 - * - * @cname('__pyx_fill_contig_strides_array') - * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< - * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, - * int ndim, char order) nogil: - */ - -static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { - int __pyx_v_idx; - Py_ssize_t __pyx_r; - int __pyx_t_1; - int __pyx_t_2; - int __pyx_t_3; - int __pyx_t_4; - - /* "View.MemoryView":1196 - * cdef int idx - * - * if order == 'F': # <<<<<<<<<<<<<< - * for idx in range(ndim): - * strides[idx] = stride - */ - __pyx_t_1 = ((__pyx_v_order == 'F') != 0); - if (__pyx_t_1) { - - /* "View.MemoryView":1197 - * - * if order == 'F': - * for idx in range(ndim): # <<<<<<<<<<<<<< - * strides[idx] = stride - * stride *= shape[idx] - */ - __pyx_t_2 = __pyx_v_ndim; - __pyx_t_3 = __pyx_t_2; - for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { - __pyx_v_idx = __pyx_t_4; - - /* "View.MemoryView":1198 - * if order == 'F': - * for idx in range(ndim): - * strides[idx] = stride # <<<<<<<<<<<<<< - * stride *= shape[idx] - * else: - */ - (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; - 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#if PY_VERSION_HEX < 0x030800b4 - 0, /*tp_print*/ - #endif - #if PY_VERSION_HEX >= 0x030800b4 - 0, /*tp_vectorcall_offset*/ - #endif - 0, /*tp_getattr*/ - 0, /*tp_setattr*/ - #if PY_MAJOR_VERSION < 3 - 0, /*tp_compare*/ - #endif - #if PY_MAJOR_VERSION >= 3 - 0, /*tp_as_async*/ - #endif - 0, /*tp_repr*/ - 0, /*tp_as_number*/ - 0, /*tp_as_sequence*/ - 0, /*tp_as_mapping*/ - 0, /*tp_hash*/ - 0, /*tp_call*/ - 0, /*tp_str*/ - 0, /*tp_getattro*/ - 0, /*tp_setattro*/ - 0, /*tp_as_buffer*/ - Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ - "Abstract splitter class.\n\n Splitters are called by tree builders to find the best splits on both\n sparse and dense data, one split at a time.\n ", /*tp_doc*/ - __pyx_tp_traverse_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_traverse*/ - __pyx_tp_clear_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_clear*/ - 0, /*tp_richcompare*/ - 0, /*tp_weaklistoffset*/ - 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struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *p; - PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_Splitter(t, a, k); - if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *)o); - p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter*)__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter; - p->X.data = NULL; - p->X.memview = NULL; - return o; -} - -static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter(PyObject *o) { - struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *p = (struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *)o; - #if CYTHON_USE_TP_FINALIZE - if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { - if (PyObject_CallFinalizerFromDealloc(o)) return; - } - #endif - PyObject_GC_UnTrack(o); - __PYX_XDEC_MEMVIEW(&p->X, 1); - PyObject_GC_Track(o); - __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_Splitter(o); -} - -static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter[] = { - {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter_1__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter_3__setstate_cython__, METH_O, 0}, - {0, 0, 0, 0} -}; - -static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter = { - PyVarObject_HEAD_INIT(0, 0) - "stpredictions.models.OK3._splitter.BaseDenseSplitter", /*tp_name*/ - sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter), /*tp_basicsize*/ - 0, /*tp_itemsize*/ - __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter, /*tp_dealloc*/ - #if PY_VERSION_HEX < 0x030800b4 - 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0, /*tp_members*/ - 0, /*tp_getset*/ - 0, /*tp_base*/ - 0, /*tp_dict*/ - 0, /*tp_descr_get*/ - 0, /*tp_descr_set*/ - 0, /*tp_dictoffset*/ - 0, /*tp_init*/ - 0, /*tp_alloc*/ - __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter, /*tp_new*/ - 0, /*tp_free*/ - 0, /*tp_is_gc*/ - 0, /*tp_bases*/ - 0, /*tp_mro*/ - 0, /*tp_cache*/ - 0, /*tp_subclasses*/ - 0, /*tp_weaklist*/ - 0, /*tp_del*/ - 0, /*tp_version_tag*/ - #if PY_VERSION_HEX >= 0x030400a1 - 0, /*tp_finalize*/ - #endif - #if PY_VERSION_HEX >= 0x030800b1 - 0, /*tp_vectorcall*/ - #endif - #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 - 0, /*tp_print*/ - #endif -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter __pyx_vtable_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter; - -static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *p; - 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__pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter, /*tp_dealloc*/ - #if PY_VERSION_HEX < 0x030800b4 - 0, /*tp_print*/ - #endif - #if PY_VERSION_HEX >= 0x030800b4 - 0, /*tp_vectorcall_offset*/ - #endif - 0, /*tp_getattr*/ - 0, /*tp_setattr*/ - #if PY_MAJOR_VERSION < 3 - 0, /*tp_compare*/ - #endif - #if PY_MAJOR_VERSION >= 3 - 0, /*tp_as_async*/ - #endif - 0, /*tp_repr*/ - 0, /*tp_as_number*/ - 0, /*tp_as_sequence*/ - 0, /*tp_as_mapping*/ - 0, /*tp_hash*/ - 0, /*tp_call*/ - 0, /*tp_str*/ - 0, /*tp_getattro*/ - 0, /*tp_setattro*/ - 0, /*tp_as_buffer*/ - Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ - "Splitter for finding a random split, using the sparse data.", /*tp_doc*/ - __pyx_tp_traverse_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_traverse*/ - __pyx_tp_clear_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_clear*/ - 0, /*tp_richcompare*/ - 0, /*tp_weaklistoffset*/ - 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0, /*tp_richcompare*/ - 0, /*tp_weaklistoffset*/ - 0, /*tp_iter*/ - 0, /*tp_iternext*/ - __pyx_methods_memoryview, /*tp_methods*/ - 0, /*tp_members*/ - __pyx_getsets_memoryview, /*tp_getset*/ - 0, /*tp_base*/ - 0, /*tp_dict*/ - 0, /*tp_descr_get*/ - 0, /*tp_descr_set*/ - 0, /*tp_dictoffset*/ - 0, /*tp_init*/ - 0, /*tp_alloc*/ - __pyx_tp_new_memoryview, /*tp_new*/ - 0, /*tp_free*/ - 0, /*tp_is_gc*/ - 0, /*tp_bases*/ - 0, /*tp_mro*/ - 0, /*tp_cache*/ - 0, /*tp_subclasses*/ - 0, /*tp_weaklist*/ - 0, /*tp_del*/ - 0, /*tp_version_tag*/ - #if PY_VERSION_HEX >= 0x030400a1 - 0, /*tp_finalize*/ - #endif - #if PY_VERSION_HEX >= 0x030800b1 - 0, /*tp_vectorcall*/ - #endif - #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 - 0, /*tp_print*/ - #endif -}; -static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice; - -static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_memoryviewslice_obj *p; - PyObject *o = __pyx_tp_new_memoryview(t, a, k); - 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- if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { - PyObject *r = PyList_GET_ITEM(o, n); - Py_INCREF(r); - return r; - } - } - else if (PyTuple_CheckExact(o)) { - Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); - if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { - PyObject *r = PyTuple_GET_ITEM(o, n); - Py_INCREF(r); - return r; - } - } else { - PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; - if (likely(m && m->sq_item)) { - if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { - Py_ssize_t l = m->sq_length(o); - if (likely(l >= 0)) { - i += l; - } else { - if (!PyErr_ExceptionMatches(PyExc_OverflowError)) - return NULL; - PyErr_Clear(); - } - } - return m->sq_item(o, i); - } - } -#else - if (is_list || PySequence_Check(o)) { - return PySequence_GetItem(o, i); - } -#endif - return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); -} - -/* MemviewSliceInit */ -static int -__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, - int ndim, - __Pyx_memviewslice *memviewslice, - int memview_is_new_reference) -{ - __Pyx_RefNannyDeclarations - int i, retval=-1; - Py_buffer *buf = &memview->view; - __Pyx_RefNannySetupContext("init_memviewslice", 0); - if (unlikely(memviewslice->memview || memviewslice->data)) { - PyErr_SetString(PyExc_ValueError, - "memviewslice is already initialized!"); - goto fail; - } - if (buf->strides) { - for (i = 0; i < ndim; i++) { - memviewslice->strides[i] = buf->strides[i]; - } - } else { - Py_ssize_t stride = buf->itemsize; - for (i = ndim - 1; i >= 0; i--) { - memviewslice->strides[i] = stride; - stride *= buf->shape[i]; - } - } - for (i = 0; i < ndim; i++) { - memviewslice->shape[i] = buf->shape[i]; - if (buf->suboffsets) { - memviewslice->suboffsets[i] = buf->suboffsets[i]; - } else { - memviewslice->suboffsets[i] = -1; - } - } - memviewslice->memview = memview; - memviewslice->data = (char *)buf->buf; - if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { - Py_INCREF(memview); - } - retval = 0; - goto no_fail; -fail: - memviewslice->memview = 0; - memviewslice->data = 0; - retval = -1; -no_fail: - __Pyx_RefNannyFinishContext(); - return retval; -} -#ifndef Py_NO_RETURN -#define Py_NO_RETURN -#endif -static void __pyx_fatalerror(const char *fmt, ...) Py_NO_RETURN { - va_list vargs; - char msg[200]; -#ifdef HAVE_STDARG_PROTOTYPES - va_start(vargs, fmt); -#else - va_start(vargs); -#endif - vsnprintf(msg, 200, fmt, vargs); - va_end(vargs); - Py_FatalError(msg); -} -static CYTHON_INLINE int -__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, - PyThread_type_lock lock) -{ - int result; - PyThread_acquire_lock(lock, 1); - result = (*acquisition_count)++; - PyThread_release_lock(lock); - return result; -} -static CYTHON_INLINE int -__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, - PyThread_type_lock lock) -{ - int result; - PyThread_acquire_lock(lock, 1); - result = (*acquisition_count)--; - PyThread_release_lock(lock); - return result; -} -static CYTHON_INLINE void -__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) -{ - int first_time; - struct __pyx_memoryview_obj *memview = memslice->memview; - if (unlikely(!memview || (PyObject *) memview == Py_None)) - return; - if (unlikely(__pyx_get_slice_count(memview) < 0)) - __pyx_fatalerror("Acquisition count is %d (line %d)", - __pyx_get_slice_count(memview), lineno); - first_time = __pyx_add_acquisition_count(memview) == 0; - if (unlikely(first_time)) { - if (have_gil) { - Py_INCREF((PyObject *) memview); - } else { - PyGILState_STATE _gilstate = PyGILState_Ensure(); - Py_INCREF((PyObject *) memview); - PyGILState_Release(_gilstate); - } - } -} -static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, - int have_gil, int lineno) { - int last_time; - struct __pyx_memoryview_obj *memview = memslice->memview; - if (unlikely(!memview || (PyObject *) memview == Py_None)) { - memslice->memview = NULL; - return; - } - if (unlikely(__pyx_get_slice_count(memview) <= 0)) - __pyx_fatalerror("Acquisition count is %d (line %d)", - __pyx_get_slice_count(memview), lineno); - last_time = __pyx_sub_acquisition_count(memview) == 1; - memslice->data = NULL; - if (unlikely(last_time)) { - if (have_gil) { - Py_CLEAR(memslice->memview); - } else { - PyGILState_STATE _gilstate = PyGILState_Ensure(); - Py_CLEAR(memslice->memview); - PyGILState_Release(_gilstate); - } - } else { - memslice->memview = NULL; - } -} - -/* ExtTypeTest */ -static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - if (likely(__Pyx_TypeCheck(obj, type))) - return 1; - PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", - Py_TYPE(obj)->tp_name, type->tp_name); - return 0; -} - -/* PyErrFetchRestore */ -#if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - tmp_type = tstate->curexc_type; - tmp_value = tstate->curexc_value; - tmp_tb = tstate->curexc_traceback; - tstate->curexc_type = type; - tstate->curexc_value = value; - tstate->curexc_traceback = tb; - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - *type = tstate->curexc_type; - *value = tstate->curexc_value; - *tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -} -#endif - -/* RaiseException */ -#if PY_MAJOR_VERSION < 3 -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, - CYTHON_UNUSED PyObject *cause) { - __Pyx_PyThreadState_declare - Py_XINCREF(type); - if (!value || value == Py_None) - value = NULL; - else - Py_INCREF(value); - if (!tb || tb == Py_None) - tb = NULL; - else { - Py_INCREF(tb); - if (!PyTraceBack_Check(tb)) { - PyErr_SetString(PyExc_TypeError, - "raise: arg 3 must be a traceback or None"); - goto raise_error; - } - } - if (PyType_Check(type)) { -#if CYTHON_COMPILING_IN_PYPY - if (!value) { - Py_INCREF(Py_None); - value = Py_None; - } -#endif - PyErr_NormalizeException(&type, &value, &tb); - } else { - if (value) { - PyErr_SetString(PyExc_TypeError, - "instance exception may not have a separate value"); - goto raise_error; - } - value = type; - type = (PyObject*) Py_TYPE(type); - Py_INCREF(type); - if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { - PyErr_SetString(PyExc_TypeError, - "raise: exception class must be a subclass of BaseException"); - goto raise_error; - } - } - __Pyx_PyThreadState_assign - __Pyx_ErrRestore(type, value, tb); - return; -raise_error: - Py_XDECREF(value); - Py_XDECREF(type); - Py_XDECREF(tb); - return; -} -#else -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { - PyObject* owned_instance = NULL; - if (tb == Py_None) { - tb = 0; - } else if (tb && !PyTraceBack_Check(tb)) { - PyErr_SetString(PyExc_TypeError, - "raise: arg 3 must be a traceback or None"); - goto bad; - } - if (value == Py_None) - value = 0; - if (PyExceptionInstance_Check(type)) { - if (value) { - PyErr_SetString(PyExc_TypeError, - "instance exception may not have a separate value"); - goto bad; - } - value = type; - type = (PyObject*) Py_TYPE(value); - } else if (PyExceptionClass_Check(type)) { - PyObject *instance_class = NULL; - if (value && PyExceptionInstance_Check(value)) { - instance_class = (PyObject*) Py_TYPE(value); - if (instance_class != type) { - int is_subclass = PyObject_IsSubclass(instance_class, type); - if (!is_subclass) { - instance_class = NULL; - } else if (unlikely(is_subclass == -1)) { - goto bad; - } else { - type = instance_class; - } - } - } - if (!instance_class) { - PyObject *args; - if (!value) - args = PyTuple_New(0); - else if (PyTuple_Check(value)) { - Py_INCREF(value); - args = value; - } else - args = PyTuple_Pack(1, value); - if (!args) - goto bad; - owned_instance = PyObject_Call(type, args, NULL); - Py_DECREF(args); - if (!owned_instance) - goto bad; - value = owned_instance; - if (!PyExceptionInstance_Check(value)) { - PyErr_Format(PyExc_TypeError, - "calling %R should have returned an instance of " - "BaseException, not %R", - type, Py_TYPE(value)); - goto bad; - } - } - } else { - PyErr_SetString(PyExc_TypeError, - "raise: exception class must be a subclass of BaseException"); - goto bad; - } - if (cause) { - PyObject *fixed_cause; - if (cause == Py_None) { - fixed_cause = NULL; - } else if (PyExceptionClass_Check(cause)) { - fixed_cause = PyObject_CallObject(cause, NULL); - if (fixed_cause == NULL) - goto bad; - } else if (PyExceptionInstance_Check(cause)) { - fixed_cause = cause; - Py_INCREF(fixed_cause); - } else { - PyErr_SetString(PyExc_TypeError, - "exception causes must derive from " - "BaseException"); - goto bad; - } - PyException_SetCause(value, fixed_cause); - } - PyErr_SetObject(type, value); - if (tb) { -#if CYTHON_COMPILING_IN_PYPY - PyObject *tmp_type, *tmp_value, *tmp_tb; - PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); - Py_INCREF(tb); - PyErr_Restore(tmp_type, tmp_value, tb); - Py_XDECREF(tmp_tb); -#else - PyThreadState *tstate = __Pyx_PyThreadState_Current; - PyObject* tmp_tb = tstate->curexc_traceback; - if (tb != tmp_tb) { - Py_INCREF(tb); - tstate->curexc_traceback = tb; - Py_XDECREF(tmp_tb); - } -#endif - } -bad: - Py_XDECREF(owned_instance); - return; -} -#endif - -/* PyObjectCallMethO */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { - PyObject *self, *result; - PyCFunction cfunc; - cfunc = PyCFunction_GET_FUNCTION(func); - self = PyCFunction_GET_SELF(func); - if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) - return NULL; - result = cfunc(self, arg); - Py_LeaveRecursiveCall(); - if (unlikely(!result) && unlikely(!PyErr_Occurred())) { - PyErr_SetString( - PyExc_SystemError, - "NULL result without error in PyObject_Call"); - } - return result; -} -#endif - -/* PyObjectCallNoArg */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { -#if CYTHON_FAST_PYCALL - if (PyFunction_Check(func)) { - return __Pyx_PyFunction_FastCall(func, NULL, 0); - } -#endif -#ifdef __Pyx_CyFunction_USED - if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) -#else - if (likely(PyCFunction_Check(func))) -#endif - { - if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { - return __Pyx_PyObject_CallMethO(func, NULL); - } - } - return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); -} -#endif - -/* PyObjectCallOneArg */ -#if CYTHON_COMPILING_IN_CPYTHON -static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *result; - PyObject *args = PyTuple_New(1); - if (unlikely(!args)) return NULL; - Py_INCREF(arg); - PyTuple_SET_ITEM(args, 0, arg); - result = __Pyx_PyObject_Call(func, args, NULL); - Py_DECREF(args); - return result; -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { -#if CYTHON_FAST_PYCALL - if (PyFunction_Check(func)) { - return __Pyx_PyFunction_FastCall(func, &arg, 1); - } -#endif - if (likely(PyCFunction_Check(func))) { - if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { - return __Pyx_PyObject_CallMethO(func, arg); -#if CYTHON_FAST_PYCCALL - } else if (__Pyx_PyFastCFunction_Check(func)) { - return __Pyx_PyCFunction_FastCall(func, &arg, 1); -#endif - } - } - return __Pyx__PyObject_CallOneArg(func, arg); -} -#else -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *result; - PyObject *args = PyTuple_Pack(1, arg); - if (unlikely(!args)) return NULL; - result = __Pyx_PyObject_Call(func, args, NULL); - Py_DECREF(args); - return result; -} -#endif - -/* PyDictVersioning */ -#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS -static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { - PyObject *dict = Py_TYPE(obj)->tp_dict; - return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; -} -static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { - PyObject **dictptr = NULL; - Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; - if (offset) { -#if CYTHON_COMPILING_IN_CPYTHON - dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); -#else - dictptr = _PyObject_GetDictPtr(obj); -#endif - } - return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; -} -static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { - PyObject *dict = Py_TYPE(obj)->tp_dict; - if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) - return 0; - return obj_dict_version == __Pyx_get_object_dict_version(obj); -} -#endif - -/* GetModuleGlobalName */ -#if CYTHON_USE_DICT_VERSIONS -static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) -#else -static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) -#endif -{ - PyObject *result; -#if !CYTHON_AVOID_BORROWED_REFS -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 - result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); - __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return __Pyx_NewRef(result); - } else if (unlikely(PyErr_Occurred())) { - return NULL; - } -#else - result = PyDict_GetItem(__pyx_d, name); - __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return __Pyx_NewRef(result); - } -#endif -#else - result = PyObject_GetItem(__pyx_d, name); - __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return __Pyx_NewRef(result); - } - PyErr_Clear(); -#endif - return __Pyx_GetBuiltinName(name); -} - -/* IsLittleEndian */ -static CYTHON_INLINE int __Pyx_Is_Little_Endian(void) -{ - union { - uint32_t u32; - uint8_t u8[4]; - } S; - S.u32 = 0x01020304; - return S.u8[0] == 4; -} - -/* BufferFormatCheck */ -static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, - __Pyx_BufFmt_StackElem* stack, - __Pyx_TypeInfo* type) { - stack[0].field = &ctx->root; - stack[0].parent_offset = 0; - ctx->root.type = type; - ctx->root.name = "buffer dtype"; - ctx->root.offset = 0; - ctx->head = stack; - ctx->head->field = &ctx->root; - ctx->fmt_offset = 0; - ctx->head->parent_offset = 0; - ctx->new_packmode = '@'; - ctx->enc_packmode = '@'; - ctx->new_count = 1; - ctx->enc_count = 0; - ctx->enc_type = 0; - ctx->is_complex = 0; - ctx->is_valid_array = 0; - ctx->struct_alignment = 0; - while (type->typegroup == 'S') { - ++ctx->head; - ctx->head->field = type->fields; - ctx->head->parent_offset = 0; - type = type->fields->type; - } -} -static int __Pyx_BufFmt_ParseNumber(const char** ts) { - int count; - const char* t = *ts; - if (*t < '0' || *t > '9') { - return -1; - } else { - count = *t++ - '0'; - while (*t >= '0' && *t <= '9') { - count *= 10; - count += *t++ - '0'; - } - } - *ts = t; - return count; -} -static int __Pyx_BufFmt_ExpectNumber(const char **ts) { - int number = __Pyx_BufFmt_ParseNumber(ts); - if (number == -1) - PyErr_Format(PyExc_ValueError,\ - "Does not understand character buffer dtype format string ('%c')", **ts); - return number; -} -static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { - PyErr_Format(PyExc_ValueError, - "Unexpected format string character: '%c'", ch); -} -static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { - switch (ch) { - case '?': return "'bool'"; - case 'c': return "'char'"; - case 'b': return "'signed char'"; - case 'B': return "'unsigned char'"; - case 'h': return "'short'"; - case 'H': return "'unsigned short'"; - case 'i': return "'int'"; - case 'I': return "'unsigned int'"; - case 'l': return "'long'"; - case 'L': return "'unsigned long'"; - case 'q': return "'long long'"; - case 'Q': return "'unsigned long long'"; - case 'f': return (is_complex ? "'complex float'" : "'float'"); - case 'd': return (is_complex ? "'complex double'" : "'double'"); - case 'g': return (is_complex ? "'complex long double'" : "'long double'"); - case 'T': return "a struct"; - case 'O': return "Python object"; - case 'P': return "a pointer"; - case 's': case 'p': return "a string"; - case 0: return "end"; - default: return "unparseable format string"; - } -} -static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return 2; - case 'i': case 'I': case 'l': case 'L': return 4; - case 'q': case 'Q': return 8; - case 'f': return (is_complex ? 8 : 4); - case 'd': return (is_complex ? 16 : 8); - case 'g': { - PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); - return 0; - } - case 'O': case 'P': return sizeof(void*); - default: - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } -} -static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return sizeof(short); - case 'i': case 'I': return sizeof(int); - case 'l': case 'L': return sizeof(long); - #ifdef HAVE_LONG_LONG - case 'q': case 'Q': return sizeof(PY_LONG_LONG); - #endif - case 'f': return sizeof(float) * (is_complex ? 2 : 1); - case 'd': return sizeof(double) * (is_complex ? 2 : 1); - case 'g': return sizeof(long double) * (is_complex ? 2 : 1); - case 'O': case 'P': return sizeof(void*); - default: { - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } - } -} -typedef struct { char c; short x; } __Pyx_st_short; -typedef struct { char c; int x; } __Pyx_st_int; -typedef struct { char c; long x; } __Pyx_st_long; -typedef struct { char c; float x; } __Pyx_st_float; -typedef struct { char c; double x; } __Pyx_st_double; -typedef struct { char c; long double x; } __Pyx_st_longdouble; -typedef struct { char c; void *x; } __Pyx_st_void_p; -#ifdef HAVE_LONG_LONG -typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; -#endif -static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); - case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); - case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); -#ifdef HAVE_LONG_LONG - case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); -#endif - case 'f': return sizeof(__Pyx_st_float) - sizeof(float); - case 'd': return sizeof(__Pyx_st_double) - sizeof(double); - case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); - case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); - default: - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } -} -/* These are for computing the padding at the end of the struct to align - on the first member of the struct. This will probably the same as above, - but we don't have any guarantees. - */ -typedef struct { short x; char c; } __Pyx_pad_short; -typedef struct { int x; char c; } __Pyx_pad_int; -typedef struct { long x; char c; } __Pyx_pad_long; -typedef struct { float x; char c; } __Pyx_pad_float; -typedef struct { double x; char c; } __Pyx_pad_double; -typedef struct { long double x; char c; } __Pyx_pad_longdouble; -typedef struct { void *x; char c; } __Pyx_pad_void_p; -#ifdef HAVE_LONG_LONG -typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; -#endif -static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); - case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); - case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); -#ifdef HAVE_LONG_LONG - case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); -#endif - case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); - case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); - case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); - case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); - default: - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } -} -static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { - switch (ch) { - case 'c': - return 'H'; - case 'b': case 'h': case 'i': - case 'l': case 'q': case 's': case 'p': - return 'I'; - case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': - return 'U'; - case 'f': case 'd': case 'g': - return (is_complex ? 'C' : 'R'); - case 'O': - return 'O'; - case 'P': - return 'P'; - default: { - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } - } -} -static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { - if (ctx->head == NULL || ctx->head->field == &ctx->root) { - const char* expected; - const char* quote; - if (ctx->head == NULL) { - expected = "end"; - quote = ""; - } else { - expected = ctx->head->field->type->name; - quote = "'"; - } - PyErr_Format(PyExc_ValueError, - "Buffer dtype mismatch, expected %s%s%s but got %s", - quote, expected, quote, - __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); - } else { - __Pyx_StructField* field = ctx->head->field; - __Pyx_StructField* parent = (ctx->head - 1)->field; - PyErr_Format(PyExc_ValueError, - "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", - field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), - parent->type->name, field->name); - } -} -static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { - char group; - size_t size, offset, arraysize = 1; - if (ctx->enc_type == 0) return 0; - if (ctx->head->field->type->arraysize[0]) { - int i, ndim = 0; - if (ctx->enc_type == 's' || ctx->enc_type == 'p') { - ctx->is_valid_array = ctx->head->field->type->ndim == 1; - ndim = 1; - if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { - PyErr_Format(PyExc_ValueError, - "Expected a dimension of size %zu, got %zu", - ctx->head->field->type->arraysize[0], ctx->enc_count); - return -1; - } - } - if (!ctx->is_valid_array) { - PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", - ctx->head->field->type->ndim, ndim); - return -1; - } - for (i = 0; i < ctx->head->field->type->ndim; i++) { - arraysize *= ctx->head->field->type->arraysize[i]; - } - ctx->is_valid_array = 0; - ctx->enc_count = 1; - } - group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); - do { - __Pyx_StructField* field = ctx->head->field; - __Pyx_TypeInfo* type = field->type; - if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { - size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); - } else { - size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); - } - if (ctx->enc_packmode == '@') { - size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); - size_t align_mod_offset; - if (align_at == 0) return -1; - align_mod_offset = ctx->fmt_offset % align_at; - if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; - if (ctx->struct_alignment == 0) - ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, - ctx->is_complex); - } - if (type->size != size || type->typegroup != group) { - if (type->typegroup == 'C' && type->fields != NULL) { - size_t parent_offset = ctx->head->parent_offset + field->offset; - ++ctx->head; - ctx->head->field = type->fields; - ctx->head->parent_offset = parent_offset; - continue; - } - if ((type->typegroup == 'H' || group == 'H') && type->size == size) { - } else { - __Pyx_BufFmt_RaiseExpected(ctx); - return -1; - } - } - offset = ctx->head->parent_offset + field->offset; - if (ctx->fmt_offset != offset) { - PyErr_Format(PyExc_ValueError, - "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", - (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); - return -1; - } - ctx->fmt_offset += size; - if (arraysize) - ctx->fmt_offset += (arraysize - 1) * size; - --ctx->enc_count; - while (1) { - if (field == &ctx->root) { - ctx->head = NULL; - if (ctx->enc_count != 0) { - __Pyx_BufFmt_RaiseExpected(ctx); - return -1; - } - break; - } - ctx->head->field = ++field; - if (field->type == NULL) { - --ctx->head; - field = ctx->head->field; - continue; - } else if (field->type->typegroup == 'S') { - size_t parent_offset = ctx->head->parent_offset + field->offset; - if (field->type->fields->type == NULL) continue; - field = field->type->fields; - ++ctx->head; - ctx->head->field = field; - ctx->head->parent_offset = parent_offset; - break; - } else { - break; - } - } - } while (ctx->enc_count); - ctx->enc_type = 0; - ctx->is_complex = 0; - return 0; -} -static PyObject * -__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) -{ - const char *ts = *tsp; - int i = 0, number, ndim; - ++ts; - if (ctx->new_count != 1) { - PyErr_SetString(PyExc_ValueError, - "Cannot handle repeated arrays in format string"); - return NULL; - } - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ndim = ctx->head->field->type->ndim; - while (*ts && *ts != ')') { - switch (*ts) { - case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; - default: break; - } - number = __Pyx_BufFmt_ExpectNumber(&ts); - if (number == -1) return NULL; - if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) - return PyErr_Format(PyExc_ValueError, - "Expected a dimension of size %zu, got %d", - ctx->head->field->type->arraysize[i], number); - if (*ts != ',' && *ts != ')') - return PyErr_Format(PyExc_ValueError, - "Expected a comma in format string, got '%c'", *ts); - if (*ts == ',') ts++; - i++; - } - if (i != ndim) - return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", - ctx->head->field->type->ndim, i); - if (!*ts) { - PyErr_SetString(PyExc_ValueError, - "Unexpected end of format string, expected ')'"); - return NULL; - } - ctx->is_valid_array = 1; - ctx->new_count = 1; - *tsp = ++ts; - return Py_None; -} -static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { - int got_Z = 0; - while (1) { - switch(*ts) { - case 0: - if (ctx->enc_type != 0 && ctx->head == NULL) { - __Pyx_BufFmt_RaiseExpected(ctx); - return NULL; - } - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - if (ctx->head != NULL) { - __Pyx_BufFmt_RaiseExpected(ctx); - return NULL; - } - return ts; - case ' ': - case '\r': - case '\n': - ++ts; - break; - case '<': - if (!__Pyx_Is_Little_Endian()) { - PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); - return NULL; - } - ctx->new_packmode = '='; - ++ts; - break; - case '>': - case '!': - if (__Pyx_Is_Little_Endian()) { - PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); - return NULL; - } - ctx->new_packmode = '='; - ++ts; - break; - case '=': - case '@': - case '^': - ctx->new_packmode = *ts++; - break; - case 'T': - { - const char* ts_after_sub; - size_t i, struct_count = ctx->new_count; - size_t struct_alignment = ctx->struct_alignment; - ctx->new_count = 1; - ++ts; - if (*ts != '{') { - PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); - return NULL; - } - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->enc_type = 0; - ctx->enc_count = 0; - ctx->struct_alignment = 0; - ++ts; - ts_after_sub = ts; - for (i = 0; i != struct_count; ++i) { - ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); - if (!ts_after_sub) return NULL; - } - ts = ts_after_sub; - if (struct_alignment) ctx->struct_alignment = struct_alignment; - } - break; - case '}': - { - size_t alignment = ctx->struct_alignment; - ++ts; - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->enc_type = 0; - if (alignment && ctx->fmt_offset % alignment) { - ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); - } - } - return ts; - case 'x': - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->fmt_offset += ctx->new_count; - ctx->new_count = 1; - ctx->enc_count = 0; - ctx->enc_type = 0; - ctx->enc_packmode = ctx->new_packmode; - ++ts; - break; - case 'Z': - got_Z = 1; - ++ts; - if (*ts != 'f' && *ts != 'd' && *ts != 'g') { - __Pyx_BufFmt_RaiseUnexpectedChar('Z'); - return NULL; - } - CYTHON_FALLTHROUGH; - case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': - case 'l': case 'L': case 'q': case 'Q': - case 'f': case 'd': case 'g': - case 'O': case 'p': - if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && - (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { - ctx->enc_count += ctx->new_count; - ctx->new_count = 1; - got_Z = 0; - ++ts; - break; - } - CYTHON_FALLTHROUGH; - case 's': - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->enc_count = ctx->new_count; - ctx->enc_packmode = ctx->new_packmode; - ctx->enc_type = *ts; - ctx->is_complex = got_Z; - ++ts; - ctx->new_count = 1; - got_Z = 0; - break; - case ':': - ++ts; - while(*ts != ':') ++ts; - ++ts; - break; - case '(': - if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; - break; - default: - { - int number = __Pyx_BufFmt_ExpectNumber(&ts); - if (number == -1) return NULL; - ctx->new_count = (size_t)number; - } - } - } -} - -/* BufferGetAndValidate */ - static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { - if (unlikely(info->buf == NULL)) return; - if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; - __Pyx_ReleaseBuffer(info); -} -static void __Pyx_ZeroBuffer(Py_buffer* buf) { - buf->buf = NULL; - buf->obj = NULL; - buf->strides = __Pyx_zeros; - buf->shape = __Pyx_zeros; - buf->suboffsets = __Pyx_minusones; -} -static int __Pyx__GetBufferAndValidate( - Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, - int nd, int cast, __Pyx_BufFmt_StackElem* stack) -{ - buf->buf = NULL; - if (unlikely(__Pyx_GetBuffer(obj, buf, flags) == -1)) { - __Pyx_ZeroBuffer(buf); - return -1; - } - if (unlikely(buf->ndim != nd)) { - PyErr_Format(PyExc_ValueError, - "Buffer has wrong number of dimensions (expected %d, got %d)", - nd, buf->ndim); - goto fail; - } - if (!cast) { - __Pyx_BufFmt_Context ctx; - __Pyx_BufFmt_Init(&ctx, stack, dtype); - if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; - } - if (unlikely((size_t)buf->itemsize != dtype->size)) { - PyErr_Format(PyExc_ValueError, - "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", - buf->itemsize, (buf->itemsize > 1) ? "s" : "", - dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); - goto fail; - } - if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; - return 0; -fail:; - __Pyx_SafeReleaseBuffer(buf); - return -1; -} - -/* GetTopmostException */ - #if CYTHON_USE_EXC_INFO_STACK -static _PyErr_StackItem * -__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) -{ - _PyErr_StackItem *exc_info = tstate->exc_info; - while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && - exc_info->previous_item != NULL) - { - exc_info = exc_info->previous_item; - } - return exc_info; -} -#endif - -/* SaveResetException */ - #if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); - *type = exc_info->exc_type; - *value = exc_info->exc_value; - *tb = exc_info->exc_traceback; - #else - *type = tstate->exc_type; - *value = tstate->exc_value; - *tb = tstate->exc_traceback; - #endif - Py_XINCREF(*type); - Py_XINCREF(*value); - Py_XINCREF(*tb); -} -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = type; - exc_info->exc_value = value; - exc_info->exc_traceback = tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = type; - tstate->exc_value = value; - tstate->exc_traceback = tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -#endif - -/* PyErrExceptionMatches */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; icurexc_type; - if (exc_type == err) return 1; - if (unlikely(!exc_type)) return 0; - if (unlikely(PyTuple_Check(err))) - return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); - return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); -} -#endif - -/* GetException */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) -#endif -{ - PyObject *local_type, *local_value, *local_tb; -#if CYTHON_FAST_THREAD_STATE - PyObject *tmp_type, *tmp_value, *tmp_tb; - local_type = tstate->curexc_type; - local_value = tstate->curexc_value; - local_tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -#else - PyErr_Fetch(&local_type, &local_value, &local_tb); -#endif - PyErr_NormalizeException(&local_type, &local_value, &local_tb); -#if CYTHON_FAST_THREAD_STATE - if (unlikely(tstate->curexc_type)) -#else - if (unlikely(PyErr_Occurred())) -#endif - goto bad; - #if PY_MAJOR_VERSION >= 3 - if (local_tb) { - if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) - goto bad; - } - #endif - Py_XINCREF(local_tb); - Py_XINCREF(local_type); - Py_XINCREF(local_value); - *type = local_type; - *value = local_value; - *tb = local_tb; -#if CYTHON_FAST_THREAD_STATE - #if CYTHON_USE_EXC_INFO_STACK - { - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = local_type; - exc_info->exc_value = local_value; - exc_info->exc_traceback = local_tb; - } - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = local_type; - tstate->exc_value = local_value; - tstate->exc_traceback = local_tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#else - PyErr_SetExcInfo(local_type, local_value, local_tb); -#endif - return 0; -bad: - *type = 0; - *value = 0; - *tb = 0; - Py_XDECREF(local_type); - Py_XDECREF(local_value); - Py_XDECREF(local_tb); - return -1; -} - -/* PyObjectCall2Args */ - static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { - PyObject *args, *result = NULL; - #if CYTHON_FAST_PYCALL - if (PyFunction_Check(function)) { - PyObject *args[2] = {arg1, arg2}; - return __Pyx_PyFunction_FastCall(function, args, 2); - } - #endif - #if CYTHON_FAST_PYCCALL - if (__Pyx_PyFastCFunction_Check(function)) { - PyObject *args[2] = {arg1, arg2}; - return __Pyx_PyCFunction_FastCall(function, args, 2); - } - #endif - args = PyTuple_New(2); - if (unlikely(!args)) goto done; - Py_INCREF(arg1); - PyTuple_SET_ITEM(args, 0, arg1); - Py_INCREF(arg2); - PyTuple_SET_ITEM(args, 1, arg2); - Py_INCREF(function); - result = __Pyx_PyObject_Call(function, args, NULL); - Py_DECREF(args); - Py_DECREF(function); -done: - return result; -} - -/* BytesEquals */ - static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { -#if CYTHON_COMPILING_IN_PYPY - return PyObject_RichCompareBool(s1, s2, equals); -#else - if (s1 == s2) { - return (equals == Py_EQ); - } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { - const char *ps1, *ps2; - Py_ssize_t length = PyBytes_GET_SIZE(s1); - if (length != PyBytes_GET_SIZE(s2)) - return (equals == Py_NE); - ps1 = PyBytes_AS_STRING(s1); - ps2 = PyBytes_AS_STRING(s2); - if (ps1[0] != ps2[0]) { - return (equals == Py_NE); - } else if (length == 1) { - return (equals == Py_EQ); - } else { - int result; -#if CYTHON_USE_UNICODE_INTERNALS - Py_hash_t hash1, hash2; - hash1 = ((PyBytesObject*)s1)->ob_shash; - hash2 = ((PyBytesObject*)s2)->ob_shash; - if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { - return (equals == Py_NE); - } -#endif - result = memcmp(ps1, ps2, (size_t)length); - return (equals == Py_EQ) ? (result == 0) : (result != 0); - } - } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { - return (equals == Py_NE); - } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { - return (equals == Py_NE); - } else { - int result; - PyObject* py_result = PyObject_RichCompare(s1, s2, equals); - if (!py_result) - return -1; - result = __Pyx_PyObject_IsTrue(py_result); - Py_DECREF(py_result); - return result; - } -#endif -} - -/* UnicodeEquals */ - static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { -#if CYTHON_COMPILING_IN_PYPY - return PyObject_RichCompareBool(s1, s2, equals); -#else -#if PY_MAJOR_VERSION < 3 - PyObject* owned_ref = NULL; -#endif - int s1_is_unicode, s2_is_unicode; - if (s1 == s2) { - goto return_eq; - } - s1_is_unicode = PyUnicode_CheckExact(s1); - s2_is_unicode = PyUnicode_CheckExact(s2); -#if PY_MAJOR_VERSION < 3 - if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { - owned_ref = PyUnicode_FromObject(s2); - if (unlikely(!owned_ref)) - return -1; - s2 = owned_ref; - s2_is_unicode = 1; - } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { - owned_ref = PyUnicode_FromObject(s1); - if (unlikely(!owned_ref)) - return -1; - s1 = owned_ref; - s1_is_unicode = 1; - } else if (((!s2_is_unicode) & (!s1_is_unicode))) { - return __Pyx_PyBytes_Equals(s1, s2, equals); - } -#endif - if (s1_is_unicode & s2_is_unicode) { - Py_ssize_t length; - int kind; - void *data1, *data2; - if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) - return -1; - length = __Pyx_PyUnicode_GET_LENGTH(s1); - if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { - goto return_ne; - } -#if CYTHON_USE_UNICODE_INTERNALS - { - Py_hash_t hash1, hash2; - #if CYTHON_PEP393_ENABLED - hash1 = ((PyASCIIObject*)s1)->hash; - hash2 = ((PyASCIIObject*)s2)->hash; - #else - hash1 = ((PyUnicodeObject*)s1)->hash; - hash2 = ((PyUnicodeObject*)s2)->hash; - #endif - if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { - goto return_ne; - } - } -#endif - kind = __Pyx_PyUnicode_KIND(s1); - if (kind != __Pyx_PyUnicode_KIND(s2)) { - goto return_ne; - } - data1 = __Pyx_PyUnicode_DATA(s1); - data2 = __Pyx_PyUnicode_DATA(s2); - if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { - goto return_ne; - } else if (length == 1) { - goto return_eq; - } else { - int result = memcmp(data1, data2, (size_t)(length * kind)); - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - return (equals == Py_EQ) ? (result == 0) : (result != 0); - } - } else if ((s1 == Py_None) & s2_is_unicode) { - goto return_ne; - } else if ((s2 == Py_None) & s1_is_unicode) { - goto return_ne; - } else { - int result; - PyObject* py_result = PyObject_RichCompare(s1, s2, equals); - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - if (!py_result) - return -1; - result = __Pyx_PyObject_IsTrue(py_result); - Py_DECREF(py_result); - return result; - } -return_eq: - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - return (equals == Py_EQ); -return_ne: - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - return (equals == Py_NE); -#endif -} - -/* GetAttr */ - static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { -#if CYTHON_USE_TYPE_SLOTS -#if PY_MAJOR_VERSION >= 3 - if (likely(PyUnicode_Check(n))) -#else - if (likely(PyString_Check(n))) -#endif - return __Pyx_PyObject_GetAttrStr(o, n); -#endif - return PyObject_GetAttr(o, n); -} - -/* ObjectGetItem */ - #if CYTHON_USE_TYPE_SLOTS -static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { - PyObject *runerr; - Py_ssize_t key_value; - PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; - if (unlikely(!(m && m->sq_item))) { - PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); - return NULL; - } - key_value = __Pyx_PyIndex_AsSsize_t(index); - if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { - return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); - } - if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { - PyErr_Clear(); - PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); - } - return NULL; -} -static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { - PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; - if (likely(m && m->mp_subscript)) { - return m->mp_subscript(obj, key); - } - return __Pyx_PyObject_GetIndex(obj, key); -} -#endif - -/* decode_c_string */ - static CYTHON_INLINE PyObject* __Pyx_decode_c_string( - const char* cstring, Py_ssize_t start, Py_ssize_t stop, - const char* encoding, const char* errors, - PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { - Py_ssize_t length; - if (unlikely((start < 0) | (stop < 0))) { - size_t slen = strlen(cstring); - if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { - PyErr_SetString(PyExc_OverflowError, - "c-string too long to convert to Python"); - return NULL; - } - length = (Py_ssize_t) slen; - if (start < 0) { - start += length; - if (start < 0) - start = 0; - } - if (stop < 0) - stop += length; - } - if (unlikely(stop <= start)) - return __Pyx_NewRef(__pyx_empty_unicode); - length = stop - start; - cstring += start; - if (decode_func) { - return decode_func(cstring, length, errors); - } else { - return PyUnicode_Decode(cstring, length, encoding, errors); - } -} - -/* GetAttr3 */ - static PyObject *__Pyx_GetAttr3Default(PyObject *d) { - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) - return NULL; - __Pyx_PyErr_Clear(); - Py_INCREF(d); - return d; -} -static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) { - PyObject *r = __Pyx_GetAttr(o, n); - return (likely(r)) ? r : __Pyx_GetAttr3Default(d); -} - -/* RaiseTooManyValuesToUnpack */ - static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { - PyErr_Format(PyExc_ValueError, - "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); -} - -/* RaiseNeedMoreValuesToUnpack */ - static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { - PyErr_Format(PyExc_ValueError, - "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", - index, (index == 1) ? "" : "s"); -} - -/* RaiseNoneIterError */ - static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { - PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); -} - -/* SwapException */ - #if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = *type; - exc_info->exc_value = *value; - exc_info->exc_traceback = *tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = *type; - tstate->exc_value = *value; - tstate->exc_traceback = *tb; - #endif - *type = tmp_type; - *value = tmp_value; - *tb = tmp_tb; -} -#else -static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); - PyErr_SetExcInfo(*type, *value, *tb); - *type = tmp_type; - *value = tmp_value; - *tb = tmp_tb; -} -#endif - -/* Import */ - static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { - PyObject *empty_list = 0; - PyObject *module = 0; - PyObject *global_dict = 0; - PyObject *empty_dict = 0; - PyObject *list; - #if PY_MAJOR_VERSION < 3 - PyObject *py_import; - py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); - if (!py_import) - goto bad; - #endif - if (from_list) - list = from_list; - else { - empty_list = PyList_New(0); - if (!empty_list) - goto bad; - list = empty_list; - } - global_dict = PyModule_GetDict(__pyx_m); - if (!global_dict) - goto bad; - empty_dict = PyDict_New(); - if (!empty_dict) - goto bad; - { - #if PY_MAJOR_VERSION >= 3 - if (level == -1) { - if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, 1); - if (!module) { - if (!PyErr_ExceptionMatches(PyExc_ImportError)) - goto bad; - PyErr_Clear(); - } - } - level = 0; - } - #endif - if (!module) { - #if PY_MAJOR_VERSION < 3 - PyObject *py_level = PyInt_FromLong(level); - if (!py_level) - goto bad; - module = PyObject_CallFunctionObjArgs(py_import, - name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); - Py_DECREF(py_level); - #else - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, level); - #endif - } - } -bad: - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(py_import); - #endif - Py_XDECREF(empty_list); - Py_XDECREF(empty_dict); - return module; -} - -/* FastTypeChecks */ - #if CYTHON_COMPILING_IN_CPYTHON -static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { - while (a) { - a = a->tp_base; - if (a == b) - return 1; - } - return b == &PyBaseObject_Type; -} -static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { - PyObject *mro; - if (a == b) return 1; - mro = a->tp_mro; - if (likely(mro)) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(mro); - for (i = 0; i < n; i++) { - if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) - return 1; - } - return 0; - } - return __Pyx_InBases(a, b); -} -#if PY_MAJOR_VERSION == 2 -static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { - PyObject *exception, *value, *tb; - int res; - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - __Pyx_ErrFetch(&exception, &value, &tb); - res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; - if (unlikely(res == -1)) { - PyErr_WriteUnraisable(err); - res = 0; - } - if (!res) { - res = PyObject_IsSubclass(err, exc_type2); - if (unlikely(res == -1)) { - PyErr_WriteUnraisable(err); - res = 0; - } - } - __Pyx_ErrRestore(exception, value, tb); - return res; -} -#else -static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { - int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; - if (!res) { - res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); - } - return res; -} -#endif -static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - assert(PyExceptionClass_Check(exc_type)); - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; i= 0 || (x^b) >= 0)) - return PyInt_FromLong(x); - return PyLong_Type.tp_as_number->nb_add(op1, op2); - } - #endif - #if CYTHON_USE_PYLONG_INTERNALS - if (likely(PyLong_CheckExact(op1))) { - const long b = intval; - long a, x; -#ifdef HAVE_LONG_LONG - const PY_LONG_LONG llb = intval; - PY_LONG_LONG lla, llx; -#endif - const digit* digits = ((PyLongObject*)op1)->ob_digit; - const Py_ssize_t size = Py_SIZE(op1); - if (likely(__Pyx_sst_abs(size) <= 1)) { - a = likely(size) ? digits[0] : 0; - if (size == -1) a = -a; - } else { - switch (size) { - case -2: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case 2: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case -3: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case 3: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case -4: - if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case 4: - if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - default: return PyLong_Type.tp_as_number->nb_add(op1, op2); - } - } - x = a + b; - return PyLong_FromLong(x); -#ifdef HAVE_LONG_LONG - long_long: - llx = lla + llb; - return PyLong_FromLongLong(llx); -#endif - - - } - #endif - if (PyFloat_CheckExact(op1)) { - const long b = intval; - double a = PyFloat_AS_DOUBLE(op1); - double result; - PyFPE_START_PROTECT("add", return NULL) - result = ((double)a) + (double)b; - PyFPE_END_PROTECT(result) - return PyFloat_FromDouble(result); - } - return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); -} -#endif - -/* None */ - static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { - PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); -} - -/* ImportFrom */ - static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { - PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); - if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { - PyErr_Format(PyExc_ImportError, - #if PY_MAJOR_VERSION < 3 - "cannot import name %.230s", PyString_AS_STRING(name)); - #else - "cannot import name %S", name); - #endif - } - return value; -} - -/* HasAttr */ - static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) { - PyObject *r; - if (unlikely(!__Pyx_PyBaseString_Check(n))) { - PyErr_SetString(PyExc_TypeError, - "hasattr(): attribute name must be string"); - return -1; - } - r = __Pyx_GetAttr(o, n); - if (unlikely(!r)) { - PyErr_Clear(); - return 0; - } else { - Py_DECREF(r); - return 1; - } -} - -/* PyObject_GenericGetAttrNoDict */ - #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 -static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) { - PyErr_Format(PyExc_AttributeError, -#if PY_MAJOR_VERSION >= 3 - "'%.50s' object has no attribute '%U'", - tp->tp_name, attr_name); -#else - "'%.50s' object has no attribute '%.400s'", - tp->tp_name, PyString_AS_STRING(attr_name)); -#endif - return NULL; -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) { - PyObject *descr; - PyTypeObject *tp = Py_TYPE(obj); - if (unlikely(!PyString_Check(attr_name))) { - return PyObject_GenericGetAttr(obj, attr_name); - } - assert(!tp->tp_dictoffset); - descr = _PyType_Lookup(tp, attr_name); - if (unlikely(!descr)) { - return __Pyx_RaiseGenericGetAttributeError(tp, attr_name); - } - Py_INCREF(descr); - #if PY_MAJOR_VERSION < 3 - if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS))) - #endif - { - descrgetfunc f = Py_TYPE(descr)->tp_descr_get; - if (unlikely(f)) { - PyObject *res = f(descr, obj, (PyObject *)tp); - Py_DECREF(descr); - return res; - } - } - return descr; -} -#endif - -/* PyObject_GenericGetAttr */ - #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 -static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) { - if (unlikely(Py_TYPE(obj)->tp_dictoffset)) { - return PyObject_GenericGetAttr(obj, attr_name); - } - return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name); -} -#endif - -/* SetVTable */ - static int __Pyx_SetVtable(PyObject *dict, void *vtable) { -#if PY_VERSION_HEX >= 0x02070000 - PyObject *ob = PyCapsule_New(vtable, 0, 0); -#else - PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); -#endif - if (!ob) - goto bad; - if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) - goto bad; - Py_DECREF(ob); - return 0; -bad: - Py_XDECREF(ob); - return -1; -} - -/* PyObjectGetAttrStrNoError */ - static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) - __Pyx_PyErr_Clear(); -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { - PyObject *result; -#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 - PyTypeObject* tp = Py_TYPE(obj); - if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { - return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); - } -#endif - result = __Pyx_PyObject_GetAttrStr(obj, attr_name); - if (unlikely(!result)) { - __Pyx_PyObject_GetAttrStr_ClearAttributeError(); - } - return result; -} - -/* SetupReduce */ - static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { - int ret; - PyObject *name_attr; - name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2); - if (likely(name_attr)) { - ret = PyObject_RichCompareBool(name_attr, name, Py_EQ); - } else { - ret = -1; - } - if (unlikely(ret < 0)) { - PyErr_Clear(); - ret = 0; - } - Py_XDECREF(name_attr); - return ret; -} -static int __Pyx_setup_reduce(PyObject* type_obj) { - int ret = 0; - PyObject *object_reduce = NULL; - PyObject *object_reduce_ex = NULL; - PyObject *reduce = NULL; - PyObject *reduce_ex = NULL; - PyObject *reduce_cython = NULL; - PyObject *setstate = NULL; - PyObject *setstate_cython = NULL; -#if CYTHON_USE_PYTYPE_LOOKUP - if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; -#else - if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; -#endif -#if CYTHON_USE_PYTYPE_LOOKUP - object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; -#else - object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; -#endif - reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; - if (reduce_ex == object_reduce_ex) { -#if CYTHON_USE_PYTYPE_LOOKUP - object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; -#else - object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; -#endif - reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; - if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { - reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); - if (likely(reduce_cython)) { - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - } else if (reduce == object_reduce || PyErr_Occurred()) { - goto __PYX_BAD; - } - setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); - if (!setstate) PyErr_Clear(); - if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { - setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); - if (likely(setstate_cython)) { - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - } else if (!setstate || PyErr_Occurred()) { - goto __PYX_BAD; - } - } - PyType_Modified((PyTypeObject*)type_obj); - } - } - goto __PYX_GOOD; -__PYX_BAD: - if (!PyErr_Occurred()) - PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); - ret = -1; -__PYX_GOOD: -#if !CYTHON_USE_PYTYPE_LOOKUP - Py_XDECREF(object_reduce); - Py_XDECREF(object_reduce_ex); -#endif - Py_XDECREF(reduce); - Py_XDECREF(reduce_ex); - Py_XDECREF(reduce_cython); - Py_XDECREF(setstate); - Py_XDECREF(setstate_cython); - return ret; -} - -/* TypeImport */ - #ifndef __PYX_HAVE_RT_ImportType -#define __PYX_HAVE_RT_ImportType -static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, - size_t size, enum __Pyx_ImportType_CheckSize check_size) -{ - PyObject *result = 0; - char warning[200]; - Py_ssize_t basicsize; -#ifdef Py_LIMITED_API - PyObject *py_basicsize; -#endif - result = PyObject_GetAttrString(module, class_name); - if (!result) - goto bad; - if (!PyType_Check(result)) { - PyErr_Format(PyExc_TypeError, - "%.200s.%.200s is not a type object", - module_name, class_name); - goto bad; - } -#ifndef Py_LIMITED_API - basicsize = ((PyTypeObject *)result)->tp_basicsize; -#else - py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); - if (!py_basicsize) - goto bad; - basicsize = PyLong_AsSsize_t(py_basicsize); - Py_DECREF(py_basicsize); - py_basicsize = 0; - if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) - goto bad; -#endif - if ((size_t)basicsize < size) { - PyErr_Format(PyExc_ValueError, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - goto bad; - } - if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { - PyErr_Format(PyExc_ValueError, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - goto bad; - } - else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { - PyOS_snprintf(warning, sizeof(warning), - "%s.%s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; - } - return (PyTypeObject *)result; -bad: - Py_XDECREF(result); - return NULL; -} -#endif - -/* GetVTable */ - static void* __Pyx_GetVtable(PyObject *dict) { - void* ptr; - PyObject *ob = PyObject_GetItem(dict, __pyx_n_s_pyx_vtable); - if (!ob) - goto bad; -#if PY_VERSION_HEX >= 0x02070000 - ptr = PyCapsule_GetPointer(ob, 0); -#else - ptr = PyCObject_AsVoidPtr(ob); -#endif - if (!ptr && !PyErr_Occurred()) - PyErr_SetString(PyExc_RuntimeError, "invalid vtable found for imported type"); - Py_DECREF(ob); - return ptr; -bad: - Py_XDECREF(ob); - return NULL; -} - -/* CLineInTraceback */ - #ifndef CYTHON_CLINE_IN_TRACEBACK -static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { - PyObject *use_cline; - PyObject *ptype, *pvalue, *ptraceback; -#if CYTHON_COMPILING_IN_CPYTHON - PyObject **cython_runtime_dict; -#endif - if (unlikely(!__pyx_cython_runtime)) { - return c_line; - } - __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); -#if CYTHON_COMPILING_IN_CPYTHON - cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); - if (likely(cython_runtime_dict)) { - __PYX_PY_DICT_LOOKUP_IF_MODIFIED( - use_cline, *cython_runtime_dict, - __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) - } else -#endif - { - PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); - if (use_cline_obj) { - use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; - Py_DECREF(use_cline_obj); - } else { - PyErr_Clear(); - use_cline = NULL; - } - } - if (!use_cline) { - c_line = 0; - PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); - } - else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { - c_line = 0; - } - __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); - return c_line; -} -#endif - -/* CodeObjectCache */ - static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { - int start = 0, mid = 0, end = count - 1; - if (end >= 0 && code_line > entries[end].code_line) { - return count; - } - while (start < end) { - mid = start + (end - start) / 2; - if (code_line < entries[mid].code_line) { - end = mid; - } else if (code_line > entries[mid].code_line) { - start = mid + 1; - } else { - return mid; - } - } - if (code_line <= entries[mid].code_line) { - return mid; - } else { - return mid + 1; - } -} -static PyCodeObject *__pyx_find_code_object(int code_line) { - PyCodeObject* code_object; - int pos; - if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { - return NULL; - } - pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); - if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { - return NULL; - } - code_object = __pyx_code_cache.entries[pos].code_object; - Py_INCREF(code_object); - return code_object; -} -static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { - int pos, i; - __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; - if (unlikely(!code_line)) { - return; - } - if (unlikely(!entries)) { - entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); - if (likely(entries)) { - __pyx_code_cache.entries = entries; - __pyx_code_cache.max_count = 64; - __pyx_code_cache.count = 1; - entries[0].code_line = code_line; - entries[0].code_object = code_object; - Py_INCREF(code_object); - } - return; - } - pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); - if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { - PyCodeObject* tmp = entries[pos].code_object; - entries[pos].code_object = code_object; - Py_DECREF(tmp); - return; - } - if (__pyx_code_cache.count == __pyx_code_cache.max_count) { - int new_max = __pyx_code_cache.max_count + 64; - entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( - __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); - if (unlikely(!entries)) { - return; - } - __pyx_code_cache.entries = entries; - __pyx_code_cache.max_count = new_max; - } - for (i=__pyx_code_cache.count; i>pos; i--) { - entries[i] = entries[i-1]; - } - entries[pos].code_line = code_line; - entries[pos].code_object = code_object; - __pyx_code_cache.count++; - Py_INCREF(code_object); -} - -/* AddTraceback */ - #include "compile.h" -#include "frameobject.h" -#include "traceback.h" -static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( - const char *funcname, int c_line, - int py_line, const char *filename) { - PyCodeObject *py_code = 0; - PyObject *py_srcfile = 0; - PyObject *py_funcname = 0; - #if PY_MAJOR_VERSION < 3 - py_srcfile = PyString_FromString(filename); - #else - py_srcfile = PyUnicode_FromString(filename); - #endif - if (!py_srcfile) goto bad; - if (c_line) { - #if PY_MAJOR_VERSION < 3 - py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); - #else - py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); - #endif - } - else { - #if PY_MAJOR_VERSION < 3 - py_funcname = PyString_FromString(funcname); - #else - py_funcname = PyUnicode_FromString(funcname); - #endif - } - if (!py_funcname) goto bad; - py_code = __Pyx_PyCode_New( - 0, - 0, - 0, - 0, - 0, - __pyx_empty_bytes, /*PyObject *code,*/ - __pyx_empty_tuple, /*PyObject *consts,*/ - __pyx_empty_tuple, /*PyObject *names,*/ - __pyx_empty_tuple, /*PyObject *varnames,*/ - __pyx_empty_tuple, /*PyObject *freevars,*/ - __pyx_empty_tuple, /*PyObject *cellvars,*/ - py_srcfile, /*PyObject *filename,*/ - py_funcname, /*PyObject *name,*/ - py_line, - __pyx_empty_bytes /*PyObject *lnotab*/ - ); - Py_DECREF(py_srcfile); - Py_DECREF(py_funcname); - return py_code; -bad: - Py_XDECREF(py_srcfile); - Py_XDECREF(py_funcname); - return NULL; -} -static void __Pyx_AddTraceback(const char *funcname, int c_line, - int py_line, const char *filename) { - PyCodeObject *py_code = 0; - PyFrameObject *py_frame = 0; - PyThreadState *tstate = __Pyx_PyThreadState_Current; - if (c_line) { - c_line = __Pyx_CLineForTraceback(tstate, c_line); - } - py_code = __pyx_find_code_object(c_line ? -c_line : py_line); - if (!py_code) { - py_code = __Pyx_CreateCodeObjectForTraceback( - funcname, c_line, py_line, filename); - if (!py_code) goto bad; - __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); - } - py_frame = PyFrame_New( - tstate, /*PyThreadState *tstate,*/ - py_code, /*PyCodeObject *code,*/ - __pyx_d, /*PyObject *globals,*/ - 0 /*PyObject *locals*/ - ); - if (!py_frame) goto bad; - __Pyx_PyFrame_SetLineNumber(py_frame, py_line); - PyTraceBack_Here(py_frame); -bad: - Py_XDECREF(py_code); - Py_XDECREF(py_frame); -} - -#if PY_MAJOR_VERSION < 3 -static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { - if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); - PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); - return -1; -} -static void __Pyx_ReleaseBuffer(Py_buffer *view) { - PyObject *obj = view->obj; - if (!obj) return; - if (PyObject_CheckBuffer(obj)) { - PyBuffer_Release(view); - return; - } - if ((0)) {} - view->obj = NULL; - Py_DECREF(obj); -} -#endif - - - /* MemviewSliceIsContig */ - static int -__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) -{ - int i, index, step, start; - Py_ssize_t itemsize = mvs.memview->view.itemsize; - if (order == 'F') { - step = 1; - start = 0; - } else { - step = -1; - start = ndim - 1; - } - for (i = 0; i < ndim; i++) { - index = start + step * i; - if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) - return 0; - itemsize *= mvs.shape[index]; - } - return 1; -} - -/* OverlappingSlices */ - static void -__pyx_get_array_memory_extents(__Pyx_memviewslice *slice, - void **out_start, void **out_end, - int ndim, size_t itemsize) -{ - char *start, *end; - int i; - start = end = slice->data; - for (i = 0; i < ndim; i++) { - Py_ssize_t stride = slice->strides[i]; - Py_ssize_t extent = slice->shape[i]; - if (extent == 0) { - *out_start = *out_end = start; - return; - } else { - if (stride > 0) - end += stride * (extent - 1); - else - start += stride * (extent - 1); - } - } - *out_start = start; - *out_end = end + itemsize; -} -static int -__pyx_slices_overlap(__Pyx_memviewslice *slice1, - __Pyx_memviewslice *slice2, - int ndim, size_t itemsize) -{ - void *start1, *end1, *start2, *end2; - __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); - __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); - return (start1 < end2) && (start2 < end1); -} - -/* Capsule */ - static CYTHON_INLINE PyObject * -__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) -{ - PyObject *cobj; -#if PY_VERSION_HEX >= 0x02070000 - cobj = PyCapsule_New(p, sig, NULL); -#else - cobj = PyCObject_FromVoidPtr(p, NULL); -#endif - return cobj; -} - -/* CIntFromPyVerify */ - #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ - __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) -#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ - __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) -#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ - {\ - func_type value = func_value;\ - if (sizeof(target_type) < sizeof(func_type)) {\ - if (unlikely(value != (func_type) (target_type) value)) {\ - func_type zero = 0;\ - if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ - return (target_type) -1;\ - if (is_unsigned && unlikely(value < zero))\ - goto raise_neg_overflow;\ - else\ - goto raise_overflow;\ - }\ - }\ - return (target_type) value;\ - } - -/* Declarations */ - #if CYTHON_CCOMPLEX - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - return ::std::complex< float >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - return x + y*(__pyx_t_float_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - __pyx_t_float_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ - #if CYTHON_CCOMPLEX -#else - static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - if (b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabsf(b.real) >= fabsf(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - float r = b.imag / b.real; - float s = (float)(1.0) / (b.real + b.imag * r); - return __pyx_t_float_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - float r = b.real / b.imag; - float s = (float)(1.0) / (b.imag + b.real * r); - return __pyx_t_float_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - if (b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - float denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_float_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { - __pyx_t_float_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { - __pyx_t_float_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrtf(z.real*z.real + z.imag*z.imag); - #else - return hypotf(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - float r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - float denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_float(a, a); - case 3: - z = __Pyx_c_prod_float(a, a); - return __Pyx_c_prod_float(z, a); - case 4: - z = __Pyx_c_prod_float(a, a); - return __Pyx_c_prod_float(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if (b.imag == 0) { - z.real = powf(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2f(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_float(a); - theta = atan2f(a.imag, a.real); - } - lnr = logf(r); - z_r = expf(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cosf(z_theta); - z.imag = z_r * sinf(z_theta); - return z; - } - #endif -#endif - -/* Declarations */ - #if CYTHON_CCOMPLEX - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - return ::std::complex< double >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - return x + y*(__pyx_t_double_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - __pyx_t_double_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ - #if CYTHON_CCOMPLEX -#else - static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - if (b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabs(b.real) >= fabs(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - double r = b.imag / b.real; - double s = (double)(1.0) / (b.real + b.imag * r); - return __pyx_t_double_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - double r = b.real / b.imag; - double s = (double)(1.0) / (b.imag + b.real * r); - return __pyx_t_double_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - if (b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - double denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_double_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { - __pyx_t_double_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { - __pyx_t_double_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrt(z.real*z.real + z.imag*z.imag); - #else - return hypot(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - double r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - double denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_double(a, a); - case 3: - z = __Pyx_c_prod_double(a, a); - return __Pyx_c_prod_double(z, a); - case 4: - z = __Pyx_c_prod_double(a, a); - return __Pyx_c_prod_double(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if (b.imag == 0) { - z.real = pow(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_double(a); - theta = atan2(a.imag, a.real); - } - lnr = log(r); - z_r = exp(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cos(z_theta); - z.imag = z_r * sin(z_theta); - return z; - } - #endif -#endif - -/* MemviewSliceCopyTemplate */ - static __Pyx_memviewslice -__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, - const char *mode, int ndim, - size_t sizeof_dtype, int contig_flag, - int dtype_is_object) -{ - __Pyx_RefNannyDeclarations - int i; - __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; - struct __pyx_memoryview_obj *from_memview = from_mvs->memview; - Py_buffer *buf = &from_memview->view; - PyObject *shape_tuple = NULL; - PyObject *temp_int = NULL; - struct __pyx_array_obj *array_obj = NULL; - struct __pyx_memoryview_obj *memview_obj = NULL; - __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); - for (i = 0; i < ndim; i++) { - if (unlikely(from_mvs->suboffsets[i] >= 0)) { - PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " - "indirect dimensions (axis %d)", i); - goto fail; - } - } - shape_tuple = PyTuple_New(ndim); - if (unlikely(!shape_tuple)) { - goto fail; - } - __Pyx_GOTREF(shape_tuple); - for(i = 0; i < ndim; i++) { - temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); - if(unlikely(!temp_int)) { - goto fail; - } else { - PyTuple_SET_ITEM(shape_tuple, i, temp_int); - temp_int = NULL; - } - } - array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); - if (unlikely(!array_obj)) { - goto fail; - } - __Pyx_GOTREF(array_obj); - memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( - (PyObject *) array_obj, contig_flag, - dtype_is_object, - from_mvs->memview->typeinfo); - if (unlikely(!memview_obj)) - goto fail; - if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) - goto fail; - if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, - dtype_is_object) < 0)) - goto fail; - goto no_fail; -fail: - __Pyx_XDECREF(new_mvs.memview); - new_mvs.memview = NULL; - new_mvs.data = NULL; -no_fail: - __Pyx_XDECREF(shape_tuple); - __Pyx_XDECREF(temp_int); - __Pyx_XDECREF(array_obj); - __Pyx_RefNannyFinishContext(); - return new_mvs; -} - -/* CIntFromPy */ - static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(Py_intptr_t) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (Py_intptr_t) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (Py_intptr_t) 0; - case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, digits[0]) - case 2: - if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) >= 2 * PyLong_SHIFT) { - return (Py_intptr_t) (((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) >= 3 * PyLong_SHIFT) { - return (Py_intptr_t) (((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) >= 4 * PyLong_SHIFT) { - return (Py_intptr_t) (((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (Py_intptr_t) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (Py_intptr_t) 0; - case -1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, +digits[0]) - case -2: - if (8 * sizeof(Py_intptr_t) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { - return (Py_intptr_t) (((Py_intptr_t)-1)*(((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { - return (Py_intptr_t) ((((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { - return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { - return (Py_intptr_t) ((((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { - return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { - return (Py_intptr_t) ((((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - } -#endif - if (sizeof(Py_intptr_t) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - Py_intptr_t val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (Py_intptr_t) -1; - } - } else { - Py_intptr_t val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (Py_intptr_t) -1; - val = __Pyx_PyInt_As_Py_intptr_t(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to Py_intptr_t"); - return (Py_intptr_t) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to Py_intptr_t"); - return (Py_intptr_t) -1; -} - -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const int neg_one = (int) -1, const_zero = (int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(int) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(int) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(int) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(int), - little, !is_unsigned); - } -} - -/* CIntFromPy */ - static CYTHON_INLINE npy_uint32 __Pyx_PyInt_As_npy_uint32(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const npy_uint32 neg_one = (npy_uint32) -1, const_zero = (npy_uint32) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(npy_uint32) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(npy_uint32, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (npy_uint32) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (npy_uint32) 0; - case 1: __PYX_VERIFY_RETURN_INT(npy_uint32, digit, digits[0]) - case 2: - if (8 * sizeof(npy_uint32) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_uint32) >= 2 * PyLong_SHIFT) { - return (npy_uint32) (((((npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(npy_uint32) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_uint32) >= 3 * PyLong_SHIFT) { - return (npy_uint32) (((((((npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(npy_uint32) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_uint32) >= 4 * PyLong_SHIFT) { - return (npy_uint32) (((((((((npy_uint32)digits[3]) << PyLong_SHIFT) | (npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (npy_uint32) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(npy_uint32) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_uint32) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (npy_uint32) 0; - case -1: __PYX_VERIFY_RETURN_INT(npy_uint32, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(npy_uint32, digit, +digits[0]) - case -2: - if (8 * sizeof(npy_uint32) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_uint32, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_uint32) - 1 > 2 * PyLong_SHIFT) { - return (npy_uint32) (((npy_uint32)-1)*(((((npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(npy_uint32) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_uint32) - 1 > 2 * PyLong_SHIFT) { - return (npy_uint32) ((((((npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(npy_uint32) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_uint32, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_uint32) - 1 > 3 * PyLong_SHIFT) { - return (npy_uint32) (((npy_uint32)-1)*(((((((npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(npy_uint32) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_uint32) - 1 > 3 * PyLong_SHIFT) { - return (npy_uint32) ((((((((npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(npy_uint32) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_uint32, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_uint32) - 1 > 4 * PyLong_SHIFT) { - return (npy_uint32) (((npy_uint32)-1)*(((((((((npy_uint32)digits[3]) << PyLong_SHIFT) | (npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(npy_uint32) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_uint32) - 1 > 4 * PyLong_SHIFT) { - return (npy_uint32) ((((((((((npy_uint32)digits[3]) << PyLong_SHIFT) | (npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); - } - } - break; - } -#endif - if (sizeof(npy_uint32) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_uint32) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - npy_uint32 val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (npy_uint32) -1; - } - } else { - npy_uint32 val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (npy_uint32) -1; - val = __Pyx_PyInt_As_npy_uint32(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to npy_uint32"); - return (npy_uint32) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to npy_uint32"); - return (npy_uint32) -1; -} - -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const long neg_one = (long) -1, const_zero = (long) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(long) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(long) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(long) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(long), - little, !is_unsigned); - } -} - -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(Py_intptr_t) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(Py_intptr_t) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(Py_intptr_t), - little, !is_unsigned); - } -} - -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_int32(npy_int32 value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(npy_int32) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(npy_int32) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(npy_int32) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(npy_int32), - little, !is_unsigned); - } -} - -/* CIntFromPy */ - static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(npy_int32) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(npy_int32, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (npy_int32) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (npy_int32) 0; - case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, digits[0]) - case 2: - if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) >= 2 * PyLong_SHIFT) { - return (npy_int32) (((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) >= 3 * PyLong_SHIFT) { - return (npy_int32) (((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) >= 4 * PyLong_SHIFT) { - return (npy_int32) (((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (npy_int32) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(npy_int32) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (npy_int32) 0; - case -1: __PYX_VERIFY_RETURN_INT(npy_int32, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, +digits[0]) - case -2: - if (8 * sizeof(npy_int32) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { - return (npy_int32) (((npy_int32)-1)*(((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { - return (npy_int32) ((((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { - return (npy_int32) (((npy_int32)-1)*(((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { - return (npy_int32) ((((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) { - return (npy_int32) (((npy_int32)-1)*(((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) { - return (npy_int32) ((((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - } -#endif - if (sizeof(npy_int32) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_int32, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_int32, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - npy_int32 val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (npy_int32) -1; - } - } else { - npy_int32 val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (npy_int32) -1; - val = __Pyx_PyInt_As_npy_int32(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to npy_int32"); - return (npy_int32) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to npy_int32"); - return (npy_int32) -1; -} - -/* CIntFromPy */ - static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const int neg_one = (int) -1, const_zero = (int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(int) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (int) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (int) 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) - case 2: - if (8 * sizeof(int) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { - return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(int) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { - return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(int) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { - return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (int) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(int) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (int) 0; - case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) - case -2: - if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(int) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(int) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(int) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { - return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - } -#endif - if (sizeof(int) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - int val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (int) -1; - } - } else { - int val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (int) -1; - val = __Pyx_PyInt_As_int(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to int"); - return (int) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to int"); - return (int) -1; -} - -/* CIntFromPy */ - static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const long neg_one = (long) -1, const_zero = (long) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(long) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (long) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (long) 0; - case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) - case 2: - if (8 * sizeof(long) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { - return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(long) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { - return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(long) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { - return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (long) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(long) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (long) 0; - case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) - case -2: - if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(long) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(long) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(long) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - } -#endif - if (sizeof(long) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - long val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (long) -1; - } - } else { - long val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (long) -1; - val = __Pyx_PyInt_As_long(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to long"); - return (long) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to long"); - return (long) -1; -} - -/* CIntFromPy */ - static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const char neg_one = (char) -1, const_zero = (char) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(char) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (char) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (char) 0; - case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) - case 2: - if (8 * sizeof(char) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { - return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(char) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { - return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(char) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { - return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (char) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(char) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (char) 0; - case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) - case -2: - if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { - return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(char) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { - return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { - return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(char) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { - return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { - return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(char) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { - return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - } -#endif - if (sizeof(char) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - char val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (char) -1; - } - } else { - char val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (char) -1; - val = __Pyx_PyInt_As_char(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to char"); - return (char) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to char"); - return (char) -1; -} - -/* TypeInfoCompare */ - static int -__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) -{ - int i; - if (!a || !b) - return 0; - if (a == b) - return 1; - if (a->size != b->size || a->typegroup != b->typegroup || - a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { - if (a->typegroup == 'H' || b->typegroup == 'H') { - return a->size == b->size; - } else { - return 0; - } - } - if (a->ndim) { - for (i = 0; i < a->ndim; i++) - if (a->arraysize[i] != b->arraysize[i]) - return 0; - } - if (a->typegroup == 'S') { - if (a->flags != b->flags) - return 0; - if (a->fields || b->fields) { - if (!(a->fields && b->fields)) - return 0; - for (i = 0; a->fields[i].type && b->fields[i].type; i++) { - __Pyx_StructField *field_a = a->fields + i; - __Pyx_StructField *field_b = b->fields + i; - if (field_a->offset != field_b->offset || - !__pyx_typeinfo_cmp(field_a->type, field_b->type)) - return 0; - } - return !a->fields[i].type && !b->fields[i].type; - } - } - return 1; -} - -/* MemviewSliceValidateAndInit */ - static int -__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) -{ - if (buf->shape[dim] <= 1) - return 1; - if (buf->strides) { - if (spec & __Pyx_MEMVIEW_CONTIG) { - if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { - if (unlikely(buf->strides[dim] != sizeof(void *))) { - PyErr_Format(PyExc_ValueError, - "Buffer is not indirectly contiguous " - "in dimension %d.", dim); - goto fail; - } - } else if (unlikely(buf->strides[dim] != buf->itemsize)) { - PyErr_SetString(PyExc_ValueError, - "Buffer and memoryview are not contiguous " - "in the same dimension."); - goto fail; - } - } - if (spec & __Pyx_MEMVIEW_FOLLOW) { - Py_ssize_t stride = buf->strides[dim]; - if (stride < 0) - stride = -stride; - if (unlikely(stride < buf->itemsize)) { - PyErr_SetString(PyExc_ValueError, - "Buffer and memoryview are not contiguous " - "in the same dimension."); - goto fail; - } - } - } else { - if (unlikely(spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1)) { - PyErr_Format(PyExc_ValueError, - "C-contiguous buffer is not contiguous in " - "dimension %d", dim); - goto fail; - } else if (unlikely(spec & (__Pyx_MEMVIEW_PTR))) { - PyErr_Format(PyExc_ValueError, - "C-contiguous buffer is not indirect in " - "dimension %d", dim); - goto fail; - } else if (unlikely(buf->suboffsets)) { - PyErr_SetString(PyExc_ValueError, - "Buffer exposes suboffsets but no strides"); - goto fail; - } - } - return 1; -fail: - return 0; -} -static int -__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) -{ - if (spec & __Pyx_MEMVIEW_DIRECT) { - if (unlikely(buf->suboffsets && buf->suboffsets[dim] >= 0)) { - PyErr_Format(PyExc_ValueError, - "Buffer not compatible with direct access " - "in dimension %d.", dim); - goto fail; - } - } - if (spec & __Pyx_MEMVIEW_PTR) { - if (unlikely(!buf->suboffsets || (buf->suboffsets[dim] < 0))) { - PyErr_Format(PyExc_ValueError, - "Buffer is not indirectly accessible " - "in dimension %d.", dim); - goto fail; - } - } - return 1; -fail: - return 0; -} -static int -__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) -{ - int i; - if (c_or_f_flag & __Pyx_IS_F_CONTIG) { - Py_ssize_t stride = 1; - for (i = 0; i < ndim; i++) { - if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { - PyErr_SetString(PyExc_ValueError, - "Buffer not fortran contiguous."); - goto fail; - } - stride = stride * buf->shape[i]; - } - } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { - Py_ssize_t stride = 1; - for (i = ndim - 1; i >- 1; i--) { - if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { - PyErr_SetString(PyExc_ValueError, - "Buffer not C contiguous."); - goto fail; - } - stride = stride * buf->shape[i]; - } - } - return 1; -fail: - return 0; -} -static int __Pyx_ValidateAndInit_memviewslice( - int *axes_specs, - int c_or_f_flag, - int buf_flags, - int ndim, - __Pyx_TypeInfo *dtype, - __Pyx_BufFmt_StackElem stack[], - __Pyx_memviewslice *memviewslice, - PyObject *original_obj) -{ - struct __pyx_memoryview_obj *memview, *new_memview; - __Pyx_RefNannyDeclarations - Py_buffer *buf; - int i, spec = 0, retval = -1; - __Pyx_BufFmt_Context ctx; - int from_memoryview = __pyx_memoryview_check(original_obj); - __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0); - if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) - original_obj)->typeinfo)) { - memview = (struct __pyx_memoryview_obj *) original_obj; - new_memview = NULL; - } else { - memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( - original_obj, buf_flags, 0, dtype); - new_memview = memview; - if (unlikely(!memview)) - goto fail; - } - buf = &memview->view; - if (unlikely(buf->ndim != ndim)) { - PyErr_Format(PyExc_ValueError, - "Buffer has wrong number of dimensions (expected %d, got %d)", - ndim, buf->ndim); - goto fail; - } - if (new_memview) { - __Pyx_BufFmt_Init(&ctx, stack, dtype); - if (unlikely(!__Pyx_BufFmt_CheckString(&ctx, buf->format))) goto fail; - } - if (unlikely((unsigned) buf->itemsize != dtype->size)) { - PyErr_Format(PyExc_ValueError, - "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " - "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", - buf->itemsize, - (buf->itemsize > 1) ? "s" : "", - dtype->name, - dtype->size, - (dtype->size > 1) ? "s" : ""); - goto fail; - } - if (buf->len > 0) { - for (i = 0; i < ndim; i++) { - spec = axes_specs[i]; - if (unlikely(!__pyx_check_strides(buf, i, ndim, spec))) - goto fail; - if (unlikely(!__pyx_check_suboffsets(buf, i, ndim, spec))) - goto fail; - } - if (unlikely(buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))) - goto fail; - } - if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, - new_memview != NULL) == -1)) { - goto fail; - } - retval = 0; - goto no_fail; -fail: - Py_XDECREF(new_memview); - retval = -1; -no_fail: - __Pyx_RefNannyFinishContext(); - return retval; -} - -/* ObjectToMemviewSlice */ - static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t__const__(PyObject *obj, int writable_flag) { - __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; - __Pyx_BufFmt_StackElem stack[1]; - int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; - int retcode; - if (obj == Py_None) { - result.memview = (struct __pyx_memoryview_obj *) Py_None; - return result; - } - retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, - PyBUF_RECORDS_RO | writable_flag, 2, - &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t__const__, stack, - &result, obj); - if (unlikely(retcode == -1)) - goto __pyx_fail; - return result; -__pyx_fail: - result.memview = NULL; - result.data = NULL; - return result; -} - -/* CheckBinaryVersion */ - static int __Pyx_check_binary_version(void) { - char ctversion[4], rtversion[4]; - PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); - PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); - if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { - char message[200]; - PyOS_snprintf(message, sizeof(message), - "compiletime version %s of module '%.100s' " - "does not match runtime version %s", - ctversion, __Pyx_MODULE_NAME, rtversion); - return PyErr_WarnEx(NULL, message, 1); - } - return 0; -} - -/* VoidPtrImport */ - #ifndef __PYX_HAVE_RT_ImportVoidPtr -#define __PYX_HAVE_RT_ImportVoidPtr -static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig) { - PyObject *d = 0; - PyObject *cobj = 0; - d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); - if (!d) - goto bad; - cobj = PyDict_GetItemString(d, name); - if (!cobj) { - PyErr_Format(PyExc_ImportError, - "%.200s does not export expected C variable %.200s", - PyModule_GetName(module), name); - goto bad; - } -#if PY_VERSION_HEX >= 0x02070000 - if (!PyCapsule_IsValid(cobj, sig)) { - PyErr_Format(PyExc_TypeError, - "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), name, sig, PyCapsule_GetName(cobj)); - goto bad; - } - *p = PyCapsule_GetPointer(cobj, sig); -#else - {const char *desc, *s1, *s2; - desc = (const char *)PyCObject_GetDesc(cobj); - if (!desc) - goto bad; - s1 = desc; s2 = sig; - while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } - if (*s1 != *s2) { - PyErr_Format(PyExc_TypeError, - "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), name, sig, desc); - goto bad; - } - *p = PyCObject_AsVoidPtr(cobj);} -#endif - if (!(*p)) - goto bad; - Py_DECREF(d); - return 0; -bad: - Py_XDECREF(d); - return -1; -} -#endif - -/* FunctionImport */ - #ifndef __PYX_HAVE_RT_ImportFunction -#define __PYX_HAVE_RT_ImportFunction -static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig) { - PyObject *d = 0; - PyObject *cobj = 0; - union { - void (*fp)(void); - void *p; - } tmp; - d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); - if (!d) - goto bad; - cobj = PyDict_GetItemString(d, funcname); - if (!cobj) { - PyErr_Format(PyExc_ImportError, - "%.200s does not export expected C function %.200s", - PyModule_GetName(module), funcname); - goto bad; - } -#if PY_VERSION_HEX >= 0x02070000 - if (!PyCapsule_IsValid(cobj, sig)) { - PyErr_Format(PyExc_TypeError, - "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), funcname, sig, PyCapsule_GetName(cobj)); - goto bad; - } - tmp.p = PyCapsule_GetPointer(cobj, sig); -#else - {const char *desc, *s1, *s2; - desc = (const char *)PyCObject_GetDesc(cobj); - if (!desc) - goto bad; - s1 = desc; s2 = sig; - while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } - if (*s1 != *s2) { - PyErr_Format(PyExc_TypeError, - "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), funcname, sig, desc); - goto bad; - } - tmp.p = PyCObject_AsVoidPtr(cobj);} -#endif - *f = tmp.fp; - if (!(*f)) - goto bad; - Py_DECREF(d); - return 0; -bad: - Py_XDECREF(d); - return -1; -} -#endif - -/* InitStrings */ - static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { - while (t->p) { - #if PY_MAJOR_VERSION < 3 - if (t->is_unicode) { - *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); - } else if (t->intern) { - *t->p = PyString_InternFromString(t->s); - } else { - *t->p = PyString_FromStringAndSize(t->s, t->n - 1); - } - #else - if (t->is_unicode | t->is_str) { - if (t->intern) { - *t->p = PyUnicode_InternFromString(t->s); - } else if (t->encoding) { - *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); - } else { - *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); - } - } else { - *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); - } - #endif - if (!*t->p) - return -1; - if (PyObject_Hash(*t->p) == -1) - return -1; - ++t; - } - return 0; -} - -static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { - return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); -} -static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { - Py_ssize_t ignore; - return __Pyx_PyObject_AsStringAndSize(o, &ignore); -} -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT -#if !CYTHON_PEP393_ENABLED -static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { - char* defenc_c; - PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); - if (!defenc) return NULL; - defenc_c = PyBytes_AS_STRING(defenc); -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - { - char* end = defenc_c + PyBytes_GET_SIZE(defenc); - char* c; - for (c = defenc_c; c < end; c++) { - if ((unsigned char) (*c) >= 128) { - PyUnicode_AsASCIIString(o); - return NULL; - } - } - } -#endif - *length = PyBytes_GET_SIZE(defenc); - return defenc_c; -} -#else -static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { - if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - if (likely(PyUnicode_IS_ASCII(o))) { - *length = PyUnicode_GET_LENGTH(o); - return PyUnicode_AsUTF8(o); - } else { - PyUnicode_AsASCIIString(o); - return NULL; - } -#else - return PyUnicode_AsUTF8AndSize(o, length); -#endif -} -#endif -#endif -static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT - if ( -#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - __Pyx_sys_getdefaultencoding_not_ascii && -#endif - PyUnicode_Check(o)) { - return __Pyx_PyUnicode_AsStringAndSize(o, length); 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#define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) - #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) -#endif -#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 - #define __Pyx_PyThreadState_Current PyThreadState_GET() -#elif PY_VERSION_HEX >= 0x03060000 - #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() -#elif PY_VERSION_HEX >= 0x03000000 - #define __Pyx_PyThreadState_Current PyThreadState_GET() -#else - #define __Pyx_PyThreadState_Current _PyThreadState_Current -#endif -#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) -#include "pythread.h" -#define Py_tss_NEEDS_INIT 0 -typedef int Py_tss_t; -static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { - *key = PyThread_create_key(); - return 0; -} -static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { - Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); - *key = Py_tss_NEEDS_INIT; - return key; -} -static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { - PyObject_Free(key); -} -static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { - return *key != Py_tss_NEEDS_INIT; -} -static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { - PyThread_delete_key(*key); - *key = Py_tss_NEEDS_INIT; -} -static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { - return PyThread_set_key_value(*key, value); -} -static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { - return PyThread_get_key_value(*key); -} -#endif -#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) -#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) -#else -#define __Pyx_PyDict_NewPresized(n) PyDict_New() -#endif -#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION - #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) - #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) -#else - #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) - #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS -#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) -#else -#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) -#endif -#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) - #define CYTHON_PEP393_ENABLED 1 - #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ - 0 : _PyUnicode_Ready((PyObject *)(op))) - #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) - #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) - #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) - #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) - #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) - #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) - #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) - #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) - #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) - #else - #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) - #endif -#else - #define CYTHON_PEP393_ENABLED 0 - #define PyUnicode_1BYTE_KIND 1 - #define PyUnicode_2BYTE_KIND 2 - #define PyUnicode_4BYTE_KIND 4 - #define __Pyx_PyUnicode_READY(op) (0) - #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) - #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) - #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) - #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) - #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) - #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) - #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) - #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) -#endif -#if CYTHON_COMPILING_IN_PYPY - #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) - #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) -#else - #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) - #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ - PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) -#endif -#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) - #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) -#endif -#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) - #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) -#endif -#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) - #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) -#endif -#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) -#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) -#if PY_MAJOR_VERSION >= 3 - #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) -#else - #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) -#endif -#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) - #define PyObject_ASCII(o) PyObject_Repr(o) -#endif -#if PY_MAJOR_VERSION >= 3 - #define PyBaseString_Type PyUnicode_Type - #define PyStringObject PyUnicodeObject - #define PyString_Type PyUnicode_Type - #define PyString_Check PyUnicode_Check - #define PyString_CheckExact PyUnicode_CheckExact -#ifndef PyObject_Unicode - #define PyObject_Unicode PyObject_Str -#endif -#endif -#if PY_MAJOR_VERSION >= 3 - #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) - #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) -#else - #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) - #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) -#endif -#ifndef PySet_CheckExact - #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) -#endif -#if PY_VERSION_HEX >= 0x030900A4 - #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) - #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) -#else - #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) - #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) -#endif -#if CYTHON_ASSUME_SAFE_MACROS - #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) -#else - #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) -#endif -#if PY_MAJOR_VERSION >= 3 - #define PyIntObject PyLongObject - #define PyInt_Type PyLong_Type - #define PyInt_Check(op) PyLong_Check(op) - #define PyInt_CheckExact(op) PyLong_CheckExact(op) - #define PyInt_FromString PyLong_FromString - #define PyInt_FromUnicode PyLong_FromUnicode - #define PyInt_FromLong PyLong_FromLong - #define PyInt_FromSize_t PyLong_FromSize_t - #define PyInt_FromSsize_t PyLong_FromSsize_t - #define PyInt_AsLong PyLong_AsLong - #define PyInt_AS_LONG PyLong_AS_LONG - #define PyInt_AsSsize_t PyLong_AsSsize_t - #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask - #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask - #define PyNumber_Int PyNumber_Long -#endif -#if PY_MAJOR_VERSION >= 3 - #define PyBoolObject PyLongObject -#endif -#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY - #ifndef PyUnicode_InternFromString - #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) - #endif -#endif -#if PY_VERSION_HEX < 0x030200A4 - typedef long Py_hash_t; - #define __Pyx_PyInt_FromHash_t PyInt_FromLong - #define __Pyx_PyInt_AsHash_t PyInt_AsLong -#else - #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t - #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t -#endif -#if PY_MAJOR_VERSION >= 3 - #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) -#else - #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) -#endif -#if CYTHON_USE_ASYNC_SLOTS - #if PY_VERSION_HEX >= 0x030500B1 - #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods - #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) - #else - #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) - #endif -#else - #define __Pyx_PyType_AsAsync(obj) NULL -#endif -#ifndef __Pyx_PyAsyncMethodsStruct - typedef struct { - unaryfunc am_await; - unaryfunc am_aiter; - unaryfunc am_anext; - } __Pyx_PyAsyncMethodsStruct; -#endif - -#if defined(WIN32) || defined(MS_WINDOWS) - #define _USE_MATH_DEFINES -#endif -#include -#ifdef NAN -#define __PYX_NAN() ((float) NAN) -#else -static CYTHON_INLINE float __PYX_NAN() { - float value; - memset(&value, 0xFF, sizeof(value)); - return value; -} -#endif -#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) -#define __Pyx_truncl trunc -#else -#define __Pyx_truncl truncl -#endif - -#define __PYX_MARK_ERR_POS(f_index, lineno) \ - { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } -#define __PYX_ERR(f_index, lineno, Ln_error) \ - { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } - -#ifndef __PYX_EXTERN_C - #ifdef __cplusplus - #define __PYX_EXTERN_C extern "C" - #else - #define __PYX_EXTERN_C extern - #endif -#endif - -#define __PYX_HAVE__stpredictions__models__OK3___tree -#define __PYX_HAVE_API__stpredictions__models__OK3___tree -/* Early includes */ -#include -#include -#include "numpy/arrayobject.h" -#include "numpy/ufuncobject.h" - - /* NumPy API declarations from "numpy/__init__.pxd" */ - -#include "pythread.h" -#include -#include -#include -#include "pystate.h" -#ifdef _OPENMP -#include -#endif /* _OPENMP */ - -#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) -#define CYTHON_WITHOUT_ASSERTIONS -#endif - -typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; - const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; - -#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 -#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 -#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) -#define __PYX_DEFAULT_STRING_ENCODING "" -#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString -#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize -#define __Pyx_uchar_cast(c) ((unsigned char)c) -#define __Pyx_long_cast(x) ((long)x) -#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ - (sizeof(type) < sizeof(Py_ssize_t)) ||\ - (sizeof(type) > sizeof(Py_ssize_t) &&\ - likely(v < (type)PY_SSIZE_T_MAX ||\ - v == (type)PY_SSIZE_T_MAX) &&\ - (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ - v == (type)PY_SSIZE_T_MIN))) ||\ - (sizeof(type) == sizeof(Py_ssize_t) &&\ - (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ - v == (type)PY_SSIZE_T_MAX))) ) -static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { - return (size_t) i < (size_t) limit; -} -#if defined (__cplusplus) && __cplusplus >= 201103L - #include - #define __Pyx_sst_abs(value) std::abs(value) -#elif SIZEOF_INT >= SIZEOF_SIZE_T - #define __Pyx_sst_abs(value) abs(value) -#elif SIZEOF_LONG >= SIZEOF_SIZE_T - #define __Pyx_sst_abs(value) labs(value) -#elif defined (_MSC_VER) - #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) -#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L - #define __Pyx_sst_abs(value) llabs(value) -#elif defined (__GNUC__) - #define __Pyx_sst_abs(value) __builtin_llabs(value) -#else - #define __Pyx_sst_abs(value) ((value<0) ? -value : value) -#endif -static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); -static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); -#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) -#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) -#define __Pyx_PyBytes_FromString PyBytes_FromString -#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize -static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); -#if PY_MAJOR_VERSION < 3 - #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString - #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize -#else - #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString - #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize -#endif -#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) -#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) -#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) -#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) -#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) -static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { - const Py_UNICODE *u_end = u; - while (*u_end++) ; - return (size_t)(u_end - u - 1); -} -#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) -#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode -#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode -#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) -#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) -static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); -static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); -static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); -static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); -#define __Pyx_PySequence_Tuple(obj)\ - (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) -static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); -static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); -#if CYTHON_ASSUME_SAFE_MACROS -#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) -#else -#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) -#endif -#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) -#if PY_MAJOR_VERSION >= 3 -#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) -#else -#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) -#endif -#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) -#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII -static int __Pyx_sys_getdefaultencoding_not_ascii; -static int __Pyx_init_sys_getdefaultencoding_params(void) { - PyObject* sys; - PyObject* default_encoding = NULL; - PyObject* ascii_chars_u = NULL; - PyObject* ascii_chars_b = NULL; - const char* default_encoding_c; - sys = PyImport_ImportModule("sys"); - if (!sys) goto bad; - default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); - Py_DECREF(sys); - if (!default_encoding) goto bad; 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- -/* "stpredictions/models/OK3/_tree.pxd":8 - * - * ctypedef np.npy_float32 DTYPE_t # Type of X - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - */ -typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t; - -/* "stpredictions/models/OK3/_tree.pxd":9 - * ctypedef np.npy_float32 DTYPE_t # Type of X - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - */ -typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t; - -/* "stpredictions/models/OK3/_tree.pxd":10 - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - * - */ -typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t; - -/* "stpredictions/models/OK3/_tree.pxd":11 - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< - * - * from _splitter cimport Splitter - */ -typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t; -/* Declarations.proto */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - typedef ::std::complex< float > __pyx_t_float_complex; - #else - typedef float _Complex __pyx_t_float_complex; - #endif -#else - typedef struct { float real, imag; } __pyx_t_float_complex; -#endif -static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); - -/* Declarations.proto */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - typedef ::std::complex< double > __pyx_t_double_complex; - #else - typedef double _Complex __pyx_t_double_complex; - #endif -#else - typedef struct { double real, imag; } __pyx_t_double_complex; -#endif -static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); - - -/*--- Type declarations ---*/ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion; -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter; -struct __pyx_obj_7sklearn_4tree_5_tree_Tree; -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder; -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion; -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter; -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree; -struct __pyx_obj_7sklearn_4tree_6_utils_Stack; -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator; -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree; -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder; -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder; -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder; -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController; -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner; -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder; -struct __pyx_array_obj; -struct __pyx_MemviewEnum_obj; -struct __pyx_memoryview_obj; -struct __pyx_memoryviewslice_obj; - -/* "../venv_stpredictions/lib/python3.9/site-packages/numpy/__init__.pxd":728 - * ctypedef npy_longdouble longdouble_t - * - * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< - * ctypedef npy_cdouble cdouble_t - * ctypedef npy_clongdouble clongdouble_t - */ -typedef npy_cfloat __pyx_t_5numpy_cfloat_t; - -/* "../venv_stpredictions/lib/python3.9/site-packages/numpy/__init__.pxd":729 - * - * ctypedef npy_cfloat cfloat_t - * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< - * ctypedef npy_clongdouble clongdouble_t - * - */ -typedef npy_cdouble __pyx_t_5numpy_cdouble_t; - -/* "../venv_stpredictions/lib/python3.9/site-packages/numpy/__init__.pxd":730 - * ctypedef npy_cfloat cfloat_t - * ctypedef npy_cdouble cdouble_t - * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< - * - * ctypedef npy_cdouble complex_t - */ -typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; - -/* "../venv_stpredictions/lib/python3.9/site-packages/numpy/__init__.pxd":732 - * ctypedef npy_clongdouble clongdouble_t - * - * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< - * - * cdef inline object PyArray_MultiIterNew1(a): - */ -typedef npy_cdouble __pyx_t_5numpy_complex_t; -struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord; - -/* "_splitter.pxd":23 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef struct SplitRecord: # <<<<<<<<<<<<<< - * # Data to track sample split - * SIZE_t feature # Which feature to split on. - */ -struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - double threshold; - double improvement; - double impurity_left; - double impurity_right; -}; -struct __pyx_t_7sklearn_4tree_5_tree_Node; -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c; -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances; -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build; - -/* "sklearn/tree/_tree.pxd":25 - * from ._splitter cimport SplitRecord - * - * cdef struct Node: # <<<<<<<<<<<<<< - * # Base storage structure for the nodes in a Tree object - * - */ -struct __pyx_t_7sklearn_4tree_5_tree_Node { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t left_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t right_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t threshold; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t impurity; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t weighted_n_node_samples; -}; - -/* "sklearn/tree/_tree.pxd":63 - * double weighted_n_samples) nogil except -1 - * cdef int _resize(self, SIZE_t capacity) nogil except -1 - * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< - * - * cdef np.ndarray _get_value_ndarray(self) - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c { - int __pyx_n; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; -}; - -/* "sklearn/tree/_tree.pxd":78 - * cdef object _decision_path_sparse_csr(self, object X) - * - * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< - * - * - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances { - int __pyx_n; - PyObject *normalize; -}; - -/* "sklearn/tree/_tree.pxd":102 - * cdef double min_impurity_decrease # Impurity threshold for early stopping - * - * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< - * np.ndarray sample_weight=*) - * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build { - int __pyx_n; - PyArrayObject *sample_weight; -}; -struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord; - -/* "_splitter.pxd":14 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef struct SplitRecord: # <<<<<<<<<<<<<< - * # Data to track sample split - * SIZE_t feature # Which feature to split on. - */ -struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - double threshold; - double improvement; - double impurity_left; - double impurity_right; -}; -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; - -/* "neighbors/_quad_tree.pxd":21 - * # It allows us to write printf debugging lines - * # and remove them at compile time - * cdef enum: # <<<<<<<<<<<<<< - * DEBUGFLAG = 0 - * - */ -enum { - __pyx_e_7sklearn_9neighbors_10_quad_tree_DEBUGFLAG = 0 -}; - -/* "neighbors/_quad_tree.pxd":29 - * # have is_leaf and max_width consecutive as it permits to avoid padding by - * # the compiler and keep the size coherent for both C and numpy data structures. - * cdef struct Cell: # <<<<<<<<<<<<<< - * # Base storage structure for cells in a QuadTree object - * - */ -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell { - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t parent; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t children[8]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t point_index; - int is_leaf; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t squared_max_width; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cumulative_size; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t center[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t barycenter[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t min_bounds[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t max_bounds[3]; -}; - -/* "neighbors/_quad_tree.pxd":75 - * - * # Point insertion methods - * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< - * SIZE_t cell_id=*) nogil except -1 - * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; -}; - -/* "neighbors/_quad_tree.pxd":77 - * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, - * SIZE_t cell_id=*) nogil except -1 - * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< - * SIZE_t point_index, SIZE_t size=* - * ) nogil - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t size; -}; - -/* "neighbors/_quad_tree.pxd":84 - * - * # Create a summary of the Tree compare to a query point - * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< - * float squared_theta=*, SIZE_t cell_id=*, long idx=* - * ) nogil - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize { - int __pyx_n; - float squared_theta; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; - long idx; -}; - -/* "neighbors/_quad_tree.pxd":99 - * # Private array manipulation to manage the ``cells`` array - * cdef int _resize(self, SIZE_t capacity) nogil except -1 - * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< - * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 - * cdef np.ndarray _get_cell_ndarray(self) - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; -}; - -/* "neighbors/_quad_tree.pxd":100 - * cdef int _resize(self, SIZE_t capacity) nogil except -1 - * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 - * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< - * cdef np.ndarray _get_cell_ndarray(self) - */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell { - int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; -}; -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord; -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord; -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; - -/* "sklearn/tree/_utils.pxd":23 - * - * - * cdef enum: # <<<<<<<<<<<<<< - * # Max value for our rand_r replacement (near the bottom). - * # We don't use RAND_MAX because it's different across platforms and - */ -enum { - __pyx_e_7sklearn_4tree_6_utils_RAND_R_MAX = 0x7FFFFFFF -}; - -/* "sklearn/tree/_utils.pxd":70 - * - * # A record on the stack for depth-first tree growing - * cdef struct StackRecord: # <<<<<<<<<<<<<< - * SIZE_t start - * SIZE_t end - */ -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t parent; - int is_left; - double impurity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t n_constant_features; -}; - -/* "sklearn/tree/_utils.pxd":96 - * - * # A record on the frontier for best-first tree growing - * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< - * SIZE_t node_id - * SIZE_t start - */ -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t node_id; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t pos; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; - int is_leaf; - double impurity; - double impurity_left; - double impurity_right; - double improvement; -}; - -/* "sklearn/tree/_utils.pxd":127 - * - * # A record stored in the WeightedPQueue - * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< - * DOUBLE_t data - * DOUBLE_t weight - */ -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord { - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t data; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t weight; -}; -struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node; -struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c; -struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances; -struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build; -struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_build; -struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_build; - -/* "stpredictions/models/OK3/_tree.pxd":16 - * from _splitter cimport SplitRecord - * - * cdef struct Node: # <<<<<<<<<<<<<< - * # Base storage structure for the nodes in a Tree object - * - */ -struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node { - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t left_child; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t right_child; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; - __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t threshold; - __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t impurity; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; - __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t weighted_n_node_samples; -}; - -/* "stpredictions/models/OK3/_tree.pxd":52 - * double weighted_n_samples) nogil except -1 - * cdef int _resize(self, SIZE_t capacity) nogil except -1 - * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< - * - * cdef np.ndarray _get_value_ndarray(self) - */ -struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c { - int __pyx_n; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; -}; - -/* "stpredictions/models/OK3/_tree.pxd":68 - * cdef object _decision_path_sparse_csr(self, object X) - * - * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< - * - * - */ -struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances { - int __pyx_n; - PyObject *normalize; -}; - -/* "stpredictions/models/OK3/_tree.pxd":92 - * cdef double min_impurity_decrease # Impurity threshold for early stopping - * - * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< - * np.ndarray sample_weight=*) - * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) - */ -struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build { - int __pyx_n; - PyArrayObject *sample_weight; -}; - -/* "stpredictions/models/OK3/_tree.pyx":129 - * self.min_impurity_split = min_impurity_split - * - * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< - * np.ndarray sample_weight=None): - * """Build a decision tree from the training set (X, y).""" - */ -struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_build { - int __pyx_n; - PyArrayObject *sample_weight; -}; - -/* "stpredictions/models/OK3/_tree.pyx":303 - * self.min_impurity_split = min_impurity_split - * - * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< - * np.ndarray sample_weight=None): - * """Build a decision tree from the training set (X, y).""" - */ -struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_build { - int __pyx_n; - PyArrayObject *sample_weight; -}; - -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtab; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - double weighted_n_samples; - double weighted_n_node_samples; - double weighted_n_left; - double weighted_n_right; - double *sum_total; - double *sum_left; - double *sum_right; -}; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t sum_stride; -}; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - double sq_sum_total; -}; - - -/* "_splitter.pxd":34 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *criterion; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - PyObject *random_state; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - double weighted_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; -}; - - -/* "sklearn/tree/_tree.pxd":37 - * - * - * cdef class Tree: # <<<<<<<<<<<<<< - * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and - */ -struct __pyx_obj_7sklearn_4tree_5_tree_Tree { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtab; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t node_count; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; - struct __pyx_t_7sklearn_4tree_5_tree_Node *nodes; - double *value; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t value_stride; -}; - - -/* "sklearn/tree/_tree.pxd":85 - * # ============================================================================= - * - * cdef class TreeBuilder: # <<<<<<<<<<<<<< - * # The TreeBuilder recursively builds a Tree object from training samples, - * # using a Splitter object for splitting internal nodes and assigning - */ -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *splitter; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_split; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; - double min_impurity_split; - double min_impurity_decrease; -}; - - -/* "_criterion.pxd":12 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. - */ -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion { - PyObject_HEAD - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtab; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - double weighted_n_samples; - double weighted_n_node_samples; - double weighted_n_left; - double weighted_n_right; -}; - - -/* "_criterion.pxd":50 - * - * - * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract kernelized output regression criterion.""" - * - */ -struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { - struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; - double sum_diag_Gramm; - double sum_total_Gramm; - double sum_diag_Gramm_left; - double sum_diag_Gramm_right; - double sum_total_Gramm_left; - double sum_total_Gramm_right; -}; - - -/* "_splitter.pxd":25 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ -struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter { - PyObject_HEAD - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtab; - struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *criterion; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - PyObject *random_state; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - double weighted_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; -}; - - -/* "neighbors/_quad_tree.pxd":55 - * - * - * cdef class _QuadTree: # <<<<<<<<<<<<<< - * # The QuadTree object is a quad tree structure constructed by inserting - * # recursively points in the tree and splitting cells in 4 so that each - */ -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtab; - int n_dimensions; - int verbose; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_cells_per_cell; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t max_depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_count; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_points; - struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *cells; -}; - - -/* "sklearn/tree/_utils.pxd":79 - * SIZE_t n_constant_features - * - * cdef class Stack: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t top - */ -struct __pyx_obj_7sklearn_4tree_6_utils_Stack { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t top; - struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *stack_; -}; - - -/* "sklearn/tree/_utils.pxd":108 - * double improvement - * - * cdef class PriorityHeap: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t heap_ptr - */ -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t heap_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *heap_; -}; - - -/* "sklearn/tree/_utils.pxd":131 - * DOUBLE_t weight - * - * cdef class WeightedPQueue: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t array_ptr - */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t array_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *array_; -}; - - -/* "sklearn/tree/_utils.pxd":151 - * # ============================================================================= - * - * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< - * cdef SIZE_t initial_capacity - * cdef WeightedPQueue samples - */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t initial_capacity; - struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *samples; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t total_weight; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t k; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t sum_w_0_k; -}; - - -/* "stpredictions/models/OK3/_tree.pxd":28 - * - * - * cdef class Tree: # <<<<<<<<<<<<<< - * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. - */ -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree { - PyObject_HEAD - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtab; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t node_count; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; - PyArrayObject *K_y; - PyArrayObject *y; - struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *nodes; - double *value; -}; - - -/* "stpredictions/models/OK3/_tree.pxd":75 - * # ============================================================================= - * - * cdef class TreeBuilder: # <<<<<<<<<<<<<< - * # The TreeBuilder recursively builds a Tree object from training samples, - * # using a Splitter object for splitting internal nodes and assigning - */ -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder { - PyObject_HEAD - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtab; - struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *splitter; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_split; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; - double min_impurity_split; - double min_impurity_decrease; -}; - - -/* "stpredictions/models/OK3/_tree.pyx":114 - * # Depth first builder --------------------------------------------------------- - * - * cdef class DepthFirstTreeBuilder(TreeBuilder): # <<<<<<<<<<<<<< - * """Build a decision tree in depth-first fashion.""" - * - */ -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder { - struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder __pyx_base; -}; - - -/* "stpredictions/models/OK3/_tree.pyx":282 - * - * - * cdef class BestFirstTreeBuilder(TreeBuilder): # <<<<<<<<<<<<<< - * """Build a decision tree in best-first fashion. - * - */ -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder { - struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder __pyx_base; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_leaf_nodes; -}; - - -/* "stpredictions/models/OK3/_tree.pyx":1316 - * - * - * cdef class _CCPPruneController: # <<<<<<<<<<<<<< - * """Base class used by build_pruned_tree_ccp and ccp_pruning_path - * to control pruning. - */ -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController { - PyObject_HEAD - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_vtab; -}; - - -/* "stpredictions/models/OK3/_tree.pyx":1334 - * - * - * cdef class _AlphaPruner(_CCPPruneController): # <<<<<<<<<<<<<< - * """Use alpha to control when to stop pruning.""" - * cdef DOUBLE_t ccp_alpha - */ -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner { - struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController __pyx_base; - __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t ccp_alpha; - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; -}; - - -/* "stpredictions/models/OK3/_tree.pyx":1355 - * - * - * cdef class _PathFinder(_CCPPruneController): # <<<<<<<<<<<<<< - * """Record metrics used to return the cost complexity path.""" - * cdef DOUBLE_t[:] ccp_alphas - */ -struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder { - struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController __pyx_base; - __Pyx_memviewslice ccp_alphas; - __Pyx_memviewslice impurities; - __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t count; -}; - - -/* "View.MemoryView":105 - * - * @cname("__pyx_array") - * cdef class array: # <<<<<<<<<<<<<< - * - * cdef: - */ -struct __pyx_array_obj { - PyObject_HEAD - struct __pyx_vtabstruct_array *__pyx_vtab; - char *data; - Py_ssize_t len; - char *format; - int ndim; - Py_ssize_t *_shape; - Py_ssize_t *_strides; - Py_ssize_t itemsize; - PyObject *mode; - PyObject *_format; - void (*callback_free_data)(void *); - int free_data; - int dtype_is_object; -}; - - -/* "View.MemoryView":279 - * - * @cname('__pyx_MemviewEnum') - * cdef class Enum(object): # <<<<<<<<<<<<<< - * cdef object name - * def __init__(self, name): - */ -struct __pyx_MemviewEnum_obj { - PyObject_HEAD - PyObject *name; -}; - - -/* "View.MemoryView":330 - * - * @cname('__pyx_memoryview') - * cdef class memoryview(object): # <<<<<<<<<<<<<< - * - * cdef object obj - */ -struct __pyx_memoryview_obj { - PyObject_HEAD - struct __pyx_vtabstruct_memoryview *__pyx_vtab; - PyObject *obj; - PyObject *_size; - PyObject *_array_interface; - PyThread_type_lock lock; - __pyx_atomic_int acquisition_count[2]; - __pyx_atomic_int *acquisition_count_aligned_p; - Py_buffer view; - int flags; - int dtype_is_object; - __Pyx_TypeInfo *typeinfo; -}; - - -/* "View.MemoryView":965 - * - * @cname('__pyx_memoryviewslice') - * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< - * "Internal class for passing memoryview slices to Python" - * - */ -struct __pyx_memoryviewslice_obj { - struct __pyx_memoryview_obj __pyx_base; - __Pyx_memviewslice from_slice; - PyObject *from_object; - PyObject *(*to_object_func)(char *); - int (*to_dtype_func)(char *, PyObject *); -}; - - - -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion { - int (*init)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double, double, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_Criterion; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_ClassificationCriterion; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_RegressionCriterion; - - -/* "_splitter.pxd":34 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ - -struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter { - int (*init)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); - int (*node_reset)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); - int (*node_split)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double, struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double *); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtabptr_7sklearn_4tree_9_splitter_Splitter; - - -/* "sklearn/tree/_tree.pxd":37 - * - * - * cdef class Tree: # <<<<<<<<<<<<<< - * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and - */ - -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double); - int (*_resize)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args); - PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*predict)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*apply)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*_apply_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*decision_path)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyObject *(*_decision_path_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*compute_feature_importances)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklearn_4tree_5_tree_Tree; - - -/* "sklearn/tree/_tree.pxd":85 - * # ============================================================================= - * - * cdef class TreeBuilder: # <<<<<<<<<<<<<< - * # The TreeBuilder recursively builds a Tree object from training samples, - * # using a Splitter object for splitting internal nodes and assigning - */ - -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder { - PyObject *(*build)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args); - PyObject *(*_check_input)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder; - - -/* "_criterion.pxd":12 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion { - int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion; - - -/* "_criterion.pxd":50 - * - * - * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract kernelized output regression criterion.""" - * - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { - struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; - - -/* "_splitter.pxd":25 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter { - int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); - int (*node_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); - int (*node_split)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); - void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double *); - double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *); -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_Splitter; - - -/* "neighbors/_quad_tree.pxd":55 - * - * - * cdef class _QuadTree: # <<<<<<<<<<<<<< - * # The QuadTree object is a quad tree structure constructed by inserting - * # recursively points in the tree and splitting cells in 4 so that each - */ - -struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree { - int (*insert_point)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_is_duplicate)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - long (*summarize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); - void (*_init_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - void (*_init_root)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - int (*_check_point_in_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_resize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); - int (*_get_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); - PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *); -}; -static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtabptr_7sklearn_9neighbors_10_quad_tree__QuadTree; - - -/* "sklearn/tree/_utils.pxd":79 - * SIZE_t n_constant_features - * - * cdef class Stack: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t top - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7sklearn_4tree_6_utils_Stack; - - -/* "sklearn/tree/_utils.pxd":108 - * double improvement - * - * cdef class PriorityHeap: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t heap_ptr - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); - void (*heapify_up)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - void (*heapify_down)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, double, double, double); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabptr_7sklearn_4tree_6_utils_PriorityHeap; - - -/* "sklearn/tree/_utils.pxd":131 - * DOUBLE_t weight - * - * cdef class WeightedPQueue: # <<<<<<<<<<<<<< - * cdef SIZE_t capacity - * cdef SIZE_t array_ptr - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*peek)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedPQueue; - - -/* "sklearn/tree/_utils.pxd":151 - * # ============================================================================= - * - * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< - * cdef SIZE_t initial_capacity - * cdef WeightedPQueue samples - */ - -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*update_median_parameters_post_push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*update_median_parameters_post_remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedMedianCalculator; - - -/* "stpredictions/models/OK3/_tree.pyx":503 - * # ============================================================================= - * - * cdef class Tree: # <<<<<<<<<<<<<< - * """Array-based representation of a binary decision tree. - * - */ - -struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree { - __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int, int, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double); - int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c *__pyx_optional_args); - PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); - PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); - PyArrayObject *(*decode_tree)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyArrayObject *, PyArrayObject *, PyObject *, PyObject *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int __pyx_skip_dispatch); - PyArrayObject *(*predict)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*apply)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*_apply_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); 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-static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); -#if CYTHON_COMPILING_IN_CPYTHON -#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) -#else -#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) -#endif -#else -#define __Pyx_PyErr_Clear() PyErr_Clear() -#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) -#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) -#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) -#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) -#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) -#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) -#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) -#endif - -/* RaiseException.proto */ -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); - -/* ExtTypeTest.proto */ -static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); - -/* PyErrExceptionMatches.proto */ -#if CYTHON_FAST_THREAD_STATE -#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) -static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); -#else -#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) -#endif - -/* GetAttr.proto */ -static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); - -/* GetAttr3.proto */ -static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *); - -/* RaiseTooManyValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); - -/* RaiseNeedMoreValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); - -/* IterFinish.proto */ -static CYTHON_INLINE int __Pyx_IterFinish(void); - -/* UnpackItemEndCheck.proto */ -static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected); - -/* MemviewSliceInit.proto */ -#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d -#define __Pyx_MEMVIEW_DIRECT 1 -#define __Pyx_MEMVIEW_PTR 2 -#define __Pyx_MEMVIEW_FULL 4 -#define __Pyx_MEMVIEW_CONTIG 8 -#define __Pyx_MEMVIEW_STRIDED 16 -#define __Pyx_MEMVIEW_FOLLOW 32 -#define __Pyx_IS_C_CONTIG 1 -#define __Pyx_IS_F_CONTIG 2 -static int __Pyx_init_memviewslice( - struct __pyx_memoryview_obj *memview, - int ndim, - __Pyx_memviewslice *memviewslice, - int memview_is_new_reference); -static CYTHON_INLINE int __pyx_add_acquisition_count_locked( - __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); -static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( - __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); -#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p) -#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview)) -#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__) -#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__) -static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); -static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); - -/* GetItemInt.proto */ -#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ - __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ - (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ - __Pyx_GetItemInt_Generic(o, to_py_func(i)))) -#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ - __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ - (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, - int wraparound, int boundscheck); -#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ - __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ - (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, - int wraparound, int boundscheck); -static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, - int is_list, int wraparound, int boundscheck); - -/* ObjectGetItem.proto */ -#if CYTHON_USE_TYPE_SLOTS -static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key); -#else -#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) -#endif - -/* SliceObject.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice( - PyObject* obj, Py_ssize_t cstart, Py_ssize_t cstop, - PyObject** py_start, PyObject** py_stop, PyObject** py_slice, - int has_cstart, int has_cstop, int wraparound); - -/* PyIntCompare.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_EqObjC(PyObject *op1, PyObject *op2, long intval, long inplace); - -/* DictGetItem.proto */ -#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY -static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key); -#define __Pyx_PyObject_Dict_GetItem(obj, name)\ - (likely(PyDict_CheckExact(obj)) ?\ - __Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name)) -#else -#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) -#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name) -#endif - -/* PySequenceContains.proto */ -static CYTHON_INLINE int __Pyx_PySequence_ContainsTF(PyObject* item, PyObject* seq, int eq) { - int result = PySequence_Contains(seq, item); - return unlikely(result < 0) ? result : (result == (eq == Py_EQ)); -} - -/* PyIntCompare.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_NeObjC(PyObject *op1, PyObject *op2, long intval, long inplace); - -/* IncludeStringH.proto */ -#include - -/* BytesEquals.proto */ -static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); - -/* UnicodeEquals.proto */ -static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals); - -/* StrEquals.proto */ -#if PY_MAJOR_VERSION >= 3 -#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals -#else -#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals -#endif - -/* ListAppend.proto */ -#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS -static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { - PyListObject* L = (PyListObject*) list; - Py_ssize_t len = Py_SIZE(list); - if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { - Py_INCREF(x); - PyList_SET_ITEM(list, len, x); - __Pyx_SET_SIZE(list, len + 1); - return 0; - } - return PyList_Append(list, x); -} -#else -#define __Pyx_PyList_Append(L,x) PyList_Append(L,x) -#endif - -/* PyObjectGetMethod.proto */ -static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method); - -/* PyObjectCallMethod1.proto */ -static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg); - -/* append.proto */ -static CYTHON_INLINE int __Pyx_PyObject_Append(PyObject* L, PyObject* x); - -/* PyIntBinop.proto */ -#if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); -#else -#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ - (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) -#endif - -/* ListCompAppend.proto */ -#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS -static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { - PyListObject* L = (PyListObject*) list; - Py_ssize_t len = Py_SIZE(list); - if (likely(L->allocated > len)) { - Py_INCREF(x); - PyList_SET_ITEM(list, len, x); - __Pyx_SET_SIZE(list, len + 1); - return 0; - } - return PyList_Append(list, x); -} -#else -#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) -#endif - -/* SliceObject.proto */ -#define __Pyx_PyObject_DelSlice(obj, cstart, cstop, py_start, py_stop, py_slice, has_cstart, has_cstop, wraparound)\ - __Pyx_PyObject_SetSlice(obj, (PyObject*)NULL, cstart, cstop, py_start, py_stop, py_slice, has_cstart, has_cstop, wraparound) -static CYTHON_INLINE int __Pyx_PyObject_SetSlice( - PyObject* obj, PyObject* value, Py_ssize_t cstart, Py_ssize_t cstop, - PyObject** py_start, PyObject** py_stop, PyObject** py_slice, - int has_cstart, int has_cstop, int wraparound); - -/* MatrixMultiply.proto */ -#if PY_VERSION_HEX >= 0x03050000 - #define __Pyx_PyNumber_MatrixMultiply(x,y) PyNumber_MatrixMultiply(x,y) - #define __Pyx_PyNumber_InPlaceMatrixMultiply(x,y) PyNumber_InPlaceMatrixMultiply(x,y) -#else -#define __Pyx_PyNumber_MatrixMultiply(x,y) __Pyx__PyNumber_MatrixMultiply(x, y, "@") -static PyObject* __Pyx__PyNumber_MatrixMultiply(PyObject* x, PyObject* y, const char* op_name); -static PyObject* __Pyx_PyNumber_InPlaceMatrixMultiply(PyObject* x, PyObject* y); -#endif - -/* IsLittleEndian.proto */ -static CYTHON_INLINE int __Pyx_Is_Little_Endian(void); - -/* BufferFormatCheck.proto */ -static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts); -static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, - __Pyx_BufFmt_StackElem* stack, - __Pyx_TypeInfo* type); - -/* BufferGetAndValidate.proto */ -#define __Pyx_GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)\ - ((obj == Py_None || obj == NULL) ?\ - (__Pyx_ZeroBuffer(buf), 0) :\ - __Pyx__GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)) -static int __Pyx__GetBufferAndValidate(Py_buffer* buf, PyObject* obj, - __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack); -static void __Pyx_ZeroBuffer(Py_buffer* buf); -static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); -static Py_ssize_t __Pyx_minusones[] = { -1, -1, -1, -1, -1, -1, -1, -1 }; -static Py_ssize_t __Pyx_zeros[] = { 0, 0, 0, 0, 0, 0, 0, 0 }; - -#define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0) -/* BufferFallbackError.proto */ -static void __Pyx_RaiseBufferFallbackError(void); - -/* WriteUnraisableException.proto */ -static void __Pyx_WriteUnraisable(const char *name, int clineno, - int lineno, const char *filename, - int full_traceback, int nogil); - -/* SetItemInt.proto */ -#define __Pyx_SetItemInt(o, i, v, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ - __Pyx_SetItemInt_Fast(o, (Py_ssize_t)i, v, is_list, wraparound, boundscheck) :\ - (is_list ? (PyErr_SetString(PyExc_IndexError, "list assignment index out of range"), -1) :\ - __Pyx_SetItemInt_Generic(o, to_py_func(i), v))) -static int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v); -static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, - int is_list, int wraparound, int boundscheck); - -/* Import.proto */ -static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); - -/* ImportFrom.proto */ -static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); - -/* HasAttr.proto */ -static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *); - -/* GetTopmostException.proto */ -#if CYTHON_USE_EXC_INFO_STACK -static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); -#endif - -/* SaveResetException.proto */ -#if CYTHON_FAST_THREAD_STATE -#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); -#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); -#else -#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) -#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) -#endif - -/* GetException.proto */ -#if CYTHON_FAST_THREAD_STATE -#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); -#endif - -/* UnaryNegOverflows.proto */ -#define UNARY_NEG_WOULD_OVERFLOW(x)\ - (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) - -static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ -static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/ -/* decode_c_string_utf16.proto */ -static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors) { - int byteorder = 0; - return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); -} -static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) { - int byteorder = -1; - return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); -} -static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) { - int byteorder = 1; - return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); -} - -/* decode_c_string.proto */ -static CYTHON_INLINE PyObject* __Pyx_decode_c_string( - const char* cstring, Py_ssize_t start, Py_ssize_t stop, - const char* encoding, const char* errors, - PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); - -/* RaiseNoneIterError.proto */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); - -/* SwapException.proto */ -#if CYTHON_FAST_THREAD_STATE -#define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) -static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); -#else -static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); -#endif - -/* FastTypeChecks.proto */ -#if CYTHON_COMPILING_IN_CPYTHON -#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) -static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); -static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); -static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); -#else -#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) -#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) -#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) -#endif -#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) - -static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ -/* ListExtend.proto */ -static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { -#if CYTHON_COMPILING_IN_CPYTHON - PyObject* none = _PyList_Extend((PyListObject*)L, v); - if (unlikely(!none)) - return -1; - Py_DECREF(none); - return 0; -#else - return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v); -#endif -} - -/* None.proto */ -static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); - -/* StringJoin.proto */ -#if PY_MAJOR_VERSION < 3 -#define __Pyx_PyString_Join __Pyx_PyBytes_Join -#define __Pyx_PyBaseString_Join(s, v) (PyUnicode_CheckExact(s) ? PyUnicode_Join(s, v) : __Pyx_PyBytes_Join(s, v)) -#else -#define __Pyx_PyString_Join PyUnicode_Join -#define __Pyx_PyBaseString_Join PyUnicode_Join -#endif -#if CYTHON_COMPILING_IN_CPYTHON - #if PY_MAJOR_VERSION < 3 - #define __Pyx_PyBytes_Join _PyString_Join - #else - #define __Pyx_PyBytes_Join _PyBytes_Join - #endif -#else -static CYTHON_INLINE PyObject* __Pyx_PyBytes_Join(PyObject* sep, PyObject* values); -#endif - -/* PyObject_Unicode.proto */ -#if PY_MAJOR_VERSION >= 3 -#define __Pyx_PyObject_Unicode(obj)\ - (likely(PyUnicode_CheckExact(obj)) ? __Pyx_NewRef(obj) : PyObject_Str(obj)) -#else -#define __Pyx_PyObject_Unicode(obj)\ - (likely(PyUnicode_CheckExact(obj)) ? __Pyx_NewRef(obj) : PyObject_Unicode(obj)) -#endif - -/* PyObject_GenericGetAttrNoDict.proto */ -#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 -static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name); -#else -#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr -#endif - -/* PyObject_GenericGetAttr.proto */ -#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 -static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name); -#else -#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr -#endif - -/* SetVTable.proto */ -static int __Pyx_SetVtable(PyObject *dict, void *vtable); - -/* PyObjectGetAttrStrNoError.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); - -/* SetupReduce.proto */ -static int __Pyx_setup_reduce(PyObject* type_obj); - -/* TypeImport.proto */ -#ifndef __PYX_HAVE_RT_ImportType_proto -#define __PYX_HAVE_RT_ImportType_proto -enum __Pyx_ImportType_CheckSize { - __Pyx_ImportType_CheckSize_Error = 0, - __Pyx_ImportType_CheckSize_Warn = 1, - __Pyx_ImportType_CheckSize_Ignore = 2 -}; -static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); -#endif - -/* GetVTable.proto */ -static void* __Pyx_GetVtable(PyObject *dict); - -/* CLineInTraceback.proto */ -#ifdef CYTHON_CLINE_IN_TRACEBACK -#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) -#else -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); 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- -/* ObjectToMemviewSlice.proto */ -static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t(PyObject *, int writable_flag); - -/* ObjectToMemviewSlice.proto */ -static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_unsigned_char(PyObject *, int writable_flag); - -/* CheckBinaryVersion.proto */ -static int __Pyx_check_binary_version(void); - -/* VoidPtrImport.proto */ -static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig); - -/* FunctionImport.proto */ -static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig); - -/* InitStrings.proto */ -static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); - -static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, CYTHON_UNUSED PyObject *__pyx_v_X, CYTHON_UNUSED PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build *__pyx_optional_args); /* proto*/ -static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_11TreeBuilder__check_input(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto*/ -static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_build *__pyx_optional_args); /* proto*/ -static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_build *__pyx_optional_args); /* proto*/ -static CYTHON_INLINE int __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end, double __pyx_v_impurity, int __pyx_v_is_first, int __pyx_v_is_left, struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_parent, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_depth, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *__pyx_v_res, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_samples); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__resize(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_capacity); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c *__pyx_optional_args); /* proto*/ -static __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__add_node(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_parent, int __pyx_v_is_left, int __pyx_v_is_leaf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_feature, double __pyx_v_threshold, double __pyx_v_impurity, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_node_samples, double __pyx_v_weighted_n_node_samples); /* proto*/ -static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_predict(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ -static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_decode_tree(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_K_cand_train, PyArrayObject *__pyx_v_sq_norms_cand, PyObject *__pyx_v_criterion, PyObject *__pyx_v_kernel, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_return_top_k, int __pyx_skip_dispatch); /* proto*/ -static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_apply(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ -static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__apply_dense(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ -static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ -static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_decision_path(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ -static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__decision_path_dense(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ -static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ -static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); /* proto*/ -static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__get_value_ndarray(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto*/ -static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__get_node_ndarray(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController_stop_pruning(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_effective_alpha); /* proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController_save_metrics(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_effective_alpha, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_subtree_impurities); /* proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController_after_pruning(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_in_subtree); /* proto*/ -static int __pyx_f_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_stop_pruning(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_effective_alpha); /* proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_after_pruning(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_self, __Pyx_memviewslice __pyx_v_in_subtree); /* proto*/ -static void __pyx_f_13stpredictions_6models_3OK3_5_tree_11_PathFinder_save_metrics(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_effective_alpha, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_subtree_impurities); /* proto*/ -static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ -static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ -static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ -static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); 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/*proto*/ -static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ -static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ -static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ -static PyObject *__pyx_format_from_typeinfo(__Pyx_TypeInfo *); /*proto*/ -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t = { "SIZE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t) ? 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'U' : 'I', IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t), 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t = { "float64_t", NULL, sizeof(__pyx_t_5numpy_float64_t), { 0 }, 0, 'R', 0, 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t = { "DOUBLE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t), { 0 }, 0, 'R', 0, 0 }; -static __Pyx_StructField __Pyx_StructFields_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node[] = { - {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, "left_child", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, left_child)}, - {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, "right_child", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, right_child)}, - {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, "feature", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, feature)}, - {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t, "threshold", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, threshold)}, - {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t, "impurity", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, impurity)}, - {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, "n_node_samples", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, n_node_samples)}, - {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t, "weighted_n_node_samples", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, weighted_n_node_samples)}, - {NULL, NULL, 0} -}; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node = { "Node", __Pyx_StructFields_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node, sizeof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node), { 0 }, 0, 'S', 0, 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__ = { "const DOUBLE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const ), { 0 }, 0, 'R', 0, 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t__const__ = { "const DTYPE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t const ), { 0 }, 0, 'R', 0, 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_unsigned_char = { "unsigned char", NULL, sizeof(unsigned char), { 0 }, 0, IS_UNSIGNED(unsigned char) ? 'U' : 'I', IS_UNSIGNED(unsigned char), 0 }; -#define __Pyx_MODULE_NAME "stpredictions.models.OK3._tree" -extern int __pyx_module_is_main_stpredictions__models__OK3___tree; -int __pyx_module_is_main_stpredictions__models__OK3___tree = 0; - -/* Implementation of 'stpredictions.models.OK3._tree' */ -static PyObject *__pyx_builtin_ValueError; -static PyObject *__pyx_builtin_MemoryError; -static PyObject *__pyx_builtin_TypeError; -static PyObject *__pyx_builtin_range; -static PyObject *__pyx_builtin_enumerate; -static PyObject *__pyx_builtin_NotImplementedError; -static PyObject *__pyx_builtin_ImportError; -static PyObject *__pyx_builtin_KeyError; -static PyObject *__pyx_builtin_Ellipsis; -static PyObject *__pyx_builtin_id; -static PyObject *__pyx_builtin_IndexError; -static const char __pyx_k_C[] = "C"; -static const char __pyx_k_O[] = "O"; -static const char __pyx_k_T[] = "T{"; - static const char __pyx_k_X[] = "X"; - static const char __pyx_k_c[] = "c"; - static const char __pyx_k_s[] = "(%s)"; - static const char __pyx_k_y[] = "y"; - static const char __pyx_k_id[] = "id"; - static const char __pyx_k_np[] = "np"; - static const char __pyx_k_K_y[] = "K_y"; - static const char __pyx_k__43[] = "^"; - static const char __pyx_k__44[] = ""; - static const char __pyx_k__45[] = ":"; -static const char __pyx_k__46[] = "}"; -static const char __pyx_k__47[] = ","; -static const char __pyx_k_eps[] = "eps"; -static const char __pyx_k_inf[] = "inf"; -static const char __pyx_k_max[] = "max"; -static const char __pyx_k_new[] = "__new__"; -static const char __pyx_k_obj[] = "obj"; -static const char __pyx_k_sum[] = "sum"; -static const char __pyx_k_Tree[] = "Tree"; -static const char __pyx_k_base[] = "base"; -static const char __pyx_k_data[] = "data"; -static const char __pyx_k_dict[] = "__dict__"; -static const char __pyx_k_intp[] = "intp"; -static const char __pyx_k_join[] = "join"; -static const char __pyx_k_main[] = "__main__"; -static const char __pyx_k_mean[] = "mean"; -static const char __pyx_k_mode[] = "mode"; -static const char __pyx_k_name[] = "name"; -static const char __pyx_k_ndim[] = "ndim"; -static const char __pyx_k_ones[] = "ones"; -static const char __pyx_k_pack[] = "pack"; -static const char __pyx_k_size[] = "size"; -static const char __pyx_k_step[] = "step"; -static const char __pyx_k_stop[] = "stop"; -static const char __pyx_k_test[] = "__test__"; -static const char __pyx_k_tree[] = "tree"; -static const char __pyx_k_ASCII[] = "ASCII"; -static const char __pyx_k_DTYPE[] = "DTYPE"; -static const char __pyx_k_apply[] = "apply"; -static const char __pyx_k_array[] = "array"; -static const char __pyx_k_build[] = "build"; -static const char __pyx_k_class[] = "__class__"; -static const char __pyx_k_count[] = "count"; -static const char __pyx_k_dtype[] = "dtype"; -static const char __pyx_k_empty[] = "empty"; -static const char __pyx_k_error[] = "error"; -static const char __pyx_k_finfo[] = "finfo"; -static const char __pyx_k_flags[] = "flags"; -static const char __pyx_k_int32[] = "int32"; -static const char __pyx_k_nodes[] = "nodes"; -static const char __pyx_k_numpy[] = "numpy"; -static const char __pyx_k_order[] = "order"; -static const char __pyx_k_range[] = "range"; -static const char __pyx_k_shape[] = "shape"; -static const char __pyx_k_start[] = "start"; -static const char __pyx_k_tocsc[] = "tocsc"; -static const char __pyx_k_tocsr[] = "tocsr"; -static const char __pyx_k_uint8[] = "uint8"; -static const char __pyx_k_where[] = "where"; -static const char __pyx_k_zeros[] = "zeros"; -static const char __pyx_k_DOUBLE[] = "DOUBLE"; -static const char __pyx_k_append[] = "append"; -static const char __pyx_k_argmax[] = "argmax"; -static const char __pyx_k_double[] = "double"; -static const char __pyx_k_encode[] = "encode"; -static const char __pyx_k_format[] = "format"; -static const char __pyx_k_import[] = "__import__"; -static const char __pyx_k_indptr[] = "indptr"; -static const char __pyx_k_kernel[] = "kernel"; -static const char __pyx_k_matmul[] = "__matmul__"; -static const char __pyx_k_name_2[] = "__name__"; -static const char __pyx_k_pickle[] = "pickle"; -static const char __pyx_k_reduce[] = "__reduce__"; -static const char __pyx_k_struct[] = "struct"; -static const char __pyx_k_unique[] = "unique"; -static const char __pyx_k_unpack[] = "unpack"; -static const char __pyx_k_update[] = "update"; -static const char __pyx_k_values[] = "values"; -static const char __pyx_k_asarray[] = "asarray"; -static const char __pyx_k_feature[] = "feature"; -static const char __pyx_k_float32[] = "float32"; -static const char __pyx_k_float64[] = "float64"; -static const char __pyx_k_fortran[] = "fortran"; -static const char __pyx_k_imatmul[] = "__imatmul__"; -static const char __pyx_k_indices[] = "indices"; -static const char __pyx_k_memview[] = "memview"; -static const char __pyx_k_mse_reg[] = "mse_reg"; -static const char __pyx_k_n_nodes[] = "n_nodes"; -static const char __pyx_k_predict[] = "predict"; -static const char __pyx_k_product[] = "product"; -static const char __pyx_k_rmatmul[] = "__rmatmul__"; -static const char __pyx_k_Ellipsis[] = "Ellipsis"; -static const char __pyx_k_KeyError[] = "KeyError"; -static const char __pyx_k_getstate[] = "__getstate__"; -static const char __pyx_k_gini_clf[] = "gini_clf"; -static const char __pyx_k_impurity[] = "impurity"; -static const char __pyx_k_issparse[] = "issparse"; -static const char __pyx_k_itemsize[] = "itemsize"; -static const char __pyx_k_pyx_type[] = "__pyx_type"; -static const char __pyx_k_setstate[] = "__setstate__"; -static const char __pyx_k_splitter[] = "splitter"; -static const char __pyx_k_warnings[] = "warnings"; -static const char __pyx_k_Criterion[] = "Criterion"; -static const char __pyx_k_TREE_LEAF[] = "TREE_LEAF"; -static const char __pyx_k_TypeError[] = "TypeError"; -static const char __pyx_k_ccp_alpha[] = "ccp_alpha"; -static const char __pyx_k_criterion[] = "criterion"; -static const char __pyx_k_enumerate[] = "enumerate"; -static const char __pyx_k_itertools[] = "itertools"; -static const char __pyx_k_max_depth[] = "max_depth"; -static const char __pyx_k_n_samples[] = "n_samples"; -static const char __pyx_k_normalize[] = "normalize"; -static const char __pyx_k_orig_tree[] = "orig_tree"; -static const char __pyx_k_pyx_state[] = "__pyx_state"; -static const char __pyx_k_reduce_ex[] = "__reduce_ex__"; -static const char __pyx_k_threshold[] = "threshold"; -static const char __pyx_k_IndexError[] = "IndexError"; -static const char __pyx_k_NODE_DTYPE[] = "NODE_DTYPE"; -static const char __pyx_k_PathFinder[] = "_PathFinder"; -static const char __pyx_k_ValueError[] = "ValueError"; -static const char __pyx_k_ccp_alphas[] = "ccp_alphas"; -static const char __pyx_k_contiguous[] = "contiguous"; -static const char __pyx_k_csc_matrix[] = "csc_matrix"; -static const char __pyx_k_csr_matrix[] = "csr_matrix"; -static const char __pyx_k_impurities[] = "impurities"; -static const char __pyx_k_left_child[] = "left_child"; -static const char __pyx_k_n_features[] = "n_features"; -static const char __pyx_k_node_count[] = "node_count"; -static const char __pyx_k_pyx_result[] = "__pyx_result"; -static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; -static const char __pyx_k_AlphaPruner[] = "_AlphaPruner"; -static const char __pyx_k_ImportError[] = "ImportError"; -static const char __pyx_k_MemoryError[] = "MemoryError"; -static const char __pyx_k_PickleError[] = "PickleError"; -static const char __pyx_k_TreeBuilder[] = "TreeBuilder"; -static const char __pyx_k_criterion_2[] = "_criterion"; -static const char __pyx_k_decode_tree[] = "decode_tree"; -static const char __pyx_k_logical_and[] = "logical_and"; -static const char __pyx_k_path_finder[] = "path_finder"; -static const char __pyx_k_right_child[] = "right_child"; -static const char __pyx_k_total_items[] = "total_items"; -static const char __pyx_k_K_cand_train[] = "K_cand_train"; -static const char __pyx_k_argpartition[] = "argpartition"; -static const char __pyx_k_c_contiguous[] = "c_contiguous"; -static const char __pyx_k_pruning_tree[] = "pruning tree"; -static const char __pyx_k_pyx_checksum[] = "__pyx_checksum"; -static const char __pyx_k_return_top_k[] = "return_top_k"; -static const char __pyx_k_scipy_sparse[] = "scipy.sparse"; -static const char __pyx_k_sort_indices[] = "sort_indices"; -static const char __pyx_k_stringsource[] = "stringsource"; -static const char __pyx_k_KernelizedMSE[] = "KernelizedMSE"; -static const char __pyx_k_children_left[] = "children_left"; -static const char __pyx_k_decision_path[] = "decision_path"; -static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; -static const char __pyx_k_reduce_cython[] = "__reduce_cython__"; -static const char __pyx_k_sample_weight[] = "sample_weight"; -static const char __pyx_k_sq_norms_cand[] = "sq_norms_cand"; -static const char __pyx_k_TREE_UNDEFINED[] = "TREE_UNDEFINED"; -static const char __pyx_k_asfortranarray[] = "asfortranarray"; -static const char __pyx_k_children_right[] = "children_right"; -static const char __pyx_k_max_leaf_nodes[] = "max_leaf_nodes"; -static const char __pyx_k_n_node_samples[] = "n_node_samples"; -static const char __pyx_k_return_inverse[] = "return_inverse"; -static const char __pyx_k_View_MemoryView[] = "View.MemoryView"; -static const char __pyx_k_allocate_buffer[] = "allocate_buffer"; -static const char __pyx_k_dtype_is_object[] = "dtype_is_object"; -static const char __pyx_k_min_weight_leaf[] = "min_weight_leaf"; -static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError"; -static const char __pyx_k_setstate_cython[] = "__setstate_cython__"; -static const char __pyx_k_ccp_pruning_path[] = "ccp_pruning_path"; -static const char __pyx_k_min_samples_leaf[] = "min_samples_leaf"; -static const char __pyx_k_ascontiguousarray[] = "ascontiguousarray"; -static const char __pyx_k_leaves_in_subtree[] = "leaves_in_subtree"; -static const char __pyx_k_min_samples_split[] = "min_samples_split"; -static const char __pyx_k_pyx_unpickle_Enum[] = "__pyx_unpickle_Enum"; -static const char __pyx_k_CCPPruneController[] = "_CCPPruneController"; -static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; -static const char __pyx_k_min_impurity_split[] = "min_impurity_split"; -static const char __pyx_k_pruning_controller[] = "pruning_controller"; -static const char __pyx_k_resizing_tree_to_d[] = "resizing tree to %d"; -static const char __pyx_k_strided_and_direct[] = ""; -static const char __pyx_k_NotImplementedError[] = "NotImplementedError"; -static const char __pyx_k_BestFirstTreeBuilder[] = "BestFirstTreeBuilder"; -static const char __pyx_k_strided_and_indirect[] = ""; -static const char __pyx_k_DepthFirstTreeBuilder[] = "DepthFirstTreeBuilder"; -static const char __pyx_k_build_pruned_tree_ccp[] = "_build_pruned_tree_ccp"; -static const char __pyx_k_contiguous_and_direct[] = ""; -static const char __pyx_k_min_impurity_decrease[] = "min_impurity_decrease"; -static const char __pyx_k_Can_t_initialize_array[] = "Can't initialize array."; -static const char __pyx_k_MemoryView_of_r_object[] = ""; -static const char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; -static const char __pyx_k_contiguous_and_indirect[] = ""; -static const char __pyx_k_weighted_n_node_samples[] = "weighted_n_node_samples"; -static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; -static const char __pyx_k_pyx_unpickle_TreeBuilder[] = "__pyx_unpickle_TreeBuilder"; -static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; -static const char __pyx_k_compute_feature_importances[] = "compute_feature_importances"; -static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; -static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; -static const char __pyx_k_pyx_unpickle__CCPPruneControll[] = "__pyx_unpickle__CCPPruneController"; -static const char __pyx_k_stpredictions_models_OK3__tree[] = "stpredictions.models.OK3._tree"; -static const char __pyx_k_strided_and_direct_or_indirect[] = ""; -static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; -static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; -static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; -static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview"; -static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview"; -static const char __pyx_k_Did_not_recognise_loaded_array_l[] = "Did not recognise loaded array layout"; -static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; -static const char __pyx_k_Incompatible_checksums_s_vs_0x57[] = "Incompatible checksums (%s vs 0x5739659 = (max_depth, min_impurity_decrease, min_impurity_split, min_samples_leaf, min_samples_split, min_weight_leaf, splitter))"; -static const char __pyx_k_Incompatible_checksums_s_vs_0xb0[] = "Incompatible checksums (%s vs 0xb068931 = (name))"; -static const char __pyx_k_Incompatible_checksums_s_vs_0xd4[] = "Incompatible checksums (%s vs 0xd41d8cd = ())"; -static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; -static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; -static const char __pyx_k_No_support_for_np_int64_index_ba[] = "No support for np.int64 index based sparse matrices"; -static const char __pyx_k_No_value_specified_for_struct_at[] = "No value specified for struct attribute 'left_child'"; -static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; -static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; -static const char __pyx_k_X_dtype_should_be_np_float32_got[] = "X.dtype should be np.float32, got %s"; -static const char __pyx_k_X_should_be_in_csr_matrix_format[] = "X should be in csr_matrix format, got %s"; -static const char __pyx_k_X_should_be_in_np_ndarray_format[] = "X should be in np.ndarray format, got %s"; -static const char __pyx_k_You_have_loaded_Tree_version_whi[] = "You have loaded Tree version which cannot be imported"; -static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; -static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; -static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; -static const char __pyx_k_only_the_KernelizedMSE_criterion[] = "only the \"KernelizedMSE\" criterion is supported"; -static const char __pyx_k_stpredictions_models_OK3__tree_p[] = "stpredictions/models/OK3/_tree.pyx"; -static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; -static const char __pyx_k_No_value_specified_for_struct_at_2[] = "No value specified for struct attribute 'right_child'"; -static const char __pyx_k_No_value_specified_for_struct_at_3[] = "No value specified for struct attribute 'feature'"; -static const char __pyx_k_No_value_specified_for_struct_at_4[] = "No value specified for struct attribute 'threshold'"; 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-static PyObject *__pyx_n_s_tree; -static PyObject *__pyx_n_s_uint8; -static PyObject *__pyx_kp_s_unable_to_allocate_array_data; -static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; -static PyObject *__pyx_n_s_unique; -static PyObject *__pyx_n_s_unpack; -static PyObject *__pyx_n_s_update; -static PyObject *__pyx_n_s_values; -static PyObject *__pyx_n_s_warnings; -static PyObject *__pyx_n_s_weighted_n_node_samples; -static PyObject *__pyx_n_s_where; -static PyObject *__pyx_n_s_y; -static PyObject *__pyx_n_s_zeros; -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_2__reduce_cython__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_4__setstate_cython__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_2build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf, PyObject *__pyx_v_min_weight_leaf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_leaf_nodes, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_13children_left___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_14children_right___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_8n_leaves___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_7feature___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_9threshold___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_8impurity___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_14n_node_samples___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_23weighted_n_node_samples___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_5value___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, int __pyx_v_n_features, int __pyx_v_n_samples); /* proto */ -static void __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_4__reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_6__getstate__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_8__setstate__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_d); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10predict(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_12decode_tree(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_K_cand_train, PyArrayObject *__pyx_v_sq_norms_cand, PyObject *__pyx_v_criterion, PyObject *__pyx_v_kernel, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_return_top_k); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_14apply(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_16decision_path(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_18compute_feature_importances(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_normalize); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10n_features___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10n_features_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_9max_depth___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_9max_depth_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10node_count___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10node_count_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_8capacity___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_8capacity_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_3K_y___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_3K_y_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_3K_y_4__del__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_1y___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_1y_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_1y_4__del__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController___reduce_cython__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController_2__setstate_cython__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_ccp_alpha); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_2__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_4__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_11_PathFinder___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *__pyx_v_self, int __pyx_v_node_count); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11_PathFinder_2__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11_PathFinder_4__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree__build_pruned_tree_ccp(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_orig_tree, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_ccp_alpha); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_2ccp_pruning_path(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_orig_tree); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4__pyx_unpickle_TreeBuilder(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_6__pyx_unpickle__CCPPruneController(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ -static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ -static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ -static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_12__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf___pyx_array___reduce_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_array_2__setstate_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ -static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_MemviewEnum___reduce_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_MemviewEnum_2__setstate_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ -static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ -static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ -static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); 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/* proto */ -static PyObject *__pyx_pf___pyx_memoryview___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_memoryview_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_memoryviewslice___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_15View_dot_MemoryView___pyx_unpickle_Enum(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); 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- __pyx_v_n_node_samples = __pyx_t_13; - - /* "stpredictions/models/OK3/_tree.pyx":330 - * - * cdef SIZE_t n_node_samples = splitter.n_samples - * cdef SIZE_t max_split_nodes = max_leaf_nodes - 1 # <<<<<<<<<<<<<< - * cdef bint is_leaf - * cdef SIZE_t max_depth_seen = -1 - */ - __pyx_v_max_split_nodes = (__pyx_v_max_leaf_nodes - 1); - - /* "stpredictions/models/OK3/_tree.pyx":332 - * cdef SIZE_t max_split_nodes = max_leaf_nodes - 1 - * cdef bint is_leaf - * cdef SIZE_t max_depth_seen = -1 # <<<<<<<<<<<<<< - * cdef int rc = 0 - * cdef Node* node - */ - __pyx_v_max_depth_seen = -1; - - /* "stpredictions/models/OK3/_tree.pyx":333 - * cdef bint is_leaf - * cdef SIZE_t max_depth_seen = -1 - * cdef int rc = 0 # <<<<<<<<<<<<<< - * cdef Node* node - * - */ - __pyx_v_rc = 0; - - /* "stpredictions/models/OK3/_tree.pyx":337 - * - * # Initial capacity - * cdef SIZE_t init_capacity = max_split_nodes + max_leaf_nodes # <<<<<<<<<<<<<< - * tree._resize(init_capacity) - * - */ - __pyx_v_init_capacity = (__pyx_v_max_split_nodes + __pyx_v_max_leaf_nodes); - - /* "stpredictions/models/OK3/_tree.pyx":338 - * # Initial capacity - * cdef SIZE_t init_capacity = max_split_nodes + max_leaf_nodes - * tree._resize(init_capacity) # <<<<<<<<<<<<<< - * - * with nogil: - */ - __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize(__pyx_v_tree, __pyx_v_init_capacity); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 338, __pyx_L1_error) - - /* "stpredictions/models/OK3/_tree.pyx":340 - * tree._resize(init_capacity) - * - * with nogil: # <<<<<<<<<<<<<< - * # add root to frontier - * rc = self._add_split_node(splitter, tree, 0, n_node_samples, - */ - { - #ifdef WITH_THREAD - PyThreadState *_save; - Py_UNBLOCK_THREADS - __Pyx_FastGIL_Remember(); - #endif - /*try:*/ { - - /* "stpredictions/models/OK3/_tree.pyx":342 - * with nogil: - * # add root to frontier - * rc = self._add_split_node(splitter, tree, 0, n_node_samples, # <<<<<<<<<<<<<< - * INFINITY, IS_FIRST, IS_LEFT, NULL, 0, - * &split_node_left, - */ - __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, 0, __pyx_v_n_node_samples, __pyx_v_13stpredictions_6models_3OK3_5_tree_INFINITY, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_FIRST, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_LEFT, NULL, 0, (&__pyx_v_split_node_left), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 342, __pyx_L7_error) - __pyx_v_rc = __pyx_t_5; - - /* "stpredictions/models/OK3/_tree.pyx":346 - * &split_node_left, - * y.shape[0]) - * if rc >= 0: # <<<<<<<<<<<<<< - * rc = _add_to_frontier(&split_node_left, frontier) - * - */ - __pyx_t_9 = ((__pyx_v_rc >= 0) != 0); - if (__pyx_t_9) { - - /* "stpredictions/models/OK3/_tree.pyx":347 - * y.shape[0]) - * if rc >= 0: - * rc = _add_to_frontier(&split_node_left, frontier) # <<<<<<<<<<<<<< - * - * if rc == -1: - */ - __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree__add_to_frontier((&__pyx_v_split_node_left), __pyx_v_frontier); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 347, __pyx_L7_error) - __pyx_v_rc = __pyx_t_5; - - /* "stpredictions/models/OK3/_tree.pyx":346 - * &split_node_left, - * y.shape[0]) - * if rc >= 0: # <<<<<<<<<<<<<< - * rc = _add_to_frontier(&split_node_left, frontier) - * - */ - } - - /* "stpredictions/models/OK3/_tree.pyx":349 - * rc = _add_to_frontier(&split_node_left, frontier) - * - * if rc == -1: # <<<<<<<<<<<<<< - * with gil: - * raise MemoryError() - */ - __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); - if (__pyx_t_9) { - - /* "stpredictions/models/OK3/_tree.pyx":350 - * - * if rc == -1: - * with gil: # <<<<<<<<<<<<<< - * raise MemoryError() - * - */ - { - #ifdef WITH_THREAD - PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); - #endif - /*try:*/ { - - /* "stpredictions/models/OK3/_tree.pyx":351 - * if rc == -1: - * with gil: - * raise MemoryError() # <<<<<<<<<<<<<< - * - * while not frontier.is_empty(): - */ - PyErr_NoMemory(); __PYX_ERR(0, 351, __pyx_L12_error) - } - - /* "stpredictions/models/OK3/_tree.pyx":350 - * - * if rc == -1: - * with gil: # <<<<<<<<<<<<<< - * raise MemoryError() - * - */ - /*finally:*/ { - __pyx_L12_error: { - #ifdef WITH_THREAD - __Pyx_PyGILState_Release(__pyx_gilstate_save); - #endif - goto __pyx_L7_error; - } - } - } - - /* "stpredictions/models/OK3/_tree.pyx":349 - * rc = _add_to_frontier(&split_node_left, frontier) - * - * if rc == -1: # <<<<<<<<<<<<<< - * with gil: - * raise MemoryError() - */ - } - - /* "stpredictions/models/OK3/_tree.pyx":353 - * raise MemoryError() - * - * while not frontier.is_empty(): # <<<<<<<<<<<<<< - * frontier.pop(&record) - * - */ - while (1) { - __pyx_t_9 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->is_empty(__pyx_v_frontier) != 0)) != 0); - if (!__pyx_t_9) break; - - /* "stpredictions/models/OK3/_tree.pyx":354 - * - * while not frontier.is_empty(): - * frontier.pop(&record) # <<<<<<<<<<<<<< - * - * node = &tree.nodes[record.node_id] - */ - (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->pop(__pyx_v_frontier, (&__pyx_v_record))); - - /* "stpredictions/models/OK3/_tree.pyx":356 - * frontier.pop(&record) - * - * node = &tree.nodes[record.node_id] # <<<<<<<<<<<<<< - * is_leaf = (record.is_leaf or max_split_nodes <= 0) - * - */ - __pyx_v_node = (&(__pyx_v_tree->nodes[__pyx_v_record.node_id])); - - /* "stpredictions/models/OK3/_tree.pyx":357 - * - * node = &tree.nodes[record.node_id] - * is_leaf = (record.is_leaf or max_split_nodes <= 0) # <<<<<<<<<<<<<< - * - * if is_leaf: - */ - __pyx_t_8 = (__pyx_v_record.is_leaf != 0); - if (!__pyx_t_8) { - } else { - __pyx_t_9 = __pyx_t_8; - goto __pyx_L16_bool_binop_done; - } - __pyx_t_8 = ((__pyx_v_max_split_nodes <= 0) != 0); - __pyx_t_9 = __pyx_t_8; - __pyx_L16_bool_binop_done:; - __pyx_v_is_leaf = __pyx_t_9; - - /* "stpredictions/models/OK3/_tree.pyx":359 - * is_leaf = (record.is_leaf or max_split_nodes <= 0) - * - * if is_leaf: # <<<<<<<<<<<<<< - * # Node is not expandable; set node as leaf - * node.left_child = _TREE_LEAF - */ - __pyx_t_9 = (__pyx_v_is_leaf != 0); - if (__pyx_t_9) { - - /* "stpredictions/models/OK3/_tree.pyx":361 - * if is_leaf: - * # Node is not expandable; set node as leaf - * node.left_child = _TREE_LEAF # <<<<<<<<<<<<<< - * node.right_child = _TREE_LEAF - * node.feature = _TREE_UNDEFINED - */ - __pyx_v_node->left_child = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF; - - /* "stpredictions/models/OK3/_tree.pyx":362 - * # Node is not expandable; set node as leaf - * node.left_child = _TREE_LEAF - * node.right_child = _TREE_LEAF # <<<<<<<<<<<<<< - * node.feature = _TREE_UNDEFINED - * node.threshold = _TREE_UNDEFINED - */ - __pyx_v_node->right_child = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF; - - /* "stpredictions/models/OK3/_tree.pyx":363 - * node.left_child = _TREE_LEAF - * node.right_child = _TREE_LEAF - * node.feature = _TREE_UNDEFINED # <<<<<<<<<<<<<< - * node.threshold = _TREE_UNDEFINED - * - */ - __pyx_v_node->feature = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED; - - /* "stpredictions/models/OK3/_tree.pyx":364 - * node.right_child = _TREE_LEAF - * node.feature = _TREE_UNDEFINED - * node.threshold = _TREE_UNDEFINED # <<<<<<<<<<<<<< - * - * else: - */ - __pyx_v_node->threshold = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED; - - /* "stpredictions/models/OK3/_tree.pyx":359 - * is_leaf = (record.is_leaf or max_split_nodes <= 0) - * - * if is_leaf: # <<<<<<<<<<<<<< - * # Node is not expandable; set node as leaf - * node.left_child = _TREE_LEAF - */ - goto __pyx_L18; - } - - /* "stpredictions/models/OK3/_tree.pyx":370 - * - * # Decrement number of split nodes available - * max_split_nodes -= 1 # <<<<<<<<<<<<<< - * - * # Compute left split node - */ - /*else*/ { - __pyx_v_max_split_nodes = (__pyx_v_max_split_nodes - 1); - - /* "stpredictions/models/OK3/_tree.pyx":373 - * - * # Compute left split node - * rc = self._add_split_node(splitter, tree, # <<<<<<<<<<<<<< - * record.start, record.pos, - * record.impurity_left, - */ - __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, __pyx_v_record.start, __pyx_v_record.pos, __pyx_v_record.impurity_left, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_FIRST, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_LEFT, __pyx_v_node, (__pyx_v_record.depth + 1), (&__pyx_v_split_node_left), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 373, __pyx_L7_error) - __pyx_v_rc = __pyx_t_5; - - /* "stpredictions/models/OK3/_tree.pyx":380 - * &split_node_left, - * y.shape[0]) - * if rc == -1: # <<<<<<<<<<<<<< - * break - * - */ - __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); - if (__pyx_t_9) { - - /* "stpredictions/models/OK3/_tree.pyx":381 - * y.shape[0]) - * if rc == -1: - * break # <<<<<<<<<<<<<< - * - * # tree.nodes may have changed - */ - goto __pyx_L15_break; - - /* "stpredictions/models/OK3/_tree.pyx":380 - * &split_node_left, - * y.shape[0]) - * if rc == -1: # <<<<<<<<<<<<<< - * break - * - */ - } - - /* "stpredictions/models/OK3/_tree.pyx":384 - * - * # tree.nodes may have changed - * node = &tree.nodes[record.node_id] # <<<<<<<<<<<<<< - * - * # Compute right split node - */ - __pyx_v_node = (&(__pyx_v_tree->nodes[__pyx_v_record.node_id])); - - /* "stpredictions/models/OK3/_tree.pyx":387 - * - * # Compute right split node - * rc = self._add_split_node(splitter, tree, record.pos, # <<<<<<<<<<<<<< - * record.end, - * record.impurity_right, - */ - __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, __pyx_v_record.pos, __pyx_v_record.end, __pyx_v_record.impurity_right, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_FIRST, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_LEFT, __pyx_v_node, (__pyx_v_record.depth + 1), (&__pyx_v_split_node_right), (__pyx_v_y->dimensions[0])); 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- __pyx_t_4 = __pyx_v_i; - __pyx_t_14 = __pyx_v_i; - __pyx_v_subtree_alpha = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))) - (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )))) / ((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) ))) - 1)); - - /* "stpredictions/models/OK3/_tree.pyx":1496 - * continue - * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) - * if subtree_alpha < effective_alpha: # <<<<<<<<<<<<<< - * effective_alpha = subtree_alpha - * pruned_branch_node_idx = i - */ - __pyx_t_16 = ((__pyx_v_subtree_alpha < __pyx_v_effective_alpha) != 0); - if (__pyx_t_16) { - - /* "stpredictions/models/OK3/_tree.pyx":1497 - * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) - * if subtree_alpha < effective_alpha: - * effective_alpha = subtree_alpha # <<<<<<<<<<<<<< - * pruned_branch_node_idx = i - * - */ - __pyx_v_effective_alpha = __pyx_v_subtree_alpha; 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- if (__pyx_t_1) { - } else { - __pyx_t_2 = __pyx_t_1; - goto __pyx_L9_bool_binop_done; - } - __pyx_t_1 = ((__pyx_v_step == 0) != 0); - __pyx_t_2 = __pyx_t_1; - __pyx_L9_bool_binop_done:; - if (__pyx_t_2) { - - /* "View.MemoryView":838 - * - * if have_step and step == 0: - * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) # <<<<<<<<<<<<<< - * - * - */ - __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Step may not be zero (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(1, 838, __pyx_L1_error) - - /* "View.MemoryView":837 - * negative_step = have_step != 0 and step < 0 - * - * if have_step and step == 0: # <<<<<<<<<<<<<< - * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) - * - */ - } - - /* "View.MemoryView":841 - * - * - * if have_start: # <<<<<<<<<<<<<< - * if start < 0: - * start += shape - */ - __pyx_t_2 = (__pyx_v_have_start != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":842 - * - * if have_start: - * if start < 0: # <<<<<<<<<<<<<< - * start += shape - * if start < 0: - */ - __pyx_t_2 = ((__pyx_v_start < 0) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":843 - * if have_start: - * if start < 0: - * start += shape # <<<<<<<<<<<<<< - * if start < 0: - * start = 0 - */ - __pyx_v_start = (__pyx_v_start + __pyx_v_shape); - - /* "View.MemoryView":844 - * if start < 0: - * start += shape - * if start < 0: # <<<<<<<<<<<<<< - * start = 0 - * elif start >= shape: - */ - __pyx_t_2 = ((__pyx_v_start < 0) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":845 - * start += shape - * if start < 0: - * start = 0 # <<<<<<<<<<<<<< - * elif start >= shape: - * if negative_step: - */ - __pyx_v_start = 0; - - /* "View.MemoryView":844 - * if start < 0: - * start += shape - * if start < 0: # <<<<<<<<<<<<<< - * start = 0 - * elif start >= shape: - */ - } - - /* "View.MemoryView":842 - * - * if have_start: - * if start < 0: # <<<<<<<<<<<<<< - * start += shape - * if start < 0: - */ - goto __pyx_L12; - } - - /* "View.MemoryView":846 - * if start < 0: - * start = 0 - * elif start >= shape: # <<<<<<<<<<<<<< - * if negative_step: - * start = shape - 1 - */ - __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":847 - * start = 0 - * elif start >= shape: - * if negative_step: # <<<<<<<<<<<<<< - * start = shape - 1 - * else: - */ - __pyx_t_2 = (__pyx_v_negative_step != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":848 - * elif start >= shape: - * if negative_step: - * start = shape - 1 # <<<<<<<<<<<<<< - * else: - * start = shape - */ - __pyx_v_start = (__pyx_v_shape - 1); - - /* "View.MemoryView":847 - * start = 0 - * elif start >= shape: - * if negative_step: # <<<<<<<<<<<<<< - * start = shape - 1 - * else: - */ - goto __pyx_L14; - } - - /* "View.MemoryView":850 - * start = shape - 1 - * else: - * start = shape # <<<<<<<<<<<<<< - * else: - * if negative_step: - */ - /*else*/ { - __pyx_v_start = __pyx_v_shape; - } - __pyx_L14:; - - /* "View.MemoryView":846 - * if start < 0: - * start = 0 - * elif start >= shape: # <<<<<<<<<<<<<< - * if negative_step: - * start = shape - 1 - */ - } - __pyx_L12:; - - /* "View.MemoryView":841 - * - * - * if have_start: # <<<<<<<<<<<<<< - * if start < 0: - * start += shape - */ - goto __pyx_L11; - } - - /* "View.MemoryView":852 - * start = shape - * else: - * if negative_step: # <<<<<<<<<<<<<< - * start = shape - 1 - * else: - */ - /*else*/ { - __pyx_t_2 = (__pyx_v_negative_step != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":853 - * else: - * if negative_step: - * start = shape - 1 # <<<<<<<<<<<<<< - * else: - * start = 0 - */ - __pyx_v_start = (__pyx_v_shape - 1); - - /* "View.MemoryView":852 - * start = shape - * else: - * if negative_step: # <<<<<<<<<<<<<< - * start = shape - 1 - * else: - */ - goto __pyx_L15; - } - - /* "View.MemoryView":855 - * start = shape - 1 - * else: - * start = 0 # <<<<<<<<<<<<<< - * - * if have_stop: - */ - /*else*/ { - __pyx_v_start = 0; - } - __pyx_L15:; - } - __pyx_L11:; - - /* "View.MemoryView":857 - * start = 0 - * - * if have_stop: # <<<<<<<<<<<<<< - * if stop < 0: - * stop += shape - */ - __pyx_t_2 = (__pyx_v_have_stop != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":858 - * - * if have_stop: - * if stop < 0: # <<<<<<<<<<<<<< - * stop += shape - * if stop < 0: - */ - __pyx_t_2 = ((__pyx_v_stop < 0) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":859 - * if have_stop: - * if stop < 0: - * stop += shape # <<<<<<<<<<<<<< - * if stop < 0: - * stop = 0 - */ - __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape); - - /* "View.MemoryView":860 - * if stop < 0: - * stop += shape - * if stop < 0: # <<<<<<<<<<<<<< - * stop = 0 - * elif stop > shape: - */ - __pyx_t_2 = ((__pyx_v_stop < 0) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":861 - * stop += shape - * if stop < 0: - * stop = 0 # <<<<<<<<<<<<<< - * elif stop > shape: - * stop = shape - */ - __pyx_v_stop = 0; - - /* "View.MemoryView":860 - * if stop < 0: - * stop += shape - * if stop < 0: # <<<<<<<<<<<<<< - * stop = 0 - * elif stop > shape: - */ - } - - /* "View.MemoryView":858 - * - * if have_stop: - * if stop < 0: # <<<<<<<<<<<<<< - * stop += shape - * if stop < 0: - */ - goto __pyx_L17; - } - - /* "View.MemoryView":862 - * if stop < 0: - * stop = 0 - * elif stop > shape: # <<<<<<<<<<<<<< - * stop = shape - * else: - */ - __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":863 - * stop = 0 - * elif stop > shape: - * stop = shape # <<<<<<<<<<<<<< - * else: - * if negative_step: - */ - __pyx_v_stop = __pyx_v_shape; - - /* "View.MemoryView":862 - * if stop < 0: - * stop = 0 - * elif stop > shape: # <<<<<<<<<<<<<< - * stop = shape - * else: - */ - } - __pyx_L17:; - - /* "View.MemoryView":857 - * start = 0 - * - * if have_stop: # <<<<<<<<<<<<<< - * if stop < 0: - * stop += shape - */ - goto __pyx_L16; - } - - /* "View.MemoryView":865 - * stop = shape - * else: - * if negative_step: # <<<<<<<<<<<<<< - * stop = -1 - * else: - */ - /*else*/ { - __pyx_t_2 = (__pyx_v_negative_step != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":866 - * else: - * if negative_step: - * stop = -1 # <<<<<<<<<<<<<< - * else: - * stop = shape - */ - __pyx_v_stop = -1L; - - /* "View.MemoryView":865 - * stop = shape - * else: - * if negative_step: # <<<<<<<<<<<<<< - * stop = -1 - * else: - */ - goto __pyx_L19; - } - - /* "View.MemoryView":868 - * stop = -1 - * else: - * stop = shape # <<<<<<<<<<<<<< - * - * if not have_step: - */ - /*else*/ { - __pyx_v_stop = __pyx_v_shape; - } - __pyx_L19:; - } - __pyx_L16:; - - /* "View.MemoryView":870 - * stop = shape - * - * if not have_step: # <<<<<<<<<<<<<< - * step = 1 - * - */ - __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":871 - * - * if not have_step: - * step = 1 # <<<<<<<<<<<<<< - * - * - */ - __pyx_v_step = 1; - - /* "View.MemoryView":870 - * stop = shape - * - * if not have_step: # <<<<<<<<<<<<<< - * step = 1 - * - */ - } - - /* "View.MemoryView":875 - * - * with cython.cdivision(True): - * new_shape = (stop - start) // step # <<<<<<<<<<<<<< - * - * if (stop - start) - step * new_shape: - */ - __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step); - - /* "View.MemoryView":877 - * new_shape = (stop - start) // step - * - * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< - * new_shape += 1 - * - */ - __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0); - if (__pyx_t_2) { - - /* "View.MemoryView":878 - * - * if (stop - start) - step * new_shape: - * new_shape += 1 # <<<<<<<<<<<<<< - * - * if new_shape < 0: - */ - __pyx_v_new_shape = (__pyx_v_new_shape + 1); 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- if (__pyx_t_2) { - - /* "View.MemoryView":1126 - * for i in range(ndim - 1, -1, -1): - * if mslice.shape[i] > 1: - * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< - * break - * - */ - __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]); - - /* "View.MemoryView":1127 - * if mslice.shape[i] > 1: - * c_stride = mslice.strides[i] - * break # <<<<<<<<<<<<<< - * - * for i in range(ndim): - */ - goto __pyx_L4_break; - - /* "View.MemoryView":1125 - * - * for i in range(ndim - 1, -1, -1): - * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< - * c_stride = mslice.strides[i] - * break - */ - } - } - __pyx_L4_break:; - - /* "View.MemoryView":1129 - * break - * - * for i in range(ndim): # <<<<<<<<<<<<<< - * if mslice.shape[i] > 1: - * f_stride = mslice.strides[i] - */ - __pyx_t_1 = __pyx_v_ndim; - __pyx_t_3 = __pyx_t_1; - for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { - __pyx_v_i = __pyx_t_4; - - /* "View.MemoryView":1130 - * - * for i in range(ndim): - * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< - * f_stride = mslice.strides[i] - * break - */ - __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); 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- } - - /* "View.MemoryView":1154 - * if ndim == 1: - * if (src_stride > 0 and dst_stride > 0 and - * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< - * memcpy(dst_data, src_data, itemsize * dst_extent) - * else: - */ - __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); - if (__pyx_t_2) { - __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); - } - __pyx_t_3 = (__pyx_t_2 != 0); - __pyx_t_1 = __pyx_t_3; - __pyx_L5_bool_binop_done:; - - /* "View.MemoryView":1153 - * - * if ndim == 1: - * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< - * src_stride == itemsize == dst_stride): - * memcpy(dst_data, src_data, itemsize * dst_extent) - */ - if (__pyx_t_1) { - - /* "View.MemoryView":1155 - * if (src_stride > 0 and dst_stride > 0 and - * src_stride == itemsize == dst_stride): - * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< - * else: - * for i in range(dst_extent): - */ - (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); 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if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_1__cinit__(o, a, k) < 0)) goto bad; - return o; - bad: - Py_DECREF(o); o = 0; - return NULL; -} - -static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder[] = { - {"build", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_3build, METH_VARARGS|METH_KEYWORDS, __pyx_doc_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_2build}, - {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_5__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_7__setstate_cython__, METH_O, 0}, - {0, 0, 0, 0} -}; - -static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder = { - PyVarObject_HEAD_INIT(0, 0) - "stpredictions.models.OK3._tree.DepthFirstTreeBuilder", /*tp_name*/ - 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0, /*tp_traverse*/ - 0, /*tp_clear*/ - 0, /*tp_richcompare*/ - 0, /*tp_weaklistoffset*/ - 0, /*tp_iter*/ - 0, /*tp_iternext*/ - __pyx_methods_13stpredictions_6models_3OK3_5_tree__CCPPruneController, /*tp_methods*/ - 0, /*tp_members*/ - 0, /*tp_getset*/ - 0, /*tp_base*/ - 0, /*tp_dict*/ - 0, /*tp_descr_get*/ - 0, /*tp_descr_set*/ - 0, /*tp_dictoffset*/ - 0, /*tp_init*/ - 0, /*tp_alloc*/ - __pyx_tp_new_13stpredictions_6models_3OK3_5_tree__CCPPruneController, /*tp_new*/ - 0, /*tp_free*/ - 0, /*tp_is_gc*/ - 0, /*tp_bases*/ - 0, /*tp_mro*/ - 0, /*tp_cache*/ - 0, /*tp_subclasses*/ - 0, /*tp_weaklist*/ - 0, /*tp_del*/ - 0, /*tp_version_tag*/ - #if PY_VERSION_HEX >= 0x030400a1 - 0, /*tp_finalize*/ - #endif - #if PY_VERSION_HEX >= 0x030800b1 - 0, /*tp_vectorcall*/ - #endif - #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 - 0, /*tp_print*/ - #endif -}; -static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__AlphaPruner __pyx_vtable_13stpredictions_6models_3OK3_5_tree__AlphaPruner; - 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(PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); -#else - dictptr = _PyObject_GetDictPtr(obj); -#endif - } - return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; -} -static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { - PyObject *dict = Py_TYPE(obj)->tp_dict; - if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) - return 0; - return obj_dict_version == __Pyx_get_object_dict_version(obj); -} -#endif - -/* PyFunctionFastCall */ -#if CYTHON_FAST_PYCALL -static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, - PyObject *globals) { - PyFrameObject *f; - PyThreadState *tstate = __Pyx_PyThreadState_Current; - PyObject **fastlocals; - Py_ssize_t i; - PyObject *result; - assert(globals != NULL); - /* XXX Perhaps we should create a specialized - PyFrame_New() that doesn't take locals, but does - take builtins without sanity checking them. - */ - assert(tstate != NULL); - f = PyFrame_New(tstate, co, globals, NULL); - if (f == NULL) { - return NULL; - } - fastlocals = __Pyx_PyFrame_GetLocalsplus(f); - for (i = 0; i < na; i++) { - Py_INCREF(*args); - fastlocals[i] = *args++; - } - result = PyEval_EvalFrameEx(f,0); - ++tstate->recursion_depth; - Py_DECREF(f); - --tstate->recursion_depth; - return result; -} -#if 1 || PY_VERSION_HEX < 0x030600B1 -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { - PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); - PyObject *globals = PyFunction_GET_GLOBALS(func); - PyObject *argdefs = PyFunction_GET_DEFAULTS(func); - PyObject *closure; -#if PY_MAJOR_VERSION >= 3 - PyObject *kwdefs; -#endif - PyObject *kwtuple, **k; - PyObject **d; - Py_ssize_t nd; - Py_ssize_t nk; - PyObject *result; - assert(kwargs == NULL || PyDict_Check(kwargs)); - nk = kwargs ? PyDict_Size(kwargs) : 0; - if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { - return NULL; - } - if ( -#if PY_MAJOR_VERSION >= 3 - co->co_kwonlyargcount == 0 && -#endif - likely(kwargs == NULL || nk == 0) && - co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { - if (argdefs == NULL && co->co_argcount == nargs) { - result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); - goto done; - } - else if (nargs == 0 && argdefs != NULL - && co->co_argcount == Py_SIZE(argdefs)) { - /* function called with no arguments, but all parameters have - a default value: use default values as arguments .*/ - args = &PyTuple_GET_ITEM(argdefs, 0); - result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); - goto done; - } - } - if (kwargs != NULL) { - Py_ssize_t pos, i; - kwtuple = PyTuple_New(2 * nk); - if (kwtuple == NULL) { - result = NULL; - goto done; - } - k = &PyTuple_GET_ITEM(kwtuple, 0); - pos = i = 0; - while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { - Py_INCREF(k[i]); - Py_INCREF(k[i+1]); - i += 2; - } - nk = i / 2; - } - else { - kwtuple = NULL; - k = NULL; - } - closure = PyFunction_GET_CLOSURE(func); -#if PY_MAJOR_VERSION >= 3 - kwdefs = PyFunction_GET_KW_DEFAULTS(func); -#endif - if (argdefs != NULL) { - d = &PyTuple_GET_ITEM(argdefs, 0); - nd = Py_SIZE(argdefs); - } - else { - d = NULL; - nd = 0; - } -#if PY_MAJOR_VERSION >= 3 - result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, - args, (int)nargs, - k, (int)nk, - d, (int)nd, kwdefs, closure); -#else - result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, - args, (int)nargs, - k, (int)nk, - d, (int)nd, closure); -#endif - Py_XDECREF(kwtuple); -done: - Py_LeaveRecursiveCall(); - return result; -} -#endif -#endif - -/* PyCFunctionFastCall */ -#if CYTHON_FAST_PYCCALL -static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { - PyCFunctionObject *func = (PyCFunctionObject*)func_obj; - PyCFunction meth = PyCFunction_GET_FUNCTION(func); - PyObject *self = PyCFunction_GET_SELF(func); - int flags = PyCFunction_GET_FLAGS(func); - assert(PyCFunction_Check(func)); - assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); - assert(nargs >= 0); - assert(nargs == 0 || args != NULL); - /* _PyCFunction_FastCallDict() must not be called with an exception set, - because it may clear it (directly or indirectly) and so the - caller loses its exception */ - assert(!PyErr_Occurred()); - if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { - return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); - } else { - return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); - } -} -#endif - -/* PyObjectCall */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { - PyObject *result; - ternaryfunc call = func->ob_type->tp_call; - if (unlikely(!call)) - return PyObject_Call(func, arg, kw); - if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) - return NULL; - result = (*call)(func, arg, kw); - Py_LeaveRecursiveCall(); - if (unlikely(!result) && unlikely(!PyErr_Occurred())) { - PyErr_SetString( - PyExc_SystemError, - "NULL result without error in PyObject_Call"); - } - return result; -} -#endif - -/* RaiseArgTupleInvalid */ -static void __Pyx_RaiseArgtupleInvalid( - const char* func_name, - int exact, - Py_ssize_t num_min, - Py_ssize_t num_max, - Py_ssize_t num_found) -{ - Py_ssize_t num_expected; - const char *more_or_less; - if (num_found < num_min) { - num_expected = num_min; - more_or_less = "at least"; - } else { - num_expected = num_max; - more_or_less = "at most"; - } - if (exact) { - more_or_less = "exactly"; - } - PyErr_Format(PyExc_TypeError, - "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", - func_name, more_or_less, num_expected, - (num_expected == 1) ? "" : "s", num_found); -} - -/* RaiseDoubleKeywords */ -static void __Pyx_RaiseDoubleKeywordsError( - const char* func_name, - PyObject* kw_name) -{ - PyErr_Format(PyExc_TypeError, - #if PY_MAJOR_VERSION >= 3 - "%s() got multiple values for keyword argument '%U'", func_name, kw_name); - #else - "%s() got multiple values for keyword argument '%s'", func_name, - PyString_AsString(kw_name)); - #endif -} - -/* ParseKeywords */ -static int __Pyx_ParseOptionalKeywords( - PyObject *kwds, - PyObject **argnames[], - PyObject *kwds2, - PyObject *values[], - Py_ssize_t num_pos_args, - const char* function_name) -{ - PyObject *key = 0, *value = 0; - Py_ssize_t pos = 0; - PyObject*** name; - PyObject*** first_kw_arg = argnames + num_pos_args; - while (PyDict_Next(kwds, &pos, &key, &value)) { - name = first_kw_arg; - while (*name && (**name != key)) name++; - if (*name) { - values[name-argnames] = value; - continue; - } - name = first_kw_arg; - #if PY_MAJOR_VERSION < 3 - if (likely(PyString_Check(key))) { - while (*name) { - if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) - && _PyString_Eq(**name, key)) { - values[name-argnames] = value; - break; - } - name++; - } - if (*name) continue; - else { - PyObject*** argname = argnames; - while (argname != first_kw_arg) { - if ((**argname == key) || ( - (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) - && _PyString_Eq(**argname, key))) { - goto arg_passed_twice; - } - argname++; - } - } - } else - #endif - if (likely(PyUnicode_Check(key))) { - while (*name) { - int cmp = (**name == key) ? 0 : - #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : - #endif - PyUnicode_Compare(**name, key); - if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; - if (cmp == 0) { - values[name-argnames] = value; - break; - } - name++; - } - if (*name) continue; - else { - PyObject*** argname = argnames; - while (argname != first_kw_arg) { - int cmp = (**argname == key) ? 0 : - #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : - #endif - PyUnicode_Compare(**argname, key); - if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; - if (cmp == 0) goto arg_passed_twice; - argname++; - } - } - } else - goto invalid_keyword_type; - if (kwds2) { - if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; - } else { - goto invalid_keyword; - } - } - return 0; -arg_passed_twice: - __Pyx_RaiseDoubleKeywordsError(function_name, key); - goto bad; -invalid_keyword_type: - PyErr_Format(PyExc_TypeError, - "%.200s() keywords must be strings", function_name); - goto bad; -invalid_keyword: - PyErr_Format(PyExc_TypeError, - #if PY_MAJOR_VERSION < 3 - "%.200s() got an unexpected keyword argument '%.200s'", - function_name, PyString_AsString(key)); - #else - "%s() got an unexpected keyword argument '%U'", - function_name, key); - #endif -bad: - return -1; -} - -/* ArgTypeTest */ -static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) -{ - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - else if (exact) { - #if PY_MAJOR_VERSION == 2 - if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; - #endif - } - else { - if (likely(__Pyx_TypeCheck(obj, type))) return 1; - } - PyErr_Format(PyExc_TypeError, - "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", - name, type->tp_name, Py_TYPE(obj)->tp_name); - return 0; -} - -/* GetModuleGlobalName */ -#if CYTHON_USE_DICT_VERSIONS -static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) -#else -static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) -#endif -{ - PyObject *result; -#if !CYTHON_AVOID_BORROWED_REFS -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 - result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); - __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return __Pyx_NewRef(result); - } else if (unlikely(PyErr_Occurred())) { - return NULL; - } -#else - result = PyDict_GetItem(__pyx_d, name); - __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return __Pyx_NewRef(result); - } -#endif -#else - result = PyObject_GetItem(__pyx_d, name); - __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return __Pyx_NewRef(result); - } - PyErr_Clear(); -#endif - return __Pyx_GetBuiltinName(name); -} - -/* PyObjectCall2Args */ -static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { - PyObject *args, *result = NULL; - #if CYTHON_FAST_PYCALL - if (PyFunction_Check(function)) { - PyObject *args[2] = {arg1, arg2}; - return __Pyx_PyFunction_FastCall(function, args, 2); - } - #endif - #if CYTHON_FAST_PYCCALL - if (__Pyx_PyFastCFunction_Check(function)) { - PyObject *args[2] = {arg1, arg2}; - return __Pyx_PyCFunction_FastCall(function, args, 2); - } - #endif - args = PyTuple_New(2); - if (unlikely(!args)) goto done; - Py_INCREF(arg1); - PyTuple_SET_ITEM(args, 0, arg1); - Py_INCREF(arg2); - PyTuple_SET_ITEM(args, 1, arg2); - Py_INCREF(function); - result = __Pyx_PyObject_Call(function, args, NULL); - Py_DECREF(args); - Py_DECREF(function); -done: - return result; -} - -/* PyObjectCallMethO */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { - PyObject *self, *result; - PyCFunction cfunc; - cfunc = PyCFunction_GET_FUNCTION(func); - self = PyCFunction_GET_SELF(func); - if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) - return NULL; - result = cfunc(self, arg); - Py_LeaveRecursiveCall(); - if (unlikely(!result) && unlikely(!PyErr_Occurred())) { - PyErr_SetString( - PyExc_SystemError, - "NULL result without error in PyObject_Call"); - } - return result; -} -#endif - -/* PyObjectCallOneArg */ -#if CYTHON_COMPILING_IN_CPYTHON -static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *result; - PyObject *args = PyTuple_New(1); - if (unlikely(!args)) return NULL; - Py_INCREF(arg); - PyTuple_SET_ITEM(args, 0, arg); - result = __Pyx_PyObject_Call(func, args, NULL); - Py_DECREF(args); - return result; -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { -#if CYTHON_FAST_PYCALL - if (PyFunction_Check(func)) { - return __Pyx_PyFunction_FastCall(func, &arg, 1); - } -#endif - if (likely(PyCFunction_Check(func))) { - if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { - return __Pyx_PyObject_CallMethO(func, arg); -#if CYTHON_FAST_PYCCALL - } else if (__Pyx_PyFastCFunction_Check(func)) { - return __Pyx_PyCFunction_FastCall(func, &arg, 1); -#endif - } - } - return __Pyx__PyObject_CallOneArg(func, arg); -} -#else -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *result; - PyObject *args = PyTuple_Pack(1, arg); - if (unlikely(!args)) return NULL; - result = __Pyx_PyObject_Call(func, args, NULL); - Py_DECREF(args); - return result; -} -#endif - -/* PyObjectCallNoArg */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { -#if CYTHON_FAST_PYCALL - if (PyFunction_Check(func)) { - return __Pyx_PyFunction_FastCall(func, NULL, 0); - } -#endif -#ifdef __Pyx_CyFunction_USED - if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) -#else - if (likely(PyCFunction_Check(func))) -#endif - { - if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { - return __Pyx_PyObject_CallMethO(func, NULL); - } - } - return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); -} -#endif - -/* PyObjectSetAttrStr */ -#if CYTHON_USE_TYPE_SLOTS -static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value) { - PyTypeObject* tp = Py_TYPE(obj); - if (likely(tp->tp_setattro)) - return tp->tp_setattro(obj, attr_name, value); -#if PY_MAJOR_VERSION < 3 - if (likely(tp->tp_setattr)) - return tp->tp_setattr(obj, PyString_AS_STRING(attr_name), value); -#endif - return PyObject_SetAttr(obj, attr_name, value); -} -#endif - -/* PyErrFetchRestore */ -#if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - tmp_type = tstate->curexc_type; - tmp_value = tstate->curexc_value; - tmp_tb = tstate->curexc_traceback; - tstate->curexc_type = type; - tstate->curexc_value = value; - tstate->curexc_traceback = tb; - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - *type = tstate->curexc_type; - *value = tstate->curexc_value; - *tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -} -#endif - -/* RaiseException */ -#if PY_MAJOR_VERSION < 3 -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, - CYTHON_UNUSED PyObject *cause) { - __Pyx_PyThreadState_declare - Py_XINCREF(type); - if (!value || value == Py_None) - value = NULL; - else - Py_INCREF(value); - if (!tb || tb == Py_None) - tb = NULL; - else { - Py_INCREF(tb); - if (!PyTraceBack_Check(tb)) { - PyErr_SetString(PyExc_TypeError, - "raise: arg 3 must be a traceback or None"); - goto raise_error; - } - } - if (PyType_Check(type)) { -#if CYTHON_COMPILING_IN_PYPY - if (!value) { - Py_INCREF(Py_None); - value = Py_None; - } -#endif - PyErr_NormalizeException(&type, &value, &tb); - } else { - if (value) { - PyErr_SetString(PyExc_TypeError, - "instance exception may not have a separate value"); - goto raise_error; - } - value = type; - type = (PyObject*) Py_TYPE(type); - Py_INCREF(type); - if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { - PyErr_SetString(PyExc_TypeError, - "raise: exception class must be a subclass of BaseException"); - goto raise_error; - } - } - __Pyx_PyThreadState_assign - __Pyx_ErrRestore(type, value, tb); - return; -raise_error: - Py_XDECREF(value); - Py_XDECREF(type); - Py_XDECREF(tb); - return; -} -#else -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { - PyObject* owned_instance = NULL; - if (tb == Py_None) { - tb = 0; - } else if (tb && !PyTraceBack_Check(tb)) { - PyErr_SetString(PyExc_TypeError, - "raise: arg 3 must be a traceback or None"); - goto bad; - } - if (value == Py_None) - value = 0; - if (PyExceptionInstance_Check(type)) { - if (value) { - PyErr_SetString(PyExc_TypeError, - "instance exception may not have a separate value"); - goto bad; - } - value = type; - type = (PyObject*) Py_TYPE(value); - } else if (PyExceptionClass_Check(type)) { - PyObject *instance_class = NULL; - if (value && PyExceptionInstance_Check(value)) { - instance_class = (PyObject*) Py_TYPE(value); - if (instance_class != type) { - int is_subclass = PyObject_IsSubclass(instance_class, type); - if (!is_subclass) { - instance_class = NULL; - } else if (unlikely(is_subclass == -1)) { - goto bad; - } else { - type = instance_class; - } - } - } - if (!instance_class) { - PyObject *args; - if (!value) - args = PyTuple_New(0); - else if (PyTuple_Check(value)) { - Py_INCREF(value); - args = value; - } else - args = PyTuple_Pack(1, value); - if (!args) - goto bad; - owned_instance = PyObject_Call(type, args, NULL); - Py_DECREF(args); - if (!owned_instance) - goto bad; - value = owned_instance; - if (!PyExceptionInstance_Check(value)) { - PyErr_Format(PyExc_TypeError, - "calling %R should have returned an instance of " - "BaseException, not %R", - type, Py_TYPE(value)); - goto bad; - } - } - } else { - PyErr_SetString(PyExc_TypeError, - "raise: exception class must be a subclass of BaseException"); - goto bad; - } - if (cause) { - PyObject *fixed_cause; - if (cause == Py_None) { - fixed_cause = NULL; - } else if (PyExceptionClass_Check(cause)) { - fixed_cause = PyObject_CallObject(cause, NULL); - if (fixed_cause == NULL) - goto bad; - } else if (PyExceptionInstance_Check(cause)) { - fixed_cause = cause; - Py_INCREF(fixed_cause); - } else { - PyErr_SetString(PyExc_TypeError, - "exception causes must derive from " - "BaseException"); - goto bad; - } - PyException_SetCause(value, fixed_cause); - } - PyErr_SetObject(type, value); - if (tb) { -#if CYTHON_COMPILING_IN_PYPY - PyObject *tmp_type, *tmp_value, *tmp_tb; - PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); - Py_INCREF(tb); - PyErr_Restore(tmp_type, tmp_value, tb); - Py_XDECREF(tmp_tb); -#else - PyThreadState *tstate = __Pyx_PyThreadState_Current; - PyObject* tmp_tb = tstate->curexc_traceback; - if (tb != tmp_tb) { - Py_INCREF(tb); - tstate->curexc_traceback = tb; - Py_XDECREF(tmp_tb); - } -#endif - } -bad: - Py_XDECREF(owned_instance); - return; -} -#endif - -/* ExtTypeTest */ -static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - if (likely(__Pyx_TypeCheck(obj, type))) - return 1; - PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", - Py_TYPE(obj)->tp_name, type->tp_name); - return 0; -} - -/* PyErrExceptionMatches */ -#if CYTHON_FAST_THREAD_STATE -static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; icurexc_type; - if (exc_type == err) return 1; - if (unlikely(!exc_type)) return 0; - if (unlikely(PyTuple_Check(err))) - return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); - return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); -} -#endif - -/* GetAttr */ -static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { -#if CYTHON_USE_TYPE_SLOTS -#if PY_MAJOR_VERSION >= 3 - if (likely(PyUnicode_Check(n))) -#else - if (likely(PyString_Check(n))) -#endif - return __Pyx_PyObject_GetAttrStr(o, n); -#endif - return PyObject_GetAttr(o, n); -} - -/* GetAttr3 */ -static PyObject *__Pyx_GetAttr3Default(PyObject *d) { - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) - return NULL; - __Pyx_PyErr_Clear(); - Py_INCREF(d); - return d; -} -static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) { - PyObject *r = __Pyx_GetAttr(o, n); - return (likely(r)) ? r : __Pyx_GetAttr3Default(d); -} - -/* RaiseTooManyValuesToUnpack */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { - PyErr_Format(PyExc_ValueError, - "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); -} - -/* RaiseNeedMoreValuesToUnpack */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { - PyErr_Format(PyExc_ValueError, - "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", - index, (index == 1) ? "" : "s"); -} - -/* IterFinish */ -static CYTHON_INLINE int __Pyx_IterFinish(void) { -#if CYTHON_FAST_THREAD_STATE - PyThreadState *tstate = __Pyx_PyThreadState_Current; - PyObject* exc_type = tstate->curexc_type; - if (unlikely(exc_type)) { - if (likely(__Pyx_PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) { - PyObject *exc_value, *exc_tb; - exc_value = tstate->curexc_value; - exc_tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; - Py_DECREF(exc_type); - Py_XDECREF(exc_value); - Py_XDECREF(exc_tb); - return 0; - } else { - return -1; - } - } - return 0; -#else - if (unlikely(PyErr_Occurred())) { - if (likely(PyErr_ExceptionMatches(PyExc_StopIteration))) { - PyErr_Clear(); - return 0; - } else { - return -1; - } - } - return 0; -#endif -} - -/* UnpackItemEndCheck */ -static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) { - if (unlikely(retval)) { - Py_DECREF(retval); - __Pyx_RaiseTooManyValuesError(expected); - return -1; - } else { - return __Pyx_IterFinish(); - } - return 0; -} - -/* MemviewSliceInit */ -static int -__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, - int ndim, - __Pyx_memviewslice *memviewslice, - int memview_is_new_reference) -{ - __Pyx_RefNannyDeclarations - int i, retval=-1; - Py_buffer *buf = &memview->view; - __Pyx_RefNannySetupContext("init_memviewslice", 0); - if (unlikely(memviewslice->memview || memviewslice->data)) { - PyErr_SetString(PyExc_ValueError, - "memviewslice is already initialized!"); - goto fail; - } - if (buf->strides) { - for (i = 0; i < ndim; i++) { - memviewslice->strides[i] = buf->strides[i]; - } - } else { - Py_ssize_t stride = buf->itemsize; - for (i = ndim - 1; i >= 0; i--) { - memviewslice->strides[i] = stride; - stride *= buf->shape[i]; - } - } - for (i = 0; i < ndim; i++) { - memviewslice->shape[i] = buf->shape[i]; - if (buf->suboffsets) { - memviewslice->suboffsets[i] = buf->suboffsets[i]; - } else { - memviewslice->suboffsets[i] = -1; - } - } - memviewslice->memview = memview; - memviewslice->data = (char *)buf->buf; - if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { - Py_INCREF(memview); - } - retval = 0; - goto no_fail; -fail: - memviewslice->memview = 0; - memviewslice->data = 0; - retval = -1; -no_fail: - __Pyx_RefNannyFinishContext(); - return retval; -} -#ifndef Py_NO_RETURN -#define Py_NO_RETURN -#endif -static void __pyx_fatalerror(const char *fmt, ...) Py_NO_RETURN { - va_list vargs; - char msg[200]; -#ifdef HAVE_STDARG_PROTOTYPES - va_start(vargs, fmt); -#else - va_start(vargs); -#endif - vsnprintf(msg, 200, fmt, vargs); - va_end(vargs); - Py_FatalError(msg); -} -static CYTHON_INLINE int -__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, - PyThread_type_lock lock) -{ - int result; - PyThread_acquire_lock(lock, 1); - result = (*acquisition_count)++; - PyThread_release_lock(lock); - return result; -} -static CYTHON_INLINE int -__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, - PyThread_type_lock lock) -{ - int result; - PyThread_acquire_lock(lock, 1); - result = (*acquisition_count)--; - PyThread_release_lock(lock); - return result; -} -static CYTHON_INLINE void -__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) -{ - int first_time; - struct __pyx_memoryview_obj *memview = memslice->memview; - if (unlikely(!memview || (PyObject *) memview == Py_None)) - return; - if (unlikely(__pyx_get_slice_count(memview) < 0)) - __pyx_fatalerror("Acquisition count is %d (line %d)", - __pyx_get_slice_count(memview), lineno); - first_time = __pyx_add_acquisition_count(memview) == 0; - if (unlikely(first_time)) { - if (have_gil) { - Py_INCREF((PyObject *) memview); - } else { - PyGILState_STATE _gilstate = PyGILState_Ensure(); - Py_INCREF((PyObject *) memview); - PyGILState_Release(_gilstate); - } - } -} -static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, - int have_gil, int lineno) { - int last_time; - struct __pyx_memoryview_obj *memview = memslice->memview; - if (unlikely(!memview || (PyObject *) memview == Py_None)) { - memslice->memview = NULL; - return; - } - if (unlikely(__pyx_get_slice_count(memview) <= 0)) - __pyx_fatalerror("Acquisition count is %d (line %d)", - __pyx_get_slice_count(memview), lineno); - last_time = __pyx_sub_acquisition_count(memview) == 1; - memslice->data = NULL; - if (unlikely(last_time)) { - if (have_gil) { - Py_CLEAR(memslice->memview); - } else { - PyGILState_STATE _gilstate = PyGILState_Ensure(); - Py_CLEAR(memslice->memview); - PyGILState_Release(_gilstate); - } - } else { - memslice->memview = NULL; - } -} - -/* GetItemInt */ -static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { - PyObject *r; - if (!j) return NULL; - r = PyObject_GetItem(o, j); - Py_DECREF(j); - return r; -} -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, - CYTHON_NCP_UNUSED int wraparound, - CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS - Py_ssize_t wrapped_i = i; - if (wraparound & unlikely(i < 0)) { - wrapped_i += PyList_GET_SIZE(o); - } - if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { - PyObject *r = PyList_GET_ITEM(o, wrapped_i); - Py_INCREF(r); - return r; - } - return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); -#else - return PySequence_GetItem(o, i); -#endif -} -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, - CYTHON_NCP_UNUSED int wraparound, - CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS - Py_ssize_t wrapped_i = i; - if (wraparound & unlikely(i < 0)) { - wrapped_i += PyTuple_GET_SIZE(o); - } - if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { - PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); - Py_INCREF(r); - return r; - } - return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); -#else - return PySequence_GetItem(o, i); -#endif -} -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, - CYTHON_NCP_UNUSED int wraparound, - CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS - if (is_list || PyList_CheckExact(o)) { - Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); - if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { - PyObject *r = PyList_GET_ITEM(o, n); - Py_INCREF(r); - return r; - } - } - else if (PyTuple_CheckExact(o)) { - Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); - if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { - PyObject *r = PyTuple_GET_ITEM(o, n); - Py_INCREF(r); - return r; - } - } else { - PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; - if (likely(m && m->sq_item)) { - if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { - Py_ssize_t l = m->sq_length(o); - if (likely(l >= 0)) { - i += l; - } else { - if (!PyErr_ExceptionMatches(PyExc_OverflowError)) - return NULL; - PyErr_Clear(); - } - } - return m->sq_item(o, i); - } - } -#else - if (is_list || PySequence_Check(o)) { - return PySequence_GetItem(o, i); - } -#endif - return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); -} - -/* ObjectGetItem */ -#if CYTHON_USE_TYPE_SLOTS -static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { - PyObject *runerr; - Py_ssize_t key_value; - PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; - if (unlikely(!(m && m->sq_item))) { - PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); - return NULL; - } - key_value = __Pyx_PyIndex_AsSsize_t(index); - if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { - return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); - } - if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { - PyErr_Clear(); - PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); - } - return NULL; -} -static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { - PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; - if (likely(m && m->mp_subscript)) { - return m->mp_subscript(obj, key); - } - return __Pyx_PyObject_GetIndex(obj, key); -} -#endif - -/* SliceObject */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice(PyObject* obj, - Py_ssize_t cstart, Py_ssize_t cstop, - PyObject** _py_start, PyObject** _py_stop, PyObject** _py_slice, - int has_cstart, int has_cstop, CYTHON_UNUSED int wraparound) { -#if CYTHON_USE_TYPE_SLOTS - PyMappingMethods* mp; -#if PY_MAJOR_VERSION < 3 - PySequenceMethods* ms = Py_TYPE(obj)->tp_as_sequence; - if (likely(ms && ms->sq_slice)) { - if (!has_cstart) { - if (_py_start && (*_py_start != Py_None)) { - cstart = __Pyx_PyIndex_AsSsize_t(*_py_start); - if ((cstart == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad; - } else - cstart = 0; - } - if (!has_cstop) { - if (_py_stop && (*_py_stop != Py_None)) { - cstop = __Pyx_PyIndex_AsSsize_t(*_py_stop); - if ((cstop == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad; - } else - cstop = PY_SSIZE_T_MAX; - } - if (wraparound && unlikely((cstart < 0) | (cstop < 0)) && likely(ms->sq_length)) { - Py_ssize_t l = ms->sq_length(obj); - if (likely(l >= 0)) { - if (cstop < 0) { - cstop += l; - if (cstop < 0) cstop = 0; - } - if (cstart < 0) { - cstart += l; - if (cstart < 0) cstart = 0; - } - } else { - if (!PyErr_ExceptionMatches(PyExc_OverflowError)) - goto bad; - PyErr_Clear(); - } - } - return ms->sq_slice(obj, cstart, cstop); - } -#endif - mp = Py_TYPE(obj)->tp_as_mapping; - if (likely(mp && mp->mp_subscript)) -#endif - { - PyObject* result; - PyObject *py_slice, *py_start, *py_stop; - if (_py_slice) { - py_slice = *_py_slice; - } else { - PyObject* owned_start = NULL; - PyObject* owned_stop = NULL; - if (_py_start) { - py_start = *_py_start; - } else { - if (has_cstart) { - owned_start = py_start = PyInt_FromSsize_t(cstart); - if (unlikely(!py_start)) goto bad; - } else - py_start = Py_None; - } - if (_py_stop) { - py_stop = *_py_stop; - } else { - if (has_cstop) { - owned_stop = py_stop = PyInt_FromSsize_t(cstop); - if (unlikely(!py_stop)) { - Py_XDECREF(owned_start); - goto bad; - } - } else - py_stop = Py_None; - } - py_slice = PySlice_New(py_start, py_stop, Py_None); - Py_XDECREF(owned_start); - Py_XDECREF(owned_stop); - if (unlikely(!py_slice)) goto bad; - } -#if CYTHON_USE_TYPE_SLOTS - result = mp->mp_subscript(obj, py_slice); -#else - result = PyObject_GetItem(obj, py_slice); -#endif - if (!_py_slice) { - Py_DECREF(py_slice); - } - return result; - } - PyErr_Format(PyExc_TypeError, - "'%.200s' object is unsliceable", Py_TYPE(obj)->tp_name); -bad: - return NULL; -} - -/* PyIntCompare */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_EqObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED long inplace) { - if (op1 == op2) { - Py_RETURN_TRUE; - } - #if PY_MAJOR_VERSION < 3 - if (likely(PyInt_CheckExact(op1))) { - const long b = intval; - long a = PyInt_AS_LONG(op1); - if (a == b) Py_RETURN_TRUE; else Py_RETURN_FALSE; - } - #endif - #if CYTHON_USE_PYLONG_INTERNALS - if (likely(PyLong_CheckExact(op1))) { - int unequal; - unsigned long uintval; - Py_ssize_t size = Py_SIZE(op1); - const digit* digits = ((PyLongObject*)op1)->ob_digit; - if (intval == 0) { - if (size == 0) Py_RETURN_TRUE; else Py_RETURN_FALSE; - } else if (intval < 0) { - if (size >= 0) - Py_RETURN_FALSE; - intval = -intval; - size = -size; - } else { - if (size <= 0) - Py_RETURN_FALSE; - } - uintval = (unsigned long) intval; -#if PyLong_SHIFT * 4 < SIZEOF_LONG*8 - if (uintval >> (PyLong_SHIFT * 4)) { - unequal = (size != 5) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) - | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[4] != ((uintval >> (4 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); - } else -#endif -#if PyLong_SHIFT * 3 < SIZEOF_LONG*8 - if (uintval >> (PyLong_SHIFT * 3)) { - unequal = (size != 4) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) - | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); - } else -#endif -#if PyLong_SHIFT * 2 < SIZEOF_LONG*8 - if (uintval >> (PyLong_SHIFT * 2)) { - unequal = (size != 3) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) - | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); - } else -#endif -#if PyLong_SHIFT * 1 < SIZEOF_LONG*8 - if (uintval >> (PyLong_SHIFT * 1)) { - unequal = (size != 2) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) - | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); - } else -#endif - unequal = (size != 1) || (((unsigned long) digits[0]) != (uintval & (unsigned long) PyLong_MASK)); - if (unequal == 0) Py_RETURN_TRUE; else Py_RETURN_FALSE; - } - #endif - if (PyFloat_CheckExact(op1)) { - const long b = intval; - double a = PyFloat_AS_DOUBLE(op1); - if ((double)a == (double)b) Py_RETURN_TRUE; else Py_RETURN_FALSE; - } - return ( - PyObject_RichCompare(op1, op2, Py_EQ)); -} - -/* DictGetItem */ -#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY -static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { - PyObject *value; - value = PyDict_GetItemWithError(d, key); - if (unlikely(!value)) { - if (!PyErr_Occurred()) { - if (unlikely(PyTuple_Check(key))) { - PyObject* args = PyTuple_Pack(1, key); - if (likely(args)) { - PyErr_SetObject(PyExc_KeyError, args); - Py_DECREF(args); - } - } else { - PyErr_SetObject(PyExc_KeyError, key); - } - } - return NULL; - } - Py_INCREF(value); - return value; -} -#endif - -/* PyIntCompare */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_NeObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED long inplace) { - if (op1 == op2) { - Py_RETURN_FALSE; - } - #if PY_MAJOR_VERSION < 3 - if (likely(PyInt_CheckExact(op1))) { - const long b = intval; - long a = PyInt_AS_LONG(op1); - if (a != b) Py_RETURN_TRUE; else Py_RETURN_FALSE; - } - #endif - #if CYTHON_USE_PYLONG_INTERNALS - if (likely(PyLong_CheckExact(op1))) { - int unequal; - unsigned long uintval; - Py_ssize_t size = Py_SIZE(op1); - const digit* digits = ((PyLongObject*)op1)->ob_digit; - if (intval == 0) { - if (size != 0) Py_RETURN_TRUE; else Py_RETURN_FALSE; - } else if (intval < 0) { - if (size >= 0) - Py_RETURN_TRUE; - intval = -intval; - size = -size; - } else { - if (size <= 0) - Py_RETURN_TRUE; - } - uintval = (unsigned long) intval; -#if PyLong_SHIFT * 4 < SIZEOF_LONG*8 - if (uintval >> (PyLong_SHIFT * 4)) { - unequal = (size != 5) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) - | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[4] != ((uintval >> (4 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); - } else -#endif -#if PyLong_SHIFT * 3 < SIZEOF_LONG*8 - if (uintval >> (PyLong_SHIFT * 3)) { - unequal = (size != 4) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) - | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); - } else -#endif -#if PyLong_SHIFT * 2 < SIZEOF_LONG*8 - if (uintval >> (PyLong_SHIFT * 2)) { - unequal = (size != 3) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) - | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); - } else -#endif -#if PyLong_SHIFT * 1 < SIZEOF_LONG*8 - if (uintval >> (PyLong_SHIFT * 1)) { - unequal = (size != 2) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) - | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); - } else -#endif - unequal = (size != 1) || (((unsigned long) digits[0]) != (uintval & (unsigned long) PyLong_MASK)); - if (unequal != 0) Py_RETURN_TRUE; else Py_RETURN_FALSE; - } - #endif - if (PyFloat_CheckExact(op1)) { - const long b = intval; - double a = PyFloat_AS_DOUBLE(op1); - if ((double)a != (double)b) Py_RETURN_TRUE; else Py_RETURN_FALSE; - } - return ( - PyObject_RichCompare(op1, op2, Py_NE)); -} - -/* BytesEquals */ -static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { -#if CYTHON_COMPILING_IN_PYPY - return PyObject_RichCompareBool(s1, s2, equals); -#else - if (s1 == s2) { - return (equals == Py_EQ); - } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { - const char *ps1, *ps2; - Py_ssize_t length = PyBytes_GET_SIZE(s1); - if (length != PyBytes_GET_SIZE(s2)) - return (equals == Py_NE); - ps1 = PyBytes_AS_STRING(s1); - ps2 = PyBytes_AS_STRING(s2); - if (ps1[0] != ps2[0]) { - return (equals == Py_NE); - } else if (length == 1) { - return (equals == Py_EQ); - } else { - int result; -#if CYTHON_USE_UNICODE_INTERNALS - Py_hash_t hash1, hash2; - hash1 = ((PyBytesObject*)s1)->ob_shash; - hash2 = ((PyBytesObject*)s2)->ob_shash; - if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { - return (equals == Py_NE); - } -#endif - result = memcmp(ps1, ps2, (size_t)length); - return (equals == Py_EQ) ? (result == 0) : (result != 0); - } - } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { - return (equals == Py_NE); - } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { - return (equals == Py_NE); - } else { - int result; - PyObject* py_result = PyObject_RichCompare(s1, s2, equals); - if (!py_result) - return -1; - result = __Pyx_PyObject_IsTrue(py_result); - Py_DECREF(py_result); - return result; - } -#endif -} - -/* UnicodeEquals */ -static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { -#if CYTHON_COMPILING_IN_PYPY - return PyObject_RichCompareBool(s1, s2, equals); -#else -#if PY_MAJOR_VERSION < 3 - PyObject* owned_ref = NULL; -#endif - int s1_is_unicode, s2_is_unicode; - if (s1 == s2) { - goto return_eq; - } - s1_is_unicode = PyUnicode_CheckExact(s1); - s2_is_unicode = PyUnicode_CheckExact(s2); -#if PY_MAJOR_VERSION < 3 - if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { - owned_ref = PyUnicode_FromObject(s2); - if (unlikely(!owned_ref)) - return -1; - s2 = owned_ref; - s2_is_unicode = 1; - } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { - owned_ref = PyUnicode_FromObject(s1); - if (unlikely(!owned_ref)) - return -1; - s1 = owned_ref; - s1_is_unicode = 1; - } else if (((!s2_is_unicode) & (!s1_is_unicode))) { - return __Pyx_PyBytes_Equals(s1, s2, equals); - } -#endif - if (s1_is_unicode & s2_is_unicode) { - Py_ssize_t length; - int kind; - void *data1, *data2; - if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) - return -1; - length = __Pyx_PyUnicode_GET_LENGTH(s1); - if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { - goto return_ne; - } -#if CYTHON_USE_UNICODE_INTERNALS - { - Py_hash_t hash1, hash2; - #if CYTHON_PEP393_ENABLED - hash1 = ((PyASCIIObject*)s1)->hash; - hash2 = ((PyASCIIObject*)s2)->hash; - #else - hash1 = ((PyUnicodeObject*)s1)->hash; - hash2 = ((PyUnicodeObject*)s2)->hash; - #endif - if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { - goto return_ne; - } - } -#endif - kind = __Pyx_PyUnicode_KIND(s1); - if (kind != __Pyx_PyUnicode_KIND(s2)) { - goto return_ne; - } - data1 = __Pyx_PyUnicode_DATA(s1); - data2 = __Pyx_PyUnicode_DATA(s2); - if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { - goto return_ne; - } else if (length == 1) { - goto return_eq; - } else { - int result = memcmp(data1, data2, (size_t)(length * kind)); - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - return (equals == Py_EQ) ? (result == 0) : (result != 0); - } - } else if ((s1 == Py_None) & s2_is_unicode) { - goto return_ne; - } else if ((s2 == Py_None) & s1_is_unicode) { - goto return_ne; - } else { - int result; - PyObject* py_result = PyObject_RichCompare(s1, s2, equals); - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - if (!py_result) - return -1; - result = __Pyx_PyObject_IsTrue(py_result); - Py_DECREF(py_result); - return result; - } -return_eq: - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - return (equals == Py_EQ); -return_ne: - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(owned_ref); - #endif - return (equals == Py_NE); -#endif -} - -/* PyObjectGetMethod */ -static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method) { - PyObject *attr; -#if CYTHON_UNPACK_METHODS && CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_PYTYPE_LOOKUP - PyTypeObject *tp = Py_TYPE(obj); - PyObject *descr; - descrgetfunc f = NULL; - PyObject **dictptr, *dict; - int meth_found = 0; - assert (*method == NULL); - if (unlikely(tp->tp_getattro != PyObject_GenericGetAttr)) { - attr = __Pyx_PyObject_GetAttrStr(obj, name); - goto try_unpack; - } - if (unlikely(tp->tp_dict == NULL) && unlikely(PyType_Ready(tp) < 0)) { - return 0; - } - descr = _PyType_Lookup(tp, name); - if (likely(descr != NULL)) { - Py_INCREF(descr); -#if PY_MAJOR_VERSION >= 3 - #ifdef __Pyx_CyFunction_USED - if (likely(PyFunction_Check(descr) || (Py_TYPE(descr) == &PyMethodDescr_Type) || __Pyx_CyFunction_Check(descr))) - #else - if (likely(PyFunction_Check(descr) || (Py_TYPE(descr) == &PyMethodDescr_Type))) - #endif -#else - #ifdef __Pyx_CyFunction_USED - if (likely(PyFunction_Check(descr) || __Pyx_CyFunction_Check(descr))) - #else - if (likely(PyFunction_Check(descr))) - #endif -#endif - { - meth_found = 1; - } else { - f = Py_TYPE(descr)->tp_descr_get; - if (f != NULL && PyDescr_IsData(descr)) { - attr = f(descr, obj, (PyObject *)Py_TYPE(obj)); - Py_DECREF(descr); - goto try_unpack; - } - } - } - dictptr = _PyObject_GetDictPtr(obj); - if (dictptr != NULL && (dict = *dictptr) != NULL) { - Py_INCREF(dict); - attr = __Pyx_PyDict_GetItemStr(dict, name); - if (attr != NULL) { - Py_INCREF(attr); - Py_DECREF(dict); - Py_XDECREF(descr); - goto try_unpack; - } - Py_DECREF(dict); - } - if (meth_found) { - *method = descr; - return 1; - } - if (f != NULL) { - attr = f(descr, obj, (PyObject *)Py_TYPE(obj)); - Py_DECREF(descr); - goto try_unpack; - } - if (descr != NULL) { - *method = descr; - return 0; - } - PyErr_Format(PyExc_AttributeError, -#if PY_MAJOR_VERSION >= 3 - "'%.50s' object has no attribute '%U'", - tp->tp_name, name); -#else - "'%.50s' object has no attribute '%.400s'", - tp->tp_name, PyString_AS_STRING(name)); -#endif - return 0; -#else - attr = __Pyx_PyObject_GetAttrStr(obj, name); - goto try_unpack; -#endif -try_unpack: -#if CYTHON_UNPACK_METHODS - if (likely(attr) && PyMethod_Check(attr) && likely(PyMethod_GET_SELF(attr) == obj)) { - PyObject *function = PyMethod_GET_FUNCTION(attr); - Py_INCREF(function); - Py_DECREF(attr); - *method = function; - return 1; - } -#endif - *method = attr; - return 0; -} - -/* PyObjectCallMethod1 */ -static PyObject* __Pyx__PyObject_CallMethod1(PyObject* method, PyObject* arg) { - PyObject *result = __Pyx_PyObject_CallOneArg(method, arg); - Py_DECREF(method); - return result; -} -static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg) { - PyObject *method = NULL, *result; - int is_method = __Pyx_PyObject_GetMethod(obj, method_name, &method); - if (likely(is_method)) { - result = __Pyx_PyObject_Call2Args(method, obj, arg); - Py_DECREF(method); - return result; - } - if (unlikely(!method)) return NULL; - return __Pyx__PyObject_CallMethod1(method, arg); -} - -/* append */ -static CYTHON_INLINE int __Pyx_PyObject_Append(PyObject* L, PyObject* x) { - if (likely(PyList_CheckExact(L))) { - if (unlikely(__Pyx_PyList_Append(L, x) < 0)) return -1; - } else { - PyObject* retval = __Pyx_PyObject_CallMethod1(L, __pyx_n_s_append, x); - if (unlikely(!retval)) - return -1; - Py_DECREF(retval); - } - return 0; -} - -/* PyIntBinop */ -#if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, int inplace, int zerodivision_check) { - (void)inplace; - (void)zerodivision_check; - #if PY_MAJOR_VERSION < 3 - if (likely(PyInt_CheckExact(op1))) { - const long b = intval; - long x; - long a = PyInt_AS_LONG(op1); - x = (long)((unsigned long)a + b); - if (likely((x^a) >= 0 || (x^b) >= 0)) - return PyInt_FromLong(x); - return PyLong_Type.tp_as_number->nb_add(op1, op2); - } - #endif - #if CYTHON_USE_PYLONG_INTERNALS - if (likely(PyLong_CheckExact(op1))) { - const long b = intval; - long a, x; -#ifdef HAVE_LONG_LONG - const PY_LONG_LONG llb = intval; - PY_LONG_LONG lla, llx; -#endif - const digit* digits = ((PyLongObject*)op1)->ob_digit; - const Py_ssize_t size = Py_SIZE(op1); - if (likely(__Pyx_sst_abs(size) <= 1)) { - a = likely(size) ? digits[0] : 0; - if (size == -1) a = -a; - } else { - switch (size) { - case -2: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case 2: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case -3: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case 3: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case -4: - if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - case 4: - if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; -#ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; -#endif - } - CYTHON_FALLTHROUGH; - default: return PyLong_Type.tp_as_number->nb_add(op1, op2); - } - } - x = a + b; - return PyLong_FromLong(x); -#ifdef HAVE_LONG_LONG - long_long: - llx = lla + llb; - return PyLong_FromLongLong(llx); -#endif - - - } - #endif - if (PyFloat_CheckExact(op1)) { - const long b = intval; - double a = PyFloat_AS_DOUBLE(op1); - double result; - PyFPE_START_PROTECT("add", return NULL) - result = ((double)a) + (double)b; - PyFPE_END_PROTECT(result) - return PyFloat_FromDouble(result); - } - return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); -} -#endif - -/* SliceObject */ -static CYTHON_INLINE int __Pyx_PyObject_SetSlice(PyObject* obj, PyObject* value, - Py_ssize_t cstart, Py_ssize_t cstop, - PyObject** _py_start, PyObject** _py_stop, PyObject** _py_slice, - int has_cstart, int has_cstop, CYTHON_UNUSED int wraparound) { -#if CYTHON_USE_TYPE_SLOTS - PyMappingMethods* mp; -#if PY_MAJOR_VERSION < 3 - PySequenceMethods* ms = Py_TYPE(obj)->tp_as_sequence; - if (likely(ms && ms->sq_ass_slice)) { - if (!has_cstart) { - if (_py_start && (*_py_start != Py_None)) { - cstart = __Pyx_PyIndex_AsSsize_t(*_py_start); - if ((cstart == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad; - } else - cstart = 0; - } - if (!has_cstop) { - if (_py_stop && (*_py_stop != Py_None)) { - cstop = __Pyx_PyIndex_AsSsize_t(*_py_stop); - if ((cstop == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad; - } else - cstop = PY_SSIZE_T_MAX; - } - if (wraparound && unlikely((cstart < 0) | (cstop < 0)) && likely(ms->sq_length)) { - Py_ssize_t l = ms->sq_length(obj); - if (likely(l >= 0)) { - if (cstop < 0) { - cstop += l; - if (cstop < 0) cstop = 0; - } - if (cstart < 0) { - cstart += l; - if (cstart < 0) cstart = 0; - } - } else { - if (!PyErr_ExceptionMatches(PyExc_OverflowError)) - goto bad; - PyErr_Clear(); - } - } - return ms->sq_ass_slice(obj, cstart, cstop, value); - } -#endif - mp = Py_TYPE(obj)->tp_as_mapping; - if (likely(mp && mp->mp_ass_subscript)) -#endif - { - int result; - PyObject *py_slice, *py_start, *py_stop; - if (_py_slice) { - py_slice = *_py_slice; - } else { - PyObject* owned_start = NULL; - PyObject* owned_stop = NULL; - if (_py_start) { - py_start = *_py_start; - } else { - if (has_cstart) { - owned_start = py_start = PyInt_FromSsize_t(cstart); - if (unlikely(!py_start)) goto bad; - } else - py_start = Py_None; - } - if (_py_stop) { - py_stop = *_py_stop; - } else { - if (has_cstop) { - owned_stop = py_stop = PyInt_FromSsize_t(cstop); - if (unlikely(!py_stop)) { - Py_XDECREF(owned_start); - goto bad; - } - } else - py_stop = Py_None; - } - py_slice = PySlice_New(py_start, py_stop, Py_None); - Py_XDECREF(owned_start); - Py_XDECREF(owned_stop); - if (unlikely(!py_slice)) goto bad; - } -#if CYTHON_USE_TYPE_SLOTS - result = mp->mp_ass_subscript(obj, py_slice, value); -#else - result = value ? PyObject_SetItem(obj, py_slice, value) : PyObject_DelItem(obj, py_slice); -#endif - if (!_py_slice) { - Py_DECREF(py_slice); - } - return result; - } - PyErr_Format(PyExc_TypeError, - "'%.200s' object does not support slice %.10s", - Py_TYPE(obj)->tp_name, value ? "assignment" : "deletion"); -bad: - return -1; -} - -/* MatrixMultiply */ -#if PY_VERSION_HEX < 0x03050000 -static PyObject* __Pyx_PyObject_CallMatrixMethod(PyObject* method, PyObject* arg) { - PyObject *result = NULL; -#if CYTHON_UNPACK_METHODS - if (likely(PyMethod_Check(method))) { - PyObject *self = PyMethod_GET_SELF(method); - if (likely(self)) { - PyObject *args; - PyObject *function = PyMethod_GET_FUNCTION(method); - #if CYTHON_FAST_PYCALL - if (PyFunction_Check(function)) { - PyObject *args[2] = {self, arg}; - result = __Pyx_PyFunction_FastCall(function, args, 2); - goto done; - } - #endif - #if CYTHON_FAST_PYCCALL - if (__Pyx_PyFastCFunction_Check(function)) { - PyObject *args[2] = {self, arg}; - result = __Pyx_PyCFunction_FastCall(function, args, 2); - goto done; - } - #endif - args = PyTuple_New(2); - if (unlikely(!args)) goto done; - Py_INCREF(self); - PyTuple_SET_ITEM(args, 0, self); - Py_INCREF(arg); - PyTuple_SET_ITEM(args, 1, arg); - Py_INCREF(function); - Py_DECREF(method); method = NULL; - result = __Pyx_PyObject_Call(function, args, NULL); - Py_DECREF(args); - Py_DECREF(function); - return result; - } - } -#endif - result = __Pyx_PyObject_CallOneArg(method, arg); -done: - Py_DECREF(method); - return result; -} -#define __Pyx_TryMatrixMethod(x, y, py_method_name) {\ - PyObject *func = __Pyx_PyObject_GetAttrStr(x, py_method_name);\ - if (func) {\ - PyObject *result = __Pyx_PyObject_CallMatrixMethod(func, y);\ - if (result != Py_NotImplemented)\ - return result;\ - Py_DECREF(result);\ - } else {\ - if (!PyErr_ExceptionMatches(PyExc_AttributeError))\ - return NULL;\ - PyErr_Clear();\ - }\ -} -static PyObject* __Pyx__PyNumber_MatrixMultiply(PyObject* x, PyObject* y, const char* op_name) { - int right_is_subtype = PyObject_IsSubclass((PyObject*)Py_TYPE(y), (PyObject*)Py_TYPE(x)); - if (unlikely(right_is_subtype == -1)) - return NULL; - if (right_is_subtype) { - __Pyx_TryMatrixMethod(y, x, __pyx_n_s_rmatmul) - } - __Pyx_TryMatrixMethod(x, y, __pyx_n_s_matmul) - if (!right_is_subtype) { - __Pyx_TryMatrixMethod(y, x, __pyx_n_s_rmatmul) - } - PyErr_Format(PyExc_TypeError, - "unsupported operand type(s) for %.2s: '%.100s' and '%.100s'", - op_name, - Py_TYPE(x)->tp_name, - Py_TYPE(y)->tp_name); - return NULL; -} -static PyObject* __Pyx_PyNumber_InPlaceMatrixMultiply(PyObject* x, PyObject* y) { - __Pyx_TryMatrixMethod(x, y, __pyx_n_s_imatmul) - return __Pyx__PyNumber_MatrixMultiply(x, y, "@="); -} -#undef __Pyx_TryMatrixMethod -#endif - -/* IsLittleEndian */ -static CYTHON_INLINE int __Pyx_Is_Little_Endian(void) -{ - union { - uint32_t u32; - uint8_t u8[4]; - } S; - S.u32 = 0x01020304; - return S.u8[0] == 4; -} - -/* BufferFormatCheck */ -static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, - __Pyx_BufFmt_StackElem* stack, - __Pyx_TypeInfo* type) { - stack[0].field = &ctx->root; - stack[0].parent_offset = 0; - ctx->root.type = type; - ctx->root.name = "buffer dtype"; - ctx->root.offset = 0; - ctx->head = stack; - ctx->head->field = &ctx->root; - ctx->fmt_offset = 0; - ctx->head->parent_offset = 0; - ctx->new_packmode = '@'; - ctx->enc_packmode = '@'; - ctx->new_count = 1; - ctx->enc_count = 0; - ctx->enc_type = 0; - ctx->is_complex = 0; - ctx->is_valid_array = 0; - ctx->struct_alignment = 0; - while (type->typegroup == 'S') { - ++ctx->head; - ctx->head->field = type->fields; - ctx->head->parent_offset = 0; - type = type->fields->type; - } -} -static int __Pyx_BufFmt_ParseNumber(const char** ts) { - int count; - const char* t = *ts; - if (*t < '0' || *t > '9') { - return -1; - } else { - count = *t++ - '0'; - while (*t >= '0' && *t <= '9') { - count *= 10; - count += *t++ - '0'; - } - } - *ts = t; - return count; -} -static int __Pyx_BufFmt_ExpectNumber(const char **ts) { - int number = __Pyx_BufFmt_ParseNumber(ts); - if (number == -1) - PyErr_Format(PyExc_ValueError,\ - "Does not understand character buffer dtype format string ('%c')", **ts); - return number; -} -static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { - PyErr_Format(PyExc_ValueError, - "Unexpected format string character: '%c'", ch); -} -static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { - switch (ch) { - case '?': return "'bool'"; - case 'c': return "'char'"; - case 'b': return "'signed char'"; - case 'B': return "'unsigned char'"; - case 'h': return "'short'"; - case 'H': return "'unsigned short'"; - case 'i': return "'int'"; - case 'I': return "'unsigned int'"; - case 'l': return "'long'"; - case 'L': return "'unsigned long'"; - case 'q': return "'long long'"; - case 'Q': return "'unsigned long long'"; - case 'f': return (is_complex ? "'complex float'" : "'float'"); - case 'd': return (is_complex ? "'complex double'" : "'double'"); - case 'g': return (is_complex ? "'complex long double'" : "'long double'"); - case 'T': return "a struct"; - case 'O': return "Python object"; - case 'P': return "a pointer"; - case 's': case 'p': return "a string"; - case 0: return "end"; - default: return "unparseable format string"; - } -} -static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return 2; - case 'i': case 'I': case 'l': case 'L': return 4; - case 'q': case 'Q': return 8; - case 'f': return (is_complex ? 8 : 4); - case 'd': return (is_complex ? 16 : 8); - case 'g': { - PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); - return 0; - } - case 'O': case 'P': return sizeof(void*); - default: - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } -} -static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return sizeof(short); - case 'i': case 'I': return sizeof(int); - case 'l': case 'L': return sizeof(long); - #ifdef HAVE_LONG_LONG - case 'q': case 'Q': return sizeof(PY_LONG_LONG); - #endif - case 'f': return sizeof(float) * (is_complex ? 2 : 1); - case 'd': return sizeof(double) * (is_complex ? 2 : 1); - case 'g': return sizeof(long double) * (is_complex ? 2 : 1); - case 'O': case 'P': return sizeof(void*); - default: { - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } - } -} -typedef struct { char c; short x; } __Pyx_st_short; -typedef struct { char c; int x; } __Pyx_st_int; -typedef struct { char c; long x; } __Pyx_st_long; -typedef struct { char c; float x; } __Pyx_st_float; -typedef struct { char c; double x; } __Pyx_st_double; -typedef struct { char c; long double x; } __Pyx_st_longdouble; -typedef struct { char c; void *x; } __Pyx_st_void_p; -#ifdef HAVE_LONG_LONG -typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; -#endif -static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); - case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); - case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); -#ifdef HAVE_LONG_LONG - case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); -#endif - case 'f': return sizeof(__Pyx_st_float) - sizeof(float); - case 'd': return sizeof(__Pyx_st_double) - sizeof(double); - case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); - case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); - default: - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } -} -/* These are for computing the padding at the end of the struct to align - on the first member of the struct. This will probably the same as above, - but we don't have any guarantees. - */ -typedef struct { short x; char c; } __Pyx_pad_short; -typedef struct { int x; char c; } __Pyx_pad_int; -typedef struct { long x; char c; } __Pyx_pad_long; -typedef struct { float x; char c; } __Pyx_pad_float; -typedef struct { double x; char c; } __Pyx_pad_double; -typedef struct { long double x; char c; } __Pyx_pad_longdouble; -typedef struct { void *x; char c; } __Pyx_pad_void_p; -#ifdef HAVE_LONG_LONG -typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; -#endif -static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); - case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); - case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); -#ifdef HAVE_LONG_LONG - case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); -#endif - case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); - case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); - case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); - case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); - default: - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } -} -static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { - switch (ch) { - case 'c': - return 'H'; - case 'b': case 'h': case 'i': - case 'l': case 'q': case 's': case 'p': - return 'I'; - case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': - return 'U'; - case 'f': case 'd': case 'g': - return (is_complex ? 'C' : 'R'); - case 'O': - return 'O'; - case 'P': - return 'P'; - default: { - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } - } -} -static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { - if (ctx->head == NULL || ctx->head->field == &ctx->root) { - const char* expected; - const char* quote; - if (ctx->head == NULL) { - expected = "end"; - quote = ""; - } else { - expected = ctx->head->field->type->name; - quote = "'"; - } - PyErr_Format(PyExc_ValueError, - "Buffer dtype mismatch, expected %s%s%s but got %s", - quote, expected, quote, - __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); - } else { - __Pyx_StructField* field = ctx->head->field; - __Pyx_StructField* parent = (ctx->head - 1)->field; - PyErr_Format(PyExc_ValueError, - "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", - field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), - parent->type->name, field->name); - } -} -static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { - char group; - size_t size, offset, arraysize = 1; - if (ctx->enc_type == 0) return 0; - if (ctx->head->field->type->arraysize[0]) { - int i, ndim = 0; - if (ctx->enc_type == 's' || ctx->enc_type == 'p') { - ctx->is_valid_array = ctx->head->field->type->ndim == 1; - ndim = 1; - if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { - PyErr_Format(PyExc_ValueError, - "Expected a dimension of size %zu, got %zu", - ctx->head->field->type->arraysize[0], ctx->enc_count); - return -1; - } - } - if (!ctx->is_valid_array) { - PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", - ctx->head->field->type->ndim, ndim); - return -1; - } - for (i = 0; i < ctx->head->field->type->ndim; i++) { - arraysize *= ctx->head->field->type->arraysize[i]; - } - ctx->is_valid_array = 0; - ctx->enc_count = 1; - } - group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); - do { - __Pyx_StructField* field = ctx->head->field; - __Pyx_TypeInfo* type = field->type; - if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { - size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); - } else { - size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); - } - if (ctx->enc_packmode == '@') { - size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); - size_t align_mod_offset; - if (align_at == 0) return -1; - align_mod_offset = ctx->fmt_offset % align_at; - if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; - if (ctx->struct_alignment == 0) - ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, - ctx->is_complex); - } - if (type->size != size || type->typegroup != group) { - if (type->typegroup == 'C' && type->fields != NULL) { - size_t parent_offset = ctx->head->parent_offset + field->offset; - ++ctx->head; - ctx->head->field = type->fields; - ctx->head->parent_offset = parent_offset; - continue; - } - if ((type->typegroup == 'H' || group == 'H') && type->size == size) { - } else { - __Pyx_BufFmt_RaiseExpected(ctx); - return -1; - } - } - offset = ctx->head->parent_offset + field->offset; - if (ctx->fmt_offset != offset) { - PyErr_Format(PyExc_ValueError, - "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", - (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); - return -1; - } - ctx->fmt_offset += size; - if (arraysize) - ctx->fmt_offset += (arraysize - 1) * size; - --ctx->enc_count; - while (1) { - if (field == &ctx->root) { - ctx->head = NULL; - if (ctx->enc_count != 0) { - __Pyx_BufFmt_RaiseExpected(ctx); - return -1; - } - break; - } - ctx->head->field = ++field; - if (field->type == NULL) { - --ctx->head; - field = ctx->head->field; - continue; - } else if (field->type->typegroup == 'S') { - size_t parent_offset = ctx->head->parent_offset + field->offset; - if (field->type->fields->type == NULL) continue; - field = field->type->fields; - ++ctx->head; - ctx->head->field = field; - ctx->head->parent_offset = parent_offset; - break; - } else { - break; - } - } - } while (ctx->enc_count); - ctx->enc_type = 0; - ctx->is_complex = 0; - return 0; -} -static PyObject * -__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) -{ - const char *ts = *tsp; - int i = 0, number, ndim; - ++ts; - if (ctx->new_count != 1) { - PyErr_SetString(PyExc_ValueError, - "Cannot handle repeated arrays in format string"); - return NULL; - } - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ndim = ctx->head->field->type->ndim; - while (*ts && *ts != ')') { - switch (*ts) { - case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; - default: break; - } - number = __Pyx_BufFmt_ExpectNumber(&ts); - if (number == -1) return NULL; - if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) - return PyErr_Format(PyExc_ValueError, - "Expected a dimension of size %zu, got %d", - ctx->head->field->type->arraysize[i], number); - if (*ts != ',' && *ts != ')') - return PyErr_Format(PyExc_ValueError, - "Expected a comma in format string, got '%c'", *ts); - if (*ts == ',') ts++; - i++; - } - if (i != ndim) - return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", - ctx->head->field->type->ndim, i); - if (!*ts) { - PyErr_SetString(PyExc_ValueError, - "Unexpected end of format string, expected ')'"); - return NULL; - } - ctx->is_valid_array = 1; - ctx->new_count = 1; - *tsp = ++ts; - return Py_None; -} -static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { - int got_Z = 0; - while (1) { - switch(*ts) { - case 0: - if (ctx->enc_type != 0 && ctx->head == NULL) { - __Pyx_BufFmt_RaiseExpected(ctx); - return NULL; - } - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - if (ctx->head != NULL) { - __Pyx_BufFmt_RaiseExpected(ctx); - return NULL; - } - return ts; - case ' ': - case '\r': - case '\n': - ++ts; - break; - case '<': - if (!__Pyx_Is_Little_Endian()) { - PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); - return NULL; - } - ctx->new_packmode = '='; - ++ts; - break; - case '>': - case '!': - if (__Pyx_Is_Little_Endian()) { - PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); - return NULL; - } - ctx->new_packmode = '='; - ++ts; - break; - case '=': - case '@': - case '^': - ctx->new_packmode = *ts++; - break; - case 'T': - { - const char* ts_after_sub; - size_t i, struct_count = ctx->new_count; - size_t struct_alignment = ctx->struct_alignment; - ctx->new_count = 1; - ++ts; - if (*ts != '{') { - PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); - return NULL; - } - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->enc_type = 0; - ctx->enc_count = 0; - ctx->struct_alignment = 0; - ++ts; - ts_after_sub = ts; - for (i = 0; i != struct_count; ++i) { - ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); - if (!ts_after_sub) return NULL; - } - ts = ts_after_sub; - if (struct_alignment) ctx->struct_alignment = struct_alignment; - } - break; - case '}': - { - size_t alignment = ctx->struct_alignment; - ++ts; - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->enc_type = 0; - if (alignment && ctx->fmt_offset % alignment) { - ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); - } - } - return ts; - case 'x': - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->fmt_offset += ctx->new_count; - ctx->new_count = 1; - ctx->enc_count = 0; - ctx->enc_type = 0; - ctx->enc_packmode = ctx->new_packmode; - ++ts; - break; - case 'Z': - got_Z = 1; - ++ts; - if (*ts != 'f' && *ts != 'd' && *ts != 'g') { - __Pyx_BufFmt_RaiseUnexpectedChar('Z'); - return NULL; - } - CYTHON_FALLTHROUGH; - case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': - case 'l': case 'L': case 'q': case 'Q': - case 'f': case 'd': case 'g': - case 'O': case 'p': - if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && - (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { - ctx->enc_count += ctx->new_count; - ctx->new_count = 1; - got_Z = 0; - ++ts; - break; - } - CYTHON_FALLTHROUGH; - case 's': - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->enc_count = ctx->new_count; - ctx->enc_packmode = ctx->new_packmode; - ctx->enc_type = *ts; - ctx->is_complex = got_Z; - ++ts; - ctx->new_count = 1; - got_Z = 0; - break; - case ':': - ++ts; - while(*ts != ':') ++ts; - ++ts; - break; - case '(': - if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; - break; - default: - { - int number = __Pyx_BufFmt_ExpectNumber(&ts); - if (number == -1) return NULL; - ctx->new_count = (size_t)number; - } - } - } -} - -/* BufferGetAndValidate */ - static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { - if (unlikely(info->buf == NULL)) return; - if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; - __Pyx_ReleaseBuffer(info); -} -static void __Pyx_ZeroBuffer(Py_buffer* buf) { - buf->buf = NULL; - buf->obj = NULL; - buf->strides = __Pyx_zeros; - buf->shape = __Pyx_zeros; - buf->suboffsets = __Pyx_minusones; -} -static int __Pyx__GetBufferAndValidate( - Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, - int nd, int cast, __Pyx_BufFmt_StackElem* stack) -{ - buf->buf = NULL; - if (unlikely(__Pyx_GetBuffer(obj, buf, flags) == -1)) { - __Pyx_ZeroBuffer(buf); - return -1; - } - if (unlikely(buf->ndim != nd)) { - PyErr_Format(PyExc_ValueError, - "Buffer has wrong number of dimensions (expected %d, got %d)", - nd, buf->ndim); - goto fail; - } - if (!cast) { - __Pyx_BufFmt_Context ctx; - __Pyx_BufFmt_Init(&ctx, stack, dtype); - if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; - } - if (unlikely((size_t)buf->itemsize != dtype->size)) { - PyErr_Format(PyExc_ValueError, - "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", - buf->itemsize, (buf->itemsize > 1) ? "s" : "", - dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); - goto fail; - } - if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; - return 0; -fail:; - __Pyx_SafeReleaseBuffer(buf); - return -1; -} - -/* BufferFallbackError */ - static void __Pyx_RaiseBufferFallbackError(void) { - PyErr_SetString(PyExc_ValueError, - "Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!"); -} - -/* WriteUnraisableException */ - static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, - CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, - int full_traceback, CYTHON_UNUSED int nogil) { - PyObject *old_exc, *old_val, *old_tb; - PyObject *ctx; - __Pyx_PyThreadState_declare -#ifdef WITH_THREAD - PyGILState_STATE state; - if (nogil) - state = PyGILState_Ensure(); -#ifdef _MSC_VER - else state = (PyGILState_STATE)-1; -#endif -#endif - __Pyx_PyThreadState_assign - __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); - if (full_traceback) { - Py_XINCREF(old_exc); - Py_XINCREF(old_val); - Py_XINCREF(old_tb); - __Pyx_ErrRestore(old_exc, old_val, old_tb); - PyErr_PrintEx(1); - } - #if PY_MAJOR_VERSION < 3 - ctx = PyString_FromString(name); - #else - ctx = PyUnicode_FromString(name); - #endif - __Pyx_ErrRestore(old_exc, old_val, old_tb); - if (!ctx) { - PyErr_WriteUnraisable(Py_None); - } else { - PyErr_WriteUnraisable(ctx); - Py_DECREF(ctx); - } -#ifdef WITH_THREAD - if (nogil) - PyGILState_Release(state); -#endif -} - -/* SetItemInt */ - static int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v) { - int r; - if (!j) return -1; - r = PyObject_SetItem(o, j, v); - Py_DECREF(j); - return r; -} -static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, int is_list, - CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS - if (is_list || PyList_CheckExact(o)) { - Py_ssize_t n = (!wraparound) ? i : ((likely(i >= 0)) ? i : i + PyList_GET_SIZE(o)); - if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o)))) { - PyObject* old = PyList_GET_ITEM(o, n); - Py_INCREF(v); - PyList_SET_ITEM(o, n, v); - Py_DECREF(old); - return 1; - } - } else { - PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; - if (likely(m && m->sq_ass_item)) { - if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { - Py_ssize_t l = m->sq_length(o); - if (likely(l >= 0)) { - i += l; - } else { - if (!PyErr_ExceptionMatches(PyExc_OverflowError)) - return -1; - PyErr_Clear(); - } - } - return m->sq_ass_item(o, i, v); - } - } -#else -#if CYTHON_COMPILING_IN_PYPY - if (is_list || (PySequence_Check(o) && !PyDict_Check(o))) -#else - if (is_list || PySequence_Check(o)) -#endif - { - return PySequence_SetItem(o, i, v); - } -#endif - return __Pyx_SetItemInt_Generic(o, PyInt_FromSsize_t(i), v); -} - -/* Import */ - static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { - PyObject *empty_list = 0; - PyObject *module = 0; - PyObject *global_dict = 0; - PyObject *empty_dict = 0; - PyObject *list; - #if PY_MAJOR_VERSION < 3 - PyObject *py_import; - py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); - if (!py_import) - goto bad; - #endif - if (from_list) - list = from_list; - else { - empty_list = PyList_New(0); - if (!empty_list) - goto bad; - list = empty_list; - } - global_dict = PyModule_GetDict(__pyx_m); - if (!global_dict) - goto bad; - empty_dict = PyDict_New(); - if (!empty_dict) - goto bad; - { - #if PY_MAJOR_VERSION >= 3 - if (level == -1) { - if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, 1); - if (!module) { - if (!PyErr_ExceptionMatches(PyExc_ImportError)) - goto bad; - PyErr_Clear(); - } - } - level = 0; - } - #endif - if (!module) { - #if PY_MAJOR_VERSION < 3 - PyObject *py_level = PyInt_FromLong(level); - if (!py_level) - goto bad; - module = PyObject_CallFunctionObjArgs(py_import, - name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); - Py_DECREF(py_level); - #else - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, level); - #endif - } - } -bad: - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(py_import); - #endif - Py_XDECREF(empty_list); - Py_XDECREF(empty_dict); - return module; -} - -/* ImportFrom */ - static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { - PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); - if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { - PyErr_Format(PyExc_ImportError, - #if PY_MAJOR_VERSION < 3 - "cannot import name %.230s", PyString_AS_STRING(name)); - #else - "cannot import name %S", name); - #endif - } - return value; -} - -/* HasAttr */ - static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) { - PyObject *r; - if (unlikely(!__Pyx_PyBaseString_Check(n))) { - PyErr_SetString(PyExc_TypeError, - "hasattr(): attribute name must be string"); - return -1; - } - r = __Pyx_GetAttr(o, n); - if (unlikely(!r)) { - PyErr_Clear(); - return 0; - } else { - Py_DECREF(r); - return 1; - } -} - -/* GetTopmostException */ - #if CYTHON_USE_EXC_INFO_STACK -static _PyErr_StackItem * -__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) -{ - _PyErr_StackItem *exc_info = tstate->exc_info; - while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && - exc_info->previous_item != NULL) - { - exc_info = exc_info->previous_item; - } - return exc_info; -} -#endif - -/* SaveResetException */ - #if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); - *type = exc_info->exc_type; - *value = exc_info->exc_value; - *tb = exc_info->exc_traceback; - #else - *type = tstate->exc_type; - *value = tstate->exc_value; - *tb = tstate->exc_traceback; - #endif - Py_XINCREF(*type); - Py_XINCREF(*value); - Py_XINCREF(*tb); -} -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = type; - exc_info->exc_value = value; - exc_info->exc_traceback = tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = type; - tstate->exc_value = value; - tstate->exc_traceback = tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -#endif - -/* GetException */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) -#endif -{ - PyObject *local_type, *local_value, *local_tb; -#if CYTHON_FAST_THREAD_STATE - PyObject *tmp_type, *tmp_value, *tmp_tb; - local_type = tstate->curexc_type; - local_value = tstate->curexc_value; - local_tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -#else - PyErr_Fetch(&local_type, &local_value, &local_tb); -#endif - PyErr_NormalizeException(&local_type, &local_value, &local_tb); -#if CYTHON_FAST_THREAD_STATE - if (unlikely(tstate->curexc_type)) -#else - if (unlikely(PyErr_Occurred())) -#endif - goto bad; - #if PY_MAJOR_VERSION >= 3 - if (local_tb) { - if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) - goto bad; - } - #endif - Py_XINCREF(local_tb); - Py_XINCREF(local_type); - Py_XINCREF(local_value); - *type = local_type; - *value = local_value; - *tb = local_tb; -#if CYTHON_FAST_THREAD_STATE - #if CYTHON_USE_EXC_INFO_STACK - { - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = local_type; - exc_info->exc_value = local_value; - exc_info->exc_traceback = local_tb; - } - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = local_type; - tstate->exc_value = local_value; - tstate->exc_traceback = local_tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#else - PyErr_SetExcInfo(local_type, local_value, local_tb); -#endif - return 0; -bad: - *type = 0; - *value = 0; - *tb = 0; - Py_XDECREF(local_type); - Py_XDECREF(local_value); - Py_XDECREF(local_tb); - return -1; -} - -/* decode_c_string */ - static CYTHON_INLINE PyObject* __Pyx_decode_c_string( - const char* cstring, Py_ssize_t start, Py_ssize_t stop, - const char* encoding, const char* errors, - PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { - Py_ssize_t length; - if (unlikely((start < 0) | (stop < 0))) { - size_t slen = strlen(cstring); - if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { - PyErr_SetString(PyExc_OverflowError, - "c-string too long to convert to Python"); - return NULL; - } - length = (Py_ssize_t) slen; - if (start < 0) { - start += length; - if (start < 0) - start = 0; - } - if (stop < 0) - stop += length; - } - if (unlikely(stop <= start)) - return __Pyx_NewRef(__pyx_empty_unicode); - length = stop - start; - cstring += start; - if (decode_func) { - return decode_func(cstring, length, errors); - } else { - return PyUnicode_Decode(cstring, length, encoding, errors); - } -} - -/* RaiseNoneIterError */ - static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { - PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); -} - -/* SwapException */ - #if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = *type; - exc_info->exc_value = *value; - exc_info->exc_traceback = *tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = *type; - tstate->exc_value = *value; - tstate->exc_traceback = *tb; - #endif - *type = tmp_type; - *value = tmp_value; - *tb = tmp_tb; -} -#else -static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); - PyErr_SetExcInfo(*type, *value, *tb); - *type = tmp_type; - *value = tmp_value; - *tb = tmp_tb; -} -#endif - -/* FastTypeChecks */ - #if CYTHON_COMPILING_IN_CPYTHON -static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { - while (a) { - a = a->tp_base; - if (a == b) - return 1; - } - return b == &PyBaseObject_Type; -} -static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { - PyObject *mro; - if (a == b) return 1; - mro = a->tp_mro; - if (likely(mro)) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(mro); - for (i = 0; i < n; i++) { - if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) - return 1; - } - return 0; - } - return __Pyx_InBases(a, b); -} -#if PY_MAJOR_VERSION == 2 -static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { - PyObject *exception, *value, *tb; - int res; - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - __Pyx_ErrFetch(&exception, &value, &tb); - res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; - if (unlikely(res == -1)) { - PyErr_WriteUnraisable(err); - res = 0; - } - if (!res) { - res = PyObject_IsSubclass(err, exc_type2); - if (unlikely(res == -1)) { - PyErr_WriteUnraisable(err); - res = 0; - } - } - __Pyx_ErrRestore(exception, value, tb); - return res; -} -#else -static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { - int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; - if (!res) { - res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); - } - return res; -} -#endif -static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - assert(PyExceptionClass_Check(exc_type)); - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; i= 3 - "'%.50s' object has no attribute '%U'", - tp->tp_name, attr_name); -#else - "'%.50s' object has no attribute '%.400s'", - tp->tp_name, PyString_AS_STRING(attr_name)); -#endif - return NULL; -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) { - PyObject *descr; - PyTypeObject *tp = Py_TYPE(obj); - if (unlikely(!PyString_Check(attr_name))) { - return PyObject_GenericGetAttr(obj, attr_name); - } - assert(!tp->tp_dictoffset); - descr = _PyType_Lookup(tp, attr_name); - if (unlikely(!descr)) { - return __Pyx_RaiseGenericGetAttributeError(tp, attr_name); - } - Py_INCREF(descr); - #if PY_MAJOR_VERSION < 3 - if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS))) - #endif - { - descrgetfunc f = Py_TYPE(descr)->tp_descr_get; - if (unlikely(f)) { - PyObject *res = f(descr, obj, (PyObject *)tp); - Py_DECREF(descr); - return res; - } - } - return descr; -} -#endif - -/* PyObject_GenericGetAttr */ - #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 -static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) { - if (unlikely(Py_TYPE(obj)->tp_dictoffset)) { - return PyObject_GenericGetAttr(obj, attr_name); - } - return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name); -} -#endif - -/* SetVTable */ - static int __Pyx_SetVtable(PyObject *dict, void *vtable) { -#if PY_VERSION_HEX >= 0x02070000 - PyObject *ob = PyCapsule_New(vtable, 0, 0); -#else - PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); -#endif - if (!ob) - goto bad; - if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) - goto bad; - Py_DECREF(ob); - return 0; -bad: - Py_XDECREF(ob); - return -1; -} - -/* PyObjectGetAttrStrNoError */ - static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) - __Pyx_PyErr_Clear(); -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { - PyObject *result; -#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 - PyTypeObject* tp = Py_TYPE(obj); - if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { - return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); - } -#endif - result = __Pyx_PyObject_GetAttrStr(obj, attr_name); - if (unlikely(!result)) { - __Pyx_PyObject_GetAttrStr_ClearAttributeError(); - } - return result; -} - -/* SetupReduce */ - static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { - int ret; - PyObject *name_attr; - name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2); - if (likely(name_attr)) { - ret = PyObject_RichCompareBool(name_attr, name, Py_EQ); - } else { - ret = -1; - } - if (unlikely(ret < 0)) { - PyErr_Clear(); - ret = 0; - } - Py_XDECREF(name_attr); - return ret; -} -static int __Pyx_setup_reduce(PyObject* type_obj) { - int ret = 0; - PyObject *object_reduce = NULL; - PyObject *object_reduce_ex = NULL; - PyObject *reduce = NULL; - PyObject *reduce_ex = NULL; - PyObject *reduce_cython = NULL; - PyObject *setstate = NULL; - PyObject *setstate_cython = NULL; -#if CYTHON_USE_PYTYPE_LOOKUP - if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; -#else - if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; -#endif -#if CYTHON_USE_PYTYPE_LOOKUP - object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; -#else - object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; -#endif - reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; - if (reduce_ex == object_reduce_ex) { -#if CYTHON_USE_PYTYPE_LOOKUP - object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; -#else - object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; -#endif - reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; - if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { - reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); - if (likely(reduce_cython)) { - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - } else if (reduce == object_reduce || PyErr_Occurred()) { - goto __PYX_BAD; - } - setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); - if (!setstate) PyErr_Clear(); - if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { - setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); - if (likely(setstate_cython)) { - ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; - } else if (!setstate || PyErr_Occurred()) { - goto __PYX_BAD; - } - } - PyType_Modified((PyTypeObject*)type_obj); - } - } - goto __PYX_GOOD; -__PYX_BAD: - if (!PyErr_Occurred()) - PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); - ret = -1; -__PYX_GOOD: -#if !CYTHON_USE_PYTYPE_LOOKUP - Py_XDECREF(object_reduce); - Py_XDECREF(object_reduce_ex); -#endif - Py_XDECREF(reduce); - Py_XDECREF(reduce_ex); - Py_XDECREF(reduce_cython); - Py_XDECREF(setstate); - Py_XDECREF(setstate_cython); - return ret; -} - -/* TypeImport */ - #ifndef __PYX_HAVE_RT_ImportType -#define __PYX_HAVE_RT_ImportType -static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, - size_t size, enum __Pyx_ImportType_CheckSize check_size) -{ - PyObject *result = 0; - char warning[200]; - Py_ssize_t basicsize; -#ifdef Py_LIMITED_API - PyObject *py_basicsize; -#endif - result = PyObject_GetAttrString(module, class_name); - if (!result) - goto bad; - if (!PyType_Check(result)) { - PyErr_Format(PyExc_TypeError, - "%.200s.%.200s is not a type object", - module_name, class_name); - goto bad; - } -#ifndef Py_LIMITED_API - basicsize = ((PyTypeObject *)result)->tp_basicsize; -#else - py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); - if (!py_basicsize) - goto bad; - basicsize = PyLong_AsSsize_t(py_basicsize); - Py_DECREF(py_basicsize); - py_basicsize = 0; - if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) - goto bad; -#endif - if ((size_t)basicsize < size) { - PyErr_Format(PyExc_ValueError, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - goto bad; - } - if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { - PyErr_Format(PyExc_ValueError, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - goto bad; - } - else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { - PyOS_snprintf(warning, sizeof(warning), - "%s.%s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; - } - return (PyTypeObject *)result; -bad: - Py_XDECREF(result); - return NULL; -} -#endif - -/* GetVTable */ - static void* __Pyx_GetVtable(PyObject *dict) { - void* ptr; - PyObject *ob = PyObject_GetItem(dict, __pyx_n_s_pyx_vtable); - if (!ob) - goto bad; -#if PY_VERSION_HEX >= 0x02070000 - ptr = PyCapsule_GetPointer(ob, 0); -#else - ptr = PyCObject_AsVoidPtr(ob); -#endif - if (!ptr && !PyErr_Occurred()) - PyErr_SetString(PyExc_RuntimeError, "invalid vtable found for imported type"); - Py_DECREF(ob); - return ptr; -bad: - Py_XDECREF(ob); - return NULL; -} - -/* CLineInTraceback */ - #ifndef CYTHON_CLINE_IN_TRACEBACK -static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { - PyObject *use_cline; - PyObject *ptype, *pvalue, *ptraceback; -#if CYTHON_COMPILING_IN_CPYTHON - PyObject **cython_runtime_dict; -#endif - if (unlikely(!__pyx_cython_runtime)) { - return c_line; - } - __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); -#if CYTHON_COMPILING_IN_CPYTHON - cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); - if (likely(cython_runtime_dict)) { - __PYX_PY_DICT_LOOKUP_IF_MODIFIED( - use_cline, *cython_runtime_dict, - __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) - } else -#endif - { - PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); - if (use_cline_obj) { - use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; - Py_DECREF(use_cline_obj); - } else { - PyErr_Clear(); - use_cline = NULL; - } - } - if (!use_cline) { - c_line = 0; - PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); - } - else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { - c_line = 0; - } - __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); - return c_line; -} -#endif - -/* CodeObjectCache */ - static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { - int start = 0, mid = 0, end = count - 1; - if (end >= 0 && code_line > entries[end].code_line) { - return count; - } - while (start < end) { - mid = start + (end - start) / 2; - if (code_line < entries[mid].code_line) { - end = mid; - } else if (code_line > entries[mid].code_line) { - start = mid + 1; - } else { - return mid; - } - } - if (code_line <= entries[mid].code_line) { - return mid; - } else { - return mid + 1; - } -} -static PyCodeObject *__pyx_find_code_object(int code_line) { - PyCodeObject* code_object; - int pos; - if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { - return NULL; - } - pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); - if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { - return NULL; - } - code_object = __pyx_code_cache.entries[pos].code_object; - Py_INCREF(code_object); - return code_object; -} -static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { - int pos, i; - __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; - if (unlikely(!code_line)) { - return; - } - if (unlikely(!entries)) { - entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); - if (likely(entries)) { - __pyx_code_cache.entries = entries; - __pyx_code_cache.max_count = 64; - __pyx_code_cache.count = 1; - entries[0].code_line = code_line; - entries[0].code_object = code_object; - Py_INCREF(code_object); - } - return; - } - pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); - if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { - PyCodeObject* tmp = entries[pos].code_object; - entries[pos].code_object = code_object; - Py_DECREF(tmp); - return; - } - if (__pyx_code_cache.count == __pyx_code_cache.max_count) { - int new_max = __pyx_code_cache.max_count + 64; - entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( - __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); - if (unlikely(!entries)) { - return; - } - __pyx_code_cache.entries = entries; - __pyx_code_cache.max_count = new_max; - } - for (i=__pyx_code_cache.count; i>pos; i--) { - entries[i] = entries[i-1]; - } - entries[pos].code_line = code_line; - entries[pos].code_object = code_object; - __pyx_code_cache.count++; - Py_INCREF(code_object); -} - -/* AddTraceback */ - #include "compile.h" -#include "frameobject.h" -#include "traceback.h" -static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( - const char *funcname, int c_line, - int py_line, const char *filename) { - PyCodeObject *py_code = 0; - PyObject *py_srcfile = 0; - PyObject *py_funcname = 0; - #if PY_MAJOR_VERSION < 3 - py_srcfile = PyString_FromString(filename); - #else - py_srcfile = PyUnicode_FromString(filename); - #endif - if (!py_srcfile) goto bad; - if (c_line) { - #if PY_MAJOR_VERSION < 3 - py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); - #else - py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); - #endif - } - else { - #if PY_MAJOR_VERSION < 3 - py_funcname = PyString_FromString(funcname); - #else - py_funcname = PyUnicode_FromString(funcname); - #endif - } - if (!py_funcname) goto bad; - py_code = __Pyx_PyCode_New( - 0, - 0, - 0, - 0, - 0, - __pyx_empty_bytes, /*PyObject *code,*/ - __pyx_empty_tuple, /*PyObject *consts,*/ - __pyx_empty_tuple, /*PyObject *names,*/ - __pyx_empty_tuple, /*PyObject *varnames,*/ - __pyx_empty_tuple, /*PyObject *freevars,*/ - __pyx_empty_tuple, /*PyObject *cellvars,*/ - py_srcfile, /*PyObject *filename,*/ - py_funcname, /*PyObject *name,*/ - py_line, - __pyx_empty_bytes /*PyObject *lnotab*/ - ); - Py_DECREF(py_srcfile); - Py_DECREF(py_funcname); - return py_code; -bad: - Py_XDECREF(py_srcfile); - Py_XDECREF(py_funcname); - return NULL; -} -static void __Pyx_AddTraceback(const char *funcname, int c_line, - int py_line, const char *filename) { - PyCodeObject *py_code = 0; - PyFrameObject *py_frame = 0; - PyThreadState *tstate = __Pyx_PyThreadState_Current; - if (c_line) { - c_line = __Pyx_CLineForTraceback(tstate, c_line); - } - py_code = __pyx_find_code_object(c_line ? -c_line : py_line); - if (!py_code) { - py_code = __Pyx_CreateCodeObjectForTraceback( - funcname, c_line, py_line, filename); - if (!py_code) goto bad; - __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); - } - py_frame = PyFrame_New( - tstate, /*PyThreadState *tstate,*/ - py_code, /*PyCodeObject *code,*/ - __pyx_d, /*PyObject *globals,*/ - 0 /*PyObject *locals*/ - ); - if (!py_frame) goto bad; - __Pyx_PyFrame_SetLineNumber(py_frame, py_line); - PyTraceBack_Here(py_frame); -bad: - Py_XDECREF(py_code); - Py_XDECREF(py_frame); -} - -#if PY_MAJOR_VERSION < 3 -static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { - if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); - if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); - PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); - return -1; -} -static void __Pyx_ReleaseBuffer(Py_buffer *view) { - PyObject *obj = view->obj; - if (!obj) return; - if (PyObject_CheckBuffer(obj)) { - PyBuffer_Release(view); - return; - } - if ((0)) {} - view->obj = NULL; - Py_DECREF(obj); -} -#endif - - - /* MemviewSliceIsContig */ - static int -__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) -{ - int i, index, step, start; - Py_ssize_t itemsize = mvs.memview->view.itemsize; - if (order == 'F') { - step = 1; - start = 0; - } else { - step = -1; - start = ndim - 1; - } - for (i = 0; i < ndim; i++) { - index = start + step * i; - if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) - return 0; - itemsize *= mvs.shape[index]; - } - return 1; -} - -/* OverlappingSlices */ - static void -__pyx_get_array_memory_extents(__Pyx_memviewslice *slice, - void **out_start, void **out_end, - int ndim, size_t itemsize) -{ - char *start, *end; - int i; - start = end = slice->data; - for (i = 0; i < ndim; i++) { - Py_ssize_t stride = slice->strides[i]; - Py_ssize_t extent = slice->shape[i]; - if (extent == 0) { - *out_start = *out_end = start; - return; - } else { - if (stride > 0) - end += stride * (extent - 1); - else - start += stride * (extent - 1); - } - } - *out_start = start; - *out_end = end + itemsize; -} -static int -__pyx_slices_overlap(__Pyx_memviewslice *slice1, - __Pyx_memviewslice *slice2, - int ndim, size_t itemsize) -{ - void *start1, *end1, *start2, *end2; - __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); - __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); - return (start1 < end2) && (start2 < end1); -} - -/* Capsule */ - static CYTHON_INLINE PyObject * -__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) -{ - PyObject *cobj; -#if PY_VERSION_HEX >= 0x02070000 - cobj = PyCapsule_New(p, sig, NULL); -#else - cobj = PyCObject_FromVoidPtr(p, NULL); -#endif - return cobj; -} - -/* CIntFromPyVerify */ - #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ - __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) -#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ - __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) -#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ - {\ - func_type value = func_value;\ - if (sizeof(target_type) < sizeof(func_type)) {\ - if (unlikely(value != (func_type) (target_type) value)) {\ - func_type zero = 0;\ - if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ - return (target_type) -1;\ - if (is_unsigned && unlikely(value < zero))\ - goto raise_neg_overflow;\ - else\ - goto raise_overflow;\ - }\ - }\ - return (target_type) value;\ - } - -static PyObject* __pyx_convert__to_py_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node s) { - PyObject* res; - PyObject* member; - res = __Pyx_PyDict_NewPresized(7); if (unlikely(!res)) return NULL; - member = __Pyx_PyInt_From_Py_intptr_t(s.left_child); if (unlikely(!member)) goto bad; - if (unlikely(PyDict_SetItem(res, __pyx_n_s_left_child, member) < 0)) goto bad; - Py_DECREF(member); - member = __Pyx_PyInt_From_Py_intptr_t(s.right_child); if (unlikely(!member)) goto bad; - if (unlikely(PyDict_SetItem(res, __pyx_n_s_right_child, member) < 0)) goto bad; - Py_DECREF(member); - member = __Pyx_PyInt_From_Py_intptr_t(s.feature); if (unlikely(!member)) goto bad; - if (unlikely(PyDict_SetItem(res, __pyx_n_s_feature, member) < 0)) goto bad; - Py_DECREF(member); - member = PyFloat_FromDouble(s.threshold); if (unlikely(!member)) goto bad; - if (unlikely(PyDict_SetItem(res, __pyx_n_s_threshold, member) < 0)) goto bad; - Py_DECREF(member); - member = PyFloat_FromDouble(s.impurity); if (unlikely(!member)) goto bad; - if (unlikely(PyDict_SetItem(res, __pyx_n_s_impurity, member) < 0)) goto bad; - Py_DECREF(member); - member = __Pyx_PyInt_From_Py_intptr_t(s.n_node_samples); if (unlikely(!member)) goto bad; - if (unlikely(PyDict_SetItem(res, __pyx_n_s_n_node_samples, member) < 0)) goto bad; - Py_DECREF(member); - member = PyFloat_FromDouble(s.weighted_n_node_samples); if (unlikely(!member)) goto bad; - if (unlikely(PyDict_SetItem(res, __pyx_n_s_weighted_n_node_samples, member) < 0)) goto bad; - Py_DECREF(member); - return res; - bad: - Py_XDECREF(member); - Py_DECREF(res); - return NULL; - } - /* MemviewDtypeToObject */ - static CYTHON_INLINE PyObject *__pyx_memview_get_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(const char *itemp) { - return (PyObject *) __pyx_convert__to_py_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(*(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *) itemp); -} -static CYTHON_INLINE int __pyx_memview_set_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(const char *itemp, PyObject *obj) { - struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node value = __pyx_convert__from_py_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(obj); - if (PyErr_Occurred()) - return 0; - *(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *) itemp = value; - return 1; -} - -/* None */ - static CYTHON_INLINE long __Pyx_pow_long(long b, long e) { - long t = b; - switch (e) { - case 3: - t *= b; - CYTHON_FALLTHROUGH; - case 2: - t *= b; - CYTHON_FALLTHROUGH; - case 1: - return t; - case 0: - return 1; - } - #if 1 - if (unlikely(e<0)) return 0; - #endif - t = 1; - while (likely(e)) { - t *= (b * (e&1)) | ((~e)&1); - b *= b; - e >>= 1; - } - return t; -} - -/* None */ - static CYTHON_INLINE int __Pyx_ErrOccurredWithGIL(void) { - int err; - #ifdef WITH_THREAD - PyGILState_STATE _save = PyGILState_Ensure(); - #endif - err = !!PyErr_Occurred(); - #ifdef WITH_THREAD - PyGILState_Release(_save); - #endif - return err; -} - -/* Declarations */ - #if CYTHON_CCOMPLEX - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - return ::std::complex< float >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - return x + y*(__pyx_t_float_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - __pyx_t_float_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ - #if CYTHON_CCOMPLEX -#else - static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - if (b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabsf(b.real) >= fabsf(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - float r = b.imag / b.real; - float s = (float)(1.0) / (b.real + b.imag * r); - return __pyx_t_float_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - float r = b.real / b.imag; - float s = (float)(1.0) / (b.imag + b.real * r); - return __pyx_t_float_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - if (b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - float denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_float_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { - __pyx_t_float_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { - __pyx_t_float_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrtf(z.real*z.real + z.imag*z.imag); - #else - return hypotf(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - float r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - float denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_float(a, a); - case 3: - z = __Pyx_c_prod_float(a, a); - return __Pyx_c_prod_float(z, a); - case 4: - z = __Pyx_c_prod_float(a, a); - return __Pyx_c_prod_float(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if (b.imag == 0) { - z.real = powf(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2f(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_float(a); - theta = atan2f(a.imag, a.real); - } - lnr = logf(r); - z_r = expf(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cosf(z_theta); - z.imag = z_r * sinf(z_theta); - return z; - } - #endif -#endif - -/* Declarations */ - #if CYTHON_CCOMPLEX - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - return ::std::complex< double >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - return x + y*(__pyx_t_double_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - __pyx_t_double_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ - #if CYTHON_CCOMPLEX -#else - static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - if (b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabs(b.real) >= fabs(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - double r = b.imag / b.real; - double s = (double)(1.0) / (b.real + b.imag * r); - return __pyx_t_double_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - double r = b.real / b.imag; - double s = (double)(1.0) / (b.imag + b.real * r); - return __pyx_t_double_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - if (b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - double denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_double_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { - __pyx_t_double_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { - __pyx_t_double_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrt(z.real*z.real + z.imag*z.imag); - #else - return hypot(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - double r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - double denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_double(a, a); - case 3: - z = __Pyx_c_prod_double(a, a); - return __Pyx_c_prod_double(z, a); - case 4: - z = __Pyx_c_prod_double(a, a); - return __Pyx_c_prod_double(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if (b.imag == 0) { - z.real = pow(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_double(a); - theta = atan2(a.imag, a.real); - } - lnr = log(r); - z_r = exp(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cos(z_theta); - z.imag = z_r * sin(z_theta); - return z; - } - #endif -#endif - -/* MemviewSliceCopyTemplate */ - static __Pyx_memviewslice -__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, - const char *mode, int ndim, - size_t sizeof_dtype, int contig_flag, - int dtype_is_object) -{ - __Pyx_RefNannyDeclarations - int i; - __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; - struct __pyx_memoryview_obj *from_memview = from_mvs->memview; - Py_buffer *buf = &from_memview->view; - PyObject *shape_tuple = NULL; - PyObject *temp_int = NULL; - struct __pyx_array_obj *array_obj = NULL; - struct __pyx_memoryview_obj *memview_obj = NULL; - __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); - for (i = 0; i < ndim; i++) { - if (unlikely(from_mvs->suboffsets[i] >= 0)) { - PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " - "indirect dimensions (axis %d)", i); - goto fail; - } - } - shape_tuple = PyTuple_New(ndim); - if (unlikely(!shape_tuple)) { - goto fail; - } - __Pyx_GOTREF(shape_tuple); - for(i = 0; i < ndim; i++) { - temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); - if(unlikely(!temp_int)) { - goto fail; - } else { - PyTuple_SET_ITEM(shape_tuple, i, temp_int); - temp_int = NULL; - } - } - array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); - if (unlikely(!array_obj)) { - goto fail; - } - __Pyx_GOTREF(array_obj); - memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( - (PyObject *) array_obj, contig_flag, - dtype_is_object, - from_mvs->memview->typeinfo); - if (unlikely(!memview_obj)) - goto fail; - if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) - goto fail; - if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, - dtype_is_object) < 0)) - goto fail; - goto no_fail; -fail: - __Pyx_XDECREF(new_mvs.memview); - new_mvs.memview = NULL; - new_mvs.data = NULL; -no_fail: - __Pyx_XDECREF(shape_tuple); - __Pyx_XDECREF(temp_int); - __Pyx_XDECREF(array_obj); - __Pyx_RefNannyFinishContext(); - return new_mvs; -} - -/* TypeInfoToFormat */ - static struct __pyx_typeinfo_string __Pyx_TypeInfoToFormat(__Pyx_TypeInfo *type) { - struct __pyx_typeinfo_string result = { {0} }; - char *buf = (char *) result.string; - size_t size = type->size; - switch (type->typegroup) { - case 'H': - *buf = 'c'; - break; - case 'I': - case 'U': - if (size == 1) - *buf = (type->is_unsigned) ? 'B' : 'b'; - else if (size == 2) - *buf = (type->is_unsigned) ? 'H' : 'h'; - else if (size == 4) - *buf = (type->is_unsigned) ? 'I' : 'i'; - else if (size == 8) - *buf = (type->is_unsigned) ? 'Q' : 'q'; - break; - case 'P': - *buf = 'P'; - break; - case 'C': - { - __Pyx_TypeInfo complex_type = *type; - complex_type.typegroup = 'R'; - complex_type.size /= 2; - *buf++ = 'Z'; - *buf = __Pyx_TypeInfoToFormat(&complex_type).string[0]; - break; - } - case 'R': - if (size == 4) - *buf = 'f'; - else if (size == 8) - *buf = 'd'; - else - *buf = 'g'; - break; - } - return result; -} - -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(Py_intptr_t) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(Py_intptr_t) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(Py_intptr_t), - little, !is_unsigned); - } -} - -/* CIntFromPy */ - static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(Py_intptr_t) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (Py_intptr_t) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (Py_intptr_t) 0; - case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, digits[0]) - case 2: - if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) >= 2 * PyLong_SHIFT) { - return (Py_intptr_t) (((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) >= 3 * PyLong_SHIFT) { - return (Py_intptr_t) (((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) >= 4 * PyLong_SHIFT) { - return (Py_intptr_t) (((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (Py_intptr_t) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (Py_intptr_t) 0; - case -1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, +digits[0]) - case -2: - if (8 * sizeof(Py_intptr_t) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { - return (Py_intptr_t) (((Py_intptr_t)-1)*(((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { - return (Py_intptr_t) ((((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { - return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { - return (Py_intptr_t) ((((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { - return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { - return (Py_intptr_t) ((((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); - } - } - break; - } -#endif - if (sizeof(Py_intptr_t) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - Py_intptr_t val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (Py_intptr_t) -1; - } - } else { - Py_intptr_t val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (Py_intptr_t) -1; - val = __Pyx_PyInt_As_Py_intptr_t(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to Py_intptr_t"); - return (Py_intptr_t) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to Py_intptr_t"); - return (Py_intptr_t) -1; -} - -/* CIntFromPy */ - static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const int neg_one = (int) -1, const_zero = (int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(int) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (int) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (int) 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) - case 2: - if (8 * sizeof(int) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { - return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(int) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { - return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(int) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { - return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (int) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(int) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (int) 0; - case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) - case -2: - if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(int) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(int) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(int) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { - return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - } -#endif - if (sizeof(int) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - int val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (int) -1; - } - } else { - int val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (int) -1; - val = __Pyx_PyInt_As_int(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to int"); - return (int) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to int"); - return (int) -1; -} - -/* CIntFromPy */ - static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const long neg_one = (long) -1, const_zero = (long) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(long) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (long) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (long) 0; - case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) - case 2: - if (8 * sizeof(long) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { - return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(long) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { - return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(long) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { - return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (long) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(long) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (long) 0; - case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) - case -2: - if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(long) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(long) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(long) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - } -#endif - if (sizeof(long) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - long val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (long) -1; - } - } else { - long val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (long) -1; - val = __Pyx_PyInt_As_long(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to long"); - return (long) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to long"); - return (long) -1; -} - -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const int neg_one = (int) -1, const_zero = (int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(int) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(int) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(int) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(int), - little, !is_unsigned); - } -} - -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const long neg_one = (long) -1, const_zero = (long) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(long) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(long) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(long) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(long), - little, !is_unsigned); - } -} - -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_int32(npy_int32 value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(npy_int32) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(npy_int32) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(npy_int32) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(npy_int32), - little, !is_unsigned); - } -} - -/* CIntFromPy */ - static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(npy_int32) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(npy_int32, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (npy_int32) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (npy_int32) 0; - case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, digits[0]) - case 2: - if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) >= 2 * PyLong_SHIFT) { - return (npy_int32) (((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) >= 3 * PyLong_SHIFT) { - return (npy_int32) (((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) >= 4 * PyLong_SHIFT) { - return (npy_int32) (((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (npy_int32) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(npy_int32) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (npy_int32) 0; - case -1: __PYX_VERIFY_RETURN_INT(npy_int32, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, +digits[0]) - case -2: - if (8 * sizeof(npy_int32) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { - return (npy_int32) (((npy_int32)-1)*(((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { - return (npy_int32) ((((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { - return (npy_int32) (((npy_int32)-1)*(((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { - return (npy_int32) ((((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) { - return (npy_int32) (((npy_int32)-1)*(((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) { - return (npy_int32) ((((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); - } - } - break; - } -#endif - if (sizeof(npy_int32) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_int32, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(npy_int32, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - npy_int32 val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (npy_int32) -1; - } - } else { - npy_int32 val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (npy_int32) -1; - val = __Pyx_PyInt_As_npy_int32(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to npy_int32"); - return (npy_int32) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to npy_int32"); - return (npy_int32) -1; -} - -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_uint32(npy_uint32 value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const npy_uint32 neg_one = (npy_uint32) -1, const_zero = (npy_uint32) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(npy_uint32) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(npy_uint32) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_uint32) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(npy_uint32) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(npy_uint32) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(npy_uint32), - little, !is_unsigned); - } -} - -/* CIntFromPy */ - static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const char neg_one = (char) -1, const_zero = (char) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(char) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (char) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (char) 0; - case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) - case 2: - if (8 * sizeof(char) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { - return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(char) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { - return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(char) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { - return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (char) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(char) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (char) 0; - case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) - case -2: - if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { - return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(char) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { - return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { - return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(char) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { - return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { - return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(char) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { - return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); - } - } - break; - } -#endif - if (sizeof(char) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - char val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (char) -1; - } - } else { - char val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (char) -1; - val = __Pyx_PyInt_As_char(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to char"); - return (char) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to char"); - return (char) -1; -} - -/* TypeInfoCompare */ - static int -__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) -{ - int i; - if (!a || !b) - return 0; - if (a == b) - return 1; - if (a->size != b->size || a->typegroup != b->typegroup || - a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { - if (a->typegroup == 'H' || b->typegroup == 'H') { - return a->size == b->size; - } else { - return 0; - } - } - if (a->ndim) { - for (i = 0; i < a->ndim; i++) - if (a->arraysize[i] != b->arraysize[i]) - return 0; - } - if (a->typegroup == 'S') { - if (a->flags != b->flags) - return 0; - if (a->fields || b->fields) { - if (!(a->fields && b->fields)) - return 0; - for (i = 0; a->fields[i].type && b->fields[i].type; i++) { - __Pyx_StructField *field_a = a->fields + i; - __Pyx_StructField *field_b = b->fields + i; - if (field_a->offset != field_b->offset || - !__pyx_typeinfo_cmp(field_a->type, field_b->type)) - return 0; - } - return !a->fields[i].type && !b->fields[i].type; - } - } - return 1; -} - -/* MemviewSliceValidateAndInit */ - static int -__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) -{ - if (buf->shape[dim] <= 1) - return 1; - if (buf->strides) { - if (spec & __Pyx_MEMVIEW_CONTIG) { - if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { - if (unlikely(buf->strides[dim] != sizeof(void *))) { - PyErr_Format(PyExc_ValueError, - "Buffer is not indirectly contiguous " - "in dimension %d.", dim); - goto fail; - } - } else if (unlikely(buf->strides[dim] != buf->itemsize)) { - PyErr_SetString(PyExc_ValueError, - "Buffer and memoryview are not contiguous " - "in the same dimension."); - goto fail; - } - } - if (spec & __Pyx_MEMVIEW_FOLLOW) { - Py_ssize_t stride = buf->strides[dim]; - if (stride < 0) - stride = -stride; - if (unlikely(stride < buf->itemsize)) { - PyErr_SetString(PyExc_ValueError, - "Buffer and memoryview are not contiguous " - "in the same dimension."); - goto fail; - } - } - } else { - if (unlikely(spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1)) { - PyErr_Format(PyExc_ValueError, - "C-contiguous buffer is not contiguous in " - "dimension %d", dim); - goto fail; - } else if (unlikely(spec & (__Pyx_MEMVIEW_PTR))) { - PyErr_Format(PyExc_ValueError, - "C-contiguous buffer is not indirect in " - "dimension %d", dim); - goto fail; - } else if (unlikely(buf->suboffsets)) { - PyErr_SetString(PyExc_ValueError, - "Buffer exposes suboffsets but no strides"); - goto fail; - } - } - return 1; -fail: - return 0; -} -static int -__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) -{ - if (spec & __Pyx_MEMVIEW_DIRECT) { - if (unlikely(buf->suboffsets && buf->suboffsets[dim] >= 0)) { - PyErr_Format(PyExc_ValueError, - "Buffer not compatible with direct access " - "in dimension %d.", dim); - goto fail; - } - } - if (spec & __Pyx_MEMVIEW_PTR) { - if (unlikely(!buf->suboffsets || (buf->suboffsets[dim] < 0))) { - PyErr_Format(PyExc_ValueError, - "Buffer is not indirectly accessible " - "in dimension %d.", dim); - goto fail; - } - } - return 1; -fail: - return 0; -} -static int -__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) -{ - int i; - if (c_or_f_flag & __Pyx_IS_F_CONTIG) { - Py_ssize_t stride = 1; - for (i = 0; i < ndim; i++) { - if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { - PyErr_SetString(PyExc_ValueError, - "Buffer not fortran contiguous."); - goto fail; - } - stride = stride * buf->shape[i]; - } - } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { - Py_ssize_t stride = 1; - for (i = ndim - 1; i >- 1; i--) { - if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { - PyErr_SetString(PyExc_ValueError, - "Buffer not C contiguous."); - goto fail; - } - stride = stride * buf->shape[i]; - } - } - return 1; -fail: - return 0; -} -static int __Pyx_ValidateAndInit_memviewslice( - int *axes_specs, - int c_or_f_flag, - int buf_flags, - int ndim, - __Pyx_TypeInfo *dtype, - __Pyx_BufFmt_StackElem stack[], - __Pyx_memviewslice *memviewslice, - PyObject *original_obj) -{ - struct __pyx_memoryview_obj *memview, *new_memview; - __Pyx_RefNannyDeclarations - Py_buffer *buf; - int i, spec = 0, retval = -1; - __Pyx_BufFmt_Context ctx; - int from_memoryview = __pyx_memoryview_check(original_obj); - __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0); - if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) - original_obj)->typeinfo)) { - memview = (struct __pyx_memoryview_obj *) original_obj; - new_memview = NULL; - } else { - memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( - original_obj, buf_flags, 0, dtype); - new_memview = memview; - if (unlikely(!memview)) - goto fail; - } - buf = &memview->view; - if (unlikely(buf->ndim != ndim)) { - PyErr_Format(PyExc_ValueError, - "Buffer has wrong number of dimensions (expected %d, got %d)", - ndim, buf->ndim); - goto fail; - } - if (new_memview) { - __Pyx_BufFmt_Init(&ctx, stack, dtype); - if (unlikely(!__Pyx_BufFmt_CheckString(&ctx, buf->format))) goto fail; - } - if (unlikely((unsigned) buf->itemsize != dtype->size)) { - PyErr_Format(PyExc_ValueError, - "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " - "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", - buf->itemsize, - (buf->itemsize > 1) ? "s" : "", - dtype->name, - dtype->size, - (dtype->size > 1) ? "s" : ""); - goto fail; - } - if (buf->len > 0) { - for (i = 0; i < ndim; i++) { - spec = axes_specs[i]; - if (unlikely(!__pyx_check_strides(buf, i, ndim, spec))) - goto fail; - if (unlikely(!__pyx_check_suboffsets(buf, i, ndim, spec))) - goto fail; - } - if (unlikely(buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))) - goto fail; - } - if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, - new_memview != NULL) == -1)) { - goto fail; - } - retval = 0; - goto no_fail; -fail: - Py_XDECREF(new_memview); - retval = -1; -no_fail: - __Pyx_RefNannyFinishContext(); - return retval; -} - -/* ObjectToMemviewSlice */ - static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__(PyObject *obj, int writable_flag) { - __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; - __Pyx_BufFmt_StackElem stack[1]; - int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) }; - int retcode; - if (obj == Py_None) { - result.memview = (struct __pyx_memoryview_obj *) Py_None; - return result; - } - retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG, - (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT) | writable_flag, 2, - &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__, stack, - &result, obj); - if (unlikely(retcode == -1)) - goto __pyx_fail; - return result; -__pyx_fail: - result.memview = NULL; - result.data = NULL; - return result; -} - -/* ObjectToMemviewSlice */ - static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t__const__(PyObject *obj, int writable_flag) { - __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; - __Pyx_BufFmt_StackElem stack[1]; - int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; - int retcode; - if (obj == Py_None) { - result.memview = (struct __pyx_memoryview_obj *) Py_None; - return result; - } - retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, - PyBUF_RECORDS_RO | writable_flag, 2, - &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t__const__, stack, - &result, obj); - if (unlikely(retcode == -1)) - goto __pyx_fail; - return result; -__pyx_fail: - result.memview = NULL; - result.data = NULL; - return result; -} - -/* ObjectToMemviewSlice */ - static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t(PyObject *obj, int writable_flag) { - __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; - __Pyx_BufFmt_StackElem stack[1]; - int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; - int retcode; - if (obj == Py_None) { - result.memview = (struct __pyx_memoryview_obj *) Py_None; - return result; - } - retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, - PyBUF_RECORDS_RO | writable_flag, 1, - &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t, stack, - &result, obj); - if (unlikely(retcode == -1)) - goto __pyx_fail; - return result; -__pyx_fail: - result.memview = NULL; - result.data = NULL; - return result; -} - -/* ObjectToMemviewSlice */ - static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t(PyObject *obj, int writable_flag) { - __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; - __Pyx_BufFmt_StackElem stack[1]; - int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; - int retcode; - if (obj == Py_None) { - result.memview = (struct __pyx_memoryview_obj *) Py_None; - return result; - } - retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, - PyBUF_RECORDS_RO | writable_flag, 1, - &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, stack, - &result, obj); - if (unlikely(retcode == -1)) - goto __pyx_fail; - return result; -__pyx_fail: - result.memview = NULL; - result.data = NULL; - return result; -} - -/* ObjectToMemviewSlice */ - static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_unsigned_char(PyObject *obj, int writable_flag) { - __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; - __Pyx_BufFmt_StackElem stack[1]; - int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; - int retcode; - if (obj == Py_None) { - result.memview = (struct __pyx_memoryview_obj *) Py_None; - return result; - } - retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, - PyBUF_RECORDS_RO | writable_flag, 1, - &__Pyx_TypeInfo_unsigned_char, stack, - &result, obj); - if (unlikely(retcode == -1)) - goto __pyx_fail; - return result; -__pyx_fail: - result.memview = NULL; - result.data = NULL; - return result; -} - -/* CheckBinaryVersion */ - static int __Pyx_check_binary_version(void) { - char ctversion[4], rtversion[4]; - PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); - PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); - if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { - char message[200]; - PyOS_snprintf(message, sizeof(message), - "compiletime version %s of module '%.100s' " - "does not match runtime version %s", - ctversion, __Pyx_MODULE_NAME, rtversion); - return PyErr_WarnEx(NULL, message, 1); - } - return 0; -} - -/* VoidPtrImport */ - #ifndef __PYX_HAVE_RT_ImportVoidPtr -#define __PYX_HAVE_RT_ImportVoidPtr -static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig) { - PyObject *d = 0; - PyObject *cobj = 0; - d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); - if (!d) - goto bad; - cobj = PyDict_GetItemString(d, name); - if (!cobj) { - PyErr_Format(PyExc_ImportError, - "%.200s does not export expected C variable %.200s", - PyModule_GetName(module), name); - goto bad; - } -#if PY_VERSION_HEX >= 0x02070000 - if (!PyCapsule_IsValid(cobj, sig)) { - PyErr_Format(PyExc_TypeError, - "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), name, sig, PyCapsule_GetName(cobj)); - goto bad; - } - *p = PyCapsule_GetPointer(cobj, sig); -#else - {const char *desc, *s1, *s2; - desc = (const char *)PyCObject_GetDesc(cobj); - if (!desc) - goto bad; - s1 = desc; s2 = sig; - while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } - if (*s1 != *s2) { - PyErr_Format(PyExc_TypeError, - "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), name, sig, desc); - goto bad; - } - *p = PyCObject_AsVoidPtr(cobj);} -#endif - if (!(*p)) - goto bad; - Py_DECREF(d); - return 0; -bad: - Py_XDECREF(d); - return -1; -} -#endif - -/* FunctionImport */ - #ifndef __PYX_HAVE_RT_ImportFunction -#define __PYX_HAVE_RT_ImportFunction -static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig) { - PyObject *d = 0; - PyObject *cobj = 0; - union { - void (*fp)(void); - void *p; - } tmp; - d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); - if (!d) - goto bad; - cobj = PyDict_GetItemString(d, funcname); - if (!cobj) { - PyErr_Format(PyExc_ImportError, - "%.200s does not export expected C function %.200s", - PyModule_GetName(module), funcname); - goto bad; - } -#if PY_VERSION_HEX >= 0x02070000 - if (!PyCapsule_IsValid(cobj, sig)) { - PyErr_Format(PyExc_TypeError, - "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), funcname, sig, PyCapsule_GetName(cobj)); - goto bad; - } - tmp.p = PyCapsule_GetPointer(cobj, sig); -#else - {const char *desc, *s1, *s2; - desc = (const char *)PyCObject_GetDesc(cobj); - if (!desc) - goto bad; - s1 = desc; s2 = sig; - while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } - if (*s1 != *s2) { - PyErr_Format(PyExc_TypeError, - "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", - PyModule_GetName(module), funcname, sig, desc); - goto bad; - } - tmp.p = PyCObject_AsVoidPtr(cobj);} -#endif - *f = tmp.fp; - if (!(*f)) - goto bad; - Py_DECREF(d); - return 0; -bad: - Py_XDECREF(d); - return -1; -} -#endif - -/* InitStrings */ - static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { - while (t->p) { - #if PY_MAJOR_VERSION < 3 - if (t->is_unicode) { - *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); - } else if (t->intern) { - *t->p = PyString_InternFromString(t->s); - } else { - *t->p = PyString_FromStringAndSize(t->s, t->n - 1); - } - #else - if (t->is_unicode | t->is_str) { - if (t->intern) { - *t->p = PyUnicode_InternFromString(t->s); - } else if (t->encoding) { - *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); - } else { - *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); - } - } else { - *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); - } - #endif - if (!*t->p) - return -1; - if (PyObject_Hash(*t->p) == -1) - return -1; - ++t; - } - return 0; -} - -static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { - return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); -} -static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { - Py_ssize_t ignore; - return __Pyx_PyObject_AsStringAndSize(o, &ignore); -} -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT -#if !CYTHON_PEP393_ENABLED -static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { - char* defenc_c; - PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); - if (!defenc) return NULL; - defenc_c = PyBytes_AS_STRING(defenc); -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - { - char* end = defenc_c + PyBytes_GET_SIZE(defenc); - char* c; - for (c = defenc_c; c < end; c++) { - if ((unsigned char) (*c) >= 128) { - PyUnicode_AsASCIIString(o); - return NULL; - } - } - } -#endif - *length = PyBytes_GET_SIZE(defenc); - return defenc_c; -} -#else -static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { - if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - if (likely(PyUnicode_IS_ASCII(o))) { - *length = PyUnicode_GET_LENGTH(o); - return PyUnicode_AsUTF8(o); - } else { - PyUnicode_AsASCIIString(o); - return NULL; - } -#else - return PyUnicode_AsUTF8AndSize(o, length); -#endif -} -#endif -#endif -static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT - if ( -#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - __Pyx_sys_getdefaultencoding_not_ascii && -#endif - PyUnicode_Check(o)) { - return __Pyx_PyUnicode_AsStringAndSize(o, length); - } else -#endif -#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) - if (PyByteArray_Check(o)) { - *length = PyByteArray_GET_SIZE(o); - return PyByteArray_AS_STRING(o); - } else -#endif - { - char* result; - int r = PyBytes_AsStringAndSize(o, &result, length); - if (unlikely(r < 0)) { - return NULL; - } else { - return result; - } - } -} -static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { - int is_true = x == Py_True; - if (is_true | (x == Py_False) | (x == Py_None)) return is_true; - else return PyObject_IsTrue(x); -} -static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { - int retval; - if (unlikely(!x)) return -1; - retval = __Pyx_PyObject_IsTrue(x); - Py_DECREF(x); - return retval; -} -static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { -#if PY_MAJOR_VERSION >= 3 - if (PyLong_Check(result)) { - if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, - "__int__ returned non-int (type %.200s). " - "The ability to return an instance of a strict subclass of int " - "is deprecated, and may be removed in a future version of Python.", - Py_TYPE(result)->tp_name)) { - Py_DECREF(result); - return NULL; - } - return result; - } -#endif - PyErr_Format(PyExc_TypeError, - "__%.4s__ returned non-%.4s (type %.200s)", - type_name, type_name, Py_TYPE(result)->tp_name); - Py_DECREF(result); - return NULL; -} -static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { -#if CYTHON_USE_TYPE_SLOTS - PyNumberMethods *m; -#endif - const char *name = NULL; - PyObject *res = NULL; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x) || PyLong_Check(x))) -#else - if (likely(PyLong_Check(x))) -#endif - return __Pyx_NewRef(x); -#if CYTHON_USE_TYPE_SLOTS - m = Py_TYPE(x)->tp_as_number; - #if PY_MAJOR_VERSION < 3 - if (m && m->nb_int) { - name = "int"; - res = m->nb_int(x); - } - else if (m && m->nb_long) { - name = "long"; - res = m->nb_long(x); - } - #else - if (likely(m && m->nb_int)) { - name = "int"; - res = m->nb_int(x); - } - #endif -#else - if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { - res = PyNumber_Int(x); - } -#endif - if (likely(res)) { -#if PY_MAJOR_VERSION < 3 - if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { -#else - if (unlikely(!PyLong_CheckExact(res))) { -#endif - return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); - } - } - else if (!PyErr_Occurred()) { - PyErr_SetString(PyExc_TypeError, - "an integer is required"); - } - return res; -} -static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { - Py_ssize_t ival; - PyObject *x; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_CheckExact(b))) { - if (sizeof(Py_ssize_t) >= sizeof(long)) - return PyInt_AS_LONG(b); - else - return PyInt_AsSsize_t(b); - } -#endif - if (likely(PyLong_CheckExact(b))) { - #if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)b)->ob_digit; - const Py_ssize_t size = Py_SIZE(b); - if (likely(__Pyx_sst_abs(size) <= 1)) { - ival = likely(size) ? digits[0] : 0; - if (size == -1) ival = -ival; - return ival; - } else { - switch (size) { - case 2: - if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { - return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - case -2: - if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { - return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - case 3: - if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { - return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - case -3: - if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { - return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - case 4: - if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { - return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - case -4: - if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { - return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - } - } - #endif - return PyLong_AsSsize_t(b); - } - x = PyNumber_Index(b); - if (!x) return -1; - ival = PyInt_AsSsize_t(x); - Py_DECREF(x); - return ival; -} -static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { - return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); -} -static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { - return PyInt_FromSize_t(ival); -} - - -#endif /* Py_PYTHON_H */ From f3a696bd255ec5797f0f2523982ebbf84f61bab5 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 11:00:07 +0100 Subject: [PATCH 02/33] Modifying stpredictions for py310 --- .github/workflows/pytest_cp39.yml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index 7c0692318..b7d53417a 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -2,9 +2,9 @@ name: pytesting 3.9 on: push: - branches-ignore: - - "main" -# branches: [ main ] + # branches-ignore: + # - "main" + branches: [ main ] schedule: - cron: '0 0 1 * *' # pull_request: From 3bbc48e23e55cceb679a6deb404f461d767c2ca3 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 11:08:24 +0100 Subject: [PATCH 03/33] Modifying stpredictions for py310 --- .github/workflows/pytest_cp37.yml | 1 + .github/workflows/pytest_cp39.yml | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/pytest_cp37.yml b/.github/workflows/pytest_cp37.yml index 5e36d40fb..d1344902f 100644 --- a/.github/workflows/pytest_cp37.yml +++ b/.github/workflows/pytest_cp37.yml @@ -2,6 +2,7 @@ name: pytesting 3.7 on: push: + ### This will ignore the testing # branches-ignore: # - "main" # # branches: [ main ] diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index b7d53417a..47b124d0f 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -4,7 +4,7 @@ on: push: # branches-ignore: # - "main" - branches: [ main ] + # # branches: [ main ] schedule: - cron: '0 0 1 * *' # pull_request: From a2063d2f628f31a4dabfa2e5fe6a525146ac3230 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 11:18:37 +0100 Subject: [PATCH 04/33] Modifying stpredictions for py310 --- .github/workflows/pytest_cp39.yml | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index 47b124d0f..eeac45846 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -56,12 +56,13 @@ jobs: # make clean # pip install . ################## Use this when you want to use local wheel installation through dist ###################### - # make dist - # pip install dist/* + make dist + pip install dist/* ############################################################################# # python setup.py develop # pip install -i https://test.pypi.org/simple/ structured-predictions==0.0.6 - pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple structured-predictions + #### To install from TestPyPi + # pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple structured-predictions # pip install -i https://test.pypi.org/simple/ structured-predictions # python tests/tests_DIOKR/Demo_DeepIOKR_bibtex.py - name: Test with pytest From 1f39bc936d94d7e96bda400376a6f7700261882f Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 11:22:35 +0100 Subject: [PATCH 05/33] Modifying stpredictions for py310 --- .github/workflows/pytest_cp37.yml | 6 +++++- .github/workflows/pytest_cp38.yml | 4 ++++ .github/workflows/pytest_cp39.yml | 4 ++++ 3 files changed, 13 insertions(+), 1 deletion(-) diff --git a/.github/workflows/pytest_cp37.yml b/.github/workflows/pytest_cp37.yml index d1344902f..0961b8865 100644 --- a/.github/workflows/pytest_cp37.yml +++ b/.github/workflows/pytest_cp37.yml @@ -1,3 +1,7 @@ +################## GitHub Action Tips ##############3 +# If you use GitHub Action for specific project after long Time. +# You first need to modify the Action file in order for GitHub Action to work + name: pytesting 3.7 on: @@ -33,7 +37,7 @@ jobs: run: | python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# - # pip install -r requirements.txt + pip install -r requirements.txt # - name: Lint with flake8 # run: | # pip install flake8 diff --git a/.github/workflows/pytest_cp38.yml b/.github/workflows/pytest_cp38.yml index 1273162f6..9e7d9107b 100644 --- a/.github/workflows/pytest_cp38.yml +++ b/.github/workflows/pytest_cp38.yml @@ -1,3 +1,7 @@ +################## GitHub Action Tips ##############3 +# If you use GitHub Action for specific project after long Time. +# You first need to modify the Action file in order for GitHub Action to work + name: pytesting 3.8 on: diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index eeac45846..40730e1c8 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -1,3 +1,7 @@ +################## GitHub Action Tips ##############3 +# If you use GitHub Action for specific project after long Time. +# You first need to modify the Action file in order for GitHub Action to work + name: pytesting 3.9 on: From 7c156f6fd3613e4eff59c38d05e236741e0e6cea Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 11:26:45 +0100 Subject: [PATCH 06/33] Modifying stpredictions for py310 --- .github/workflows/pytest_cp37.yml | 4 ++-- .github/workflows/pytest_cp38.yml | 4 ++-- .github/workflows/pytest_cp39.yml | 6 +++--- 3 files changed, 7 insertions(+), 7 deletions(-) diff --git a/.github/workflows/pytest_cp37.yml b/.github/workflows/pytest_cp37.yml index 0961b8865..d36c6bdd1 100644 --- a/.github/workflows/pytest_cp37.yml +++ b/.github/workflows/pytest_cp37.yml @@ -7,8 +7,8 @@ name: pytesting 3.7 on: push: ### This will ignore the testing - # branches-ignore: - # - "main" + branches-ignore: + - "main" # # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/.github/workflows/pytest_cp38.yml b/.github/workflows/pytest_cp38.yml index 9e7d9107b..d768c2114 100644 --- a/.github/workflows/pytest_cp38.yml +++ b/.github/workflows/pytest_cp38.yml @@ -6,8 +6,8 @@ name: pytesting 3.8 on: push: - # branches-ignore: - # - "main" + branches-ignore: + - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index 40730e1c8..d3c60bc77 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -20,8 +20,8 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - # os: [macos-latest] - os: [macos-latest, ubuntu-latest, windows-latest] + os: [ubuntu-latest] + # os: [macos-latest, ubuntu-latest, windows-latest] python: ['3.9',] env: OS: ${{ matrix.os }} @@ -36,7 +36,7 @@ jobs: run: | python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# - # pip install -r requirements.txt + pip install -r requirements.txt # - name: Lint with flake8 # run: | # pip install flake8 From ab1801db8bf8824171cf1bd729ac924641168ff5 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 11:32:13 +0100 Subject: [PATCH 07/33] Modifying stpredictions for py310 --- requirements.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/requirements.txt b/requirements.txt index 8b753c28a..81210ecb4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -23,8 +23,8 @@ Keras-Preprocessing==1.1.2 kiwisolver==1.3.1 Markdown==3.3.4 matplotlib==3.4.2 -# numpy==1.19.5 -numpy>=1.20.0 +numpy==1.19.5 +# numpy>=1.20.0 oauthlib==3.1.1 operalib==0.2b27 opt-einsum==3.3.0 From fee8294b98b663f08a1cc31353f49aa2e1b7741b Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 11:36:05 +0100 Subject: [PATCH 08/33] Modifying stpredictions for py310 --- .github/workflows/pytest_cp39.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index d3c60bc77..2670ebc30 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -36,6 +36,7 @@ jobs: run: | python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# + pip install numpy==1.19.5 pip install -r requirements.txt # - name: Lint with flake8 # run: | From 8e9134f6b6ccf4c96fd36fd8c58b6c11d64c3ca7 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 11:40:12 +0100 Subject: [PATCH 09/33] Modifying stpredictions for py310 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 81210ecb4..f864d81e9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -26,7 +26,7 @@ matplotlib==3.4.2 numpy==1.19.5 # numpy>=1.20.0 oauthlib==3.1.1 -operalib==0.2b27 +# operalib==0.2b27 opt-einsum==3.3.0 packaging==21.3 pandas==1.2.4 From b891ebaf3ac15db7fdc856c6b5f3c5c22bb97898 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 11:42:14 +0100 Subject: [PATCH 10/33] Modifying stpredictions for py310 --- requirements.txt | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index f864d81e9..0f81999ae 100644 --- a/requirements.txt +++ b/requirements.txt @@ -6,7 +6,8 @@ certifi==2021.5.30 chardet==4.0.0 cvxopt==1.2.6 cycler==0.10.0 -Cython==0.29.23 +# Cython==0.29.23 +Cython flatbuffers==1.12 gast==0.4.0 ghalton==0.6.2 From 2868480a85316c54b373144af6d8a7317940059c Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 11:51:41 +0100 Subject: [PATCH 11/33] Modifying stpredictions for py310 --- .github/workflows/pytest_cp39.yml | 2 +- requirements.txt | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index 2670ebc30..dbe478ef9 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -36,7 +36,7 @@ jobs: run: | python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# - pip install numpy==1.19.5 + # pip install numpy==1.19.5 pip install -r requirements.txt # - name: Lint with flake8 # run: | diff --git a/requirements.txt b/requirements.txt index 0f81999ae..a4770861c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -6,8 +6,8 @@ certifi==2021.5.30 chardet==4.0.0 cvxopt==1.2.6 cycler==0.10.0 -# Cython==0.29.23 -Cython +Cython==0.29.23 +# Cython flatbuffers==1.12 gast==0.4.0 ghalton==0.6.2 From f2de7fac8cfe4e1c5d3965325535b7fa474a3133 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 12:03:15 +0100 Subject: [PATCH 12/33] Modifying stpredictions for py310 --- stpredictions/models/OK3/{ => extra}/_criterion.c | 0 .../OK3/{ => extra}/_criterion.cp37-win_amd64.pyd | Bin .../models/OK3/{ => extra}/_criterion.html | 0 .../OK3/{ => extra}/_splitter.cp37-win_amd64.pyd | Bin stpredictions/models/OK3/{ => extra}/_splitter.html | 0 stpredictions/models/OK3/{ => extra}/_splitter.pxd | 0 .../models/OK3/{ => extra}/_tree.cp37-win_amd64.pyd | Bin stpredictions/models/OK3/{ => extra}/_tree.html | 0 stpredictions/models/OK3/{ => extra}/_tree.pxd | 0 stpredictions/models/OK3/{ => extra}/_utils.pxd | 0 10 files changed, 0 insertions(+), 0 deletions(-) rename stpredictions/models/OK3/{ => extra}/_criterion.c (100%) rename stpredictions/models/OK3/{ => extra}/_criterion.cp37-win_amd64.pyd (100%) rename stpredictions/models/OK3/{ => extra}/_criterion.html (100%) rename stpredictions/models/OK3/{ => extra}/_splitter.cp37-win_amd64.pyd (100%) rename stpredictions/models/OK3/{ => extra}/_splitter.html (100%) rename stpredictions/models/OK3/{ => extra}/_splitter.pxd (100%) rename stpredictions/models/OK3/{ => extra}/_tree.cp37-win_amd64.pyd (100%) rename stpredictions/models/OK3/{ => extra}/_tree.html (100%) rename stpredictions/models/OK3/{ => extra}/_tree.pxd (100%) rename stpredictions/models/OK3/{ => extra}/_utils.pxd (100%) diff --git a/stpredictions/models/OK3/_criterion.c b/stpredictions/models/OK3/extra/_criterion.c similarity index 100% rename from stpredictions/models/OK3/_criterion.c rename to stpredictions/models/OK3/extra/_criterion.c diff --git a/stpredictions/models/OK3/_criterion.cp37-win_amd64.pyd b/stpredictions/models/OK3/extra/_criterion.cp37-win_amd64.pyd similarity index 100% rename from stpredictions/models/OK3/_criterion.cp37-win_amd64.pyd rename to stpredictions/models/OK3/extra/_criterion.cp37-win_amd64.pyd diff --git a/stpredictions/models/OK3/_criterion.html b/stpredictions/models/OK3/extra/_criterion.html similarity index 100% rename from stpredictions/models/OK3/_criterion.html rename to stpredictions/models/OK3/extra/_criterion.html diff --git a/stpredictions/models/OK3/_splitter.cp37-win_amd64.pyd b/stpredictions/models/OK3/extra/_splitter.cp37-win_amd64.pyd similarity index 100% rename from stpredictions/models/OK3/_splitter.cp37-win_amd64.pyd rename to stpredictions/models/OK3/extra/_splitter.cp37-win_amd64.pyd diff --git a/stpredictions/models/OK3/_splitter.html b/stpredictions/models/OK3/extra/_splitter.html similarity index 100% rename from stpredictions/models/OK3/_splitter.html rename to stpredictions/models/OK3/extra/_splitter.html diff --git a/stpredictions/models/OK3/_splitter.pxd b/stpredictions/models/OK3/extra/_splitter.pxd similarity index 100% rename from stpredictions/models/OK3/_splitter.pxd rename to stpredictions/models/OK3/extra/_splitter.pxd diff --git a/stpredictions/models/OK3/_tree.cp37-win_amd64.pyd b/stpredictions/models/OK3/extra/_tree.cp37-win_amd64.pyd similarity index 100% rename from stpredictions/models/OK3/_tree.cp37-win_amd64.pyd rename to stpredictions/models/OK3/extra/_tree.cp37-win_amd64.pyd diff --git a/stpredictions/models/OK3/_tree.html b/stpredictions/models/OK3/extra/_tree.html similarity index 100% rename from stpredictions/models/OK3/_tree.html rename to stpredictions/models/OK3/extra/_tree.html diff --git a/stpredictions/models/OK3/_tree.pxd b/stpredictions/models/OK3/extra/_tree.pxd similarity index 100% rename from stpredictions/models/OK3/_tree.pxd rename to stpredictions/models/OK3/extra/_tree.pxd diff --git a/stpredictions/models/OK3/_utils.pxd b/stpredictions/models/OK3/extra/_utils.pxd similarity index 100% rename from stpredictions/models/OK3/_utils.pxd rename to stpredictions/models/OK3/extra/_utils.pxd From 07a2a6a975c3407a77de4c512a1605f27c496267 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 19 Dec 2023 13:11:44 +0100 Subject: [PATCH 13/33] Modifying stpredictions for py310 --- stpredictions/models/OK3/MANIFEST | 5 + stpredictions/models/OK3/README.md | 36 + stpredictions/models/OK3/__init__.py | 20 - stpredictions/models/OK3/_classes.py | 2006 +- stpredictions/models/OK3/_criterion.c | 25520 ++++++++ stpredictions/models/OK3/_criterion.pxd | 61 + stpredictions/models/OK3/_criterion.pyx | 1355 +- stpredictions/models/OK3/_export.py | 1097 - stpredictions/models/OK3/_forest.py | 274 +- stpredictions/models/OK3/_reingold_tilford.py | 188 - stpredictions/models/OK3/_splitter.c | 35305 ++++++++++++ .../models/OK3/{extra => }/_splitter.pxd | 72 +- stpredictions/models/OK3/_splitter.pyx | 1937 +- stpredictions/models/OK3/_tree.c | 48004 ++++++++++++++++ .../models/OK3/{extra => }/_tree.pxd | 75 +- stpredictions/models/OK3/_tree.pyx | 1139 +- stpredictions/models/OK3/_utils.pyx | 447 - stpredictions/models/OK3/extra/_criterion.c | 1 - .../OK3/extra/_criterion.cp37-win_amd64.pyd | Bin 119808 -> 0 bytes .../models/OK3/extra/_criterion.html | 1512 - .../OK3/extra/_splitter.cp37-win_amd64.pyd | Bin 162816 -> 0 bytes stpredictions/models/OK3/extra/_splitter.html | 4641 -- .../models/OK3/extra/_tree.cp37-win_amd64.pyd | Bin 311296 -> 0 bytes stpredictions/models/OK3/extra/_tree.html | 10843 ---- stpredictions/models/OK3/extra/_utils.pxd | 110 - stpredictions/models/OK3/kernel.py | 114 +- stpredictions/models/OK3/setup.py | 42 + stpredictions/models/OK3/structured_object.py | 14 +- 28 files changed, 111918 insertions(+), 22900 deletions(-) create mode 100644 stpredictions/models/OK3/MANIFEST create mode 100644 stpredictions/models/OK3/README.md delete mode 100644 stpredictions/models/OK3/__init__.py create mode 100644 stpredictions/models/OK3/_criterion.c create mode 100644 stpredictions/models/OK3/_criterion.pxd delete mode 100644 stpredictions/models/OK3/_export.py delete mode 100644 stpredictions/models/OK3/_reingold_tilford.py create mode 100644 stpredictions/models/OK3/_splitter.c rename stpredictions/models/OK3/{extra => }/_splitter.pxd (62%) create mode 100644 stpredictions/models/OK3/_tree.c rename stpredictions/models/OK3/{extra => }/_tree.pxd (58%) delete mode 100644 stpredictions/models/OK3/_utils.pyx delete mode 100644 stpredictions/models/OK3/extra/_criterion.c delete mode 100644 stpredictions/models/OK3/extra/_criterion.cp37-win_amd64.pyd delete mode 100644 stpredictions/models/OK3/extra/_criterion.html delete mode 100644 stpredictions/models/OK3/extra/_splitter.cp37-win_amd64.pyd delete mode 100644 stpredictions/models/OK3/extra/_splitter.html delete mode 100644 stpredictions/models/OK3/extra/_tree.cp37-win_amd64.pyd delete mode 100644 stpredictions/models/OK3/extra/_tree.html delete mode 100644 stpredictions/models/OK3/extra/_utils.pxd create mode 100644 stpredictions/models/OK3/setup.py diff --git a/stpredictions/models/OK3/MANIFEST b/stpredictions/models/OK3/MANIFEST new file mode 100644 index 000000000..1d7f493e8 --- /dev/null +++ b/stpredictions/models/OK3/MANIFEST @@ -0,0 +1,5 @@ +# file GENERATED by distutils, do NOT edit +_criterion.c +_splitter.c +_tree.c +setup.py diff --git a/stpredictions/models/OK3/README.md b/stpredictions/models/OK3/README.md new file mode 100644 index 000000000..43d41d84d --- /dev/null +++ b/stpredictions/models/OK3/README.md @@ -0,0 +1,36 @@ +# pythonOK3 +classes and methods to implement the OK3 method : decision trees with a kernelized output for structured prediction. + + +Afin de tester facilement OK3, j'ai fais en sorte qu'il puisse prendre en argument des matrices de vecteurs de sortie plutôt que uniquement des matrices de Gram, il construira ensuite en interne la matrice de Gram des sorties et la donnera au "vraies" méthodes fit et predict notamment. + + +Pour tester les arbres OK3 pour de la classification multilabel ou de la régression sur des données vectorielles (avec respectivement un critère d'impurté Gini et variance), une série de tests est rédigée dans le fichier tests/test_tree_clf_and_reg.py. + + + +Protocole : + + +1 - Cloner le projet 'pythonOK3' + + +2 - Dans son dossier cloné, exécuter dans un terminal : python setup.py build_ext --inplace + + Cela va compiler les différents fichiers Cython, et certainment lever plusieurs warnings (à ignorer) + + +3 - Eventuellement restart le kernel de la console iPython si l'on souhaite y travailler pour prendre en compte les chanements dans les fichiers compilés + + +4 - Pour lancer la batterie de tests, entrer dans un terminal : pytest tests/test_treeclf_and_reg.py + + Cela va lancer la totalité des tests de ce fichier, certains étant assez longs. (Durée totale inférieure à 11min) + Ces tests sont appliqués à des tâches de régression et de classification uniquement, il reste à tester sur des vrais problèmes structurés. + + +5 - Une autre manière de tester très rapidement ces fonctions de classification et régression et de comparer aux résultats obtenus avec les arbres de classification et régression classique est d'exécuter les fichiers test_classification et test_regression qui vont imprimer certaines lignes démontrant la quasi identité des arbres construits par OK3 et ceux classiques. + + +6 - Pour tester la prédiction structurée (différent de la régression et classification simple), voir le fichier tests.exemple_utilisation.py qui décrit comment utiliser les arbres ok3 (sur un problème de classification multilabel pouvant s'apparenter à un pb de prédiction structurée). + diff --git a/stpredictions/models/OK3/__init__.py b/stpredictions/models/OK3/__init__.py deleted file mode 100644 index 5d116c4c0..000000000 --- a/stpredictions/models/OK3/__init__.py +++ /dev/null @@ -1,20 +0,0 @@ -""" -The :mod:`sklearn.tree` module includes decision tree-based models for -classification and regression. -""" - -from ._classes import BaseKernelizedOutputTree -from ._classes import OK3Regressor -from ._classes import ExtraOK3Regressor -from ._forest import BaseOKForest -from ._forest import OKForestRegressor -from ._forest import RandomOKForestRegressor - -__all__ = [ - "BaseKernelizedOutputTree", - "OK3Regressor", - "ExtraOK3Regressor", - "BaseOKForest", - "OKForestRegressor", - "RandomOKForestRegressor", -] diff --git a/stpredictions/models/OK3/_classes.py b/stpredictions/models/OK3/_classes.py index 6e01b8b49..3b2a19037 100644 --- a/stpredictions/models/OK3/_classes.py +++ b/stpredictions/models/OK3/_classes.py @@ -1,59 +1,48 @@ """ -This module gathers tree-based methods, including decision, regression and -randomized trees. Single and multi-output problems are both handled. +This module implement the OK3 method. +Handles the problem of learning functions with a structured output space, +represented by vectors but whiwh is often not a vectorial space. """ -# Authors: Gilles Louppe -# Peter Prettenhofer -# Brian Holt -# Noel Dawe -# Satrajit Gosh -# Joly Arnaud -# Fares Hedayati -# Nelson Liu -# -# License: BSD 3 clause - import numbers import warnings -import copy from abc import ABCMeta from abc import abstractmethod from math import ceil -from numbers import Integral, Real + +import time import numpy as np from scipy.sparse import issparse -from ..base import BaseEstimator -from ..base import ClassifierMixin -from ..base import clone -from ..base import RegressorMixin -from ..base import is_classifier -from ..base import MultiOutputMixin -from ..utils import Bunch -from ..utils import check_random_state -from ..utils.validation import _check_sample_weight -from ..utils import compute_sample_weight -from ..utils.multiclass import check_classification_targets -from ..utils.validation import check_is_fitted -from ..utils._param_validation import Hidden, Interval, StrOptions - -from ._criterion import Criterion -from ._splitter import Splitter -from ._tree import DepthFirstTreeBuilder -from ._tree import BestFirstTreeBuilder -from ._tree import Tree -from ._tree import _build_pruned_tree_ccp -from ._tree import ccp_pruning_path -from . import _tree, _splitter, _criterion - -__all__ = [ - "DecisionTreeClassifier", - "DecisionTreeRegressor", - "ExtraTreeClassifier", - "ExtraTreeRegressor", -] +from sklearn.metrics import accuracy_score +from sklearn.metrics import hamming_loss +from sklearn.metrics import r2_score + +from sklearn.base import BaseEstimator +from sklearn.base import clone + +from base import StructuredOutputMixin + +from sklearn.utils import Bunch +from sklearn.utils import check_array +from sklearn.utils import check_random_state +from sklearn.utils.validation import _check_sample_weight +from sklearn.utils.multiclass import check_classification_targets +from sklearn.utils.validation import check_is_fitted +from sklearn.utils.validation import _deprecate_positional_args + +from _criterion import Criterion +from _splitter import Splitter +from kernel import Kernel +from _tree import DepthFirstTreeBuilder +from _tree import BestFirstTreeBuilder +from _tree import Tree +from _tree import _build_pruned_tree_ccp +from _tree import ccp_pruning_path +import _tree, _splitter, _criterion, kernel + +__all__ = ["OK3Regressor", "ExtraOK3Regressor"] # ============================================================================= @@ -63,78 +52,58 @@ DTYPE = _tree.DTYPE DOUBLE = _tree.DOUBLE -CRITERIA_CLF = { - "gini": _criterion.Gini, - "log_loss": _criterion.Entropy, - "entropy": _criterion.Entropy, -} -CRITERIA_REG = { - "squared_error": _criterion.MSE, - "friedman_mse": _criterion.FriedmanMSE, - "absolute_error": _criterion.MAE, - "poisson": _criterion.Poisson, -} - -DENSE_SPLITTERS = {"best": _splitter.BestSplitter, "random": _splitter.RandomSplitter} - -SPARSE_SPLITTERS = { - "best": _splitter.BestSparseSplitter, - "random": _splitter.RandomSparseSplitter, -} +# The criteria is the loss function (in the embedding Hilbert space) the tree +# wants to minimise. Here we've implemented the classic variance reduction, called here "mse". +CRITERIA = {"mse": _criterion.KernelizedMSE} + +# This is the different types of kernels which can be used to compute similarities between vectorial representations of the outputs. +# Each one of them corresponds to a different embedding in an Hilbert space. +# There is two particular kernels : "gini_clf" and "mse_reg" which actually correspond +# to the "mean-dirac" kernel and the linear kernel but by specifying that we want +# (for a classification or a regression task) to perform an exact search of the output +# instead of an approximate minimisation of the criterion among alist of candidates. +KERNELS = {"gini_clf": kernel.Gini_Kernel, + "mse_reg": kernel.MSE_Kernel, + "mean_dirac": kernel.Mean_Dirac_Kernel, + "linear": kernel.Linear_Kernel, + "laplacian": kernel.Laplacian_Kernel, + "gaussian": kernel.Gaussian_Kernel} + +# Les splitters sont des classes définissant les stratégies de recherche des splits (feature+threshold) +DENSE_SPLITTERS = {"best": _splitter.BestSplitter, + "random": _splitter.RandomSplitter} + +SPARSE_SPLITTERS = {"best": _splitter.BestSparseSplitter, + "random": _splitter.RandomSparseSplitter} # ============================================================================= # Base decision tree # ============================================================================= -class BaseDecisionTree(MultiOutputMixin, BaseEstimator, metaclass=ABCMeta): - """Base class for decision trees. +class BaseKernelizedOutputTree(StructuredOutputMixin, BaseEstimator, metaclass=ABCMeta): + """Base class for regression trees with a kernel in the output space. Warning: This class should not be used directly. Use derived classes instead. """ - _parameter_constraints: dict = { - "splitter": [StrOptions({"best", "random"})], - "max_depth": [Interval(Integral, 1, None, closed="left"), None], - "min_samples_split": [ - Interval(Integral, 2, None, closed="left"), - Interval("real_not_int", 0.0, 1.0, closed="right"), - ], - "min_samples_leaf": [ - Interval(Integral, 1, None, closed="left"), - Interval("real_not_int", 0.0, 1.0, closed="neither"), - ], - "min_weight_fraction_leaf": [Interval(Real, 0.0, 0.5, closed="both")], - "max_features": [ - Interval(Integral, 1, None, closed="left"), - Interval("real_not_int", 0.0, 1.0, closed="right"), - StrOptions({"auto", "sqrt", "log2"}, deprecated={"auto"}), - None, - ], - "random_state": ["random_state"], - "max_leaf_nodes": [Interval(Integral, 2, None, closed="left"), None], - "min_impurity_decrease": [Interval(Real, 0.0, None, closed="left")], - "ccp_alpha": [Interval(Real, 0.0, None, closed="left")], - } - @abstractmethod - def __init__( - self, - *, - criterion, - splitter, - max_depth, - min_samples_split, - min_samples_leaf, - min_weight_fraction_leaf, - max_features, - max_leaf_nodes, - random_state, - min_impurity_decrease, - class_weight=None, - ccp_alpha=0.0, - ): + @_deprecate_positional_args + def __init__(self, *, + criterion, + splitter, + max_depth, + min_samples_split, + min_samples_leaf, + min_weight_fraction_leaf, + max_features, + max_leaf_nodes, + random_state, + min_impurity_decrease, + min_impurity_split, + ccp_alpha=0.0, + kernel): self.criterion = criterion self.splitter = splitter self.max_depth = max_depth @@ -145,8 +114,10 @@ def __init__( self.max_leaf_nodes = max_leaf_nodes self.random_state = random_state self.min_impurity_decrease = min_impurity_decrease - self.class_weight = class_weight + self.min_impurity_split = min_impurity_split self.ccp_alpha = ccp_alpha + self.kernel = kernel + self.leaves_preds = None def get_depth(self): """Return the depth of the decision tree. @@ -172,91 +143,168 @@ def get_n_leaves(self): """ check_is_fitted(self) return self.tree_.n_leaves + + def fit(self, X, y, sample_weight=None, check_input=True, + X_idx_sorted="deprecated", kernel=None, in_ensemble=False, Gram_y=None): + """ + kernel : Optional input. If not provided, the kernel attribute of the + estimatoris used. If provided, the kernel attribute of the estimator + is updated. + + Some possible values : + + "gini_clf" : y is a matrix of labels for multilabel classification. + shape (n_train_samples, n_labels) + We have to compute the corresponding gram matrix, + equivalent to the use of a Classification Tree with the gini + index as impurity. Exact solution search is performed. + "mse_reg" : y is a matrix of real vectors for multiouput regression. + shape (n_train_samples, n_outputs) + We have to compute the corresponding gram matrix, + equivalent to the use of a Regression Tree with the mse + as impurity. Exact solution search is performed. + "mean_dirac" : y is a matrix or vectors (vectorial representation of structured objects). + shape (n_train_samples, vector_length) + The similarity between two objects is computed with a mean dirac equality kernel. + "linear" : y is a matrix or vectors (vectorial representation of structured objects). + shape (n_train_samples, vector_length) + The similarity between two objects is computed with a linear kernel. + "gaussian" : y is a matrix or vectors (vectorial representation of structured objects). + shape (n_train_samples, vector_length) + The similarity between two objects is computed with a gaussian kernel. + + in_ensemble : boolean, default=False + flag to set to true when the estimator is used with an ensemble method, + if True, the Gram matrix of the outputs is also given (as K_y) and doesn't have to + be computed by the tree --> avoid this heavy calculation for all trees. + + Gram_y : the output gram matrix, default=None + Allows to avoid the Gram matrix calculation if we already have it (useful when in_ensemble=True) + """ - def fit(self, X, y, sample_weight=None, check_input=True): - self._validate_params() + if kernel is None: + kernel = self.kernel + else: # on peut mettre à jour l'attribut kernel de l'estimateur à travers le fit. + self.kernel = kernel + random_state = check_random_state(self.random_state) + if self.ccp_alpha < 0.0: + raise ValueError("ccp_alpha must be greater than or equal to 0") + if check_input: # Need to validate separately here. - # We can't pass multi_output=True because that would allow y to be + # We can't pass multi_ouput=True because that would allow y to be # csr. check_X_params = dict(dtype=DTYPE, accept_sparse="csc") check_y_params = dict(ensure_2d=False, dtype=None) - X, y = self._validate_data( - X, y, validate_separately=(check_X_params, check_y_params) - ) + X, y = self._validate_data(X, y, + validate_separately=(check_X_params, + check_y_params)) if issparse(X): X.sort_indices() if X.indices.dtype != np.intc or X.indptr.dtype != np.intc: - raise ValueError( - "No support for np.int64 index based sparse matrices" - ) - - if self.criterion == "poisson": - if np.any(y < 0): - raise ValueError( - "Some value(s) of y are negative which is" - " not allowed for Poisson regression." - ) - if np.sum(y) <= 0: - raise ValueError( - "Sum of y is not positive which is " - "necessary for Poisson regression." - ) + raise ValueError("No support for np.int64 index based " + "sparse matrices") # Determine output settings - n_samples, self.n_features_in_ = X.shape - is_classification = is_classifier(self) + n_samples, self.n_features_ = X.shape y = np.atleast_1d(y) - expanded_class_weight = None + + if not isinstance(kernel, Kernel): + params = () + if isinstance(kernel, tuple): + kernel, params = kernel[0], kernel[1:] + try: + kernel = KERNELS[kernel](*params) + except KeyError: + print("Error : 'kernel' attribute (or its first element if it is a tuple) has to be either a Kernel class or a string which is a valid key for the dict 'KERNELS'.") + raise + if y.ndim == 1: # reshape is necessary to preserve the data contiguity against vs # [:, np.newaxis] that does not. y = np.reshape(y, (-1, 1)) - - self.n_outputs_ = y.shape[1] - - if is_classification: + + if y.shape[1] == y.shape[0]: + warnings.warn("The target parameter is a square matrix." + "Are you sure this is the matrix of outputs and " + "not a Gram matrix ? " + "If it is a Gram matrix, sorry but you have to " + "provide the vectorialized data representation " + "instead and provide a 'kernel' argument which " + "describes how to compute the Gram matrix you want." + "Or you can also provided the gram as K_y in addition to y.") + + if "clf" in kernel.get_name(): check_classification_targets(y) - y = np.copy(y) - - self.classes_ = [] - self.n_classes_ = [] - - if self.class_weight is not None: - y_original = np.copy(y) - - y_encoded = np.zeros(y.shape, dtype=int) - for k in range(self.n_outputs_): - classes_k, y_encoded[:, k] = np.unique(y[:, k], return_inverse=True) - self.classes_.append(classes_k) - self.n_classes_.append(classes_k.shape[0]) - y = y_encoded - - if self.class_weight is not None: - expanded_class_weight = compute_sample_weight( - self.class_weight, y_original - ) - - self.n_classes_ = np.array(self.n_classes_, dtype=np.intp) - + + + if Gram_y is not None: + # une matrice de Gram est donnée, on l'utilise + if not in_ensemble: + # dangereux d'accepter des matrics de Gram calculées par l'utilisateur : elles peuvent comporter des erreurs + warnings.warn("You passed a gram matrix of the outputs as an argument and" + "the tree isn't in an ensemble method : please be sure it corresponds " + "to the outputs presented in 'y' and the kernel given in 'kernel' " + "because we are not going to recompute another gram matrix.") + if Gram_y.ndim == 1: + raise ValueError("Gram_y must be a 2d numpy array of shape " + "n_samples*n_samples (Gram matrix of the " + "outputs of the learning set), got a 1d array") + + if Gram_y.shape[1] != Gram_y.shape[0]: + raise ValueError("Gram_y must be a 2d numpy array of shape " + "n_samples*n_samples (Gram matrix of the " + "outputs of the learning set)") + + K_y = Gram_y + + else: + start_computation = time.time() + # compute the Gram matrix of the outputs + K_y = kernel.get_Gram_matrix(y) + print("Time to compute the training Gram matrix : " + str(time.time() - start_computation) + " s.") + + if getattr(y, "dtype", None) != DOUBLE or not y.flags.contiguous: y = np.ascontiguousarray(y, dtype=DOUBLE) - max_depth = np.iinfo(np.int32).max if self.max_depth is None else self.max_depth + # Check parameters + max_depth = (np.iinfo(np.int32).max if self.max_depth is None + else self.max_depth) + max_leaf_nodes = (-1 if self.max_leaf_nodes is None + else self.max_leaf_nodes) if isinstance(self.min_samples_leaf, numbers.Integral): + if not 1 <= self.min_samples_leaf: + raise ValueError("min_samples_leaf must be at least 1 " + "or in (0, 0.5], got %s" + % self.min_samples_leaf) min_samples_leaf = self.min_samples_leaf else: # float + if not 0. < self.min_samples_leaf <= 0.5: + raise ValueError("min_samples_leaf must be at least 1 " + "or in (0, 0.5], got %s" + % self.min_samples_leaf) min_samples_leaf = int(ceil(self.min_samples_leaf * n_samples)) if isinstance(self.min_samples_split, numbers.Integral): + if not 2 <= self.min_samples_split: + raise ValueError("min_samples_split must be an integer " + "greater than 1 or a float in (0.0, 1.0]; " + "got the integer %s" + % self.min_samples_split) min_samples_split = self.min_samples_split else: # float + if not 0. < self.min_samples_split <= 1.: + raise ValueError("min_samples_split must be an integer " + "greater than 1 or a float in (0.0, 1.0]; " + "got the float %s" + % self.min_samples_split) min_samples_split = int(ceil(self.min_samples_split * n_samples)) min_samples_split = max(2, min_samples_split) @@ -264,147 +312,178 @@ def fit(self, X, y, sample_weight=None, check_input=True): if isinstance(self.max_features, str): if self.max_features == "auto": - if is_classification: - max_features = max(1, int(np.sqrt(self.n_features_in_))) - warnings.warn( - "`max_features='auto'` has been deprecated in 1.1 " - "and will be removed in 1.3. To keep the past behaviour, " - "explicitly set `max_features='sqrt'`.", - FutureWarning, - ) + if "clf" in kernel.get_name(): + max_features = max(1, int(np.sqrt(self.n_features_))) else: - max_features = self.n_features_in_ - warnings.warn( - "`max_features='auto'` has been deprecated in 1.1 " - "and will be removed in 1.3. To keep the past behaviour, " - "explicitly set `max_features=1.0'`.", - FutureWarning, - ) + max_features = self.n_features_ elif self.max_features == "sqrt": - max_features = max(1, int(np.sqrt(self.n_features_in_))) + max_features = max(1, int(np.sqrt(self.n_features_))) elif self.max_features == "log2": - max_features = max(1, int(np.log2(self.n_features_in_))) + max_features = max(1, int(np.log2(self.n_features_))) + else: + raise ValueError("Invalid value for max_features. " + "Allowed string values are 'auto', " + "'sqrt' or 'log2'.") elif self.max_features is None: - max_features = self.n_features_in_ + max_features = self.n_features_ elif isinstance(self.max_features, numbers.Integral): max_features = self.max_features else: # float if self.max_features > 0.0: - max_features = max(1, int(self.max_features * self.n_features_in_)) + max_features = max(1, + int(self.max_features * self.n_features_)) else: max_features = 0 self.max_features_ = max_features - max_leaf_nodes = -1 if self.max_leaf_nodes is None else self.max_leaf_nodes - if len(y) != n_samples: - raise ValueError( - "Number of labels=%d does not match number of samples=%d" - % (len(y), n_samples) - ) + raise ValueError("Number of outputs=%d does not match " + "number of samples=%d" % (len(y), n_samples)) + if not 0 <= self.min_weight_fraction_leaf <= 0.5: + raise ValueError("min_weight_fraction_leaf must in [0, 0.5]") + if max_depth <= 0: + raise ValueError("max_depth must be greater than zero. ") + if not (0 < max_features <= self.n_features_): + raise ValueError("max_features must be in (0, n_features]") + if not isinstance(max_leaf_nodes, numbers.Integral): + raise ValueError("max_leaf_nodes must be integral number but was " + "%r" % max_leaf_nodes) + if -1 < max_leaf_nodes < 2: + raise ValueError(("max_leaf_nodes {0} must be either None " + "or larger than 1").format(max_leaf_nodes)) if sample_weight is not None: sample_weight = _check_sample_weight(sample_weight, X, DOUBLE) - if expanded_class_weight is not None: - if sample_weight is not None: - sample_weight = sample_weight * expanded_class_weight - else: - sample_weight = expanded_class_weight - # Set min_weight_leaf from min_weight_fraction_leaf if sample_weight is None: - min_weight_leaf = self.min_weight_fraction_leaf * n_samples + min_weight_leaf = (self.min_weight_fraction_leaf * + n_samples) + else: + min_weight_leaf = (self.min_weight_fraction_leaf * + np.sum(sample_weight)) + + min_impurity_split = self.min_impurity_split + if min_impurity_split is not None: + warnings.warn("The min_impurity_split parameter is deprecated. " + "Its default value has changed from 1e-7 to 0 in " + "version 0.23, and it will be removed in 0.25. " + "Use the min_impurity_decrease parameter instead.", + FutureWarning) + + if min_impurity_split < 0.: + raise ValueError("min_impurity_split must be greater than " + "or equal to 0") else: - min_weight_leaf = self.min_weight_fraction_leaf * np.sum(sample_weight) + min_impurity_split = 0 + + if self.min_impurity_decrease < 0.: + raise ValueError("min_impurity_decrease must be greater than " + "or equal to 0") + + # TODO: Remove in v0.26 + if X_idx_sorted != "deprecated": + warnings.warn("The parameter 'X_idx_sorted' is deprecated and has " + "no effect. It will be removed in v0.26. You can " + "suppress this warning by not passing any value to " + "the 'X_idx_sorted' parameter.", FutureWarning) # Build tree criterion = self.criterion if not isinstance(criterion, Criterion): - if is_classification: - criterion = CRITERIA_CLF[self.criterion]( - self.n_outputs_, self.n_classes_ - ) - else: - criterion = CRITERIA_REG[self.criterion](self.n_outputs_, n_samples) - else: - # Make a deepcopy in case the criterion has mutable attributes that - # might be shared and modified concurrently during parallel fitting - criterion = copy.deepcopy(criterion) + criterion = CRITERIA[self.criterion](n_samples) SPLITTERS = SPARSE_SPLITTERS if issparse(X) else DENSE_SPLITTERS splitter = self.splitter if not isinstance(self.splitter, Splitter): - splitter = SPLITTERS[self.splitter]( - criterion, - self.max_features_, - min_samples_leaf, - min_weight_leaf, - random_state, - ) - - if is_classifier(self): - self.tree_ = Tree(self.n_features_in_, self.n_classes_, self.n_outputs_) - else: - self.tree_ = Tree( - self.n_features_in_, - # TODO: tree shouldn't need this in this case - np.array([1] * self.n_outputs_, dtype=np.intp), - self.n_outputs_, - ) + splitter = SPLITTERS[self.splitter](criterion, + self.max_features_, + min_samples_leaf, + min_weight_leaf, + random_state) + + self.tree_ = Tree(self.n_features_, n_samples) # Use BestFirst if max_leaf_nodes given; use DepthFirst otherwise if max_leaf_nodes < 0: - builder = DepthFirstTreeBuilder( - splitter, - min_samples_split, - min_samples_leaf, - min_weight_leaf, - max_depth, - self.min_impurity_decrease, - ) + builder = DepthFirstTreeBuilder(splitter, min_samples_split, + min_samples_leaf, + min_weight_leaf, + max_depth, + self.min_impurity_decrease, + min_impurity_split) else: - builder = BestFirstTreeBuilder( - splitter, - min_samples_split, - min_samples_leaf, - min_weight_leaf, - max_depth, - max_leaf_nodes, - self.min_impurity_decrease, - ) - - builder.build(self.tree_, X, y, sample_weight) - - if self.n_outputs_ == 1 and is_classifier(self): - self.n_classes_ = self.n_classes_[0] - self.classes_ = self.classes_[0] + builder = BestFirstTreeBuilder(splitter, min_samples_split, + min_samples_leaf, + min_weight_leaf, + max_depth, + max_leaf_nodes, + self.min_impurity_decrease, + min_impurity_split) + + builder.build(self.tree_, X, K_y, sample_weight) + # store the output training examples + self.tree_.y = y self._prune_tree() - + + # reset leaves_preds because the tree changed + self.leaves_preds = None + return self def _validate_X_predict(self, X, check_input): - """Validate the training data on predict (probabilities).""" + """Validate X whenever one tries to predict, apply""" if check_input: - X = self._validate_data(X, dtype=DTYPE, accept_sparse="csr", reset=False) - if issparse(X) and ( - X.indices.dtype != np.intc or X.indptr.dtype != np.intc - ): - raise ValueError("No support for np.int64 index based sparse matrices") - else: - # The number of features is checked regardless of `check_input` - self._check_n_features(X, reset=False) + X = check_array(X, dtype=DTYPE, accept_sparse="csr") + if issparse(X) and (X.indices.dtype != np.intc or + X.indptr.dtype != np.intc): + raise ValueError("No support for np.int64 index based " + "sparse matrices") + + n_features = X.shape[1] + if self.n_features_ != n_features: + raise ValueError("Number of features of the model must " + "match the input. Model n_features is %s and " + "input n_features is %s " + % (self.n_features_, n_features)) + return X - def predict(self, X, check_input=True): - """Predict class or regression value for X. + def get_leaves_weights(self): + """Gives the weighted training samples in each leaf + + Returns + ------- + A (n_nodes, n_training_samples) array which gives for each node (line number) + and for each training sample its weight in the node (O if the sample doesn't fall + in the node, and a non-negative value depending on 'sample_weight' otherwise.) + """ + check_is_fitted(self) + return self.tree_.value + + def predict_weights(self, X, check_input=True): + """Predict the output for X as weighted combinations of training outputs + It is kind of the representation in the Hilbert space. + + Returns + ------- + A (len(X), n_training_samples) array which gives for each test example (line number) + and for each training sample its weight in the node (O if the sample doesn't fall + in the same leaf as the test example, and a non-negative value depending on 'sample_weight' otherwise.) + """ + check_is_fitted(self) + X = self._validate_X_predict(X, check_input) + + return self.tree_.predict(X) + + def predict(self, X, candidates=None, check_input=True, return_top_k=1): + """Predict structured objects for X. - For a classification model, the predicted class for each sample in X is - returned. For a regression model, the predicted value based on X is - returned. + The predicted structured objects based on X are returned. + Performs an argmin research algorithm amongst the possible outputs Parameters ---------- @@ -412,49 +491,173 @@ def predict(self, X, check_input=True): The input samples. Internally, it will be converted to ``dtype=np.float32`` and if a sparse matrix is provided to a sparse ``csr_matrix``. + + candidates : array of shape (nb_candidates, vectorial_repr_len), default=None + The candidates outputs for the minimisation problem of decoding the predictions + in the Hilbert space. + If not given or None, it will be set to the output training matrix. check_input : bool, default=True Allow to bypass several input checking. - Don't use this parameter unless you know what you're doing. + Don't use this parameter unless you know what you do. + + return_top_k : int, default=1 + Indicate how many decoded outputs to return for each example (or for each leaf). + Default is one : select the output that gives the minimum "distance" with the + predicted value in the Hilbert space. + But it is useful to be able to return for example the 5 best candidates in order + to evaluate a top 5 accuracy metric. Returns ------- - y : array-like of shape (n_samples,) or (n_samples, n_outputs) - The predicted classes, or the predict values. + output : + array of shape (n_samples, vectorial_repr_len) containing the vectorial + representations of the structured output objects (found in the set of candidates, + or if it is not given, among the training outputs). """ + kernel = self.kernel + if isinstance(kernel, Kernel): + kernel = kernel.get_name() + elif isinstance(kernel, tuple): + kernel = kernel[0] + check_is_fitted(self) X = self._validate_X_predict(X, check_input) - proba = self.tree_.predict(X) - n_samples = X.shape[0] - - # Classification - if is_classifier(self): - if self.n_outputs_ == 1: - return self.classes_.take(np.argmax(proba, axis=1), axis=0) + + criterion = self.criterion + if not isinstance(criterion, Criterion): + criterion = CRITERIA[self.criterion](X.shape[0]) + + if "reg" in kernel and return_top_k > 1: + warnings.warn("On ne peut pas retourner plusieurs candidats d'outputs dans le cas d'une régression, veuillez plutôt choisir kernel=linear. " + "return_top_k va etre mis à 1.") + return_top_k = 1 + + if candidates is None: + + if self.leaves_preds is None: + if not("clf" in kernel or "reg" in kernel): + warnings.warn("Vous n'avez pas renseigné de candidats ni excécuté de précédentes prédictions, " + "le décodage se fait donc parmi l'ensemble de sorties d'entrapinement.\n" + "Si ce n'est pas ce que vous souhaitez, veuillez renseigner un ensemble de candidats de sorties afin de décoder.") + + elif self.leaves_preds.shape[0] != self.tree_.node_count*return_top_k: + # cas ou leaves_preds n'est pas None mais return_top_k a changé depuis le précédent décodage + if not("clf" in kernel or "reg" in kernel): + warnings.warn("Vous n'avez pas renseigné de candidats et les précédents décodages demandaient un nombre différent de propositions de candidats ('return_top_k'), " + "le décodage se fait donc parmi l'ensemble de sorties d'entrapinement.\n" + "Si ce n'est pas ce que vous souhaitez, veuillez renseigner un ensemble de candidats de sorties afin de décoder.") else: - class_type = self.classes_[0].dtype - predictions = np.zeros((n_samples, self.n_outputs_), dtype=class_type) - for k in range(self.n_outputs_): - predictions[:, k] = self.classes_[k].take( - np.argmax(proba[:, k], axis=1), axis=0 - ) + # le nombre de prédictions par feuille est le meme: + X_leaves = self.apply(X) + # X_leaves_indices est là pour aller chercher les bons indices + # dans self.leaves_preds. En effet chaque noeud a return_top_k + # indices d'affilé dans le tableau leaves_preds, + # de node_id*return_top_k à node_id*return_top_k+return_top_k + X_leaves_indices = np.zeros(X_leaves.shape[0]*return_top_k, dtype=X_leaves.dtype) + for k in range(return_top_k): + X_leaves_indices[k::return_top_k] = X_leaves*return_top_k+k + return self.leaves_preds[X_leaves_indices] + + # on calcule la totalité des sorties avec cet ensemble de candidats (et on met à jour self.leaves_preds) + self.decode_tree(candidates, return_top_k=return_top_k) + # on utilise ces sorties pour calculer celles demandées + return self.predict(X, return_top_k=return_top_k) + + def decode(self, X, candidates=None, check_input=True, return_top_k=1): + """ Synonyme de predict """ + return self.predict(X=X, candidates=candidates, check_input=check_input, return_top_k=return_top_k) + + def decode_tree(self, candidates=None, return_top_k=1): + """Decode each leaves predictions of the tree, AND store the array of the decoded outputs + as an attribut of the estimator : self.leaves_preds. + + ATTENTION, les prédictions correspondant aux noeuds qui ne sont pas des feuilles n'ont aucu sens : elles sont arbitraires. + Elles n'ont volontairement pas été calculées pour question d'économie de temps. - return predictions + Parameters + ---------- + + candidates : array of shape (nb_candidates, vectorial_repr_len), default=None + The candidates outputs for the minimisation problem of decoding the predictions + in the Hilbert space. + If not given or None, it will be set to the output training matrix. + + return_top_k : int, default=1 + Indicate how many decoded outputs to return for each example (or for each leaf). + Default is one : select the output that gives the minimum "distance" with the + predicted value in the Hilbert space. + But it is useful to be able to return for example the 5 best candidates in order + to evaluate a top 5 accuracy metric. + + Returns + ------- + leaves_preds : array-like of shape (node_count,vector_length) + For each leaf, return the vectorial representation of the output in 'candidates' + that minimizes the "distance" with the "exact" prediction in the Hilbert space. + + leaves_preds[i*return_top_k : (i+1)*return_top_k] is the non-ordered list od the + decoded outputs of the node i among candidates. + """ + kernel = self.kernel + + if not isinstance(kernel, Kernel): + params = () + if isinstance(kernel, tuple): + kernel, params = kernel[0], kernel[1:] + try: + kernel = KERNELS[kernel](*params) + except KeyError: + print("Error : 'kernel' attribute (or its first element if it is a tuple) has to be either a Kernel class or a string which is a valid key for the dict 'KERNELS'.") + raise - # Regression - else: - if self.n_outputs_ == 1: - return proba[:, 0] - else: - return proba[:, :, 0] + check_is_fitted(self) + criterion = self.criterion + if not isinstance(criterion, Criterion): + criterion = CRITERIA[self.criterion](0) + + if candidates is not None: + # candidates doit etre un ensemble : pas de répétition + candidates = np.unique(candidates, axis=0) + + K_cand_train = kernel.get_Gram_matrix(candidates, self.tree_.y) + sq_norms_cand = kernel.get_sq_norms(candidates) + else: # recherche dans le learning set + candidates, indices = np.unique(self.tree_.y, return_index=True, axis=0) + K_cand_train = self.tree_.K_y[indices] + sq_norms_cand = self.tree_.K_y[indices, indices] + + if return_top_k > 1 and return_top_k >= len(candidates): + warnings.warn("Le nombre de prédictions demandées pour chaque entrée dépasse le nombre de sorties candidates, return_top_k va être réduit à sa valeur maximale.") + return_top_k = len(candidates)-1 + + if "reg" in kernel.get_name() and return_top_k > 1: + warnings.warn("On ne peut pas retourner plusieurs candidats d'outputs dans le cas d'une régression, veuillez plutôt choisir kernel=linear. " + "return_top_k va etre mis à 1.") + return_top_k = 1 + + leaves_preds = self.tree_.decode_tree(K_cand_train = K_cand_train, sq_norms_cand=sq_norms_cand, criterion=criterion, kernel=kernel.get_name(), return_top_k=return_top_k) + + if not("reg" in kernel.get_name() or "clf" in kernel.get_name()): + # les outputs récupérées sont alors des indices corrspondants au set de candidats + # on traduit les indices renvoyés en représentations vectorielles + leaves_preds = candidates[leaves_preds] + + + if leaves_preds.shape[1] == 1: + leaves_preds = leaves_preds.reshape(-1) + + # On stocke les sorties décodées de l'arbre pour pouvoir les sortir rapidement pour les prochains décodages. + self.leaves_preds = leaves_preds + + return leaves_preds + def apply(self, X, check_input=True): """Return the index of the leaf that each sample is predicted as. - .. versionadded:: 0.17 - Parameters ---------- X : {array-like, sparse matrix} of shape (n_samples, n_features) @@ -464,7 +667,7 @@ def apply(self, X, check_input=True): check_input : bool, default=True Allow to bypass several input checking. - Don't use this parameter unless you know what you're doing. + Don't use this parameter unless you know what you do. Returns ------- @@ -478,11 +681,170 @@ def apply(self, X, check_input=True): X = self._validate_X_predict(X, check_input) return self.tree_.apply(X) + + def score(self, X, y, candidates=None, metric="accuracy", sample_weight=None): + """ + Calcule le score après décodage + + Return either + + -the coefficient of determination R^2 of the prediction. + The coefficient R^2 is defined as (1 - u/v), where u is the residual + sum of squares ((y_true - y_pred) ** 2).sum() and v is the total + sum of squares ((y_true - y_true.mean()) ** 2).sum(). + + (IF self.kernel="mse_reg") + + -the mean accuracy of the predictions if metric="accuracy". + (Requires that all labels match to count as positive in case of multilabel) + + -the mean hamming score of the predictions if metric="hamming" + (Well suited for multilabel classification) + + -the mean top k accuracy score if metric="top_"+str(k) + It works with all wanted value of k. + + It is possible to set the 'sample_weight' parameter for all these metrics. + + Note: + ----- + All this score metrics are highly dependent on the candidates set because it + deals with the decoded predictions (which are among this set). + If you want to compute a score only based on the tree structure, you can + use the following method 'r2_score_in_Hilbert'. + + + Parameters + ---------- + X : array-like of shape (n_samples, n_features) + Test samples. + y : array-like of shape (n_samples,) or (n_samples, n_outputs) + True outputs for X. + candidates : array-like of shape (nb_candidates, n_outputs) + Possible decoded outputs for X + metric : str, default="accuracy" + The way to compute the score + sample_weight : array-like of shape (n_samples,), default=None + Sample weights. + Returns + ------- + score : float + Chosen score between self.predict(X) and y. + """ + kernel = self.kernel + if isinstance(kernel, Kernel): + kernel = kernel.get_name() + elif isinstance(kernel, tuple): + kernel = kernel[0] + return_top_k = 1 + top_k_score = False + if metric[:4] == "top_": + try: + return_top_k = int(metric[4:]) + top_k_score = True + except ValueError: + raise(ValueError("Pour calculer le score 'top k', veuillez renseigner un nombre juste après le 'top_'. Nous avons reçu '"+metric[4:]+"'.")) + + y_pred = self.predict(X, candidates=candidates, return_top_k=return_top_k) + + if "reg" in kernel: + return r2_score(y, y_pred, sample_weight=sample_weight) + else: + if metric == "accuracy": + return accuracy_score(y, y_pred, sample_weight=sample_weight) + elif metric == "hamming": + return 1 - hamming_loss(y, y_pred, sample_weight=sample_weight) + elif top_k_score: + contains_true = [False]*len(y) + for ex in range(len(y)): + for candidate in range(ex*return_top_k, (ex+1)*return_top_k): + if np.atleast_1d(y[ex] == y_pred[candidate]).all(): + contains_true[ex] = True + if sample_weight is not None: + score = np.sum(sample_weight[contains_true]) / np.sum(sample_weight) + else: + score = np.sum(contains_true) / len(y) + return score + else: + raise ValueError("La metric renseignée n'est pas prise en charge.") + + + def r2_score_in_Hilbert(self, X, y, sample_weight=None): + """ + Calcule le score R2 SANS décodage + + Return the coefficient of determination R^2 of the prediction in the Hilbert space. + The coefficient R^2 is defined as (1 - u/v), where u is the residual + sum of squares ((y_true - y_pred) ** 2).sum() and v is the total + sum of squares ((y_true - y_true.mean()) ** 2).sum(). + + Parameters + ---------- + X : array-like of shape (n_samples, n_features) + Test samples. + y : array-like of shape (n_samples,) or (n_samples, n_outputs) + True outputs for X. + sample_weight : array-like of shape (n_samples,), default=None + Sample weights. + Returns + ------- + score : float + R2 score of the predictions in the Hilbert space wrt. the embedded values of y. + """ + + kernel = self.kernel + + if not isinstance(kernel, Kernel): + params = () + if isinstance(kernel, tuple): + kernel, params = kernel[0], kernel[1:] + try: + kernel = KERNELS[kernel](*params) + except KeyError: + print("Error : 'kernel' attribute (or its first element if it is a tuple) has to be either a Kernel class or a string which is a valid key for the dict 'KERNELS'.") + raise + + weights = self.predict_weights(X) + + K_train = self.tree_.K_y + + K_test_train = kernel.get_Gram_matrix(y, self.tree_.y) + + K_test_test = kernel.get_Gram_matrix(y) + + + if sample_weight is not None: + if len(sample_weight != len(y)): + raise ValueError("sample_weights has to have the same length as y. " + "y is len "+str(len(y))+", and sample_weight is len "+str(len(sample_weight))) + sample_weight[sample_weight<0] = 0 + if np.sum(sample_weight) == 0: + warnings.warn("all weights in sample_weight were set to 0 or bellow. It is unvalid so sample_weight will be ignored.") + sample_weight = None + + res_sq_sums = np.diag(K_test_test) - 2 * np.diag(K_test_train @ (weights.T)) + np.diag(weights @ K_train @ (weights.T)) + + if sample_weight is not None: + tot_sq_sums = np.diag(K_test_test) - np.sum(K_test_test @ np.diag(sample_weight), axis=1) / np.sum(sample_weight) + else: + tot_sq_sums = np.diag(K_test_test) - np.sum(K_test_test, axis=1)/K_test_test.shape[1] + + + if sample_weight is not None: + res_sq_sum = np.sum(sample_weight*res_sq_sums) / np.sum(sample_weight) + tot_sq_sum = np.sum(sample_weight*tot_sq_sums) / np.sum(sample_weight) + else: + res_sq_sum = np.mean(res_sq_sums) + tot_sq_sum = np.mean(tot_sq_sums) + + r2 = 1 - ( res_sq_sum / tot_sq_sum ) + + return r2 + + def decision_path(self, X, check_input=True): """Return the decision path in the tree. - .. versionadded:: 0.18 - Parameters ---------- X : {array-like, sparse matrix} of shape (n_samples, n_features) @@ -492,7 +854,7 @@ def decision_path(self, X, check_input=True): check_input : bool, default=True Allow to bypass several input checking. - Don't use this parameter unless you know what you're doing. + Don't use this parameter unless you know what you do. Returns ------- @@ -507,20 +869,14 @@ def _prune_tree(self): """Prune tree using Minimal Cost-Complexity Pruning.""" check_is_fitted(self) + if self.ccp_alpha < 0.0: + raise ValueError("ccp_alpha must be greater than or equal to 0") + if self.ccp_alpha == 0.0: return # build pruned tree - if is_classifier(self): - n_classes = np.atleast_1d(self.n_classes_) - pruned_tree = Tree(self.n_features_in_, n_classes, self.n_outputs_) - else: - pruned_tree = Tree( - self.n_features_in_, - # TODO: the tree shouldn't need this param - np.array([1] * self.n_outputs_, dtype=np.intp), - self.n_outputs_, - ) + pruned_tree = Tree(self.n_features_, self.tree_.K_y.shape[0]) _build_pruned_tree_ccp(pruned_tree, self.tree_, self.ccp_alpha) self.tree_ = pruned_tree @@ -559,7 +915,7 @@ def cost_complexity_pruning_path(self, X, y, sample_weight=None): impurities : ndarray Sum of the impurities of the subtree leaves for the corresponding alpha value in ``ccp_alphas``. - """ + """ est = clone(self).set_params(ccp_alpha=0.0) est.fit(X, y, sample_weight=sample_weight) return Bunch(**ccp_pruning_path(est.tree_)) @@ -591,18 +947,19 @@ def feature_importances_(self): # Public estimators # ============================================================================= - -class DecisionTreeClassifier(ClassifierMixin, BaseDecisionTree): - """A decision tree classifier. - - Read more in the :ref:`User Guide `. +class OK3Regressor(BaseKernelizedOutputTree): + """A decision tree regressor for the OK3 method. Parameters ---------- - criterion : {"gini", "entropy", "log_loss"}, default="gini" - The function to measure the quality of a split. Supported criteria are - "gini" for the Gini impurity and "log_loss" and "entropy" both for the - Shannon information gain, see :ref:`tree_mathematical_formulation`. + criterion : {"mse"}, default="mse" + The function to measure the quality of a split. Supported criteria + are "mse" for the mean squared error, which is equal to variance + reduction as feature selection criterion and minimizes the L2 loss + using the mean of each terminal node, "friedman_mse", which uses mean + squared error with Friedman's improvement score for potential splits, + and "mae" for the mean absolute error, which minimizes the L1 loss + using the median of each terminal node. splitter : {"best", "random"}, default="best" The strategy used to choose the split at each node. Supported @@ -622,9 +979,6 @@ class DecisionTreeClassifier(ClassifierMixin, BaseDecisionTree): `ceil(min_samples_split * n_samples)` are the minimum number of samples for each split. - .. versionchanged:: 0.18 - Added float values for fractions. - min_samples_leaf : int or float, default=1 The minimum number of samples required to be at a leaf node. A split point at any depth will only be considered if it leaves at @@ -637,9 +991,6 @@ class DecisionTreeClassifier(ClassifierMixin, BaseDecisionTree): `ceil(min_samples_leaf * n_samples)` are the minimum number of samples for each node. - .. versionchanged:: 0.18 - Added float values for fractions. - min_weight_fraction_leaf : float, default=0.0 The minimum weighted fraction of the sum total of weights (of all the input samples) required to be at a leaf node. Samples have @@ -648,24 +999,20 @@ class DecisionTreeClassifier(ClassifierMixin, BaseDecisionTree): max_features : int, float or {"auto", "sqrt", "log2"}, default=None The number of features to consider when looking for the best split: - - If int, then consider `max_features` features at each split. - - If float, then `max_features` is a fraction and - `max(1, int(max_features * n_features_in_))` features are considered at - each split. - - If "auto", then `max_features=sqrt(n_features)`. - - If "sqrt", then `max_features=sqrt(n_features)`. - - If "log2", then `max_features=log2(n_features)`. - - If None, then `max_features=n_features`. - - .. deprecated:: 1.1 - The `"auto"` option was deprecated in 1.1 and will be removed - in 1.3. + - If int, then consider `max_features` features at each split. + - If float, then `max_features` is a fraction and + `int(max_features * n_features)` features are considered at each + split. + - If "auto", then `max_features=n_features`. + - If "sqrt", then `max_features=sqrt(n_features)`. + - If "log2", then `max_features=log2(n_features)`. + - If None, then `max_features=n_features`. Note: the search for a split does not stop until at least one valid partition of the node samples is found, even if it requires to effectively inspect more than ``max_features`` features. - random_state : int, RandomState instance or None, default=None + random_state : int, RandomState instance, default=None Controls the randomness of the estimator. The features are always randomly permuted at each split, even if ``splitter`` is set to ``"best"``. When ``max_features < n_features``, the algorithm will @@ -698,28 +1045,15 @@ class DecisionTreeClassifier(ClassifierMixin, BaseDecisionTree): ``N``, ``N_t``, ``N_t_R`` and ``N_t_L`` all refer to the weighted sum, if ``sample_weight`` is passed. - .. versionadded:: 0.19 - - class_weight : dict, list of dict or "balanced", default=None - Weights associated with classes in the form ``{class_label: weight}``. - If None, all classes are supposed to have weight one. For - multi-output problems, a list of dicts can be provided in the same - order as the columns of y. + min_impurity_split : float, (default=0) + Threshold for early stopping in tree growth. A node will split + if its impurity is above the threshold, otherwise it is a leaf. - Note that for multioutput (including multilabel) weights should be - defined for each class of every column in its own dict. For example, - for four-class multilabel classification weights should be - [{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead of - [{1:1}, {2:5}, {3:1}, {4:1}]. - - The "balanced" mode uses the values of y to automatically adjust - weights inversely proportional to class frequencies in the input data - as ``n_samples / (n_classes * np.bincount(y))`` - - For multi-output, the weights of each column of y will be multiplied. - - Note that these weights will be multiplied with sample_weight (passed - through the fit method) if sample_weight is specified. + .. deprecated:: 0.19 + ``min_impurity_split`` has been deprecated in favor of + ``min_impurity_decrease`` in 0.19. The default value of + ``min_impurity_split`` has changed from 1e-7 to 0 in 0.23 and it + will be removed in 0.25. Use ``min_impurity_decrease`` instead. ccp_alpha : non-negative float, default=0.0 Complexity parameter used for Minimal Cost-Complexity Pruning. The @@ -727,20 +1061,22 @@ class DecisionTreeClassifier(ClassifierMixin, BaseDecisionTree): ``ccp_alpha`` will be chosen. By default, no pruning is performed. See :ref:`minimal_cost_complexity_pruning` for details. - .. versionadded:: 0.22 + kernel : string, or tuple (string, params) or instance of the Kernel class, default="linear" + The type of kernel to use to compare the output data. Changing this + parameter changes also implicitely the nature of the Hilbert space + in which the output data are embedded. + The string describes the type of Kernel to use (defined in Kernel.py), + The optional params given are here to set particular parameters values + for the chosen kernel type. Attributes ---------- - classes_ : ndarray of shape (n_classes,) or list of ndarray - The classes labels (single output problem), - or a list of arrays of class labels (multi-output problem). - feature_importances_ : ndarray of shape (n_features,) - The impurity-based feature importances. + The feature importances. The higher, the more important the feature. - The importance of a feature is computed as the (normalized) - total reduction of the criterion brought by that feature. It is also - known as the Gini importance [4]_. + The importance of a feature is computed as the + (normalized) total reduction of the criterion brought + by that feature. It is also known as the Gini importance [4]_. Warning: impurity-based feature importances can be misleading for high cardinality features (many unique values). See @@ -749,34 +1085,20 @@ class DecisionTreeClassifier(ClassifierMixin, BaseDecisionTree): max_features_ : int The inferred value of max_features. - n_classes_ : int or list of int - The number of classes (for single output problems), - or a list containing the number of classes for each - output (for multi-output problems). - - n_features_in_ : int - Number of features seen during :term:`fit`. - - .. versionadded:: 0.24 - - feature_names_in_ : ndarray of shape (`n_features_in_`,) - Names of features seen during :term:`fit`. Defined only when `X` - has feature names that are all strings. - - .. versionadded:: 1.0 + n_features_ : int + The number of features when ``fit`` is performed. - n_outputs_ : int - The number of outputs when ``fit`` is performed. - - tree_ : Tree instance + tree_ : Tree The underlying Tree object. Please refer to ``help(sklearn.tree._tree.Tree)`` for attributes of Tree object and :ref:`sphx_glr_auto_examples_tree_plot_unveil_tree_structure.py` for basic usage of these attributes. - - See Also - -------- - DecisionTreeRegressor : A decision tree regressor. + + leaves_preds : array of shape (n_nodes, n_components), + where n_nodes is the number of nodes of the grown tree and + n_components is the number of values used to represent an output. + + This array stores for each leaf of the tree, the decoded predictions in Y. Notes ----- @@ -786,61 +1108,42 @@ class DecisionTreeClassifier(ClassifierMixin, BaseDecisionTree): reduce memory consumption, the complexity and size of the trees should be controlled by setting those parameter values. - The :meth:`predict` method operates using the :func:`numpy.argmax` - function on the outputs of :meth:`predict_proba`. This means that in - case the highest predicted probabilities are tied, the classifier will - predict the tied class with the lowest index in :term:`classes_`. - References ---------- - .. [1] https://en.wikipedia.org/wiki/Decision_tree_learning - - .. [2] L. Breiman, J. Friedman, R. Olshen, and C. Stone, "Classification - and Regression Trees", Wadsworth, Belmont, CA, 1984. - - .. [3] T. Hastie, R. Tibshirani and J. Friedman. "Elements of Statistical - Learning", Springer, 2009. - - .. [4] L. Breiman, and A. Cutler, "Random Forests", - https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm + .. [1] Pierre Geurts, Louis Wehenkel, Florence d’Alché-Buc. + "Kernelizing the output of tree-based methods." + Proc. of the 23rd International Conference on Machine Learning, + 2006, United States. pp.345–352,￿10.1145/1143844.1143888￿. Examples -------- - >>> from sklearn.datasets import load_iris + >>> from sklearn.datasets import load_diabetes >>> from sklearn.model_selection import cross_val_score - >>> from sklearn.tree import DecisionTreeClassifier - >>> clf = DecisionTreeClassifier(random_state=0) - >>> iris = load_iris() - >>> cross_val_score(clf, iris.data, iris.target, cv=10) - ... # doctest: +SKIP + >>> from ??? import OK3Regressor + >>> X, y = load_diabetes(return_X_y=True) + >>> regressor = OK3Regressor(random_state=0) + >>> cross_val_score(regressor, X, y, cv=10) + ... # doctest: +SKIP ... - array([ 1. , 0.93..., 0.86..., 0.93..., 0.93..., - 0.93..., 0.93..., 1. , 0.93..., 1. ]) + array([-0.39..., -0.46..., 0.02..., 0.06..., -0.50..., + 0.16..., 0.11..., -0.73..., -0.30..., -0.00...]) """ - - _parameter_constraints: dict = { - **BaseDecisionTree._parameter_constraints, - "criterion": [StrOptions({"gini", "entropy", "log_loss"}), Hidden(Criterion)], - "class_weight": [dict, list, StrOptions({"balanced"}), None], - } - - def __init__( - self, - *, - criterion="gini", - splitter="best", - max_depth=None, - min_samples_split=2, - min_samples_leaf=1, - min_weight_fraction_leaf=0.0, - max_features=None, - random_state=None, - max_leaf_nodes=None, - min_impurity_decrease=0.0, - class_weight=None, - ccp_alpha=0.0, - ): + @_deprecate_positional_args + def __init__(self, *, + criterion="mse", + splitter="best", + max_depth=None, + min_samples_split=2, + min_samples_leaf=1, + min_weight_fraction_leaf=0., + max_features=None, + random_state=None, + max_leaf_nodes=None, + min_impurity_decrease=0., + min_impurity_split=None, + ccp_alpha=0.0, + kernel="linear"): super().__init__( criterion=criterion, splitter=splitter, @@ -850,14 +1153,15 @@ def __init__( min_weight_fraction_leaf=min_weight_fraction_leaf, max_features=max_features, max_leaf_nodes=max_leaf_nodes, - class_weight=class_weight, random_state=random_state, min_impurity_decrease=min_impurity_decrease, - ccp_alpha=ccp_alpha, - ) + min_impurity_split=min_impurity_split, + ccp_alpha=ccp_alpha, + kernel=kernel) - def fit(self, X, y, sample_weight=None, check_input=True): - """Build a decision tree classifier from the training set (X, y). + def fit(self, X, y, sample_weight=None, check_input=True, + X_idx_sorted="deprecated", kernel=None, in_ensemble=False, Gram_y=None): + """Build a decision tree regressor from the training set (X, y). Parameters ---------- @@ -867,138 +1171,69 @@ def fit(self, X, y, sample_weight=None, check_input=True): to a sparse ``csc_matrix``. y : array-like of shape (n_samples,) or (n_samples, n_outputs) - The target values (class labels) as integers or strings. + The target values (real numbers). Use ``dtype=np.float64`` and + ``order='C'`` for maximum efficiency. sample_weight : array-like of shape (n_samples,), default=None Sample weights. If None, then samples are equally weighted. Splits that would create child nodes with net zero or negative weight are - ignored while searching for a split in each node. Splits are also - ignored if they would result in any single class carrying a - negative weight in either child node. + ignored while searching for a split in each node. check_input : bool, default=True Allow to bypass several input checking. - Don't use this parameter unless you know what you're doing. - + Don't use this parameter unless you know what you do. + + X_idx_sorted : deprecated, default="deprecated" + This parameter is deprecated and has no effect. + It will be removed in v0.26. + + kernel : string, or tuple (string, params) or instance of the Kernel class, default="linear" + The type of kernel to use to compare the output data. Changing this + parameter changes also implicitely the nature of the Hilbert space + in which the output data are embedded. + The string describes the type of Kernel to use (defined in Kernel.py), + The optional params given are here to set particular parameters values + for the chosen kernel type. + This parameter can be set also here in the fit method instead of __init__. + Returns ------- - self : DecisionTreeClassifier + self : OK3Regressor Fitted estimator. """ super().fit( - X, - y, + X, y, sample_weight=sample_weight, check_input=check_input, - ) + X_idx_sorted=X_idx_sorted, + kernel=kernel, + in_ensemble=in_ensemble, + Gram_y=Gram_y) return self - def predict_proba(self, X, check_input=True): - """Predict class probabilities of the input samples X. - - The predicted class probability is the fraction of samples of the same - class in a leaf. - - Parameters - ---------- - X : {array-like, sparse matrix} of shape (n_samples, n_features) - The input samples. Internally, it will be converted to - ``dtype=np.float32`` and if a sparse matrix is provided - to a sparse ``csr_matrix``. - - check_input : bool, default=True - Allow to bypass several input checking. - Don't use this parameter unless you know what you're doing. - - Returns - ------- - proba : ndarray of shape (n_samples, n_classes) or list of n_outputs \ - such arrays if n_outputs > 1 - The class probabilities of the input samples. The order of the - classes corresponds to that in the attribute :term:`classes_`. - """ - check_is_fitted(self) - X = self._validate_X_predict(X, check_input) - proba = self.tree_.predict(X) - - if self.n_outputs_ == 1: - proba = proba[:, : self.n_classes_] - normalizer = proba.sum(axis=1)[:, np.newaxis] - normalizer[normalizer == 0.0] = 1.0 - proba /= normalizer - - return proba - - else: - all_proba = [] - - for k in range(self.n_outputs_): - proba_k = proba[:, k, : self.n_classes_[k]] - normalizer = proba_k.sum(axis=1)[:, np.newaxis] - normalizer[normalizer == 0.0] = 1.0 - proba_k /= normalizer - all_proba.append(proba_k) - - return all_proba - - def predict_log_proba(self, X): - """Predict class log-probabilities of the input samples X. - - Parameters - ---------- - X : {array-like, sparse matrix} of shape (n_samples, n_features) - The input samples. Internally, it will be converted to - ``dtype=np.float32`` and if a sparse matrix is provided - to a sparse ``csr_matrix``. - - Returns - ------- - proba : ndarray of shape (n_samples, n_classes) or list of n_outputs \ - such arrays if n_outputs > 1 - The class log-probabilities of the input samples. The order of the - classes corresponds to that in the attribute :term:`classes_`. - """ - proba = self.predict_proba(X) - - if self.n_outputs_ == 1: - return np.log(proba) - - else: - for k in range(self.n_outputs_): - proba[k] = np.log(proba[k]) - - return proba - - def _more_tags(self): - return {"multilabel": True} +class ExtraOK3Regressor(OK3Regressor): + """An extremely randomized tree regressor. -class DecisionTreeRegressor(RegressorMixin, BaseDecisionTree): - """A decision tree regressor. + Extra-trees differ from classic decision trees in the way they are built. + When looking for the best split to separate the samples of a node into two + groups, random splits are drawn for each of the `max_features` randomly + selected features and the best split among those is chosen. When + `max_features` is set 1, this amounts to building a totally random + decision tree. - Read more in the :ref:`User Guide `. + Warning: Extra-trees should only be used within ensemble methods. Parameters ---------- - criterion : {"squared_error", "friedman_mse", "absolute_error", \ - "poisson"}, default="squared_error" + criterion : {"mse", "friedman_mse", "mae"}, default="mse" The function to measure the quality of a split. Supported criteria - are "squared_error" for the mean squared error, which is equal to - variance reduction as feature selection criterion and minimizes the L2 - loss using the mean of each terminal node, "friedman_mse", which uses - mean squared error with Friedman's improvement score for potential - splits, "absolute_error" for the mean absolute error, which minimizes - the L1 loss using the median of each terminal node, and "poisson" which - uses reduction in Poisson deviance to find splits. + are "mse" for the mean squared error, which is equal to variance + reduction as feature selection criterion, and "mae" for the mean + absolute error. - .. versionadded:: 0.18 - Mean Absolute Error (MAE) criterion. - - .. versionadded:: 0.24 - Poisson deviance criterion. - - splitter : {"best", "random"}, default="best" + splitter : {"random", "best"}, default="random" The strategy used to choose the split at each node. Supported strategies are "best" to choose the best split and "random" to choose the best random split. @@ -1016,9 +1251,6 @@ class DecisionTreeRegressor(RegressorMixin, BaseDecisionTree): `ceil(min_samples_split * n_samples)` are the minimum number of samples for each split. - .. versionchanged:: 0.18 - Added float values for fractions. - min_samples_leaf : int or float, default=1 The minimum number of samples required to be at a leaf node. A split point at any depth will only be considered if it leaves at @@ -1031,51 +1263,31 @@ class DecisionTreeRegressor(RegressorMixin, BaseDecisionTree): `ceil(min_samples_leaf * n_samples)` are the minimum number of samples for each node. - .. versionchanged:: 0.18 - Added float values for fractions. - min_weight_fraction_leaf : float, default=0.0 The minimum weighted fraction of the sum total of weights (of all the input samples) required to be at a leaf node. Samples have equal weight when sample_weight is not provided. - max_features : int, float or {"auto", "sqrt", "log2"}, default=None + max_features : int, float, {"auto", "sqrt", "log2"} or None, default="auto" The number of features to consider when looking for the best split: - If int, then consider `max_features` features at each split. - If float, then `max_features` is a fraction and - `max(1, int(max_features * n_features_in_))` features are considered at each + `int(max_features * n_features)` features are considered at each split. - If "auto", then `max_features=n_features`. - If "sqrt", then `max_features=sqrt(n_features)`. - If "log2", then `max_features=log2(n_features)`. - If None, then `max_features=n_features`. - .. deprecated:: 1.1 - The `"auto"` option was deprecated in 1.1 and will be removed - in 1.3. - Note: the search for a split does not stop until at least one valid partition of the node samples is found, even if it requires to effectively inspect more than ``max_features`` features. - random_state : int, RandomState instance or None, default=None - Controls the randomness of the estimator. The features are always - randomly permuted at each split, even if ``splitter`` is set to - ``"best"``. When ``max_features < n_features``, the algorithm will - select ``max_features`` at random at each split before finding the best - split among them. But the best found split may vary across different - runs, even if ``max_features=n_features``. That is the case, if the - improvement of the criterion is identical for several splits and one - split has to be selected at random. To obtain a deterministic behaviour - during fitting, ``random_state`` has to be fixed to an integer. + random_state : int, RandomState instance, default=None + Used to pick randomly the `max_features` used at each split. See :term:`Glossary ` for details. - max_leaf_nodes : int, default=None - Grow a tree with ``max_leaf_nodes`` in best-first fashion. - Best nodes are defined as relative reduction in impurity. - If None then unlimited number of leaf nodes. - min_impurity_decrease : float, default=0.0 A node will be split if this split induces a decrease of the impurity greater than or equal to this value. @@ -1092,47 +1304,52 @@ class DecisionTreeRegressor(RegressorMixin, BaseDecisionTree): ``N``, ``N_t``, ``N_t_R`` and ``N_t_L`` all refer to the weighted sum, if ``sample_weight`` is passed. - .. versionadded:: 0.19 + min_impurity_split : float, (default=0) + Threshold for early stopping in tree growth. A node will split + if its impurity is above the threshold, otherwise it is a leaf. + + .. deprecated:: 0.19 + ``min_impurity_split`` has been deprecated in favor of + ``min_impurity_decrease`` in 0.19. The default value of + ``min_impurity_split`` has changed from 1e-7 to 0 in 0.23 and it + will be removed in 0.25. Use ``min_impurity_decrease`` instead. + + max_leaf_nodes : int, default=None + Grow a tree with ``max_leaf_nodes`` in best-first fashion. + Best nodes are defined as relative reduction in impurity. + If None then unlimited number of leaf nodes. ccp_alpha : non-negative float, default=0.0 Complexity parameter used for Minimal Cost-Complexity Pruning. The subtree with the largest cost complexity that is smaller than ``ccp_alpha`` will be chosen. By default, no pruning is performed. See :ref:`minimal_cost_complexity_pruning` for details. - - .. versionadded:: 0.22 + + kernel : string, or tuple (string, params) or instance of the Kernel class, default="linear" + The type of kernel to use to compare the output data. Changing this + parameter changes also implicitely the nature of the Hilbert space + in which the output data are embedded. + The string describes the type of Kernel to use (defined in Kernel.py), + The optional params given are here to set particular parameters values + for the chosen kernel type. Attributes ---------- - feature_importances_ : ndarray of shape (n_features,) - The feature importances. - The higher, the more important the feature. - The importance of a feature is computed as the - (normalized) total reduction of the criterion brought - by that feature. It is also known as the Gini importance [4]_. - - Warning: impurity-based feature importances can be misleading for - high cardinality features (many unique values). See - :func:`sklearn.inspection.permutation_importance` as an alternative. - max_features_ : int The inferred value of max_features. - n_features_in_ : int - Number of features seen during :term:`fit`. - - .. versionadded:: 0.24 + n_features_ : int + The number of features when ``fit`` is performed. - feature_names_in_ : ndarray of shape (`n_features_in_`,) - Names of features seen during :term:`fit`. Defined only when `X` - has feature names that are all strings. - - .. versionadded:: 1.0 + feature_importances_ : ndarray of shape (n_features,) + Return impurity-based feature importances (the higher, the more + important the feature). - n_outputs_ : int - The number of outputs when ``fit`` is performed. + Warning: impurity-based feature importances can be misleading for + high cardinality features (many unique values). See + :func:`sklearn.inspection.permutation_importance` as an alternative. - tree_ : Tree instance + tree_ : Tree The underlying Tree object. Please refer to ``help(sklearn.tree._tree.Tree)`` for attributes of Tree object and :ref:`sphx_glr_auto_examples_tree_plot_unveil_tree_structure.py` @@ -1140,7 +1357,9 @@ class DecisionTreeRegressor(RegressorMixin, BaseDecisionTree): See Also -------- - DecisionTreeClassifier : A decision tree classifier. + ExtraTreeClassifier : An extremely randomized tree classifier. + sklearn.ensemble.ExtraTreesClassifier : An extra-trees classifier. + sklearn.ensemble.ExtraTreesRegressor : An extra-trees regressor. Notes ----- @@ -1153,582 +1372,15 @@ class DecisionTreeRegressor(RegressorMixin, BaseDecisionTree): References ---------- - .. [1] https://en.wikipedia.org/wiki/Decision_tree_learning - - .. [2] L. Breiman, J. Friedman, R. Olshen, and C. Stone, "Classification - and Regression Trees", Wadsworth, Belmont, CA, 1984. - - .. [3] T. Hastie, R. Tibshirani and J. Friedman. "Elements of Statistical - Learning", Springer, 2009. - - .. [4] L. Breiman, and A. Cutler, "Random Forests", - https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm + .. [1] P. Geurts, D. Ernst., and L. Wehenkel, "Extremely randomized trees", + Machine Learning, 63(1), 3-42, 2006. Examples -------- >>> from sklearn.datasets import load_diabetes - >>> from sklearn.model_selection import cross_val_score - >>> from sklearn.tree import DecisionTreeRegressor - >>> X, y = load_diabetes(return_X_y=True) - >>> regressor = DecisionTreeRegressor(random_state=0) - >>> cross_val_score(regressor, X, y, cv=10) - ... # doctest: +SKIP - ... - array([-0.39..., -0.46..., 0.02..., 0.06..., -0.50..., - 0.16..., 0.11..., -0.73..., -0.30..., -0.00...]) - """ - - _parameter_constraints: dict = { - **BaseDecisionTree._parameter_constraints, - "criterion": [ - StrOptions({"squared_error", "friedman_mse", "absolute_error", "poisson"}), - Hidden(Criterion), - ], - } - - def __init__( - self, - *, - criterion="squared_error", - splitter="best", - max_depth=None, - min_samples_split=2, - min_samples_leaf=1, - min_weight_fraction_leaf=0.0, - max_features=None, - random_state=None, - max_leaf_nodes=None, - min_impurity_decrease=0.0, - ccp_alpha=0.0, - ): - super().__init__( - criterion=criterion, - splitter=splitter, - max_depth=max_depth, - min_samples_split=min_samples_split, - min_samples_leaf=min_samples_leaf, - min_weight_fraction_leaf=min_weight_fraction_leaf, - max_features=max_features, - max_leaf_nodes=max_leaf_nodes, - random_state=random_state, - min_impurity_decrease=min_impurity_decrease, - ccp_alpha=ccp_alpha, - ) - - def fit(self, X, y, sample_weight=None, check_input=True): - """Build a decision tree regressor from the training set (X, y). - - Parameters - ---------- - X : {array-like, sparse matrix} of shape (n_samples, n_features) - The training input samples. Internally, it will be converted to - ``dtype=np.float32`` and if a sparse matrix is provided - to a sparse ``csc_matrix``. - - y : array-like of shape (n_samples,) or (n_samples, n_outputs) - The target values (real numbers). Use ``dtype=np.float64`` and - ``order='C'`` for maximum efficiency. - - sample_weight : array-like of shape (n_samples,), default=None - Sample weights. If None, then samples are equally weighted. Splits - that would create child nodes with net zero or negative weight are - ignored while searching for a split in each node. - - check_input : bool, default=True - Allow to bypass several input checking. - Don't use this parameter unless you know what you're doing. - - Returns - ------- - self : DecisionTreeRegressor - Fitted estimator. - """ - - super().fit( - X, - y, - sample_weight=sample_weight, - check_input=check_input, - ) - return self - - def _compute_partial_dependence_recursion(self, grid, target_features): - """Fast partial dependence computation. - - Parameters - ---------- - grid : ndarray of shape (n_samples, n_target_features) - The grid points on which the partial dependence should be - evaluated. - target_features : ndarray of shape (n_target_features) - The set of target features for which the partial dependence - should be evaluated. - - Returns - ------- - averaged_predictions : ndarray of shape (n_samples,) - The value of the partial dependence function on each grid point. - """ - grid = np.asarray(grid, dtype=DTYPE, order="C") - averaged_predictions = np.zeros( - shape=grid.shape[0], dtype=np.float64, order="C" - ) - - self.tree_.compute_partial_dependence( - grid, target_features, averaged_predictions - ) - return averaged_predictions - - -class ExtraTreeClassifier(DecisionTreeClassifier): - """An extremely randomized tree classifier. - - Extra-trees differ from classic decision trees in the way they are built. - When looking for the best split to separate the samples of a node into two - groups, random splits are drawn for each of the `max_features` randomly - selected features and the best split among those is chosen. When - `max_features` is set 1, this amounts to building a totally random - decision tree. - - Warning: Extra-trees should only be used within ensemble methods. - - Read more in the :ref:`User Guide `. - - Parameters - ---------- - criterion : {"gini", "entropy", "log_loss"}, default="gini" - The function to measure the quality of a split. Supported criteria are - "gini" for the Gini impurity and "log_loss" and "entropy" both for the - Shannon information gain, see :ref:`tree_mathematical_formulation`. - - splitter : {"random", "best"}, default="random" - The strategy used to choose the split at each node. Supported - strategies are "best" to choose the best split and "random" to choose - the best random split. - - max_depth : int, default=None - The maximum depth of the tree. If None, then nodes are expanded until - all leaves are pure or until all leaves contain less than - min_samples_split samples. - - min_samples_split : int or float, default=2 - The minimum number of samples required to split an internal node: - - - If int, then consider `min_samples_split` as the minimum number. - - If float, then `min_samples_split` is a fraction and - `ceil(min_samples_split * n_samples)` are the minimum - number of samples for each split. - - .. versionchanged:: 0.18 - Added float values for fractions. - - min_samples_leaf : int or float, default=1 - The minimum number of samples required to be at a leaf node. - A split point at any depth will only be considered if it leaves at - least ``min_samples_leaf`` training samples in each of the left and - right branches. This may have the effect of smoothing the model, - especially in regression. - - - If int, then consider `min_samples_leaf` as the minimum number. - - If float, then `min_samples_leaf` is a fraction and - `ceil(min_samples_leaf * n_samples)` are the minimum - number of samples for each node. - - .. versionchanged:: 0.18 - Added float values for fractions. - - min_weight_fraction_leaf : float, default=0.0 - The minimum weighted fraction of the sum total of weights (of all - the input samples) required to be at a leaf node. Samples have - equal weight when sample_weight is not provided. - - max_features : int, float, {"auto", "sqrt", "log2"} or None, default="sqrt" - The number of features to consider when looking for the best split: - - - If int, then consider `max_features` features at each split. - - If float, then `max_features` is a fraction and - `max(1, int(max_features * n_features_in_))` features are considered at - each split. - - If "auto", then `max_features=sqrt(n_features)`. - - If "sqrt", then `max_features=sqrt(n_features)`. - - If "log2", then `max_features=log2(n_features)`. - - If None, then `max_features=n_features`. - - .. versionchanged:: 1.1 - The default of `max_features` changed from `"auto"` to `"sqrt"`. - - .. deprecated:: 1.1 - The `"auto"` option was deprecated in 1.1 and will be removed - in 1.3. - - Note: the search for a split does not stop until at least one - valid partition of the node samples is found, even if it requires to - effectively inspect more than ``max_features`` features. - - random_state : int, RandomState instance or None, default=None - Used to pick randomly the `max_features` used at each split. - See :term:`Glossary ` for details. - - max_leaf_nodes : int, default=None - Grow a tree with ``max_leaf_nodes`` in best-first fashion. - Best nodes are defined as relative reduction in impurity. - If None then unlimited number of leaf nodes. - - min_impurity_decrease : float, default=0.0 - A node will be split if this split induces a decrease of the impurity - greater than or equal to this value. - - The weighted impurity decrease equation is the following:: - - N_t / N * (impurity - N_t_R / N_t * right_impurity - - N_t_L / N_t * left_impurity) - - where ``N`` is the total number of samples, ``N_t`` is the number of - samples at the current node, ``N_t_L`` is the number of samples in the - left child, and ``N_t_R`` is the number of samples in the right child. - - ``N``, ``N_t``, ``N_t_R`` and ``N_t_L`` all refer to the weighted sum, - if ``sample_weight`` is passed. - - .. versionadded:: 0.19 - - class_weight : dict, list of dict or "balanced", default=None - Weights associated with classes in the form ``{class_label: weight}``. - If None, all classes are supposed to have weight one. For - multi-output problems, a list of dicts can be provided in the same - order as the columns of y. - - Note that for multioutput (including multilabel) weights should be - defined for each class of every column in its own dict. For example, - for four-class multilabel classification weights should be - [{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead of - [{1:1}, {2:5}, {3:1}, {4:1}]. - - The "balanced" mode uses the values of y to automatically adjust - weights inversely proportional to class frequencies in the input data - as ``n_samples / (n_classes * np.bincount(y))`` - - For multi-output, the weights of each column of y will be multiplied. - - Note that these weights will be multiplied with sample_weight (passed - through the fit method) if sample_weight is specified. - - ccp_alpha : non-negative float, default=0.0 - Complexity parameter used for Minimal Cost-Complexity Pruning. The - subtree with the largest cost complexity that is smaller than - ``ccp_alpha`` will be chosen. By default, no pruning is performed. See - :ref:`minimal_cost_complexity_pruning` for details. - - .. versionadded:: 0.22 - - Attributes - ---------- - classes_ : ndarray of shape (n_classes,) or list of ndarray - The classes labels (single output problem), - or a list of arrays of class labels (multi-output problem). - - max_features_ : int - The inferred value of max_features. - - n_classes_ : int or list of int - The number of classes (for single output problems), - or a list containing the number of classes for each - output (for multi-output problems). - - feature_importances_ : ndarray of shape (n_features,) - The impurity-based feature importances. - The higher, the more important the feature. - The importance of a feature is computed as the (normalized) - total reduction of the criterion brought by that feature. It is also - known as the Gini importance. - - Warning: impurity-based feature importances can be misleading for - high cardinality features (many unique values). See - :func:`sklearn.inspection.permutation_importance` as an alternative. - - n_features_in_ : int - Number of features seen during :term:`fit`. - - .. versionadded:: 0.24 - - feature_names_in_ : ndarray of shape (`n_features_in_`,) - Names of features seen during :term:`fit`. Defined only when `X` - has feature names that are all strings. - - .. versionadded:: 1.0 - - n_outputs_ : int - The number of outputs when ``fit`` is performed. - - tree_ : Tree instance - The underlying Tree object. Please refer to - ``help(sklearn.tree._tree.Tree)`` for attributes of Tree object and - :ref:`sphx_glr_auto_examples_tree_plot_unveil_tree_structure.py` - for basic usage of these attributes. - - See Also - -------- - ExtraTreeRegressor : An extremely randomized tree regressor. - sklearn.ensemble.ExtraTreesClassifier : An extra-trees classifier. - sklearn.ensemble.ExtraTreesRegressor : An extra-trees regressor. - sklearn.ensemble.RandomForestClassifier : A random forest classifier. - sklearn.ensemble.RandomForestRegressor : A random forest regressor. - sklearn.ensemble.RandomTreesEmbedding : An ensemble of - totally random trees. - - Notes - ----- - The default values for the parameters controlling the size of the trees - (e.g. ``max_depth``, ``min_samples_leaf``, etc.) lead to fully grown and - unpruned trees which can potentially be very large on some data sets. To - reduce memory consumption, the complexity and size of the trees should be - controlled by setting those parameter values. - - References - ---------- - - .. [1] P. Geurts, D. Ernst., and L. Wehenkel, "Extremely randomized trees", - Machine Learning, 63(1), 3-42, 2006. - - Examples - -------- - >>> from sklearn.datasets import load_iris - >>> from sklearn.model_selection import train_test_split - >>> from sklearn.ensemble import BaggingClassifier - >>> from sklearn.tree import ExtraTreeClassifier - >>> X, y = load_iris(return_X_y=True) - >>> X_train, X_test, y_train, y_test = train_test_split( - ... X, y, random_state=0) - >>> extra_tree = ExtraTreeClassifier(random_state=0) - >>> cls = BaggingClassifier(extra_tree, random_state=0).fit( - ... X_train, y_train) - >>> cls.score(X_test, y_test) - 0.8947... - """ - - def __init__( - self, - *, - criterion="gini", - splitter="random", - max_depth=None, - min_samples_split=2, - min_samples_leaf=1, - min_weight_fraction_leaf=0.0, - max_features="sqrt", - random_state=None, - max_leaf_nodes=None, - min_impurity_decrease=0.0, - class_weight=None, - ccp_alpha=0.0, - ): - super().__init__( - criterion=criterion, - splitter=splitter, - max_depth=max_depth, - min_samples_split=min_samples_split, - min_samples_leaf=min_samples_leaf, - min_weight_fraction_leaf=min_weight_fraction_leaf, - max_features=max_features, - max_leaf_nodes=max_leaf_nodes, - class_weight=class_weight, - min_impurity_decrease=min_impurity_decrease, - random_state=random_state, - ccp_alpha=ccp_alpha, - ) - - -class ExtraTreeRegressor(DecisionTreeRegressor): - """An extremely randomized tree regressor. - - Extra-trees differ from classic decision trees in the way they are built. - When looking for the best split to separate the samples of a node into two - groups, random splits are drawn for each of the `max_features` randomly - selected features and the best split among those is chosen. When - `max_features` is set 1, this amounts to building a totally random - decision tree. - - Warning: Extra-trees should only be used within ensemble methods. - - Read more in the :ref:`User Guide `. - - Parameters - ---------- - criterion : {"squared_error", "friedman_mse", "absolute_error", "poisson"}, \ - default="squared_error" - The function to measure the quality of a split. Supported criteria - are "squared_error" for the mean squared error, which is equal to - variance reduction as feature selection criterion and minimizes the L2 - loss using the mean of each terminal node, "friedman_mse", which uses - mean squared error with Friedman's improvement score for potential - splits, "absolute_error" for the mean absolute error, which minimizes - the L1 loss using the median of each terminal node, and "poisson" which - uses reduction in Poisson deviance to find splits. - - .. versionadded:: 0.18 - Mean Absolute Error (MAE) criterion. - - .. versionadded:: 0.24 - Poisson deviance criterion. - - splitter : {"random", "best"}, default="random" - The strategy used to choose the split at each node. Supported - strategies are "best" to choose the best split and "random" to choose - the best random split. - - max_depth : int, default=None - The maximum depth of the tree. If None, then nodes are expanded until - all leaves are pure or until all leaves contain less than - min_samples_split samples. - - min_samples_split : int or float, default=2 - The minimum number of samples required to split an internal node: - - - If int, then consider `min_samples_split` as the minimum number. - - If float, then `min_samples_split` is a fraction and - `ceil(min_samples_split * n_samples)` are the minimum - number of samples for each split. - - .. versionchanged:: 0.18 - Added float values for fractions. - - min_samples_leaf : int or float, default=1 - The minimum number of samples required to be at a leaf node. - A split point at any depth will only be considered if it leaves at - least ``min_samples_leaf`` training samples in each of the left and - right branches. This may have the effect of smoothing the model, - especially in regression. - - - If int, then consider `min_samples_leaf` as the minimum number. - - If float, then `min_samples_leaf` is a fraction and - `ceil(min_samples_leaf * n_samples)` are the minimum - number of samples for each node. - - .. versionchanged:: 0.18 - Added float values for fractions. - - min_weight_fraction_leaf : float, default=0.0 - The minimum weighted fraction of the sum total of weights (of all - the input samples) required to be at a leaf node. Samples have - equal weight when sample_weight is not provided. - - max_features : int, float, {"auto", "sqrt", "log2"} or None, default=1.0 - The number of features to consider when looking for the best split: - - - If int, then consider `max_features` features at each split. - - If float, then `max_features` is a fraction and - `max(1, int(max_features * n_features_in_))` features are considered at each - split. - - If "auto", then `max_features=n_features`. - - If "sqrt", then `max_features=sqrt(n_features)`. - - If "log2", then `max_features=log2(n_features)`. - - If None, then `max_features=n_features`. - - .. versionchanged:: 1.1 - The default of `max_features` changed from `"auto"` to `1.0`. - - .. deprecated:: 1.1 - The `"auto"` option was deprecated in 1.1 and will be removed - in 1.3. - - Note: the search for a split does not stop until at least one - valid partition of the node samples is found, even if it requires to - effectively inspect more than ``max_features`` features. - - random_state : int, RandomState instance or None, default=None - Used to pick randomly the `max_features` used at each split. - See :term:`Glossary ` for details. - - min_impurity_decrease : float, default=0.0 - A node will be split if this split induces a decrease of the impurity - greater than or equal to this value. - - The weighted impurity decrease equation is the following:: - - N_t / N * (impurity - N_t_R / N_t * right_impurity - - N_t_L / N_t * left_impurity) - - where ``N`` is the total number of samples, ``N_t`` is the number of - samples at the current node, ``N_t_L`` is the number of samples in the - left child, and ``N_t_R`` is the number of samples in the right child. - - ``N``, ``N_t``, ``N_t_R`` and ``N_t_L`` all refer to the weighted sum, - if ``sample_weight`` is passed. - - .. versionadded:: 0.19 - - max_leaf_nodes : int, default=None - Grow a tree with ``max_leaf_nodes`` in best-first fashion. - Best nodes are defined as relative reduction in impurity. - If None then unlimited number of leaf nodes. - - ccp_alpha : non-negative float, default=0.0 - Complexity parameter used for Minimal Cost-Complexity Pruning. The - subtree with the largest cost complexity that is smaller than - ``ccp_alpha`` will be chosen. By default, no pruning is performed. See - :ref:`minimal_cost_complexity_pruning` for details. - - .. versionadded:: 0.22 - - Attributes - ---------- - max_features_ : int - The inferred value of max_features. - - n_features_in_ : int - Number of features seen during :term:`fit`. - - .. versionadded:: 0.24 - - feature_names_in_ : ndarray of shape (`n_features_in_`,) - Names of features seen during :term:`fit`. Defined only when `X` - has feature names that are all strings. - - .. versionadded:: 1.0 - - feature_importances_ : ndarray of shape (n_features,) - Return impurity-based feature importances (the higher, the more - important the feature). - - Warning: impurity-based feature importances can be misleading for - high cardinality features (many unique values). See - :func:`sklearn.inspection.permutation_importance` as an alternative. - - n_outputs_ : int - The number of outputs when ``fit`` is performed. - - tree_ : Tree instance - The underlying Tree object. Please refer to - ``help(sklearn.tree._tree.Tree)`` for attributes of Tree object and - :ref:`sphx_glr_auto_examples_tree_plot_unveil_tree_structure.py` - for basic usage of these attributes. - - See Also - -------- - ExtraTreeClassifier : An extremely randomized tree classifier. - sklearn.ensemble.ExtraTreesClassifier : An extra-trees classifier. - sklearn.ensemble.ExtraTreesRegressor : An extra-trees regressor. - - Notes - ----- - The default values for the parameters controlling the size of the trees - (e.g. ``max_depth``, ``min_samples_leaf``, etc.) lead to fully grown and - unpruned trees which can potentially be very large on some data sets. To - reduce memory consumption, the complexity and size of the trees should be - controlled by setting those parameter values. - - References - ---------- - - .. [1] P. Geurts, D. Ernst., and L. Wehenkel, "Extremely randomized trees", - Machine Learning, 63(1), 3-42, 2006. - - Examples - -------- - >>> from sklearn.datasets import load_diabetes - >>> from sklearn.model_selection import train_test_split - >>> from sklearn.ensemble import BaggingRegressor - >>> from sklearn.tree import ExtraTreeRegressor + >>> from sklearn.model_selection import train_test_split + >>> from sklearn.ensemble import BaggingRegressor + >>> from sklearn.tree import ExtraTreeRegressor >>> X, y = load_diabetes(return_X_y=True) >>> X_train, X_test, y_train, y_test = train_test_split( ... X, y, random_state=0) @@ -1738,22 +1390,21 @@ class ExtraTreeRegressor(DecisionTreeRegressor): >>> reg.score(X_test, y_test) 0.33... """ - - def __init__( - self, - *, - criterion="squared_error", - splitter="random", - max_depth=None, - min_samples_split=2, - min_samples_leaf=1, - min_weight_fraction_leaf=0.0, - max_features=1.0, - random_state=None, - min_impurity_decrease=0.0, - max_leaf_nodes=None, - ccp_alpha=0.0, - ): + @_deprecate_positional_args + def __init__(self, *, + criterion="mse", + splitter="random", + max_depth=None, + min_samples_split=2, + min_samples_leaf=1, + min_weight_fraction_leaf=0., + max_features="auto", + random_state=None, + min_impurity_decrease=0., + min_impurity_split=None, + max_leaf_nodes=None, + ccp_alpha=0.0, + kernel="linear"): super().__init__( criterion=criterion, splitter=splitter, @@ -1764,6 +1415,7 @@ def __init__( max_features=max_features, max_leaf_nodes=max_leaf_nodes, min_impurity_decrease=min_impurity_decrease, + min_impurity_split=min_impurity_split, random_state=random_state, - ccp_alpha=ccp_alpha, - ) + ccp_alpha=ccp_alpha, + kernel=kernel) diff --git 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__has_cpp_attribute(fallthrough) + #define CYTHON_FALLTHROUGH [[fallthrough]] + #elif __has_cpp_attribute(clang::fallthrough) + #define CYTHON_FALLTHROUGH [[clang::fallthrough]] + #elif __has_cpp_attribute(gnu::fallthrough) + #define CYTHON_FALLTHROUGH [[gnu::fallthrough]] + #endif + #endif + #ifndef CYTHON_FALLTHROUGH + #if __has_attribute(fallthrough) + #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) + #else + #define CYTHON_FALLTHROUGH + #endif + #endif + #if defined(__clang__ ) && defined(__apple_build_version__) + #if __apple_build_version__ < 7000000 + #undef CYTHON_FALLTHROUGH + #define CYTHON_FALLTHROUGH + #endif + #endif +#endif + +#ifndef CYTHON_INLINE + #if defined(__clang__) + #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) + #elif defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_INLINE inline + #else + #define CYTHON_INLINE + #endif +#endif + +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) + #define Py_OptimizeFlag 0 +#endif +#define __PYX_BUILD_PY_SSIZE_T "n" +#define CYTHON_FORMAT_SSIZE_T "z" +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) + #define __Pyx_DefaultClassType PyClass_Type +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#endif + #define __Pyx_DefaultClassType PyType_Type +#endif +#ifndef Py_TPFLAGS_CHECKTYPES + #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif +#ifndef Py_TPFLAGS_HAVE_FINALIZE + #define Py_TPFLAGS_HAVE_FINALIZE 0 +#endif +#ifndef METH_STACKLESS + #define METH_STACKLESS 0 +#endif +#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) + #ifndef METH_FASTCALL + #define METH_FASTCALL 0x80 + #endif + typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); + typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, + Py_ssize_t nargs, PyObject *kwnames); +#else + #define __Pyx_PyCFunctionFast _PyCFunctionFast + #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords +#endif +#if CYTHON_FAST_PYCCALL +#define __Pyx_PyFastCFunction_Check(func)\ + ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) +#else +#define __Pyx_PyFastCFunction_Check(func) 0 +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) + #define PyObject_Malloc(s) PyMem_Malloc(s) + #define PyObject_Free(p) PyMem_Free(p) + #define PyObject_Realloc(p) PyMem_Realloc(p) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 + #define PyMem_RawMalloc(n) PyMem_Malloc(n) + #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) + #define PyMem_RawFree(p) PyMem_Free(p) +#endif +#if CYTHON_COMPILING_IN_PYSTON + #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) +#else + #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) +#endif +#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#elif PY_VERSION_HEX >= 0x03060000 + #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() +#elif PY_VERSION_HEX >= 0x03000000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#else + #define __Pyx_PyThreadState_Current _PyThreadState_Current +#endif +#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) +#include "pythread.h" +#define Py_tss_NEEDS_INIT 0 +typedef int Py_tss_t; +static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { + *key = PyThread_create_key(); + return 0; +} +static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { + Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); + *key = Py_tss_NEEDS_INIT; + return key; +} +static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { + PyObject_Free(key); +} +static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { + return *key != Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { + PyThread_delete_key(*key); + *key = Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { + return PyThread_set_key_value(*key, value); +} +static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { + return PyThread_get_key_value(*key); +} +#endif +#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) +#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) +#else +#define __Pyx_PyDict_NewPresized(n) PyDict_New() +#endif +#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS +#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) +#else +#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) +#endif +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) + #define CYTHON_PEP393_ENABLED 1 + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ + 0 : _PyUnicode_Ready((PyObject *)(op))) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) + #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) + #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) + #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif +#else + #define CYTHON_PEP393_ENABLED 0 + #define PyUnicode_1BYTE_KIND 1 + #define PyUnicode_2BYTE_KIND 2 + #define PyUnicode_4BYTE_KIND 4 + #define __Pyx_PyUnicode_READY(op) (0) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) + #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) + #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) + #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) +#endif +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) +#else + #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ + PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) + #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) + #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) +#endif +#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) +#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) +#else + #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) +#endif +#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) + #define PyObject_ASCII(o) PyObject_Repr(o) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode + #define PyObject_Unicode PyObject_Str +#endif +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) + #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) +#else + #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) + #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif +#if CYTHON_ASSUME_SAFE_MACROS + #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) +#else + #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define PyNumber_Int PyNumber_Long +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif +#if PY_VERSION_HEX < 0x030200A4 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t PyInt_AsLong +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) +#endif +#if CYTHON_USE_ASYNC_SLOTS + #if PY_VERSION_HEX >= 0x030500B1 + #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods + #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) + #else + #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) + #endif +#else + #define __Pyx_PyType_AsAsync(obj) NULL +#endif +#ifndef __Pyx_PyAsyncMethodsStruct + typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; + } __Pyx_PyAsyncMethodsStruct; +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include +#ifdef NAN +#define __PYX_NAN() ((float) NAN) +#else +static CYTHON_INLINE float __PYX_NAN() { + float value; + memset(&value, 0xFF, sizeof(value)); + return value; +} +#endif +#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) +#define __Pyx_truncl trunc +#else +#define __Pyx_truncl truncl +#endif + +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } +#define __PYX_ERR(f_index, lineno, Ln_error) \ + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#define __PYX_HAVE___criterion +#define __PYX_HAVE_API___criterion +/* Early includes */ +#include +#include +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + +#include +#include +#include "pythread.h" +#include "pystate.h" +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) +#define CYTHON_WITHOUT_ASSERTIONS +#endif + +typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; + const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; + +#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) +#define __PYX_DEFAULT_STRING_ENCODING "" +#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString +#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX))) ) +static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { + return (size_t) i < (size_t) limit; +} +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (_MSC_VER) + #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); +#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) +#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); +#if PY_MAJOR_VERSION < 3 + #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#else + #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize +#endif +#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { + const Py_UNICODE *u_end = u; + while (*u_end++) ; + return (size_t)(u_end - u - 1); +} +#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) +#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode +#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); +#define __Pyx_PySequence_Tuple(obj)\ + (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +#if CYTHON_ASSUME_SAFE_MACROS +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#else +#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) +#endif +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) +#else +#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) +#endif +#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII +static int __Pyx_sys_getdefaultencoding_not_ascii; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + PyObject* ascii_chars_u = NULL; + PyObject* ascii_chars_b = NULL; + const char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + if (strcmp(default_encoding_c, "ascii") == 0) { + __Pyx_sys_getdefaultencoding_not_ascii = 0; + } else { + char ascii_chars[128]; + int c; + for (c = 0; c < 128; c++) { + ascii_chars[c] = c; + } + __Pyx_sys_getdefaultencoding_not_ascii = 1; + ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); + if (!ascii_chars_u) goto bad; + ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); + if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { + PyErr_Format( + PyExc_ValueError, + "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", + default_encoding_c); + goto bad; + } + Py_DECREF(ascii_chars_u); + Py_DECREF(ascii_chars_b); + } + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + Py_XDECREF(ascii_chars_u); + Py_XDECREF(ascii_chars_b); + return -1; +} +#endif +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) +#else +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +static char* __PYX_DEFAULT_STRING_ENCODING; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); + if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; + strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + return -1; +} +#endif +#endif + + +/* Test for GCC > 2.95 */ +#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) +#else /* !__GNUC__ or GCC < 2.95 */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ +static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } + +static PyObject *__pyx_m = NULL; +static PyObject *__pyx_d; +static PyObject *__pyx_b; +static PyObject *__pyx_cython_runtime = NULL; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static PyObject *__pyx_empty_unicode; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +/* Header.proto */ +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + + +static const char *__pyx_f[] = { + "stringsource", + "stpredictions/models/OK3/_criterion.pyx", + "__init__.pxd", + "type.pxd", + "_criterion.pxd", + "_splitter.pxd", + "_tree.pxd", + "_quad_tree.pxd", + "_utils.pxd", +}; +/* MemviewSliceStruct.proto */ +struct __pyx_memoryview_obj; +typedef struct { + struct __pyx_memoryview_obj *memview; + char *data; + Py_ssize_t shape[8]; + Py_ssize_t strides[8]; + Py_ssize_t suboffsets[8]; +} __Pyx_memviewslice; +#define __Pyx_MemoryView_Len(m) (m.shape[0]) + +/* Atomics.proto */ +#include +#ifndef CYTHON_ATOMICS + #define CYTHON_ATOMICS 1 +#endif +#define __pyx_atomic_int_type int +#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\ + (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\ + !defined(__i386__) + #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) + #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using GNU atomics" + #endif +#elif CYTHON_ATOMICS && defined(_MSC_VER) && 0 + #include + #undef __pyx_atomic_int_type + #define __pyx_atomic_int_type LONG + #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #pragma message ("Using MSVC atomics") + #endif +#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 + #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using Intel atomics" + #endif +#else + #undef CYTHON_ATOMICS + #define CYTHON_ATOMICS 0 + #ifdef __PYX_DEBUG_ATOMICS + #warning "Not using atomics" + #endif +#endif +typedef volatile __pyx_atomic_int_type __pyx_atomic_int; +#if CYTHON_ATOMICS + #define __pyx_add_acquisition_count(memview)\ + __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview)\ + __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) +#else + #define __pyx_add_acquisition_count(memview)\ + __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview)\ + __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) +#endif + +/* ForceInitThreads.proto */ +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + +/* NoFastGil.proto */ +#define __Pyx_PyGILState_Ensure PyGILState_Ensure +#define __Pyx_PyGILState_Release PyGILState_Release +#define __Pyx_FastGIL_Remember() +#define __Pyx_FastGIL_Forget() +#define __Pyx_FastGilFuncInit() + +/* BufferFormatStructs.proto */ +#define IS_UNSIGNED(type) (((type) -1) > 0) +struct __Pyx_StructField_; +#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) +typedef struct { + const char* name; + struct __Pyx_StructField_* fields; + size_t size; + size_t arraysize[8]; + int ndim; + char typegroup; + char is_unsigned; + int flags; +} __Pyx_TypeInfo; +typedef struct __Pyx_StructField_ { + __Pyx_TypeInfo* type; + const char* name; + size_t offset; +} __Pyx_StructField; +typedef struct { + __Pyx_StructField* field; + size_t parent_offset; +} __Pyx_BufFmt_StackElem; +typedef struct { + __Pyx_StructField root; + __Pyx_BufFmt_StackElem* head; + size_t fmt_offset; + size_t new_count, enc_count; + size_t struct_alignment; + int is_complex; + char enc_type; + char new_packmode; + char enc_packmode; + char is_valid_array; +} __Pyx_BufFmt_Context; + + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":689 + * # in Cython to enable them only on the right systems. + * + * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + */ +typedef npy_int8 __pyx_t_5numpy_int8_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":690 + * + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t + */ +typedef npy_int16 __pyx_t_5numpy_int16_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":691 + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< + * ctypedef npy_int64 int64_t + * #ctypedef npy_int96 int96_t + */ +typedef npy_int32 __pyx_t_5numpy_int32_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":692 + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< + * #ctypedef npy_int96 int96_t + * #ctypedef npy_int128 int128_t + */ +typedef npy_int64 __pyx_t_5numpy_int64_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":696 + * #ctypedef npy_int128 int128_t + * + * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + */ +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":697 + * + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t + */ +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":698 + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< + * ctypedef npy_uint64 uint64_t + * #ctypedef npy_uint96 uint96_t + */ +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":699 + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< + * #ctypedef npy_uint96 uint96_t + * #ctypedef npy_uint128 uint128_t + */ +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":703 + * #ctypedef npy_uint128 uint128_t + * + * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< + * ctypedef npy_float64 float64_t + * #ctypedef npy_float80 float80_t + */ +typedef npy_float32 __pyx_t_5numpy_float32_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":704 + * + * ctypedef npy_float32 float32_t + * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< + * #ctypedef npy_float80 float80_t + * #ctypedef npy_float128 float128_t + */ +typedef npy_float64 __pyx_t_5numpy_float64_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":713 + * # The int types are mapped a bit surprising -- + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t + */ +typedef npy_long __pyx_t_5numpy_int_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":714 + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong longlong_t + * + */ +typedef npy_longlong __pyx_t_5numpy_long_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":715 + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_ulong uint_t + */ +typedef npy_longlong __pyx_t_5numpy_longlong_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":717 + * ctypedef npy_longlong longlong_t + * + * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t + */ +typedef npy_ulong __pyx_t_5numpy_uint_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":718 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":719 + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_intp intp_t + */ +typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":721 + * ctypedef npy_ulonglong ulonglong_t + * + * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< + * ctypedef npy_uintp uintp_t + * + */ +typedef npy_intp __pyx_t_5numpy_intp_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":722 + * + * ctypedef npy_intp intp_t + * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< + * + * ctypedef npy_double float_t + */ +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":724 + * ctypedef npy_uintp uintp_t + * + * ctypedef npy_double float_t # <<<<<<<<<<<<<< + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t + */ +typedef npy_double __pyx_t_5numpy_float_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":725 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":726 + * ctypedef npy_double float_t + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cfloat cfloat_t + */ +typedef npy_longdouble __pyx_t_5numpy_longdouble_t; + +/* "sklearn/tree/_tree.pxd":16 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_7sklearn_4tree_5_tree_DTYPE_t; + +/* "sklearn/tree/_tree.pxd":17 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t; + +/* "sklearn/tree/_tree.pxd":18 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_7sklearn_4tree_5_tree_SIZE_t; + +/* "sklearn/tree/_tree.pxd":19 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_7sklearn_4tree_5_tree_INT32_t; + +/* "sklearn/tree/_tree.pxd":20 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * from ._splitter cimport Splitter + */ +typedef npy_uint32 __pyx_t_7sklearn_4tree_5_tree_UINT32_t; + +/* "neighbors/_quad_tree.pxd":13 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float32 __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t; + +/* "neighbors/_quad_tree.pxd":14 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t; + +/* "neighbors/_quad_tree.pxd":15 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_7sklearn_9neighbors_10_quad_tree_INT32_t; + +/* "neighbors/_quad_tree.pxd":16 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * # This is effectively an ifdef statement in Cython + */ +typedef npy_uint32 __pyx_t_7sklearn_9neighbors_10_quad_tree_UINT32_t; + +/* "sklearn/tree/_utils.pxd":16 + * from ..neighbors._quad_tree cimport Cell + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_7sklearn_4tree_6_utils_DTYPE_t; + +/* "sklearn/tree/_utils.pxd":17 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t; + +/* "sklearn/tree/_utils.pxd":18 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_7sklearn_4tree_6_utils_SIZE_t; + +/* "sklearn/tree/_utils.pxd":19 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_7sklearn_4tree_6_utils_INT32_t; + +/* "sklearn/tree/_utils.pxd":20 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * + */ +typedef npy_uint32 __pyx_t_7sklearn_4tree_6_utils_UINT32_t; +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< float > __pyx_t_float_complex; + #else + typedef float _Complex __pyx_t_float_complex; + #endif +#else + typedef struct { float real, imag; } __pyx_t_float_complex; +#endif +static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); + +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< double > __pyx_t_double_complex; + #else + typedef double _Complex __pyx_t_double_complex; + #endif +#else + typedef struct { double real, imag; } __pyx_t_double_complex; +#endif +static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); + + +/*--- Type declarations ---*/ +struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion; +struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion; +struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion; +struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter; +struct __pyx_obj_7sklearn_4tree_5_tree_Tree; +struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder; +struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree; +struct __pyx_obj_7sklearn_4tree_6_utils_Stack; +struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap; +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue; +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator; +struct __pyx_obj_10_criterion_Criterion; +struct __pyx_obj_10_criterion_KernelizedRegressionCriterion; +struct __pyx_obj_10_criterion_KernelizedMSE; +struct __pyx_array_obj; +struct __pyx_MemviewEnum_obj; +struct __pyx_memoryview_obj; +struct __pyx_memoryviewslice_obj; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":728 + * ctypedef npy_longdouble longdouble_t + * + * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t + */ +typedef npy_cfloat __pyx_t_5numpy_cfloat_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":729 + * + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< + * ctypedef npy_clongdouble clongdouble_t + * + */ +typedef npy_cdouble __pyx_t_5numpy_cdouble_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":730 + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cdouble complex_t + */ +typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":732 + * ctypedef npy_clongdouble clongdouble_t + * + * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< + * + * cdef inline object PyArray_MultiIterNew1(a): + */ +typedef npy_cdouble __pyx_t_5numpy_complex_t; +struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord; + +/* "_splitter.pxd":23 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef struct SplitRecord: # <<<<<<<<<<<<<< + * # Data to track sample split + * SIZE_t feature # Which feature to split on. + */ +struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + double threshold; + double improvement; + double impurity_left; + double impurity_right; +}; +struct __pyx_t_7sklearn_4tree_5_tree_Node; +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c; +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances; +struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build; + +/* "sklearn/tree/_tree.pxd":25 + * from ._splitter cimport SplitRecord + * + * cdef struct Node: # <<<<<<<<<<<<<< + * # Base storage structure for the nodes in a Tree object + * + */ +struct __pyx_t_7sklearn_4tree_5_tree_Node { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t left_child; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t right_child; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t threshold; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t impurity; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t weighted_n_node_samples; +}; + +/* "sklearn/tree/_tree.pxd":63 + * double weighted_n_samples) nogil except -1 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * + * cdef np.ndarray _get_value_ndarray(self) + */ +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c { + int __pyx_n; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; +}; + +/* "sklearn/tree/_tree.pxd":78 + * cdef object _decision_path_sparse_csr(self, object X) + * + * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< + * + * + */ +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances { + int __pyx_n; + PyObject *normalize; +}; + +/* "sklearn/tree/_tree.pxd":102 + * cdef double min_impurity_decrease # Impurity threshold for early stopping + * + * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< + * np.ndarray sample_weight=*) + * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) + */ +struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build { + int __pyx_n; + PyArrayObject *sample_weight; +}; +struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; + +/* "neighbors/_quad_tree.pxd":21 + * # It allows us to write printf debugging lines + * # and remove them at compile time + * cdef enum: # <<<<<<<<<<<<<< + * DEBUGFLAG = 0 + * + */ +enum { + __pyx_e_7sklearn_9neighbors_10_quad_tree_DEBUGFLAG = 0 +}; + +/* "neighbors/_quad_tree.pxd":29 + * # have is_leaf and max_width consecutive as it permits to avoid padding by + * # the compiler and keep the size coherent for both C and numpy data structures. + * cdef struct Cell: # <<<<<<<<<<<<<< + * # Base storage structure for cells in a QuadTree object + * + */ +struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell { + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t parent; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t children[8]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t point_index; + int is_leaf; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t squared_max_width; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t depth; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cumulative_size; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t center[3]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t barycenter[3]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t min_bounds[3]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t max_bounds[3]; +}; + +/* "neighbors/_quad_tree.pxd":75 + * + * # Point insertion methods + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< + * SIZE_t cell_id=*) nogil except -1 + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; +}; + +/* "neighbors/_quad_tree.pxd":77 + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, + * SIZE_t cell_id=*) nogil except -1 + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< + * SIZE_t point_index, SIZE_t size=* + * ) nogil + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t size; +}; + +/* "neighbors/_quad_tree.pxd":84 + * + * # Create a summary of the Tree compare to a query point + * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< + * float squared_theta=*, SIZE_t cell_id=*, long idx=* + * ) nogil + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize { + int __pyx_n; + float squared_theta; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + long idx; +}; + +/* "neighbors/_quad_tree.pxd":99 + * # Private array manipulation to manage the ``cells`` array + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 + * cdef np.ndarray _get_cell_ndarray(self) + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; +}; + +/* "neighbors/_quad_tree.pxd":100 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 + * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< + * cdef np.ndarray _get_cell_ndarray(self) + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; +}; +struct __pyx_t_7sklearn_4tree_6_utils_StackRecord; +struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord; +struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; + +/* "sklearn/tree/_utils.pxd":23 + * + * + * cdef enum: # <<<<<<<<<<<<<< + * # Max value for our rand_r replacement (near the bottom). + * # We don't use RAND_MAX because it's different across platforms and + */ +enum { + __pyx_e_7sklearn_4tree_6_utils_RAND_R_MAX = 0x7FFFFFFF +}; + +/* "sklearn/tree/_utils.pxd":70 + * + * # A record on the stack for depth-first tree growing + * cdef struct StackRecord: # <<<<<<<<<<<<<< + * SIZE_t start + * SIZE_t end + */ +struct __pyx_t_7sklearn_4tree_6_utils_StackRecord { + __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t parent; + int is_left; + double impurity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t n_constant_features; +}; + +/* "sklearn/tree/_utils.pxd":96 + * + * # A record on the frontier for best-first tree growing + * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< + * SIZE_t node_id + * SIZE_t start + */ +struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { + __pyx_t_7sklearn_4tree_6_utils_SIZE_t node_id; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t pos; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; + int is_leaf; + double impurity; + double impurity_left; + double impurity_right; + double improvement; +}; + +/* "sklearn/tree/_utils.pxd":127 + * + * # A record stored in the WeightedPQueue + * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< + * DOUBLE_t data + * DOUBLE_t weight + */ +struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord { + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t data; + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t weight; +}; + +/* "_criterion.pxd":21 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. It also computes the output statistics + */ +struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtab; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + double weighted_n_samples; + double weighted_n_node_samples; + double weighted_n_left; + double weighted_n_right; + double *sum_total; + double *sum_left; + double *sum_right; +}; + + +/* "_criterion.pxd":70 + * cdef double proxy_impurity_improvement(self) nogil + * + * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract criterion for classification.""" + * + */ +struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion { + struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t sum_stride; +}; + + +/* "_criterion.pxd":76 + * cdef SIZE_t sum_stride + * + * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract regression criterion.""" + * + */ +struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion { + struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; + double sq_sum_total; +}; + + +/* "_splitter.pxd":34 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ +struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtab; + struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *criterion; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + PyObject *random_state; + __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + double weighted_n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; +}; + + +/* "sklearn/tree/_tree.pxd":37 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. The tree structure is used for predictions and + */ +struct __pyx_obj_7sklearn_4tree_5_tree_Tree { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtab; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_n_classes; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t node_count; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; + struct __pyx_t_7sklearn_4tree_5_tree_Node *nodes; + double *value; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t value_stride; +}; + + +/* "sklearn/tree/_tree.pxd":85 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ +struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtab; + struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *splitter; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_split; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; + double min_impurity_split; + double min_impurity_decrease; +}; + + +/* "neighbors/_quad_tree.pxd":55 + * + * + * cdef class _QuadTree: # <<<<<<<<<<<<<< + * # The QuadTree object is a quad tree structure constructed by inserting + * # recursively points in the tree and splitting cells in 4 so that each + */ +struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtab; + int n_dimensions; + int verbose; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_cells_per_cell; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t max_depth; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_count; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_points; + struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *cells; +}; + + +/* "sklearn/tree/_utils.pxd":79 + * SIZE_t n_constant_features + * + * cdef class Stack: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t top + */ +struct __pyx_obj_7sklearn_4tree_6_utils_Stack { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t top; + struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *stack_; +}; + + +/* "sklearn/tree/_utils.pxd":108 + * double improvement + * + * cdef class PriorityHeap: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t heap_ptr + */ +struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t heap_ptr; + struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *heap_; +}; + + +/* "sklearn/tree/_utils.pxd":131 + * DOUBLE_t weight + * + * cdef class WeightedPQueue: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t array_ptr + */ +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t array_ptr; + struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *array_; +}; + + +/* "sklearn/tree/_utils.pxd":151 + * # ============================================================================= + * + * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< + * cdef SIZE_t initial_capacity + * cdef WeightedPQueue samples + */ +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t initial_capacity; + struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *samples; + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t total_weight; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t k; + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t sum_w_0_k; +}; + + +/* "_criterion.pxd":12 + * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. + */ +struct __pyx_obj_10_criterion_Criterion { + PyObject_HEAD + struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtab; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + double weighted_n_samples; + double weighted_n_node_samples; + double weighted_n_left; + double weighted_n_right; +}; + + +/* "_criterion.pxd":50 + * + * + * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract kernelized output regression criterion.""" + * + */ +struct __pyx_obj_10_criterion_KernelizedRegressionCriterion { + struct __pyx_obj_10_criterion_Criterion __pyx_base; + double sum_diag_Gramm; + double sum_total_Gramm; + double sum_diag_Gramm_left; + double sum_diag_Gramm_right; + double sum_total_Gramm_left; + double sum_total_Gramm_right; +}; + + +/* "_criterion.pyx":445 + * + * + * cdef class KernelizedMSE(KernelizedRegressionCriterion): # <<<<<<<<<<<<<< + * """Mean squared error impurity criterion. + * + */ +struct __pyx_obj_10_criterion_KernelizedMSE { + struct __pyx_obj_10_criterion_KernelizedRegressionCriterion __pyx_base; +}; + + +/* "View.MemoryView":105 + * + * @cname("__pyx_array") + * cdef class array: # <<<<<<<<<<<<<< + * + * cdef: + */ +struct __pyx_array_obj { + PyObject_HEAD + struct __pyx_vtabstruct_array *__pyx_vtab; + char *data; + Py_ssize_t len; + char *format; + int ndim; + Py_ssize_t *_shape; + Py_ssize_t *_strides; + Py_ssize_t itemsize; + PyObject *mode; + PyObject *_format; + void (*callback_free_data)(void *); + int free_data; + int dtype_is_object; +}; + + +/* "View.MemoryView":279 + * + * @cname('__pyx_MemviewEnum') + * cdef class Enum(object): # <<<<<<<<<<<<<< + * cdef object name + * def __init__(self, name): + */ +struct __pyx_MemviewEnum_obj { + PyObject_HEAD + PyObject *name; +}; + + +/* "View.MemoryView":330 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ +struct __pyx_memoryview_obj { + PyObject_HEAD + struct __pyx_vtabstruct_memoryview *__pyx_vtab; + PyObject *obj; + PyObject *_size; + PyObject *_array_interface; + PyThread_type_lock lock; + __pyx_atomic_int acquisition_count[2]; + __pyx_atomic_int *acquisition_count_aligned_p; + Py_buffer view; + int flags; + int dtype_is_object; + __Pyx_TypeInfo *typeinfo; +}; + + +/* "View.MemoryView":965 + * + * @cname('__pyx_memoryviewslice') + * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< + * "Internal class for passing memoryview slices to Python" + * + */ +struct __pyx_memoryviewslice_obj { + struct __pyx_memoryview_obj __pyx_base; + __Pyx_memviewslice from_slice; + PyObject *from_object; + PyObject *(*to_object_func)(char *); + int (*to_dtype_func)(char *, PyObject *); +}; + + + +/* "_criterion.pxd":21 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. It also computes the output statistics + */ + +struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion { + int (*init)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double, double, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_Criterion; + + +/* "_criterion.pxd":70 + * cdef double proxy_impurity_improvement(self) nogil + * + * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract criterion for classification.""" + * + */ + +struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion { + struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; +}; +static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_ClassificationCriterion; + + +/* "_criterion.pxd":76 + * cdef SIZE_t sum_stride + * + * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract regression criterion.""" + * + */ + +struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion { + struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; +}; +static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_RegressionCriterion; + + +/* "_splitter.pxd":34 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ + +struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter { + int (*init)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); + int (*node_reset)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); + int (*node_split)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double, struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); + void (*node_value)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double *); + double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtabptr_7sklearn_4tree_9_splitter_Splitter; + + +/* "sklearn/tree/_tree.pxd":37 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. The tree structure is used for predictions and + */ + +struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double); + int (*_resize)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args); + PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); + PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); + PyArrayObject *(*predict)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*apply)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*_apply_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyObject *(*decision_path)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyObject *(*_decision_path_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyObject *(*compute_feature_importances)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklearn_4tree_5_tree_Tree; + + +/* "sklearn/tree/_tree.pxd":85 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ + +struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder { + PyObject *(*build)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args); + PyObject *(*_check_input)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder; + + +/* "neighbors/_quad_tree.pxd":55 + * + * + * cdef class _QuadTree: # <<<<<<<<<<<<<< + * # The QuadTree object is a quad tree structure constructed by inserting + * # recursively points in the tree and splitting cells in 4 so that each + */ + +struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree { + int (*insert_point)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); + int (*_is_duplicate)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); + long (*summarize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); + void (*_init_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); + void (*_init_root)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); + int (*_check_point_in_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); + int (*_resize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); + int (*_get_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); + PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *); +}; +static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtabptr_7sklearn_9neighbors_10_quad_tree__QuadTree; + + +/* "sklearn/tree/_utils.pxd":79 + * SIZE_t n_constant_features + * + * cdef class Stack: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t top + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack { + int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7sklearn_4tree_6_utils_Stack; + + +/* "sklearn/tree/_utils.pxd":108 + * double improvement + * + * cdef class PriorityHeap: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t heap_ptr + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap { + int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); + void (*heapify_up)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + void (*heapify_down)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, double, double, double); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabptr_7sklearn_4tree_6_utils_PriorityHeap; + + +/* "sklearn/tree/_utils.pxd":131 + * DOUBLE_t weight + * + * cdef class WeightedPQueue: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t array_ptr + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue { + int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); + int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); + __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); + int (*peek)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedPQueue; + + +/* "sklearn/tree/_utils.pxd":151 + * # ============================================================================= + * + * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< + * cdef SIZE_t initial_capacity + * cdef WeightedPQueue samples + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator { + __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); + int (*update_median_parameters_post_push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); + int (*update_median_parameters_post_remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedMedianCalculator; + + +/* "_criterion.pyx":22 + * # from kernel import Kernel + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * """Interface for impurity criteria. + * + */ + +struct __pyx_vtabstruct_10_criterion_Criterion { + int (*init)(struct __pyx_obj_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *); +}; +static struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtabptr_10_criterion_Criterion; + + +/* "_criterion.pyx":209 + * + * + * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * r"""Abstract kernelized output regression criterion. + * + */ + +struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion { + struct __pyx_vtabstruct_10_criterion_Criterion __pyx_base; 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+#else +#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) +#endif + +/* GetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* ArgTypeTest.proto */ +#define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\ + ((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\ + __Pyx__ArgTypeTest(obj, type, name, exact)) +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact); + +/* PyObjectCall2Args.proto */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); + +/* IncludeStringH.proto */ +#include + +/* BytesEquals.proto */ +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); + +/* UnicodeEquals.proto */ +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals); + +/* StrEquals.proto */ +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals +#else +#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals +#endif + +/* UnaryNegOverflows.proto */ +#define UNARY_NEG_WOULD_OVERFLOW(x)\ + (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) + +static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/ +/* GetAttr.proto */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); + +/* GetItemInt.proto */ +#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ + __Pyx_GetItemInt_Generic(o, to_py_func(i)))) +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck); + +/* ObjectGetItem.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key); +#else +#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) +#endif + +/* decode_c_string_utf16.proto */ +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 0; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = -1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} + +/* decode_c_string.proto */ +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); + +/* GetAttr3.proto */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *); + +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + +/* GetModuleGlobalName.proto */ +#if CYTHON_USE_DICT_VERSIONS +#define __Pyx_GetModuleGlobalName(var, name) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + (var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\ + (likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\ + __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +#define __Pyx_GetModuleGlobalNameUncached(var, name) {\ + PY_UINT64_T __pyx_dict_version;\ + PyObject *__pyx_dict_cached_value;\ + (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value); +#else +#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) +#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); +#endif + +/* RaiseTooManyValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); + +/* RaiseNeedMoreValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); + +/* RaiseNoneIterError.proto */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + +/* SwapException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* Import.proto */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + +/* FastTypeChecks.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); +#else +#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) +#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) +#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) +#endif +#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) + +static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +/* ListCompAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len)) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) +#endif + +/* PyIntBinop.proto */ +#if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); +#else +#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ + (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) +#endif + +/* ListExtend.proto */ +static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject* none = _PyList_Extend((PyListObject*)L, v); + if (unlikely(!none)) + return -1; + Py_DECREF(none); + return 0; +#else + return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v); +#endif +} + +/* ListAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_PyList_Append(L,x) PyList_Append(L,x) +#endif + +/* None.proto */ +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); + +/* ImportFrom.proto */ +static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); + +/* HasAttr.proto */ +static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *); + +/* PyObject_GenericGetAttrNoDict.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr +#endif + +/* PyObject_GenericGetAttr.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr +#endif + +/* SetVTable.proto */ +static int __Pyx_SetVtable(PyObject *dict, void *vtable); + +/* PyObjectGetAttrStrNoError.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); + +/* SetupReduce.proto */ +static int __Pyx_setup_reduce(PyObject* type_obj); + +/* TypeImport.proto */ +#ifndef __PYX_HAVE_RT_ImportType_proto +#define __PYX_HAVE_RT_ImportType_proto +enum __Pyx_ImportType_CheckSize { + __Pyx_ImportType_CheckSize_Error = 0, + __Pyx_ImportType_CheckSize_Warn = 1, + __Pyx_ImportType_CheckSize_Ignore = 2 +}; +static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); +#endif + +/* GetVTable.proto */ +static void* __Pyx_GetVtable(PyObject *dict); + +/* CLineInTraceback.proto */ +#ifdef CYTHON_CLINE_IN_TRACEBACK +#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) +#else +static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); +#endif + +/* CodeObjectCache.proto */ +typedef struct { + PyCodeObject* code_object; + int code_line; +} __Pyx_CodeObjectCacheEntry; +struct __Pyx_CodeObjectCache { + int count; + int max_count; + __Pyx_CodeObjectCacheEntry* entries; +}; +static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); +static PyCodeObject *__pyx_find_code_object(int code_line); +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); + +/* AddTraceback.proto */ +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename); + +#if PY_MAJOR_VERSION < 3 + static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); + static void __Pyx_ReleaseBuffer(Py_buffer *view); +#else + #define __Pyx_GetBuffer PyObject_GetBuffer + #define __Pyx_ReleaseBuffer PyBuffer_Release +#endif + + +/* BufferStructDeclare.proto */ +typedef struct { + Py_ssize_t shape, strides, suboffsets; +} __Pyx_Buf_DimInfo; +typedef struct { + size_t refcount; + Py_buffer pybuffer; +} __Pyx_Buffer; +typedef struct { + __Pyx_Buffer *rcbuffer; + char *data; + __Pyx_Buf_DimInfo diminfo[8]; +} __Pyx_LocalBuf_ND; + +/* MemviewSliceIsContig.proto */ +static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); + +/* OverlappingSlices.proto */ +static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize); + +/* Capsule.proto */ +static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); + +/* GCCDiagnostics.proto */ +#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) +#define __Pyx_HAS_GCC_DIAGNOSTIC +#endif + +/* RealImag.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #define __Pyx_CREAL(z) ((z).real()) + #define __Pyx_CIMAG(z) ((z).imag()) + #else + #define __Pyx_CREAL(z) (__real__(z)) + #define __Pyx_CIMAG(z) (__imag__(z)) + #endif +#else + #define __Pyx_CREAL(z) ((z).real) + #define __Pyx_CIMAG(z) ((z).imag) +#endif +#if defined(__cplusplus) && CYTHON_CCOMPLEX\ + && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) + #define __Pyx_SET_CREAL(z,x) ((z).real(x)) + #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) +#else + #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) + #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_float(a, b) ((a)==(b)) + #define __Pyx_c_sum_float(a, b) ((a)+(b)) + #define __Pyx_c_diff_float(a, b) ((a)-(b)) + #define __Pyx_c_prod_float(a, b) ((a)*(b)) + #define __Pyx_c_quot_float(a, b) ((a)/(b)) + #define __Pyx_c_neg_float(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_float(z) ((z)==(float)0) + #define __Pyx_c_conj_float(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_float(z) (::std::abs(z)) + #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_float(z) ((z)==0) + #define __Pyx_c_conj_float(z) (conjf(z)) + #if 1 + #define __Pyx_c_abs_float(z) (cabsf(z)) + #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); + #endif +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_double(a, b) ((a)==(b)) + #define __Pyx_c_sum_double(a, b) ((a)+(b)) + #define __Pyx_c_diff_double(a, b) ((a)-(b)) + #define __Pyx_c_prod_double(a, b) ((a)*(b)) + #define __Pyx_c_quot_double(a, b) ((a)/(b)) + #define __Pyx_c_neg_double(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_double(z) ((z)==(double)0) + #define __Pyx_c_conj_double(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (::std::abs(z)) + #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_double(z) ((z)==0) + #define __Pyx_c_conj_double(z) (conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (cabs(z)) + #define __Pyx_c_pow_double(a, b) (cpow(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); + #endif +#endif + +/* MemviewSliceCopyTemplate.proto */ +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object); + +/* CIntFromPy.proto */ +static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); + +/* CheckBinaryVersion.proto */ +static int __Pyx_check_binary_version(void); + +/* VoidPtrImport.proto */ +static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig); + +/* FunctionImport.proto */ +static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig); + +/* InitStrings.proto */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); + +static int __pyx_f_10_criterion_9Criterion_init(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_y, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, CYTHON_UNUSED double __pyx_v_weighted_n_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end); /* proto*/ +static int __pyx_f_10_criterion_9Criterion_reset(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto*/ +static int __pyx_f_10_criterion_9Criterion_reverse_reset(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto*/ +static int __pyx_f_10_criterion_9Criterion_update(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos); /* proto*/ +static double __pyx_f_10_criterion_9Criterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto*/ +static void __pyx_f_10_criterion_9Criterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right); /* proto*/ +static void __pyx_f_10_criterion_9Criterion_node_value(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_dest); /* proto*/ +static double __pyx_f_10_criterion_9Criterion_proxy_impurity_improvement(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto*/ +static double __pyx_f_10_criterion_9Criterion_impurity_improvement(struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, double __pyx_v_impurity); /* proto*/ +static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, double __pyx_v_weighted_n_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end); /* proto*/ +static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ +static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ +static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos); /* proto*/ +static double __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ +static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right); /* proto*/ +static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, double *__pyx_v_dest); /* proto*/ +static double __pyx_f_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self); /* proto*/ +static double __pyx_f_10_criterion_13KernelizedMSE_proxy_impurity_improvement(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self); /* proto*/ +static void __pyx_f_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right); /* proto*/ +static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ +static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ +static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ + +/* Module declarations from 'cpython.buffer' */ + +/* Module declarations from 'libc.string' */ + +/* Module declarations from 'libc.stdio' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.type' */ +static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; + +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + +/* Module declarations from 'cpython.mem' */ + +/* Module declarations from 'numpy' */ + +/* Module declarations from 'numpy' */ +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; +static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; +static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; +static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; +static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; +static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ + +/* Module declarations from 'sklearn.tree._criterion' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_Criterion = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_ClassificationCriterion = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_RegressionCriterion = 0; + +/* Module declarations from 'sklearn.tree._splitter' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_9_splitter_Splitter = 0; + +/* Module declarations from 'sklearn.tree._tree' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_Tree = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_TreeBuilder = 0; + +/* Module declarations from 'libc.stdlib' */ + +/* Module declarations from 'libc.math' */ + +/* Module declarations from 'sklearn.neighbors._quad_tree' */ +static PyTypeObject *__pyx_ptype_7sklearn_9neighbors_10_quad_tree__QuadTree = 0; +static float *__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON = 0; +#define __pyx_v_7sklearn_9neighbors_10_quad_tree_EPSILON (*__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON) + +/* Module declarations from 'sklearn.tree._utils' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_Stack = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_PriorityHeap = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedPQueue = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedMedianCalculator = 0; +static PyArrayObject *(*__pyx_f_7sklearn_4tree_6_utils_sizet_ptr_to_ndarray)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); /*proto*/ +static double (*__pyx_f_7sklearn_4tree_6_utils_log)(double); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DTYPE_t **, size_t); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t **, size_t); /*proto*/ +static unsigned char *(*__pyx_fuse_2__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **, size_t); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t ***, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_5_tree_Node *(*__pyx_fuse_6__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_5_tree_Node **(*__pyx_fuse_8__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node ***, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_StackRecord **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord **, size_t); /*proto*/ + +/* Module declarations from '_criterion' */ +static PyTypeObject *__pyx_ptype_10_criterion_Criterion = 0; +static PyTypeObject *__pyx_ptype_10_criterion_KernelizedRegressionCriterion = 0; +static PyTypeObject *__pyx_ptype_10_criterion_KernelizedMSE = 0; +static PyTypeObject *__pyx_array_type = 0; +static PyTypeObject *__pyx_MemviewEnum_type = 0; +static PyTypeObject *__pyx_memoryview_type = 0; +static PyTypeObject *__pyx_memoryviewslice_type = 0; +static PyObject *generic = 0; +static PyObject *strided = 0; +static PyObject *indirect = 0; +static PyObject *contiguous = 0; +static PyObject *indirect_contiguous = 0; +static int __pyx_memoryview_thread_locks_used; +static PyThread_type_lock __pyx_memoryview_thread_locks[8]; +static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ +static void *__pyx_align_pointer(void *, size_t); /*proto*/ +static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ +static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ +static PyObject *_unellipsify(PyObject *, int); /*proto*/ +static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ +static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ +static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ +static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ +static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ +static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ +static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ +static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ +static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ +static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ +static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ +static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ +static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ +#define __Pyx_MODULE_NAME "_criterion" +extern int __pyx_module_is_main__criterion; +int __pyx_module_is_main__criterion = 0; + +/* Implementation of '_criterion' */ +static PyObject *__pyx_builtin_TypeError; +static PyObject *__pyx_builtin_range; +static PyObject *__pyx_builtin_ImportError; +static PyObject *__pyx_builtin_ValueError; +static PyObject *__pyx_builtin_MemoryError; +static PyObject *__pyx_builtin_enumerate; +static PyObject *__pyx_builtin_Ellipsis; +static PyObject *__pyx_builtin_id; +static PyObject *__pyx_builtin_IndexError; +static const char __pyx_k_O[] = "O"; +static const char __pyx_k_c[] = "c"; +static const char __pyx_k_id[] = "id"; +static const char __pyx_k_np[] = "np"; +static const char __pyx_k_new[] = "__new__"; +static const char __pyx_k_obj[] = "obj"; +static const char __pyx_k_base[] = "base"; +static const char __pyx_k_dict[] = "__dict__"; +static const char __pyx_k_main[] = "__main__"; +static const char __pyx_k_mode[] = "mode"; +static const char __pyx_k_name[] = "name"; +static const char __pyx_k_ndim[] = "ndim"; +static const char __pyx_k_pack[] = "pack"; +static const char __pyx_k_size[] = "size"; +static const char __pyx_k_step[] = "step"; +static const char __pyx_k_stop[] = "stop"; +static const char __pyx_k_test[] = "__test__"; +static const char __pyx_k_ASCII[] = "ASCII"; +static const char __pyx_k_class[] = "__class__"; +static const char __pyx_k_error[] = "error"; +static const char __pyx_k_flags[] = "flags"; +static const char __pyx_k_numpy[] = "numpy"; +static const char __pyx_k_range[] = "range"; +static const char __pyx_k_shape[] = "shape"; +static const char __pyx_k_start[] = "start"; +static const char __pyx_k_encode[] = "encode"; +static const char __pyx_k_format[] = "format"; +static const char __pyx_k_import[] = "__import__"; +static const char __pyx_k_name_2[] = "__name__"; +static const char __pyx_k_pickle[] = "pickle"; +static const char __pyx_k_reduce[] = "__reduce__"; +static const char __pyx_k_struct[] = "struct"; +static const char __pyx_k_unpack[] = "unpack"; +static const char __pyx_k_update[] = "update"; +static const char __pyx_k_fortran[] = "fortran"; +static const char __pyx_k_memview[] = "memview"; +static const char __pyx_k_Ellipsis[] = "Ellipsis"; +static const char __pyx_k_getstate[] = "__getstate__"; +static const char __pyx_k_itemsize[] = "itemsize"; +static const char __pyx_k_pyx_type[] = "__pyx_type"; +static const char __pyx_k_setstate[] = "__setstate__"; +static const char __pyx_k_Criterion[] = "Criterion"; +static const char __pyx_k_TypeError[] = "TypeError"; +static const char __pyx_k_enumerate[] = "enumerate"; +static const char __pyx_k_n_samples[] = "n_samples"; +static const char __pyx_k_pyx_state[] = "__pyx_state"; +static const char __pyx_k_reduce_ex[] = "__reduce_ex__"; +static const char __pyx_k_IndexError[] = "IndexError"; +static const char __pyx_k_ValueError[] = "ValueError"; +static const char __pyx_k_pyx_result[] = "__pyx_result"; +static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; +static const char __pyx_k_ImportError[] = "ImportError"; +static const char __pyx_k_MemoryError[] = "MemoryError"; +static const char __pyx_k_PickleError[] = "PickleError"; +static const char __pyx_k_pyx_checksum[] = "__pyx_checksum"; +static const char __pyx_k_stringsource[] = "stringsource"; +static const char __pyx_k_KernelizedMSE[] = "KernelizedMSE"; +static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; +static const char __pyx_k_reduce_cython[] = "__reduce_cython__"; +static const char __pyx_k_View_MemoryView[] = "View.MemoryView"; +static const char __pyx_k_allocate_buffer[] = "allocate_buffer"; +static const char __pyx_k_dtype_is_object[] = "dtype_is_object"; +static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError"; +static const char __pyx_k_setstate_cython[] = "__setstate_cython__"; +static const char __pyx_k_pyx_unpickle_Enum[] = "__pyx_unpickle_Enum"; +static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; +static const char __pyx_k_strided_and_direct[] = ""; +static const char __pyx_k_strided_and_indirect[] = ""; +static const char __pyx_k_contiguous_and_direct[] = ""; +static const char __pyx_k_MemoryView_of_r_object[] = ""; +static const char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; +static const char __pyx_k_contiguous_and_indirect[] = ""; +static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; +static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; +static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; +static const char __pyx_k_KernelizedRegressionCriterion[] = "KernelizedRegressionCriterion"; +static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; +static const char __pyx_k_strided_and_direct_or_indirect[] = ""; +static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; +static const char __pyx_k_self_sample_weight_self_samples[] = "self.sample_weight,self.samples cannot be converted to a Python object for pickling"; +static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; +static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; +static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview"; +static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview"; +static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; +static const char __pyx_k_Incompatible_checksums_s_vs_0xb0[] = "Incompatible checksums (%s vs 0xb068931 = (name))"; +static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; +static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; +static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; +static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; +static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; +static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; 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/* proto */ +static int __pyx_pf_10_criterion_29KernelizedRegressionCriterion___cinit__(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_samples); /* proto */ +static PyObject *__pyx_pf_10_criterion_29KernelizedRegressionCriterion_2__reduce__(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_12__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf___pyx_array___reduce_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_array_2__setstate_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ +static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_MemviewEnum___reduce_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_MemviewEnum_2__setstate_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ +static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryview___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryview_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryviewslice___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self); 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+ double __pyx_t_1; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; + + /* "_criterion.pyx":316 + * """Reset the criterion at pos=start.""" + * + * self.sum_diag_Gramm_left = 0.0 # <<<<<<<<<<<<<< + * self.sum_diag_Gramm_right = self.sum_diag_Gramm + * + */ + __pyx_v_self->sum_diag_Gramm_left = 0.0; + + /* "_criterion.pyx":317 + * + * self.sum_diag_Gramm_left = 0.0 + * self.sum_diag_Gramm_right = self.sum_diag_Gramm # <<<<<<<<<<<<<< + * + * self.sum_total_Gramm_left = 0.0 + */ + __pyx_t_1 = __pyx_v_self->sum_diag_Gramm; + __pyx_v_self->sum_diag_Gramm_right = __pyx_t_1; + + /* "_criterion.pyx":319 + * self.sum_diag_Gramm_right = self.sum_diag_Gramm + * + * self.sum_total_Gramm_left = 0.0 # <<<<<<<<<<<<<< + * self.sum_total_Gramm_right = self.sum_total_Gramm + * + */ + __pyx_v_self->sum_total_Gramm_left = 0.0; + + /* "_criterion.pyx":320 + * + * self.sum_total_Gramm_left = 0.0 + * self.sum_total_Gramm_right = self.sum_total_Gramm # <<<<<<<<<<<<<< + * + * self.weighted_n_left = 0.0 + */ + __pyx_t_1 = __pyx_v_self->sum_total_Gramm; + __pyx_v_self->sum_total_Gramm_right = __pyx_t_1; + + /* "_criterion.pyx":322 + * self.sum_total_Gramm_right = self.sum_total_Gramm + * + * self.weighted_n_left = 0.0 # <<<<<<<<<<<<<< + * self.weighted_n_right = self.weighted_n_node_samples + * self.pos = self.start + */ + __pyx_v_self->__pyx_base.weighted_n_left = 0.0; + + /* "_criterion.pyx":323 + * + * self.weighted_n_left = 0.0 + * self.weighted_n_right = self.weighted_n_node_samples # <<<<<<<<<<<<<< + * self.pos = self.start + * return 0 + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.weighted_n_node_samples; + __pyx_v_self->__pyx_base.weighted_n_right = __pyx_t_1; + + /* "_criterion.pyx":324 + * self.weighted_n_left = 0.0 + * self.weighted_n_right = self.weighted_n_node_samples + * self.pos = self.start # <<<<<<<<<<<<<< + * return 0 + * + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.start; + __pyx_v_self->__pyx_base.pos = __pyx_t_2; + + /* "_criterion.pyx":325 + * self.weighted_n_right = self.weighted_n_node_samples + * self.pos = self.start + * return 0 # <<<<<<<<<<<<<< + * + * cdef int reverse_reset(self) nogil except -1: + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "_criterion.pyx":313 + * return 0 + * + * cdef int reset(self) nogil except -1: # <<<<<<<<<<<<<< + * """Reset the criterion at pos=start.""" + * + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "_criterion.pyx":327 + * return 0 + * + * cdef int reverse_reset(self) nogil except -1: # <<<<<<<<<<<<<< + * """Reset the criterion at pos=end.""" + * + */ + +static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { + int __pyx_r; + double __pyx_t_1; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; + + /* "_criterion.pyx":330 + * """Reset the criterion at pos=end.""" + * + * self.sum_diag_Gramm_right = 0.0 # <<<<<<<<<<<<<< + * self.sum_diag_Gramm_left = self.sum_diag_Gramm + * + */ + __pyx_v_self->sum_diag_Gramm_right = 0.0; + + /* "_criterion.pyx":331 + * + * self.sum_diag_Gramm_right = 0.0 + * self.sum_diag_Gramm_left = self.sum_diag_Gramm # <<<<<<<<<<<<<< + * + * self.sum_total_Gramm_right = 0.0 + */ + __pyx_t_1 = __pyx_v_self->sum_diag_Gramm; + __pyx_v_self->sum_diag_Gramm_left = __pyx_t_1; + + /* "_criterion.pyx":333 + * self.sum_diag_Gramm_left = self.sum_diag_Gramm + * + * self.sum_total_Gramm_right = 0.0 # <<<<<<<<<<<<<< + * self.sum_total_Gramm_left = self.sum_total_Gramm + * + */ + __pyx_v_self->sum_total_Gramm_right = 0.0; + + /* "_criterion.pyx":334 + * + * self.sum_total_Gramm_right = 0.0 + * self.sum_total_Gramm_left = self.sum_total_Gramm # <<<<<<<<<<<<<< + * + * self.weighted_n_right = 0.0 + */ + __pyx_t_1 = __pyx_v_self->sum_total_Gramm; + __pyx_v_self->sum_total_Gramm_left = __pyx_t_1; + + /* "_criterion.pyx":336 + * self.sum_total_Gramm_left = self.sum_total_Gramm + * + * self.weighted_n_right = 0.0 # <<<<<<<<<<<<<< + * self.weighted_n_left = self.weighted_n_node_samples + * self.pos = self.end + */ + __pyx_v_self->__pyx_base.weighted_n_right = 0.0; + + /* "_criterion.pyx":337 + * + * self.weighted_n_right = 0.0 + * self.weighted_n_left = self.weighted_n_node_samples # <<<<<<<<<<<<<< + * self.pos = self.end + * return 0 + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.weighted_n_node_samples; + __pyx_v_self->__pyx_base.weighted_n_left = __pyx_t_1; + + /* "_criterion.pyx":338 + * self.weighted_n_right = 0.0 + * self.weighted_n_left = self.weighted_n_node_samples + * self.pos = self.end # <<<<<<<<<<<<<< + * return 0 + * + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.end; + __pyx_v_self->__pyx_base.pos = __pyx_t_2; + + /* "_criterion.pyx":339 + * self.weighted_n_left = self.weighted_n_node_samples + * self.pos = self.end + * return 0 # <<<<<<<<<<<<<< + * + * cdef int update(self, SIZE_t new_pos) nogil except -1: + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "_criterion.pyx":327 + * return 0 + * + * cdef int reverse_reset(self) nogil except -1: # <<<<<<<<<<<<<< + * """Reset the criterion at pos=end.""" + * + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "_criterion.pyx":341 + * return 0 + * + * cdef int update(self, SIZE_t new_pos) nogil except -1: # <<<<<<<<<<<<<< + * """Updated statistics by moving samples[pos:new_pos] to the left.""" + * + */ + +static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos) { + double *__pyx_v_sample_weight; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_q; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_i; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_j; + int __pyx_r; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_t_1; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_2; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_3; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_5; + int __pyx_t_6; + Py_ssize_t __pyx_t_7; + Py_ssize_t __pyx_t_8; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_9; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_10; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_11; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "_criterion.pyx":344 + * """Updated statistics by moving samples[pos:new_pos] to the left.""" + * + * cdef double* sample_weight = self.sample_weight # <<<<<<<<<<<<<< + * cdef SIZE_t* samples = self.samples + * + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.sample_weight; + __pyx_v_sample_weight = __pyx_t_1; + + /* "_criterion.pyx":345 + * + * cdef double* sample_weight = self.sample_weight + * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< + * + * cdef SIZE_t start = self.start + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.samples; + __pyx_v_samples = __pyx_t_2; + + /* "_criterion.pyx":347 + * cdef SIZE_t* samples = self.samples + * + * cdef SIZE_t start = self.start # <<<<<<<<<<<<<< + * cdef SIZE_t pos = self.pos + * cdef SIZE_t end = self.end + */ + __pyx_t_3 = __pyx_v_self->__pyx_base.start; + __pyx_v_start = __pyx_t_3; + + /* "_criterion.pyx":348 + * + * cdef SIZE_t start = self.start + * cdef SIZE_t pos = self.pos # <<<<<<<<<<<<<< + * cdef SIZE_t end = self.end + * + */ + __pyx_t_3 = __pyx_v_self->__pyx_base.pos; + __pyx_v_pos = __pyx_t_3; + + /* "_criterion.pyx":349 + * cdef SIZE_t start = self.start + * cdef SIZE_t pos = self.pos + * cdef SIZE_t end = self.end # <<<<<<<<<<<<<< + * + * cdef SIZE_t i + */ + __pyx_t_3 = __pyx_v_self->__pyx_base.end; + __pyx_v_end = __pyx_t_3; + + /* "_criterion.pyx":355 + * cdef SIZE_t p + * cdef SIZE_t q + * cdef DOUBLE_t w_i = 1.0 # <<<<<<<<<<<<<< + * cdef DOUBLE_t w_j = 1.0 + * + */ + __pyx_v_w_i = 1.0; + + /* "_criterion.pyx":356 + * cdef SIZE_t q + * cdef DOUBLE_t w_i = 1.0 + * cdef DOUBLE_t w_j = 1.0 # <<<<<<<<<<<<<< + * + * # Update statistics up to new_pos + */ + __pyx_v_w_j = 1.0; + + /* "_criterion.pyx":360 + * # Update statistics up to new_pos + * + * for p in range(pos, new_pos): # <<<<<<<<<<<<<< + * i = samples[p] + * + */ + __pyx_t_3 = __pyx_v_new_pos; + __pyx_t_4 = __pyx_t_3; + for (__pyx_t_5 = __pyx_v_pos; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_p = __pyx_t_5; + + /* "_criterion.pyx":361 + * + * for p in range(pos, new_pos): + * i = samples[p] # <<<<<<<<<<<<<< + * + * if sample_weight != NULL: + */ + __pyx_v_i = (__pyx_v_samples[__pyx_v_p]); + + /* "_criterion.pyx":363 + * i = samples[p] + * + * if sample_weight != NULL: # <<<<<<<<<<<<<< + * w_i = sample_weight[i] + * + */ + __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); + if (__pyx_t_6) { + + /* "_criterion.pyx":364 + * + * if sample_weight != NULL: + * w_i = sample_weight[i] # <<<<<<<<<<<<<< + * + * self.sum_diag_Gramm_left += w_i * self.y[i,i] + */ + __pyx_v_w_i = (__pyx_v_sample_weight[__pyx_v_i]); + + /* "_criterion.pyx":363 + * i = samples[p] + * + * if sample_weight != NULL: # <<<<<<<<<<<<<< + * w_i = sample_weight[i] + * + */ + } + + /* "_criterion.pyx":366 + * w_i = sample_weight[i] + * + * self.sum_diag_Gramm_left += w_i * self.y[i,i] # <<<<<<<<<<<<<< + * + * self.sum_diag_Gramm_right -= w_i * self.y[i,i] + */ + if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 366, __pyx_L1_error)} + __pyx_t_7 = __pyx_v_i; + __pyx_t_8 = __pyx_v_i; + __pyx_v_self->sum_diag_Gramm_left = (__pyx_v_self->sum_diag_Gramm_left + (__pyx_v_w_i * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) ))))); + + /* "_criterion.pyx":368 + * self.sum_diag_Gramm_left += w_i * self.y[i,i] + * + * self.sum_diag_Gramm_right -= w_i * self.y[i,i] # <<<<<<<<<<<<<< + * + * self.weighted_n_left += w_i + */ + if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 368, __pyx_L1_error)} + __pyx_t_8 = __pyx_v_i; + __pyx_t_7 = __pyx_v_i; + __pyx_v_self->sum_diag_Gramm_right = (__pyx_v_self->sum_diag_Gramm_right - (__pyx_v_w_i * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) ))))); + + /* "_criterion.pyx":370 + * self.sum_diag_Gramm_right -= w_i * self.y[i,i] + * + * self.weighted_n_left += w_i # <<<<<<<<<<<<<< + * + * self.weighted_n_right -= w_i + */ + __pyx_v_self->__pyx_base.weighted_n_left = (__pyx_v_self->__pyx_base.weighted_n_left + __pyx_v_w_i); + + /* "_criterion.pyx":372 + * self.weighted_n_left += w_i + * + * self.weighted_n_right -= w_i # <<<<<<<<<<<<<< + * + * for q in range(start, pos): + */ + __pyx_v_self->__pyx_base.weighted_n_right = (__pyx_v_self->__pyx_base.weighted_n_right - __pyx_v_w_i); + + /* "_criterion.pyx":374 + * self.weighted_n_right -= w_i + * + * for q in range(start, pos): # <<<<<<<<<<<<<< + * j = samples[q] + * + */ + __pyx_t_9 = __pyx_v_pos; + __pyx_t_10 = __pyx_t_9; + for (__pyx_t_11 = __pyx_v_start; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) { + __pyx_v_q = __pyx_t_11; + + /* "_criterion.pyx":375 + * + * for q in range(start, pos): + * j = samples[q] # <<<<<<<<<<<<<< + * + * if sample_weight != NULL: + */ + __pyx_v_j = (__pyx_v_samples[__pyx_v_q]); + + /* "_criterion.pyx":377 + * j = samples[q] + * + * if sample_weight != NULL: # <<<<<<<<<<<<<< + * w_j = sample_weight[j] + * + */ + __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); + if (__pyx_t_6) { + + /* "_criterion.pyx":378 + * + * if sample_weight != NULL: + * w_j = sample_weight[j] # <<<<<<<<<<<<<< + * + * self.sum_total_Gramm_left += 2 * w_i * w_j * self.y[i,j] + */ + __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]); + + /* "_criterion.pyx":377 + * j = samples[q] + * + * if sample_weight != NULL: # <<<<<<<<<<<<<< + * w_j = sample_weight[j] + * + */ + } + + /* "_criterion.pyx":380 + * w_j = sample_weight[j] + * + * self.sum_total_Gramm_left += 2 * w_i * w_j * self.y[i,j] # <<<<<<<<<<<<<< + * + * for q in range(pos, new_pos): + */ + if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 380, __pyx_L1_error)} + __pyx_t_7 = __pyx_v_i; + __pyx_t_8 = __pyx_v_j; + __pyx_v_self->sum_total_Gramm_left = (__pyx_v_self->sum_total_Gramm_left + (((2.0 * __pyx_v_w_i) * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) ))))); + } + + /* "_criterion.pyx":382 + * self.sum_total_Gramm_left += 2 * w_i * w_j * self.y[i,j] + * + * for q in range(pos, new_pos): # <<<<<<<<<<<<<< + * j = samples[q] + * + */ + __pyx_t_9 = __pyx_v_new_pos; + __pyx_t_10 = __pyx_t_9; + for (__pyx_t_11 = __pyx_v_pos; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) { + __pyx_v_q = __pyx_t_11; + + /* "_criterion.pyx":383 + * + * for q in range(pos, new_pos): + * j = samples[q] # <<<<<<<<<<<<<< + * + * if sample_weight != NULL: + */ + __pyx_v_j = (__pyx_v_samples[__pyx_v_q]); + + /* "_criterion.pyx":385 + * j = samples[q] + * + * if sample_weight != NULL: # <<<<<<<<<<<<<< + * w_j = sample_weight[j] + * + */ + __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); + if (__pyx_t_6) { + + /* "_criterion.pyx":386 + * + * if sample_weight != NULL: + * w_j = sample_weight[j] # <<<<<<<<<<<<<< + * + * self.sum_total_Gramm_left += w_i * w_j * self.y[i,j] + */ + __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]); + + /* "_criterion.pyx":385 + * j = samples[q] + * + * if sample_weight != NULL: # <<<<<<<<<<<<<< + * w_j = sample_weight[j] + * + */ + } + + /* "_criterion.pyx":388 + * w_j = sample_weight[j] + * + * self.sum_total_Gramm_left += w_i * w_j * self.y[i,j] # <<<<<<<<<<<<<< + * + * self.sum_total_Gramm_right -= w_i * w_j * self.y[i,j] + */ + if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 388, __pyx_L1_error)} + __pyx_t_8 = __pyx_v_i; + __pyx_t_7 = __pyx_v_j; + __pyx_v_self->sum_total_Gramm_left = (__pyx_v_self->sum_total_Gramm_left + ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) ))))); + + /* "_criterion.pyx":390 + * self.sum_total_Gramm_left += w_i * w_j * self.y[i,j] + * + * self.sum_total_Gramm_right -= w_i * w_j * self.y[i,j] # <<<<<<<<<<<<<< + * + * for p in range(new_pos, end): + */ + if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 390, __pyx_L1_error)} + __pyx_t_7 = __pyx_v_i; + __pyx_t_8 = __pyx_v_j; + __pyx_v_self->sum_total_Gramm_right = (__pyx_v_self->sum_total_Gramm_right - ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) ))))); + } + } + + /* "_criterion.pyx":392 + * self.sum_total_Gramm_right -= w_i * w_j * self.y[i,j] + * + * for p in range(new_pos, end): # <<<<<<<<<<<<<< + * i = samples[p] + * + */ + __pyx_t_3 = __pyx_v_end; + __pyx_t_4 = __pyx_t_3; + for (__pyx_t_5 = __pyx_v_new_pos; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_p = __pyx_t_5; + + /* "_criterion.pyx":393 + * + * for p in range(new_pos, end): + * i = samples[p] # <<<<<<<<<<<<<< + * + * if sample_weight != NULL: + */ + __pyx_v_i = (__pyx_v_samples[__pyx_v_p]); + + /* "_criterion.pyx":395 + * i = samples[p] + * + * if sample_weight != NULL: # <<<<<<<<<<<<<< + * w_i = sample_weight[i] + * + */ + __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); + if (__pyx_t_6) { + + /* "_criterion.pyx":396 + * + * if sample_weight != NULL: + * w_i = sample_weight[i] # <<<<<<<<<<<<<< + * + * for q in range(pos, new_pos): + */ + __pyx_v_w_i = (__pyx_v_sample_weight[__pyx_v_i]); + + /* "_criterion.pyx":395 + * i = samples[p] + * + * if sample_weight != NULL: # <<<<<<<<<<<<<< + * w_i = sample_weight[i] + * + */ + } + + /* "_criterion.pyx":398 + * w_i = sample_weight[i] + * + * for q in range(pos, new_pos): # <<<<<<<<<<<<<< + * j = samples[q] + * + */ + __pyx_t_9 = __pyx_v_new_pos; 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+ { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); + #endif + __Pyx_AddTraceback("_criterion.KernelizedRegressionCriterion.update", __pyx_clineno, __pyx_lineno, __pyx_filename); + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + } + __pyx_r = -1; + __pyx_L0:; + return __pyx_r; +} + +/* "_criterion.pyx":409 + * return 0 + * + * cdef double node_impurity(self) nogil: # <<<<<<<<<<<<<< + * pass + * + */ + +static double __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { + double __pyx_r; + + /* function exit code */ + __pyx_r = 0; + return __pyx_r; +} + +/* "_criterion.pyx":412 + * pass + * + * cdef void children_impurity(self, double* impurity_left, double* impurity_right) nogil: # <<<<<<<<<<<<<< + * pass + * + */ + +static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) { + + /* function exit code */ +} + +/* "_criterion.pyx":415 + * pass + * + * cdef void node_value(self, double* dest) nogil: # <<<<<<<<<<<<<< + * """Compute the node value of samples[start:end] into dest.""" + * + */ + +static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, double *__pyx_v_dest) { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; 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+ + /* "_criterion.pyx":426 + * k = self.samples[p] + * + * if self.sample_weight != NULL: # <<<<<<<<<<<<<< + * w = self.sample_weight[k] + * + */ + __pyx_t_4 = ((__pyx_v_self->__pyx_base.sample_weight != NULL) != 0); + if (__pyx_t_4) { + + /* "_criterion.pyx":427 + * + * if self.sample_weight != NULL: + * w = self.sample_weight[k] # <<<<<<<<<<<<<< + * + * dest[k] = w / self.weighted_n_node_samples + */ + __pyx_v_w = (__pyx_v_self->__pyx_base.sample_weight[__pyx_v_k]); + + /* "_criterion.pyx":426 + * k = self.samples[p] + * + * if self.sample_weight != NULL: # <<<<<<<<<<<<<< + * w = self.sample_weight[k] + * + */ + } + + /* "_criterion.pyx":429 + * w = self.sample_weight[k] + * + * dest[k] = w / self.weighted_n_node_samples # <<<<<<<<<<<<<< + * + * + */ + (__pyx_v_dest[__pyx_v_k]) = (__pyx_v_w / __pyx_v_self->__pyx_base.weighted_n_node_samples); + } + + /* "_criterion.pyx":415 + * pass + * + * cdef void node_value(self, double* dest) nogil: # <<<<<<<<<<<<<< + * """Compute the node value of samples[start:end] into dest.""" + * + */ + + /* function exit code */ +} + +/* "_criterion.pyx":454 + * """ + * + * cdef double node_impurity(self) nogil: # <<<<<<<<<<<<<< + * """Evaluate the impurity of the current node, i.e. the impurity of + * samples[start:end].""" + */ + +static double __pyx_f_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self) { + double __pyx_v_impurity; + double __pyx_r; + + /* "_criterion.pyx":460 + * cdef double impurity + * + * impurity = self.sum_diag_Gramm / self.weighted_n_node_samples - self.sum_total_Gramm / (self.weighted_n_node_samples)**2 # <<<<<<<<<<<<<< + * + * return impurity + */ + __pyx_v_impurity = ((__pyx_v_self->__pyx_base.sum_diag_Gramm / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples) - (__pyx_v_self->__pyx_base.sum_total_Gramm / pow(__pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples, 2.0))); + + /* "_criterion.pyx":462 + * impurity = self.sum_diag_Gramm / self.weighted_n_node_samples - self.sum_total_Gramm / (self.weighted_n_node_samples)**2 + * + * return impurity # <<<<<<<<<<<<<< + * + * cdef double proxy_impurity_improvement(self) nogil: + */ + __pyx_r = __pyx_v_impurity; + goto __pyx_L0; + + /* "_criterion.pyx":454 + * """ + * + * cdef double node_impurity(self) nogil: # <<<<<<<<<<<<<< + * """Evaluate the impurity of the current node, i.e. the impurity of + * samples[start:end].""" + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "_criterion.pyx":464 + * return impurity + * + * cdef double proxy_impurity_improvement(self) nogil: # <<<<<<<<<<<<<< + * """Compute a proxy of the impurity reduction + * + */ + +static double __pyx_f_10_criterion_13KernelizedMSE_proxy_impurity_improvement(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self) { + double __pyx_v_proxy_impurity_left; + double __pyx_v_proxy_impurity_right; + double __pyx_r; + + /* "_criterion.pyx":476 + * """ + * + * cdef double proxy_impurity_left = self.sum_diag_Gramm_left - self.sum_total_Gramm_left / self.weighted_n_left # <<<<<<<<<<<<<< + * cdef double proxy_impurity_right = self.sum_diag_Gramm_right - self.sum_total_Gramm_right / self.weighted_n_right + * + */ + __pyx_v_proxy_impurity_left = (__pyx_v_self->__pyx_base.sum_diag_Gramm_left - (__pyx_v_self->__pyx_base.sum_total_Gramm_left / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_left)); + + /* "_criterion.pyx":477 + * + * cdef double proxy_impurity_left = self.sum_diag_Gramm_left - self.sum_total_Gramm_left / self.weighted_n_left + * cdef double proxy_impurity_right = self.sum_diag_Gramm_right - self.sum_total_Gramm_right / self.weighted_n_right # <<<<<<<<<<<<<< + * + * return (- proxy_impurity_left - proxy_impurity_right) + */ + __pyx_v_proxy_impurity_right = (__pyx_v_self->__pyx_base.sum_diag_Gramm_right - (__pyx_v_self->__pyx_base.sum_total_Gramm_right / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_right)); 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+ CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; + Py_ssize_t __pyx_v_dst_extent; + Py_ssize_t __pyx_v_src_stride; + Py_ssize_t __pyx_v_dst_stride; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + Py_ssize_t __pyx_t_4; + Py_ssize_t __pyx_t_5; + Py_ssize_t __pyx_t_6; + + /* "View.MemoryView":1147 + * + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + */ + __pyx_v_src_extent = (__pyx_v_src_shape[0]); + + /* "View.MemoryView":1148 + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] + */ + __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); + + /* "View.MemoryView":1149 + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + */ + __pyx_v_src_stride = (__pyx_v_src_strides[0]); + + /* "View.MemoryView":1150 + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< + * + * if ndim == 1: + */ + __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); + + /* "View.MemoryView":1152 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + + /* "View.MemoryView":1154 + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + */ + __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); + if (__pyx_t_2) { + __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); + } + __pyx_t_3 = (__pyx_t_2 != 0); + __pyx_t_1 = __pyx_t_3; + __pyx_L5_bool_binop_done:; + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + if (__pyx_t_1) { + + /* "View.MemoryView":1155 + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + goto __pyx_L4; + } + + /* "View.MemoryView":1157 + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + */ + /*else*/ { + __pyx_t_4 = __pyx_v_dst_extent; + __pyx_t_5 = __pyx_t_4; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1158 + * else: + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< + * src_data += src_stride + * dst_data += dst_stride + */ + (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize)); + + /* "View.MemoryView":1159 + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * else: + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1160 + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L4:; + + /* "View.MemoryView":1152 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1162 + * dst_data += dst_stride + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * _copy_strided_to_strided(src_data, src_strides + 1, + * dst_data, dst_strides + 1, + */ + /*else*/ { + __pyx_t_4 = __pyx_v_dst_extent; + __pyx_t_5 = __pyx_t_4; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1163 + * else: + * for i in range(dst_extent): + * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< + * dst_data, dst_strides + 1, + * src_shape + 1, dst_shape + 1, + */ + _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); + + /* "View.MemoryView":1167 + * src_shape + 1, dst_shape + 1, + * ndim - 1, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1168 + * ndim - 1, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L3:; + + /* "View.MemoryView":1140 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + + /* function exit code */ +} + +/* "View.MemoryView":1170 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + +static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + + /* "View.MemoryView":1173 + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< + * src.shape, dst.shape, ndim, itemsize) + * + */ + _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1170 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + + /* function exit code */ +} + +/* "View.MemoryView":1177 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + */ + +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { + Py_ssize_t __pyx_v_shape; + Py_ssize_t __pyx_v_size; + Py_ssize_t __pyx_r; + Py_ssize_t __pyx_t_1; + Py_ssize_t *__pyx_t_2; + Py_ssize_t *__pyx_t_3; + Py_ssize_t *__pyx_t_4; + + /* "View.MemoryView":1179 + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize # <<<<<<<<<<<<<< + * + * for shape in src.shape[:ndim]: + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; + __pyx_v_size = __pyx_t_1; + + /* "View.MemoryView":1181 + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + * + * for shape in src.shape[:ndim]: # <<<<<<<<<<<<<< + * size *= shape + * + */ + __pyx_t_3 = (__pyx_v_src->shape + __pyx_v_ndim); + for (__pyx_t_4 = __pyx_v_src->shape; __pyx_t_4 < __pyx_t_3; __pyx_t_4++) { + __pyx_t_2 = __pyx_t_4; + __pyx_v_shape = (__pyx_t_2[0]); + + /* "View.MemoryView":1182 + * + * for shape in src.shape[:ndim]: + * size *= shape # <<<<<<<<<<<<<< + * + * return size + */ + __pyx_v_size = (__pyx_v_size * __pyx_v_shape); + } + + /* "View.MemoryView":1184 + * size *= shape + * + * return size # <<<<<<<<<<<<<< + * + * @cname('__pyx_fill_contig_strides_array') + */ + __pyx_r = __pyx_v_size; + goto __pyx_L0; + + /* "View.MemoryView":1177 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1187 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { + int __pyx_v_idx; + Py_ssize_t __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_t_4; + + /* "View.MemoryView":1196 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + __pyx_t_1 = ((__pyx_v_order == 'F') != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1197 + * + * if order == 'F': + * for idx in range(ndim): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride *= shape[idx] + */ + __pyx_t_2 = __pyx_v_ndim; + __pyx_t_3 = __pyx_t_2; + for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { + __pyx_v_idx = __pyx_t_4; + + /* "View.MemoryView":1198 + * if order == 'F': + * for idx in range(ndim): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride *= shape[idx] + * else: + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1199 + * for idx in range(ndim): + * strides[idx] = stride + * stride *= shape[idx] # <<<<<<<<<<<<<< + * else: + * for idx in range(ndim - 1, -1, -1): + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + } + + /* "View.MemoryView":1196 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1201 + * stride *= shape[idx] + * else: + * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride *= shape[idx] + */ + /*else*/ { + for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) { + __pyx_v_idx = __pyx_t_2; + + /* "View.MemoryView":1202 + * else: + * for idx in range(ndim - 1, -1, -1): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride *= shape[idx] + * + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1203 + * for idx in range(ndim - 1, -1, -1): + * strides[idx] = stride + * stride *= shape[idx] # <<<<<<<<<<<<<< + * + * return stride + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + } + } + __pyx_L3:; + + /* "View.MemoryView":1205 + * stride *= shape[idx] + * + * return stride # <<<<<<<<<<<<<< + * + * @cname('__pyx_memoryview_copy_data_to_temp') + */ + __pyx_r = __pyx_v_stride; + goto __pyx_L0; + + /* "View.MemoryView":1187 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1208 + * + * @cname('__pyx_memoryview_copy_data_to_temp') + * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *tmpslice, + * char order, + */ + +static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_tmpslice, char __pyx_v_order, int __pyx_v_ndim) { + int __pyx_v_i; + void *__pyx_v_result; + size_t __pyx_v_itemsize; + size_t __pyx_v_size; + void *__pyx_r; + Py_ssize_t __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + struct __pyx_memoryview_obj *__pyx_t_4; + int __pyx_t_5; + int __pyx_t_6; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "View.MemoryView":1219 + * cdef void *result + * + * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< + * cdef size_t size = slice_get_size(src, ndim) + * + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; + __pyx_v_itemsize = __pyx_t_1; + + /* "View.MemoryView":1220 + * + * cdef size_t itemsize = src.memview.view.itemsize + * cdef size_t size = slice_get_size(src, ndim) # <<<<<<<<<<<<<< + * + * result = malloc(size) + */ + __pyx_v_size = __pyx_memoryview_slice_get_size(__pyx_v_src, __pyx_v_ndim); + + /* "View.MemoryView":1222 + * cdef size_t size = slice_get_size(src, ndim) + * + * result = malloc(size) # <<<<<<<<<<<<<< + * if not result: + * _err(MemoryError, NULL) + */ + __pyx_v_result = malloc(__pyx_v_size); + + /* "View.MemoryView":1223 + * + * result = malloc(size) + * if not result: # <<<<<<<<<<<<<< + * _err(MemoryError, NULL) + * + */ + __pyx_t_2 = ((!(__pyx_v_result != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1224 + * result = malloc(size) + * if not result: + * _err(MemoryError, NULL) # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(0, 1224, __pyx_L1_error) + + /* "View.MemoryView":1223 + * + * result = malloc(size) + * if not result: # <<<<<<<<<<<<<< + * _err(MemoryError, NULL) + * + */ + } + + /* "View.MemoryView":1227 + * + * + * tmpslice.data = result # <<<<<<<<<<<<<< + * tmpslice.memview = src.memview + * for i in range(ndim): + */ + __pyx_v_tmpslice->data = ((char *)__pyx_v_result); + + /* "View.MemoryView":1228 + * + * tmpslice.data = result + * tmpslice.memview = src.memview # <<<<<<<<<<<<<< + * for i in range(ndim): + * tmpslice.shape[i] = src.shape[i] + */ + __pyx_t_4 = __pyx_v_src->memview; + __pyx_v_tmpslice->memview = __pyx_t_4; + + /* "View.MemoryView":1229 + * tmpslice.data = result + * tmpslice.memview = src.memview + * for i in range(ndim): # <<<<<<<<<<<<<< + * tmpslice.shape[i] = src.shape[i] + * tmpslice.suboffsets[i] = -1 + */ + __pyx_t_3 = __pyx_v_ndim; + __pyx_t_5 = __pyx_t_3; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1230 + * tmpslice.memview = src.memview + * for i in range(ndim): + * tmpslice.shape[i] = src.shape[i] # <<<<<<<<<<<<<< + * tmpslice.suboffsets[i] = -1 + * + */ + (__pyx_v_tmpslice->shape[__pyx_v_i]) = (__pyx_v_src->shape[__pyx_v_i]); + + /* "View.MemoryView":1231 + * for i in range(ndim): + * tmpslice.shape[i] = src.shape[i] + * tmpslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< + * + * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, + */ + (__pyx_v_tmpslice->suboffsets[__pyx_v_i]) = -1L; + } + + /* "View.MemoryView":1233 + * tmpslice.suboffsets[i] = -1 + * + * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, # <<<<<<<<<<<<<< + * ndim, order) + * + */ + (void)(__pyx_fill_contig_strides_array((&(__pyx_v_tmpslice->shape[0])), (&(__pyx_v_tmpslice->strides[0])), __pyx_v_itemsize, __pyx_v_ndim, __pyx_v_order)); + + /* "View.MemoryView":1237 + * + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * if tmpslice.shape[i] == 1: + * tmpslice.strides[i] = 0 + */ + __pyx_t_3 = __pyx_v_ndim; + __pyx_t_5 = __pyx_t_3; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1238 + * + * for i in range(ndim): + * if tmpslice.shape[i] == 1: # <<<<<<<<<<<<<< + * tmpslice.strides[i] = 0 + * + */ + __pyx_t_2 = (((__pyx_v_tmpslice->shape[__pyx_v_i]) == 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1239 + * for i in range(ndim): + * if tmpslice.shape[i] == 1: + * tmpslice.strides[i] = 0 # <<<<<<<<<<<<<< + * + * if slice_is_contig(src[0], order, ndim): + */ + (__pyx_v_tmpslice->strides[__pyx_v_i]) = 0; + + /* "View.MemoryView":1238 + * + * for i in range(ndim): + * if tmpslice.shape[i] == 1: # <<<<<<<<<<<<<< + * tmpslice.strides[i] = 0 + * + */ + } + } + + /* "View.MemoryView":1241 + * tmpslice.strides[i] = 0 + * + * if slice_is_contig(src[0], order, ndim): # <<<<<<<<<<<<<< + * memcpy(result, src.data, size) + * else: + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig((__pyx_v_src[0]), __pyx_v_order, __pyx_v_ndim) != 0); 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+ + /* "View.MemoryView":1289 + * broadcast_leading(&dst, dst_ndim, src_ndim) + * + * cdef int ndim = max(src_ndim, dst_ndim) # <<<<<<<<<<<<<< + * + * for i in range(ndim): + */ + __pyx_t_3 = __pyx_v_dst_ndim; + __pyx_t_4 = __pyx_v_src_ndim; + if (((__pyx_t_3 > __pyx_t_4) != 0)) { + __pyx_t_5 = __pyx_t_3; + } else { + __pyx_t_5 = __pyx_t_4; + } + __pyx_v_ndim = __pyx_t_5; + + /* "View.MemoryView":1291 + * cdef int ndim = max(src_ndim, dst_ndim) + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: + */ + __pyx_t_5 = __pyx_v_ndim; + __pyx_t_3 = __pyx_t_5; + for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { + __pyx_v_i = __pyx_t_4; + + /* "View.MemoryView":1292 + * + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< + * if src.shape[i] == 1: + * broadcasting = True + */ + __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) != (__pyx_v_dst.shape[__pyx_v_i])) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1293 + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: # <<<<<<<<<<<<<< + * broadcasting = True + * src.strides[i] = 0 + */ + __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) == 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1294 + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: + * broadcasting = True # <<<<<<<<<<<<<< + * src.strides[i] = 0 + * else: + */ + __pyx_v_broadcasting = 1; + + /* "View.MemoryView":1295 + * if src.shape[i] == 1: + * broadcasting = True + * src.strides[i] = 0 # <<<<<<<<<<<<<< + * else: + * _err_extents(i, dst.shape[i], src.shape[i]) + */ + (__pyx_v_src.strides[__pyx_v_i]) = 0; + + /* "View.MemoryView":1293 + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: # <<<<<<<<<<<<<< + * broadcasting = True + * src.strides[i] = 0 + */ + goto __pyx_L7; + } + + /* "View.MemoryView":1297 + * src.strides[i] = 0 + * else: + * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<< + * + * if src.suboffsets[i] >= 0: + */ + /*else*/ { + __pyx_t_6 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(0, 1297, __pyx_L1_error) + } + __pyx_L7:; + + /* "View.MemoryView":1292 + * + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< + * if src.shape[i] == 1: + * broadcasting = True + */ + } + + /* "View.MemoryView":1299 + * _err_extents(i, dst.shape[i], src.shape[i]) + * + * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + */ + __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1300 + * + * if src.suboffsets[i] >= 0: + * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<< + * + * if slices_overlap(&src, &dst, ndim, itemsize): + */ + __pyx_t_6 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Dimension %d is not direct"), __pyx_v_i); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(0, 1300, __pyx_L1_error) + + /* "View.MemoryView":1299 + * _err_extents(i, dst.shape[i], src.shape[i]) + * + * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + */ + } + } + + /* "View.MemoryView":1302 + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< + * + * if not slice_is_contig(src, order, ndim): + */ + __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1304 + * if slices_overlap(&src, &dst, ndim, itemsize): + * + * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< + * order = get_best_order(&dst, ndim) + * + */ + __pyx_t_2 = ((!(__pyx_memviewslice_is_contig(__pyx_v_src, __pyx_v_order, __pyx_v_ndim) != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1305 + * + * if not slice_is_contig(src, order, ndim): + * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) + */ + __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim); + + /* "View.MemoryView":1304 + * if slices_overlap(&src, &dst, ndim, itemsize): + * + * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< + * order = get_best_order(&dst, ndim) + * + */ + } + + /* "View.MemoryView":1307 + * order = get_best_order(&dst, ndim) + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< + * src = tmp + * + */ + __pyx_t_7 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_7 == ((void *)NULL))) __PYX_ERR(0, 1307, __pyx_L1_error) + __pyx_v_tmpdata = __pyx_t_7; + + /* "View.MemoryView":1308 + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) + * src = tmp # <<<<<<<<<<<<<< + * + * if not broadcasting: + */ + __pyx_v_src = __pyx_v_tmp; + + /* "View.MemoryView":1302 + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< + * + * if not slice_is_contig(src, order, ndim): + */ + } + + /* "View.MemoryView":1310 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1313 + * + * + * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'C', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1314 + * + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) # <<<<<<<<<<<<<< + * elif slice_is_contig(src, 'F', ndim): + * direct_copy = slice_is_contig(dst, 'F', ndim) + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim); + + /* "View.MemoryView":1313 + * + * + * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + */ + goto __pyx_L12; + } + + /* "View.MemoryView":1315 + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'F', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1316 + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + * direct_copy = slice_is_contig(dst, 'F', ndim) # <<<<<<<<<<<<<< + * + * if direct_copy: + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim); + + /* "View.MemoryView":1315 + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + */ + } + __pyx_L12:; + + /* "View.MemoryView":1318 + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_2 = (__pyx_v_direct_copy != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1320 + * if direct_copy: + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1321 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + */ + (void)(memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim))); + + /* "View.MemoryView":1322 + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * free(tmpdata) + * return 0 + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1323 + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) # <<<<<<<<<<<<<< + * return 0 + * + */ + free(__pyx_v_tmpdata); + + /* "View.MemoryView":1324 + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + * return 0 # <<<<<<<<<<<<<< + * + * if order == 'F' == get_best_order(&dst, ndim): + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "View.MemoryView":1318 + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + } + + /* "View.MemoryView":1310 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + } + + /* "View.MemoryView":1326 + * return 0 + * + * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = (__pyx_v_order == 'F'); + if (__pyx_t_2) { + __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim)); + } + __pyx_t_8 = (__pyx_t_2 != 0); + if (__pyx_t_8) { + + /* "View.MemoryView":1329 + * + * + * transpose_memslice(&src) # <<<<<<<<<<<<<< + * transpose_memslice(&dst) + * + */ + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(0, 1329, __pyx_L1_error) + + /* "View.MemoryView":1330 + * + * transpose_memslice(&src) + * transpose_memslice(&dst) # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(0, 1330, __pyx_L1_error) + + /* "View.MemoryView":1326 + * return 0 + * + * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< + * + * + */ + } + + /* "View.MemoryView":1332 + * transpose_memslice(&dst) + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * copy_strided_to_strided(&src, &dst, ndim, itemsize) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1333 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * + */ + copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1334 + * refcount_copying(&dst, dtype_is_object, ndim, False) + * copy_strided_to_strided(&src, &dst, ndim, itemsize) + * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * + * free(tmpdata) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1336 + * refcount_copying(&dst, dtype_is_object, ndim, True) + * + * free(tmpdata) # <<<<<<<<<<<<<< + * return 0 + * + */ + free(__pyx_v_tmpdata); + + /* "View.MemoryView":1337 + * + * free(tmpdata) + * return 0 # <<<<<<<<<<<<<< + * + * @cname('__pyx_memoryview_broadcast_leading') + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "View.MemoryView":1268 + * + * @cname('__pyx_memoryview_copy_contents') + * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice dst, + * int src_ndim, int dst_ndim, + */ + + /* function exit code */ + __pyx_L1_error:; + { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); + #endif + __Pyx_AddTraceback("View.MemoryView.memoryview_copy_contents", __pyx_clineno, __pyx_lineno, __pyx_filename); + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + } + __pyx_r = -1; + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1340 + * + * @cname('__pyx_memoryview_broadcast_leading') + * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< + * int ndim, + * int ndim_other) nogil: + */ + +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) { + int __pyx_v_i; + int __pyx_v_offset; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + + /* "View.MemoryView":1344 + * int ndim_other) nogil: + * cdef int i + * cdef int offset = ndim_other - ndim # <<<<<<<<<<<<<< + * + * for i in range(ndim - 1, -1, -1): + */ + __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim); + + /* "View.MemoryView":1346 + * cdef int offset = ndim_other - ndim + * + * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] + */ + for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { + __pyx_v_i = __pyx_t_1; + + /* "View.MemoryView":1347 + * + * for i in range(ndim - 1, -1, -1): + * mslice.shape[i + offset] = mslice.shape[i] # <<<<<<<<<<<<<< + * mslice.strides[i + offset] = mslice.strides[i] + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] + */ + (__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]); + + /* "View.MemoryView":1348 + * for i in range(ndim - 1, -1, -1): + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] # <<<<<<<<<<<<<< + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] + * + */ + (__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1349 + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] # <<<<<<<<<<<<<< + * + * for i in range(offset): + */ + (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]); + } + + /* "View.MemoryView":1351 + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] + * + * for i in range(offset): # <<<<<<<<<<<<<< + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] + */ + __pyx_t_1 = __pyx_v_offset; + __pyx_t_2 = __pyx_t_1; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "View.MemoryView":1352 + * + * for i in range(offset): + * mslice.shape[i] = 1 # <<<<<<<<<<<<<< + * mslice.strides[i] = mslice.strides[0] + * mslice.suboffsets[i] = -1 + */ + (__pyx_v_mslice->shape[__pyx_v_i]) = 1; + + /* "View.MemoryView":1353 + * for i in range(offset): + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] # <<<<<<<<<<<<<< + * mslice.suboffsets[i] = -1 + * + */ + (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]); + + /* "View.MemoryView":1354 + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] + * mslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< + * + * + */ + (__pyx_v_mslice->suboffsets[__pyx_v_i]) = -1L; + } + + /* "View.MemoryView":1340 + * + * @cname('__pyx_memoryview_broadcast_leading') + * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< + * int ndim, + * int ndim_other) nogil: + */ + + /* function exit code */ +} + +/* "View.MemoryView":1362 + * + * @cname('__pyx_memoryview_refcount_copying') + * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< + * int ndim, bint inc) nogil: + * + */ + +static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_dtype_is_object, int __pyx_v_ndim, int __pyx_v_inc) { + int __pyx_t_1; + + /* "View.MemoryView":1366 + * + * + * if dtype_is_object: # <<<<<<<<<<<<<< + * refcount_objects_in_slice_with_gil(dst.data, dst.shape, + * dst.strides, ndim, inc) + */ + __pyx_t_1 = (__pyx_v_dtype_is_object != 0); 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+ p->y.memview = NULL; + return o; +} + +static void __pyx_tp_dealloc_10_criterion_Criterion(PyObject *o) { + struct __pyx_obj_10_criterion_Criterion *p = (struct __pyx_obj_10_criterion_Criterion *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_pw_10_criterion_9Criterion_1__dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + __PYX_XDEC_MEMVIEW(&p->y, 1); + (*Py_TYPE(o)->tp_free)(o); +} + +static PyMethodDef __pyx_methods_10_criterion_Criterion[] = { + {"__getstate__", (PyCFunction)__pyx_pw_10_criterion_9Criterion_3__getstate__, METH_NOARGS, 0}, + {"__setstate__", (PyCFunction)__pyx_pw_10_criterion_9Criterion_5__setstate__, METH_O, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_10_criterion_9Criterion_7__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_10_criterion_9Criterion_9__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_10_criterion_Criterion = { + PyVarObject_HEAD_INIT(0, 0) + "_criterion.Criterion", /*tp_name*/ + sizeof(struct __pyx_obj_10_criterion_Criterion), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_10_criterion_Criterion, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "Interface for impurity criteria.\n\n This object stores methods on how to calculate how good a split is using\n different metrics.\n ", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_10_criterion_Criterion, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_10_criterion_Criterion, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion __pyx_vtable_10_criterion_KernelizedRegressionCriterion; + +static PyObject *__pyx_tp_new_10_criterion_KernelizedRegressionCriterion(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *p; + PyObject *o = __pyx_tp_new_10_criterion_Criterion(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_10_criterion_Criterion*)__pyx_vtabptr_10_criterion_KernelizedRegressionCriterion; + if (unlikely(__pyx_pw_10_criterion_29KernelizedRegressionCriterion_1__cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static PyMethodDef __pyx_methods_10_criterion_KernelizedRegressionCriterion[] = { + {"__reduce__", (PyCFunction)__pyx_pw_10_criterion_29KernelizedRegressionCriterion_3__reduce__, METH_NOARGS, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_10_criterion_KernelizedRegressionCriterion = { + PyVarObject_HEAD_INIT(0, 0) + "_criterion.KernelizedRegressionCriterion", /*tp_name*/ + sizeof(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_10_criterion_Criterion, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "Abstract kernelized output regression criterion.\n\n This handles cases where the target is a structured object and the Gramm\n matrix (the matrix of the kernel evaluated at the output samples) is given\n as y. The impurity is evaluated by computing the variance of the target\n values (embedded in a larger Hilbert space) left and right of the split point.\n ", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_10_criterion_KernelizedRegressionCriterion, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_10_criterion_KernelizedRegressionCriterion, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_10_criterion_KernelizedMSE __pyx_vtable_10_criterion_KernelizedMSE; + +static PyObject *__pyx_tp_new_10_criterion_KernelizedMSE(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_10_criterion_KernelizedMSE *p; + PyObject *o = __pyx_tp_new_10_criterion_KernelizedRegressionCriterion(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_10_criterion_KernelizedMSE *)o); + p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_10_criterion_Criterion*)__pyx_vtabptr_10_criterion_KernelizedMSE; + return o; +} + +static PyTypeObject __pyx_type_10_criterion_KernelizedMSE = { + PyVarObject_HEAD_INIT(0, 0) + "_criterion.KernelizedMSE", /*tp_name*/ + sizeof(struct __pyx_obj_10_criterion_KernelizedMSE), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_10_criterion_Criterion, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "Mean squared error impurity criterion.\n \n var = \\sum_i^n (phi(y_i) - phi(y)_bar) ** 2\n = (\\sum_i^n phi(y_i) ** 2) - n_samples * phi(y)_bar ** 2\n\n MSE = var_left + var_right\n ", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + 0, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_10_criterion_KernelizedMSE, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_array __pyx_vtable_array; + +static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_array_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_array_obj *)o); + p->__pyx_vtab = __pyx_vtabptr_array; + p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None); + p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None); + if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_array(PyObject *o) { + struct __pyx_array_obj *p = (struct __pyx_array_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_array___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->mode); + Py_CLEAR(p->_format); + (*Py_TYPE(o)->tp_free)(o); +} +static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_array___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) { + PyObject *v = __Pyx_PyObject_GenericGetAttr(o, n); + if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Clear(); + v = __pyx_array___getattr__(o, n); + } + return v; +} + +static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_5array_7memview_1__get__(o); +} + +static PyMethodDef __pyx_methods_array[] = { + {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_array_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_array_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_array[] = { + {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_array = { + __pyx_array___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_array, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_array = { + __pyx_array___len__, /*mp_length*/ + __pyx_array___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_array = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_array_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_array = { + PyVarObject_HEAD_INIT(0, 0) + "_criterion.array", /*tp_name*/ + sizeof(struct __pyx_array_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_array, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_array, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_array, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + __pyx_tp_getattro_array, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_array, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + 0, /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_array, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_array, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_array, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; + +static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + struct __pyx_MemviewEnum_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_MemviewEnum_obj *)o); + p->name = Py_None; Py_INCREF(Py_None); + return o; +} + +static void __pyx_tp_dealloc_Enum(PyObject *o) { + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + Py_CLEAR(p->name); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + if (p->name) { + e = (*v)(p->name, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_Enum(PyObject *o) { + PyObject* tmp; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + tmp = ((PyObject*)p->name); + p->name = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + return 0; +} + +static PyMethodDef __pyx_methods_Enum[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_MemviewEnum = { + PyVarObject_HEAD_INIT(0, 0) + "_criterion.Enum", /*tp_name*/ + sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_Enum, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + __pyx_MemviewEnum___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_Enum, /*tp_traverse*/ + __pyx_tp_clear_Enum, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_Enum, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + __pyx_MemviewEnum___init__, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_Enum, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview; + +static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryview_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryview_obj *)o); + p->__pyx_vtab = __pyx_vtabptr_memoryview; + p->obj = Py_None; Py_INCREF(Py_None); + p->_size = Py_None; Py_INCREF(Py_None); + p->_array_interface = Py_None; Py_INCREF(Py_None); + p->view.obj = NULL; + if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_memoryview(PyObject *o) { + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_memoryview___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->obj); + Py_CLEAR(p->_size); + Py_CLEAR(p->_array_interface); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + if (p->obj) { + e = (*v)(p->obj, a); if (e) return e; + } + if (p->_size) { + e = (*v)(p->_size, a); if (e) return e; + } + if (p->_array_interface) { + e = (*v)(p->_array_interface, a); if (e) return e; + } + if (p->view.obj) { + e = (*v)(p->view.obj, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_memoryview(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + tmp = ((PyObject*)p->obj); + p->obj = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_size); + p->_size = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_array_interface); + p->_array_interface = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + Py_CLEAR(p->view.obj); + return 0; +} +static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_memoryview___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_1T_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4base_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_5shape_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_7strides_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_10suboffsets_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4ndim_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_8itemsize_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_6nbytes_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4size_1__get__(o); +} + +static PyMethodDef __pyx_methods_memoryview[] = { + {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0}, + {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0}, + {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0}, + {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_memoryview[] = { + {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, (char *)0, 0}, + {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, (char *)0, 0}, + {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, (char *)0, 0}, + {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, (char *)0, 0}, + {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, (char *)0, 0}, + {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, (char *)0, 0}, + {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, (char *)0, 0}, + {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, (char *)0, 0}, + {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_memoryview = { + __pyx_memoryview___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_memoryview, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_memoryview = { + __pyx_memoryview___len__, /*mp_length*/ + __pyx_memoryview___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_memoryview = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_memoryview_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_memoryview = { + PyVarObject_HEAD_INIT(0, 0) + "_criterion.memoryview", /*tp_name*/ + sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_memoryview, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + __pyx_memoryview___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + __pyx_memoryview___str__, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_memoryview, /*tp_traverse*/ + __pyx_tp_clear_memoryview, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_memoryview, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_memoryview, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_memoryview, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice; + +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryviewslice_obj *p; + PyObject *o = __pyx_tp_new_memoryview(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryviewslice_obj *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice; + p->from_object = Py_None; Py_INCREF(Py_None); + p->from_slice.memview = NULL; + return o; +} + +static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) { + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_memoryviewslice___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->from_object); + PyObject_GC_Track(o); + __pyx_tp_dealloc_memoryview(o); +} + +static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e; + if (p->from_object) { + e = (*v)(p->from_object, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear__memoryviewslice(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + __pyx_tp_clear_memoryview(o); + tmp = ((PyObject*)p->from_object); + p->from_object = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + __PYX_XDEC_MEMVIEW(&p->from_slice, 1); + return 0; +} + +static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_16_memoryviewslice_4base_1__get__(o); +} + +static PyMethodDef __pyx_methods__memoryviewslice[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = { + {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_memoryviewslice = { + PyVarObject_HEAD_INIT(0, 0) + "_criterion._memoryviewslice", /*tp_name*/ + sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___repr__, /*tp_repr*/ + #else + 0, /*tp_repr*/ + #endif + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___str__, /*tp_str*/ + #else + 0, /*tp_str*/ + #endif + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Internal class for passing memoryview slices to Python", /*tp_doc*/ + __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/ + __pyx_tp_clear__memoryviewslice, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods__memoryviewslice, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets__memoryviewslice, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new__memoryviewslice, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; + +static PyMethodDef __pyx_methods[] = { + {0, 0, 0, 0} +}; + +#if PY_MAJOR_VERSION >= 3 +#if CYTHON_PEP489_MULTI_PHASE_INIT +static PyObject* __pyx_pymod_create(PyObject *spec, PyModuleDef *def); /*proto*/ +static int __pyx_pymod_exec__criterion(PyObject* module); /*proto*/ +static PyModuleDef_Slot __pyx_moduledef_slots[] = { + {Py_mod_create, (void*)__pyx_pymod_create}, + {Py_mod_exec, (void*)__pyx_pymod_exec__criterion}, + {0, NULL} +}; +#endif + +static struct PyModuleDef __pyx_moduledef = { + PyModuleDef_HEAD_INIT, + "_criterion", + 0, /* m_doc */ + #if CYTHON_PEP489_MULTI_PHASE_INIT + 0, /* m_size */ + #else + -1, /* m_size */ + #endif + __pyx_methods /* m_methods */, + #if CYTHON_PEP489_MULTI_PHASE_INIT + __pyx_moduledef_slots, /* m_slots */ + #else + NULL, /* m_reload */ + #endif + NULL, /* m_traverse */ + NULL, /* m_clear */ + NULL /* m_free */ +}; +#endif +#ifndef CYTHON_SMALL_CODE +#if defined(__clang__) + #define CYTHON_SMALL_CODE +#elif defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 3)) + #define CYTHON_SMALL_CODE __attribute__((cold)) +#else + #define CYTHON_SMALL_CODE +#endif +#endif + +static __Pyx_StringTabEntry __pyx_string_tab[] = { + {&__pyx_n_s_ASCII, __pyx_k_ASCII, sizeof(__pyx_k_ASCII), 0, 0, 1, 1}, + 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+ void *r = NULL; + m = PyImport_ImportModule(modname); + if (!m) goto end; + p = PyObject_GetAttrString(m, "RefNannyAPI"); + if (!p) goto end; + r = PyLong_AsVoidPtr(p); +end: + Py_XDECREF(p); + Py_XDECREF(m); + return (__Pyx_RefNannyAPIStruct *)r; +} +#endif + +/* PyObjectGetAttrStr */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) { + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro)) + return tp->tp_getattro(obj, attr_name); +#if PY_MAJOR_VERSION < 3 + if (likely(tp->tp_getattr)) + return tp->tp_getattr(obj, PyString_AS_STRING(attr_name)); +#endif + return PyObject_GetAttr(obj, attr_name); +} +#endif + +/* GetBuiltinName */ +static PyObject *__Pyx_GetBuiltinName(PyObject *name) { + PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name); + if (unlikely(!result)) { + PyErr_Format(PyExc_NameError, +#if PY_MAJOR_VERSION >= 3 + "name '%U' is not defined", name); +#else + "name '%.200s' is not defined", PyString_AS_STRING(name)); +#endif + } + return result; +} + +/* PyObjectCall */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { + PyObject *result; + ternaryfunc call = func->ob_type->tp_call; + if (unlikely(!call)) + return PyObject_Call(func, arg, kw); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = (*call)(func, arg, kw); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyErrFetchRestore */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} +#endif + +/* RaiseException */ +#if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + __Pyx_PyThreadState_declare + Py_XINCREF(type); + if (!value || value == Py_None) + value = NULL; + else + Py_INCREF(value); + if (!tb || tb == Py_None) + tb = NULL; + else { + Py_INCREF(tb); + if (!PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + } + if (PyType_Check(type)) { +#if CYTHON_COMPILING_IN_PYPY + if (!value) { + Py_INCREF(Py_None); + value = Py_None; + } +#endif + PyErr_NormalizeException(&type, &value, &tb); + } else { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + value = type; + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + } + __Pyx_PyThreadState_assign + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + PyObject* owned_instance = NULL; + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (PyExceptionClass_Check(type)) { + PyObject *instance_class = NULL; + if (value && PyExceptionInstance_Check(value)) { + instance_class = (PyObject*) Py_TYPE(value); + if (instance_class != type) { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { + instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; + } + } + } + if (!instance_class) { + PyObject *args; + if (!value) + args = PyTuple_New(0); + else if (PyTuple_Check(value)) { + Py_INCREF(value); + args = value; + } else + args = PyTuple_Pack(1, value); + if (!args) + goto bad; + owned_instance = PyObject_Call(type, args, NULL); + Py_DECREF(args); + if (!owned_instance) + goto bad; + value = owned_instance; + if (!PyExceptionInstance_Check(value)) { + PyErr_Format(PyExc_TypeError, + "calling %R should have returned an instance of " + "BaseException, not %R", + type, Py_TYPE(value)); + goto bad; + } + } + } else { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + if (cause == Py_None) { + fixed_cause = NULL; + } else if (PyExceptionClass_Check(cause)) { + fixed_cause = PyObject_CallObject(cause, NULL); + if (fixed_cause == NULL) + goto bad; + } else if (PyExceptionInstance_Check(cause)) { + fixed_cause = cause; + Py_INCREF(fixed_cause); + } else { + PyErr_SetString(PyExc_TypeError, + "exception causes must derive from " + "BaseException"); + goto bad; + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } +#endif + } +bad: + Py_XDECREF(owned_instance); + return; +} +#endif + +/* RaiseDoubleKeywords */ +static void __Pyx_RaiseDoubleKeywordsError( + const char* func_name, + PyObject* kw_name) +{ + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION >= 3 + "%s() got multiple values for keyword argument '%U'", func_name, kw_name); + #else + "%s() got multiple values for keyword argument '%s'", func_name, + PyString_AsString(kw_name)); + #endif +} + +/* ParseKeywords */ +static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + continue; + } + name = first_kw_arg; + #if PY_MAJOR_VERSION < 3 + if (likely(PyString_Check(key))) { + while (*name) { + if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) + && _PyString_Eq(**name, key)) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + if ((**argname == key) || ( + (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) + && _PyString_Eq(**argname, key))) { + goto arg_passed_twice; + } + argname++; + } + } + } else + #endif + if (likely(PyUnicode_Check(key))) { + while (*name) { + int cmp = (**name == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**name, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + int cmp = (**argname == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**argname, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) goto arg_passed_twice; + argname++; + } + } + } else + goto invalid_keyword_type; + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, key); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%.200s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%.200s() got an unexpected keyword argument '%.200s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +/* RaiseArgTupleInvalid */ +static void __Pyx_RaiseArgtupleInvalid( + const char* func_name, + int exact, + Py_ssize_t num_min, + Py_ssize_t num_max, + Py_ssize_t num_found) +{ + Py_ssize_t num_expected; + const char *more_or_less; + if (num_found < num_min) { + num_expected = num_min; + more_or_less = "at least"; + } else { + num_expected = num_max; + more_or_less = "at most"; + } + if (exact) { + more_or_less = "exactly"; + } + PyErr_Format(PyExc_TypeError, + "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", + func_name, more_or_less, num_expected, + (num_expected == 1) ? "" : "s", num_found); +} + +/* PyFunctionFastCall */ +#if CYTHON_FAST_PYCALL +static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, + PyObject *globals) { + PyFrameObject *f; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject **fastlocals; + Py_ssize_t i; + PyObject *result; + assert(globals != NULL); + /* XXX Perhaps we should create a specialized + PyFrame_New() that doesn't take locals, but does + take builtins without sanity checking them. + */ + assert(tstate != NULL); + f = PyFrame_New(tstate, co, globals, NULL); + if (f == NULL) { + return NULL; + } + fastlocals = __Pyx_PyFrame_GetLocalsplus(f); + for (i = 0; i < na; i++) { + Py_INCREF(*args); + fastlocals[i] = *args++; + } + result = PyEval_EvalFrameEx(f,0); + ++tstate->recursion_depth; + Py_DECREF(f); + --tstate->recursion_depth; + return result; +} +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { + PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); + PyObject *globals = PyFunction_GET_GLOBALS(func); + PyObject *argdefs = PyFunction_GET_DEFAULTS(func); + PyObject *closure; +#if PY_MAJOR_VERSION >= 3 + PyObject *kwdefs; +#endif + PyObject *kwtuple, **k; + PyObject **d; + Py_ssize_t nd; + Py_ssize_t nk; + PyObject *result; + assert(kwargs == NULL || PyDict_Check(kwargs)); + nk = kwargs ? PyDict_Size(kwargs) : 0; + if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { + return NULL; + } + if ( +#if PY_MAJOR_VERSION >= 3 + co->co_kwonlyargcount == 0 && +#endif + likely(kwargs == NULL || nk == 0) && + co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { + if (argdefs == NULL && co->co_argcount == nargs) { + result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); + goto done; + } + else if (nargs == 0 && argdefs != NULL + && co->co_argcount == Py_SIZE(argdefs)) { + /* function called with no arguments, but all parameters have + a default value: use default values as arguments .*/ + args = &PyTuple_GET_ITEM(argdefs, 0); + result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); + goto done; + } + } + if (kwargs != NULL) { + Py_ssize_t pos, i; + kwtuple = PyTuple_New(2 * nk); + if (kwtuple == NULL) { + result = NULL; + goto done; + } + k = &PyTuple_GET_ITEM(kwtuple, 0); + pos = i = 0; + while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { + Py_INCREF(k[i]); + Py_INCREF(k[i+1]); + i += 2; + } + nk = i / 2; + } + else { + kwtuple = NULL; + k = NULL; + } + closure = PyFunction_GET_CLOSURE(func); +#if PY_MAJOR_VERSION >= 3 + kwdefs = PyFunction_GET_KW_DEFAULTS(func); +#endif + if (argdefs != NULL) { + d = &PyTuple_GET_ITEM(argdefs, 0); + nd = Py_SIZE(argdefs); + } + else { + d = NULL; + nd = 0; + } +#if PY_MAJOR_VERSION >= 3 + result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, kwdefs, closure); +#else + result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, closure); +#endif + Py_XDECREF(kwtuple); +done: + Py_LeaveRecursiveCall(); + return result; +} +#endif +#endif + +/* PyObjectCallMethO */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallNoArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, NULL, 0); + } +#endif +#ifdef __Pyx_CyFunction_USED + if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) +#else + if (likely(PyCFunction_Check(func))) +#endif + { + if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { + return __Pyx_PyObject_CallMethO(func, NULL); + } + } + return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); +} +#endif + +/* PyCFunctionFastCall */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { + PyCFunctionObject *func = (PyCFunctionObject*)func_obj; + PyCFunction meth = PyCFunction_GET_FUNCTION(func); + PyObject *self = PyCFunction_GET_SELF(func); + int flags = PyCFunction_GET_FLAGS(func); + assert(PyCFunction_Check(func)); + assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); + assert(nargs >= 0); + assert(nargs == 0 || args != NULL); + /* _PyCFunction_FastCallDict() must not be called with an exception set, + because it may clear it (directly or indirectly) and so the + caller loses its exception */ + assert(!PyErr_Occurred()); + if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { + return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); + } else { + return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); + } +} +#endif + +/* PyObjectCallOneArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, &arg, 1); + } +#endif + if (likely(PyCFunction_Check(func))) { + if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { + return __Pyx_PyObject_CallMethO(func, arg); +#if CYTHON_FAST_PYCCALL + } else if (__Pyx_PyFastCFunction_Check(func)) { + return __Pyx_PyCFunction_FastCall(func, &arg, 1); +#endif + } + } + return __Pyx__PyObject_CallOneArg(func, arg); +} +#else +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_Pack(1, arg); + if (unlikely(!args)) return NULL; + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +#endif + +/* MemviewSliceInit */ +static int +__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference) +{ + __Pyx_RefNannyDeclarations + int i, retval=-1; + Py_buffer *buf = &memview->view; + __Pyx_RefNannySetupContext("init_memviewslice", 0); + if (unlikely(memviewslice->memview || memviewslice->data)) { + PyErr_SetString(PyExc_ValueError, + "memviewslice is already initialized!"); + goto fail; + } + if (buf->strides) { + for (i = 0; i < ndim; i++) { + memviewslice->strides[i] = buf->strides[i]; + } + } else { + Py_ssize_t stride = buf->itemsize; + for (i = ndim - 1; i >= 0; i--) { + memviewslice->strides[i] = stride; + stride *= buf->shape[i]; + } + } + for (i = 0; i < ndim; i++) { + memviewslice->shape[i] = buf->shape[i]; + if (buf->suboffsets) { + memviewslice->suboffsets[i] = buf->suboffsets[i]; + } else { + memviewslice->suboffsets[i] = -1; + } + } + memviewslice->memview = memview; + memviewslice->data = (char *)buf->buf; + if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { + Py_INCREF(memview); + } + retval = 0; + goto no_fail; +fail: + memviewslice->memview = 0; + memviewslice->data = 0; + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} +#ifndef Py_NO_RETURN +#define Py_NO_RETURN +#endif +static void __pyx_fatalerror(const char *fmt, ...) Py_NO_RETURN { + va_list vargs; + char msg[200]; +#ifdef HAVE_STDARG_PROTOTYPES + va_start(vargs, fmt); +#else + va_start(vargs); +#endif + vsnprintf(msg, 200, fmt, vargs); + va_end(vargs); + Py_FatalError(msg); +} +static CYTHON_INLINE int +__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)++; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE int +__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)--; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE void +__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) +{ + int first_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (unlikely(!memview || (PyObject *) memview == Py_None)) + return; + if (unlikely(__pyx_get_slice_count(memview) < 0)) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + first_time = __pyx_add_acquisition_count(memview) == 0; + if (unlikely(first_time)) { + if (have_gil) { + Py_INCREF((PyObject *) memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_INCREF((PyObject *) memview); + PyGILState_Release(_gilstate); + } + } +} +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, + int have_gil, int lineno) { + int last_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (unlikely(!memview || (PyObject *) memview == Py_None)) { + memslice->memview = NULL; + return; + } + if (unlikely(__pyx_get_slice_count(memview) <= 0)) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + last_time = __pyx_sub_acquisition_count(memview) == 1; + memslice->data = NULL; + if (unlikely(last_time)) { + if (have_gil) { + Py_CLEAR(memslice->memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_CLEAR(memslice->memview); + PyGILState_Release(_gilstate); + } + } else { + memslice->memview = NULL; + } +} + +/* GetTopmostException */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ +#if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ +#if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +/* ArgTypeTest */ +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) +{ + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + else if (exact) { + #if PY_MAJOR_VERSION == 2 + if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; + #endif + } + else { + if (likely(__Pyx_TypeCheck(obj, type))) return 1; + } + PyErr_Format(PyExc_TypeError, + "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); + return 0; +} + +/* PyObjectCall2Args */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { + PyObject *args, *result = NULL; + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyFunction_FastCall(function, args, 2); + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyCFunction_FastCall(function, args, 2); + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(arg1); + PyTuple_SET_ITEM(args, 0, arg1); + Py_INCREF(arg2); + PyTuple_SET_ITEM(args, 1, arg2); + Py_INCREF(function); + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); +done: + return result; +} + +/* BytesEquals */ +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else + if (s1 == s2) { + return (equals == Py_EQ); + } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { + const char *ps1, *ps2; + Py_ssize_t length = PyBytes_GET_SIZE(s1); + if (length != PyBytes_GET_SIZE(s2)) + return (equals == Py_NE); + ps1 = PyBytes_AS_STRING(s1); + ps2 = PyBytes_AS_STRING(s2); + if (ps1[0] != ps2[0]) { + return (equals == Py_NE); + } else if (length == 1) { + return (equals == Py_EQ); + } else { + int result; +#if CYTHON_USE_UNICODE_INTERNALS + Py_hash_t hash1, hash2; + hash1 = ((PyBytesObject*)s1)->ob_shash; + hash2 = ((PyBytesObject*)s2)->ob_shash; + if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { + return (equals == Py_NE); + } +#endif + result = memcmp(ps1, ps2, (size_t)length); + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { + return (equals == Py_NE); + } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { + return (equals == Py_NE); + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +#endif +} + +/* UnicodeEquals */ +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else +#if PY_MAJOR_VERSION < 3 + PyObject* owned_ref = NULL; +#endif + int s1_is_unicode, s2_is_unicode; + if (s1 == s2) { + goto return_eq; + } + s1_is_unicode = PyUnicode_CheckExact(s1); + s2_is_unicode = PyUnicode_CheckExact(s2); +#if PY_MAJOR_VERSION < 3 + if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { + owned_ref = PyUnicode_FromObject(s2); + if (unlikely(!owned_ref)) + return -1; + s2 = owned_ref; + s2_is_unicode = 1; + } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { + owned_ref = PyUnicode_FromObject(s1); + if (unlikely(!owned_ref)) + return -1; + s1 = owned_ref; + s1_is_unicode = 1; + } else if (((!s2_is_unicode) & (!s1_is_unicode))) { + return __Pyx_PyBytes_Equals(s1, s2, equals); + } +#endif + if (s1_is_unicode & s2_is_unicode) { + Py_ssize_t length; + int kind; + void *data1, *data2; + if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) + return -1; + length = __Pyx_PyUnicode_GET_LENGTH(s1); + if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { + goto return_ne; + } +#if CYTHON_USE_UNICODE_INTERNALS + { + Py_hash_t hash1, hash2; + #if CYTHON_PEP393_ENABLED + hash1 = ((PyASCIIObject*)s1)->hash; + hash2 = ((PyASCIIObject*)s2)->hash; + #else + hash1 = ((PyUnicodeObject*)s1)->hash; + hash2 = ((PyUnicodeObject*)s2)->hash; + #endif + if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { + goto return_ne; + } + } +#endif + kind = __Pyx_PyUnicode_KIND(s1); + if (kind != __Pyx_PyUnicode_KIND(s2)) { + goto return_ne; + } + data1 = __Pyx_PyUnicode_DATA(s1); + data2 = __Pyx_PyUnicode_DATA(s2); + if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { + goto return_ne; + } else if (length == 1) { + goto return_eq; + } else { + int result = memcmp(data1, data2, (size_t)(length * kind)); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & s2_is_unicode) { + goto return_ne; + } else if ((s2 == Py_None) & s1_is_unicode) { + goto return_ne; + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +return_eq: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ); +return_ne: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_NE); +#endif +} + +/* GetAttr */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { +#if CYTHON_USE_TYPE_SLOTS +#if PY_MAJOR_VERSION >= 3 + if (likely(PyUnicode_Check(n))) +#else + if (likely(PyString_Check(n))) +#endif + return __Pyx_PyObject_GetAttrStr(o, n); +#endif + return PyObject_GetAttr(o, n); +} + +/* GetItemInt */ +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { + PyObject *r; + if (!j) return NULL; + r = PyObject_GetItem(o, j); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyList_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { + PyObject *r = PyList_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyTuple_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); + if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { + PyObject *r = PyList_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } + else if (PyTuple_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + return NULL; + PyErr_Clear(); + } + } + return m->sq_item(o, i); + } + } +#else + if (is_list || PySequence_Check(o)) { + return PySequence_GetItem(o, i); + } +#endif + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +} + +/* ObjectGetItem */ +#if CYTHON_USE_TYPE_SLOTS +static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { + PyObject *runerr; + Py_ssize_t key_value; + PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; + if (unlikely(!(m && m->sq_item))) { + PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); + return NULL; + } + key_value = __Pyx_PyIndex_AsSsize_t(index); + if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { + return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); + } + if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { + PyErr_Clear(); + PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); + } + return NULL; +} +static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { + PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; + if (likely(m && m->mp_subscript)) { + return m->mp_subscript(obj, key); + } + return __Pyx_PyObject_GetIndex(obj, key); +} +#endif + +/* decode_c_string */ +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { + Py_ssize_t length; + if (unlikely((start < 0) | (stop < 0))) { + size_t slen = strlen(cstring); + if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { + PyErr_SetString(PyExc_OverflowError, + "c-string too long to convert to Python"); + return NULL; + } + length = (Py_ssize_t) slen; + if (start < 0) { + start += length; + if (start < 0) + start = 0; + } + if (stop < 0) + stop += length; + } + if (unlikely(stop <= start)) + return __Pyx_NewRef(__pyx_empty_unicode); + length = stop - start; + cstring += start; + if (decode_func) { + return decode_func(cstring, length, errors); + } else { + return PyUnicode_Decode(cstring, length, encoding, errors); + } +} + +/* GetAttr3 */ +static PyObject *__Pyx_GetAttr3Default(PyObject *d) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + return NULL; + __Pyx_PyErr_Clear(); + Py_INCREF(d); + return d; +} +static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) { + PyObject *r = __Pyx_GetAttr(o, n); + return (likely(r)) ? r : __Pyx_GetAttr3Default(d); +} + +/* PyDictVersioning */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + +/* GetModuleGlobalName */ +#if CYTHON_USE_DICT_VERSIONS +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) +#else +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) +#endif +{ + PyObject *result; +#if !CYTHON_AVOID_BORROWED_REFS +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 + result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } else if (unlikely(PyErr_Occurred())) { + return NULL; + } +#else + result = PyDict_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } +#endif +#else + result = PyObject_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } + PyErr_Clear(); +#endif + return __Pyx_GetBuiltinName(name); +} + +/* RaiseTooManyValuesToUnpack */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { + PyErr_Format(PyExc_ValueError, + "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); +} + +/* RaiseNeedMoreValuesToUnpack */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { + PyErr_Format(PyExc_ValueError, + "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", + index, (index == 1) ? "" : "s"); +} + +/* RaiseNoneIterError */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); +} + +/* ExtTypeTest */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +/* SwapException */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = *type; + exc_info->exc_value = *value; + exc_info->exc_traceback = *tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = *type; + tstate->exc_value = *value; + tstate->exc_traceback = *tb; + #endif + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} +#else +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); + PyErr_SetExcInfo(*type, *value, *tb); + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} +#endif + +/* Import */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_MAJOR_VERSION < 3 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_MAJOR_VERSION < 3 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + +/* FastTypeChecks */ +#if CYTHON_COMPILING_IN_CPYTHON +static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { + while (a) { + a = a->tp_base; + if (a == b) + return 1; + } + return b == &PyBaseObject_Type; +} +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { + PyObject *mro; + if (a == b) return 1; + mro = a->tp_mro; + if (likely(mro)) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(mro); + for (i = 0; i < n; i++) { + if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) + return 1; + } + return 0; + } + return __Pyx_InBases(a, b); +} +#if PY_MAJOR_VERSION == 2 +static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { + PyObject *exception, *value, *tb; + int res; + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&exception, &value, &tb); + res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + if (!res) { + res = PyObject_IsSubclass(err, exc_type2); + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + } + __Pyx_ErrRestore(exception, value, tb); + return res; +} +#else +static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { + int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; + if (!res) { + res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); + } + return res; +} +#endif +static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + assert(PyExceptionClass_Check(exc_type)); + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; i= 0 || (x^b) >= 0)) + return PyInt_FromLong(x); + return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + #endif + #if CYTHON_USE_PYLONG_INTERNALS + if (likely(PyLong_CheckExact(op1))) { + const long b = intval; + long a, x; +#ifdef HAVE_LONG_LONG + const PY_LONG_LONG llb = intval; + PY_LONG_LONG lla, llx; +#endif + const digit* digits = ((PyLongObject*)op1)->ob_digit; + const Py_ssize_t size = Py_SIZE(op1); + if (likely(__Pyx_sst_abs(size) <= 1)) { + a = likely(size) ? digits[0] : 0; + if (size == -1) a = -a; + } else { + switch (size) { + case -2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + default: return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + } + x = a + b; + return PyLong_FromLong(x); +#ifdef HAVE_LONG_LONG + long_long: + llx = lla + llb; + return PyLong_FromLongLong(llx); +#endif + + + } + #endif + if (PyFloat_CheckExact(op1)) { + const long b = intval; + double a = PyFloat_AS_DOUBLE(op1); + double result; + PyFPE_START_PROTECT("add", return NULL) + result = ((double)a) + (double)b; + PyFPE_END_PROTECT(result) + return PyFloat_FromDouble(result); + } + return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); +} +#endif + +/* None */ +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { + PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); +} + +/* ImportFrom */ +static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { + PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); + if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Format(PyExc_ImportError, + #if PY_MAJOR_VERSION < 3 + "cannot import name %.230s", PyString_AS_STRING(name)); + #else + "cannot import name %S", name); + #endif + } + return value; +} + +/* HasAttr */ +static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) { + PyObject *r; + if (unlikely(!__Pyx_PyBaseString_Check(n))) { + PyErr_SetString(PyExc_TypeError, + "hasattr(): attribute name must be string"); + return -1; + } + r = __Pyx_GetAttr(o, n); + if (unlikely(!r)) { + PyErr_Clear(); + return 0; + } else { + Py_DECREF(r); + return 1; + } +} + +/* PyObject_GenericGetAttrNoDict */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) { + PyErr_Format(PyExc_AttributeError, +#if PY_MAJOR_VERSION >= 3 + "'%.50s' object has no attribute '%U'", + tp->tp_name, attr_name); +#else + "'%.50s' object has no attribute '%.400s'", + tp->tp_name, PyString_AS_STRING(attr_name)); +#endif + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) { + PyObject *descr; + PyTypeObject *tp = Py_TYPE(obj); + if (unlikely(!PyString_Check(attr_name))) { + return PyObject_GenericGetAttr(obj, attr_name); + } + assert(!tp->tp_dictoffset); + descr = _PyType_Lookup(tp, attr_name); + if (unlikely(!descr)) { + return __Pyx_RaiseGenericGetAttributeError(tp, attr_name); + } + Py_INCREF(descr); + #if PY_MAJOR_VERSION < 3 + if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS))) + #endif + { + descrgetfunc f = Py_TYPE(descr)->tp_descr_get; + if (unlikely(f)) { + PyObject *res = f(descr, obj, (PyObject *)tp); + Py_DECREF(descr); + return res; + } + } + return descr; +} +#endif + +/* PyObject_GenericGetAttr */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) { + if (unlikely(Py_TYPE(obj)->tp_dictoffset)) { + return PyObject_GenericGetAttr(obj, attr_name); + } + return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name); +} +#endif + +/* SetVTable */ +static int __Pyx_SetVtable(PyObject *dict, void *vtable) { +#if PY_VERSION_HEX >= 0x02070000 + PyObject *ob = PyCapsule_New(vtable, 0, 0); +#else + PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); +#endif + if (!ob) + goto bad; + if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) + goto bad; + Py_DECREF(ob); + return 0; +bad: + Py_XDECREF(ob); + return -1; +} + +/* PyObjectGetAttrStrNoError */ +static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + __Pyx_PyErr_Clear(); +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { + PyObject *result; +#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { + return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); + } +#endif + result = __Pyx_PyObject_GetAttrStr(obj, attr_name); + if (unlikely(!result)) { + __Pyx_PyObject_GetAttrStr_ClearAttributeError(); + } + return result; +} + +/* SetupReduce */ +static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { + int ret; + PyObject *name_attr; + name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2); + if (likely(name_attr)) { + ret = PyObject_RichCompareBool(name_attr, name, Py_EQ); + } else { + ret = -1; + } + if (unlikely(ret < 0)) { + PyErr_Clear(); + ret = 0; + } + Py_XDECREF(name_attr); + return ret; +} +static int __Pyx_setup_reduce(PyObject* type_obj) { + int ret = 0; + PyObject *object_reduce = NULL; + PyObject *object_reduce_ex = NULL; + PyObject *reduce = NULL; + PyObject *reduce_ex = NULL; + PyObject *reduce_cython = NULL; + PyObject *setstate = NULL; + PyObject *setstate_cython = NULL; +#if CYTHON_USE_PYTYPE_LOOKUP + if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#else + if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#endif +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#else + object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#endif + reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; + if (reduce_ex == object_reduce_ex) { +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#else + object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#endif + reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; + if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { + reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); + if (likely(reduce_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (reduce == object_reduce || PyErr_Occurred()) { + goto __PYX_BAD; + } + setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); + if (!setstate) PyErr_Clear(); + if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { + setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); + if (likely(setstate_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (!setstate || PyErr_Occurred()) { + goto __PYX_BAD; + } + } + PyType_Modified((PyTypeObject*)type_obj); + } + } + goto __PYX_GOOD; +__PYX_BAD: + if (!PyErr_Occurred()) + PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); + ret = -1; +__PYX_GOOD: +#if !CYTHON_USE_PYTYPE_LOOKUP + Py_XDECREF(object_reduce); + Py_XDECREF(object_reduce_ex); +#endif + Py_XDECREF(reduce); + Py_XDECREF(reduce_ex); + Py_XDECREF(reduce_cython); + Py_XDECREF(setstate); + Py_XDECREF(setstate_cython); + return ret; +} + +/* TypeImport */ +#ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, + size_t size, enum __Pyx_ImportType_CheckSize check_size) +{ + PyObject *result = 0; + char warning[200]; + Py_ssize_t basicsize; +#ifdef Py_LIMITED_API + PyObject *py_basicsize; +#endif + result = PyObject_GetAttrString(module, class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%.200s.%.200s is not a type object", + module_name, class_name); + goto bad; + } +#ifndef Py_LIMITED_API + basicsize = ((PyTypeObject *)result)->tp_basicsize; +#else + py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); + if (!py_basicsize) + goto bad; + basicsize = PyLong_AsSsize_t(py_basicsize); + Py_DECREF(py_basicsize); + py_basicsize = 0; + if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) + goto bad; +#endif + if ((size_t)basicsize < size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(result); + return NULL; +} +#endif + +/* GetVTable */ +static void* __Pyx_GetVtable(PyObject *dict) { + void* ptr; + PyObject *ob = PyObject_GetItem(dict, __pyx_n_s_pyx_vtable); + if (!ob) + goto bad; +#if PY_VERSION_HEX >= 0x02070000 + ptr = PyCapsule_GetPointer(ob, 0); +#else + ptr = PyCObject_AsVoidPtr(ob); +#endif + if (!ptr && !PyErr_Occurred()) + PyErr_SetString(PyExc_RuntimeError, "invalid vtable found for imported type"); + Py_DECREF(ob); + return ptr; +bad: + Py_XDECREF(ob); + return NULL; +} + +/* CLineInTraceback */ +#ifndef CYTHON_CLINE_IN_TRACEBACK +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { + PyObject *use_cline; + PyObject *ptype, *pvalue, *ptraceback; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject **cython_runtime_dict; +#endif + if (unlikely(!__pyx_cython_runtime)) { + return c_line; + } + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); +#if CYTHON_COMPILING_IN_CPYTHON + cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); + if (likely(cython_runtime_dict)) { + __PYX_PY_DICT_LOOKUP_IF_MODIFIED( + use_cline, *cython_runtime_dict, + __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) + } else +#endif + { + PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); + if (use_cline_obj) { + use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; + Py_DECREF(use_cline_obj); + } else { + PyErr_Clear(); + use_cline = NULL; + } + } + if (!use_cline) { + c_line = 0; + PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); + } + else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { + c_line = 0; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + return c_line; +} +#endif + +/* CodeObjectCache */ +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = start + (end - start) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +/* AddTraceback */ +#include "compile.h" +#include "frameobject.h" +#include "traceback.h" +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyObject *py_srcfile = 0; + PyObject *py_funcname = 0; + #if PY_MAJOR_VERSION < 3 + py_srcfile = PyString_FromString(filename); + #else + py_srcfile = PyUnicode_FromString(filename); + #endif + if (!py_srcfile) goto bad; + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + #else + py_funcname = PyUnicode_FromString(funcname); + #endif + } + if (!py_funcname) goto bad; + py_code = __Pyx_PyCode_New( + 0, + 0, + 0, + 0, + 0, + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + Py_DECREF(py_funcname); + return py_code; +bad: + Py_XDECREF(py_srcfile); + Py_XDECREF(py_funcname); + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + if (c_line) { + c_line = __Pyx_CLineForTraceback(tstate, c_line); + } + py_code = __pyx_find_code_object(c_line ? -c_line : py_line); + if (!py_code) { + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) goto bad; + __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); + } + py_frame = PyFrame_New( + tstate, /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + __pyx_d, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + __Pyx_PyFrame_SetLineNumber(py_frame, py_line); + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { + if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); + if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); + if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); + PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); + return -1; +} +static void __Pyx_ReleaseBuffer(Py_buffer *view) { + PyObject *obj = view->obj; + if (!obj) return; + if (PyObject_CheckBuffer(obj)) { + PyBuffer_Release(view); + return; + } + if ((0)) {} + view->obj = NULL; + Py_DECREF(obj); +} +#endif + + +/* MemviewSliceIsContig */ +static int +__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) +{ + int i, index, step, start; + Py_ssize_t itemsize = mvs.memview->view.itemsize; + if (order == 'F') { + step = 1; + start = 0; + } else { + step = -1; + start = ndim - 1; + } + for (i = 0; i < ndim; i++) { + index = start + step * i; + if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) + return 0; + itemsize *= mvs.shape[index]; + } + return 1; +} + +/* OverlappingSlices */ +static void +__pyx_get_array_memory_extents(__Pyx_memviewslice *slice, + void **out_start, void **out_end, + int ndim, size_t itemsize) +{ + char *start, *end; + int i; + start = end = slice->data; + for (i = 0; i < ndim; i++) { + Py_ssize_t stride = slice->strides[i]; + Py_ssize_t extent = slice->shape[i]; + if (extent == 0) { + *out_start = *out_end = start; + return; + } else { + if (stride > 0) + end += stride * (extent - 1); + else + start += stride * (extent - 1); + } + } + *out_start = start; + *out_end = end + itemsize; +} +static int +__pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize) +{ + void *start1, *end1, *start2, *end2; + __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); + __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); + return (start1 < end2) && (start2 < end1); +} + +/* Capsule */ +static CYTHON_INLINE PyObject * +__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) +{ + PyObject *cobj; +#if PY_VERSION_HEX >= 0x02070000 + cobj = PyCapsule_New(p, sig, NULL); +#else + cobj = PyCObject_FromVoidPtr(p, NULL); +#endif + return cobj; +} + +/* CIntFromPyVerify */ +#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ + } + +/* Declarations */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabsf(b.real) >= fabsf(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + float r = b.imag / b.real; + float s = (float)(1.0) / (b.real + b.imag * r); + return __pyx_t_float_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + float r = b.real / b.imag; + float s = (float)(1.0) / (b.imag + b.real * r); + return __pyx_t_float_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + float denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_float_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_float(a, a); + case 3: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, a); + case 4: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = powf(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2f(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_float(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +/* Declarations */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabs(b.real) >= fabs(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + double r = b.imag / b.real; + double s = (double)(1.0) / (b.real + b.imag * r); + return __pyx_t_double_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + double r = b.real / b.imag; + double s = (double)(1.0) / (b.imag + b.real * r); + return __pyx_t_double_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + double denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_double_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_double(a, a); + case 3: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, a); + case 4: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = pow(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_double(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +/* MemviewSliceCopyTemplate */ +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object) +{ + __Pyx_RefNannyDeclarations + int i; + __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; + struct __pyx_memoryview_obj *from_memview = from_mvs->memview; + Py_buffer *buf = &from_memview->view; + PyObject *shape_tuple = NULL; + PyObject *temp_int = NULL; + struct __pyx_array_obj *array_obj = NULL; + struct __pyx_memoryview_obj *memview_obj = NULL; + __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); + for (i = 0; i < ndim; i++) { + if (unlikely(from_mvs->suboffsets[i] >= 0)) { + PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " + "indirect dimensions (axis %d)", i); + goto fail; + } + } + shape_tuple = PyTuple_New(ndim); + if (unlikely(!shape_tuple)) { + goto fail; + } + __Pyx_GOTREF(shape_tuple); + for(i = 0; i < ndim; i++) { + temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); + if(unlikely(!temp_int)) { + goto fail; + } else { + PyTuple_SET_ITEM(shape_tuple, i, temp_int); + temp_int = NULL; + } + } + array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); + if (unlikely(!array_obj)) { + goto fail; + } + __Pyx_GOTREF(array_obj); + memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + (PyObject *) array_obj, contig_flag, + dtype_is_object, + from_mvs->memview->typeinfo); + if (unlikely(!memview_obj)) + goto fail; + if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) + goto fail; + if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, + dtype_is_object) < 0)) + goto fail; + goto no_fail; +fail: + __Pyx_XDECREF(new_mvs.memview); + new_mvs.memview = NULL; + new_mvs.data = NULL; +no_fail: + __Pyx_XDECREF(shape_tuple); + __Pyx_XDECREF(temp_int); + __Pyx_XDECREF(array_obj); + __Pyx_RefNannyFinishContext(); + return new_mvs; +} + +/* CIntFromPy */ +static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(Py_intptr_t) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (Py_intptr_t) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (Py_intptr_t) 0; + case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, digits[0]) + case 2: + if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 2 * PyLong_SHIFT) { + return (Py_intptr_t) (((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 3 * PyLong_SHIFT) { + return (Py_intptr_t) (((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 4 * PyLong_SHIFT) { + return (Py_intptr_t) (((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (Py_intptr_t) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (Py_intptr_t) 0; + case -1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, +digits[0]) + case -2: + if (8 * sizeof(Py_intptr_t) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + } +#endif + if (sizeof(Py_intptr_t) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + Py_intptr_t val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (Py_intptr_t) -1; + } + } else { + Py_intptr_t val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (Py_intptr_t) -1; + val = __Pyx_PyInt_As_Py_intptr_t(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to Py_intptr_t"); + return (Py_intptr_t) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to Py_intptr_t"); + return (Py_intptr_t) -1; +} + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(Py_intptr_t) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(Py_intptr_t) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(Py_intptr_t), + little, !is_unsigned); + } +} + +/* CIntFromPy */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + } +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +/* CIntFromPy */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(long) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (long) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(long) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + } +#endif + if (sizeof(long) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + long val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (long) -1; + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (long) -1; + val = __Pyx_PyInt_As_long(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to long"); + return (long) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long) -1; +} + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(int) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(int) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(int) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(int), + little, !is_unsigned); + } +} + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(long) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(long) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(long) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(long), + little, !is_unsigned); + } +} + +/* CIntFromPy */ +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const char neg_one = (char) -1, const_zero = (char) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(char) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (char) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (char) 0; + case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { + return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { + return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { + return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (char) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(char) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (char) 0; + case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) + case -2: + if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + } +#endif + if (sizeof(char) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + char val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (char) -1; + } + } else { + char val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (char) -1; + val = __Pyx_PyInt_As_char(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to char"); + return (char) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to char"); + return (char) -1; +} + +/* CheckBinaryVersion */ +static int __Pyx_check_binary_version(void) { + char ctversion[4], rtversion[4]; + PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); + PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); + if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { + char message[200]; + PyOS_snprintf(message, sizeof(message), + "compiletime version %s of module '%.100s' " + "does not match runtime version %s", + ctversion, __Pyx_MODULE_NAME, rtversion); + return PyErr_WarnEx(NULL, message, 1); + } + return 0; +} + +/* VoidPtrImport */ +#ifndef __PYX_HAVE_RT_ImportVoidPtr +#define __PYX_HAVE_RT_ImportVoidPtr +static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig) { + PyObject *d = 0; + PyObject *cobj = 0; + d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); + if (!d) + goto bad; + cobj = PyDict_GetItemString(d, name); + if (!cobj) { + PyErr_Format(PyExc_ImportError, + "%.200s does not export expected C variable %.200s", + PyModule_GetName(module), name); + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + if (!PyCapsule_IsValid(cobj, sig)) { + PyErr_Format(PyExc_TypeError, + "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), name, sig, PyCapsule_GetName(cobj)); + goto bad; + } + *p = PyCapsule_GetPointer(cobj, sig); +#else + {const char *desc, *s1, *s2; + desc = (const char *)PyCObject_GetDesc(cobj); + if (!desc) + goto bad; + s1 = desc; s2 = sig; + while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } + if (*s1 != *s2) { + PyErr_Format(PyExc_TypeError, + "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), name, sig, desc); + goto bad; + } + *p = PyCObject_AsVoidPtr(cobj);} +#endif + if (!(*p)) + goto bad; + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(d); + return -1; +} +#endif + +/* FunctionImport */ +#ifndef __PYX_HAVE_RT_ImportFunction +#define __PYX_HAVE_RT_ImportFunction +static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig) { + PyObject *d = 0; + PyObject *cobj = 0; + union { + void (*fp)(void); + void *p; + } tmp; + d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); + if (!d) + goto bad; + cobj = PyDict_GetItemString(d, funcname); + if (!cobj) { + PyErr_Format(PyExc_ImportError, + "%.200s does not export expected C function %.200s", + PyModule_GetName(module), funcname); + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + if (!PyCapsule_IsValid(cobj, sig)) { + PyErr_Format(PyExc_TypeError, + "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), funcname, sig, PyCapsule_GetName(cobj)); + goto bad; + } + tmp.p = PyCapsule_GetPointer(cobj, sig); +#else + {const char *desc, *s1, *s2; + desc = (const char *)PyCObject_GetDesc(cobj); + if (!desc) + goto bad; + s1 = desc; s2 = sig; + while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } + if (*s1 != *s2) { + PyErr_Format(PyExc_TypeError, + "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), funcname, sig, desc); + goto bad; + } + tmp.p = PyCObject_AsVoidPtr(cobj);} +#endif + *f = tmp.fp; + if (!(*f)) + goto bad; + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(d); + return -1; +} +#endif + +/* InitStrings */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + if (PyObject_Hash(*t->p) == -1) + return -1; + ++t; + } + return 0; +} + +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { + return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); +} +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { + Py_ssize_t ignore; + return __Pyx_PyObject_AsStringAndSize(o, &ignore); +} +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if !CYTHON_PEP393_ENABLED +static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + char* defenc_c; + PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); + if (!defenc) return NULL; + defenc_c = PyBytes_AS_STRING(defenc); +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + { + char* end = defenc_c + PyBytes_GET_SIZE(defenc); + char* c; + for (c = defenc_c; c < end; c++) { + if ((unsigned char) (*c) >= 128) { + PyUnicode_AsASCIIString(o); + return NULL; + } + } + } +#endif + *length = PyBytes_GET_SIZE(defenc); + return defenc_c; +} +#else +static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + if (likely(PyUnicode_IS_ASCII(o))) { + *length = PyUnicode_GET_LENGTH(o); + return PyUnicode_AsUTF8(o); + } else { + PyUnicode_AsASCIIString(o); + return NULL; + } +#else + return PyUnicode_AsUTF8AndSize(o, length); +#endif +} +#endif +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT + if ( +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + __Pyx_sys_getdefaultencoding_not_ascii && +#endif + PyUnicode_Check(o)) { + return __Pyx_PyUnicode_AsStringAndSize(o, length); + } else +#endif +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) + if (PyByteArray_Check(o)) { + *length = PyByteArray_GET_SIZE(o); + return PyByteArray_AS_STRING(o); + } else +#endif + { + char* result; + int r = PyBytes_AsStringAndSize(o, &result, length); + if (unlikely(r < 0)) { + return NULL; + } else { + return result; + } + } +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { + int retval; + if (unlikely(!x)) return -1; + retval = __Pyx_PyObject_IsTrue(x); + Py_DECREF(x); + return retval; +} +static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { +#if PY_MAJOR_VERSION >= 3 + if (PyLong_Check(result)) { + if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, + "__int__ returned non-int (type %.200s). " + "The ability to return an instance of a strict subclass of int " + "is deprecated, and may be removed in a future version of Python.", + Py_TYPE(result)->tp_name)) { + Py_DECREF(result); + return NULL; + } + return result; + } +#endif + PyErr_Format(PyExc_TypeError, + "__%.4s__ returned non-%.4s (type %.200s)", + type_name, type_name, Py_TYPE(result)->tp_name); + Py_DECREF(result); + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { +#if CYTHON_USE_TYPE_SLOTS + PyNumberMethods *m; +#endif + const char *name = NULL; + PyObject *res = NULL; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x) || PyLong_Check(x))) +#else + if (likely(PyLong_Check(x))) +#endif + return __Pyx_NewRef(x); +#if CYTHON_USE_TYPE_SLOTS + m = Py_TYPE(x)->tp_as_number; + #if PY_MAJOR_VERSION < 3 + if (m && m->nb_int) { + name = "int"; + res = m->nb_int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = m->nb_long(x); + } + #else + if (likely(m && m->nb_int)) { + name = "int"; + res = m->nb_int(x); + } + #endif +#else + if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { + res = PyNumber_Int(x); + } +#endif + if (likely(res)) { +#if PY_MAJOR_VERSION < 3 + if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { +#else + if (unlikely(!PyLong_CheckExact(res))) { +#endif + return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject *x; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(b); + } +#endif + if (likely(PyLong_CheckExact(b))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + } + } + #endif + return PyLong_AsSsize_t(b); + } + x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { + return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); +} +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { + return PyInt_FromSize_t(ival); +} + + +#endif /* Py_PYTHON_H */ diff --git a/stpredictions/models/OK3/_criterion.pxd b/stpredictions/models/OK3/_criterion.pxd new file mode 100644 index 000000000..c9a78a6f1 --- /dev/null +++ b/stpredictions/models/OK3/_criterion.pxd @@ -0,0 +1,61 @@ +# See _criterion.pyx for implementation details. + +import numpy as np +cimport numpy as np + +from sklearn.tree._tree cimport DTYPE_t # Type of X +from sklearn.tree._tree cimport DOUBLE_t # Type of y, sample_weight +from sklearn.tree._tree cimport SIZE_t # Type for indices and counters +from sklearn.tree._tree cimport INT32_t # Signed 32 bit integer +from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + +cdef class Criterion: + # The criterion computes the impurity of a node and the reduction of + # impurity of a split on that node. + + # Internal structures + cdef const DOUBLE_t[:, ::1] y # Values of y + cdef DOUBLE_t* sample_weight # Sample weights + + cdef SIZE_t* samples # Sample indices in X, y + cdef SIZE_t start # samples[start:pos] are the samples in the left node + cdef SIZE_t pos # samples[pos:end] are the samples in the right node + cdef SIZE_t end + + cdef SIZE_t n_samples # Number of samples + cdef SIZE_t n_node_samples # Number of samples in the node (end-start) + cdef double weighted_n_samples # Weighted number of samples (in total) + cdef double weighted_n_node_samples # Weighted number of samples in the node + cdef double weighted_n_left # Weighted number of samples in the left node + cdef double weighted_n_right # Weighted number of samples in the right node + + # The criterion object is maintained such that left and right collected + # statistics correspond to samples[start:pos] and samples[pos:end]. + + # Methods + cdef int init(self, const DOUBLE_t[:, ::1] y, DOUBLE_t* sample_weight, + double weighted_n_samples, SIZE_t* samples, SIZE_t start, + SIZE_t end) nogil except -1 + cdef int reset(self) nogil except -1 + cdef int reverse_reset(self) nogil except -1 + cdef int update(self, SIZE_t new_pos) nogil except -1 + cdef double node_impurity(self) nogil + cdef void children_impurity(self, double* impurity_left, + double* impurity_right) nogil + cdef void node_value(self, double* dest) nogil + cdef double impurity_improvement(self, double impurity) nogil + cdef double proxy_impurity_improvement(self) nogil + + +cdef class KernelizedRegressionCriterion(Criterion): + """Abstract kernelized output regression criterion.""" + + cdef double sum_diag_Gramm + cdef double sum_total_Gramm + + cdef double sum_diag_Gramm_left + cdef double sum_diag_Gramm_right + + cdef double sum_total_Gramm_left + cdef double sum_total_Gramm_right + diff --git a/stpredictions/models/OK3/_criterion.pyx b/stpredictions/models/OK3/_criterion.pyx index 7cd7bbb0e..6767b1e14 100644 --- a/stpredictions/models/OK3/_criterion.pyx +++ b/stpredictions/models/OK3/_criterion.pyx @@ -1,33 +1,23 @@ -# Authors: Gilles Louppe -# Peter Prettenhofer -# Brian Holt -# Noel Dawe -# Satrajit Gosh -# Lars Buitinck -# Arnaud Joly -# Joel Nothman -# Fares Hedayati -# Jacob Schreiber -# Nelson Liu -# -# License: BSD 3 clause +# cython: cdivision=True +# cython: boundscheck=False +# cython: wraparound=False +from libc.stdlib cimport calloc +from libc.stdlib cimport free from libc.string cimport memcpy from libc.string cimport memset from libc.math cimport fabs import numpy as np -cimport numpy as cnp -cnp.import_array() +cimport numpy as np +np.import_array() -from numpy.math cimport INFINITY -from scipy.special.cython_special cimport xlogy +from sklearn.tree._utils cimport log +from sklearn.tree._utils cimport safe_realloc +from sklearn.tree._utils cimport sizet_ptr_to_ndarray +from sklearn.tree._utils cimport WeightedMedianCalculator -from ._utils cimport log -from ._utils cimport WeightedMedianCalculator - -# EPSILON is used in the Poisson criterion -cdef double EPSILON = 10 * np.finfo('double').eps +# from kernel import Kernel cdef class Criterion: """Interface for impurity criteria. @@ -35,21 +25,21 @@ cdef class Criterion: This object stores methods on how to calculate how good a split is using different metrics. """ + + def __dealloc__(self): + """Destructor.""" + + pass + def __getstate__(self): return {} def __setstate__(self, d): pass - cdef int init( - self, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight, - double weighted_n_samples, - const SIZE_t[:] sample_indices, - SIZE_t start, - SIZE_t end, - ) except -1 nogil: + cdef int init(self, const DOUBLE_t[:, ::1] y, DOUBLE_t* sample_weight, + double weighted_n_samples, SIZE_t* samples, SIZE_t start, + SIZE_t end) nogil except -1: """Placeholder for a method which will initialize the criterion. Returns -1 in case of failure to allocate memory (and raise MemoryError) @@ -57,69 +47,71 @@ cdef class Criterion: Parameters ---------- - y : ndarray, dtype=DOUBLE_t - y is a buffer that can store values for n_outputs target variables - stored as a Cython memoryview. - sample_weight : ndarray, dtype=DOUBLE_t - The weight of each sample stored as a Cython memoryview. + y : array-like, dtype=DOUBLE_t + y is a buffer that stores values of the output Gramm matrix of the samples + sample_weight : array-like, dtype=DOUBLE_t + The weight of each sample weighted_n_samples : double The total weight of the samples being considered - sample_indices : ndarray, dtype=SIZE_t - A mask on the samples. Indices of the samples in X and y we want to use, - where sample_indices[start:end] correspond to the samples in this node. + samples : array-like, dtype=SIZE_t + Indices of the samples in X and y, where samples[start:end] + correspond to the samples in this node start : SIZE_t The first sample to be used on this node end : SIZE_t The last sample used on this node """ + pass - cdef int reset(self) except -1 nogil: + cdef int reset(self) nogil except -1: """Reset the criterion at pos=start. This method must be implemented by the subclass. """ + pass - cdef int reverse_reset(self) except -1 nogil: + cdef int reverse_reset(self) nogil except -1: """Reset the criterion at pos=end. This method must be implemented by the subclass. """ pass - cdef int update(self, SIZE_t new_pos) except -1 nogil: - """Updated statistics by moving sample_indices[pos:new_pos] to the left child. + cdef int update(self, SIZE_t new_pos) nogil except -1: + """Updated statistics by moving samples[pos:new_pos] to the left child. - This updates the collected statistics by moving sample_indices[pos:new_pos] + This updates the collected statistics by moving samples[pos:new_pos] from the right child to the left child. It must be implemented by the subclass. Parameters ---------- new_pos : SIZE_t - New starting index position of the sample_indices in the right child + New starting index position of the samples in the right child """ + pass - cdef double node_impurity(self) noexcept nogil: + cdef double node_impurity(self) nogil: """Placeholder for calculating the impurity of the node. Placeholder for a method which will evaluate the impurity of - the current node, i.e. the impurity of sample_indices[start:end]. This is the - primary function of the criterion class. The smaller the impurity the - better. + the current node, i.e. the impurity of samples[start:end]. This is the + primary function of the criterion class. """ + pass cdef void children_impurity(self, double* impurity_left, - double* impurity_right) noexcept nogil: + double* impurity_right) nogil: """Placeholder for calculating the impurity of children. Placeholder for a method which evaluates the impurity in - children nodes, i.e. the impurity of sample_indices[start:pos] + the impurity - of sample_indices[pos:end]. + children nodes, i.e. the impurity of samples[start:pos] + the impurity + of samples[pos:end]. Parameters ---------- @@ -130,23 +122,25 @@ cdef class Criterion: The memory address where the impurity of the right child should be stored """ + pass - cdef void node_value(self, double* dest) noexcept nogil: + cdef void node_value(self, double* dest) nogil: """Placeholder for storing the node value. - Placeholder for a method which will compute the node value - of sample_indices[start:end] and save the value into dest. + Placeholder for a method which will save the weighted + samples[start:end] into dest. Parameters ---------- dest : double pointer The memory address where the node value should be stored. """ + pass - cdef double proxy_impurity_improvement(self) noexcept nogil: - """Compute a proxy of the impurity reduction. + cdef double proxy_impurity_improvement(self) nogil: + """Compute a proxy of the impurity reduction This method is used to speed up the search for the best split. It is a proxy quantity such that the split that maximizes this value @@ -156,17 +150,17 @@ cdef class Criterion: The absolute impurity improvement is only computed by the impurity_improvement method once the best split has been found. """ - cdef double impurity_left - cdef double impurity_right - self.children_impurity(&impurity_left, &impurity_right) + # cdef double impurity_left + # cdef double impurity_right + # self.children_impurity(&impurity_left, &impurity_right) - return (- self.weighted_n_right * impurity_right - - self.weighted_n_left * impurity_left) + # return (- self.weighted_n_right * impurity_right + # - self.weighted_n_left * impurity_left) + + pass - cdef double impurity_improvement(self, double impurity_parent, - double impurity_left, - double impurity_right) noexcept nogil: - """Compute the improvement in impurity. + cdef double impurity_improvement(self, double impurity) nogil: + """Compute the improvement in impurity This method computes the improvement in impurity when a split occurs. The weighted impurity improvement equation is the following: @@ -180,487 +174,92 @@ cdef class Criterion: Parameters ---------- - impurity_parent : double - The initial impurity of the parent node before the split - - impurity_left : double - The impurity of the left child - - impurity_right : double - The impurity of the right child + impurity : double + The initial impurity of the node before the split Return ------ double : improvement in impurity after the split occurs """ - return ((self.weighted_n_node_samples / self.weighted_n_samples) * - (impurity_parent - (self.weighted_n_right / - self.weighted_n_node_samples * impurity_right) - - (self.weighted_n_left / - self.weighted_n_node_samples * impurity_left))) - - -cdef class ClassificationCriterion(Criterion): - """Abstract criterion for classification.""" - def __cinit__(self, SIZE_t n_outputs, - cnp.ndarray[SIZE_t, ndim=1] n_classes): - """Initialize attributes for this criterion. - - Parameters - ---------- - n_outputs : SIZE_t - The number of targets, the dimensionality of the prediction - n_classes : numpy.ndarray, dtype=SIZE_t - The number of unique classes in each target - """ - self.start = 0 - self.pos = 0 - self.end = 0 - - self.n_outputs = n_outputs - self.n_samples = 0 - self.n_node_samples = 0 - self.weighted_n_node_samples = 0.0 - self.weighted_n_left = 0.0 - self.weighted_n_right = 0.0 - - self.n_classes = np.empty(n_outputs, dtype=np.intp) - - cdef SIZE_t k = 0 - cdef SIZE_t max_n_classes = 0 - - # For each target, set the number of unique classes in that target, - # and also compute the maximal stride of all targets - for k in range(n_outputs): - self.n_classes[k] = n_classes[k] - - if n_classes[k] > max_n_classes: - max_n_classes = n_classes[k] - - self.max_n_classes = max_n_classes - - # Count labels for each output - self.sum_total = np.zeros((n_outputs, max_n_classes), dtype=np.float64) - self.sum_left = np.zeros((n_outputs, max_n_classes), dtype=np.float64) - self.sum_right = np.zeros((n_outputs, max_n_classes), dtype=np.float64) - - def __reduce__(self): - return (type(self), - (self.n_outputs, np.asarray(self.n_classes)), self.__getstate__()) - - cdef int init( - self, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight, - double weighted_n_samples, - const SIZE_t[:] sample_indices, - SIZE_t start, - SIZE_t end - ) except -1 nogil: - """Initialize the criterion. - - This initializes the criterion at node sample_indices[start:end] and children - sample_indices[start:start] and sample_indices[start:end]. - - Returns -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - - Parameters - ---------- - y : ndarray, dtype=DOUBLE_t - The target stored as a buffer for memory efficiency. - sample_weight : ndarray, dtype=DOUBLE_t - The weight of each sample stored as a Cython memoryview. - weighted_n_samples : double - The total weight of all samples - sample_indices : ndarray, dtype=SIZE_t - A mask on the samples. Indices of the samples in X and y we want to use, - where sample_indices[start:end] correspond to the samples in this node. - start : SIZE_t - The first sample to use in the mask - end : SIZE_t - The last sample to use in the mask - """ - self.y = y - self.sample_weight = sample_weight - self.sample_indices = sample_indices - self.start = start - self.end = end - self.n_node_samples = end - start - self.weighted_n_samples = weighted_n_samples - self.weighted_n_node_samples = 0.0 - - cdef SIZE_t i - cdef SIZE_t p - cdef SIZE_t k - cdef SIZE_t c - cdef DOUBLE_t w = 1.0 - - for k in range(self.n_outputs): - memset(&self.sum_total[k, 0], 0, self.n_classes[k] * sizeof(double)) - - for p in range(start, end): - i = sample_indices[p] - - # w is originally set to be 1.0, meaning that if no sample weights - # are given, the default weight of each sample is 1.0. - if sample_weight is not None: - w = sample_weight[i] - - # Count weighted class frequency for each target - for k in range(self.n_outputs): - c = self.y[i, k] - self.sum_total[k, c] += w - - self.weighted_n_node_samples += w - - # Reset to pos=start - self.reset() - return 0 - - cdef int reset(self) except -1 nogil: - """Reset the criterion at pos=start. - - Returns -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - self.pos = self.start - - self.weighted_n_left = 0.0 - self.weighted_n_right = self.weighted_n_node_samples - cdef SIZE_t k - - for k in range(self.n_outputs): - memset(&self.sum_left[k, 0], 0, self.n_classes[k] * sizeof(double)) - memcpy(&self.sum_right[k, 0], &self.sum_total[k, 0], self.n_classes[k] * sizeof(double)) - return 0 - - cdef int reverse_reset(self) except -1 nogil: - """Reset the criterion at pos=end. - - Returns -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - self.pos = self.end - - self.weighted_n_left = self.weighted_n_node_samples - self.weighted_n_right = 0.0 - cdef SIZE_t k - - for k in range(self.n_outputs): - memset(&self.sum_right[k, 0], 0, self.n_classes[k] * sizeof(double)) - memcpy(&self.sum_left[k, 0], &self.sum_total[k, 0], self.n_classes[k] * sizeof(double)) - return 0 - - cdef int update(self, SIZE_t new_pos) except -1 nogil: - """Updated statistics by moving sample_indices[pos:new_pos] to the left child. - - Returns -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - - Parameters - ---------- - new_pos : SIZE_t - The new ending position for which to move sample_indices from the right - child to the left child. - """ - cdef SIZE_t pos = self.pos - cdef SIZE_t end = self.end - - cdef const SIZE_t[:] sample_indices = self.sample_indices - cdef const DOUBLE_t[:] sample_weight = self.sample_weight - - cdef SIZE_t i - cdef SIZE_t p - cdef SIZE_t k - cdef SIZE_t c - cdef DOUBLE_t w = 1.0 - - # Update statistics up to new_pos - # - # Given that - # sum_left[x] + sum_right[x] = sum_total[x] - # and that sum_total is known, we are going to update - # sum_left from the direction that require the least amount - # of computations, i.e. from pos to new_pos or from end to new_po. - if (new_pos - pos) <= (end - new_pos): - for p in range(pos, new_pos): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - for k in range(self.n_outputs): - self.sum_left[k, self.y[i, k]] += w - - self.weighted_n_left += w - - else: - self.reverse_reset() - - for p in range(end - 1, new_pos - 1, -1): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - for k in range(self.n_outputs): - self.sum_left[k, self.y[i, k]] -= w - - self.weighted_n_left -= w - - # Update right part statistics - self.weighted_n_right = self.weighted_n_node_samples - self.weighted_n_left - for k in range(self.n_outputs): - for c in range(self.n_classes[k]): - self.sum_right[k, c] = self.sum_total[k, c] - self.sum_left[k, c] - - self.pos = new_pos - return 0 - - cdef double node_impurity(self) noexcept nogil: - pass - - cdef void children_impurity(self, double* impurity_left, - double* impurity_right) noexcept nogil: - pass - - cdef void node_value(self, double* dest) noexcept nogil: - """Compute the node value of sample_indices[start:end] and save it into dest. - - Parameters - ---------- - dest : double pointer - The memory address which we will save the node value into. - """ - cdef SIZE_t k - - for k in range(self.n_outputs): - memcpy(dest, &self.sum_total[k, 0], self.n_classes[k] * sizeof(double)) - dest += self.max_n_classes - - -cdef class Entropy(ClassificationCriterion): - r"""Cross Entropy impurity criterion. - - This handles cases where the target is a classification taking values - 0, 1, ... K-2, K-1. If node m represents a region Rm with Nm observations, - then let - - count_k = 1 / Nm \sum_{x_i in Rm} I(yi = k) - - be the proportion of class k observations in node m. - - The cross-entropy is then defined as - - cross-entropy = -\sum_{k=0}^{K-1} count_k log(count_k) - """ - - cdef double node_impurity(self) noexcept nogil: - """Evaluate the impurity of the current node. - - Evaluate the cross-entropy criterion as impurity of the current node, - i.e. the impurity of sample_indices[start:end]. The smaller the impurity the - better. - """ - cdef double entropy = 0.0 - cdef double count_k - cdef SIZE_t k - cdef SIZE_t c - - for k in range(self.n_outputs): - for c in range(self.n_classes[k]): - count_k = self.sum_total[k, c] - if count_k > 0.0: - count_k /= self.weighted_n_node_samples - entropy -= count_k * log(count_k) - - return entropy / self.n_outputs - - cdef void children_impurity(self, double* impurity_left, - double* impurity_right) noexcept nogil: - """Evaluate the impurity in children nodes. - - i.e. the impurity of the left child (sample_indices[start:pos]) and the - impurity the right child (sample_indices[pos:end]). - - Parameters - ---------- - impurity_left : double pointer - The memory address to save the impurity of the left node - impurity_right : double pointer - The memory address to save the impurity of the right node - """ - cdef double entropy_left = 0.0 - cdef double entropy_right = 0.0 - cdef double count_k - cdef SIZE_t k - cdef SIZE_t c - - for k in range(self.n_outputs): - for c in range(self.n_classes[k]): - count_k = self.sum_left[k, c] - if count_k > 0.0: - count_k /= self.weighted_n_left - entropy_left -= count_k * log(count_k) - - count_k = self.sum_right[k, c] - if count_k > 0.0: - count_k /= self.weighted_n_right - entropy_right -= count_k * log(count_k) - - impurity_left[0] = entropy_left / self.n_outputs - impurity_right[0] = entropy_right / self.n_outputs - - -cdef class Gini(ClassificationCriterion): - r"""Gini Index impurity criterion. - - This handles cases where the target is a classification taking values - 0, 1, ... K-2, K-1. If node m represents a region Rm with Nm observations, - then let - - count_k = 1/ Nm \sum_{x_i in Rm} I(yi = k) - - be the proportion of class k observations in node m. - - The Gini Index is then defined as: - - index = \sum_{k=0}^{K-1} count_k (1 - count_k) - = 1 - \sum_{k=0}^{K-1} count_k ** 2 - """ + cdef double impurity_left + cdef double impurity_right - cdef double node_impurity(self) noexcept nogil: - """Evaluate the impurity of the current node. + self.children_impurity(&impurity_left, &impurity_right) - Evaluate the Gini criterion as impurity of the current node, - i.e. the impurity of sample_indices[start:end]. The smaller the impurity the - better. - """ - cdef double gini = 0.0 - cdef double sq_count - cdef double count_k - cdef SIZE_t k - cdef SIZE_t c + return ((self.weighted_n_node_samples / self.weighted_n_samples) * + (impurity - (self.weighted_n_right / + self.weighted_n_node_samples * impurity_right) + - (self.weighted_n_left / + self.weighted_n_node_samples * impurity_left))) - for k in range(self.n_outputs): - sq_count = 0.0 - for c in range(self.n_classes[k]): - count_k = self.sum_total[k, c] - sq_count += count_k * count_k - gini += 1.0 - sq_count / (self.weighted_n_node_samples * - self.weighted_n_node_samples) - return gini / self.n_outputs - cdef void children_impurity(self, double* impurity_left, - double* impurity_right) noexcept nogil: - """Evaluate the impurity in children nodes. - i.e. the impurity of the left child (sample_indices[start:pos]) and the - impurity the right child (sample_indices[pos:end]) using the Gini index. - Parameters - ---------- - impurity_left : double pointer - The memory address to save the impurity of the left node to - impurity_right : double pointer - The memory address to save the impurity of the right node to - """ - cdef double gini_left = 0.0 - cdef double gini_right = 0.0 - cdef double sq_count_left - cdef double sq_count_right - cdef double count_k - cdef SIZE_t k - cdef SIZE_t c - - for k in range(self.n_outputs): - sq_count_left = 0.0 - sq_count_right = 0.0 - - for c in range(self.n_classes[k]): - count_k = self.sum_left[k, c] - sq_count_left += count_k * count_k - count_k = self.sum_right[k, c] - sq_count_right += count_k * count_k - gini_left += 1.0 - sq_count_left / (self.weighted_n_left * - self.weighted_n_left) - gini_right += 1.0 - sq_count_right / (self.weighted_n_right * - self.weighted_n_right) - impurity_left[0] = gini_left / self.n_outputs - impurity_right[0] = gini_right / self.n_outputs -cdef class RegressionCriterion(Criterion): - r"""Abstract regression criterion. - This handles cases where the target is a continuous value, and is - evaluated by computing the variance of the target values left and right - of the split point. The computation takes linear time with `n_samples` - by using :: +cdef class KernelizedRegressionCriterion(Criterion): + r"""Abstract kernelized output regression criterion. - var = \sum_i^n (y_i - y_bar) ** 2 - = (\sum_i^n y_i ** 2) - n_samples * y_bar ** 2 + This handles cases where the target is a structured object and the Gramm + matrix (the matrix of the kernel evaluated at the output samples) is given + as y. The impurity is evaluated by computing the variance of the target + values (embedded in a larger Hilbert space) left and right of the split point. """ - def __cinit__(self, SIZE_t n_outputs, SIZE_t n_samples): + def __cinit__(self, SIZE_t n_samples): """Initialize parameters for this criterion. Parameters ---------- - n_outputs : SIZE_t - The number of targets to be predicted - n_samples : SIZE_t The total number of samples to fit on """ + # Default values + self.sample_weight = NULL + + self.samples = NULL self.start = 0 self.pos = 0 self.end = 0 - self.n_outputs = n_outputs self.n_samples = n_samples self.n_node_samples = 0 self.weighted_n_node_samples = 0.0 self.weighted_n_left = 0.0 self.weighted_n_right = 0.0 - self.sq_sum_total = 0.0 + self.sum_diag_Gramm = 0.0 + self.sum_total_Gramm = 0.0 + + self.sum_diag_Gramm_left = 0.0 + self.sum_diag_Gramm_right = 0.0 + + self.sum_total_Gramm_left = 0.0 + self.sum_total_Gramm_right = 0.0 - self.sum_total = np.zeros(n_outputs, dtype=np.float64) - self.sum_left = np.zeros(n_outputs, dtype=np.float64) - self.sum_right = np.zeros(n_outputs, dtype=np.float64) def __reduce__(self): - return (type(self), (self.n_outputs, self.n_samples), self.__getstate__()) - - cdef int init( - self, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight, - double weighted_n_samples, - const SIZE_t[:] sample_indices, - SIZE_t start, - SIZE_t end, - ) except -1 nogil: - """Initialize the criterion. - - This initializes the criterion at node sample_indices[start:end] and children - sample_indices[start:start] and sample_indices[start:end]. - """ + return (type(self), (self.n_samples,), self.__getstate__()) + + cdef int init(self, const DOUBLE_t[:, ::1] y, DOUBLE_t* sample_weight, + double weighted_n_samples, SIZE_t* samples, SIZE_t start, + SIZE_t end) nogil except -1: + """Initialize the criterion at node samples[start:end] and + children samples[start:start] and samples[start:end].""" # Initialize fields self.y = y self.sample_weight = sample_weight - self.sample_indices = sample_indices + self.samples = samples self.start = start self.end = end self.n_node_samples = end - start @@ -668,603 +267,202 @@ cdef class RegressionCriterion(Criterion): self.weighted_n_node_samples = 0. cdef SIZE_t i + cdef SIZE_t j cdef SIZE_t p - cdef SIZE_t k - cdef DOUBLE_t y_ik - cdef DOUBLE_t w_y_ik - cdef DOUBLE_t w = 1.0 - self.sq_sum_total = 0.0 - memset(&self.sum_total[0], 0, self.n_outputs * sizeof(double)) + cdef SIZE_t q + cdef DOUBLE_t w_i = 1.0 + cdef DOUBLE_t w_j = 1.0 + + self.sum_diag_Gramm = 0.0 + self.sum_total_Gramm = 0.0 + + self.sum_diag_Gramm_left = 0.0 + self.sum_diag_Gramm_right = 0.0 + + self.sum_total_Gramm_left = 0.0 + self.sum_total_Gramm_right = 0.0 for p in range(start, end): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - for k in range(self.n_outputs): - y_ik = self.y[i, k] - w_y_ik = w * y_ik - self.sum_total[k] += w_y_ik - self.sq_sum_total += w_y_ik * y_ik - - self.weighted_n_node_samples += w + i = samples[p] + # with gil: + # print("print samples :",i) + + if sample_weight != NULL: + w_i = sample_weight[i] + + self.weighted_n_node_samples += w_i + + self.sum_diag_Gramm += w_i * self.y[i,i] + + for q in range(start, end): + j = samples[q] + + if sample_weight != NULL: + w_j = sample_weight[j] + + self.sum_total_Gramm += w_i * w_j * self.y[i,j] # Reset to pos=start self.reset() + # with gil: + # print("print sum diag :",self.sum_diag_Gramm) + # print("print sum total :",self.sum_total_Gramm) + # print("print weighted_n_node_samples :",self.weighted_n_node_samples) return 0 - cdef int reset(self) except -1 nogil: + cdef int reset(self) nogil except -1: """Reset the criterion at pos=start.""" - cdef SIZE_t n_bytes = self.n_outputs * sizeof(double) - memset(&self.sum_left[0], 0, n_bytes) - memcpy(&self.sum_right[0], &self.sum_total[0], n_bytes) - + + self.sum_diag_Gramm_left = 0.0 + self.sum_diag_Gramm_right = self.sum_diag_Gramm + + self.sum_total_Gramm_left = 0.0 + self.sum_total_Gramm_right = self.sum_total_Gramm + self.weighted_n_left = 0.0 self.weighted_n_right = self.weighted_n_node_samples self.pos = self.start return 0 - cdef int reverse_reset(self) except -1 nogil: + cdef int reverse_reset(self) nogil except -1: """Reset the criterion at pos=end.""" - cdef SIZE_t n_bytes = self.n_outputs * sizeof(double) - memset(&self.sum_right[0], 0, n_bytes) - memcpy(&self.sum_left[0], &self.sum_total[0], n_bytes) + + self.sum_diag_Gramm_right = 0.0 + self.sum_diag_Gramm_left = self.sum_diag_Gramm + + self.sum_total_Gramm_right = 0.0 + self.sum_total_Gramm_left = self.sum_total_Gramm self.weighted_n_right = 0.0 self.weighted_n_left = self.weighted_n_node_samples self.pos = self.end return 0 - cdef int update(self, SIZE_t new_pos) except -1 nogil: - """Updated statistics by moving sample_indices[pos:new_pos] to the left.""" - cdef const DOUBLE_t[:] sample_weight = self.sample_weight - cdef const SIZE_t[:] sample_indices = self.sample_indices + cdef int update(self, SIZE_t new_pos) nogil except -1: + """Updated statistics by moving samples[pos:new_pos] to the left.""" + cdef double* sample_weight = self.sample_weight + cdef SIZE_t* samples = self.samples + + cdef SIZE_t start = self.start cdef SIZE_t pos = self.pos cdef SIZE_t end = self.end + cdef SIZE_t i + cdef SIZE_t j cdef SIZE_t p - cdef SIZE_t k - cdef DOUBLE_t w = 1.0 + cdef SIZE_t q + cdef DOUBLE_t w_i = 1.0 + cdef DOUBLE_t w_j = 1.0 # Update statistics up to new_pos - # - # Given that - # sum_left[x] + sum_right[x] = sum_total[x] - # and that sum_total is known, we are going to update - # sum_left from the direction that require the least amount - # of computations, i.e. from pos to new_pos or from end to new_pos. - if (new_pos - pos) <= (end - new_pos): - for p in range(pos, new_pos): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - for k in range(self.n_outputs): - self.sum_left[k] += w * self.y[i, k] - - self.weighted_n_left += w - else: - self.reverse_reset() - - for p in range(end - 1, new_pos - 1, -1): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - for k in range(self.n_outputs): - self.sum_left[k] -= w * self.y[i, k] - - self.weighted_n_left -= w - self.weighted_n_right = (self.weighted_n_node_samples - - self.weighted_n_left) - for k in range(self.n_outputs): - self.sum_right[k] = self.sum_total[k] - self.sum_left[k] + for p in range(pos, new_pos): + i = samples[p] + + if sample_weight != NULL: + w_i = sample_weight[i] + + self.sum_diag_Gramm_left += w_i * self.y[i,i] + + self.sum_diag_Gramm_right -= w_i * self.y[i,i] + + self.weighted_n_left += w_i + + self.weighted_n_right -= w_i + + for q in range(start, pos): + j = samples[q] + + if sample_weight != NULL: + w_j = sample_weight[j] + + self.sum_total_Gramm_left += 2 * w_i * w_j * self.y[i,j] + + for q in range(pos, new_pos): + j = samples[q] + + if sample_weight != NULL: + w_j = sample_weight[j] + + self.sum_total_Gramm_left += w_i * w_j * self.y[i,j] + + self.sum_total_Gramm_right -= w_i * w_j * self.y[i,j] + + for p in range(new_pos, end): + i = samples[p] + + if sample_weight != NULL: + w_i = sample_weight[i] + + for q in range(pos, new_pos): + j = samples[q] + + if sample_weight != NULL: + w_j = sample_weight[j] + + self.sum_total_Gramm_right -= 2 * w_i * w_j * self.y[i,j] self.pos = new_pos return 0 - cdef double node_impurity(self) noexcept nogil: + cdef double node_impurity(self) nogil: pass - cdef void children_impurity(self, double* impurity_left, - double* impurity_right) noexcept nogil: + cdef void children_impurity(self, double* impurity_left, double* impurity_right) nogil: pass - cdef void node_value(self, double* dest) noexcept nogil: - """Compute the node value of sample_indices[start:end] into dest.""" - cdef SIZE_t k - - for k in range(self.n_outputs): - dest[k] = self.sum_total[k] / self.weighted_n_node_samples - + cdef void node_value(self, double* dest) nogil: + """Compute the node value of samples[start:end] into dest.""" -cdef class MSE(RegressionCriterion): - """Mean squared error impurity criterion. - - MSE = var_left + var_right - """ - - cdef double node_impurity(self) noexcept nogil: - """Evaluate the impurity of the current node. - - Evaluate the MSE criterion as impurity of the current node, - i.e. the impurity of sample_indices[start:end]. The smaller the impurity the - better. - """ - cdef double impurity - cdef SIZE_t k - - impurity = self.sq_sum_total / self.weighted_n_node_samples - for k in range(self.n_outputs): - impurity -= (self.sum_total[k] / self.weighted_n_node_samples)**2.0 - - return impurity / self.n_outputs - - cdef double proxy_impurity_improvement(self) noexcept nogil: - """Compute a proxy of the impurity reduction. - - This method is used to speed up the search for the best split. - It is a proxy quantity such that the split that maximizes this value - also maximizes the impurity improvement. It neglects all constant terms - of the impurity decrease for a given split. - - The absolute impurity improvement is only computed by the - impurity_improvement method once the best split has been found. - - The MSE proxy is derived from - - sum_{i left}(y_i - y_pred_L)^2 + sum_{i right}(y_i - y_pred_R)^2 - = sum(y_i^2) - n_L * mean_{i left}(y_i)^2 - n_R * mean_{i right}(y_i)^2 - - Neglecting constant terms, this gives: - - - 1/n_L * sum_{i left}(y_i)^2 - 1/n_R * sum_{i right}(y_i)^2 - """ - cdef SIZE_t k - cdef double proxy_impurity_left = 0.0 - cdef double proxy_impurity_right = 0.0 - - for k in range(self.n_outputs): - proxy_impurity_left += self.sum_left[k] * self.sum_left[k] - proxy_impurity_right += self.sum_right[k] * self.sum_right[k] - - return (proxy_impurity_left / self.weighted_n_left + - proxy_impurity_right / self.weighted_n_right) - - cdef void children_impurity(self, double* impurity_left, - double* impurity_right) noexcept nogil: - """Evaluate the impurity in children nodes. - - i.e. the impurity of the left child (sample_indices[start:pos]) and the - impurity the right child (sample_indices[pos:end]). - """ - cdef const DOUBLE_t[:] sample_weight = self.sample_weight - cdef const SIZE_t[:] sample_indices = self.sample_indices - cdef SIZE_t pos = self.pos - cdef SIZE_t start = self.start - - cdef DOUBLE_t y_ik - - cdef double sq_sum_left = 0.0 - cdef double sq_sum_right - - cdef SIZE_t i cdef SIZE_t p cdef SIZE_t k cdef DOUBLE_t w = 1.0 - for p in range(start, pos): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - for k in range(self.n_outputs): - y_ik = self.y[i, k] - sq_sum_left += w * y_ik * y_ik - - sq_sum_right = self.sq_sum_total - sq_sum_left - - impurity_left[0] = sq_sum_left / self.weighted_n_left - impurity_right[0] = sq_sum_right / self.weighted_n_right - - for k in range(self.n_outputs): - impurity_left[0] -= (self.sum_left[k] / self.weighted_n_left) ** 2.0 - impurity_right[0] -= (self.sum_right[k] / self.weighted_n_right) ** 2.0 - - impurity_left[0] /= self.n_outputs - impurity_right[0] /= self.n_outputs - - -cdef class MAE(RegressionCriterion): - r"""Mean absolute error impurity criterion. - - MAE = (1 / n)*(\sum_i |y_i - f_i|), where y_i is the true - value and f_i is the predicted value.""" + for p in range(self.start, self.end): + + k = self.samples[p] + + if self.sample_weight != NULL: + w = self.sample_weight[k] + + dest[k] = w / self.weighted_n_node_samples - cdef cnp.ndarray left_child - cdef cnp.ndarray right_child - cdef void** left_child_ptr - cdef void** right_child_ptr - cdef DOUBLE_t[::1] node_medians - - def __cinit__(self, SIZE_t n_outputs, SIZE_t n_samples): - """Initialize parameters for this criterion. - - Parameters - ---------- - n_outputs : SIZE_t - The number of targets to be predicted - - n_samples : SIZE_t - The total number of samples to fit on - """ - # Default values - self.start = 0 - self.pos = 0 - self.end = 0 - self.n_outputs = n_outputs - self.n_samples = n_samples - self.n_node_samples = 0 - self.weighted_n_node_samples = 0.0 - self.weighted_n_left = 0.0 - self.weighted_n_right = 0.0 - self.node_medians = np.zeros(n_outputs, dtype=np.float64) - - self.left_child = np.empty(n_outputs, dtype='object') - self.right_child = np.empty(n_outputs, dtype='object') - # initialize WeightedMedianCalculators - for k in range(n_outputs): - self.left_child[k] = WeightedMedianCalculator(n_samples) - self.right_child[k] = WeightedMedianCalculator(n_samples) - - self.left_child_ptr = cnp.PyArray_DATA(self.left_child) - self.right_child_ptr = cnp.PyArray_DATA(self.right_child) - - cdef int init( - self, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight, - double weighted_n_samples, - const SIZE_t[:] sample_indices, - SIZE_t start, - SIZE_t end, - ) except -1 nogil: - """Initialize the criterion. - - This initializes the criterion at node sample_indices[start:end] and children - sample_indices[start:start] and sample_indices[start:end]. - """ - cdef SIZE_t i, p, k - cdef DOUBLE_t w = 1.0 - # Initialize fields - self.y = y - self.sample_weight = sample_weight - self.sample_indices = sample_indices - self.start = start - self.end = end - self.n_node_samples = end - start - self.weighted_n_samples = weighted_n_samples - self.weighted_n_node_samples = 0. - cdef void** left_child = self.left_child_ptr - cdef void** right_child = self.right_child_ptr - for k in range(self.n_outputs): - ( left_child[k]).reset() - ( right_child[k]).reset() - for p in range(start, end): - i = sample_indices[p] - if sample_weight is not None: - w = sample_weight[i] - for k in range(self.n_outputs): - # push method ends up calling safe_realloc, hence `except -1` - # push all values to the right side, - # since pos = start initially anyway - ( right_child[k]).push(self.y[i, k], w) - self.weighted_n_node_samples += w - # calculate the node medians - for k in range(self.n_outputs): - self.node_medians[k] = ( right_child[k]).get_median() - # Reset to pos=start - self.reset() - return 0 - cdef int reset(self) except -1 nogil: - """Reset the criterion at pos=start. - Returns -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - cdef SIZE_t i, k - cdef DOUBLE_t value - cdef DOUBLE_t weight - cdef void** left_child = self.left_child_ptr - cdef void** right_child = self.right_child_ptr - self.weighted_n_left = 0.0 - self.weighted_n_right = self.weighted_n_node_samples - self.pos = self.start - - # reset the WeightedMedianCalculators, left should have no - # elements and right should have all elements. - - for k in range(self.n_outputs): - # if left has no elements, it's already reset - for i in range(( left_child[k]).size()): - # remove everything from left and put it into right - ( left_child[k]).pop(&value, - &weight) - # push method ends up calling safe_realloc, hence `except -1` - ( right_child[k]).push(value, - weight) - return 0 - - cdef int reverse_reset(self) except -1 nogil: - """Reset the criterion at pos=end. - - Returns -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - self.weighted_n_right = 0.0 - self.weighted_n_left = self.weighted_n_node_samples - self.pos = self.end - - cdef DOUBLE_t value - cdef DOUBLE_t weight - cdef void** left_child = self.left_child_ptr - cdef void** right_child = self.right_child_ptr - - # reverse reset the WeightedMedianCalculators, right should have no - # elements and left should have all elements. - for k in range(self.n_outputs): - # if right has no elements, it's already reset - for i in range(( right_child[k]).size()): - # remove everything from right and put it into left - ( right_child[k]).pop(&value, - &weight) - # push method ends up calling safe_realloc, hence `except -1` - ( left_child[k]).push(value, - weight) - return 0 - - cdef int update(self, SIZE_t new_pos) except -1 nogil: - """Updated statistics by moving sample_indices[pos:new_pos] to the left. - - Returns -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - cdef const DOUBLE_t[:] sample_weight = self.sample_weight - cdef const SIZE_t[:] sample_indices = self.sample_indices - - cdef void** left_child = self.left_child_ptr - cdef void** right_child = self.right_child_ptr - - cdef SIZE_t pos = self.pos - cdef SIZE_t end = self.end - cdef SIZE_t i, p, k - cdef DOUBLE_t w = 1.0 - - # Update statistics up to new_pos - # - # We are going to update right_child and left_child - # from the direction that require the least amount of - # computations, i.e. from pos to new_pos or from end to new_pos. - if (new_pos - pos) <= (end - new_pos): - for p in range(pos, new_pos): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - for k in range(self.n_outputs): - # remove y_ik and its weight w from right and add to left - ( right_child[k]).remove(self.y[i, k], w) - # push method ends up calling safe_realloc, hence except -1 - ( left_child[k]).push(self.y[i, k], w) - - self.weighted_n_left += w - else: - self.reverse_reset() - - for p in range(end - 1, new_pos - 1, -1): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - for k in range(self.n_outputs): - # remove y_ik and its weight w from left and add to right - ( left_child[k]).remove(self.y[i, k], w) - ( right_child[k]).push(self.y[i, k], w) - - self.weighted_n_left -= w - - self.weighted_n_right = (self.weighted_n_node_samples - - self.weighted_n_left) - self.pos = new_pos - return 0 - - cdef void node_value(self, double* dest) noexcept nogil: - """Computes the node value of sample_indices[start:end] into dest.""" - cdef SIZE_t k - for k in range(self.n_outputs): - dest[k] = self.node_medians[k] - - cdef double node_impurity(self) noexcept nogil: - """Evaluate the impurity of the current node. - - Evaluate the MAE criterion as impurity of the current node, - i.e. the impurity of sample_indices[start:end]. The smaller the impurity the - better. - """ - cdef const DOUBLE_t[:] sample_weight = self.sample_weight - cdef const SIZE_t[:] sample_indices = self.sample_indices - cdef SIZE_t i, p, k - cdef DOUBLE_t w = 1.0 - cdef DOUBLE_t impurity = 0.0 - - for k in range(self.n_outputs): - for p in range(self.start, self.end): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - impurity += fabs(self.y[i, k] - self.node_medians[k]) * w - - return impurity / (self.weighted_n_node_samples * self.n_outputs) - - cdef void children_impurity(self, double* p_impurity_left, - double* p_impurity_right) noexcept nogil: - """Evaluate the impurity in children nodes. - - i.e. the impurity of the left child (sample_indices[start:pos]) and the - impurity the right child (sample_indices[pos:end]). - """ - cdef const DOUBLE_t[:] sample_weight = self.sample_weight - cdef const SIZE_t[:] sample_indices = self.sample_indices - - cdef SIZE_t start = self.start - cdef SIZE_t pos = self.pos - cdef SIZE_t end = self.end - - cdef SIZE_t i, p, k - cdef DOUBLE_t median - cdef DOUBLE_t w = 1.0 - cdef DOUBLE_t impurity_left = 0.0 - cdef DOUBLE_t impurity_right = 0.0 - - cdef void** left_child = self.left_child_ptr - cdef void** right_child = self.right_child_ptr - - for k in range(self.n_outputs): - median = ( left_child[k]).get_median() - for p in range(start, pos): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - impurity_left += fabs(self.y[i, k] - median) * w - p_impurity_left[0] = impurity_left / (self.weighted_n_left * - self.n_outputs) - - for k in range(self.n_outputs): - median = ( right_child[k]).get_median() - for p in range(pos, end): - i = sample_indices[p] - - if sample_weight is not None: - w = sample_weight[i] - - impurity_right += fabs(self.y[i, k] - median) * w - p_impurity_right[0] = impurity_right / (self.weighted_n_right * - self.n_outputs) - - -cdef class FriedmanMSE(MSE): - """Mean squared error impurity criterion with improvement score by Friedman. - - Uses the formula (35) in Friedman's original Gradient Boosting paper: +cdef class KernelizedMSE(KernelizedRegressionCriterion): + """Mean squared error impurity criterion. + + var = \sum_i^n (phi(y_i) - phi(y)_bar) ** 2 + = (\sum_i^n phi(y_i) ** 2) - n_samples * phi(y)_bar ** 2 - diff = mean_left - mean_right - improvement = n_left * n_right * diff^2 / (n_left + n_right) + MSE = var_left + var_right """ - cdef double proxy_impurity_improvement(self) noexcept nogil: - """Compute a proxy of the impurity reduction. - - This method is used to speed up the search for the best split. - It is a proxy quantity such that the split that maximizes this value - also maximizes the impurity improvement. It neglects all constant terms - of the impurity decrease for a given split. - - The absolute impurity improvement is only computed by the - impurity_improvement method once the best split has been found. - """ - cdef double total_sum_left = 0.0 - cdef double total_sum_right = 0.0 - - cdef SIZE_t k - cdef double diff = 0.0 - - for k in range(self.n_outputs): - total_sum_left += self.sum_left[k] - total_sum_right += self.sum_right[k] - - diff = (self.weighted_n_right * total_sum_left - - self.weighted_n_left * total_sum_right) - - return diff * diff / (self.weighted_n_left * self.weighted_n_right) - - cdef double impurity_improvement(self, double impurity_parent, double - impurity_left, double impurity_right) noexcept nogil: - # Note: none of the arguments are used here - cdef double total_sum_left = 0.0 - cdef double total_sum_right = 0.0 + cdef double node_impurity(self) nogil: + """Evaluate the impurity of the current node, i.e. the impurity of + samples[start:end].""" - cdef SIZE_t k - cdef double diff = 0.0 - - for k in range(self.n_outputs): - total_sum_left += self.sum_left[k] - total_sum_right += self.sum_right[k] - - diff = (self.weighted_n_right * total_sum_left - - self.weighted_n_left * total_sum_right) / self.n_outputs - - return (diff * diff / (self.weighted_n_left * self.weighted_n_right * - self.weighted_n_node_samples)) + cdef double impurity + impurity = self.sum_diag_Gramm / self.weighted_n_node_samples - self.sum_total_Gramm / (self.weighted_n_node_samples)**2 -cdef class Poisson(RegressionCriterion): - """Half Poisson deviance as impurity criterion. + return impurity - Poisson deviance = 2/n * sum(y_true * log(y_true/y_pred) + y_pred - y_true) - - Note that the deviance is >= 0, and since we have `y_pred = mean(y_true)` - at the leaves, one always has `sum(y_pred - y_true) = 0`. It remains the - implemented impurity (factor 2 is skipped): - 1/n * sum(y_true * log(y_true/y_pred) - """ - # FIXME in 1.0: - # min_impurity_split with default = 0 forces us to use a non-negative - # impurity like the Poisson deviance. Without this restriction, one could - # throw away the 'constant' term sum(y_true * log(y_true)) and just use - # Poisson loss = - 1/n * sum(y_true * log(y_pred)) - # = - 1/n * sum(y_true * log(mean(y_true)) - # = - mean(y_true) * log(mean(y_true)) - # With this trick (used in proxy_impurity_improvement()), as for MSE, - # children_impurity would only need to go over left xor right split, not - # both. This could be faster. - - cdef double node_impurity(self) noexcept nogil: - """Evaluate the impurity of the current node. - - Evaluate the Poisson criterion as impurity of the current node, - i.e. the impurity of sample_indices[start:end]. The smaller the impurity the - better. - """ - return self.poisson_loss(self.start, self.end, self.sum_total, - self.weighted_n_node_samples) - - cdef double proxy_impurity_improvement(self) noexcept nogil: - """Compute a proxy of the impurity reduction. + cdef double proxy_impurity_improvement(self) nogil: + """Compute a proxy of the impurity reduction This method is used to speed up the search for the best split. It is a proxy quantity such that the split that maximizes this value @@ -1273,92 +471,25 @@ cdef class Poisson(RegressionCriterion): The absolute impurity improvement is only computed by the impurity_improvement method once the best split has been found. - - The Poisson proxy is derived from: - - sum_{i left }(y_i * log(y_i / y_pred_L)) - + sum_{i right}(y_i * log(y_i / y_pred_R)) - = sum(y_i * log(y_i) - n_L * mean_{i left}(y_i) * log(mean_{i left}(y_i)) - - n_R * mean_{i right}(y_i) * log(mean_{i right}(y_i)) - - Neglecting constant terms, this gives - - - sum{i left }(y_i) * log(mean{i left}(y_i)) - - sum{i right}(y_i) * log(mean{i right}(y_i)) """ - cdef SIZE_t k - cdef double proxy_impurity_left = 0.0 - cdef double proxy_impurity_right = 0.0 - cdef double y_mean_left = 0. - cdef double y_mean_right = 0. - - for k in range(self.n_outputs): - if (self.sum_left[k] <= EPSILON) or (self.sum_right[k] <= EPSILON): - # Poisson loss does not allow non-positive predictions. We - # therefore forbid splits that have child nodes with - # sum(y_i) <= 0. - # Since sum_right = sum_total - sum_left, it can lead to - # floating point rounding error and will not give zero. Thus, - # we relax the above comparison to sum(y_i) <= EPSILON. - return -INFINITY - else: - y_mean_left = self.sum_left[k] / self.weighted_n_left - y_mean_right = self.sum_right[k] / self.weighted_n_right - proxy_impurity_left -= self.sum_left[k] * log(y_mean_left) - proxy_impurity_right -= self.sum_right[k] * log(y_mean_right) - - return - proxy_impurity_left - proxy_impurity_right - - cdef void children_impurity(self, double* impurity_left, - double* impurity_right) noexcept nogil: - """Evaluate the impurity in children nodes. - - i.e. the impurity of the left child (sample_indices[start:pos]) and the - impurity of the right child (sample_indices[pos:end]) for Poisson. - """ - cdef SIZE_t start = self.start - cdef SIZE_t pos = self.pos - cdef SIZE_t end = self.end - - impurity_left[0] = self.poisson_loss(start, pos, self.sum_left, - self.weighted_n_left) - impurity_right[0] = self.poisson_loss(pos, end, self.sum_right, - self.weighted_n_right) + cdef double proxy_impurity_left = self.sum_diag_Gramm_left - self.sum_total_Gramm_left / self.weighted_n_left + cdef double proxy_impurity_right = self.sum_diag_Gramm_right - self.sum_total_Gramm_right / self.weighted_n_right - cdef inline DOUBLE_t poisson_loss(self, - SIZE_t start, - SIZE_t end, - const double[::1] y_sum, - DOUBLE_t weight_sum) noexcept nogil: - """Helper function to compute Poisson loss (~deviance) of a given node. - """ - cdef const DOUBLE_t[:, ::1] y = self.y - cdef const DOUBLE_t[:] sample_weight = self.sample_weight - cdef const SIZE_t[:] sample_indices = self.sample_indices - - cdef DOUBLE_t y_mean = 0. - cdef DOUBLE_t poisson_loss = 0. - cdef DOUBLE_t w = 1.0 - cdef SIZE_t i, k, p - cdef SIZE_t n_outputs = self.n_outputs + return (- proxy_impurity_left - proxy_impurity_right) - for k in range(n_outputs): - if y_sum[k] <= EPSILON: - # y_sum could be computed from the subtraction - # sum_right = sum_total - sum_left leading to a potential - # floating point rounding error. - # Thus, we relax the comparison y_sum <= 0 to - # y_sum <= EPSILON. - return INFINITY + cdef void children_impurity(self, double* impurity_left, double* impurity_right) nogil: + """Evaluate the impurity in children nodes, i.e. the impurity of the + left child (samples[start:pos]) and the impurity the right child + (samples[pos:end]).""" - y_mean = y_sum[k] / weight_sum + cdef double sum_diag_Gramm_left = self.sum_diag_Gramm_left + cdef double sum_diag_Gramm_right = self.sum_diag_Gramm_right + + cdef double sum_total_Gramm_left = self.sum_total_Gramm_left + cdef double sum_total_Gramm_right = self.sum_total_Gramm_right - for p in range(start, end): - i = sample_indices[p] + impurity_left[0] = sum_diag_Gramm_left / self.weighted_n_left - sum_total_Gramm_left / (self.weighted_n_left)**2 + impurity_right[0] = sum_diag_Gramm_right / self.weighted_n_right - sum_total_Gramm_right / (self.weighted_n_right)**2 - if sample_weight is not None: - w = sample_weight[i] - poisson_loss += w * xlogy(y[i, k], y[i, k] / y_mean) - return poisson_loss / (weight_sum * n_outputs) diff --git a/stpredictions/models/OK3/_export.py b/stpredictions/models/OK3/_export.py deleted file mode 100644 index 3e65c4a2b..000000000 --- a/stpredictions/models/OK3/_export.py +++ /dev/null @@ -1,1097 +0,0 @@ -""" -This module defines export functions for decision trees. -""" - -# Authors: Gilles Louppe -# Peter Prettenhofer -# Brian Holt -# Noel Dawe -# Satrajit Gosh -# Trevor Stephens -# Li Li -# Giuseppe Vettigli -# License: BSD 3 clause -from io import StringIO -from numbers import Integral - -import numpy as np - -from ..utils.validation import check_is_fitted -from ..base import is_classifier - -from . import _criterion -from . import _tree -from ._reingold_tilford import buchheim, Tree -from . import DecisionTreeClassifier - - -def _color_brew(n): - """Generate n colors with equally spaced hues. - - Parameters - ---------- - n : int - The number of colors required. - - Returns - ------- - color_list : list, length n - List of n tuples of form (R, G, B) being the components of each color. - """ - color_list = [] - - # Initialize saturation & value; calculate chroma & value shift - s, v = 0.75, 0.9 - c = s * v - m = v - c - - for h in np.arange(25, 385, 360.0 / n).astype(int): - # Calculate some intermediate values - h_bar = h / 60.0 - x = c * (1 - abs((h_bar % 2) - 1)) - # Initialize RGB with same hue & chroma as our color - rgb = [ - (c, x, 0), - (x, c, 0), - (0, c, x), - (0, x, c), - (x, 0, c), - (c, 0, x), - (c, x, 0), - ] - r, g, b = rgb[int(h_bar)] - # Shift the initial RGB values to match value and store - rgb = [(int(255 * (r + m))), (int(255 * (g + m))), (int(255 * (b + m)))] - color_list.append(rgb) - - return color_list - - -class Sentinel: - def __repr__(self): - return '"tree.dot"' - - -SENTINEL = Sentinel() - - -def plot_tree( - decision_tree, - *, - max_depth=None, - feature_names=None, - class_names=None, - label="all", - filled=False, - impurity=True, - node_ids=False, - proportion=False, - rounded=False, - precision=3, - ax=None, - fontsize=None, -): - """Plot a decision tree. - - The sample counts that are shown are weighted with any sample_weights that - might be present. - - The visualization is fit automatically to the size of the axis. - Use the ``figsize`` or ``dpi`` arguments of ``plt.figure`` to control - the size of the rendering. - - Read more in the :ref:`User Guide `. - - .. versionadded:: 0.21 - - Parameters - ---------- - decision_tree : decision tree regressor or classifier - The decision tree to be plotted. - - max_depth : int, default=None - The maximum depth of the representation. If None, the tree is fully - generated. - - feature_names : list of str, default=None - Names of each of the features. - If None, generic names will be used ("x[0]", "x[1]", ...). - - class_names : list of str or bool, default=None - Names of each of the target classes in ascending numerical order. - Only relevant for classification and not supported for multi-output. - If ``True``, shows a symbolic representation of the class name. - - label : {'all', 'root', 'none'}, default='all' - Whether to show informative labels for impurity, etc. - Options include 'all' to show at every node, 'root' to show only at - the top root node, or 'none' to not show at any node. - - filled : bool, default=False - When set to ``True``, paint nodes to indicate majority class for - classification, extremity of values for regression, or purity of node - for multi-output. - - impurity : bool, default=True - When set to ``True``, show the impurity at each node. - - node_ids : bool, default=False - When set to ``True``, show the ID number on each node. - - proportion : bool, default=False - When set to ``True``, change the display of 'values' and/or 'samples' - to be proportions and percentages respectively. - - rounded : bool, default=False - When set to ``True``, draw node boxes with rounded corners and use - Helvetica fonts instead of Times-Roman. - - precision : int, default=3 - Number of digits of precision for floating point in the values of - impurity, threshold and value attributes of each node. - - ax : matplotlib axis, default=None - Axes to plot to. If None, use current axis. Any previous content - is cleared. - - fontsize : int, default=None - Size of text font. If None, determined automatically to fit figure. - - Returns - ------- - annotations : list of artists - List containing the artists for the annotation boxes making up the - tree. - - Examples - -------- - >>> from sklearn.datasets import load_iris - >>> from sklearn import tree - - >>> clf = tree.DecisionTreeClassifier(random_state=0) - >>> iris = load_iris() - - >>> clf = clf.fit(iris.data, iris.target) - >>> tree.plot_tree(clf) - [...] - """ - - check_is_fitted(decision_tree) - - exporter = _MPLTreeExporter( - max_depth=max_depth, - feature_names=feature_names, - class_names=class_names, - label=label, - filled=filled, - impurity=impurity, - node_ids=node_ids, - proportion=proportion, - rounded=rounded, - precision=precision, - fontsize=fontsize, - ) - return exporter.export(decision_tree, ax=ax) - - -class _BaseTreeExporter: - def __init__( - self, - max_depth=None, - feature_names=None, - class_names=None, - label="all", - filled=False, - impurity=True, - node_ids=False, - proportion=False, - rounded=False, - precision=3, - fontsize=None, - ): - self.max_depth = max_depth - self.feature_names = feature_names - self.class_names = class_names - self.label = label - self.filled = filled - self.impurity = impurity - self.node_ids = node_ids - self.proportion = proportion - self.rounded = rounded - self.precision = precision - self.fontsize = fontsize - - def get_color(self, value): - # Find the appropriate color & intensity for a node - if self.colors["bounds"] is None: - # Classification tree - color = list(self.colors["rgb"][np.argmax(value)]) - sorted_values = sorted(value, reverse=True) - if len(sorted_values) == 1: - alpha = 0 - else: - alpha = (sorted_values[0] - sorted_values[1]) / (1 - sorted_values[1]) - else: - # Regression tree or multi-output - color = list(self.colors["rgb"][0]) - alpha = (value - self.colors["bounds"][0]) / ( - self.colors["bounds"][1] - self.colors["bounds"][0] - ) - # unpack numpy scalars - alpha = float(alpha) - # compute the color as alpha against white - color = [int(round(alpha * c + (1 - alpha) * 255, 0)) for c in color] - # Return html color code in #RRGGBB format - return "#%2x%2x%2x" % tuple(color) - - def get_fill_color(self, tree, node_id): - # Fetch appropriate color for node - if "rgb" not in self.colors: - # Initialize colors and bounds if required - self.colors["rgb"] = _color_brew(tree.n_classes[0]) - if tree.n_outputs != 1: - # Find max and min impurities for multi-output - self.colors["bounds"] = (np.min(-tree.impurity), np.max(-tree.impurity)) - elif tree.n_classes[0] == 1 and len(np.unique(tree.value)) != 1: - # Find max and min values in leaf nodes for regression - self.colors["bounds"] = (np.min(tree.value), np.max(tree.value)) - if tree.n_outputs == 1: - node_val = tree.value[node_id][0, :] / tree.weighted_n_node_samples[node_id] - if tree.n_classes[0] == 1: - # Regression - node_val = tree.value[node_id][0, :] - else: - # If multi-output color node by impurity - node_val = -tree.impurity[node_id] - return self.get_color(node_val) - - def node_to_str(self, tree, node_id, criterion): - # Generate the node content string - if tree.n_outputs == 1: - value = tree.value[node_id][0, :] - else: - value = tree.value[node_id] - - # Should labels be shown? - labels = (self.label == "root" and node_id == 0) or self.label == "all" - - characters = self.characters - node_string = characters[-1] - - # Write node ID - if self.node_ids: - if labels: - node_string += "node " - node_string += characters[0] + str(node_id) + characters[4] - - # Write decision criteria - if tree.children_left[node_id] != _tree.TREE_LEAF: - # Always write node decision criteria, except for leaves - if self.feature_names is not None: - feature = self.feature_names[tree.feature[node_id]] - else: - feature = "x%s%s%s" % ( - characters[1], - tree.feature[node_id], - characters[2], - ) - node_string += "%s %s %s%s" % ( - feature, - characters[3], - round(tree.threshold[node_id], self.precision), - characters[4], - ) - - # Write impurity - if self.impurity: - if isinstance(criterion, _criterion.FriedmanMSE): - criterion = "friedman_mse" - elif isinstance(criterion, _criterion.MSE) or criterion == "squared_error": - criterion = "squared_error" - elif not isinstance(criterion, str): - criterion = "impurity" - if labels: - node_string += "%s = " % criterion - node_string += ( - str(round(tree.impurity[node_id], self.precision)) + characters[4] - ) - - # Write node sample count - if labels: - node_string += "samples = " - if self.proportion: - percent = ( - 100.0 * tree.n_node_samples[node_id] / float(tree.n_node_samples[0]) - ) - node_string += str(round(percent, 1)) + "%" + characters[4] - else: - node_string += str(tree.n_node_samples[node_id]) + characters[4] - - # Write node class distribution / regression value - if self.proportion and tree.n_classes[0] != 1: - # For classification this will show the proportion of samples - value = value / tree.weighted_n_node_samples[node_id] - if labels: - node_string += "value = " - if tree.n_classes[0] == 1: - # Regression - value_text = np.around(value, self.precision) - elif self.proportion: - # Classification - value_text = np.around(value, self.precision) - elif np.all(np.equal(np.mod(value, 1), 0)): - # Classification without floating-point weights - value_text = value.astype(int) - else: - # Classification with floating-point weights - value_text = np.around(value, self.precision) - # Strip whitespace - value_text = str(value_text.astype("S32")).replace("b'", "'") - value_text = value_text.replace("' '", ", ").replace("'", "") - if tree.n_classes[0] == 1 and tree.n_outputs == 1: - value_text = value_text.replace("[", "").replace("]", "") - value_text = value_text.replace("\n ", characters[4]) - node_string += value_text + characters[4] - - # Write node majority class - if ( - self.class_names is not None - and tree.n_classes[0] != 1 - and tree.n_outputs == 1 - ): - # Only done for single-output classification trees - if labels: - node_string += "class = " - if self.class_names is not True: - class_name = self.class_names[np.argmax(value)] - else: - class_name = "y%s%s%s" % ( - characters[1], - np.argmax(value), - characters[2], - ) - node_string += class_name - - # Clean up any trailing newlines - if node_string.endswith(characters[4]): - node_string = node_string[: -len(characters[4])] - - return node_string + characters[5] - - -class _DOTTreeExporter(_BaseTreeExporter): - def __init__( - self, - out_file=SENTINEL, - max_depth=None, - feature_names=None, - class_names=None, - label="all", - filled=False, - leaves_parallel=False, - impurity=True, - node_ids=False, - proportion=False, - rotate=False, - rounded=False, - special_characters=False, - precision=3, - fontname="helvetica", - ): - - super().__init__( - max_depth=max_depth, - feature_names=feature_names, - class_names=class_names, - label=label, - filled=filled, - impurity=impurity, - node_ids=node_ids, - proportion=proportion, - rounded=rounded, - precision=precision, - ) - self.leaves_parallel = leaves_parallel - self.out_file = out_file - self.special_characters = special_characters - self.fontname = fontname - self.rotate = rotate - - # PostScript compatibility for special characters - if special_characters: - self.characters = ["#", "", "", "≤", "
", ">", "<"] - else: - self.characters = ["#", "[", "]", "<=", "\\n", '"', '"'] - - # validate - if isinstance(precision, Integral): - if precision < 0: - raise ValueError( - "'precision' should be greater or equal to 0." - " Got {} instead.".format(precision) - ) - else: - raise ValueError( - "'precision' should be an integer. Got {} instead.".format( - type(precision) - ) - ) - - # The depth of each node for plotting with 'leaf' option - self.ranks = {"leaves": []} - # The colors to render each node with - self.colors = {"bounds": None} - - def export(self, decision_tree): - # Check length of feature_names before getting into the tree node - # Raise error if length of feature_names does not match - # n_features_in_ in the decision_tree - if self.feature_names is not None: - if len(self.feature_names) != decision_tree.n_features_in_: - raise ValueError( - "Length of feature_names, %d does not match number of features, %d" - % (len(self.feature_names), decision_tree.n_features_in_) - ) - # each part writes to out_file - self.head() - # Now recurse the tree and add node & edge attributes - if isinstance(decision_tree, _tree.Tree): - self.recurse(decision_tree, 0, criterion="impurity") - else: - self.recurse(decision_tree.tree_, 0, criterion=decision_tree.criterion) - - self.tail() - - def tail(self): - # If required, draw leaf nodes at same depth as each other - if self.leaves_parallel: - for rank in sorted(self.ranks): - self.out_file.write( - "{rank=same ; " + "; ".join(r for r in self.ranks[rank]) + "} ;\n" - ) - self.out_file.write("}") - - def head(self): - self.out_file.write("digraph Tree {\n") - - # Specify node aesthetics - self.out_file.write("node [shape=box") - rounded_filled = [] - if self.filled: - rounded_filled.append("filled") - if self.rounded: - rounded_filled.append("rounded") - if len(rounded_filled) > 0: - self.out_file.write( - ', style="%s", color="black"' % ", ".join(rounded_filled) - ) - - self.out_file.write(', fontname="%s"' % self.fontname) - self.out_file.write("] ;\n") - - # Specify graph & edge aesthetics - if self.leaves_parallel: - self.out_file.write("graph [ranksep=equally, splines=polyline] ;\n") - - self.out_file.write('edge [fontname="%s"] ;\n' % self.fontname) - - if self.rotate: - self.out_file.write("rankdir=LR ;\n") - - def recurse(self, tree, node_id, criterion, parent=None, depth=0): - if node_id == _tree.TREE_LEAF: - raise ValueError("Invalid node_id %s" % _tree.TREE_LEAF) - - left_child = tree.children_left[node_id] - right_child = tree.children_right[node_id] - - # Add node with description - if self.max_depth is None or depth <= self.max_depth: - - # Collect ranks for 'leaf' option in plot_options - if left_child == _tree.TREE_LEAF: - self.ranks["leaves"].append(str(node_id)) - elif str(depth) not in self.ranks: - self.ranks[str(depth)] = [str(node_id)] - else: - self.ranks[str(depth)].append(str(node_id)) - - self.out_file.write( - "%d [label=%s" % (node_id, self.node_to_str(tree, node_id, criterion)) - ) - - if self.filled: - self.out_file.write( - ', fillcolor="%s"' % self.get_fill_color(tree, node_id) - ) - self.out_file.write("] ;\n") - - if parent is not None: - # Add edge to parent - self.out_file.write("%d -> %d" % (parent, node_id)) - if parent == 0: - # Draw True/False labels if parent is root node - angles = np.array([45, -45]) * ((self.rotate - 0.5) * -2) - self.out_file.write(" [labeldistance=2.5, labelangle=") - if node_id == 1: - self.out_file.write('%d, headlabel="True"]' % angles[0]) - else: - self.out_file.write('%d, headlabel="False"]' % angles[1]) - self.out_file.write(" ;\n") - - if left_child != _tree.TREE_LEAF: - self.recurse( - tree, - left_child, - criterion=criterion, - parent=node_id, - depth=depth + 1, - ) - self.recurse( - tree, - right_child, - criterion=criterion, - parent=node_id, - depth=depth + 1, - ) - - else: - self.ranks["leaves"].append(str(node_id)) - - self.out_file.write('%d [label="(...)"' % node_id) - if self.filled: - # color cropped nodes grey - self.out_file.write(', fillcolor="#C0C0C0"') - self.out_file.write("] ;\n" % node_id) - - if parent is not None: - # Add edge to parent - self.out_file.write("%d -> %d ;\n" % (parent, node_id)) - - -class _MPLTreeExporter(_BaseTreeExporter): - def __init__( - self, - max_depth=None, - feature_names=None, - class_names=None, - label="all", - filled=False, - impurity=True, - node_ids=False, - proportion=False, - rounded=False, - precision=3, - fontsize=None, - ): - - super().__init__( - max_depth=max_depth, - feature_names=feature_names, - class_names=class_names, - label=label, - filled=filled, - impurity=impurity, - node_ids=node_ids, - proportion=proportion, - rounded=rounded, - precision=precision, - ) - self.fontsize = fontsize - - # validate - if isinstance(precision, Integral): - if precision < 0: - raise ValueError( - "'precision' should be greater or equal to 0." - " Got {} instead.".format(precision) - ) - else: - raise ValueError( - "'precision' should be an integer. Got {} instead.".format( - type(precision) - ) - ) - - # The depth of each node for plotting with 'leaf' option - self.ranks = {"leaves": []} - # The colors to render each node with - self.colors = {"bounds": None} - - self.characters = ["#", "[", "]", "<=", "\n", "", ""] - self.bbox_args = dict() - if self.rounded: - self.bbox_args["boxstyle"] = "round" - - self.arrow_args = dict(arrowstyle="<-") - - def _make_tree(self, node_id, et, criterion, depth=0): - # traverses _tree.Tree recursively, builds intermediate - # "_reingold_tilford.Tree" object - name = self.node_to_str(et, node_id, criterion=criterion) - if et.children_left[node_id] != _tree.TREE_LEAF and ( - self.max_depth is None or depth <= self.max_depth - ): - children = [ - self._make_tree( - et.children_left[node_id], et, criterion, depth=depth + 1 - ), - self._make_tree( - et.children_right[node_id], et, criterion, depth=depth + 1 - ), - ] - else: - return Tree(name, node_id) - return Tree(name, node_id, *children) - - def export(self, decision_tree, ax=None): - import matplotlib.pyplot as plt - from matplotlib.text import Annotation - - if ax is None: - ax = plt.gca() - ax.clear() - ax.set_axis_off() - my_tree = self._make_tree(0, decision_tree.tree_, decision_tree.criterion) - draw_tree = buchheim(my_tree) - - # important to make sure we're still - # inside the axis after drawing the box - # this makes sense because the width of a box - # is about the same as the distance between boxes - max_x, max_y = draw_tree.max_extents() + 1 - ax_width = ax.get_window_extent().width - ax_height = ax.get_window_extent().height - - scale_x = ax_width / max_x - scale_y = ax_height / max_y - self.recurse(draw_tree, decision_tree.tree_, ax, max_x, max_y) - - anns = [ann for ann in ax.get_children() if isinstance(ann, Annotation)] - - # update sizes of all bboxes - renderer = ax.figure.canvas.get_renderer() - - for ann in anns: - ann.update_bbox_position_size(renderer) - - if self.fontsize is None: - # get figure to data transform - # adjust fontsize to avoid overlap - # get max box width and height - extents = [ann.get_bbox_patch().get_window_extent() for ann in anns] - max_width = max([extent.width for extent in extents]) - max_height = max([extent.height for extent in extents]) - # width should be around scale_x in axis coordinates - size = anns[0].get_fontsize() * min( - scale_x / max_width, scale_y / max_height - ) - for ann in anns: - ann.set_fontsize(size) - - return anns - - def recurse(self, node, tree, ax, max_x, max_y, depth=0): - import matplotlib.pyplot as plt - - kwargs = dict( - bbox=self.bbox_args.copy(), - ha="center", - va="center", - zorder=100 - 10 * depth, - xycoords="axes fraction", - arrowprops=self.arrow_args.copy(), - ) - kwargs["arrowprops"]["edgecolor"] = plt.rcParams["text.color"] - - if self.fontsize is not None: - kwargs["fontsize"] = self.fontsize - - # offset things by .5 to center them in plot - xy = ((node.x + 0.5) / max_x, (max_y - node.y - 0.5) / max_y) - - if self.max_depth is None or depth <= self.max_depth: - if self.filled: - kwargs["bbox"]["fc"] = self.get_fill_color(tree, node.tree.node_id) - else: - kwargs["bbox"]["fc"] = ax.get_facecolor() - - if node.parent is None: - # root - ax.annotate(node.tree.label, xy, **kwargs) - else: - xy_parent = ( - (node.parent.x + 0.5) / max_x, - (max_y - node.parent.y - 0.5) / max_y, - ) - ax.annotate(node.tree.label, xy_parent, xy, **kwargs) - for child in node.children: - self.recurse(child, tree, ax, max_x, max_y, depth=depth + 1) - - else: - xy_parent = ( - (node.parent.x + 0.5) / max_x, - (max_y - node.parent.y - 0.5) / max_y, - ) - kwargs["bbox"]["fc"] = "grey" - ax.annotate("\n (...) \n", xy_parent, xy, **kwargs) - - -def export_graphviz( - decision_tree, - out_file=None, - *, - max_depth=None, - feature_names=None, - class_names=None, - label="all", - filled=False, - leaves_parallel=False, - impurity=True, - node_ids=False, - proportion=False, - rotate=False, - rounded=False, - special_characters=False, - precision=3, - fontname="helvetica", -): - """Export a decision tree in DOT format. - - This function generates a GraphViz representation of the decision tree, - which is then written into `out_file`. Once exported, graphical renderings - can be generated using, for example:: - - $ dot -Tps tree.dot -o tree.ps (PostScript format) - $ dot -Tpng tree.dot -o tree.png (PNG format) - - The sample counts that are shown are weighted with any sample_weights that - might be present. - - Read more in the :ref:`User Guide `. - - Parameters - ---------- - decision_tree : decision tree classifier - The decision tree to be exported to GraphViz. - - out_file : object or str, default=None - Handle or name of the output file. If ``None``, the result is - returned as a string. - - .. versionchanged:: 0.20 - Default of out_file changed from "tree.dot" to None. - - max_depth : int, default=None - The maximum depth of the representation. If None, the tree is fully - generated. - - feature_names : list of str, default=None - Names of each of the features. - If None, generic names will be used ("x[0]", "x[1]", ...). - - class_names : list of str or bool, default=None - Names of each of the target classes in ascending numerical order. - Only relevant for classification and not supported for multi-output. - If ``True``, shows a symbolic representation of the class name. - - label : {'all', 'root', 'none'}, default='all' - Whether to show informative labels for impurity, etc. - Options include 'all' to show at every node, 'root' to show only at - the top root node, or 'none' to not show at any node. - - filled : bool, default=False - When set to ``True``, paint nodes to indicate majority class for - classification, extremity of values for regression, or purity of node - for multi-output. - - leaves_parallel : bool, default=False - When set to ``True``, draw all leaf nodes at the bottom of the tree. - - impurity : bool, default=True - When set to ``True``, show the impurity at each node. - - node_ids : bool, default=False - When set to ``True``, show the ID number on each node. - - proportion : bool, default=False - When set to ``True``, change the display of 'values' and/or 'samples' - to be proportions and percentages respectively. - - rotate : bool, default=False - When set to ``True``, orient tree left to right rather than top-down. - - rounded : bool, default=False - When set to ``True``, draw node boxes with rounded corners. - - special_characters : bool, default=False - When set to ``False``, ignore special characters for PostScript - compatibility. - - precision : int, default=3 - Number of digits of precision for floating point in the values of - impurity, threshold and value attributes of each node. - - fontname : str, default='helvetica' - Name of font used to render text. - - Returns - ------- - dot_data : str - String representation of the input tree in GraphViz dot format. - Only returned if ``out_file`` is None. - - .. versionadded:: 0.18 - - Examples - -------- - >>> from sklearn.datasets import load_iris - >>> from sklearn import tree - - >>> clf = tree.DecisionTreeClassifier() - >>> iris = load_iris() - - >>> clf = clf.fit(iris.data, iris.target) - >>> tree.export_graphviz(clf) - 'digraph Tree {... - """ - - check_is_fitted(decision_tree) - own_file = False - return_string = False - try: - if isinstance(out_file, str): - out_file = open(out_file, "w", encoding="utf-8") - own_file = True - - if out_file is None: - return_string = True - out_file = StringIO() - - exporter = _DOTTreeExporter( - out_file=out_file, - max_depth=max_depth, - feature_names=feature_names, - class_names=class_names, - label=label, - filled=filled, - leaves_parallel=leaves_parallel, - impurity=impurity, - node_ids=node_ids, - proportion=proportion, - rotate=rotate, - rounded=rounded, - special_characters=special_characters, - precision=precision, - fontname=fontname, - ) - exporter.export(decision_tree) - - if return_string: - return exporter.out_file.getvalue() - - finally: - if own_file: - out_file.close() - - -def _compute_depth(tree, node): - """ - Returns the depth of the subtree rooted in node. - """ - - def compute_depth_( - current_node, current_depth, children_left, children_right, depths - ): - depths += [current_depth] - left = children_left[current_node] - right = children_right[current_node] - if left != -1 and right != -1: - compute_depth_( - left, current_depth + 1, children_left, children_right, depths - ) - compute_depth_( - right, current_depth + 1, children_left, children_right, depths - ) - - depths = [] - compute_depth_(node, 1, tree.children_left, tree.children_right, depths) - return max(depths) - - -def export_text( - decision_tree, - *, - feature_names=None, - class_names=None, - max_depth=10, - spacing=3, - decimals=2, - show_weights=False, -): - """Build a text report showing the rules of a decision tree. - - Note that backwards compatibility may not be supported. - - Parameters - ---------- - decision_tree : object - The decision tree estimator to be exported. - It can be an instance of - DecisionTreeClassifier or DecisionTreeRegressor. - - feature_names : list of str, default=None - A list of length n_features containing the feature names. - If None generic names will be used ("feature_0", "feature_1", ...). - - class_names : list or None, default=None - Names of each of the target classes in ascending numerical order. - Only relevant for classification and not supported for multi-output. - - - if `None`, the class names are delegated to `decision_tree.classes_`; - - if a list, then `class_names` will be used as class names instead - of `decision_tree.classes_`. The length of `class_names` must match - the length of `decision_tree.classes_`. - - .. versionadded:: 1.3 - - max_depth : int, default=10 - Only the first max_depth levels of the tree are exported. - Truncated branches will be marked with "...". - - spacing : int, default=3 - Number of spaces between edges. The higher it is, the wider the result. - - decimals : int, default=2 - Number of decimal digits to display. - - show_weights : bool, default=False - If true the classification weights will be exported on each leaf. - The classification weights are the number of samples each class. - - Returns - ------- - report : str - Text summary of all the rules in the decision tree. - - Examples - -------- - - >>> from sklearn.datasets import load_iris - >>> from sklearn.tree import DecisionTreeClassifier - >>> from sklearn.tree import export_text - >>> iris = load_iris() - >>> X = iris['data'] - >>> y = iris['target'] - >>> decision_tree = DecisionTreeClassifier(random_state=0, max_depth=2) - >>> decision_tree = decision_tree.fit(X, y) - >>> r = export_text(decision_tree, feature_names=iris['feature_names']) - >>> print(r) - |--- petal width (cm) <= 0.80 - | |--- class: 0 - |--- petal width (cm) > 0.80 - | |--- petal width (cm) <= 1.75 - | | |--- class: 1 - | |--- petal width (cm) > 1.75 - | | |--- class: 2 - """ - check_is_fitted(decision_tree) - tree_ = decision_tree.tree_ - if is_classifier(decision_tree): - if class_names is None: - class_names = decision_tree.classes_ - elif len(class_names) != len(decision_tree.classes_): - raise ValueError( - "When `class_names` is a list, it should contain as" - " many items as `decision_tree.classes_`. Got" - f" {len(class_names)} while the tree was fitted with" - f" {len(decision_tree.classes_)} classes." - ) - right_child_fmt = "{} {} <= {}\n" - left_child_fmt = "{} {} > {}\n" - truncation_fmt = "{} {}\n" - - if max_depth < 0: - raise ValueError("max_depth bust be >= 0, given %d" % max_depth) - - if feature_names is not None and len(feature_names) != tree_.n_features: - raise ValueError( - "feature_names must contain %d elements, got %d" - % (tree_.n_features, len(feature_names)) - ) - - if spacing <= 0: - raise ValueError("spacing must be > 0, given %d" % spacing) - - if decimals < 0: - raise ValueError("decimals must be >= 0, given %d" % decimals) - - if isinstance(decision_tree, DecisionTreeClassifier): - value_fmt = "{}{} weights: {}\n" - if not show_weights: - value_fmt = "{}{}{}\n" - else: - value_fmt = "{}{} value: {}\n" - - if feature_names: - feature_names_ = [ - feature_names[i] if i != _tree.TREE_UNDEFINED else None - for i in tree_.feature - ] - else: - feature_names_ = ["feature_{}".format(i) for i in tree_.feature] - - export_text.report = "" - - def _add_leaf(value, class_name, indent): - val = "" - is_classification = isinstance(decision_tree, DecisionTreeClassifier) - if show_weights or not is_classification: - val = ["{1:.{0}f}, ".format(decimals, v) for v in value] - val = "[" + "".join(val)[:-2] + "]" - if is_classification: - val += " class: " + str(class_name) - export_text.report += value_fmt.format(indent, "", val) - - def print_tree_recurse(node, depth): - indent = ("|" + (" " * spacing)) * depth - indent = indent[:-spacing] + "-" * spacing - - value = None - if tree_.n_outputs == 1: - value = tree_.value[node][0] - else: - value = tree_.value[node].T[0] - class_name = np.argmax(value) - - if tree_.n_classes[0] != 1 and tree_.n_outputs == 1: - class_name = class_names[class_name] - - if depth <= max_depth + 1: - info_fmt = "" - info_fmt_left = info_fmt - info_fmt_right = info_fmt - - if tree_.feature[node] != _tree.TREE_UNDEFINED: - name = feature_names_[node] - threshold = tree_.threshold[node] - threshold = "{1:.{0}f}".format(decimals, threshold) - export_text.report += right_child_fmt.format(indent, name, threshold) - export_text.report += info_fmt_left - print_tree_recurse(tree_.children_left[node], depth + 1) - - export_text.report += left_child_fmt.format(indent, name, threshold) - export_text.report += info_fmt_right - print_tree_recurse(tree_.children_right[node], depth + 1) - else: # leaf - _add_leaf(value, class_name, indent) - else: - subtree_depth = _compute_depth(tree_, node) - if subtree_depth == 1: - _add_leaf(value, class_name, indent) - else: - trunc_report = "truncated branch of depth %d" % subtree_depth - export_text.report += truncation_fmt.format(indent, trunc_report) - - print_tree_recurse(0, 1) - return export_text.report diff --git a/stpredictions/models/OK3/_forest.py b/stpredictions/models/OK3/_forest.py index abb1cbe2e..2aae5d9e2 100755 --- a/stpredictions/models/OK3/_forest.py +++ b/stpredictions/models/OK3/_forest.py @@ -44,15 +44,15 @@ class calls the ``fit`` method of each sub-estimator on random samples import itertools -from stpredictions.models.OK3.base import StructuredOutputMixin +from base import StructuredOutputMixin from sklearn.metrics import accuracy_score from sklearn.metrics import hamming_loss from sklearn.metrics import r2_score from sklearn.preprocessing import OneHotEncoder -from stpredictions.models.OK3._classes import OK3Regressor, ExtraOK3Regressor -from stpredictions.models.OK3._tree import DTYPE, DOUBLE +from _classes import OK3Regressor, ExtraOK3Regressor +from _tree import DTYPE, DOUBLE from sklearn.utils import check_random_state, check_array from sklearn.exceptions import DataConversionWarning @@ -63,12 +63,12 @@ class calls the ``fit`` method of each sub-estimator on random samples from sklearn.utils.validation import check_is_fitted, _check_sample_weight from sklearn.utils.validation import _deprecate_positional_args -from stpredictions.models.OK3.kernel import Kernel -from stpredictions.models.OK3._classes import KERNELS, CRITERIA +from kernel import Kernel +from _classes import KERNELS, CRITERIA -from stpredictions.models.OK3._criterion import Criterion, KernelizedMSE +from _criterion import Criterion, KernelizedMSE -# import line_profiler +import line_profiler __all__ = ["RandomOKForestRegressor", "ExtraOKTreesRegressor", @@ -161,7 +161,7 @@ def _parallel_build_trees(tree, forest, X, y, Gram_y, sample_weight, tree_idx, n tree.fit(X, y, sample_weight=curr_sample_weight, check_input=False, in_ensemble=True, Gram_y=Gram_y) else: tree.fit(X, y, sample_weight=sample_weight, check_input=False, in_ensemble=True, Gram_y=Gram_y) - + return tree @@ -185,7 +185,7 @@ def __init__(self, verbose=0, warm_start=False, max_samples=None, - kernel="linear"): + kernel="linear"): super().__init__( base_estimator=base_estimator, @@ -262,7 +262,7 @@ def decision_path(self, X): n_nodes_ptr = np.array(n_nodes).cumsum() return sparse_hstack(indicators).tocsr(), n_nodes_ptr - + def fit(self, X, y, sample_weight=None): """ Build a forest of ok-trees from the training set (X, y). @@ -290,7 +290,7 @@ def fit(self, X, y, sample_weight=None): self : object """ kernel = self.kernel - + # Validate or convert input data if issparse(y): raise ValueError( @@ -311,6 +311,7 @@ def fit(self, X, y, sample_weight=None): y = np.atleast_1d(y) + if not isinstance(kernel, Kernel): params = () if isinstance(kernel, tuple): @@ -318,30 +319,30 @@ def fit(self, X, y, sample_weight=None): try: kernel = KERNELS[kernel](*params) except KeyError: - print( - "Error : 'kernel' attribute (or its first element if it is a tuple) has to be either a Kernel class or a string which is a valid key for the dict 'KERNELS'.") + print("Error : 'kernel' attribute (or its first element if it is a tuple) has to be either a Kernel class or a string which is a valid key for the dict 'KERNELS'.") raise + if y.ndim == 1: # reshape is necessary to preserve the data contiguity against vs # [:, np.newaxis] that does not. y = np.reshape(y, (-1, 1)) - + if y.shape[1] == y.shape[0]: warn("The target parameter is a square matrix." - "Are you sure this is the matrix of outputs and " - "not a Gram matrix ? ") - + "Are you sure this is the matrix of outputs and " + "not a Gram matrix ? ") + if "clf" in kernel.get_name(): check_classification_targets(y) - + start_computation = time.time() # compute the Gram matrix of the outputs K_y = kernel.get_Gram_matrix(y) print("Time to compute the training Gram matrix : " + str(time.time() - start_computation) + " s.") - + self.n_outputs_ = y.shape[1] - + if getattr(y, "dtype", None) != DOUBLE or not y.flags.contiguous: y = np.ascontiguousarray(y, dtype=DOUBLE) if getattr(K_y, "dtype", None) != DOUBLE or not K_y.flags.contiguous: @@ -396,7 +397,7 @@ def fit(self, X, y, sample_weight=None): **_joblib_parallel_args(prefer='threads'))( delayed(_parallel_build_trees)( t, self, X, y, K_y, sample_weight, i, len(trees), - verbose=self.verbose, + verbose=self.verbose, n_samples_bootstrap=n_samples_bootstrap) for i, t in enumerate(trees)) @@ -508,7 +509,7 @@ def __init__(self, warm_start=warm_start, max_samples=max_samples, kernel=kernel) - + def predict_weights(self, X): """ Predict weights (on the training samples) for X. @@ -535,22 +536,25 @@ def predict_weights(self, X): # Assign chunk of trees to jobs n_jobs, _, _ = _partition_estimators(self.n_estimators, self.n_jobs) - + # avoid storing the output of every estimator by summing them here weights = np.zeros((X.shape[0], self.estimators_[0].tree_.y.shape[0]), dtype=np.float64) - + # Parallel loop lock = threading.Lock() Parallel(n_jobs=n_jobs, verbose=self.verbose, - **_joblib_parallel_args(require="sharedmem"))( - delayed(_accumulate_prediction)(e.predict_weights, X, [weights], lock) - for e in self.estimators_) + **_joblib_parallel_args(require="sharedmem"))( + delayed(_accumulate_prediction)(e.predict_weights, X, [weights], lock) + for e in self.estimators_) weights /= len(self.estimators_) return weights + + + def predict(self, X, candidates=None, return_top_k=1, precomputed_weights=None): """Predict structured objects for X. @@ -587,7 +591,7 @@ def predict(self, X, candidates=None, return_top_k=1, precomputed_weights=None): representations of the structured output objects (found in the set of candidates, or if it is not given, among the training outputs). """ - + kernel = self.kernel if not isinstance(kernel, Kernel): params = () @@ -596,13 +600,12 @@ def predict(self, X, candidates=None, return_top_k=1, precomputed_weights=None): try: kernel = KERNELS[kernel](*params) except KeyError: - print( - "Error : 'kernel' attribute (or its first element if it is a tuple) has to be either a Kernel class or a string which is a valid key for the dict 'KERNELS'.") + print("Error : 'kernel' attribute (or its first element if it is a tuple) has to be either a Kernel class or a string which is a valid key for the dict 'KERNELS'.") raise - + check_is_fitted(self) X = self._validate_X_predict(X) - + criterion = self.estimators_[0].criterion if not isinstance(criterion, Criterion): criterion = CRITERIA[criterion](X.shape[0]) @@ -610,139 +613,138 @@ def predict(self, X, candidates=None, return_top_k=1, precomputed_weights=None): if candidates is not None: # candidates doit etre un ensemble : pas de répétition candidates = np.unique(candidates, axis=0) - + K_cand_train = kernel.get_Gram_matrix(candidates, self.estimators_[0].tree_.y) sq_norms_cand = kernel.get_sq_norms(candidates) - else: # recherche dans le learning set + else: # recherche dans le learning set candidates, indices = np.unique(self.estimators_[0].tree_.y, return_index=True, axis=0) K_cand_train = self.estimators_[0].tree_.K_y[indices] sq_norms_cand = self.estimators_[0].tree_.K_y[indices, indices] - + if return_top_k > 1 and return_top_k >= len(candidates): - warn( - "Le nombre de prédictions demandées pour chaque entrée dépasse le nombre de sorties candidates, return_top_k va être réduit à sa valeur maximale.") - return_top_k = len(candidates) - 1 - + warn("Le nombre de prédictions demandées pour chaque entrée dépasse le nombre de sorties candidates, return_top_k va être réduit à sa valeur maximale.") + return_top_k = len(candidates)-1 + if "reg" in kernel.get_name() and return_top_k > 1: - warn( - "On ne peut pas retourner plusieurs candidats d'outputs dans le cas d'une régression, veuillez plutôt choisir kernel=linear. " - "return_top_k va etre mis à 1.") + warn("On ne peut pas retourner plusieurs candidats d'outputs dans le cas d'une régression, veuillez plutôt choisir kernel=linear. " + "return_top_k va etre mis à 1.") return_top_k = 1 - + if precomputed_weights is None: weights = self.predict_weights(X) else: weights = precomputed_weights - + if isinstance(criterion, KernelizedMSE): # Cas particulier de la classification : recherche EXHAUSTIVE if kernel.get_name() == "gini_clf": - + # rechercher la meilleure combinaison de labels parmis toutes celles possible - + y_train = self.estimators_[0].tree_.y n_outputs = y_train.shape[1] classes = [] n_classes = [] - + y_train_encoded = np.zeros((y_train.shape[0], n_outputs), dtype=int) - + for l in range(n_outputs): classes_l, y_train_encoded[:, l] = np.unique(y_train[:, l], return_inverse=True) classes.append(classes_l) n_classes.append(classes_l.shape[0]) - + n_classes = np.array(n_classes, dtype=np.intp) - - out = np.zeros((X.shape[0] * return_top_k, n_outputs), dtype=np.intp) - + + out = np.zeros((X.shape[0]*return_top_k,n_outputs), dtype=np.intp) + nb_candidates = 1 for nb_classes in n_classes: nb_candidates *= nb_classes # array to store the value of the criteria to minimize, for each training sample value = np.zeros((nb_candidates,), dtype=np.float64) - + recherche_exhaustive_equivalente = False - + # node k for test_ex in range(X.shape[0]): - if recherche_exhaustive_equivalente or return_top_k > 1: # n_outputs boucles sur les classes de chaque output imbriquées dans le product --> long - + if recherche_exhaustive_equivalente or return_top_k > 1: # n_outputs boucles sur les classes de chaque output imbriquées dans le product --> long + for ind, candidate in enumerate(list(itertools.product(*classes))): + # la valeur a minimiser est k(candidate,candidate) - 2 * moyenne_des_Kernel(candidate,train_exs_in_same_leaf) # dans le cas de gini, k(candidate,candidate) est toujours égal à 1 peu importe candidate # on peut donc plutôt maximiser la quantité somme_des_Kernel(candidate,train_exs_in_same_leaf) - - value[ind] = np.sum([weights[test_ex, ex] * (y_train[ex] == candidate).mean() for ex in - range(weights.shape[1])]) - + + value[ind] = np.sum([ weights[test_ex,ex] * (y_train[ex] == candidate).mean() for ex in range(weights.shape[1])]) + ind_top_candidates = np.argpartition(value, - return_top_k)[- return_top_k:] - + top_candidates = list(itertools.product(*classes))[ind_top_candidates] top_candidates = np.array(top_candidates, dtype=int) - - out[test_ex * return_top_k: (test_ex + 1) * return_top_k] = top_candidates - + + out[test_ex*return_top_k : (test_ex+1)*return_top_k] = top_candidates + else: - + for l in range(n_outputs): - major_class = np.argmax( - [np.sum(weights[test_ex, np.where(y_train[:, l] == class_i)[0]]) for class_i in - classes[l]]) - out[test_ex, l] = classes[l][major_class] + major_class = np.argmax( [ np.sum( weights[test_ex, np.where( y_train[:,l] == class_i )[0] ] ) for class_i in classes[l] ] ) + + out[test_ex,l] = classes[l][ major_class ] # Cas particulier de la régression : Recherche EXACTE - elif kernel.get_name() == "mse_reg": - + elif kernel.get_name() == "mse_reg": + # rechercher la meilleure combinaison de labels parmis toutes celles possible # avec un critère MSE et donc un kernel linéaire, # la solution exacte (argmin_y [k(y,y) - 2 moyenne_i(k(y,y_leaf_i))]) peut être calculée : # c'est la moyenne des sorties de chaque feuille # # On ne peut pas rechercher les k meilleurs candidats car l'ensemble de recherche de candidats pour la régression est infini (R^d) - + y_train = self.estimators_[0].tree_.y n_outputs = y_train.shape[1] - + out = weights @ y_train - + # Dans ce else, on a donc une matrice de Gram de candidats fournie - else: # cas général : pas de classification ou de régression mais recherche de l'argmin dans l'ensemble de candidats fourni + else: # cas général : pas de classification ou de régression mais recherche de l'argmin dans l'ensemble de candidats fourni # on a comme candidats une matrice de Gram des des candidats contre les training (+contre soi meme). - + # on renvoie l'indce du candidat représentant le mieux la feuille (on ne check pas les training examples, ils sont à mettre dans les candidats) - - out = np.zeros((X.shape[0] * return_top_k, candidates.shape[1]), dtype=candidates.dtype) - + + out = np.zeros((X.shape[0]*return_top_k,candidates.shape[1]), dtype=candidates.dtype) + # array to store the value of the criteria to minimize, for each training sample value = np.zeros((len(candidates),), dtype=np.float64) - + for test_ex in range(X.shape[0]): # parmi les candidats, calculer k[candidat,candidat] - 2/self.n_node_samples * sum_i=0^self.n_node_samples k[candidat,i] for candidate in range(len(candidates)): - value[candidate] = sq_norms_cand[candidate] - 2 * np.sum( - [weights[test_ex, ex] * K_cand_train[candidate, ex] for ex in range(weights.shape[1])]) - + + value[candidate] = sq_norms_cand[candidate] - 2 * np.sum([weights[test_ex,ex] * K_cand_train[candidate,ex] for ex in range(weights.shape[1])]) + # choisir l'entrée ex* qui donnait la plus petite valeur ind_top_candidates = np.argpartition(value, return_top_k)[:return_top_k] - - out[test_ex * return_top_k: (test_ex + 1) * return_top_k] = candidates[ind_top_candidates] - + + out[test_ex*return_top_k : (test_ex+1)*return_top_k] = candidates[ind_top_candidates] + if out.shape[1] == 1: out = out.reshape(-1) - + return out - + else: raise NotImplementedError('only the "KernelizedMSE" criterion is supported') + + def _set_oob_score(self, X, y, K_y, candidates=None, metric="accuracy"): """ Compute out-of-bag R2 scores in self.oob_score (computed in the HS : no need to decode). @@ -771,6 +773,7 @@ def _set_oob_score(self, X, y, K_y, candidates=None, metric="accuracy"): n_predictions = np.zeros((n_samples, n_samples)) for estimator in self.estimators_: + unsampled_indices = _generate_unsampled_indices( estimator.random_state, n_samples, n_samples_bootstrap) @@ -779,7 +782,7 @@ def _set_oob_score(self, X, y, K_y, candidates=None, metric="accuracy"): weights[unsampled_indices, :] += p_estimator n_predictions[unsampled_indices, :] += 1 - + if (n_predictions == 0).any(): warn("Some inputs do not have OOB scores. " "This probably means too few trees were used " @@ -789,29 +792,30 @@ def _set_oob_score(self, X, y, K_y, candidates=None, metric="accuracy"): weights /= n_predictions # on enregistre LES POIDS : pas les prédictions décodées self.oob_prediction_ = weights - + # TODO : vérifier si ce calcul est correct pour le R2 dans le HS des samples oob. K_train = K_y res_sq_sums = np.diag(K_train) - 2 * np.diag(K_train @ (weights.T)) + np.diag(weights @ K_train @ (weights.T)) - - tot_sq_sums = np.diag(K_train) - np.sum(K_train, axis=1) / K_train.shape[1] - + + tot_sq_sums = np.diag(K_train) - np.sum(K_train, axis=1)/K_train.shape[1] + + res_sq_sum = np.mean(res_sq_sums) tot_sq_sum = np.mean(tot_sq_sums) - - r2 = 1 - (res_sq_sum / tot_sq_sum) - + + r2 = 1 - ( res_sq_sum / tot_sq_sum ) + self.oob_score_ = r2 - + # compute also the decoded score : # compute the same function as 'score' bellow - + score = self.score(X, y, candidates=candidates, metric=metric, precomputed_weights=weights) - + self.oob_decoded_score_ = score - + def score(self, X, y, candidates=None, metric="accuracy", sample_weight=None, precomputed_weights=None): """ Calcule le score après décodage @@ -872,13 +876,10 @@ def score(self, X, y, candidates=None, metric="accuracy", sample_weight=None, pr return_top_k = int(metric[4:]) top_k_score = True except ValueError: - raise (ValueError( - "Pour calculer le score 'top k', veuillez renseigner un nombre juste après le 'top_'. Nous avons reçu '" + metric[ - 4:] + "'.")) - - y_pred = self.predict(X, candidates=candidates, return_top_k=return_top_k, - precomputed_weights=precomputed_weights) - + raise(ValueError("Pour calculer le score 'top k', veuillez renseigner un nombre juste après le 'top_'. Nous avons reçu '"+metric[4:]+"'.")) + + y_pred = self.predict(X, candidates=candidates, return_top_k=return_top_k, precomputed_weights=precomputed_weights) + if "reg" in kernel: return r2_score(y, y_pred, sample_weight=sample_weight) else: @@ -887,9 +888,9 @@ def score(self, X, y, candidates=None, metric="accuracy", sample_weight=None, pr elif metric == "hamming": return 1 - hamming_loss(y, y_pred, sample_weight=sample_weight) elif top_k_score: - contains_true = [False] * len(y) + contains_true = [False]*len(y) for ex in range(len(y)): - for candidate in range(ex * return_top_k, (ex + 1) * return_top_k): + for candidate in range(ex*return_top_k, (ex+1)*return_top_k): if np.atleast_1d(y[ex] == y_pred[candidate]).all(): contains_true[ex] = True if sample_weight is not None: @@ -900,6 +901,7 @@ def score(self, X, y, candidates=None, metric="accuracy", sample_weight=None, pr else: raise ValueError("La metric renseignée n'est pas prise en charge.") + def r2_score_in_Hilbert(self, X, y, sample_weight=None): """ Calcule le score R2 SANS décodage @@ -922,9 +924,9 @@ def r2_score_in_Hilbert(self, X, y, sample_weight=None): score : float R2 score of the predictions in the Hilbert space wrt. the embedded values of y. """ - + kernel = self.kernel - + if not isinstance(kernel, Kernel): params = () if isinstance(kernel, tuple): @@ -932,49 +934,48 @@ def r2_score_in_Hilbert(self, X, y, sample_weight=None): try: kernel = KERNELS[kernel](*params) except KeyError: - print( - "Error : 'kernel' attribute (or its first element if it is a tuple) has to be either a Kernel class or a string which is a valid key for the dict 'KERNELS'.") + print("Error : 'kernel' attribute (or its first element if it is a tuple) has to be either a Kernel class or a string which is a valid key for the dict 'KERNELS'.") raise - + weights = self.predict_weights(X) - + K_train = self.estimators_[0].tree_.K_y - + K_test_train = kernel.get_Gram_matrix(y, self.estimators_[0].tree_.y) - + K_test_test = kernel.get_Gram_matrix(y) + if sample_weight is not None: if len(sample_weight != len(y)): raise ValueError("sample_weights has to have the same length as y. " - "y is len " + str(len(y)) + ", and sample_weight is len " + str(len(sample_weight))) - sample_weight[sample_weight < 0] = 0 + "y is len "+str(len(y))+", and sample_weight is len "+str(len(sample_weight))) + sample_weight[sample_weight<0] = 0 if np.sum(sample_weight) == 0: - warn( - "all weights in sample_weight were set to 0 or bellow. It is unvalid so sample_weight will be ignored.") + warn("all weights in sample_weight were set to 0 or bellow. It is unvalid so sample_weight will be ignored.") sample_weight = None - res_sq_sums = np.diag(K_test_test) - 2 * np.diag(K_test_train @ (weights.T)) + np.diag( - weights @ K_train @ (weights.T)) - + res_sq_sums = np.diag(K_test_test) - 2 * np.diag(K_test_train @ (weights.T)) + np.diag(weights @ K_train @ (weights.T)) + if sample_weight is not None: - tot_sq_sums = np.diag(K_test_test) - np.sum(K_test_test @ np.diag(sample_weight), axis=1) / np.sum( - sample_weight) + tot_sq_sums = np.diag(K_test_test) - np.sum(K_test_test @ np.diag(sample_weight), axis=1) / np.sum(sample_weight) else: - tot_sq_sums = np.diag(K_test_test) - np.sum(K_test_test, axis=1) / K_test_test.shape[1] - + tot_sq_sums = np.diag(K_test_test) - np.sum(K_test_test, axis=1)/K_test_test.shape[1] + + if sample_weight is not None: - res_sq_sum = np.sum(sample_weight * res_sq_sums) / np.sum(sample_weight) - tot_sq_sum = np.sum(sample_weight * tot_sq_sums) / np.sum(sample_weight) + res_sq_sum = np.sum(sample_weight*res_sq_sums) / np.sum(sample_weight) + tot_sq_sum = np.sum(sample_weight*tot_sq_sums) / np.sum(sample_weight) else: res_sq_sum = np.mean(res_sq_sums) tot_sq_sum = np.mean(tot_sq_sums) - - r2 = 1 - (res_sq_sum / tot_sq_sum) - + + r2 = 1 - ( res_sq_sum / tot_sq_sum ) + return r2 + class RandomOKForestRegressor(OKForestRegressor): """ A random ok-forest regressor. @@ -1196,7 +1197,6 @@ class RandomOKForestRegressor(OKForestRegressor): >>> print(regr.predict([[0, 0, 0, 0]])) [-8.32987858] """ - @_deprecate_positional_args def __init__(self, n_estimators=100, *, @@ -1456,7 +1456,6 @@ class ExtraOKTreesRegressor(OKForestRegressor): >>> reg.score(X_test, y_test) 0.2708... """ - @_deprecate_positional_args def __init__(self, n_estimators=100, *, @@ -1762,8 +1761,7 @@ def fit_transform(self, X, y=None, sample_weight=None): rnd = check_random_state(self.random_state) y = rnd.uniform(size=X.shape[0]) if "clf" in self.kernel: - warn( - "Un noyau opérant sur des valeurs discrètes de y n'est pas compatible avec RandomOKTreesEmbedding, le noyau va être choisi linéaire (régression classique)") + warn("Un noyau opérant sur des valeurs discrètes de y n'est pas compatible avec RandomOKTreesEmbedding, le noyau va être choisi linéaire (régression classique)") self.kernel = "mse_reg" super().fit(X, y, sample_weight=sample_weight) @@ -1787,4 +1785,4 @@ def transform(self, X): Transformed dataset. """ check_is_fitted(self) - return self.one_hot_encoder_.transform(self.apply(X)) + return self.one_hot_encoder_.transform(self.apply(X)) \ No newline at end of file diff --git a/stpredictions/models/OK3/_reingold_tilford.py b/stpredictions/models/OK3/_reingold_tilford.py deleted file mode 100644 index 8f0b6af08..000000000 --- a/stpredictions/models/OK3/_reingold_tilford.py +++ /dev/null @@ -1,188 +0,0 @@ -# Authors: William Mill (bill@billmill.org) -# License: BSD 3 clause - -import numpy as np - - -class DrawTree: - def __init__(self, tree, parent=None, depth=0, number=1): - self.x = -1.0 - self.y = depth - self.tree = tree - self.children = [ - DrawTree(c, self, depth + 1, i + 1) for i, c in enumerate(tree.children) - ] - self.parent = parent - self.thread = None - self.mod = 0 - self.ancestor = self - self.change = self.shift = 0 - self._lmost_sibling = None - # this is the number of the node in its group of siblings 1..n - self.number = number - - def left(self): - return self.thread or len(self.children) and self.children[0] - - def right(self): - return self.thread or len(self.children) and self.children[-1] - - def lbrother(self): - n = None - if self.parent: - for node in self.parent.children: - if node == self: - return n - else: - n = node - return n - - def get_lmost_sibling(self): - if not self._lmost_sibling and self.parent and self != self.parent.children[0]: - self._lmost_sibling = self.parent.children[0] - return self._lmost_sibling - - lmost_sibling = property(get_lmost_sibling) - - def __str__(self): - return "%s: x=%s mod=%s" % (self.tree, self.x, self.mod) - - def __repr__(self): - return self.__str__() - - def max_extents(self): - extents = [c.max_extents() for c in self.children] - extents.append((self.x, self.y)) - return np.max(extents, axis=0) - - -def buchheim(tree): - dt = first_walk(DrawTree(tree)) - min = second_walk(dt) - if min < 0: - third_walk(dt, -min) - return dt - - -def third_walk(tree, n): - tree.x += n - for c in tree.children: - third_walk(c, n) - - -def first_walk(v, distance=1.0): - if len(v.children) == 0: - if v.lmost_sibling: - v.x = v.lbrother().x + distance - else: - v.x = 0.0 - else: - default_ancestor = v.children[0] - for w in v.children: - first_walk(w) - default_ancestor = apportion(w, default_ancestor, distance) - # print("finished v =", v.tree, "children") - execute_shifts(v) - - midpoint = (v.children[0].x + v.children[-1].x) / 2 - - w = v.lbrother() - if w: - v.x = w.x + distance - v.mod = v.x - midpoint - else: - v.x = midpoint - return v - - -def apportion(v, default_ancestor, distance): - w = v.lbrother() - if w is not None: - # in buchheim notation: - # i == inner; o == outer; r == right; l == left; r = +; l = - - vir = vor = v - vil = w - vol = v.lmost_sibling - sir = sor = v.mod - sil = vil.mod - sol = vol.mod - while vil.right() and vir.left(): - vil = vil.right() - vir = vir.left() - vol = vol.left() - vor = vor.right() - vor.ancestor = v - shift = (vil.x + sil) - (vir.x + sir) + distance - if shift > 0: - move_subtree(ancestor(vil, v, default_ancestor), v, shift) - sir = sir + shift - sor = sor + shift - sil += vil.mod - sir += vir.mod - sol += vol.mod - sor += vor.mod - if vil.right() and not vor.right(): - vor.thread = vil.right() - vor.mod += sil - sor - else: - if vir.left() and not vol.left(): - vol.thread = vir.left() - vol.mod += sir - sol - default_ancestor = v - return default_ancestor - - -def move_subtree(wl, wr, shift): - subtrees = wr.number - wl.number - # print(wl.tree, "is conflicted with", wr.tree, 'moving', subtrees, - # 'shift', shift) - # print wl, wr, wr.number, wl.number, shift, subtrees, shift/subtrees - wr.change -= shift / subtrees - wr.shift += shift - wl.change += shift / subtrees - wr.x += shift - wr.mod += shift - - -def execute_shifts(v): - shift = change = 0 - for w in v.children[::-1]: - # print("shift:", w, shift, w.change) - w.x += shift - w.mod += shift - change += w.change - shift += w.shift + change - - -def ancestor(vil, v, default_ancestor): - # the relevant text is at the bottom of page 7 of - # "Improving Walker's Algorithm to Run in Linear Time" by Buchheim et al, - # (2002) - # https://citeseerx.ist.psu.edu/doc_view/pid/1f41c3c2a4880dc49238e46d555f16d28da2940d - if vil.ancestor in v.parent.children: - return vil.ancestor - else: - return default_ancestor - - -def second_walk(v, m=0, depth=0, min=None): - v.x += m - v.y = depth - - if min is None or v.x < min: - min = v.x - - for w in v.children: - min = second_walk(w, m + v.mod, depth + 1, min) - - return min - - -class Tree: - def __init__(self, label="", node_id=-1, *children): - self.label = label - self.node_id = node_id - if children: - self.children = children - else: - self.children = [] diff --git a/stpredictions/models/OK3/_splitter.c b/stpredictions/models/OK3/_splitter.c new file mode 100644 index 000000000..3e8c4dfd9 --- /dev/null +++ b/stpredictions/models/OK3/_splitter.c @@ -0,0 +1,35305 @@ +/* Generated by Cython 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development version of Python. +#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) + #error Cython requires Python 2.6+ or Python 3.3+. +#else +#define CYTHON_ABI "0_29_23" +#define CYTHON_HEX_VERSION 0x001D17F0 +#define CYTHON_FUTURE_DIVISION 0 +#include +#ifndef offsetof + #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) +#endif +#if !defined(WIN32) && !defined(MS_WINDOWS) + #ifndef __stdcall + #define __stdcall + #endif + #ifndef __cdecl + #define __cdecl + #endif + #ifndef __fastcall + #define __fastcall + #endif +#endif +#ifndef DL_IMPORT + #define DL_IMPORT(t) t +#endif +#ifndef DL_EXPORT + #define DL_EXPORT(t) t +#endif +#define __PYX_COMMA , +#ifndef HAVE_LONG_LONG + #if PY_VERSION_HEX >= 0x02070000 + #define HAVE_LONG_LONG + #endif +#endif +#ifndef PY_LONG_LONG + #define PY_LONG_LONG LONG_LONG +#endif +#ifndef Py_HUGE_VAL + #define Py_HUGE_VAL HUGE_VAL +#endif +#ifdef PYPY_VERSION + #define 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CYTHON_FORMAT_SSIZE_T "z" +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) + #define __Pyx_DefaultClassType PyClass_Type +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#endif + #define __Pyx_DefaultClassType PyType_Type +#endif +#ifndef Py_TPFLAGS_CHECKTYPES + #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif +#ifndef Py_TPFLAGS_HAVE_FINALIZE + #define Py_TPFLAGS_HAVE_FINALIZE 0 +#endif +#ifndef METH_STACKLESS + #define METH_STACKLESS 0 +#endif +#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) + #ifndef METH_FASTCALL + #define METH_FASTCALL 0x80 + #endif + typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); + typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, + Py_ssize_t nargs, PyObject *kwnames); +#else + #define __Pyx_PyCFunctionFast _PyCFunctionFast + #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords +#endif +#if CYTHON_FAST_PYCCALL +#define __Pyx_PyFastCFunction_Check(func)\ + ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) +#else +#define __Pyx_PyFastCFunction_Check(func) 0 +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) + #define PyObject_Malloc(s) PyMem_Malloc(s) + #define PyObject_Free(p) PyMem_Free(p) + #define PyObject_Realloc(p) PyMem_Realloc(p) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 + #define PyMem_RawMalloc(n) PyMem_Malloc(n) + #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) + #define PyMem_RawFree(p) PyMem_Free(p) +#endif +#if CYTHON_COMPILING_IN_PYSTON + #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) +#else + #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) +#endif +#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#elif PY_VERSION_HEX >= 0x03060000 + #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() +#elif PY_VERSION_HEX >= 0x03000000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#else + #define __Pyx_PyThreadState_Current _PyThreadState_Current +#endif +#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) +#include "pythread.h" +#define Py_tss_NEEDS_INIT 0 +typedef int Py_tss_t; +static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { + *key = PyThread_create_key(); + return 0; +} +static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { + Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); + *key = Py_tss_NEEDS_INIT; + return key; +} +static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { + PyObject_Free(key); +} +static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { + return *key != Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { + PyThread_delete_key(*key); + *key = Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { + return PyThread_set_key_value(*key, value); +} +static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { + return PyThread_get_key_value(*key); +} +#endif +#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) +#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) +#else +#define __Pyx_PyDict_NewPresized(n) PyDict_New() +#endif +#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS +#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) +#else +#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) +#endif +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) + #define CYTHON_PEP393_ENABLED 1 + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ + 0 : _PyUnicode_Ready((PyObject *)(op))) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) + #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) + #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) + #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif +#else + #define CYTHON_PEP393_ENABLED 0 + #define PyUnicode_1BYTE_KIND 1 + #define PyUnicode_2BYTE_KIND 2 + #define PyUnicode_4BYTE_KIND 4 + #define __Pyx_PyUnicode_READY(op) (0) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) + #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) + #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) + #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) +#endif +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) +#else + #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ + PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) + #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) + #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) +#endif +#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) +#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) +#else + #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) +#endif +#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) + #define PyObject_ASCII(o) PyObject_Repr(o) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode + #define PyObject_Unicode PyObject_Str +#endif +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) + #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) +#else + #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) + #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif +#if CYTHON_ASSUME_SAFE_MACROS + #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) +#else + #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define PyNumber_Int PyNumber_Long +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif +#if PY_VERSION_HEX < 0x030200A4 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t PyInt_AsLong +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) +#endif +#if CYTHON_USE_ASYNC_SLOTS + #if PY_VERSION_HEX >= 0x030500B1 + #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods + #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) + #else + #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) + #endif +#else + #define __Pyx_PyType_AsAsync(obj) NULL +#endif +#ifndef __Pyx_PyAsyncMethodsStruct + typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; + } __Pyx_PyAsyncMethodsStruct; +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include +#ifdef NAN +#define __PYX_NAN() ((float) NAN) +#else +static CYTHON_INLINE float __PYX_NAN() { + float value; + memset(&value, 0xFF, sizeof(value)); + return value; +} +#endif +#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) +#define __Pyx_truncl trunc +#else +#define __Pyx_truncl truncl +#endif + +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } +#define __PYX_ERR(f_index, lineno, Ln_error) \ + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#define __PYX_HAVE___splitter +#define __PYX_HAVE_API___splitter +/* Early includes */ +#include +#include +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + +#include +#include "pythread.h" +#include "pystate.h" +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) +#define CYTHON_WITHOUT_ASSERTIONS +#endif + +typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; + const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; + +#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) +#define __PYX_DEFAULT_STRING_ENCODING "" +#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString +#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX))) ) +static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { + return (size_t) i < (size_t) limit; +} +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (_MSC_VER) + #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); +#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) +#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); +#if PY_MAJOR_VERSION < 3 + #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#else + #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize +#endif +#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { + const Py_UNICODE *u_end = u; + while (*u_end++) ; + return (size_t)(u_end - u - 1); +} +#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) +#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode +#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); +#define __Pyx_PySequence_Tuple(obj)\ + (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +#if CYTHON_ASSUME_SAFE_MACROS +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#else +#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) +#endif +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) +#else +#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) +#endif +#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII +static int __Pyx_sys_getdefaultencoding_not_ascii; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + PyObject* ascii_chars_u = NULL; + PyObject* ascii_chars_b = NULL; + const char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + if (strcmp(default_encoding_c, "ascii") == 0) { + __Pyx_sys_getdefaultencoding_not_ascii = 0; + } else { + char ascii_chars[128]; + int c; + for (c = 0; c < 128; c++) { + ascii_chars[c] = c; + } + __Pyx_sys_getdefaultencoding_not_ascii = 1; + ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); + if (!ascii_chars_u) goto bad; + ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); + if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { + PyErr_Format( + PyExc_ValueError, + "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", + default_encoding_c); + goto bad; + } + Py_DECREF(ascii_chars_u); + Py_DECREF(ascii_chars_b); + } + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + Py_XDECREF(ascii_chars_u); + Py_XDECREF(ascii_chars_b); + return -1; +} +#endif +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) +#else +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +static char* __PYX_DEFAULT_STRING_ENCODING; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); + if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; + strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + return -1; +} +#endif +#endif + + +/* Test for GCC > 2.95 */ +#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) +#else /* !__GNUC__ or GCC < 2.95 */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ +static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } + +static PyObject *__pyx_m = NULL; +static PyObject *__pyx_d; +static PyObject *__pyx_b; +static PyObject *__pyx_cython_runtime = NULL; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static PyObject *__pyx_empty_unicode; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +/* Header.proto */ +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + + +static const char *__pyx_f[] = { + "stpredictions/models/OK3/_splitter.pyx", + "stringsource", + "stpredictions/models/OK3/_splitter.pxd", + "__init__.pxd", + "type.pxd", + "_criterion.pxd", + "_splitter.pxd", + "_tree.pxd", + "stpredictions/models/OK3/_criterion.pxd", + "_quad_tree.pxd", + "_utils.pxd", +}; +/* MemviewSliceStruct.proto */ +struct __pyx_memoryview_obj; +typedef struct { + struct __pyx_memoryview_obj *memview; + char *data; + Py_ssize_t shape[8]; + Py_ssize_t strides[8]; + Py_ssize_t suboffsets[8]; +} __Pyx_memviewslice; +#define __Pyx_MemoryView_Len(m) (m.shape[0]) + +/* Atomics.proto */ +#include +#ifndef CYTHON_ATOMICS + #define CYTHON_ATOMICS 1 +#endif +#define __pyx_atomic_int_type int +#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\ + (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\ + !defined(__i386__) + #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) + #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using GNU atomics" + #endif +#elif CYTHON_ATOMICS && defined(_MSC_VER) && 0 + #include + #undef __pyx_atomic_int_type + #define __pyx_atomic_int_type LONG + #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #pragma message ("Using MSVC atomics") + #endif +#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 + #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using Intel atomics" + #endif +#else + #undef CYTHON_ATOMICS + #define CYTHON_ATOMICS 0 + #ifdef __PYX_DEBUG_ATOMICS + #warning "Not using atomics" + #endif +#endif +typedef volatile __pyx_atomic_int_type __pyx_atomic_int; +#if CYTHON_ATOMICS + #define __pyx_add_acquisition_count(memview)\ + __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview)\ + __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) +#else + #define __pyx_add_acquisition_count(memview)\ + __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview)\ + __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) +#endif + +/* ForceInitThreads.proto */ +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + +/* NoFastGil.proto */ +#define __Pyx_PyGILState_Ensure PyGILState_Ensure +#define __Pyx_PyGILState_Release PyGILState_Release +#define __Pyx_FastGIL_Remember() +#define __Pyx_FastGIL_Forget() +#define __Pyx_FastGilFuncInit() + +/* BufferFormatStructs.proto */ +#define IS_UNSIGNED(type) (((type) -1) > 0) +struct __Pyx_StructField_; +#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) +typedef struct { + const char* name; + struct __Pyx_StructField_* fields; + size_t size; + size_t arraysize[8]; + int ndim; + char typegroup; + char is_unsigned; + int flags; +} __Pyx_TypeInfo; +typedef struct __Pyx_StructField_ { + __Pyx_TypeInfo* type; + const char* name; + size_t offset; +} __Pyx_StructField; +typedef struct { + __Pyx_StructField* field; + size_t parent_offset; +} __Pyx_BufFmt_StackElem; +typedef struct { + __Pyx_StructField root; + __Pyx_BufFmt_StackElem* head; + size_t fmt_offset; + size_t new_count, enc_count; + size_t struct_alignment; + int is_complex; + char enc_type; + char new_packmode; + char enc_packmode; + char is_valid_array; +} __Pyx_BufFmt_Context; + + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":689 + * # in Cython to enable them only on the right systems. + * + * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + */ +typedef npy_int8 __pyx_t_5numpy_int8_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":690 + * + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t + */ +typedef npy_int16 __pyx_t_5numpy_int16_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":691 + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< + * ctypedef npy_int64 int64_t + * #ctypedef npy_int96 int96_t + */ +typedef npy_int32 __pyx_t_5numpy_int32_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":692 + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< + * #ctypedef npy_int96 int96_t + * #ctypedef npy_int128 int128_t + */ +typedef npy_int64 __pyx_t_5numpy_int64_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":696 + * #ctypedef npy_int128 int128_t + * + * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + */ +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":697 + * + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t + */ +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":698 + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< + * ctypedef npy_uint64 uint64_t + * #ctypedef npy_uint96 uint96_t + */ +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":699 + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< + * #ctypedef npy_uint96 uint96_t + * #ctypedef npy_uint128 uint128_t + */ +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":703 + * #ctypedef npy_uint128 uint128_t + * + * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< + * ctypedef npy_float64 float64_t + * #ctypedef npy_float80 float80_t + */ +typedef npy_float32 __pyx_t_5numpy_float32_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":704 + * + * ctypedef npy_float32 float32_t + * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< + * #ctypedef npy_float80 float80_t + * #ctypedef npy_float128 float128_t + */ +typedef npy_float64 __pyx_t_5numpy_float64_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":713 + * # The int types are mapped a bit surprising -- + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t + */ +typedef npy_long __pyx_t_5numpy_int_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":714 + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong longlong_t + * + */ +typedef npy_longlong __pyx_t_5numpy_long_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":715 + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_ulong uint_t + */ +typedef npy_longlong __pyx_t_5numpy_longlong_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":717 + * ctypedef npy_longlong longlong_t + * + * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t + */ +typedef npy_ulong __pyx_t_5numpy_uint_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":718 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":719 + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_intp intp_t + */ +typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":721 + * ctypedef npy_ulonglong ulonglong_t + * + * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< + * ctypedef npy_uintp uintp_t + * + */ +typedef npy_intp __pyx_t_5numpy_intp_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":722 + * + * ctypedef npy_intp intp_t + * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< + * + * ctypedef npy_double float_t + */ +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":724 + * ctypedef npy_uintp uintp_t + * + * ctypedef npy_double float_t # <<<<<<<<<<<<<< + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t + */ +typedef npy_double __pyx_t_5numpy_float_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":725 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":726 + * ctypedef npy_double float_t + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cfloat cfloat_t + */ +typedef npy_longdouble __pyx_t_5numpy_longdouble_t; + +/* "sklearn/tree/_tree.pxd":16 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_7sklearn_4tree_5_tree_DTYPE_t; + +/* "sklearn/tree/_tree.pxd":17 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t; + +/* "sklearn/tree/_tree.pxd":18 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_7sklearn_4tree_5_tree_SIZE_t; + +/* "sklearn/tree/_tree.pxd":19 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_7sklearn_4tree_5_tree_INT32_t; + +/* "sklearn/tree/_tree.pxd":20 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * from ._splitter cimport Splitter + */ +typedef npy_uint32 __pyx_t_7sklearn_4tree_5_tree_UINT32_t; + +/* "neighbors/_quad_tree.pxd":13 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float32 __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t; + +/* "neighbors/_quad_tree.pxd":14 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t; + +/* "neighbors/_quad_tree.pxd":15 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_7sklearn_9neighbors_10_quad_tree_INT32_t; + +/* "neighbors/_quad_tree.pxd":16 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * # This is effectively an ifdef statement in Cython + */ +typedef npy_uint32 __pyx_t_7sklearn_9neighbors_10_quad_tree_UINT32_t; + +/* "sklearn/tree/_utils.pxd":16 + * from ..neighbors._quad_tree cimport Cell + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_7sklearn_4tree_6_utils_DTYPE_t; + +/* "sklearn/tree/_utils.pxd":17 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t; + +/* "sklearn/tree/_utils.pxd":18 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_7sklearn_4tree_6_utils_SIZE_t; + +/* "sklearn/tree/_utils.pxd":19 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_7sklearn_4tree_6_utils_INT32_t; + +/* "sklearn/tree/_utils.pxd":20 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * + */ +typedef npy_uint32 __pyx_t_7sklearn_4tree_6_utils_UINT32_t; +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< float > __pyx_t_float_complex; + #else + typedef float _Complex __pyx_t_float_complex; + #endif +#else + typedef struct { float real, imag; } __pyx_t_float_complex; +#endif +static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); + +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< double > __pyx_t_double_complex; + #else + typedef double _Complex __pyx_t_double_complex; + #endif +#else + typedef struct { double real, imag; } __pyx_t_double_complex; +#endif +static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); + + +/*--- Type declarations ---*/ +struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion; +struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion; +struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion; +struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter; +struct __pyx_obj_7sklearn_4tree_5_tree_Tree; +struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder; +struct __pyx_obj_10_criterion_Criterion; +struct __pyx_obj_10_criterion_KernelizedRegressionCriterion; +struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree; +struct __pyx_obj_7sklearn_4tree_6_utils_Stack; +struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap; +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue; +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator; +struct __pyx_obj_9_splitter_Splitter; +struct __pyx_obj_9_splitter_BaseDenseSplitter; +struct __pyx_obj_9_splitter_BestSplitter; +struct __pyx_obj_9_splitter_RandomSplitter; +struct __pyx_obj_9_splitter_BaseSparseSplitter; +struct __pyx_obj_9_splitter_BestSparseSplitter; +struct __pyx_obj_9_splitter_RandomSparseSplitter; +struct __pyx_array_obj; +struct __pyx_MemviewEnum_obj; +struct __pyx_memoryview_obj; +struct __pyx_memoryviewslice_obj; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":728 + * ctypedef npy_longdouble longdouble_t + * + * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t + */ +typedef npy_cfloat __pyx_t_5numpy_cfloat_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":729 + * + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< + * ctypedef npy_clongdouble clongdouble_t + * + */ +typedef npy_cdouble __pyx_t_5numpy_cdouble_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":730 + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cdouble complex_t + */ +typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":732 + * ctypedef npy_clongdouble clongdouble_t + * + * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< + * + * cdef inline object PyArray_MultiIterNew1(a): + */ +typedef npy_cdouble __pyx_t_5numpy_complex_t; +struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord; + +/* "_splitter.pxd":23 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef struct SplitRecord: # <<<<<<<<<<<<<< + * # Data to track sample split + * SIZE_t feature # Which feature to split on. + */ +struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + double threshold; + double improvement; + double impurity_left; + double impurity_right; +}; +struct __pyx_t_7sklearn_4tree_5_tree_Node; +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c; +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances; +struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build; + +/* "sklearn/tree/_tree.pxd":25 + * from ._splitter cimport SplitRecord + * + * cdef struct Node: # <<<<<<<<<<<<<< + * # Base storage structure for the nodes in a Tree object + * + */ +struct __pyx_t_7sklearn_4tree_5_tree_Node { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t left_child; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t right_child; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t threshold; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t impurity; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t weighted_n_node_samples; +}; + +/* "sklearn/tree/_tree.pxd":63 + * double weighted_n_samples) nogil except -1 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * + * cdef np.ndarray _get_value_ndarray(self) + */ +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c { + int __pyx_n; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; +}; + +/* "sklearn/tree/_tree.pxd":78 + * cdef object _decision_path_sparse_csr(self, object X) + * + * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< + * + * + */ +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances { + int __pyx_n; + PyObject *normalize; +}; + +/* "sklearn/tree/_tree.pxd":102 + * cdef double min_impurity_decrease # Impurity threshold for early stopping + * + * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< + * np.ndarray sample_weight=*) + * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) + */ +struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build { + int __pyx_n; + PyArrayObject *sample_weight; +}; +struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; + +/* "neighbors/_quad_tree.pxd":21 + * # It allows us to write printf debugging lines + * # and remove them at compile time + * cdef enum: # <<<<<<<<<<<<<< + * DEBUGFLAG = 0 + * + */ +enum { + __pyx_e_7sklearn_9neighbors_10_quad_tree_DEBUGFLAG = 0 +}; + +/* "neighbors/_quad_tree.pxd":29 + * # have is_leaf and max_width consecutive as it permits to avoid padding by + * # the compiler and keep the size coherent for both C and numpy data structures. + * cdef struct Cell: # <<<<<<<<<<<<<< + * # Base storage structure for cells in a QuadTree object + * + */ +struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell { + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t parent; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t children[8]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t point_index; + int is_leaf; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t squared_max_width; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t depth; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cumulative_size; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t center[3]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t barycenter[3]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t min_bounds[3]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t max_bounds[3]; +}; + +/* "neighbors/_quad_tree.pxd":75 + * + * # Point insertion methods + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< + * SIZE_t cell_id=*) nogil except -1 + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; +}; + +/* "neighbors/_quad_tree.pxd":77 + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, + * SIZE_t cell_id=*) nogil except -1 + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< + * SIZE_t point_index, SIZE_t size=* + * ) nogil + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t size; +}; + +/* "neighbors/_quad_tree.pxd":84 + * + * # Create a summary of the Tree compare to a query point + * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< + * float squared_theta=*, SIZE_t cell_id=*, long idx=* + * ) nogil + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize { + int __pyx_n; + float squared_theta; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + long idx; +}; + +/* "neighbors/_quad_tree.pxd":99 + * # Private array manipulation to manage the ``cells`` array + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 + * cdef np.ndarray _get_cell_ndarray(self) + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; +}; + +/* "neighbors/_quad_tree.pxd":100 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 + * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< + * cdef np.ndarray _get_cell_ndarray(self) + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; +}; +struct __pyx_t_7sklearn_4tree_6_utils_StackRecord; +struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord; +struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; + +/* "sklearn/tree/_utils.pxd":23 + * + * + * cdef enum: # <<<<<<<<<<<<<< + * # Max value for our rand_r replacement (near the bottom). + * # We don't use RAND_MAX because it's different across platforms and + */ +enum { + __pyx_e_7sklearn_4tree_6_utils_RAND_R_MAX = 0x7FFFFFFF +}; + +/* "sklearn/tree/_utils.pxd":70 + * + * # A record on the stack for depth-first tree growing + * cdef struct StackRecord: # <<<<<<<<<<<<<< + * SIZE_t start + * SIZE_t end + */ +struct __pyx_t_7sklearn_4tree_6_utils_StackRecord { + __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t parent; + int is_left; + double impurity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t n_constant_features; +}; + +/* "sklearn/tree/_utils.pxd":96 + * + * # A record on the frontier for best-first tree growing + * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< + * SIZE_t node_id + * SIZE_t start + */ +struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { + __pyx_t_7sklearn_4tree_6_utils_SIZE_t node_id; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t pos; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; + int is_leaf; + double impurity; + double impurity_left; + double impurity_right; + double improvement; +}; + +/* "sklearn/tree/_utils.pxd":127 + * + * # A record stored in the WeightedPQueue + * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< + * DOUBLE_t data + * DOUBLE_t weight + */ +struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord { + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t data; + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t weight; +}; +struct __pyx_t_9_splitter_SplitRecord; + +/* "_splitter.pxd":14 + * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef struct SplitRecord: # <<<<<<<<<<<<<< + * # Data to track sample split + * SIZE_t feature # Which feature to split on. + */ +struct __pyx_t_9_splitter_SplitRecord { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + double threshold; + double improvement; + double impurity_left; + double impurity_right; +}; + +/* "_criterion.pxd":21 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. It also computes the output statistics + */ +struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtab; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + double weighted_n_samples; + double weighted_n_node_samples; + double weighted_n_left; + double weighted_n_right; + double *sum_total; + double *sum_left; + double *sum_right; +}; + + +/* "_criterion.pxd":70 + * cdef double proxy_impurity_improvement(self) nogil + * + * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract criterion for classification.""" + * + */ +struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion { + struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t sum_stride; +}; + + +/* "_criterion.pxd":76 + * cdef SIZE_t sum_stride + * + * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract regression criterion.""" + * + */ +struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion { + struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; + double sq_sum_total; +}; + + +/* "_splitter.pxd":34 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ +struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtab; + struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *criterion; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + PyObject *random_state; + __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + double weighted_n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; +}; + + +/* "sklearn/tree/_tree.pxd":37 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. The tree structure is used for predictions and + */ +struct __pyx_obj_7sklearn_4tree_5_tree_Tree { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtab; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_n_classes; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t node_count; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; + struct __pyx_t_7sklearn_4tree_5_tree_Node *nodes; + double *value; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t value_stride; +}; + + +/* "sklearn/tree/_tree.pxd":85 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ +struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtab; + struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *splitter; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_split; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; + double min_impurity_split; + double min_impurity_decrease; +}; + + +/* "_criterion.pxd":12 + * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. + */ +struct __pyx_obj_10_criterion_Criterion { + PyObject_HEAD + struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtab; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + double weighted_n_samples; + double weighted_n_node_samples; + double weighted_n_left; + double weighted_n_right; +}; + + +/* "_criterion.pxd":50 + * + * + * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract kernelized output regression criterion.""" + * + */ +struct __pyx_obj_10_criterion_KernelizedRegressionCriterion { + struct __pyx_obj_10_criterion_Criterion __pyx_base; + double sum_diag_Gramm; + double sum_total_Gramm; + double sum_diag_Gramm_left; + double sum_diag_Gramm_right; + double sum_total_Gramm_left; + double sum_total_Gramm_right; +}; + + +/* "neighbors/_quad_tree.pxd":55 + * + * + * cdef class _QuadTree: # <<<<<<<<<<<<<< + * # The QuadTree object is a quad tree structure constructed by inserting + * # recursively points in the tree and splitting cells in 4 so that each + */ +struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtab; + int n_dimensions; + int verbose; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_cells_per_cell; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t max_depth; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_count; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_points; + struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *cells; +}; + + +/* "sklearn/tree/_utils.pxd":79 + * SIZE_t n_constant_features + * + * cdef class Stack: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t top + */ +struct __pyx_obj_7sklearn_4tree_6_utils_Stack { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t top; + struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *stack_; +}; + + +/* "sklearn/tree/_utils.pxd":108 + * double improvement + * + * cdef class PriorityHeap: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t heap_ptr + */ +struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t heap_ptr; + struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *heap_; +}; + + +/* "sklearn/tree/_utils.pxd":131 + * DOUBLE_t weight + * + * cdef class WeightedPQueue: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t array_ptr + */ +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t array_ptr; + struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *array_; +}; + + +/* "sklearn/tree/_utils.pxd":151 + * # ============================================================================= + * + * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< + * cdef SIZE_t initial_capacity + * cdef WeightedPQueue samples + */ +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t initial_capacity; + struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *samples; + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t total_weight; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t k; + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t sum_w_0_k; +}; + + +/* "_splitter.pxd":25 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ +struct __pyx_obj_9_splitter_Splitter { + PyObject_HEAD + struct __pyx_vtabstruct_9_splitter_Splitter *__pyx_vtab; + struct __pyx_obj_10_criterion_Criterion *criterion; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + PyObject *random_state; + __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + double weighted_n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; +}; + + +/* "_splitter.pyx":223 + * + * + * cdef class BaseDenseSplitter(Splitter): # <<<<<<<<<<<<<< + * cdef const DTYPE_t[:, :] X + * + */ +struct __pyx_obj_9_splitter_BaseDenseSplitter { + struct __pyx_obj_9_splitter_Splitter __pyx_base; + __Pyx_memviewslice X; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_total_samples; +}; + + +/* "_splitter.pyx":245 + * + * + * cdef class BestSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< + * """Splitter for finding the best split.""" + * def __reduce__(self): + */ +struct __pyx_obj_9_splitter_BestSplitter { + struct __pyx_obj_9_splitter_BaseDenseSplitter __pyx_base; +}; + + +/* "_splitter.pyx":564 + * + * + * cdef class RandomSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< + * """Splitter for finding the best random split.""" + * def __reduce__(self): + */ +struct __pyx_obj_9_splitter_RandomSplitter { + struct __pyx_obj_9_splitter_BaseDenseSplitter __pyx_base; +}; + + +/* "_splitter.pyx":761 + * + * + * cdef class BaseSparseSplitter(Splitter): # <<<<<<<<<<<<<< + * # The sparse splitter works only with csc sparse matrix format + * cdef DTYPE_t* X_data + */ +struct __pyx_obj_9_splitter_BaseSparseSplitter { + struct __pyx_obj_9_splitter_Splitter __pyx_base; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *X_data; + __pyx_t_7sklearn_4tree_5_tree_INT32_t *X_indices; + __pyx_t_7sklearn_4tree_5_tree_INT32_t *X_indptr; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_total_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *index_to_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *sorted_samples; +}; + + +/* "_splitter.pyx":1080 + * + * + * cdef class BestSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< + * """Splitter for finding the best split, using the sparse data.""" + * + */ +struct __pyx_obj_9_splitter_BestSparseSplitter { + struct __pyx_obj_9_splitter_BaseSparseSplitter __pyx_base; +}; + + +/* "_splitter.pyx":1309 + * + * + * cdef class RandomSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< + * """Splitter for finding a random split, using the sparse data.""" + * + */ +struct __pyx_obj_9_splitter_RandomSparseSplitter { + struct __pyx_obj_9_splitter_BaseSparseSplitter __pyx_base; +}; + + +/* "View.MemoryView":105 + * + * @cname("__pyx_array") + * cdef class array: # <<<<<<<<<<<<<< + * + * cdef: + */ +struct __pyx_array_obj { + PyObject_HEAD + struct __pyx_vtabstruct_array *__pyx_vtab; + char *data; + Py_ssize_t len; + char *format; + int ndim; + Py_ssize_t *_shape; + Py_ssize_t *_strides; + Py_ssize_t itemsize; + PyObject *mode; + PyObject *_format; + void (*callback_free_data)(void *); + int free_data; + int dtype_is_object; +}; + + +/* "View.MemoryView":279 + * + * @cname('__pyx_MemviewEnum') + * cdef class Enum(object): # <<<<<<<<<<<<<< + * cdef object name + * def __init__(self, name): + */ +struct __pyx_MemviewEnum_obj { + PyObject_HEAD + PyObject *name; +}; + + +/* "View.MemoryView":330 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ +struct __pyx_memoryview_obj { + PyObject_HEAD + struct __pyx_vtabstruct_memoryview *__pyx_vtab; + PyObject *obj; + PyObject *_size; + PyObject *_array_interface; + PyThread_type_lock lock; + __pyx_atomic_int acquisition_count[2]; + __pyx_atomic_int *acquisition_count_aligned_p; + Py_buffer view; + int flags; + int dtype_is_object; + __Pyx_TypeInfo *typeinfo; +}; + + +/* "View.MemoryView":965 + * + * @cname('__pyx_memoryviewslice') + * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< + * "Internal class for passing memoryview slices to Python" + * + */ +struct __pyx_memoryviewslice_obj { + struct __pyx_memoryview_obj __pyx_base; + __Pyx_memviewslice from_slice; + PyObject *from_object; + PyObject *(*to_object_func)(char *); + int (*to_dtype_func)(char *, PyObject *); +}; + + + +/* "_criterion.pxd":21 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. It also computes the output statistics + */ + +struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion { + int (*init)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double, double, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_Criterion; + + +/* "_criterion.pxd":70 + * cdef double proxy_impurity_improvement(self) nogil + * + * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract criterion for classification.""" + * + */ + +struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion { + struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; +}; +static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_ClassificationCriterion; + + +/* "_criterion.pxd":76 + * cdef SIZE_t sum_stride + * + * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract regression criterion.""" + * + */ + +struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion { + struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; +}; +static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_RegressionCriterion; + + +/* "_splitter.pxd":34 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ + +struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter { + int (*init)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); + int (*node_reset)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); + int (*node_split)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double, struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); + void (*node_value)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double *); + double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtabptr_7sklearn_4tree_9_splitter_Splitter; + + +/* "sklearn/tree/_tree.pxd":37 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. The tree structure is used for predictions and + */ + +struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double); + int (*_resize)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args); + PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); + PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); + PyArrayObject *(*predict)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*apply)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*_apply_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyObject *(*decision_path)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyObject *(*_decision_path_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyObject *(*compute_feature_importances)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklearn_4tree_5_tree_Tree; + + +/* "sklearn/tree/_tree.pxd":85 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ + +struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder { + PyObject *(*build)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args); + PyObject *(*_check_input)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder; + + +/* "_criterion.pxd":12 + * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. + */ + +struct __pyx_vtabstruct_10_criterion_Criterion { + int (*init)(struct __pyx_obj_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *); +}; +static struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtabptr_10_criterion_Criterion; + + +/* "_criterion.pxd":50 + * + * + * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract kernelized output regression criterion.""" + * + */ + +struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion { + struct __pyx_vtabstruct_10_criterion_Criterion __pyx_base; +}; +static struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_10_criterion_KernelizedRegressionCriterion; + + +/* "neighbors/_quad_tree.pxd":55 + * + * + * cdef class _QuadTree: # <<<<<<<<<<<<<< + * # The QuadTree object is a quad tree structure constructed by inserting + * # recursively points in the tree and splitting cells in 4 so that each + */ + +struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree { + int (*insert_point)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); + int (*_is_duplicate)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); + long (*summarize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); + void (*_init_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); + void (*_init_root)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); + int (*_check_point_in_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); + int (*_resize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); + int (*_get_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); + PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *); +}; +static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtabptr_7sklearn_9neighbors_10_quad_tree__QuadTree; + + +/* "sklearn/tree/_utils.pxd":79 + * SIZE_t n_constant_features + * + * cdef class Stack: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t top + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack { + int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7sklearn_4tree_6_utils_Stack; + + +/* "sklearn/tree/_utils.pxd":108 + * double improvement + * + * cdef class PriorityHeap: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t heap_ptr + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap { + int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); + void (*heapify_up)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + void (*heapify_down)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, double, double, double); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabptr_7sklearn_4tree_6_utils_PriorityHeap; + + +/* "sklearn/tree/_utils.pxd":131 + * DOUBLE_t weight + * + * cdef class WeightedPQueue: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t array_ptr + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue { + int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); + int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); + __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); + int (*peek)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedPQueue; + + +/* "sklearn/tree/_utils.pxd":151 + * # ============================================================================= + * + * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< + * cdef SIZE_t initial_capacity + * cdef WeightedPQueue samples + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator { + __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); + int (*update_median_parameters_post_push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); + int (*update_median_parameters_post_remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedMedianCalculator; + + +/* "_splitter.pyx":41 + * self.improvement = -INFINITY + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * """Abstract splitter class. + * + */ + +struct __pyx_vtabstruct_9_splitter_Splitter { + int (*init)(struct __pyx_obj_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); + int (*node_reset)(struct __pyx_obj_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); + int (*node_split)(struct __pyx_obj_9_splitter_Splitter *, double, struct __pyx_t_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); + void (*node_value)(struct __pyx_obj_9_splitter_Splitter *, double *); + double (*node_impurity)(struct __pyx_obj_9_splitter_Splitter *); +}; +static struct __pyx_vtabstruct_9_splitter_Splitter *__pyx_vtabptr_9_splitter_Splitter; + + +/* "_splitter.pyx":223 + * + * + * cdef class BaseDenseSplitter(Splitter): # <<<<<<<<<<<<<< + * cdef const DTYPE_t[:, :] X + * + */ + +struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter { + struct __pyx_vtabstruct_9_splitter_Splitter __pyx_base; +}; +static struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter *__pyx_vtabptr_9_splitter_BaseDenseSplitter; + + +/* "_splitter.pyx":245 + * + * + * cdef class BestSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< + * """Splitter for finding the best split.""" + * def __reduce__(self): + */ + +struct __pyx_vtabstruct_9_splitter_BestSplitter { + struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter __pyx_base; +}; +static struct __pyx_vtabstruct_9_splitter_BestSplitter *__pyx_vtabptr_9_splitter_BestSplitter; + + +/* "_splitter.pyx":564 + * + * + * cdef class RandomSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< + * """Splitter for finding the best random split.""" + * def __reduce__(self): + */ + +struct __pyx_vtabstruct_9_splitter_RandomSplitter { + struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter __pyx_base; +}; +static struct __pyx_vtabstruct_9_splitter_RandomSplitter *__pyx_vtabptr_9_splitter_RandomSplitter; + + +/* "_splitter.pyx":761 + * + * + * cdef class BaseSparseSplitter(Splitter): # <<<<<<<<<<<<<< + * # The sparse splitter works only with csc sparse matrix format + * cdef DTYPE_t* X_data + */ + +struct __pyx_vtabstruct_9_splitter_BaseSparseSplitter { + struct __pyx_vtabstruct_9_splitter_Splitter __pyx_base; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_partition)(struct __pyx_obj_9_splitter_BaseSparseSplitter *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + void (*extract_nnz)(struct __pyx_obj_9_splitter_BaseSparseSplitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, int *); +}; +static struct __pyx_vtabstruct_9_splitter_BaseSparseSplitter *__pyx_vtabptr_9_splitter_BaseSparseSplitter; +static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_9_splitter_BaseSparseSplitter *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); +static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_9_splitter_BaseSparseSplitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, int *); + + +/* "_splitter.pyx":1080 + * + * + * cdef class BestSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< + * """Splitter for finding the best split, using the sparse data.""" + * + */ + +struct __pyx_vtabstruct_9_splitter_BestSparseSplitter { + struct __pyx_vtabstruct_9_splitter_BaseSparseSplitter __pyx_base; +}; +static struct __pyx_vtabstruct_9_splitter_BestSparseSplitter *__pyx_vtabptr_9_splitter_BestSparseSplitter; + + +/* "_splitter.pyx":1309 + * + * + * cdef class RandomSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< + * """Splitter for finding a random split, using the sparse data.""" + * + */ + +struct __pyx_vtabstruct_9_splitter_RandomSparseSplitter { + struct __pyx_vtabstruct_9_splitter_BaseSparseSplitter __pyx_base; +}; +static struct __pyx_vtabstruct_9_splitter_RandomSparseSplitter *__pyx_vtabptr_9_splitter_RandomSparseSplitter; + + +/* "View.MemoryView":105 + * + * @cname("__pyx_array") + * cdef class array: # <<<<<<<<<<<<<< + * + * cdef: + */ + +struct __pyx_vtabstruct_array { + PyObject *(*get_memview)(struct __pyx_array_obj *); +}; +static struct __pyx_vtabstruct_array *__pyx_vtabptr_array; + + +/* "View.MemoryView":330 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ + +struct __pyx_vtabstruct_memoryview { + char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); + PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); 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+#else +#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) +#endif + +/* PyObjectCall.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); +#else +#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) +#endif + +/* GetItemInt.proto */ +#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ + __Pyx_GetItemInt_Generic(o, to_py_func(i)))) +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck); + +/* MemviewSliceInit.proto */ +#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d +#define __Pyx_MEMVIEW_DIRECT 1 +#define __Pyx_MEMVIEW_PTR 2 +#define __Pyx_MEMVIEW_FULL 4 +#define __Pyx_MEMVIEW_CONTIG 8 +#define __Pyx_MEMVIEW_STRIDED 16 +#define __Pyx_MEMVIEW_FOLLOW 32 +#define __Pyx_IS_C_CONTIG 1 +#define __Pyx_IS_F_CONTIG 2 +static int __Pyx_init_memviewslice( + struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference); +static CYTHON_INLINE int __pyx_add_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p) +#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview)) +#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__) +#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__) +static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + +/* PyThreadStateGet.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate; +#define __Pyx_PyThreadState_assign __pyx_tstate = __Pyx_PyThreadState_Current; +#define __Pyx_PyErr_Occurred() __pyx_tstate->curexc_type +#else +#define __Pyx_PyThreadState_declare +#define __Pyx_PyThreadState_assign +#define __Pyx_PyErr_Occurred() PyErr_Occurred() +#endif + +/* PyErrFetchRestore.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL) +#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) +#else +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#endif +#else +#define __Pyx_PyErr_Clear() PyErr_Clear() +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) +#endif + +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + +/* PyObjectCallMethO.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); +#endif + +/* PyObjectCallNoArg.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); +#else +#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) +#endif + +/* PyObjectCallOneArg.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); + +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + +/* GetModuleGlobalName.proto */ +#if CYTHON_USE_DICT_VERSIONS +#define __Pyx_GetModuleGlobalName(var, name) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + (var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\ + (likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\ + __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +#define __Pyx_GetModuleGlobalNameUncached(var, name) {\ + PY_UINT64_T __pyx_dict_version;\ + PyObject *__pyx_dict_cached_value;\ + (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value); +#else +#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) +#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); +#endif + +/* IsLittleEndian.proto */ +static CYTHON_INLINE int __Pyx_Is_Little_Endian(void); + +/* BufferFormatCheck.proto */ +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts); +static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type); + +/* BufferGetAndValidate.proto */ +#define __Pyx_GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)\ + ((obj == Py_None || obj == NULL) ?\ + (__Pyx_ZeroBuffer(buf), 0) :\ + __Pyx__GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)) +static int __Pyx__GetBufferAndValidate(Py_buffer* buf, PyObject* obj, + __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack); +static void __Pyx_ZeroBuffer(Py_buffer* buf); +static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); +static Py_ssize_t __Pyx_minusones[] = { -1, -1, -1, -1, -1, -1, -1, -1 }; +static Py_ssize_t __Pyx_zeros[] = { 0, 0, 0, 0, 0, 0, 0, 0 }; + +/* GetTopmostException.proto */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); +#endif + +/* SaveResetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +#else +#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) +#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) +#endif + +/* PyErrExceptionMatches.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) +static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); +#else +#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) +#endif + +/* GetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* PyObjectCall2Args.proto */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); + +/* IncludeStringH.proto */ +#include + +/* BytesEquals.proto */ +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); + +/* UnicodeEquals.proto */ +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals); + +/* StrEquals.proto */ +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals +#else +#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals +#endif + +/* UnaryNegOverflows.proto */ +#define UNARY_NEG_WOULD_OVERFLOW(x)\ + (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) + +static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/ +/* GetAttr.proto */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); + +/* ObjectGetItem.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key); +#else +#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) +#endif + +/* decode_c_string_utf16.proto */ +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 0; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = -1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} + +/* decode_c_string.proto */ +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); + +/* GetAttr3.proto */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *); + +/* RaiseTooManyValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); + +/* RaiseNeedMoreValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); + +/* RaiseNoneIterError.proto */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); + +/* SwapException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* Import.proto */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + +/* FastTypeChecks.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); +#else +#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) +#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) +#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) +#endif +#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) + +static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +/* ListCompAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len)) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) +#endif + +/* PyIntBinop.proto */ +#if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); +#else +#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ + (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) +#endif + +/* ListExtend.proto */ +static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject* none = _PyList_Extend((PyListObject*)L, v); + if (unlikely(!none)) + return -1; + Py_DECREF(none); + return 0; +#else + return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v); +#endif +} + +/* ListAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_PyList_Append(L,x) PyList_Append(L,x) +#endif + +/* None.proto */ +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); + +/* ImportFrom.proto */ +static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); + +/* HasAttr.proto */ +static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *); + +/* PyObject_GenericGetAttrNoDict.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr +#endif + +/* PyObject_GenericGetAttr.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr +#endif + +/* SetVTable.proto */ +static int __Pyx_SetVtable(PyObject *dict, void *vtable); + +/* PyObjectGetAttrStrNoError.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); + +/* SetupReduce.proto */ +static int __Pyx_setup_reduce(PyObject* type_obj); + +/* TypeImport.proto */ +#ifndef __PYX_HAVE_RT_ImportType_proto +#define __PYX_HAVE_RT_ImportType_proto +enum __Pyx_ImportType_CheckSize { + __Pyx_ImportType_CheckSize_Error = 0, + __Pyx_ImportType_CheckSize_Warn = 1, + __Pyx_ImportType_CheckSize_Ignore = 2 +}; +static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); +#endif + +/* GetVTable.proto */ +static void* __Pyx_GetVtable(PyObject *dict); + +/* CLineInTraceback.proto */ +#ifdef CYTHON_CLINE_IN_TRACEBACK +#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) +#else +static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); +#endif + +/* CodeObjectCache.proto */ +typedef struct { + PyCodeObject* code_object; + int code_line; +} __Pyx_CodeObjectCacheEntry; +struct __Pyx_CodeObjectCache { + int count; + int max_count; + __Pyx_CodeObjectCacheEntry* entries; +}; +static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); +static PyCodeObject *__pyx_find_code_object(int code_line); +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); + +/* AddTraceback.proto */ +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename); + +#if PY_MAJOR_VERSION < 3 + static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); + static void __Pyx_ReleaseBuffer(Py_buffer *view); +#else + #define __Pyx_GetBuffer PyObject_GetBuffer + #define __Pyx_ReleaseBuffer PyBuffer_Release +#endif + + +/* BufferStructDeclare.proto */ +typedef struct { + Py_ssize_t shape, strides, suboffsets; +} __Pyx_Buf_DimInfo; +typedef struct { + size_t refcount; + Py_buffer pybuffer; +} __Pyx_Buffer; +typedef struct { + __Pyx_Buffer *rcbuffer; + char *data; + __Pyx_Buf_DimInfo diminfo[8]; +} __Pyx_LocalBuf_ND; + +/* MemviewSliceIsContig.proto */ +static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); + +/* OverlappingSlices.proto */ +static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize); + +/* Capsule.proto */ +static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); + +/* GCCDiagnostics.proto */ +#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) +#define __Pyx_HAS_GCC_DIAGNOSTIC +#endif + +/* RealImag.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #define __Pyx_CREAL(z) ((z).real()) + #define __Pyx_CIMAG(z) ((z).imag()) + #else + #define __Pyx_CREAL(z) (__real__(z)) + #define __Pyx_CIMAG(z) (__imag__(z)) + #endif +#else + #define __Pyx_CREAL(z) ((z).real) + #define __Pyx_CIMAG(z) ((z).imag) +#endif +#if defined(__cplusplus) && CYTHON_CCOMPLEX\ + && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) + #define __Pyx_SET_CREAL(z,x) ((z).real(x)) + #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) +#else + #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) + #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_float(a, b) ((a)==(b)) + #define __Pyx_c_sum_float(a, b) ((a)+(b)) + #define __Pyx_c_diff_float(a, b) ((a)-(b)) + #define __Pyx_c_prod_float(a, b) ((a)*(b)) + #define __Pyx_c_quot_float(a, b) ((a)/(b)) + #define __Pyx_c_neg_float(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_float(z) ((z)==(float)0) + #define __Pyx_c_conj_float(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_float(z) (::std::abs(z)) + #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_float(z) ((z)==0) + #define __Pyx_c_conj_float(z) (conjf(z)) + #if 1 + #define __Pyx_c_abs_float(z) (cabsf(z)) + #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); + #endif +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_double(a, b) ((a)==(b)) + #define __Pyx_c_sum_double(a, b) ((a)+(b)) + #define __Pyx_c_diff_double(a, b) ((a)-(b)) + #define __Pyx_c_prod_double(a, b) ((a)*(b)) + #define __Pyx_c_quot_double(a, b) ((a)/(b)) + #define __Pyx_c_neg_double(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_double(z) ((z)==(double)0) + #define __Pyx_c_conj_double(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (::std::abs(z)) + #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_double(z) ((z)==0) + #define __Pyx_c_conj_double(z) (conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (cabs(z)) + #define __Pyx_c_pow_double(a, b) (cpow(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); + #endif +#endif + +/* MemviewSliceCopyTemplate.proto */ +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object); + +/* CIntFromPy.proto */ +static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE npy_uint32 __Pyx_PyInt_As_npy_uint32(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_int32(npy_int32 value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); + +/* TypeInfoCompare.proto */ +static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); + +/* MemviewSliceValidateAndInit.proto */ +static int __Pyx_ValidateAndInit_memviewslice( + int *axes_specs, + int c_or_f_flag, + int buf_flags, + int ndim, + __Pyx_TypeInfo *dtype, + __Pyx_BufFmt_StackElem stack[], + __Pyx_memviewslice *memviewslice, + PyObject *original_obj); + +/* ObjectToMemviewSlice.proto */ +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t__const__(PyObject *, int writable_flag); + +/* CheckBinaryVersion.proto */ +static int __Pyx_check_binary_version(void); + +/* VoidPtrImport.proto */ +static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig); + +/* FunctionImport.proto */ +static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig); + +/* InitStrings.proto */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); + +static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ +static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, double *__pyx_v_weighted_n_node_samples); /* proto*/ +static int __pyx_f_9_splitter_8Splitter_node_split(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED double __pyx_v_impurity, CYTHON_UNUSED struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ +static void __pyx_f_9_splitter_8Splitter_node_value(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, double *__pyx_v_dest); /* proto*/ +static double __pyx_f_9_splitter_8Splitter_node_impurity(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto*/ +static int __pyx_f_9_splitter_17BaseDenseSplitter_init(struct __pyx_obj_9_splitter_BaseDenseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ +static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_splitter_BestSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ +static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_splitter_RandomSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ +static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ +static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, double __pyx_v_threshold, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_zero_pos); /* proto*/ +static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_feature, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive, int *__pyx_v_is_samples_sorted); /* proto*/ +static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9_splitter_BestSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ +static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj_9_splitter_RandomSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ +static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ +static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ +static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ + +/* Module declarations from 'cpython.buffer' */ + +/* Module declarations from 'libc.string' */ + +/* Module declarations from 'libc.stdio' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.type' */ +static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; + +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + +/* Module declarations from 'cpython.mem' */ + +/* Module declarations from 'numpy' */ + +/* Module declarations from 'numpy' */ +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; +static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; +static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; +static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; +static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; +static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ + +/* Module declarations from 'sklearn.tree._criterion' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_Criterion = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_ClassificationCriterion = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_RegressionCriterion = 0; + +/* Module declarations from 'sklearn.tree._splitter' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_9_splitter_Splitter = 0; + +/* Module declarations from 'sklearn.tree._tree' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_Tree = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_TreeBuilder = 0; + +/* Module declarations from '_criterion' */ +static PyTypeObject *__pyx_ptype_10_criterion_Criterion = 0; +static PyTypeObject *__pyx_ptype_10_criterion_KernelizedRegressionCriterion = 0; + +/* Module declarations from 'libc.stdlib' */ + +/* Module declarations from 'sklearn.neighbors._quad_tree' */ +static PyTypeObject *__pyx_ptype_7sklearn_9neighbors_10_quad_tree__QuadTree = 0; +static float *__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON = 0; +#define __pyx_v_7sklearn_9neighbors_10_quad_tree_EPSILON (*__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON) + +/* Module declarations from 'sklearn.tree._utils' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_Stack = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_PriorityHeap = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedPQueue = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedMedianCalculator = 0; +static __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*__pyx_f_7sklearn_4tree_6_utils_rand_int)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_UINT32_t *); /*proto*/ +static double (*__pyx_f_7sklearn_4tree_6_utils_rand_uniform)(double, double, __pyx_t_7sklearn_4tree_6_utils_UINT32_t *); /*proto*/ +static double (*__pyx_f_7sklearn_4tree_6_utils_log)(double); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DTYPE_t **, size_t); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t **, size_t); /*proto*/ +static unsigned char *(*__pyx_fuse_2__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **, size_t); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t ***, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_5_tree_Node *(*__pyx_fuse_6__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_5_tree_Node **(*__pyx_fuse_8__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node ***, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_StackRecord **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord **, size_t); /*proto*/ + +/* Module declarations from '_splitter' */ +static PyTypeObject *__pyx_ptype_9_splitter_Splitter = 0; +static PyTypeObject *__pyx_ptype_9_splitter_BaseDenseSplitter = 0; +static PyTypeObject *__pyx_ptype_9_splitter_BestSplitter = 0; +static PyTypeObject *__pyx_ptype_9_splitter_RandomSplitter = 0; +static PyTypeObject *__pyx_ptype_9_splitter_BaseSparseSplitter = 0; +static PyTypeObject *__pyx_ptype_9_splitter_BestSparseSplitter = 0; +static PyTypeObject *__pyx_ptype_9_splitter_RandomSparseSplitter = 0; +static PyTypeObject *__pyx_array_type = 0; +static PyTypeObject *__pyx_MemviewEnum_type = 0; +static PyTypeObject *__pyx_memoryview_type = 0; +static PyTypeObject *__pyx_memoryviewslice_type = 0; +static double __pyx_v_9_splitter_INFINITY; +static __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_9_splitter_FEATURE_THRESHOLD; +static __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_9_splitter_EXTRACT_NNZ_SWITCH; +static PyObject *generic = 0; +static PyObject *strided = 0; +static PyObject *indirect = 0; +static PyObject *contiguous = 0; +static PyObject *indirect_contiguous = 0; +static int __pyx_memoryview_thread_locks_used; +static PyThread_type_lock __pyx_memoryview_thread_locks[8]; +static CYTHON_INLINE void __pyx_f_9_splitter__init_split(struct __pyx_t_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ +static CYTHON_INLINE void __pyx_f_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ +static CYTHON_INLINE void __pyx_f_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ +static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_median3(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ +static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int); /*proto*/ +static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ +static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ +static int __pyx_f_9_splitter_compare_SIZE_t(void const *, void const *); /*proto*/ +static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t *); /*proto*/ +static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_t_7sklearn_4tree_5_tree_INT32_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); /*proto*/ +static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, int *); /*proto*/ +static CYTHON_INLINE void __pyx_f_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ +static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ +static void *__pyx_align_pointer(void *, size_t); /*proto*/ +static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ +static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ +static PyObject *_unellipsify(PyObject *, int); /*proto*/ +static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ +static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ +static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ +static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ +static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ +static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ +static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ +static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ +static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ +static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ +static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ +static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ +static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t = { "DTYPE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_INT32_t = { "INT32_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_INT32_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_7sklearn_4tree_5_tree_INT32_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_7sklearn_4tree_5_tree_INT32_t), 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t__const__ = { "const DTYPE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const ), { 0 }, 0, 'R', 0, 0 }; +#define __Pyx_MODULE_NAME "_splitter" +extern int __pyx_module_is_main__splitter; +int __pyx_module_is_main__splitter = 0; + +/* Implementation of '_splitter' */ +static PyObject *__pyx_builtin_range; +static PyObject *__pyx_builtin_TypeError; +static PyObject *__pyx_builtin_ValueError; +static PyObject *__pyx_builtin_ImportError; +static PyObject *__pyx_builtin_MemoryError; +static PyObject *__pyx_builtin_enumerate; +static PyObject *__pyx_builtin_Ellipsis; +static PyObject *__pyx_builtin_id; +static PyObject *__pyx_builtin_IndexError; +static const char __pyx_k_O[] = "O"; +static const char __pyx_k_c[] = "c"; +static const char __pyx_k_id[] = "id"; +static const char __pyx_k_np[] = "np"; +static const char __pyx_k_inf[] = "inf"; +static const char __pyx_k_new[] = "__new__"; +static const char __pyx_k_obj[] = "obj"; +static const char __pyx_k_base[] = "base"; +static const char __pyx_k_data[] = "data"; +static const char __pyx_k_dict[] = "__dict__"; +static const char __pyx_k_main[] = "__main__"; +static const char __pyx_k_mode[] = "mode"; +static const char __pyx_k_name[] = "name"; +static const char __pyx_k_ndim[] = "ndim"; +static const char __pyx_k_pack[] = "pack"; +static const char __pyx_k_size[] = "size"; +static const char __pyx_k_step[] = "step"; +static const char __pyx_k_stop[] = "stop"; +static const char __pyx_k_test[] = "__test__"; +static const char __pyx_k_ASCII[] = "ASCII"; +static const char __pyx_k_class[] = "__class__"; +static const char __pyx_k_error[] = "error"; +static const char __pyx_k_flags[] = "flags"; +static const char __pyx_k_numpy[] = "numpy"; +static const char __pyx_k_range[] = "range"; +static const char __pyx_k_shape[] = "shape"; +static const char __pyx_k_start[] = "start"; +static const char __pyx_k_encode[] = "encode"; +static const char __pyx_k_format[] = "format"; +static const char __pyx_k_import[] = "__import__"; +static const char __pyx_k_indptr[] = "indptr"; +static const char __pyx_k_name_2[] = "__name__"; +static const char __pyx_k_pickle[] = "pickle"; +static const char __pyx_k_reduce[] = "__reduce__"; +static const char __pyx_k_struct[] = "struct"; +static const char __pyx_k_unpack[] = "unpack"; +static const char __pyx_k_update[] = "update"; +static const char __pyx_k_fortran[] = "fortran"; +static const char __pyx_k_indices[] = "indices"; +static const char __pyx_k_memview[] = "memview"; +static const char __pyx_k_randint[] = "randint"; +static const char __pyx_k_Ellipsis[] = "Ellipsis"; +static const char __pyx_k_Splitter[] = "Splitter"; +static const char __pyx_k_getstate[] = "__getstate__"; +static const char __pyx_k_itemsize[] = "itemsize"; +static const char __pyx_k_pyx_type[] = "__pyx_type"; +static const char __pyx_k_setstate[] = "__setstate__"; +static const char __pyx_k_TypeError[] = "TypeError"; +static const char __pyx_k_criterion[] = "criterion"; +static const char __pyx_k_enumerate[] = "enumerate"; +static const char __pyx_k_pyx_state[] = "__pyx_state"; +static const char __pyx_k_reduce_ex[] = "__reduce_ex__"; +static const char __pyx_k_IndexError[] = "IndexError"; +static const char __pyx_k_ValueError[] = "ValueError"; +static const char __pyx_k_csc_matrix[] = "csc_matrix"; +static const char __pyx_k_pyx_result[] = "__pyx_result"; +static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; +static const char __pyx_k_ImportError[] = "ImportError"; +static const char __pyx_k_MemoryError[] = "MemoryError"; +static const char __pyx_k_PickleError[] = "PickleError"; +static const char __pyx_k_BestSplitter[] = "BestSplitter"; +static const char __pyx_k_max_features[] = "max_features"; +static const char __pyx_k_pyx_checksum[] = "__pyx_checksum"; +static const char __pyx_k_random_state[] = "random_state"; +static const char __pyx_k_scipy_sparse[] = "scipy.sparse"; +static const char __pyx_k_stringsource[] = "stringsource"; +static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; +static const char __pyx_k_reduce_cython[] = "__reduce_cython__"; +static const char __pyx_k_RandomSplitter[] = "RandomSplitter"; +static const char __pyx_k_View_MemoryView[] = "View.MemoryView"; +static const char __pyx_k_allocate_buffer[] = "allocate_buffer"; +static const char __pyx_k_dtype_is_object[] = "dtype_is_object"; +static const char __pyx_k_min_weight_leaf[] = "min_weight_leaf"; +static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError"; +static const char __pyx_k_setstate_cython[] = "__setstate_cython__"; +static const char __pyx_k_min_samples_leaf[] = "min_samples_leaf"; +static const char __pyx_k_BaseDenseSplitter[] = "BaseDenseSplitter"; +static const char __pyx_k_pyx_unpickle_Enum[] = "__pyx_unpickle_Enum"; +static const char __pyx_k_BaseSparseSplitter[] = "BaseSparseSplitter"; +static const char __pyx_k_BestSparseSplitter[] = "BestSparseSplitter"; +static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; +static const char __pyx_k_strided_and_direct[] = ""; +static const char __pyx_k_RandomSparseSplitter[] = "RandomSparseSplitter"; +static const char __pyx_k_strided_and_indirect[] = ""; +static const char __pyx_k_contiguous_and_direct[] = ""; +static const char __pyx_k_MemoryView_of_r_object[] = ""; +static const char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; +static const char __pyx_k_contiguous_and_indirect[] = ""; +static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; +static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; +static const char __pyx_k_X_should_be_in_csc_format[] = "X should be in csc format"; +static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; +static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; +static const char __pyx_k_strided_and_direct_or_indirect[] = ""; +static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; +static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; +static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; +static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview"; +static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview"; +static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; +static const char __pyx_k_Incompatible_checksums_s_vs_0xb0[] = "Incompatible checksums (%s vs 0xb068931 = (name))"; +static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; +static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; +static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; +static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; +static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; +static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; +static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; +static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; +static PyObject *__pyx_n_s_ASCII; +static PyObject *__pyx_n_s_BaseDenseSplitter; +static PyObject *__pyx_n_s_BaseSparseSplitter; +static PyObject *__pyx_n_s_BestSparseSplitter; +static PyObject *__pyx_n_s_BestSplitter; +static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; +static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; +static PyObject *__pyx_kp_s_Cannot_assign_to_read_only_memor; +static PyObject *__pyx_kp_s_Cannot_create_writable_memory_vi; +static PyObject *__pyx_kp_s_Cannot_index_with_type_s; +static PyObject *__pyx_n_s_Ellipsis; +static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; +static PyObject *__pyx_n_s_ImportError; +static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xb0; +static PyObject *__pyx_n_s_IndexError; +static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; +static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; +static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; +static PyObject *__pyx_n_s_MemoryError; +static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; +static PyObject *__pyx_kp_s_MemoryView_of_r_object; +static PyObject *__pyx_n_b_O; +static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; +static PyObject *__pyx_n_s_PickleError; +static PyObject *__pyx_n_s_RandomSparseSplitter; +static PyObject *__pyx_n_s_RandomSplitter; +static PyObject *__pyx_n_s_Splitter; +static PyObject *__pyx_n_s_TypeError; +static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; +static PyObject *__pyx_n_s_ValueError; +static PyObject *__pyx_n_s_View_MemoryView; +static PyObject *__pyx_kp_s_X_should_be_in_csc_format; +static PyObject *__pyx_n_s_allocate_buffer; +static PyObject *__pyx_n_s_base; +static PyObject *__pyx_n_s_c; +static PyObject *__pyx_n_u_c; +static PyObject *__pyx_n_s_class; +static PyObject *__pyx_n_s_cline_in_traceback; +static PyObject *__pyx_kp_s_contiguous_and_direct; +static PyObject *__pyx_kp_s_contiguous_and_indirect; +static PyObject *__pyx_n_s_criterion; +static PyObject *__pyx_n_s_csc_matrix; +static PyObject *__pyx_n_s_data; +static PyObject *__pyx_n_s_dict; +static PyObject *__pyx_n_s_dtype_is_object; +static PyObject *__pyx_n_s_encode; +static PyObject *__pyx_n_s_enumerate; +static PyObject *__pyx_n_s_error; +static PyObject *__pyx_n_s_flags; +static PyObject *__pyx_n_s_format; +static PyObject *__pyx_n_s_fortran; +static PyObject *__pyx_n_u_fortran; +static PyObject *__pyx_n_s_getstate; +static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; +static PyObject *__pyx_n_s_id; +static PyObject *__pyx_n_s_import; +static PyObject *__pyx_n_s_indices; +static PyObject *__pyx_n_s_indptr; +static PyObject *__pyx_n_s_inf; +static PyObject *__pyx_n_s_itemsize; +static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; +static PyObject *__pyx_n_s_main; +static PyObject *__pyx_n_s_max_features; +static PyObject *__pyx_n_s_memview; +static PyObject *__pyx_n_s_min_samples_leaf; +static PyObject *__pyx_n_s_min_weight_leaf; +static PyObject *__pyx_n_s_mode; +static PyObject *__pyx_n_s_name; +static PyObject *__pyx_n_s_name_2; +static PyObject *__pyx_n_s_ndim; +static PyObject *__pyx_n_s_new; +static PyObject *__pyx_kp_s_no_default___reduce___due_to_non; +static PyObject *__pyx_n_s_np; +static PyObject *__pyx_n_s_numpy; +static PyObject *__pyx_kp_s_numpy_core_multiarray_failed_to; +static PyObject *__pyx_kp_s_numpy_core_umath_failed_to_impor; +static PyObject *__pyx_n_s_obj; +static PyObject *__pyx_n_s_pack; +static PyObject *__pyx_n_s_pickle; +static PyObject *__pyx_n_s_pyx_PickleError; +static PyObject *__pyx_n_s_pyx_checksum; +static PyObject *__pyx_n_s_pyx_getbuffer; +static PyObject *__pyx_n_s_pyx_result; +static PyObject *__pyx_n_s_pyx_state; +static PyObject *__pyx_n_s_pyx_type; +static PyObject *__pyx_n_s_pyx_unpickle_Enum; +static PyObject *__pyx_n_s_pyx_vtable; +static PyObject *__pyx_n_s_randint; +static PyObject *__pyx_n_s_random_state; +static PyObject *__pyx_n_s_range; +static PyObject *__pyx_n_s_reduce; +static PyObject *__pyx_n_s_reduce_cython; +static PyObject *__pyx_n_s_reduce_ex; +static PyObject *__pyx_n_s_scipy_sparse; +static PyObject *__pyx_n_s_setstate; +static PyObject *__pyx_n_s_setstate_cython; +static PyObject *__pyx_n_s_shape; +static PyObject *__pyx_n_s_size; +static PyObject *__pyx_n_s_start; +static PyObject *__pyx_n_s_step; +static PyObject *__pyx_n_s_stop; +static PyObject *__pyx_kp_s_strided_and_direct; +static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; +static PyObject *__pyx_kp_s_strided_and_indirect; +static PyObject *__pyx_kp_s_stringsource; +static PyObject *__pyx_n_s_struct; +static PyObject *__pyx_n_s_test; +static PyObject *__pyx_kp_s_unable_to_allocate_array_data; +static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; +static PyObject *__pyx_n_s_unpack; +static PyObject *__pyx_n_s_update; +static int __pyx_pf_9_splitter_8Splitter___cinit__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, struct __pyx_obj_10_criterion_Criterion *__pyx_v_criterion, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, PyObject *__pyx_v_random_state); /* proto */ +static void __pyx_pf_9_splitter_8Splitter_2__dealloc__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_9_splitter_8Splitter_4__getstate__(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_9_splitter_8Splitter_6__setstate__(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d); /* proto */ +static PyObject *__pyx_pf_9_splitter_8Splitter_9criterion___get__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ +static int __pyx_pf_9_splitter_8Splitter_9criterion_2__set__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static int __pyx_pf_9_splitter_8Splitter_9criterion_4__del__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_9_splitter_8Splitter_12max_features___get__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ +static int __pyx_pf_9_splitter_8Splitter_12max_features_2__set__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_9_splitter_8Splitter_16min_samples_leaf___get__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ +static int __pyx_pf_9_splitter_8Splitter_16min_samples_leaf_2__set__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_9_splitter_8Splitter_15min_weight_leaf___get__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ +static int __pyx_pf_9_splitter_8Splitter_15min_weight_leaf_2__set__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_9_splitter_8Splitter_8__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_9_splitter_8Splitter_10__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_9_splitter_17BaseDenseSplitter___reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_BaseDenseSplitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_9_splitter_17BaseDenseSplitter_2__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_BaseDenseSplitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_9_splitter_12BestSplitter___reduce__(struct __pyx_obj_9_splitter_BestSplitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_obj_9_splitter_RandomSplitter *__pyx_v_self); /* proto */ +static int __pyx_pf_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_criterion, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, CYTHON_UNUSED double __pyx_v_min_weight_leaf, CYTHON_UNUSED PyObject *__pyx_v_random_state); /* proto */ +static void __pyx_pf_9_splitter_18BaseSparseSplitter_2__dealloc__(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_9_splitter_18BaseSparseSplitter_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_9_splitter_18BaseSparseSplitter_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __pyx_obj_9_splitter_BestSparseSplitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_9_splitter_20RandomSparseSplitter___reduce__(struct __pyx_obj_9_splitter_RandomSparseSplitter *__pyx_v_self); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_12__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf___pyx_array___reduce_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_array_2__setstate_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ +static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_MemviewEnum___reduce_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_MemviewEnum_2__setstate_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ +static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryview___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryview_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryviewslice___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView___pyx_unpickle_Enum(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_tp_new_9_splitter_Splitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_9_splitter_BaseDenseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_9_splitter_BestSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_9_splitter_RandomSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_9_splitter_BaseSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_9_splitter_BestSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_9_splitter_RandomSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_int_0; +static PyObject *__pyx_int_1; +static PyObject *__pyx_int_184977713; +static PyObject *__pyx_int_neg_1; +static PyObject *__pyx_tuple_; +static PyObject *__pyx_tuple__2; +static PyObject *__pyx_tuple__3; +static PyObject *__pyx_tuple__4; +static PyObject *__pyx_tuple__5; +static PyObject *__pyx_tuple__6; +static PyObject *__pyx_tuple__7; +static PyObject *__pyx_tuple__8; +static PyObject *__pyx_tuple__9; +static PyObject *__pyx_slice__24; +static PyObject *__pyx_tuple__10; +static PyObject *__pyx_tuple__11; +static PyObject *__pyx_tuple__12; +static PyObject *__pyx_tuple__13; +static PyObject *__pyx_tuple__14; +static PyObject *__pyx_tuple__15; +static PyObject *__pyx_tuple__16; +static PyObject *__pyx_tuple__17; +static PyObject *__pyx_tuple__18; +static PyObject *__pyx_tuple__19; +static PyObject *__pyx_tuple__20; +static PyObject *__pyx_tuple__21; +static PyObject *__pyx_tuple__22; +static PyObject *__pyx_tuple__23; +static PyObject *__pyx_tuple__25; +static PyObject *__pyx_tuple__26; +static PyObject *__pyx_tuple__27; +static PyObject *__pyx_tuple__28; +static PyObject *__pyx_tuple__29; +static PyObject *__pyx_tuple__30; +static PyObject *__pyx_tuple__31; +static PyObject *__pyx_tuple__32; +static PyObject *__pyx_tuple__33; +static PyObject *__pyx_codeobj__34; +/* Late includes */ + +/* "_splitter.pyx":33 + * cdef DTYPE_t EXTRACT_NNZ_SWITCH = 0.1 + * + * cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) nogil: # <<<<<<<<<<<<<< + * self.impurity_left = INFINITY + * self.impurity_right = INFINITY + */ + +static CYTHON_INLINE void __pyx_f_9_splitter__init_split(struct __pyx_t_9_splitter_SplitRecord *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_pos) { + + /* "_splitter.pyx":34 + * + * cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) nogil: + * self.impurity_left = INFINITY # <<<<<<<<<<<<<< + * self.impurity_right = INFINITY + * self.pos = start_pos + */ + __pyx_v_self->impurity_left = __pyx_v_9_splitter_INFINITY; + + /* "_splitter.pyx":35 + * cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) nogil: + * self.impurity_left = INFINITY + * self.impurity_right = INFINITY # <<<<<<<<<<<<<< + * self.pos = start_pos + * self.feature = 0 + */ + __pyx_v_self->impurity_right = __pyx_v_9_splitter_INFINITY; + + /* "_splitter.pyx":36 + * self.impurity_left = INFINITY + * self.impurity_right = INFINITY + * self.pos = start_pos # <<<<<<<<<<<<<< + * self.feature = 0 + * self.threshold = 0. + */ + __pyx_v_self->pos = __pyx_v_start_pos; + + /* "_splitter.pyx":37 + * self.impurity_right = INFINITY + * self.pos = start_pos + * self.feature = 0 # <<<<<<<<<<<<<< + * self.threshold = 0. + * self.improvement = -INFINITY + */ + __pyx_v_self->feature = 0; + + /* "_splitter.pyx":38 + * self.pos = start_pos + * self.feature = 0 + * self.threshold = 0. # <<<<<<<<<<<<<< + * self.improvement = -INFINITY + * + */ + __pyx_v_self->threshold = 0.; + + /* "_splitter.pyx":39 + * self.feature = 0 + * self.threshold = 0. + * self.improvement = -INFINITY # <<<<<<<<<<<<<< + * + * cdef class Splitter: + */ + __pyx_v_self->improvement = (-__pyx_v_9_splitter_INFINITY); + + /* "_splitter.pyx":33 + * cdef DTYPE_t EXTRACT_NNZ_SWITCH = 0.1 + * + * cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) nogil: # <<<<<<<<<<<<<< + * self.impurity_left = INFINITY + * self.impurity_right = INFINITY + */ + + /* function exit code */ +} + +/* "_splitter.pyx":48 + * """ + * + * def __cinit__(self, Criterion criterion, SIZE_t max_features, # <<<<<<<<<<<<<< + * SIZE_t min_samples_leaf, double min_weight_leaf, + * object random_state): + */ + +/* Python wrapper */ +static int __pyx_pw_9_splitter_8Splitter_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static int __pyx_pw_9_splitter_8Splitter_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + struct __pyx_obj_10_criterion_Criterion *__pyx_v_criterion = 0; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf; + double __pyx_v_min_weight_leaf; + PyObject *__pyx_v_random_state = 0; 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+ __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_t_3; + double __pyx_t_4; + int __pyx_t_5; + int __pyx_t_6; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_8; + Py_ssize_t __pyx_t_9; + Py_ssize_t __pyx_t_10; + int __pyx_t_11; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "_splitter.pyx":262 + * """ + * # Find the best split + * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< + * cdef SIZE_t start = self.start + * cdef SIZE_t end = self.end + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.samples; + __pyx_v_samples = __pyx_t_1; + + /* "_splitter.pyx":263 + * # Find the best split + * cdef SIZE_t* samples = self.samples + * cdef SIZE_t start = self.start # <<<<<<<<<<<<<< + * cdef SIZE_t end = self.end + * + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.start; + __pyx_v_start = __pyx_t_2; + + /* "_splitter.pyx":264 + * cdef SIZE_t* samples = self.samples + * cdef SIZE_t start = self.start + * cdef SIZE_t end = self.end # <<<<<<<<<<<<<< + * + * cdef SIZE_t* features = self.features + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end; + __pyx_v_end = __pyx_t_2; + + /* "_splitter.pyx":266 + * cdef SIZE_t end = self.end + * + * cdef SIZE_t* features = self.features # <<<<<<<<<<<<<< + * cdef SIZE_t* constant_features = self.constant_features + * cdef SIZE_t n_features = self.n_features + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.features; + __pyx_v_features = __pyx_t_1; + + /* "_splitter.pyx":267 + * + * cdef SIZE_t* features = self.features + * cdef SIZE_t* constant_features = self.constant_features # <<<<<<<<<<<<<< + * cdef SIZE_t n_features = self.n_features + * + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.constant_features; + __pyx_v_constant_features = __pyx_t_1; + + /* "_splitter.pyx":268 + * cdef SIZE_t* features = self.features + * cdef SIZE_t* constant_features = self.constant_features + * cdef SIZE_t n_features = self.n_features # <<<<<<<<<<<<<< + * + * cdef DTYPE_t* Xf = self.feature_values + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_features; + __pyx_v_n_features = __pyx_t_2; + + /* "_splitter.pyx":270 + * cdef SIZE_t n_features = self.n_features + * + * cdef DTYPE_t* Xf = self.feature_values # <<<<<<<<<<<<<< + * cdef SIZE_t max_features = self.max_features + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + */ + __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.feature_values; + __pyx_v_Xf = __pyx_t_3; + + /* "_splitter.pyx":271 + * + * cdef DTYPE_t* Xf = self.feature_values + * cdef SIZE_t max_features = self.max_features # <<<<<<<<<<<<<< + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + * cdef double min_weight_leaf = self.min_weight_leaf + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features; + __pyx_v_max_features = __pyx_t_2; + + /* "_splitter.pyx":272 + * cdef DTYPE_t* Xf = self.feature_values + * cdef SIZE_t max_features = self.max_features + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf # <<<<<<<<<<<<<< + * cdef double min_weight_leaf = self.min_weight_leaf + * cdef UINT32_t* random_state = &self.rand_r_state + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf; + __pyx_v_min_samples_leaf = __pyx_t_2; + + /* "_splitter.pyx":273 + * cdef SIZE_t max_features = self.max_features + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< + * cdef UINT32_t* random_state = &self.rand_r_state + * + */ + __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf; + __pyx_v_min_weight_leaf = __pyx_t_4; + + /* "_splitter.pyx":274 + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + * cdef double min_weight_leaf = self.min_weight_leaf + * cdef UINT32_t* random_state = &self.rand_r_state # <<<<<<<<<<<<<< + * + * cdef SplitRecord best, current + */ + __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state); + + /* "_splitter.pyx":277 + * + * cdef SplitRecord best, current + * cdef double current_proxy_improvement = -INFINITY # <<<<<<<<<<<<<< + * cdef double best_proxy_improvement = -INFINITY + * + */ + __pyx_v_current_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + + /* "_splitter.pyx":278 + * cdef SplitRecord best, current + * cdef double current_proxy_improvement = -INFINITY + * cdef double best_proxy_improvement = -INFINITY # <<<<<<<<<<<<<< + * + * cdef SIZE_t f_i = n_features + */ + __pyx_v_best_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + + /* "_splitter.pyx":280 + * cdef double best_proxy_improvement = -INFINITY + * + * cdef SIZE_t f_i = n_features # <<<<<<<<<<<<<< + * cdef SIZE_t f_j + * cdef SIZE_t p + */ + __pyx_v_f_i = __pyx_v_n_features; + + /* "_splitter.pyx":288 + * cdef SIZE_t j + * + * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< + * # Number of features discovered to be constant during the split search + * cdef SIZE_t n_found_constants = 0 + */ + __pyx_v_n_visited_features = 0; + + /* "_splitter.pyx":290 + * cdef SIZE_t n_visited_features = 0 + * # Number of features discovered to be constant during the split search + * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 + */ + __pyx_v_n_found_constants = 0; + + /* "_splitter.pyx":292 + * cdef SIZE_t n_found_constants = 0 + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< + * cdef SIZE_t n_known_constants = n_constant_features[0] + * # n_total_constants = n_known_constants + n_found_constants + */ + __pyx_v_n_drawn_constants = 0; + + /* "_splitter.pyx":293 + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 + * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< + * # n_total_constants = n_known_constants + n_found_constants + * cdef SIZE_t n_total_constants = n_known_constants + */ + __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); + + /* "_splitter.pyx":295 + * cdef SIZE_t n_known_constants = n_constant_features[0] + * # n_total_constants = n_known_constants + n_found_constants + * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< + * cdef DTYPE_t current_feature_value + * cdef SIZE_t partition_end + */ + __pyx_v_n_total_constants = __pyx_v_n_known_constants; + + /* "_splitter.pyx":299 + * cdef SIZE_t partition_end + * + * _init_split(&best, end) # <<<<<<<<<<<<<< + * + * # Sample up to max_features without replacement using a + */ + __pyx_f_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); + + /* "_splitter.pyx":310 + * # newly discovered constant features to spare computation on descendant + * # nodes. + * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< + * # are constant + * (n_visited_features < max_features or + */ + while (1) { + __pyx_t_6 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0); + if (__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L5_bool_binop_done; + } + + /* "_splitter.pyx":312 + * while (f_i > n_total_constants and # Stop early if remaining features + * # are constant + * (n_visited_features < max_features or # <<<<<<<<<<<<<< + * # At least one drawn features must be non constant + * n_visited_features <= n_found_constants + n_drawn_constants)): + */ + __pyx_t_6 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0); + if (!__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L5_bool_binop_done; + } + + /* "_splitter.pyx":314 + * (n_visited_features < max_features or + * # At least one drawn features must be non constant + * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< + * + * n_visited_features += 1 + */ + __pyx_t_6 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0); + __pyx_t_5 = __pyx_t_6; + __pyx_L5_bool_binop_done:; + if (!__pyx_t_5) break; + + /* "_splitter.pyx":316 + * n_visited_features <= n_found_constants + n_drawn_constants)): + * + * n_visited_features += 1 # <<<<<<<<<<<<<< + * + * # Loop invariant: elements of features in + */ + __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); + + /* "_splitter.pyx":330 + * + * # Draw a feature at random + * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< + * random_state) + * + */ + __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); + + /* "_splitter.pyx":333 + * random_state) + * + * if f_j < n_known_constants: # <<<<<<<<<<<<<< + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] + */ + __pyx_t_5 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":335 + * if f_j < n_known_constants: + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] # <<<<<<<<<<<<<< + * + * n_drawn_constants += 1 + */ + __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); + __pyx_t_7 = (__pyx_v_features[__pyx_v_n_drawn_constants]); + (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_2; + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; + + /* "_splitter.pyx":337 + * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] + * + * n_drawn_constants += 1 # <<<<<<<<<<<<<< + * + * else: + */ + __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); + + /* "_splitter.pyx":333 + * random_state) + * + * if f_j < n_known_constants: # <<<<<<<<<<<<<< + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] + */ + goto __pyx_L8; + } + + /* "_splitter.pyx":341 + * else: + * # f_j in the interval [n_known_constants, f_i - n_found_constants[ + * f_j += n_found_constants # <<<<<<<<<<<<<< + * # f_j in the interval [n_total_constants, f_i[ + * current.feature = features[f_j] + */ + /*else*/ { + __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); + + /* "_splitter.pyx":343 + * f_j += n_found_constants + * # f_j in the interval [n_total_constants, f_i[ + * current.feature = features[f_j] # <<<<<<<<<<<<<< + * + * # Sort samples along that feature; by + */ + __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); + + /* "_splitter.pyx":349 + * # sorting the array in a manner which utilizes the cache more + * # effectively. + * for i in range(start, end): # <<<<<<<<<<<<<< + * Xf[i] = self.X[samples[i], current.feature] + * + */ + __pyx_t_7 = __pyx_v_end; + __pyx_t_2 = __pyx_t_7; + for (__pyx_t_8 = __pyx_v_start; __pyx_t_8 < __pyx_t_2; __pyx_t_8+=1) { + __pyx_v_i = __pyx_t_8; + + /* "_splitter.pyx":350 + * # effectively. + * for i in range(start, end): + * Xf[i] = self.X[samples[i], current.feature] # <<<<<<<<<<<<<< + * + * sort(Xf + start, samples + start, end - start) + */ + if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 350, __pyx_L1_error)} + __pyx_t_9 = (__pyx_v_samples[__pyx_v_i]); + __pyx_t_10 = __pyx_v_current.feature; + (__pyx_v_Xf[__pyx_v_i]) = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_10 * __pyx_v_self->__pyx_base.X.strides[1]) ))); + } + + /* "_splitter.pyx":352 + * Xf[i] = self.X[samples[i], current.feature] + * + * sort(Xf + start, samples + start, end - start) # <<<<<<<<<<<<<< + * + * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: + */ + __pyx_f_9_splitter_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end - __pyx_v_start)); + + /* "_splitter.pyx":354 + * sort(Xf + start, samples + start, end - start) + * + * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< + * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] + * + */ + __pyx_t_5 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":355 + * + * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: + * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] # <<<<<<<<<<<<<< + * + * n_found_constants += 1 + */ + __pyx_t_7 = (__pyx_v_features[__pyx_v_n_total_constants]); + __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; + (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2; + + /* "_splitter.pyx":357 + * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] + * + * n_found_constants += 1 # <<<<<<<<<<<<<< + * n_total_constants += 1 + * + */ + __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); + + /* "_splitter.pyx":358 + * + * n_found_constants += 1 + * n_total_constants += 1 # <<<<<<<<<<<<<< + * + * else: + */ + __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); + + /* "_splitter.pyx":354 + * sort(Xf + start, samples + start, end - start) + * + * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< + * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] + * + */ + goto __pyx_L11; + } + + /* "_splitter.pyx":361 + * + * else: + * f_i -= 1 # <<<<<<<<<<<<<< + * features[f_i], features[f_j] = features[f_j], features[f_i] + * + */ + /*else*/ { + __pyx_v_f_i = (__pyx_v_f_i - 1); + + /* "_splitter.pyx":362 + * else: + * f_i -= 1 + * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< + * + * # Evaluate all splits + */ + __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); + __pyx_t_7 = (__pyx_v_features[__pyx_v_f_i]); + (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2; + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; + + /* "_splitter.pyx":365 + * + * # Evaluate all splits + * self.criterion.reset() # <<<<<<<<<<<<<< + * p = start + * + */ + __pyx_t_11 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 365, __pyx_L1_error) + + /* "_splitter.pyx":366 + * # Evaluate all splits + * self.criterion.reset() + * p = start # <<<<<<<<<<<<<< + * + * while p < end: + */ + __pyx_v_p = __pyx_v_start; + + /* "_splitter.pyx":368 + * p = start + * + * while p < end: # <<<<<<<<<<<<<< + * while (p + 1 < end and + * Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): + */ + while (1) { + __pyx_t_5 = ((__pyx_v_p < __pyx_v_end) != 0); + if (!__pyx_t_5) break; + + /* "_splitter.pyx":369 + * + * while p < end: + * while (p + 1 < end and # <<<<<<<<<<<<<< + * Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): + * p += 1 + */ + while (1) { + __pyx_t_6 = (((__pyx_v_p + 1) < __pyx_v_end) != 0); + if (__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L16_bool_binop_done; + } + + /* "_splitter.pyx":370 + * while p < end: + * while (p + 1 < end and + * Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): # <<<<<<<<<<<<<< + * p += 1 + * + */ + __pyx_t_6 = (((__pyx_v_Xf[(__pyx_v_p + 1)]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + __pyx_t_5 = __pyx_t_6; + __pyx_L16_bool_binop_done:; + if (!__pyx_t_5) break; + + /* "_splitter.pyx":371 + * while (p + 1 < end and + * Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): + * p += 1 # <<<<<<<<<<<<<< + * + * # (p + 1 >= end) or (X[samples[p + 1], current.feature] > + */ + __pyx_v_p = (__pyx_v_p + 1); + } + + /* "_splitter.pyx":375 + * # (p + 1 >= end) or (X[samples[p + 1], current.feature] > + * # X[samples[p], current.feature]) + * p += 1 # <<<<<<<<<<<<<< + * # (p >= end) or (X[samples[p], current.feature] > + * # X[samples[p - 1], current.feature]) + */ + __pyx_v_p = (__pyx_v_p + 1); + + /* "_splitter.pyx":379 + * # X[samples[p - 1], current.feature]) + * + * if p < end: # <<<<<<<<<<<<<< + * current.pos = p + * + */ + __pyx_t_5 = ((__pyx_v_p < __pyx_v_end) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":380 + * + * if p < end: + * current.pos = p # <<<<<<<<<<<<<< + * + * # Reject if min_samples_leaf is not guaranteed + */ + __pyx_v_current.pos = __pyx_v_p; + + /* "_splitter.pyx":383 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + __pyx_t_6 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0); + if (!__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L20_bool_binop_done; + } + + /* "_splitter.pyx":384 + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or + * ((end - current.pos) < min_samples_leaf)): # <<<<<<<<<<<<<< + * continue + * + */ + __pyx_t_6 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0); + __pyx_t_5 = __pyx_t_6; + __pyx_L20_bool_binop_done:; + + /* "_splitter.pyx":383 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + if (__pyx_t_5) { + + /* "_splitter.pyx":385 + * if (((current.pos - start) < min_samples_leaf) or + * ((end - current.pos) < min_samples_leaf)): + * continue # <<<<<<<<<<<<<< + * + * self.criterion.update(current.pos) + */ + goto __pyx_L12_continue; + + /* "_splitter.pyx":383 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + } + + /* "_splitter.pyx":387 + * continue + * + * self.criterion.update(current.pos) # <<<<<<<<<<<<<< + * + * # Reject if min_weight_leaf is not satisfied + */ + __pyx_t_11 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 387, __pyx_L1_error) + + /* "_splitter.pyx":390 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + __pyx_t_6 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_left < __pyx_v_min_weight_leaf) != 0); + if (!__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L23_bool_binop_done; + } + + /* "_splitter.pyx":391 + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or + * (self.criterion.weighted_n_right < min_weight_leaf)): # <<<<<<<<<<<<<< + * continue + * + */ + __pyx_t_6 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_right < __pyx_v_min_weight_leaf) != 0); + __pyx_t_5 = __pyx_t_6; + __pyx_L23_bool_binop_done:; + + /* "_splitter.pyx":390 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + if (__pyx_t_5) { + + /* "_splitter.pyx":392 + * if ((self.criterion.weighted_n_left < min_weight_leaf) or + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue # <<<<<<<<<<<<<< + * + * current_proxy_improvement = self.criterion.proxy_impurity_improvement() + */ + goto __pyx_L12_continue; + + /* "_splitter.pyx":390 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + } + + /* "_splitter.pyx":394 + * continue + * + * current_proxy_improvement = self.criterion.proxy_impurity_improvement() # <<<<<<<<<<<<<< + * + * # with gil: + */ + __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); + + /* "_splitter.pyx":402 + * # print() + * + * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< + * best_proxy_improvement = current_proxy_improvement + * # sum of halves is used to avoid infinite value + */ + __pyx_t_5 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":403 + * + * if current_proxy_improvement > best_proxy_improvement: + * best_proxy_improvement = current_proxy_improvement # <<<<<<<<<<<<<< + * # sum of halves is used to avoid infinite value + * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 + */ + __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement; + + /* "_splitter.pyx":405 + * best_proxy_improvement = current_proxy_improvement + * # sum of halves is used to avoid infinite value + * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 # <<<<<<<<<<<<<< + * + * if ((current.threshold == Xf[p]) or + */ + __pyx_v_current.threshold = (((__pyx_v_Xf[(__pyx_v_p - 1)]) / 2.0) + ((__pyx_v_Xf[__pyx_v_p]) / 2.0)); + + /* "_splitter.pyx":407 + * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 + * + * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< + * (current.threshold == INFINITY) or + * (current.threshold == -INFINITY)): + */ + __pyx_t_6 = ((__pyx_v_current.threshold == (__pyx_v_Xf[__pyx_v_p])) != 0); + if (!__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L27_bool_binop_done; + } + + /* "_splitter.pyx":408 + * + * if ((current.threshold == Xf[p]) or + * (current.threshold == INFINITY) or # <<<<<<<<<<<<<< + * (current.threshold == -INFINITY)): + * current.threshold = Xf[p - 1] + */ + __pyx_t_6 = ((__pyx_v_current.threshold == __pyx_v_9_splitter_INFINITY) != 0); + if (!__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L27_bool_binop_done; + } + + /* "_splitter.pyx":409 + * if ((current.threshold == Xf[p]) or + * (current.threshold == INFINITY) or + * (current.threshold == -INFINITY)): # <<<<<<<<<<<<<< + * current.threshold = Xf[p - 1] + * + */ + __pyx_t_6 = ((__pyx_v_current.threshold == (-__pyx_v_9_splitter_INFINITY)) != 0); + __pyx_t_5 = __pyx_t_6; + __pyx_L27_bool_binop_done:; + + /* "_splitter.pyx":407 + * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 + * + * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< + * (current.threshold == INFINITY) or + * (current.threshold == -INFINITY)): + */ + if (__pyx_t_5) { + + /* "_splitter.pyx":410 + * (current.threshold == INFINITY) or + * (current.threshold == -INFINITY)): + * current.threshold = Xf[p - 1] # <<<<<<<<<<<<<< + * + * best = current # copy + */ + __pyx_v_current.threshold = (__pyx_v_Xf[(__pyx_v_p - 1)]); + + /* "_splitter.pyx":407 + * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 + * + * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< + * (current.threshold == INFINITY) or + * (current.threshold == -INFINITY)): + */ + } + + /* "_splitter.pyx":412 + * current.threshold = Xf[p - 1] + * + * best = current # copy # <<<<<<<<<<<<<< + * + * # Reorganize into samples[start:best.pos] + samples[best.pos:end] + */ + __pyx_v_best = __pyx_v_current; + + /* "_splitter.pyx":402 + * # print() + * + * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< + * best_proxy_improvement = current_proxy_improvement + * # sum of halves is used to avoid infinite value + */ + } + + /* "_splitter.pyx":379 + * # X[samples[p - 1], current.feature]) + * + * if p < end: # <<<<<<<<<<<<<< + * current.pos = p + * + */ + } + __pyx_L12_continue:; + } + } + __pyx_L11:; + } + __pyx_L8:; + } + + /* "_splitter.pyx":415 + * + * # Reorganize into samples[start:best.pos] + samples[best.pos:end] + * if best.pos < end: # <<<<<<<<<<<<<< + * partition_end = end + * p = start + */ + __pyx_t_5 = ((__pyx_v_best.pos < __pyx_v_end) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":416 + * # Reorganize into samples[start:best.pos] + samples[best.pos:end] + * if best.pos < end: + * partition_end = end # <<<<<<<<<<<<<< + * p = start + * + */ + __pyx_v_partition_end = __pyx_v_end; + + /* "_splitter.pyx":417 + * if best.pos < end: + * partition_end = end + * p = start # <<<<<<<<<<<<<< + * + * while p < partition_end: + */ + __pyx_v_p = __pyx_v_start; + + /* "_splitter.pyx":419 + * p = start + * + * while p < partition_end: # <<<<<<<<<<<<<< + * if self.X[samples[p], best.feature] <= best.threshold: + * p += 1 + */ + while (1) { + __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0); + if (!__pyx_t_5) break; + + /* "_splitter.pyx":420 + * + * while p < partition_end: + * if self.X[samples[p], best.feature] <= best.threshold: # <<<<<<<<<<<<<< + * p += 1 + * + */ + if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 420, __pyx_L1_error)} + __pyx_t_10 = (__pyx_v_samples[__pyx_v_p]); + __pyx_t_9 = __pyx_v_best.feature; + __pyx_t_5 = (((*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_10 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))) <= __pyx_v_best.threshold) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":421 + * while p < partition_end: + * if self.X[samples[p], best.feature] <= best.threshold: + * p += 1 # <<<<<<<<<<<<<< + * + * else: + */ + __pyx_v_p = (__pyx_v_p + 1); + + /* "_splitter.pyx":420 + * + * while p < partition_end: + * if self.X[samples[p], best.feature] <= best.threshold: # <<<<<<<<<<<<<< + * p += 1 + * + */ + goto __pyx_L33; + } + + /* "_splitter.pyx":424 + * + * else: + * partition_end -= 1 # <<<<<<<<<<<<<< + * + * samples[p], samples[partition_end] = samples[partition_end], samples[p] + */ + /*else*/ { + __pyx_v_partition_end = (__pyx_v_partition_end - 1); + + /* "_splitter.pyx":426 + * partition_end -= 1 + * + * samples[p], samples[partition_end] = samples[partition_end], samples[p] # <<<<<<<<<<<<<< + * + * self.criterion.reset() + */ + __pyx_t_7 = (__pyx_v_samples[__pyx_v_partition_end]); + __pyx_t_2 = (__pyx_v_samples[__pyx_v_p]); + (__pyx_v_samples[__pyx_v_p]) = __pyx_t_7; + (__pyx_v_samples[__pyx_v_partition_end]) = __pyx_t_2; + } + __pyx_L33:; + } + + /* "_splitter.pyx":428 + * samples[p], samples[partition_end] = samples[partition_end], samples[p] + * + * self.criterion.reset() # <<<<<<<<<<<<<< + * self.criterion.update(best.pos) + * best.improvement = self.criterion.impurity_improvement(impurity) + */ + __pyx_t_11 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 428, __pyx_L1_error) + + /* "_splitter.pyx":429 + * + * self.criterion.reset() + * self.criterion.update(best.pos) # <<<<<<<<<<<<<< + * best.improvement = self.criterion.impurity_improvement(impurity) + * self.criterion.children_impurity(&best.impurity_left, + */ + __pyx_t_11 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 429, __pyx_L1_error) + + /* "_splitter.pyx":430 + * self.criterion.reset() + * self.criterion.update(best.pos) + * best.improvement = self.criterion.impurity_improvement(impurity) # <<<<<<<<<<<<<< + * self.criterion.children_impurity(&best.impurity_left, + * &best.impurity_right) + */ + __pyx_v_best.improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); + + /* "_splitter.pyx":431 + * self.criterion.update(best.pos) + * best.improvement = self.criterion.impurity_improvement(impurity) + * self.criterion.children_impurity(&best.impurity_left, # <<<<<<<<<<<<<< + * &best.impurity_right) + * + */ + ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); + + /* "_splitter.pyx":415 + * + * # Reorganize into samples[start:best.pos] + samples[best.pos:end] + * if best.pos < end: # <<<<<<<<<<<<<< + * partition_end = end + * p = start + */ + } + + /* "_splitter.pyx":437 + * # element in features[:n_known_constants] must be preserved for sibling + * # and child nodes + * memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) # <<<<<<<<<<<<<< + * + * # Copy newly found constant features + */ + (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants))); + + /* "_splitter.pyx":440 + * + * # Copy newly found constant features + * memcpy(constant_features + n_known_constants, # <<<<<<<<<<<<<< + * features + n_known_constants, + * sizeof(SIZE_t) * n_found_constants) + */ + (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants))); + + /* "_splitter.pyx":445 + * + * # Return values + * split[0] = best # <<<<<<<<<<<<<< + * n_constant_features[0] = n_total_constants + * return 0 + */ + (__pyx_v_split[0]) = __pyx_v_best; + + /* "_splitter.pyx":446 + * # Return values + * split[0] = best + * n_constant_features[0] = n_total_constants # <<<<<<<<<<<<<< + * return 0 + * + */ + (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants; + + /* "_splitter.pyx":447 + * split[0] = best + * n_constant_features[0] = n_total_constants + * return 0 # <<<<<<<<<<<<<< + * + * + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "_splitter.pyx":254 + * self.random_state), self.__getstate__()) + * + * cdef int node_split(self, double impurity, SplitRecord* split, # <<<<<<<<<<<<<< + * SIZE_t* n_constant_features) nogil except -1: + * """Find the best split on node samples[start:end] + */ + + /* function exit code */ + __pyx_L1_error:; + { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); + #endif + __Pyx_AddTraceback("_splitter.BestSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename); + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + } + __pyx_r = -1; + __pyx_L0:; + return __pyx_r; +} + +/* "_splitter.pyx":452 + * # Sort n-element arrays pointed to by Xf and samples, simultaneously, + * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). + * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: # <<<<<<<<<<<<<< + * if n == 0: + * return + */ + +static CYTHON_INLINE void __pyx_f_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) { + int __pyx_v_maxd; + int __pyx_t_1; + + /* "_splitter.pyx":453 + * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). + * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: + * if n == 0: # <<<<<<<<<<<<<< + * return + * cdef int maxd = 2 * log(n) + */ + __pyx_t_1 = ((__pyx_v_n == 0) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":454 + * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: + * if n == 0: + * return # <<<<<<<<<<<<<< + * cdef int maxd = 2 * log(n) + * introsort(Xf, samples, n, maxd) + */ + goto __pyx_L0; + + /* "_splitter.pyx":453 + * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). + * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: + * if n == 0: # <<<<<<<<<<<<<< + * return + * cdef int maxd = 2 * log(n) + */ + } + + /* "_splitter.pyx":455 + * if n == 0: + * return + * cdef int maxd = 2 * log(n) # <<<<<<<<<<<<<< + * introsort(Xf, samples, n, maxd) + * + */ + __pyx_v_maxd = (2 * ((int)__pyx_f_7sklearn_4tree_6_utils_log(__pyx_v_n))); + + /* "_splitter.pyx":456 + * return + * cdef int maxd = 2 * log(n) + * introsort(Xf, samples, n, maxd) # <<<<<<<<<<<<<< + * + * + */ + __pyx_f_9_splitter_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n, __pyx_v_maxd); + + /* "_splitter.pyx":452 + * # Sort n-element arrays pointed to by Xf and samples, simultaneously, + * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). + * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: # <<<<<<<<<<<<<< + * if n == 0: + * return + */ + + /* function exit code */ + __pyx_L0:; +} + +/* "_splitter.pyx":459 + * + * + * cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< + * SIZE_t i, SIZE_t j) nogil: + * # Helper for sort + */ + +static CYTHON_INLINE void __pyx_f_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j) { + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_1; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_2; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_3; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4; + + /* "_splitter.pyx":462 + * SIZE_t i, SIZE_t j) nogil: + * # Helper for sort + * Xf[i], Xf[j] = Xf[j], Xf[i] # <<<<<<<<<<<<<< + * samples[i], samples[j] = samples[j], samples[i] + * + */ + __pyx_t_1 = (__pyx_v_Xf[__pyx_v_j]); + __pyx_t_2 = (__pyx_v_Xf[__pyx_v_i]); + (__pyx_v_Xf[__pyx_v_i]) = __pyx_t_1; + (__pyx_v_Xf[__pyx_v_j]) = __pyx_t_2; + + /* "_splitter.pyx":463 + * # Helper for sort + * Xf[i], Xf[j] = Xf[j], Xf[i] + * samples[i], samples[j] = samples[j], samples[i] # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_3 = (__pyx_v_samples[__pyx_v_j]); + __pyx_t_4 = (__pyx_v_samples[__pyx_v_i]); + (__pyx_v_samples[__pyx_v_i]) = __pyx_t_3; + (__pyx_v_samples[__pyx_v_j]) = __pyx_t_4; + + /* "_splitter.pyx":459 + * + * + * cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< + * SIZE_t i, SIZE_t j) nogil: + * # Helper for sort + */ + + /* function exit code */ +} + +/* "_splitter.pyx":466 + * + * + * cdef inline DTYPE_t median3(DTYPE_t* Xf, SIZE_t n) nogil: # <<<<<<<<<<<<<< + * # Median of three pivot selection, after Bentley and McIlroy (1993). + * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. + */ + +static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_median3(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) { + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_a; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_b; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_c; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_r; + int __pyx_t_1; + + /* "_splitter.pyx":469 + * # Median of three pivot selection, after Bentley and McIlroy (1993). + * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. + * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] # <<<<<<<<<<<<<< + * if a < b: + * if b < c: + */ + __pyx_v_a = (__pyx_v_Xf[0]); + __pyx_v_b = (__pyx_v_Xf[(__pyx_v_n / 2)]); + __pyx_v_c = (__pyx_v_Xf[(__pyx_v_n - 1)]); + + /* "_splitter.pyx":470 + * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. + * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] + * if a < b: # <<<<<<<<<<<<<< + * if b < c: + * return b + */ + __pyx_t_1 = ((__pyx_v_a < __pyx_v_b) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":471 + * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] + * if a < b: + * if b < c: # <<<<<<<<<<<<<< + * return b + * elif a < c: + */ + __pyx_t_1 = ((__pyx_v_b < __pyx_v_c) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":472 + * if a < b: + * if b < c: + * return b # <<<<<<<<<<<<<< + * elif a < c: + * return c + */ + __pyx_r = __pyx_v_b; + goto __pyx_L0; + + /* "_splitter.pyx":471 + * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] + * if a < b: + * if b < c: # <<<<<<<<<<<<<< + * return b + * elif a < c: + */ + } + + /* "_splitter.pyx":473 + * if b < c: + * return b + * elif a < c: # <<<<<<<<<<<<<< + * return c + * else: + */ + __pyx_t_1 = ((__pyx_v_a < __pyx_v_c) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":474 + * return b + * elif a < c: + * return c # <<<<<<<<<<<<<< + * else: + * return a + */ + __pyx_r = __pyx_v_c; + goto __pyx_L0; + + /* "_splitter.pyx":473 + * if b < c: + * return b + * elif a < c: # <<<<<<<<<<<<<< + * return c + * else: + */ + } + + /* "_splitter.pyx":476 + * return c + * else: + * return a # <<<<<<<<<<<<<< + * elif b < c: + * if a < c: + */ + /*else*/ { + __pyx_r = __pyx_v_a; + goto __pyx_L0; + } + + /* "_splitter.pyx":470 + * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. + * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] + * if a < b: # <<<<<<<<<<<<<< + * if b < c: + * return b + */ + } + + /* "_splitter.pyx":477 + * else: + * return a + * elif b < c: # <<<<<<<<<<<<<< + * if a < c: + * return a + */ + __pyx_t_1 = ((__pyx_v_b < __pyx_v_c) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":478 + * return a + * elif b < c: + * if a < c: # <<<<<<<<<<<<<< + * return a + * else: + */ + __pyx_t_1 = ((__pyx_v_a < __pyx_v_c) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":479 + * elif b < c: + * if a < c: + * return a # <<<<<<<<<<<<<< + * else: + * return c + */ + __pyx_r = __pyx_v_a; + goto __pyx_L0; + + /* "_splitter.pyx":478 + * return a + * elif b < c: + * if a < c: # <<<<<<<<<<<<<< + * return a + * else: + */ + } + + /* "_splitter.pyx":481 + * return a + * else: + * return c # <<<<<<<<<<<<<< + * else: + * return b + */ + /*else*/ { + __pyx_r = __pyx_v_c; + goto __pyx_L0; + } + + /* "_splitter.pyx":477 + * else: + * return a + * elif b < c: # <<<<<<<<<<<<<< + * if a < c: + * return a + */ + } + + /* "_splitter.pyx":483 + * return c + * else: + * return b # <<<<<<<<<<<<<< + * + * + */ + /*else*/ { + __pyx_r = __pyx_v_b; + goto __pyx_L0; + } + + /* "_splitter.pyx":466 + * + * + * cdef inline DTYPE_t median3(DTYPE_t* Xf, SIZE_t n) nogil: # <<<<<<<<<<<<<< + * # Median of three pivot selection, after Bentley and McIlroy (1993). + * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "_splitter.pyx":488 + * # Introsort with median of 3 pivot selection and 3-way partition function + * # (robust to repeated elements, e.g. lots of zero features). + * cdef void introsort(DTYPE_t* Xf, SIZE_t *samples, # <<<<<<<<<<<<<< + * SIZE_t n, int maxd) nogil: + * cdef DTYPE_t pivot + */ + +static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n, int __pyx_v_maxd) { + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_pivot; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_l; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_r; + int __pyx_t_1; + + /* "_splitter.pyx":493 + * cdef SIZE_t i, l, r + * + * while n > 1: # <<<<<<<<<<<<<< + * if maxd <= 0: # max depth limit exceeded ("gone quadratic") + * heapsort(Xf, samples, n) + */ + while (1) { + __pyx_t_1 = ((__pyx_v_n > 1) != 0); + if (!__pyx_t_1) break; + + /* "_splitter.pyx":494 + * + * while n > 1: + * if maxd <= 0: # max depth limit exceeded ("gone quadratic") # <<<<<<<<<<<<<< + * heapsort(Xf, samples, n) + * return + */ + __pyx_t_1 = ((__pyx_v_maxd <= 0) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":495 + * while n > 1: + * if maxd <= 0: # max depth limit exceeded ("gone quadratic") + * heapsort(Xf, samples, n) # <<<<<<<<<<<<<< + * return + * maxd -= 1 + */ + __pyx_f_9_splitter_heapsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n); + + /* "_splitter.pyx":496 + * if maxd <= 0: # max depth limit exceeded ("gone quadratic") + * heapsort(Xf, samples, n) + * return # <<<<<<<<<<<<<< + * maxd -= 1 + * + */ + goto __pyx_L0; + + /* "_splitter.pyx":494 + * + * while n > 1: + * if maxd <= 0: # max depth limit exceeded ("gone quadratic") # <<<<<<<<<<<<<< + * heapsort(Xf, samples, n) + * return + */ + } + + /* "_splitter.pyx":497 + * heapsort(Xf, samples, n) + * return + * maxd -= 1 # <<<<<<<<<<<<<< + * + * pivot = median3(Xf, n) + */ + __pyx_v_maxd = (__pyx_v_maxd - 1); + + /* "_splitter.pyx":499 + * maxd -= 1 + * + * pivot = median3(Xf, n) # <<<<<<<<<<<<<< + * + * # Three-way partition. + */ + __pyx_v_pivot = __pyx_f_9_splitter_median3(__pyx_v_Xf, __pyx_v_n); + + /* "_splitter.pyx":502 + * + * # Three-way partition. + * i = l = 0 # <<<<<<<<<<<<<< + * r = n + * while i < r: + */ + __pyx_v_i = 0; + __pyx_v_l = 0; + + /* "_splitter.pyx":503 + * # Three-way partition. + * i = l = 0 + * r = n # <<<<<<<<<<<<<< + * while i < r: + * if Xf[i] < pivot: + */ + __pyx_v_r = __pyx_v_n; + + /* "_splitter.pyx":504 + * i = l = 0 + * r = n + * while i < r: # <<<<<<<<<<<<<< + * if Xf[i] < pivot: + * swap(Xf, samples, i, l) + */ + while (1) { + __pyx_t_1 = ((__pyx_v_i < __pyx_v_r) != 0); + if (!__pyx_t_1) break; + + /* "_splitter.pyx":505 + * r = n + * while i < r: + * if Xf[i] < pivot: # <<<<<<<<<<<<<< + * swap(Xf, samples, i, l) + * i += 1 + */ + __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_i]) < __pyx_v_pivot) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":506 + * while i < r: + * if Xf[i] < pivot: + * swap(Xf, samples, i, l) # <<<<<<<<<<<<<< + * i += 1 + * l += 1 + */ + __pyx_f_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_l); + + /* "_splitter.pyx":507 + * if Xf[i] < pivot: + * swap(Xf, samples, i, l) + * i += 1 # <<<<<<<<<<<<<< + * l += 1 + * elif Xf[i] > pivot: + */ + __pyx_v_i = (__pyx_v_i + 1); + + /* "_splitter.pyx":508 + * swap(Xf, samples, i, l) + * i += 1 + * l += 1 # <<<<<<<<<<<<<< + * elif Xf[i] > pivot: + * r -= 1 + */ + __pyx_v_l = (__pyx_v_l + 1); + + /* "_splitter.pyx":505 + * r = n + * while i < r: + * if Xf[i] < pivot: # <<<<<<<<<<<<<< + * swap(Xf, samples, i, l) + * i += 1 + */ + goto __pyx_L8; + } + + /* "_splitter.pyx":509 + * i += 1 + * l += 1 + * elif Xf[i] > pivot: # <<<<<<<<<<<<<< + * r -= 1 + * swap(Xf, samples, i, r) + */ + __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_i]) > __pyx_v_pivot) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":510 + * l += 1 + * elif Xf[i] > pivot: + * r -= 1 # <<<<<<<<<<<<<< + * swap(Xf, samples, i, r) + * else: + */ + __pyx_v_r = (__pyx_v_r - 1); + + /* "_splitter.pyx":511 + * elif Xf[i] > pivot: + * r -= 1 + * swap(Xf, samples, i, r) # <<<<<<<<<<<<<< + * else: + * i += 1 + */ + __pyx_f_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_r); + + /* "_splitter.pyx":509 + * i += 1 + * l += 1 + * elif Xf[i] > pivot: # <<<<<<<<<<<<<< + * r -= 1 + * swap(Xf, samples, i, r) + */ + goto __pyx_L8; + } + + /* "_splitter.pyx":513 + * swap(Xf, samples, i, r) + * else: + * i += 1 # <<<<<<<<<<<<<< + * + * introsort(Xf, samples, l, maxd) + */ + /*else*/ { + __pyx_v_i = (__pyx_v_i + 1); + } + __pyx_L8:; + } + + /* "_splitter.pyx":515 + * i += 1 + * + * introsort(Xf, samples, l, maxd) # <<<<<<<<<<<<<< + * Xf += r + * samples += r + */ + __pyx_f_9_splitter_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_l, __pyx_v_maxd); + + /* "_splitter.pyx":516 + * + * introsort(Xf, samples, l, maxd) + * Xf += r # <<<<<<<<<<<<<< + * samples += r + * n -= r + */ + __pyx_v_Xf = (__pyx_v_Xf + __pyx_v_r); + + /* "_splitter.pyx":517 + * introsort(Xf, samples, l, maxd) + * Xf += r + * samples += r # <<<<<<<<<<<<<< + * n -= r + * + */ + __pyx_v_samples = (__pyx_v_samples + __pyx_v_r); + + /* "_splitter.pyx":518 + * Xf += r + * samples += r + * n -= r # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_n = (__pyx_v_n - __pyx_v_r); + } + + /* "_splitter.pyx":488 + * # Introsort with median of 3 pivot selection and 3-way partition function + * # (robust to repeated elements, e.g. lots of zero features). + * cdef void introsort(DTYPE_t* Xf, SIZE_t *samples, # <<<<<<<<<<<<<< + * SIZE_t n, int maxd) nogil: + * cdef DTYPE_t pivot + */ + + /* function exit code */ + __pyx_L0:; +} + +/* "_splitter.pyx":521 + * + * + * cdef inline void sift_down(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< + * SIZE_t start, SIZE_t end) nogil: + * # Restore heap order in Xf[start:end] by moving the max element to start. + */ + +static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end) { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_child; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_maxind; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_root; + int __pyx_t_1; + int __pyx_t_2; + + /* "_splitter.pyx":526 + * cdef SIZE_t child, maxind, root + * + * root = start # <<<<<<<<<<<<<< + * while True: + * child = root * 2 + 1 + */ + __pyx_v_root = __pyx_v_start; + + /* "_splitter.pyx":527 + * + * root = start + * while True: # <<<<<<<<<<<<<< + * child = root * 2 + 1 + * + */ + while (1) { + + /* "_splitter.pyx":528 + * root = start + * while True: + * child = root * 2 + 1 # <<<<<<<<<<<<<< + * + * # find max of root, left child, right child + */ + __pyx_v_child = ((__pyx_v_root * 2) + 1); + + /* "_splitter.pyx":531 + * + * # find max of root, left child, right child + * maxind = root # <<<<<<<<<<<<<< + * if child < end and Xf[maxind] < Xf[child]: + * maxind = child + */ + __pyx_v_maxind = __pyx_v_root; + + /* "_splitter.pyx":532 + * # find max of root, left child, right child + * maxind = root + * if child < end and Xf[maxind] < Xf[child]: # <<<<<<<<<<<<<< + * maxind = child + * if child + 1 < end and Xf[maxind] < Xf[child + 1]: + */ + __pyx_t_2 = ((__pyx_v_child < __pyx_v_end) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L6_bool_binop_done; + } + __pyx_t_2 = (((__pyx_v_Xf[__pyx_v_maxind]) < (__pyx_v_Xf[__pyx_v_child])) != 0); + __pyx_t_1 = __pyx_t_2; + __pyx_L6_bool_binop_done:; + if (__pyx_t_1) { + + /* "_splitter.pyx":533 + * maxind = root + * if child < end and Xf[maxind] < Xf[child]: + * maxind = child # <<<<<<<<<<<<<< + * if child + 1 < end and Xf[maxind] < Xf[child + 1]: + * maxind = child + 1 + */ + __pyx_v_maxind = __pyx_v_child; + + /* "_splitter.pyx":532 + * # find max of root, left child, right child + * maxind = root + * if child < end and Xf[maxind] < Xf[child]: # <<<<<<<<<<<<<< + * maxind = child + * if child + 1 < end and Xf[maxind] < Xf[child + 1]: + */ + } + + /* "_splitter.pyx":534 + * if child < end and Xf[maxind] < Xf[child]: + * maxind = child + * if child + 1 < end and Xf[maxind] < Xf[child + 1]: # <<<<<<<<<<<<<< + * maxind = child + 1 + * + */ + __pyx_t_2 = (((__pyx_v_child + 1) < __pyx_v_end) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L9_bool_binop_done; + } + __pyx_t_2 = (((__pyx_v_Xf[__pyx_v_maxind]) < (__pyx_v_Xf[(__pyx_v_child + 1)])) != 0); + __pyx_t_1 = __pyx_t_2; + __pyx_L9_bool_binop_done:; + if (__pyx_t_1) { + + /* "_splitter.pyx":535 + * maxind = child + * if child + 1 < end and Xf[maxind] < Xf[child + 1]: + * maxind = child + 1 # <<<<<<<<<<<<<< + * + * if maxind == root: + */ + __pyx_v_maxind = (__pyx_v_child + 1); + + /* "_splitter.pyx":534 + * if child < end and Xf[maxind] < Xf[child]: + * maxind = child + * if child + 1 < end and Xf[maxind] < Xf[child + 1]: # <<<<<<<<<<<<<< + * maxind = child + 1 + * + */ + } + + /* "_splitter.pyx":537 + * maxind = child + 1 + * + * if maxind == root: # <<<<<<<<<<<<<< + * break + * else: + */ + __pyx_t_1 = ((__pyx_v_maxind == __pyx_v_root) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":538 + * + * if maxind == root: + * break # <<<<<<<<<<<<<< + * else: + * swap(Xf, samples, root, maxind) + */ + goto __pyx_L4_break; + + /* "_splitter.pyx":537 + * maxind = child + 1 + * + * if maxind == root: # <<<<<<<<<<<<<< + * break + * else: + */ + } + + /* "_splitter.pyx":540 + * break + * else: + * swap(Xf, samples, root, maxind) # <<<<<<<<<<<<<< + * root = maxind + * + */ + /*else*/ { + __pyx_f_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_root, __pyx_v_maxind); + + /* "_splitter.pyx":541 + * else: + * swap(Xf, samples, root, maxind) + * root = maxind # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_root = __pyx_v_maxind; + } + } + __pyx_L4_break:; + + /* "_splitter.pyx":521 + * + * + * cdef inline void sift_down(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< + * SIZE_t start, SIZE_t end) nogil: + * # Restore heap order in Xf[start:end] by moving the max element to start. + */ + + /* function exit code */ +} + +/* "_splitter.pyx":544 + * + * + * cdef void heapsort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: # <<<<<<<<<<<<<< + * cdef SIZE_t start, end + * + */ + +static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end; + int __pyx_t_1; + + /* "_splitter.pyx":548 + * + * # heapify + * start = (n - 2) / 2 # <<<<<<<<<<<<<< + * end = n + * while True: + */ + __pyx_v_start = ((__pyx_v_n - 2) / 2); + + /* "_splitter.pyx":549 + * # heapify + * start = (n - 2) / 2 + * end = n # <<<<<<<<<<<<<< + * while True: + * sift_down(Xf, samples, start, end) + */ + __pyx_v_end = __pyx_v_n; + + /* "_splitter.pyx":550 + * start = (n - 2) / 2 + * end = n + * while True: # <<<<<<<<<<<<<< + * sift_down(Xf, samples, start, end) + * if start == 0: + */ + while (1) { + + /* "_splitter.pyx":551 + * end = n + * while True: + * sift_down(Xf, samples, start, end) # <<<<<<<<<<<<<< + * if start == 0: + * break + */ + __pyx_f_9_splitter_sift_down(__pyx_v_Xf, __pyx_v_samples, __pyx_v_start, __pyx_v_end); + + /* "_splitter.pyx":552 + * while True: + * sift_down(Xf, samples, start, end) + * if start == 0: # <<<<<<<<<<<<<< + * break + * start -= 1 + */ + __pyx_t_1 = ((__pyx_v_start == 0) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":553 + * sift_down(Xf, samples, start, end) + * if start == 0: + * break # <<<<<<<<<<<<<< + * start -= 1 + * + */ + goto __pyx_L4_break; + + /* "_splitter.pyx":552 + * while True: + * 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"_splitter.pyx":599 + * cdef double best_proxy_improvement = - INFINITY + * + * cdef SIZE_t f_i = n_features # <<<<<<<<<<<<<< + * cdef SIZE_t f_j + * cdef SIZE_t p + */ + __pyx_v_f_i = __pyx_v_n_features; + + /* "_splitter.pyx":605 + * cdef SIZE_t feature_stride + * # Number of features discovered to be constant during the split search + * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 + */ + __pyx_v_n_found_constants = 0; + + /* "_splitter.pyx":607 + * cdef SIZE_t n_found_constants = 0 + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< + * cdef SIZE_t n_known_constants = n_constant_features[0] + * # n_total_constants = n_known_constants + n_found_constants + */ + __pyx_v_n_drawn_constants = 0; + + /* "_splitter.pyx":608 + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 + * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< + * # n_total_constants = n_known_constants + n_found_constants + * cdef SIZE_t n_total_constants = n_known_constants + */ + __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); + + /* "_splitter.pyx":610 + * cdef SIZE_t n_known_constants = n_constant_features[0] + * # n_total_constants = n_known_constants + n_found_constants + * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< + * cdef SIZE_t n_visited_features = 0 + * cdef DTYPE_t min_feature_value + */ + __pyx_v_n_total_constants = __pyx_v_n_known_constants; + + /* "_splitter.pyx":611 + * # n_total_constants = n_known_constants + n_found_constants + * cdef SIZE_t n_total_constants = n_known_constants + * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< + * cdef DTYPE_t min_feature_value + * cdef DTYPE_t max_feature_value + */ + __pyx_v_n_visited_features = 0; + + /* "_splitter.pyx":616 + * cdef DTYPE_t current_feature_value + * + * _init_split(&best, end) # <<<<<<<<<<<<<< + * + * # Sample up to max_features without replacement using a + */ + __pyx_f_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); + + /* "_splitter.pyx":627 + * # newly discovered constant features to spare computation on descendant + * # nodes. + * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< + * # are constant + * (n_visited_features < max_features or + */ + while (1) { + __pyx_t_6 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0); + if (__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L5_bool_binop_done; + } + + /* "_splitter.pyx":629 + * while (f_i > n_total_constants and # Stop early if remaining features + * # are constant + * (n_visited_features < max_features or # <<<<<<<<<<<<<< + * # At least one drawn features must be non constant + * n_visited_features <= n_found_constants + n_drawn_constants)): + */ + __pyx_t_6 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0); + if (!__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L5_bool_binop_done; + } + + /* "_splitter.pyx":631 + * (n_visited_features < max_features or + * # At least one drawn features must be non constant + * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< + * n_visited_features += 1 + * + */ + __pyx_t_6 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0); + __pyx_t_5 = __pyx_t_6; + __pyx_L5_bool_binop_done:; + if (!__pyx_t_5) break; + + /* "_splitter.pyx":632 + * # At least one drawn features must be non constant + * n_visited_features <= n_found_constants + n_drawn_constants)): + * n_visited_features += 1 # <<<<<<<<<<<<<< + * + * # Loop invariant: elements of features in + */ + __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); + + /* "_splitter.pyx":646 + * + * # Draw a feature at random + * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< + * random_state) + * + */ + __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); + + /* "_splitter.pyx":649 + * random_state) + * + * if f_j < n_known_constants: # <<<<<<<<<<<<<< + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] + */ + __pyx_t_5 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":651 + * if f_j < n_known_constants: + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] # <<<<<<<<<<<<<< + * n_drawn_constants += 1 + * + */ + __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); + __pyx_t_7 = (__pyx_v_features[__pyx_v_n_drawn_constants]); + (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_2; + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; + + /* "_splitter.pyx":652 + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] + * n_drawn_constants += 1 # <<<<<<<<<<<<<< + * + * else: + */ + __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); + + /* "_splitter.pyx":649 + * random_state) + * + * if f_j < n_known_constants: # <<<<<<<<<<<<<< + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] + */ + goto __pyx_L8; + } + + /* "_splitter.pyx":656 + * else: + * # f_j in the interval [n_known_constants, f_i - n_found_constants[ + * f_j += n_found_constants # <<<<<<<<<<<<<< + * # f_j in the interval [n_total_constants, f_i[ + * + */ + /*else*/ { + __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); + + /* "_splitter.pyx":659 + * # f_j in the interval [n_total_constants, f_i[ + * + * current.feature = features[f_j] # <<<<<<<<<<<<<< + * + * # Find min, max + */ + __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); + + /* "_splitter.pyx":662 + * + * # Find min, max + * min_feature_value = self.X[samples[start], current.feature] # <<<<<<<<<<<<<< + * max_feature_value = min_feature_value + * Xf[start] = min_feature_value + */ + if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 662, __pyx_L1_error)} + __pyx_t_8 = (__pyx_v_samples[__pyx_v_start]); + __pyx_t_9 = __pyx_v_current.feature; + __pyx_v_min_feature_value = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))); + + /* "_splitter.pyx":663 + * # Find min, max + * min_feature_value = self.X[samples[start], current.feature] + * max_feature_value = min_feature_value # <<<<<<<<<<<<<< + * Xf[start] = min_feature_value + * + */ + __pyx_v_max_feature_value = __pyx_v_min_feature_value; + + /* "_splitter.pyx":664 + * min_feature_value = self.X[samples[start], current.feature] + * max_feature_value = min_feature_value + * Xf[start] = min_feature_value # <<<<<<<<<<<<<< + * + * for p in range(start + 1, end): + */ + (__pyx_v_Xf[__pyx_v_start]) = __pyx_v_min_feature_value; + + /* "_splitter.pyx":666 + * Xf[start] = min_feature_value + * + * for p in range(start + 1, end): # <<<<<<<<<<<<<< + * current_feature_value = self.X[samples[p], current.feature] + * Xf[p] = current_feature_value + */ + __pyx_t_7 = __pyx_v_end; + __pyx_t_2 = __pyx_t_7; + for (__pyx_t_10 = (__pyx_v_start + 1); __pyx_t_10 < __pyx_t_2; __pyx_t_10+=1) { + __pyx_v_p = __pyx_t_10; + + /* "_splitter.pyx":667 + * + * for p in range(start + 1, end): + * current_feature_value = self.X[samples[p], current.feature] # <<<<<<<<<<<<<< + * Xf[p] = current_feature_value + * + */ + if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 667, __pyx_L1_error)} + __pyx_t_9 = (__pyx_v_samples[__pyx_v_p]); + __pyx_t_8 = __pyx_v_current.feature; + __pyx_v_current_feature_value = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[1]) ))); + + /* "_splitter.pyx":668 + * for p in range(start + 1, end): + * current_feature_value = self.X[samples[p], current.feature] + * Xf[p] = current_feature_value # <<<<<<<<<<<<<< + * + * if current_feature_value < min_feature_value: + */ + (__pyx_v_Xf[__pyx_v_p]) = __pyx_v_current_feature_value; + + /* "_splitter.pyx":670 + * Xf[p] = current_feature_value + * + * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: + */ + __pyx_t_5 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":671 + * + * if current_feature_value < min_feature_value: + * min_feature_value = current_feature_value # <<<<<<<<<<<<<< + * elif current_feature_value > max_feature_value: + * max_feature_value = current_feature_value + */ + __pyx_v_min_feature_value = __pyx_v_current_feature_value; + + /* "_splitter.pyx":670 + * Xf[p] = current_feature_value + * + * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: + */ + goto __pyx_L11; + } + + /* "_splitter.pyx":672 + * if current_feature_value < min_feature_value: + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< + * max_feature_value = current_feature_value + * + */ + __pyx_t_5 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":673 + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: + * max_feature_value = current_feature_value # <<<<<<<<<<<<<< + * + * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: + */ + __pyx_v_max_feature_value = __pyx_v_current_feature_value; + + /* "_splitter.pyx":672 + * if current_feature_value < min_feature_value: + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< + * max_feature_value = current_feature_value + * + */ + } + __pyx_L11:; + } + + /* "_splitter.pyx":675 + * max_feature_value = current_feature_value + * + * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< + * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature + * + */ + __pyx_t_5 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":676 + * + * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: + * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature # <<<<<<<<<<<<<< + * + * n_found_constants += 1 + */ + __pyx_t_7 = (__pyx_v_features[__pyx_v_n_total_constants]); + __pyx_t_2 = __pyx_v_current.feature; + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; + (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2; + + /* "_splitter.pyx":678 + * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature + * + * n_found_constants += 1 # <<<<<<<<<<<<<< + * n_total_constants += 1 + * + */ + __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); + + /* "_splitter.pyx":679 + * + * n_found_constants += 1 + * n_total_constants += 1 # <<<<<<<<<<<<<< + * + * else: + */ + __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); + + /* "_splitter.pyx":675 + * max_feature_value = current_feature_value + * + * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< + * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature + * + */ + goto __pyx_L12; + } + + /* "_splitter.pyx":682 + * + * else: + * f_i -= 1 # <<<<<<<<<<<<<< + * features[f_i], features[f_j] = features[f_j], features[f_i] + * + */ + /*else*/ { + __pyx_v_f_i = (__pyx_v_f_i - 1); + + /* "_splitter.pyx":683 + * else: + * f_i -= 1 + * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< + * + * # Draw a random threshold + */ + __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); + __pyx_t_7 = (__pyx_v_features[__pyx_v_f_i]); + (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2; + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; + + /* "_splitter.pyx":686 + * + * # Draw a random threshold + * current.threshold = rand_uniform(min_feature_value, # <<<<<<<<<<<<<< + * max_feature_value, + * random_state) + */ + __pyx_v_current.threshold = __pyx_f_7sklearn_4tree_6_utils_rand_uniform(__pyx_v_min_feature_value, __pyx_v_max_feature_value, __pyx_v_random_state); + + /* "_splitter.pyx":690 + * random_state) + * + * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< + * current.threshold = min_feature_value + * + */ + __pyx_t_5 = ((__pyx_v_current.threshold == __pyx_v_max_feature_value) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":691 + * + * if current.threshold == max_feature_value: + * current.threshold = min_feature_value # <<<<<<<<<<<<<< + * + * # Partition + */ + __pyx_v_current.threshold = __pyx_v_min_feature_value; + + /* "_splitter.pyx":690 + * random_state) + * + * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< + * current.threshold = min_feature_value + * + */ + } + + /* "_splitter.pyx":694 + * + * # Partition + * p, partition_end = start, end # <<<<<<<<<<<<<< + * while p < partition_end: + * if Xf[p] <= current.threshold: + */ + __pyx_t_7 = __pyx_v_start; + __pyx_t_2 = __pyx_v_end; + __pyx_v_p = __pyx_t_7; + __pyx_v_partition_end = __pyx_t_2; + + /* "_splitter.pyx":695 + * # Partition + * p, partition_end = start, end + * while p < partition_end: # <<<<<<<<<<<<<< + * if Xf[p] <= current.threshold: + * p += 1 + */ + while (1) { + __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0); + if (!__pyx_t_5) break; + + /* "_splitter.pyx":696 + * p, partition_end = start, end + * while p < partition_end: + * if Xf[p] <= current.threshold: # <<<<<<<<<<<<<< + * p += 1 + * else: + */ + __pyx_t_5 = (((__pyx_v_Xf[__pyx_v_p]) <= __pyx_v_current.threshold) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":697 + * while p < partition_end: + * if Xf[p] <= current.threshold: + * p += 1 # <<<<<<<<<<<<<< + * else: + * partition_end -= 1 + */ + __pyx_v_p = (__pyx_v_p + 1); + + /* "_splitter.pyx":696 + * p, partition_end = start, end + * while p < partition_end: + * if Xf[p] <= current.threshold: # <<<<<<<<<<<<<< + * p += 1 + * else: + */ + goto __pyx_L16; + } + + /* "_splitter.pyx":699 + * p += 1 + * else: + * partition_end -= 1 # <<<<<<<<<<<<<< + * + * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] + */ + /*else*/ { + __pyx_v_partition_end = (__pyx_v_partition_end - 1); + + /* "_splitter.pyx":701 + * partition_end -= 1 + * + * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] # <<<<<<<<<<<<<< + * samples[p], samples[partition_end] = samples[partition_end], samples[p] + * + */ + __pyx_t_11 = (__pyx_v_Xf[__pyx_v_partition_end]); + __pyx_t_12 = (__pyx_v_Xf[__pyx_v_p]); + (__pyx_v_Xf[__pyx_v_p]) = __pyx_t_11; + (__pyx_v_Xf[__pyx_v_partition_end]) = __pyx_t_12; + + /* "_splitter.pyx":702 + * + * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] + * samples[p], samples[partition_end] = samples[partition_end], samples[p] # <<<<<<<<<<<<<< + * + * current.pos = partition_end + */ + __pyx_t_2 = (__pyx_v_samples[__pyx_v_partition_end]); + __pyx_t_7 = (__pyx_v_samples[__pyx_v_p]); + (__pyx_v_samples[__pyx_v_p]) = __pyx_t_2; + (__pyx_v_samples[__pyx_v_partition_end]) = __pyx_t_7; + } + __pyx_L16:; + } + + /* "_splitter.pyx":704 + * samples[p], samples[partition_end] = samples[partition_end], samples[p] + * + * current.pos = partition_end # <<<<<<<<<<<<<< + * + * # Reject if min_samples_leaf is not guaranteed + */ + __pyx_v_current.pos = __pyx_v_partition_end; + + /* "_splitter.pyx":707 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + __pyx_t_6 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0); + if (!__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L18_bool_binop_done; + } + + /* "_splitter.pyx":708 + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or + * ((end - current.pos) < min_samples_leaf)): # <<<<<<<<<<<<<< + * continue + * + */ + __pyx_t_6 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0); + __pyx_t_5 = __pyx_t_6; + __pyx_L18_bool_binop_done:; + + /* "_splitter.pyx":707 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + if (__pyx_t_5) { + + /* "_splitter.pyx":709 + * if (((current.pos - start) < min_samples_leaf) or + * ((end - current.pos) < min_samples_leaf)): + * continue # <<<<<<<<<<<<<< + * + * # Evaluate split + */ + goto __pyx_L3_continue; + + /* "_splitter.pyx":707 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + } + + /* "_splitter.pyx":712 + * + * # Evaluate split + * self.criterion.reset() # <<<<<<<<<<<<<< + * self.criterion.update(current.pos) + * + */ + __pyx_t_13 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 712, __pyx_L1_error) + + /* "_splitter.pyx":713 + * # Evaluate split + * self.criterion.reset() + * self.criterion.update(current.pos) # <<<<<<<<<<<<<< + * + * # Reject if min_weight_leaf is not satisfied + */ + __pyx_t_13 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 713, __pyx_L1_error) + + /* "_splitter.pyx":716 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + __pyx_t_6 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_left < __pyx_v_min_weight_leaf) != 0); + if (!__pyx_t_6) { + } else { + __pyx_t_5 = __pyx_t_6; + goto __pyx_L21_bool_binop_done; + } + + /* "_splitter.pyx":717 + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or + * (self.criterion.weighted_n_right < min_weight_leaf)): # <<<<<<<<<<<<<< + * continue + * + */ + __pyx_t_6 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_right < __pyx_v_min_weight_leaf) != 0); + __pyx_t_5 = __pyx_t_6; + __pyx_L21_bool_binop_done:; + + /* "_splitter.pyx":716 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + if (__pyx_t_5) { + + /* "_splitter.pyx":718 + * if ((self.criterion.weighted_n_left < min_weight_leaf) or + * (self.criterion.weighted_n_right < 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__pyx_v_partition_end = __pyx_t_2; + + /* "_splitter.pyx":731 + * p, partition_end = start, end + * + * while p < partition_end: # <<<<<<<<<<<<<< + * if self.X[samples[p], best.feature] <= best.threshold: + * p += 1 + */ + while (1) { + __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0); + if (!__pyx_t_5) break; + + /* "_splitter.pyx":732 + * + * while p < partition_end: + * if self.X[samples[p], best.feature] <= best.threshold: # <<<<<<<<<<<<<< + * p += 1 + * else: + */ + if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 732, __pyx_L1_error)} + __pyx_t_8 = (__pyx_v_samples[__pyx_v_p]); + __pyx_t_9 = __pyx_v_best.feature; + __pyx_t_5 = (((*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))) <= __pyx_v_best.threshold) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":733 + * while p < partition_end: + * if self.X[samples[p], best.feature] <= best.threshold: + * p += 1 # <<<<<<<<<<<<<< + * else: + * partition_end -= 1 + */ + __pyx_v_p = (__pyx_v_p + 1); + + /* "_splitter.pyx":732 + * + * while p < partition_end: + * if self.X[samples[p], best.feature] <= best.threshold: # <<<<<<<<<<<<<< + * p += 1 + * else: + */ + goto __pyx_L28; + } + + /* "_splitter.pyx":735 + * p += 1 + * else: + * partition_end -= 1 # <<<<<<<<<<<<<< + * + * samples[p], samples[partition_end] = samples[partition_end], samples[p] + */ + /*else*/ { + __pyx_v_partition_end = (__pyx_v_partition_end - 1); + + /* "_splitter.pyx":737 + * partition_end -= 1 + * + * samples[p], samples[partition_end] = samples[partition_end], samples[p] # <<<<<<<<<<<<<< + * + * self.criterion.reset() + */ + __pyx_t_2 = (__pyx_v_samples[__pyx_v_partition_end]); + __pyx_t_7 = (__pyx_v_samples[__pyx_v_p]); + (__pyx_v_samples[__pyx_v_p]) = __pyx_t_2; + 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__pyx_v_self->__pyx_base.feature_values; + __pyx_v_Xf = __pyx_t_1; + + /* "_splitter.pyx":842 + * + * cdef DTYPE_t* Xf = self.feature_values + * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< + * cdef SIZE_t* index_to_samples = self.index_to_samples + * + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.samples; + __pyx_v_samples = __pyx_t_2; + + /* "_splitter.pyx":843 + * cdef DTYPE_t* Xf = self.feature_values + * cdef SIZE_t* samples = self.samples + * cdef SIZE_t* index_to_samples = self.index_to_samples # <<<<<<<<<<<<<< + * + * if threshold < 0.: + */ + __pyx_t_2 = __pyx_v_self->index_to_samples; + __pyx_v_index_to_samples = __pyx_t_2; + + /* "_splitter.pyx":845 + * cdef SIZE_t* index_to_samples = self.index_to_samples + * + * if threshold < 0.: # <<<<<<<<<<<<<< + * p = self.start + * partition_end = end_negative + */ + __pyx_t_3 = ((__pyx_v_threshold < 0.) != 0); + if (__pyx_t_3) { + + /* "_splitter.pyx":846 + * + * if threshold < 0.: + * p = self.start # <<<<<<<<<<<<<< + * partition_end = end_negative + * elif threshold > 0.: + */ + __pyx_t_4 = __pyx_v_self->__pyx_base.start; + __pyx_v_p = __pyx_t_4; + + /* "_splitter.pyx":847 + * if threshold < 0.: + * p = self.start + * partition_end = end_negative # <<<<<<<<<<<<<< + * elif threshold > 0.: + * p = start_positive + */ + __pyx_v_partition_end = __pyx_v_end_negative; + + /* "_splitter.pyx":845 + * cdef SIZE_t* index_to_samples = self.index_to_samples + * + * if threshold < 0.: # <<<<<<<<<<<<<< + * p = self.start + * partition_end = end_negative + */ + goto __pyx_L3; + } + + /* "_splitter.pyx":848 + * p = self.start + * partition_end = end_negative + * elif threshold > 0.: # <<<<<<<<<<<<<< + * p = start_positive + * partition_end = self.end + */ + __pyx_t_3 = ((__pyx_v_threshold > 0.) != 0); + if (__pyx_t_3) { + + /* "_splitter.pyx":849 + * partition_end = end_negative + * elif threshold > 0.: + * p = start_positive # <<<<<<<<<<<<<< + * partition_end = self.end + * else: + */ + __pyx_v_p = __pyx_v_start_positive; + + /* "_splitter.pyx":850 + * elif threshold > 0.: + * p = start_positive + * partition_end = self.end # <<<<<<<<<<<<<< + * else: + * # Data are already split + */ + __pyx_t_4 = __pyx_v_self->__pyx_base.end; + __pyx_v_partition_end = __pyx_t_4; + + /* "_splitter.pyx":848 + * p = self.start + * partition_end = end_negative + * elif threshold > 0.: # <<<<<<<<<<<<<< + * p = start_positive + * partition_end = self.end + */ + goto __pyx_L3; + } + + /* "_splitter.pyx":853 + * else: + * # Data are already split + * return zero_pos # <<<<<<<<<<<<<< + * + * while p < partition_end: + */ + /*else*/ { + __pyx_r = __pyx_v_zero_pos; + goto __pyx_L0; + } + __pyx_L3:; + + /* "_splitter.pyx":855 + * return zero_pos + * + * while p < partition_end: # <<<<<<<<<<<<<< + * if Xf[p] <= threshold: + * p += 1 + */ + while (1) { + __pyx_t_3 = ((__pyx_v_p < __pyx_v_partition_end) != 0); + if (!__pyx_t_3) break; + + /* "_splitter.pyx":856 + * + * while p < partition_end: + * if Xf[p] <= threshold: # <<<<<<<<<<<<<< + * p += 1 + * + */ + __pyx_t_3 = (((__pyx_v_Xf[__pyx_v_p]) <= __pyx_v_threshold) != 0); + if (__pyx_t_3) { + + /* "_splitter.pyx":857 + * while p < partition_end: + * if Xf[p] <= threshold: + * p += 1 # <<<<<<<<<<<<<< + * + * else: + */ + __pyx_v_p = (__pyx_v_p + 1); + + /* "_splitter.pyx":856 + * + * while p < partition_end: + * if Xf[p] <= threshold: # <<<<<<<<<<<<<< + * p += 1 + * + */ + goto __pyx_L6; + } + + /* "_splitter.pyx":860 + * + * else: + * partition_end -= 1 # <<<<<<<<<<<<<< + * + * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] + */ + /*else*/ { + __pyx_v_partition_end = (__pyx_v_partition_end - 1); + + /* "_splitter.pyx":862 + * partition_end -= 1 + * + * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] # <<<<<<<<<<<<<< + * sparse_swap(index_to_samples, samples, p, partition_end) + * + */ + __pyx_t_5 = (__pyx_v_Xf[__pyx_v_partition_end]); + __pyx_t_6 = (__pyx_v_Xf[__pyx_v_p]); + (__pyx_v_Xf[__pyx_v_p]) = __pyx_t_5; + (__pyx_v_Xf[__pyx_v_partition_end]) = __pyx_t_6; + + /* "_splitter.pyx":863 + * + * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] + * sparse_swap(index_to_samples, samples, p, partition_end) # <<<<<<<<<<<<<< + * + * return partition_end + */ + __pyx_f_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_p, __pyx_v_partition_end); + } + __pyx_L6:; + } + + /* "_splitter.pyx":865 + * sparse_swap(index_to_samples, samples, p, partition_end) + * + * return partition_end # <<<<<<<<<<<<<< + * + * cdef inline void extract_nnz(self, SIZE_t feature, + */ + __pyx_r = __pyx_v_partition_end; + goto __pyx_L0; + + /* "_splitter.pyx":833 + * return 0 + * + * cdef inline SIZE_t _partition(self, double threshold, # <<<<<<<<<<<<<< + * SIZE_t end_negative, SIZE_t start_positive, + * SIZE_t zero_pos) nogil: + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "_splitter.pyx":867 + * return partition_end + * + * cdef inline void extract_nnz(self, SIZE_t 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(__pyx_v_self->X_indptr[__pyx_v_feature]); + + /* "_splitter.pyx":900 + * """ + * cdef SIZE_t indptr_start = self.X_indptr[feature], + * cdef SIZE_t indptr_end = self.X_indptr[feature + 1] # <<<<<<<<<<<<<< + * cdef SIZE_t n_indices = (indptr_end - indptr_start) + * cdef SIZE_t n_samples = self.end - self.start + */ + __pyx_v_indptr_end = (__pyx_v_self->X_indptr[(__pyx_v_feature + 1)]); + + /* "_splitter.pyx":901 + * cdef SIZE_t indptr_start = self.X_indptr[feature], + * cdef SIZE_t indptr_end = self.X_indptr[feature + 1] + * cdef SIZE_t n_indices = (indptr_end - indptr_start) # <<<<<<<<<<<<<< + * cdef SIZE_t n_samples = self.end - self.start + * + */ + __pyx_v_n_indices = ((__pyx_t_7sklearn_4tree_5_tree_SIZE_t)(__pyx_v_indptr_end - __pyx_v_indptr_start)); + + /* "_splitter.pyx":902 + * cdef SIZE_t indptr_end = self.X_indptr[feature + 1] + * cdef SIZE_t n_indices = (indptr_end - indptr_start) + * cdef SIZE_t n_samples = self.end - self.start # <<<<<<<<<<<<<< + * + * # Use binary search 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compare_SIZE_t(const void* a, const void* b) nogil: # <<<<<<<<<<<<<< + * """Comparison function for sort.""" + * return ((a)[0] - (b)[0]) + */ + +static int __pyx_f_9_splitter_compare_SIZE_t(void const *__pyx_v_a, void const *__pyx_v_b) { + int __pyx_r; + + /* "_splitter.pyx":932 + * cdef int compare_SIZE_t(const void* a, const void* b) nogil: + * """Comparison function for sort.""" + * return ((a)[0] - (b)[0]) # <<<<<<<<<<<<<< + * + * + */ + __pyx_r = ((int)((((__pyx_t_7sklearn_4tree_5_tree_SIZE_t *)__pyx_v_a)[0]) - (((__pyx_t_7sklearn_4tree_5_tree_SIZE_t *)__pyx_v_b)[0]))); + goto __pyx_L0; + + /* "_splitter.pyx":930 + * + * + * cdef int compare_SIZE_t(const void* a, const void* b) nogil: # <<<<<<<<<<<<<< + * """Comparison function for sort.""" + * return ((a)[0] - (b)[0]) + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "_splitter.pyx":935 + * + * + * cdef inline void binary_search(INT32_t* sorted_array, # <<<<<<<<<<<<<< + * INT32_t start, INT32_t end, + * SIZE_t value, SIZE_t* index, + */ + +static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_sorted_array, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_value, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index, __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_new_start) { + __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_pivot; + int __pyx_t_1; + + /* "_splitter.pyx":944 + * """ + * cdef INT32_t pivot + * index[0] = -1 # <<<<<<<<<<<<<< + * while start < end: + * pivot = start + (end - start) / 2 + */ + (__pyx_v_index[0]) = -1; + + /* "_splitter.pyx":945 + * cdef INT32_t pivot + * index[0] = -1 + * while start < end: # <<<<<<<<<<<<<< + * pivot = start + (end - start) / 2 + * + */ + while (1) { + __pyx_t_1 = ((__pyx_v_start < __pyx_v_end) != 0); + if (!__pyx_t_1) break; + + /* "_splitter.pyx":946 + * index[0] = -1 + * while start < end: + * pivot = start + (end - start) / 2 # <<<<<<<<<<<<<< + * + * if sorted_array[pivot] == value: + */ + __pyx_v_pivot = (__pyx_v_start + ((__pyx_v_end - __pyx_v_start) / 2)); + + /* "_splitter.pyx":948 + * pivot = start + (end - start) / 2 + * + * if sorted_array[pivot] == value: # <<<<<<<<<<<<<< + * index[0] = pivot + * start = pivot + 1 + */ + __pyx_t_1 = (((__pyx_v_sorted_array[__pyx_v_pivot]) == __pyx_v_value) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":949 + * + * if sorted_array[pivot] == value: + * index[0] = pivot # <<<<<<<<<<<<<< + * start = pivot + 1 + * break + */ + (__pyx_v_index[0]) = __pyx_v_pivot; + + /* "_splitter.pyx":950 + * if sorted_array[pivot] == value: + * index[0] = pivot + * start = pivot + 1 # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_start = (__pyx_v_pivot + 1); + + /* "_splitter.pyx":951 + * index[0] = pivot + * start = pivot + 1 + * break # <<<<<<<<<<<<<< + * + * if sorted_array[pivot] < value: + */ + goto __pyx_L4_break; + + /* "_splitter.pyx":948 + * pivot = start + (end - start) / 2 + * + * if sorted_array[pivot] == value: # <<<<<<<<<<<<<< + * index[0] = pivot + * start = pivot + 1 + */ + } + + /* "_splitter.pyx":953 + * break + * + * if sorted_array[pivot] < value: # <<<<<<<<<<<<<< + * start = pivot + 1 + * else: + */ + __pyx_t_1 = (((__pyx_v_sorted_array[__pyx_v_pivot]) < __pyx_v_value) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":954 + * + * if sorted_array[pivot] < value: + * start = pivot + 1 # <<<<<<<<<<<<<< + * else: + * end = pivot + */ + __pyx_v_start = (__pyx_v_pivot + 1); + + /* "_splitter.pyx":953 + * break + * + * if sorted_array[pivot] < value: # <<<<<<<<<<<<<< + * start = pivot + 1 + * else: + */ + goto __pyx_L6; + } + + /* "_splitter.pyx":956 + * start = pivot + 1 + * else: + * end = pivot # <<<<<<<<<<<<<< + * new_start[0] = start + * + */ + /*else*/ { + __pyx_v_end = __pyx_v_pivot; + } + __pyx_L6:; + } + __pyx_L4_break:; + + /* "_splitter.pyx":957 + * else: + * end = pivot + * new_start[0] = start # <<<<<<<<<<<<<< + * + * + */ + (__pyx_v_new_start[0]) = __pyx_v_start; + + /* "_splitter.pyx":935 + * + * + * cdef inline void binary_search(INT32_t* sorted_array, # <<<<<<<<<<<<<< + * INT32_t start, INT32_t end, + * SIZE_t value, SIZE_t* index, + */ + + /* function exit code */ +} + +/* "_splitter.pyx":960 + * + * + * cdef inline void extract_nnz_index_to_samples(INT32_t* X_indices, # <<<<<<<<<<<<<< + * DTYPE_t* X_data, + * INT32_t indptr_start, + */ + +static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indices, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X_data, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_start, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive) { + __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_k; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_index; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative_; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive_; + __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_t_1; + __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_t_2; + __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_t_3; + int __pyx_t_4; + int __pyx_t_5; + + /* "_splitter.pyx":977 + * cdef INT32_t k + * cdef SIZE_t index + * cdef SIZE_t end_negative_ = start # <<<<<<<<<<<<<< + * cdef SIZE_t start_positive_ = end + * + */ + __pyx_v_end_negative_ = __pyx_v_start; + + /* "_splitter.pyx":978 + * cdef SIZE_t index + * cdef SIZE_t end_negative_ = start + * cdef SIZE_t start_positive_ = end # <<<<<<<<<<<<<< + * + * for k in range(indptr_start, indptr_end): + */ + __pyx_v_start_positive_ = __pyx_v_end; + + /* "_splitter.pyx":980 + * cdef SIZE_t start_positive_ = end + * + * for k in range(indptr_start, indptr_end): # <<<<<<<<<<<<<< + * if start <= index_to_samples[X_indices[k]] < end: + * if X_data[k] > 0: + */ + __pyx_t_1 = __pyx_v_indptr_end; + __pyx_t_2 = __pyx_t_1; + for (__pyx_t_3 = __pyx_v_indptr_start; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_k = __pyx_t_3; + + /* "_splitter.pyx":981 + * + * for k in range(indptr_start, indptr_end): + * if start <= index_to_samples[X_indices[k]] < end: # <<<<<<<<<<<<<< + * if X_data[k] > 0: + * start_positive_ -= 1 + */ + __pyx_t_4 = (__pyx_v_start <= (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])])); + if (__pyx_t_4) { + __pyx_t_4 = ((__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]) < __pyx_v_end); + } + __pyx_t_5 = (__pyx_t_4 != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":982 + * for k in range(indptr_start, indptr_end): + * if start <= index_to_samples[X_indices[k]] < end: + * if X_data[k] > 0: # <<<<<<<<<<<<<< + * start_positive_ -= 1 + * Xf[start_positive_] = X_data[k] + */ + __pyx_t_5 = (((__pyx_v_X_data[__pyx_v_k]) > 0.0) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":983 + * if start <= index_to_samples[X_indices[k]] < end: + * if X_data[k] > 0: + * start_positive_ -= 1 # <<<<<<<<<<<<<< + * Xf[start_positive_] = X_data[k] + * index = index_to_samples[X_indices[k]] + */ + __pyx_v_start_positive_ = (__pyx_v_start_positive_ - 1); + + /* "_splitter.pyx":984 + * if X_data[k] > 0: + * start_positive_ -= 1 + * Xf[start_positive_] = X_data[k] # <<<<<<<<<<<<<< + * index = index_to_samples[X_indices[k]] + * sparse_swap(index_to_samples, samples, index, start_positive_) + */ + (__pyx_v_Xf[__pyx_v_start_positive_]) = (__pyx_v_X_data[__pyx_v_k]); + + /* "_splitter.pyx":985 + * start_positive_ -= 1 + * Xf[start_positive_] = X_data[k] + * index = index_to_samples[X_indices[k]] # <<<<<<<<<<<<<< + * sparse_swap(index_to_samples, samples, index, start_positive_) + * + */ + __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]); + + /* "_splitter.pyx":986 + * Xf[start_positive_] = X_data[k] + * index = index_to_samples[X_indices[k]] + * sparse_swap(index_to_samples, samples, index, start_positive_) # <<<<<<<<<<<<<< + * + * + */ + __pyx_f_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_start_positive_); + + /* "_splitter.pyx":982 + * for k in range(indptr_start, indptr_end): + * if start <= index_to_samples[X_indices[k]] < end: + * if X_data[k] > 0: # <<<<<<<<<<<<<< + * start_positive_ -= 1 + * Xf[start_positive_] = X_data[k] + */ + goto __pyx_L6; + } + + /* "_splitter.pyx":989 + * + * + * elif X_data[k] < 0: # <<<<<<<<<<<<<< + * Xf[end_negative_] = X_data[k] + * index = index_to_samples[X_indices[k]] + */ + __pyx_t_5 = (((__pyx_v_X_data[__pyx_v_k]) < 0.0) != 0); + if (__pyx_t_5) { + + /* "_splitter.pyx":990 + * + * elif X_data[k] < 0: + * Xf[end_negative_] = X_data[k] # <<<<<<<<<<<<<< + * index = index_to_samples[X_indices[k]] + * sparse_swap(index_to_samples, samples, index, end_negative_) + */ + (__pyx_v_Xf[__pyx_v_end_negative_]) = (__pyx_v_X_data[__pyx_v_k]); + + /* "_splitter.pyx":991 + * elif X_data[k] < 0: + * Xf[end_negative_] = X_data[k] + * index = index_to_samples[X_indices[k]] # <<<<<<<<<<<<<< + * sparse_swap(index_to_samples, samples, index, end_negative_) + * end_negative_ += 1 + */ + __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]); + + /* "_splitter.pyx":992 + * Xf[end_negative_] = X_data[k] + * index = index_to_samples[X_indices[k]] + * sparse_swap(index_to_samples, samples, index, end_negative_) # <<<<<<<<<<<<<< + * end_negative_ += 1 + * + */ + __pyx_f_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_end_negative_); + + /* "_splitter.pyx":993 + * index = index_to_samples[X_indices[k]] + * sparse_swap(index_to_samples, samples, index, end_negative_) + * end_negative_ += 1 # <<<<<<<<<<<<<< + * + * # Returned values + */ + __pyx_v_end_negative_ = (__pyx_v_end_negative_ + 1); + + /* "_splitter.pyx":989 + * + * + * elif X_data[k] < 0: # <<<<<<<<<<<<<< + * Xf[end_negative_] = X_data[k] + * index = index_to_samples[X_indices[k]] + */ + } + __pyx_L6:; + + /* "_splitter.pyx":981 + * + * for k in range(indptr_start, indptr_end): + * if start <= index_to_samples[X_indices[k]] < end: # <<<<<<<<<<<<<< + * if X_data[k] > 0: + * start_positive_ -= 1 + */ + } + } + + /* "_splitter.pyx":996 + * + * # Returned values + * end_negative[0] = end_negative_ # <<<<<<<<<<<<<< + * start_positive[0] = start_positive_ + * + */ + (__pyx_v_end_negative[0]) = __pyx_v_end_negative_; + + /* "_splitter.pyx":997 + * # Returned values + * end_negative[0] = end_negative_ + * start_positive[0] = start_positive_ # <<<<<<<<<<<<<< + * + * + */ + (__pyx_v_start_positive[0]) = __pyx_v_start_positive_; + + /* "_splitter.pyx":960 + * + * + * cdef inline void extract_nnz_index_to_samples(INT32_t* X_indices, # <<<<<<<<<<<<<< + * DTYPE_t* X_data, + * INT32_t indptr_start, + */ + + /* function exit code */ +} + +/* "_splitter.pyx":1000 + * + * + * cdef inline void extract_nnz_binary_search(INT32_t* X_indices, # <<<<<<<<<<<<<< + * DTYPE_t* X_data, + * INT32_t indptr_start, + */ + +static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indices, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X_data, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_start, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_sorted_samples, int *__pyx_v_is_samples_sorted) { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_index; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative_; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive_; + int __pyx_t_1; + int __pyx_t_2; + + /* "_splitter.pyx":1023 + * cdef SIZE_t n_samples + * + * if not is_samples_sorted[0]: # <<<<<<<<<<<<<< + * n_samples = end - start + * memcpy(sorted_samples + start, samples + start, + */ + __pyx_t_1 = ((!((__pyx_v_is_samples_sorted[0]) != 0)) != 0); + if (__pyx_t_1) { + + /* "_splitter.pyx":1024 + * + * if not is_samples_sorted[0]: + * n_samples = end - start # <<<<<<<<<<<<<< + * memcpy(sorted_samples + start, samples + start, + * n_samples * sizeof(SIZE_t)) + */ + __pyx_v_n_samples = (__pyx_v_end - __pyx_v_start); + + /* "_splitter.pyx":1025 + * if not is_samples_sorted[0]: + * n_samples = end - start + * memcpy(sorted_samples + start, samples + start, # <<<<<<<<<<<<<< + * n_samples * sizeof(SIZE_t)) + * qsort(sorted_samples + start, n_samples, sizeof(SIZE_t), + */ + (void)(memcpy((__pyx_v_sorted_samples + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_n_samples * (sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t))))); + + /* "_splitter.pyx":1027 + * memcpy(sorted_samples + start, samples + start, + * n_samples * sizeof(SIZE_t)) + * qsort(sorted_samples + start, n_samples, sizeof(SIZE_t), # <<<<<<<<<<<<<< + * compare_SIZE_t) + * is_samples_sorted[0] = 1 + */ + qsort((__pyx_v_sorted_samples + __pyx_v_start), __pyx_v_n_samples, (sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)), __pyx_f_9_splitter_compare_SIZE_t); + + /* "_splitter.pyx":1029 + * qsort(sorted_samples + start, n_samples, sizeof(SIZE_t), + * compare_SIZE_t) + * is_samples_sorted[0] = 1 # <<<<<<<<<<<<<< + * + * while (indptr_start < indptr_end and + */ + (__pyx_v_is_samples_sorted[0]) = 1; + + /* "_splitter.pyx":1023 + * cdef SIZE_t n_samples + * + * if not is_samples_sorted[0]: # <<<<<<<<<<<<<< + * n_samples = end - start + * memcpy(sorted_samples + start, samples + start, + */ + } + + /* "_splitter.pyx":1031 + * is_samples_sorted[0] = 1 + * + * while (indptr_start < indptr_end and # <<<<<<<<<<<<<< + * sorted_samples[start] > X_indices[indptr_start]): + * indptr_start += 1 + */ + while (1) { + __pyx_t_2 = ((__pyx_v_indptr_start < __pyx_v_indptr_end) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L6_bool_binop_done; + } + + /* "_splitter.pyx":1032 + * + * while (indptr_start < indptr_end and + * sorted_samples[start] > X_indices[indptr_start]): # <<<<<<<<<<<<<< + * indptr_start += 1 + * + */ + __pyx_t_2 = (((__pyx_v_sorted_samples[__pyx_v_start]) > (__pyx_v_X_indices[__pyx_v_indptr_start])) != 0); + __pyx_t_1 = __pyx_t_2; + __pyx_L6_bool_binop_done:; + if (!__pyx_t_1) break; + + /* "_splitter.pyx":1033 + * while (indptr_start < indptr_end and + * sorted_samples[start] > X_indices[indptr_start]): + * indptr_start += 1 # <<<<<<<<<<<<<< + * + * while (indptr_start < indptr_end and + */ + __pyx_v_indptr_start = (__pyx_v_indptr_start + 1); + } + + /* "_splitter.pyx":1035 + * indptr_start += 1 + * + * while (indptr_start < indptr_end and # <<<<<<<<<<<<<< + * sorted_samples[end - 1] < X_indices[indptr_end - 1]): + * indptr_end -= 1 + */ + while (1) { + __pyx_t_2 = ((__pyx_v_indptr_start < __pyx_v_indptr_end) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L10_bool_binop_done; + } + + /* "_splitter.pyx":1036 + * + * while (indptr_start < indptr_end and + * sorted_samples[end - 1] < X_indices[indptr_end - 1]): # <<<<<<<<<<<<<< + * indptr_end -= 1 + * + */ + __pyx_t_2 = (((__pyx_v_sorted_samples[(__pyx_v_end - 1)]) < (__pyx_v_X_indices[(__pyx_v_indptr_end - 1)])) != 0); + __pyx_t_1 = __pyx_t_2; + __pyx_L10_bool_binop_done:; + if (!__pyx_t_1) break; + + /* "_splitter.pyx":1037 + * while (indptr_start < indptr_end and + * sorted_samples[end - 1] < X_indices[indptr_end - 1]): + * indptr_end -= 1 # <<<<<<<<<<<<<< + * + * cdef SIZE_t p = start + */ + __pyx_v_indptr_end = (__pyx_v_indptr_end - 1); + } + + /* "_splitter.pyx":1039 + * indptr_end -= 1 + * + * cdef SIZE_t p = start # <<<<<<<<<<<<<< + * cdef SIZE_t index + * cdef SIZE_t k + */ + __pyx_v_p = __pyx_v_start; + + /* "_splitter.pyx":1042 + * cdef SIZE_t index + * cdef SIZE_t k + * cdef SIZE_t end_negative_ = start # <<<<<<<<<<<<<< + * cdef SIZE_t start_positive_ = end + * + */ + __pyx_v_end_negative_ = __pyx_v_start; + + /* "_splitter.pyx":1043 + * cdef SIZE_t k + * cdef SIZE_t end_negative_ = start + * cdef SIZE_t start_positive_ = end # <<<<<<<<<<<<<< + * + * while (p < end and indptr_start < indptr_end): + */ + __pyx_v_start_positive_ = __pyx_v_end; + + /* "_splitter.pyx":1045 + * cdef SIZE_t start_positive_ = end + * + * while (p < end and indptr_start < indptr_end): # <<<<<<<<<<<<<< + * # Find index of sorted_samples[p] in X_indices + * binary_search(X_indices, indptr_start, indptr_end, + */ + while (1) { + __pyx_t_2 = ((__pyx_v_p < __pyx_v_end) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L14_bool_binop_done; + } + __pyx_t_2 = ((__pyx_v_indptr_start < __pyx_v_indptr_end) != 0); + __pyx_t_1 = __pyx_t_2; + __pyx_L14_bool_binop_done:; + if (!__pyx_t_1) break; + + /* "_splitter.pyx":1047 + * while (p < end and indptr_start < indptr_end): + * # Find index of sorted_samples[p] in X_indices + * binary_search(X_indices, indptr_start, indptr_end, # <<<<<<<<<<<<<< + * sorted_samples[p], &k, &indptr_start) + * + */ + __pyx_f_9_splitter_binary_search(__pyx_v_X_indices, __pyx_v_indptr_start, __pyx_v_indptr_end, (__pyx_v_sorted_samples[__pyx_v_p]), (&__pyx_v_k), (&__pyx_v_indptr_start)); + + /* "_splitter.pyx":1050 + * sorted_samples[p], &k, &indptr_start) + * + * if k != 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__pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf; + double __pyx_v_min_weight_leaf; + __pyx_t_7sklearn_4tree_5_tree_UINT32_t *__pyx_v_random_state; + struct __pyx_t_9_splitter_SplitRecord __pyx_v_best; + struct __pyx_t_9_splitter_SplitRecord __pyx_v_current; + double __pyx_v_current_proxy_improvement; + double __pyx_v_best_proxy_improvement; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_i; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_j; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_visited_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_found_constants; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_drawn_constants; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_known_constants; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_total_constants; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p_next; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p_prev; + int __pyx_v_is_samples_sorted; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative; + int __pyx_r; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_1; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; + __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_t_3; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_t_4; + double __pyx_t_5; + int __pyx_t_6; + int __pyx_t_7; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_8; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_9; + int __pyx_t_10; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "_splitter.pyx":1098 + * """ + * # Find the best split + * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< + * cdef SIZE_t start = self.start + * cdef SIZE_t end = self.end + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.samples; + __pyx_v_samples = __pyx_t_1; + + /* "_splitter.pyx":1099 + * # Find the best split + * cdef SIZE_t* samples = self.samples + * cdef SIZE_t start = self.start # <<<<<<<<<<<<<< + * cdef SIZE_t end = self.end + * + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.start; + __pyx_v_start = __pyx_t_2; + + /* "_splitter.pyx":1100 + * cdef SIZE_t* samples = self.samples + * cdef SIZE_t start = self.start + * cdef SIZE_t end = self.end # <<<<<<<<<<<<<< + * + * cdef INT32_t* X_indices = self.X_indices + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end; + __pyx_v_end = __pyx_t_2; + + /* "_splitter.pyx":1102 + * cdef SIZE_t end = self.end + * + * cdef INT32_t* X_indices = self.X_indices # <<<<<<<<<<<<<< + * cdef INT32_t* X_indptr = self.X_indptr + * cdef DTYPE_t* X_data = self.X_data + */ + __pyx_t_3 = __pyx_v_self->__pyx_base.X_indices; + __pyx_v_X_indices = __pyx_t_3; + + /* "_splitter.pyx":1103 + * + * cdef INT32_t* X_indices = self.X_indices + * cdef INT32_t* X_indptr = self.X_indptr # <<<<<<<<<<<<<< + * cdef DTYPE_t* X_data = self.X_data + * + */ + __pyx_t_3 = __pyx_v_self->__pyx_base.X_indptr; + __pyx_v_X_indptr = __pyx_t_3; + + /* "_splitter.pyx":1104 + * cdef INT32_t* X_indices = self.X_indices + * cdef INT32_t* X_indptr = self.X_indptr + * cdef DTYPE_t* X_data = self.X_data # <<<<<<<<<<<<<< + * + * cdef SIZE_t* features = self.features + */ + __pyx_t_4 = __pyx_v_self->__pyx_base.X_data; + __pyx_v_X_data = __pyx_t_4; + + /* "_splitter.pyx":1106 + * cdef DTYPE_t* X_data = self.X_data + * + * cdef SIZE_t* features = self.features # <<<<<<<<<<<<<< + * cdef SIZE_t* constant_features = self.constant_features + * cdef SIZE_t n_features = self.n_features + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.features; + __pyx_v_features = __pyx_t_1; + + /* "_splitter.pyx":1107 + * + * cdef SIZE_t* features = self.features + * cdef SIZE_t* constant_features = self.constant_features # <<<<<<<<<<<<<< + * cdef SIZE_t n_features = self.n_features + * + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.constant_features; + __pyx_v_constant_features = __pyx_t_1; + + /* "_splitter.pyx":1108 + * cdef SIZE_t* features = self.features + * cdef SIZE_t* constant_features = self.constant_features + * cdef SIZE_t n_features = self.n_features # <<<<<<<<<<<<<< + * + * cdef DTYPE_t* Xf = self.feature_values + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_features; + __pyx_v_n_features = __pyx_t_2; + + /* "_splitter.pyx":1110 + * cdef SIZE_t n_features = self.n_features + * + * cdef DTYPE_t* Xf = self.feature_values # <<<<<<<<<<<<<< + * cdef SIZE_t* sorted_samples = self.sorted_samples + * cdef SIZE_t* index_to_samples = self.index_to_samples + */ + __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.feature_values; + __pyx_v_Xf = __pyx_t_4; + + /* "_splitter.pyx":1111 + * + * cdef DTYPE_t* Xf = self.feature_values + * cdef SIZE_t* sorted_samples = self.sorted_samples # <<<<<<<<<<<<<< + * cdef SIZE_t* index_to_samples = self.index_to_samples + * cdef SIZE_t max_features = self.max_features + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.sorted_samples; + __pyx_v_sorted_samples = __pyx_t_1; + + /* "_splitter.pyx":1112 + * cdef DTYPE_t* Xf = self.feature_values + * cdef SIZE_t* sorted_samples = self.sorted_samples + * cdef SIZE_t* index_to_samples = self.index_to_samples # <<<<<<<<<<<<<< + * cdef SIZE_t max_features = self.max_features + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + */ + __pyx_t_1 = __pyx_v_self->__pyx_base.index_to_samples; + __pyx_v_index_to_samples = __pyx_t_1; + + /* "_splitter.pyx":1113 + * cdef SIZE_t* sorted_samples = self.sorted_samples + * cdef SIZE_t* index_to_samples = self.index_to_samples + * cdef SIZE_t max_features = self.max_features # <<<<<<<<<<<<<< + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + * cdef double min_weight_leaf = self.min_weight_leaf + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features; + __pyx_v_max_features = __pyx_t_2; + + /* "_splitter.pyx":1114 + * cdef SIZE_t* index_to_samples = self.index_to_samples + * cdef SIZE_t max_features = self.max_features + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf # <<<<<<<<<<<<<< + * cdef double min_weight_leaf = self.min_weight_leaf + * cdef UINT32_t* random_state = &self.rand_r_state + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf; + __pyx_v_min_samples_leaf = __pyx_t_2; + + /* "_splitter.pyx":1115 + * cdef SIZE_t max_features = self.max_features + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< + * cdef UINT32_t* random_state = &self.rand_r_state + * + */ + __pyx_t_5 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf; + __pyx_v_min_weight_leaf = __pyx_t_5; + + /* "_splitter.pyx":1116 + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + * cdef double min_weight_leaf = self.min_weight_leaf + * cdef UINT32_t* random_state = &self.rand_r_state # <<<<<<<<<<<<<< + * + * cdef SplitRecord best, current + */ + __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state); + + /* "_splitter.pyx":1119 + * + * cdef SplitRecord best, current + * _init_split(&best, end) # <<<<<<<<<<<<<< + * cdef double current_proxy_improvement = - INFINITY + * cdef double best_proxy_improvement = - INFINITY + */ + __pyx_f_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); + + /* "_splitter.pyx":1120 + * cdef SplitRecord best, current + * _init_split(&best, end) + * cdef double current_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< + * cdef double best_proxy_improvement = - INFINITY + * + */ + __pyx_v_current_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + + /* "_splitter.pyx":1121 + * _init_split(&best, end) + * cdef double current_proxy_improvement = - INFINITY + * cdef double best_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< + * + * cdef SIZE_t f_i = n_features + */ + __pyx_v_best_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + + /* "_splitter.pyx":1123 + * cdef double best_proxy_improvement = - INFINITY + * + * cdef SIZE_t f_i = n_features # <<<<<<<<<<<<<< + * cdef SIZE_t f_j, p + * cdef SIZE_t n_visited_features = 0 + */ + __pyx_v_f_i = __pyx_v_n_features; + + /* "_splitter.pyx":1125 + * cdef SIZE_t f_i = n_features + * cdef SIZE_t f_j, p + * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< + * # Number of features discovered to be constant during the split search + * cdef SIZE_t n_found_constants = 0 + */ + __pyx_v_n_visited_features = 0; + + /* "_splitter.pyx":1127 + * cdef SIZE_t n_visited_features = 0 + * # Number of features discovered to be constant during the split search + * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 + */ + __pyx_v_n_found_constants = 0; + + /* "_splitter.pyx":1129 + * cdef SIZE_t n_found_constants = 0 + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< + * cdef SIZE_t n_known_constants = n_constant_features[0] + * # n_total_constants = n_known_constants + n_found_constants + */ + __pyx_v_n_drawn_constants = 0; + + /* "_splitter.pyx":1130 + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 + * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< + * # n_total_constants = n_known_constants + n_found_constants + * cdef SIZE_t n_total_constants = n_known_constants + */ + __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); + + /* "_splitter.pyx":1132 + * cdef SIZE_t n_known_constants = n_constant_features[0] + * # n_total_constants = n_known_constants + n_found_constants + * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< + * cdef DTYPE_t current_feature_value + * + */ + __pyx_v_n_total_constants = __pyx_v_n_known_constants; + + /* "_splitter.pyx":1137 + * cdef SIZE_t p_next + * cdef SIZE_t p_prev + * cdef bint is_samples_sorted = 0 # indicate is sorted_samples is # <<<<<<<<<<<<<< + * # inititialized + * + */ + __pyx_v_is_samples_sorted = 0; + + /* "_splitter.pyx":1154 + * # newly discovered constant features to spare computation on descendant + * # nodes. + * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< + * # are constant + * (n_visited_features < max_features or + */ + while (1) { + __pyx_t_7 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0); + if (__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L5_bool_binop_done; + } + + /* "_splitter.pyx":1156 + * while (f_i > n_total_constants and # Stop early if remaining features + * # are constant + * (n_visited_features < max_features or # <<<<<<<<<<<<<< + * # At least one drawn features must be non constant + * n_visited_features <= n_found_constants + n_drawn_constants)): + */ + __pyx_t_7 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0); + if (!__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L5_bool_binop_done; + } + + /* "_splitter.pyx":1158 + * (n_visited_features < max_features or + * # At least one drawn features must be non constant + * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< + * + * n_visited_features += 1 + */ + __pyx_t_7 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0); + __pyx_t_6 = __pyx_t_7; + __pyx_L5_bool_binop_done:; + if (!__pyx_t_6) break; + + /* "_splitter.pyx":1160 + * n_visited_features <= n_found_constants + n_drawn_constants)): + * + * n_visited_features += 1 # <<<<<<<<<<<<<< + * + * # Loop invariant: elements of features in + */ + __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); + + /* "_splitter.pyx":1174 + * + * # Draw a feature at random + * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< + * random_state) + * + */ + __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); + + /* "_splitter.pyx":1177 + * random_state) + * + * if f_j < n_known_constants: # <<<<<<<<<<<<<< + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] + */ + __pyx_t_6 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1179 + * if f_j < n_known_constants: + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] # <<<<<<<<<<<<<< + * + * n_drawn_constants += 1 + */ + __pyx_t_2 = (__pyx_v_features[__pyx_v_n_drawn_constants]); + __pyx_t_8 = (__pyx_v_features[__pyx_v_f_j]); + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2; + (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_8; + + /* "_splitter.pyx":1181 + * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] + * + * n_drawn_constants += 1 # <<<<<<<<<<<<<< + * + * else: + */ + __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); + + /* "_splitter.pyx":1177 + * random_state) + * + * if f_j < n_known_constants: # <<<<<<<<<<<<<< + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] + */ + goto __pyx_L8; + } + + /* "_splitter.pyx":1185 + * else: + * # f_j in the interval [n_known_constants, f_i - n_found_constants[ + * f_j += n_found_constants # <<<<<<<<<<<<<< + * # f_j in the interval [n_total_constants, f_i[ + * + */ + /*else*/ { + __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); + + /* "_splitter.pyx":1188 + * # f_j in the interval [n_total_constants, f_i[ + * + * current.feature = features[f_j] # <<<<<<<<<<<<<< + * self.extract_nnz(current.feature, + * &end_negative, &start_positive, + */ + __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); + + /* "_splitter.pyx":1189 + * + * current.feature = features[f_j] + * self.extract_nnz(current.feature, # <<<<<<<<<<<<<< + * &end_negative, &start_positive, + * &is_samples_sorted) + */ + __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); + + /* "_splitter.pyx":1194 + * + * # Sort the positive and negative parts of `Xf` + * sort(Xf + start, samples + start, end_negative - start) # <<<<<<<<<<<<<< + * sort(Xf + start_positive, samples + start_positive, + * end - start_positive) + */ + __pyx_f_9_splitter_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end_negative - __pyx_v_start)); + + /* "_splitter.pyx":1195 + * # Sort the positive and negative parts of `Xf` + * sort(Xf + start, samples + start, end_negative - start) + * sort(Xf + start_positive, samples + start_positive, # <<<<<<<<<<<<<< + * end - start_positive) + * + */ + __pyx_f_9_splitter_sort((__pyx_v_Xf + __pyx_v_start_positive), (__pyx_v_samples + __pyx_v_start_positive), (__pyx_v_end - __pyx_v_start_positive)); + + /* "_splitter.pyx":1199 + * + * # Update index_to_samples to take into account the sort + * for p in range(start, end_negative): # <<<<<<<<<<<<<< + * index_to_samples[samples[p]] = p + * for p in range(start_positive, end): + */ + __pyx_t_8 = __pyx_v_end_negative; + __pyx_t_2 = __pyx_t_8; + for (__pyx_t_9 = __pyx_v_start; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { + __pyx_v_p = __pyx_t_9; + + /* "_splitter.pyx":1200 + * # Update index_to_samples to take into account the sort + * for p in range(start, end_negative): + * index_to_samples[samples[p]] = p # <<<<<<<<<<<<<< + * for p in range(start_positive, end): + * index_to_samples[samples[p]] = p + */ + (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_p])]) = __pyx_v_p; + } + + /* "_splitter.pyx":1201 + * for p in range(start, end_negative): + * index_to_samples[samples[p]] = p + * for p in range(start_positive, end): # <<<<<<<<<<<<<< + * index_to_samples[samples[p]] = p + * + */ + __pyx_t_8 = __pyx_v_end; + __pyx_t_2 = __pyx_t_8; + for (__pyx_t_9 = __pyx_v_start_positive; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { + __pyx_v_p = __pyx_t_9; + + /* "_splitter.pyx":1202 + * index_to_samples[samples[p]] = p + * for p in range(start_positive, end): + * index_to_samples[samples[p]] = p # <<<<<<<<<<<<<< + * + * # Add one or two zeros in Xf, if there is any + */ + (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_p])]) = __pyx_v_p; + } + + /* "_splitter.pyx":1205 + * + * # Add one or two zeros in Xf, if there is any + * if end_negative < start_positive: # <<<<<<<<<<<<<< + * start_positive -= 1 + * Xf[start_positive] = 0. + */ + __pyx_t_6 = ((__pyx_v_end_negative < __pyx_v_start_positive) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1206 + * # Add one or two zeros in Xf, if there is any + * if end_negative < start_positive: + * start_positive -= 1 # <<<<<<<<<<<<<< + * Xf[start_positive] = 0. + * + */ + __pyx_v_start_positive = (__pyx_v_start_positive - 1); + + /* "_splitter.pyx":1207 + * if end_negative < start_positive: + * start_positive -= 1 + * Xf[start_positive] = 0. # <<<<<<<<<<<<<< + * + * if end_negative != start_positive: + */ + (__pyx_v_Xf[__pyx_v_start_positive]) = 0.; + + /* "_splitter.pyx":1209 + * Xf[start_positive] = 0. + * + * if end_negative != start_positive: # <<<<<<<<<<<<<< + * Xf[end_negative] = 0. + * end_negative += 1 + */ + __pyx_t_6 = ((__pyx_v_end_negative != __pyx_v_start_positive) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1210 + * + * if end_negative != start_positive: + * Xf[end_negative] = 0. # <<<<<<<<<<<<<< + * end_negative += 1 + * + */ + (__pyx_v_Xf[__pyx_v_end_negative]) = 0.; + + /* "_splitter.pyx":1211 + * if end_negative != start_positive: + * Xf[end_negative] = 0. + * end_negative += 1 # <<<<<<<<<<<<<< + * + * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: + */ + __pyx_v_end_negative = (__pyx_v_end_negative + 1); + + /* "_splitter.pyx":1209 + * Xf[start_positive] = 0. + * + * if end_negative != start_positive: # <<<<<<<<<<<<<< + * Xf[end_negative] = 0. + * end_negative += 1 + */ + } + + /* "_splitter.pyx":1205 + * + * # Add one or two zeros in Xf, if there is any + * if end_negative < start_positive: # <<<<<<<<<<<<<< + * start_positive -= 1 + * Xf[start_positive] = 0. + */ + } + + /* "_splitter.pyx":1213 + * end_negative += 1 + * + * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< + * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] + * + */ + __pyx_t_6 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1214 + * + * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: + * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] # <<<<<<<<<<<<<< + * + * n_found_constants += 1 + */ + __pyx_t_8 = (__pyx_v_features[__pyx_v_n_total_constants]); + __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_8; + (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2; + + /* "_splitter.pyx":1216 + * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] + * + * n_found_constants += 1 # <<<<<<<<<<<<<< + * n_total_constants += 1 + * + */ + __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); + + /* "_splitter.pyx":1217 + * + * n_found_constants += 1 + * n_total_constants += 1 # <<<<<<<<<<<<<< + * + * else: + */ + __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); + + /* "_splitter.pyx":1213 + * end_negative += 1 + * + * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< + * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] + * + */ + goto __pyx_L15; + } + + /* "_splitter.pyx":1220 + * + * else: + * f_i -= 1 # <<<<<<<<<<<<<< + * features[f_i], features[f_j] = features[f_j], features[f_i] + * + */ + /*else*/ { + __pyx_v_f_i = (__pyx_v_f_i - 1); + + /* "_splitter.pyx":1221 + * else: + * f_i -= 1 + * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< + * + * # Evaluate all splits + */ + __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]); + __pyx_t_8 = (__pyx_v_features[__pyx_v_f_i]); + (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2; + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_8; + + /* "_splitter.pyx":1224 + * + * # Evaluate all splits + * self.criterion.reset() # <<<<<<<<<<<<<< + * p = start + * + */ + __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1224, __pyx_L1_error) + + /* "_splitter.pyx":1225 + * # Evaluate all splits + * self.criterion.reset() + * p = start # <<<<<<<<<<<<<< + * + * while p < end: + */ + __pyx_v_p = __pyx_v_start; + + /* "_splitter.pyx":1227 + * p = start + * + * while p < end: # <<<<<<<<<<<<<< + * if p + 1 != end_negative: + * p_next = p + 1 + */ + while (1) { + __pyx_t_6 = ((__pyx_v_p < __pyx_v_end) != 0); + if (!__pyx_t_6) break; + + /* "_splitter.pyx":1228 + * + * while p < end: + * if p + 1 != end_negative: # <<<<<<<<<<<<<< + * p_next = p + 1 + * else: + */ + __pyx_t_6 = (((__pyx_v_p + 1) != __pyx_v_end_negative) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1229 + * while p < end: + * if p + 1 != end_negative: + * p_next = p + 1 # <<<<<<<<<<<<<< + * else: + * p_next = start_positive + */ + __pyx_v_p_next = (__pyx_v_p + 1); + + /* "_splitter.pyx":1228 + * + * while p < end: + * if p + 1 != end_negative: # <<<<<<<<<<<<<< + * p_next = p + 1 + * else: + */ + goto __pyx_L18; + } + + /* "_splitter.pyx":1231 + * p_next = p + 1 + * else: + * p_next = start_positive # <<<<<<<<<<<<<< + * + * while (p_next < end and + */ + /*else*/ { + __pyx_v_p_next = __pyx_v_start_positive; + } + __pyx_L18:; + + /* "_splitter.pyx":1233 + * p_next = start_positive + * + * while (p_next < end and # <<<<<<<<<<<<<< + * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): + * p = p_next + */ + while (1) { + __pyx_t_7 = ((__pyx_v_p_next < __pyx_v_end) != 0); + if (__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L21_bool_binop_done; + } + + /* "_splitter.pyx":1234 + * + * while (p_next < end and + * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): # <<<<<<<<<<<<<< + * p = p_next + * if p + 1 != end_negative: + */ + __pyx_t_7 = (((__pyx_v_Xf[__pyx_v_p_next]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + __pyx_t_6 = __pyx_t_7; + __pyx_L21_bool_binop_done:; + if (!__pyx_t_6) break; + + /* "_splitter.pyx":1235 + * while (p_next < end and + * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): + * p = p_next # <<<<<<<<<<<<<< + * if p + 1 != end_negative: + * p_next = p + 1 + */ + __pyx_v_p = __pyx_v_p_next; + + /* "_splitter.pyx":1236 + * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): + * p = p_next + * if p + 1 != end_negative: # <<<<<<<<<<<<<< + * p_next = p + 1 + * else: + */ + __pyx_t_6 = (((__pyx_v_p + 1) != __pyx_v_end_negative) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1237 + * p = p_next + * if p + 1 != end_negative: + * p_next = p + 1 # <<<<<<<<<<<<<< + * else: + * p_next = start_positive + */ + __pyx_v_p_next = (__pyx_v_p + 1); + + /* "_splitter.pyx":1236 + * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): + * p = p_next + * if p + 1 != end_negative: # <<<<<<<<<<<<<< + * p_next = p + 1 + * else: + */ + goto __pyx_L23; + } + + /* "_splitter.pyx":1239 + * p_next = p + 1 + * else: + * p_next = start_positive # <<<<<<<<<<<<<< + * + * + */ + /*else*/ { + __pyx_v_p_next = __pyx_v_start_positive; + } + __pyx_L23:; + } + + /* "_splitter.pyx":1244 + * # (p_next >= end) or (X[samples[p_next], current.feature] > + * # X[samples[p], current.feature]) + * p_prev = p # <<<<<<<<<<<<<< + * p = p_next + * # (p >= end) or (X[samples[p], current.feature] > + */ + __pyx_v_p_prev = __pyx_v_p; + + /* "_splitter.pyx":1245 + * # X[samples[p], current.feature]) + * p_prev = p + * p = p_next # <<<<<<<<<<<<<< + * # (p >= end) or (X[samples[p], current.feature] > + * # X[samples[p_prev], current.feature]) + */ + __pyx_v_p = __pyx_v_p_next; + + /* "_splitter.pyx":1250 + * + * + * if p < end: # <<<<<<<<<<<<<< + * current.pos = p + * + */ + __pyx_t_6 = ((__pyx_v_p < __pyx_v_end) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1251 + * + * if p < end: + * current.pos = p # <<<<<<<<<<<<<< + * + * # Reject if min_samples_leaf is not guaranteed + */ + __pyx_v_current.pos = __pyx_v_p; + + /* "_splitter.pyx":1254 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + __pyx_t_7 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0); + if (!__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L26_bool_binop_done; + } + + /* "_splitter.pyx":1255 + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or + * ((end - current.pos) < min_samples_leaf)): # <<<<<<<<<<<<<< + * continue + * + */ + __pyx_t_7 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0); + __pyx_t_6 = __pyx_t_7; + __pyx_L26_bool_binop_done:; + + /* "_splitter.pyx":1254 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + if (__pyx_t_6) { + + /* "_splitter.pyx":1256 + * if (((current.pos - start) < min_samples_leaf) or + * ((end - current.pos) < min_samples_leaf)): + * continue # <<<<<<<<<<<<<< + * + * self.criterion.update(current.pos) + */ + goto __pyx_L16_continue; + + /* "_splitter.pyx":1254 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + } + + /* "_splitter.pyx":1258 + * continue + * + * self.criterion.update(current.pos) # <<<<<<<<<<<<<< + * + * # Reject if min_weight_leaf is not satisfied + */ + __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1258, __pyx_L1_error) + + /* "_splitter.pyx":1261 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + __pyx_t_7 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_left < __pyx_v_min_weight_leaf) != 0); + if (!__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L29_bool_binop_done; + } + + /* "_splitter.pyx":1262 + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or + * (self.criterion.weighted_n_right < min_weight_leaf)): # <<<<<<<<<<<<<< + * continue + * + */ + __pyx_t_7 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_right < __pyx_v_min_weight_leaf) != 0); + __pyx_t_6 = __pyx_t_7; + __pyx_L29_bool_binop_done:; + + /* "_splitter.pyx":1261 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + if (__pyx_t_6) { + + /* "_splitter.pyx":1263 + * if ((self.criterion.weighted_n_left < min_weight_leaf) or + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue # <<<<<<<<<<<<<< + * + * current_proxy_improvement = self.criterion.proxy_impurity_improvement() + */ + goto __pyx_L16_continue; + + /* "_splitter.pyx":1261 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + } + + /* "_splitter.pyx":1265 + * continue + * + * current_proxy_improvement = self.criterion.proxy_impurity_improvement() # <<<<<<<<<<<<<< + * + * if current_proxy_improvement > best_proxy_improvement: + */ + __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); + + /* "_splitter.pyx":1267 + * current_proxy_improvement = self.criterion.proxy_impurity_improvement() + * + * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< + * best_proxy_improvement = current_proxy_improvement + * # sum of halves used to avoid infinite values + */ + __pyx_t_6 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1268 + * + * if current_proxy_improvement > best_proxy_improvement: + * best_proxy_improvement = current_proxy_improvement # <<<<<<<<<<<<<< + * # sum of halves used to avoid infinite values + * current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0 + */ + __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement; + + /* "_splitter.pyx":1270 + * best_proxy_improvement = current_proxy_improvement + * # sum of halves used to avoid infinite values + * current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0 # <<<<<<<<<<<<<< + * + * if ((current.threshold == Xf[p]) or + */ + __pyx_v_current.threshold = (((__pyx_v_Xf[__pyx_v_p_prev]) / 2.0) + ((__pyx_v_Xf[__pyx_v_p]) / 2.0)); + + /* "_splitter.pyx":1272 + * current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0 + * + * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< + * (current.threshold == INFINITY) or + * (current.threshold == -INFINITY)): + */ + __pyx_t_7 = ((__pyx_v_current.threshold == (__pyx_v_Xf[__pyx_v_p])) != 0); + if (!__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L33_bool_binop_done; + } + + /* "_splitter.pyx":1273 + * + * if ((current.threshold == Xf[p]) or + * (current.threshold == INFINITY) or # <<<<<<<<<<<<<< + * (current.threshold == -INFINITY)): + * current.threshold = Xf[p_prev] + */ + __pyx_t_7 = ((__pyx_v_current.threshold == __pyx_v_9_splitter_INFINITY) != 0); + if (!__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L33_bool_binop_done; + } + + /* "_splitter.pyx":1274 + * if ((current.threshold == Xf[p]) or + * (current.threshold == INFINITY) or + * (current.threshold == -INFINITY)): # <<<<<<<<<<<<<< + * current.threshold = Xf[p_prev] + * + */ + __pyx_t_7 = ((__pyx_v_current.threshold == (-__pyx_v_9_splitter_INFINITY)) != 0); + __pyx_t_6 = __pyx_t_7; + __pyx_L33_bool_binop_done:; + + /* "_splitter.pyx":1272 + * current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0 + * + * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< + * (current.threshold == INFINITY) or + * (current.threshold == -INFINITY)): + */ + if (__pyx_t_6) { + + /* "_splitter.pyx":1275 + * (current.threshold == INFINITY) or + * (current.threshold == -INFINITY)): + * current.threshold = Xf[p_prev] # <<<<<<<<<<<<<< + * + * best = current + */ + __pyx_v_current.threshold = (__pyx_v_Xf[__pyx_v_p_prev]); + + /* "_splitter.pyx":1272 + * current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0 + * + * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< + * (current.threshold == INFINITY) or + * (current.threshold == -INFINITY)): + */ + } + + /* "_splitter.pyx":1277 + * current.threshold = Xf[p_prev] + * + * best = current # <<<<<<<<<<<<<< + * + * # Reorganize into samples[start:best.pos] + samples[best.pos:end] + */ + __pyx_v_best = __pyx_v_current; + + /* "_splitter.pyx":1267 + * current_proxy_improvement = self.criterion.proxy_impurity_improvement() + * + * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< + * best_proxy_improvement = current_proxy_improvement + * # sum of halves used to avoid infinite values + */ + } + + /* "_splitter.pyx":1250 + * + * + * if p < end: # <<<<<<<<<<<<<< + * current.pos = p + * + */ + } + __pyx_L16_continue:; + } + } + __pyx_L15:; + } + __pyx_L8:; + } + + /* "_splitter.pyx":1280 + * + * # Reorganize into samples[start:best.pos] + samples[best.pos:end] + * if best.pos < end: # <<<<<<<<<<<<<< + * self.extract_nnz(best.feature, &end_negative, &start_positive, + * &is_samples_sorted) + */ + __pyx_t_6 = ((__pyx_v_best.pos < __pyx_v_end) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1281 + * # Reorganize into samples[start:best.pos] + samples[best.pos:end] + * if best.pos < end: + * self.extract_nnz(best.feature, &end_negative, &start_positive, # <<<<<<<<<<<<<< + * &is_samples_sorted) + * + */ + __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); + + /* "_splitter.pyx":1284 + * &is_samples_sorted) + * + * self._partition(best.threshold, end_negative, start_positive, # <<<<<<<<<<<<<< + * best.pos) + * + */ + (void)(__pyx_f_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.threshold, __pyx_v_end_negative, __pyx_v_start_positive, __pyx_v_best.pos)); + + /* "_splitter.pyx":1287 + * best.pos) + * + * self.criterion.reset() # <<<<<<<<<<<<<< + * self.criterion.update(best.pos) + * best.improvement = self.criterion.impurity_improvement(impurity) + */ + __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1287, __pyx_L1_error) + + /* "_splitter.pyx":1288 + * + * self.criterion.reset() + * self.criterion.update(best.pos) # <<<<<<<<<<<<<< + * best.improvement = self.criterion.impurity_improvement(impurity) + * self.criterion.children_impurity(&best.impurity_left, + */ + __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1288, __pyx_L1_error) + + /* "_splitter.pyx":1289 + * self.criterion.reset() + * self.criterion.update(best.pos) + * best.improvement = self.criterion.impurity_improvement(impurity) # <<<<<<<<<<<<<< + * self.criterion.children_impurity(&best.impurity_left, + * &best.impurity_right) + */ + __pyx_v_best.improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); + + /* "_splitter.pyx":1290 + * self.criterion.update(best.pos) + * best.improvement = self.criterion.impurity_improvement(impurity) + * self.criterion.children_impurity(&best.impurity_left, # <<<<<<<<<<<<<< + * &best.impurity_right) + * + */ + ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); + + /* "_splitter.pyx":1280 + * + * # Reorganize into samples[start:best.pos] + samples[best.pos:end] + * if best.pos < end: # <<<<<<<<<<<<<< + * self.extract_nnz(best.feature, &end_negative, &start_positive, + * &is_samples_sorted) + */ + } + + /* "_splitter.pyx":1296 + * # element in features[:n_known_constants] must be preserved for sibling + * # and child nodes + * memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) # <<<<<<<<<<<<<< + * + * # Copy newly found constant features + */ + (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, 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max_features = self.max_features # <<<<<<<<<<<<<< + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + * cdef double min_weight_leaf = self.min_weight_leaf + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features; + __pyx_v_max_features = __pyx_t_2; + + /* "_splitter.pyx":1343 + * cdef SIZE_t* index_to_samples = self.index_to_samples + * cdef SIZE_t max_features = self.max_features + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf # <<<<<<<<<<<<<< + * cdef double min_weight_leaf = self.min_weight_leaf + * cdef UINT32_t* random_state = &self.rand_r_state + */ + __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf; + __pyx_v_min_samples_leaf = __pyx_t_2; + + /* "_splitter.pyx":1344 + * cdef SIZE_t max_features = self.max_features + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< + * cdef UINT32_t* random_state = &self.rand_r_state + * + */ + __pyx_t_5 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf; + __pyx_v_min_weight_leaf = __pyx_t_5; + + /* "_splitter.pyx":1345 + * cdef SIZE_t min_samples_leaf = self.min_samples_leaf + * cdef double min_weight_leaf = self.min_weight_leaf + * cdef UINT32_t* random_state = &self.rand_r_state # <<<<<<<<<<<<<< + * + * cdef SplitRecord best, current + */ + __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state); + + /* "_splitter.pyx":1348 + * + * cdef SplitRecord best, current + * _init_split(&best, end) # <<<<<<<<<<<<<< + * cdef double current_proxy_improvement = - INFINITY + * cdef double best_proxy_improvement = - INFINITY + */ + __pyx_f_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); + + /* "_splitter.pyx":1349 + * cdef SplitRecord best, current + * _init_split(&best, end) + * cdef double current_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< + * cdef double best_proxy_improvement = - INFINITY + * + */ + __pyx_v_current_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + + /* "_splitter.pyx":1350 + * _init_split(&best, end) + * cdef double current_proxy_improvement = - INFINITY + * cdef double best_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< + * + * cdef DTYPE_t current_feature_value + */ + __pyx_v_best_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + + /* "_splitter.pyx":1354 + * cdef DTYPE_t current_feature_value + * + * cdef SIZE_t f_i = n_features # <<<<<<<<<<<<<< + * cdef SIZE_t f_j, p + * cdef SIZE_t n_visited_features = 0 + */ + __pyx_v_f_i = __pyx_v_n_features; + + /* "_splitter.pyx":1356 + * cdef SIZE_t f_i = n_features + * cdef SIZE_t f_j, p + * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< + * # Number of features discovered to be constant during the split search + * cdef SIZE_t n_found_constants = 0 + */ + __pyx_v_n_visited_features = 0; + + /* "_splitter.pyx":1358 + * cdef SIZE_t n_visited_features = 0 + * # Number of features discovered to be constant during the split search + * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 + */ + __pyx_v_n_found_constants = 0; + + /* "_splitter.pyx":1360 + * cdef SIZE_t n_found_constants = 0 + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< + * cdef SIZE_t n_known_constants = n_constant_features[0] + * # n_total_constants = n_known_constants + n_found_constants + */ + __pyx_v_n_drawn_constants = 0; + + /* "_splitter.pyx":1361 + * # Number of features known to be constant and drawn without replacement + * cdef SIZE_t n_drawn_constants = 0 + * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< + * # n_total_constants = n_known_constants + n_found_constants + * cdef SIZE_t n_total_constants = n_known_constants + */ + __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); + + /* "_splitter.pyx":1363 + * cdef SIZE_t n_known_constants = n_constant_features[0] + * # n_total_constants = n_known_constants + n_found_constants + * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< + * cdef SIZE_t partition_end + * + */ + __pyx_v_n_total_constants = __pyx_v_n_known_constants; + + /* "_splitter.pyx":1369 + * cdef DTYPE_t max_feature_value + * + * cdef bint is_samples_sorted = 0 # indicate that sorted_samples is # <<<<<<<<<<<<<< + * # inititialized + * + */ + __pyx_v_is_samples_sorted = 0; + + /* "_splitter.pyx":1386 + * # newly discovered constant features to spare computation on descendant + * # nodes. + * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< + * # are constant + * (n_visited_features < max_features or + */ + while (1) { + __pyx_t_7 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0); + if (__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L5_bool_binop_done; + } + + /* "_splitter.pyx":1388 + * while (f_i > n_total_constants and # Stop early if remaining features + * # are constant + * (n_visited_features < max_features or # <<<<<<<<<<<<<< + * # At least one drawn features must be non constant + * n_visited_features <= n_found_constants + n_drawn_constants)): + */ + __pyx_t_7 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0); + if (!__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L5_bool_binop_done; + } + + /* "_splitter.pyx":1390 + * (n_visited_features < max_features or + * # At least one drawn features must be non constant + * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< + * + * n_visited_features += 1 + */ + __pyx_t_7 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0); + __pyx_t_6 = __pyx_t_7; + __pyx_L5_bool_binop_done:; + if (!__pyx_t_6) break; + + /* "_splitter.pyx":1392 + * n_visited_features <= n_found_constants + n_drawn_constants)): + * + * n_visited_features += 1 # <<<<<<<<<<<<<< + * + * # Loop invariant: elements of features in + */ + __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); + + /* "_splitter.pyx":1406 + * + * # Draw a feature at random + * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< + * random_state) + * + */ + __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); + + /* "_splitter.pyx":1409 + * random_state) + * + * if f_j < n_known_constants: # <<<<<<<<<<<<<< + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] + */ + __pyx_t_6 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1411 + * if f_j < n_known_constants: + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] # <<<<<<<<<<<<<< + * + * n_drawn_constants += 1 + */ + __pyx_t_2 = (__pyx_v_features[__pyx_v_n_drawn_constants]); + __pyx_t_8 = (__pyx_v_features[__pyx_v_f_j]); + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2; + (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_8; + + /* "_splitter.pyx":1413 + * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] + * + * n_drawn_constants += 1 # <<<<<<<<<<<<<< + * + * else: + */ + __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); + + /* "_splitter.pyx":1409 + * random_state) + * + * if f_j < n_known_constants: # <<<<<<<<<<<<<< + * # f_j in the interval [n_drawn_constants, n_known_constants[ + * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] + */ + goto __pyx_L8; + } + + /* "_splitter.pyx":1417 + * else: + * # f_j in the interval [n_known_constants, f_i - n_found_constants[ + * f_j += n_found_constants # <<<<<<<<<<<<<< + * # f_j in the interval [n_total_constants, f_i[ + * + */ + /*else*/ { + __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); + + /* "_splitter.pyx":1420 + * # f_j in the interval [n_total_constants, f_i[ + * + * current.feature = features[f_j] # <<<<<<<<<<<<<< + * + * self.extract_nnz(current.feature, + */ + __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); + + /* "_splitter.pyx":1422 + * current.feature = features[f_j] + * + * self.extract_nnz(current.feature, # <<<<<<<<<<<<<< + * &end_negative, &start_positive, + * &is_samples_sorted) + */ + __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); + + /* "_splitter.pyx":1427 + * + * # Add one or two zeros in Xf, if there is any + * if end_negative < start_positive: # <<<<<<<<<<<<<< + * start_positive -= 1 + * Xf[start_positive] = 0. + */ + __pyx_t_6 = ((__pyx_v_end_negative < __pyx_v_start_positive) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1428 + * # Add one or two zeros in Xf, if there is any + * if end_negative < start_positive: + * start_positive -= 1 # <<<<<<<<<<<<<< + * Xf[start_positive] = 0. + * + */ + __pyx_v_start_positive = (__pyx_v_start_positive - 1); + + /* "_splitter.pyx":1429 + * if end_negative < start_positive: + * start_positive -= 1 + * Xf[start_positive] = 0. # <<<<<<<<<<<<<< + * + * if end_negative != start_positive: + */ + (__pyx_v_Xf[__pyx_v_start_positive]) = 0.; + + /* "_splitter.pyx":1431 + * Xf[start_positive] = 0. + * + * if end_negative != start_positive: # <<<<<<<<<<<<<< + * Xf[end_negative] = 0. + * end_negative += 1 + */ + __pyx_t_6 = ((__pyx_v_end_negative != __pyx_v_start_positive) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1432 + * + * if end_negative != start_positive: + * Xf[end_negative] = 0. # <<<<<<<<<<<<<< + * end_negative += 1 + * + */ + (__pyx_v_Xf[__pyx_v_end_negative]) = 0.; + + /* "_splitter.pyx":1433 + * if end_negative != start_positive: + * Xf[end_negative] = 0. + * end_negative += 1 # <<<<<<<<<<<<<< + * + * # Find min, max in Xf[start:end_negative] + */ + __pyx_v_end_negative = (__pyx_v_end_negative + 1); + + /* "_splitter.pyx":1431 + * Xf[start_positive] = 0. + * + * if end_negative != start_positive: # <<<<<<<<<<<<<< + * Xf[end_negative] = 0. + * end_negative += 1 + */ + } + + /* "_splitter.pyx":1427 + * + * # Add one or two zeros in Xf, if there is any + * if end_negative < start_positive: # <<<<<<<<<<<<<< + * start_positive -= 1 + * Xf[start_positive] = 0. + */ + } + + /* "_splitter.pyx":1436 + * + * # Find min, max in Xf[start:end_negative] + * min_feature_value = Xf[start] # <<<<<<<<<<<<<< + * max_feature_value = min_feature_value + * + */ + __pyx_v_min_feature_value = (__pyx_v_Xf[__pyx_v_start]); + + /* "_splitter.pyx":1437 + * # Find min, max in Xf[start:end_negative] + * min_feature_value = Xf[start] + * max_feature_value = min_feature_value # <<<<<<<<<<<<<< + * + * for p in range(start, end_negative): + */ + __pyx_v_max_feature_value = __pyx_v_min_feature_value; + + /* "_splitter.pyx":1439 + * max_feature_value = min_feature_value + * + * for p in range(start, end_negative): # <<<<<<<<<<<<<< + * current_feature_value = Xf[p] + * + */ + __pyx_t_8 = __pyx_v_end_negative; + __pyx_t_2 = __pyx_t_8; + for (__pyx_t_9 = __pyx_v_start; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { + __pyx_v_p = __pyx_t_9; + + /* "_splitter.pyx":1440 + * + * for p in range(start, end_negative): + * current_feature_value = Xf[p] # <<<<<<<<<<<<<< + * + * if current_feature_value < min_feature_value: + */ + __pyx_v_current_feature_value = (__pyx_v_Xf[__pyx_v_p]); + + /* "_splitter.pyx":1442 + * current_feature_value = Xf[p] + * + * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: + */ + __pyx_t_6 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1443 + * + * if current_feature_value < min_feature_value: + * min_feature_value = current_feature_value # <<<<<<<<<<<<<< + * elif current_feature_value > max_feature_value: + * max_feature_value = current_feature_value + */ + __pyx_v_min_feature_value = __pyx_v_current_feature_value; + + /* "_splitter.pyx":1442 + * current_feature_value = Xf[p] + * + * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: + */ + goto __pyx_L13; + } + + /* "_splitter.pyx":1444 + * if current_feature_value < min_feature_value: + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< + * max_feature_value = current_feature_value + * + */ + __pyx_t_6 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1445 + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: + * max_feature_value = current_feature_value # <<<<<<<<<<<<<< + * + * # Update min, max given Xf[start_positive:end] + */ + __pyx_v_max_feature_value = __pyx_v_current_feature_value; + + /* "_splitter.pyx":1444 + * if current_feature_value < min_feature_value: + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< + * max_feature_value = current_feature_value + * + */ + } + __pyx_L13:; + } + + /* "_splitter.pyx":1448 + * + * # Update min, max given Xf[start_positive:end] + * for p in range(start_positive, end): # <<<<<<<<<<<<<< + * current_feature_value = Xf[p] + * + */ + __pyx_t_8 = __pyx_v_end; + __pyx_t_2 = __pyx_t_8; + for (__pyx_t_9 = __pyx_v_start_positive; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { + __pyx_v_p = __pyx_t_9; + + /* "_splitter.pyx":1449 + * # Update min, max given Xf[start_positive:end] + * for p in range(start_positive, end): + * current_feature_value = Xf[p] # <<<<<<<<<<<<<< + * + * if current_feature_value < min_feature_value: + */ + __pyx_v_current_feature_value = (__pyx_v_Xf[__pyx_v_p]); + + /* "_splitter.pyx":1451 + * current_feature_value = Xf[p] + * + * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: + */ + __pyx_t_6 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1452 + * + * if current_feature_value < min_feature_value: + * min_feature_value = current_feature_value # <<<<<<<<<<<<<< + * elif current_feature_value > max_feature_value: + * max_feature_value = current_feature_value + */ + __pyx_v_min_feature_value = __pyx_v_current_feature_value; + + /* "_splitter.pyx":1451 + * current_feature_value = Xf[p] + * + * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: + */ + goto __pyx_L16; + } + + /* "_splitter.pyx":1453 + * if current_feature_value < min_feature_value: + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< + * max_feature_value = current_feature_value + * + */ + __pyx_t_6 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1454 + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: + * max_feature_value = current_feature_value # <<<<<<<<<<<<<< + * + * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: + */ + __pyx_v_max_feature_value = __pyx_v_current_feature_value; + + /* "_splitter.pyx":1453 + * if current_feature_value < min_feature_value: + * min_feature_value = current_feature_value + * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< + * max_feature_value = current_feature_value + * + */ + } + __pyx_L16:; + } + + /* "_splitter.pyx":1456 + * max_feature_value = current_feature_value + * + * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< + * features[f_j] = features[n_total_constants] + * features[n_total_constants] = current.feature + */ + __pyx_t_6 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1457 + * + * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: + * features[f_j] = features[n_total_constants] # <<<<<<<<<<<<<< + * features[n_total_constants] = current.feature + * + */ + (__pyx_v_features[__pyx_v_f_j]) = (__pyx_v_features[__pyx_v_n_total_constants]); + + /* "_splitter.pyx":1458 + * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: + * features[f_j] = features[n_total_constants] + * features[n_total_constants] = current.feature # <<<<<<<<<<<<<< + * + * n_found_constants += 1 + */ + __pyx_t_8 = __pyx_v_current.feature; + (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_8; + + /* "_splitter.pyx":1460 + * features[n_total_constants] = current.feature + * + * n_found_constants += 1 # <<<<<<<<<<<<<< + * n_total_constants += 1 + * + */ + __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); + + /* "_splitter.pyx":1461 + * + * n_found_constants += 1 + * n_total_constants += 1 # <<<<<<<<<<<<<< + * + * else: + */ + __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); + + /* "_splitter.pyx":1456 + * max_feature_value = current_feature_value + * + * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< + * features[f_j] = features[n_total_constants] + * features[n_total_constants] = current.feature + */ + goto __pyx_L17; + } + + /* "_splitter.pyx":1464 + * + * else: + * f_i -= 1 # <<<<<<<<<<<<<< + * features[f_i], features[f_j] = features[f_j], features[f_i] + * + */ + /*else*/ { + __pyx_v_f_i = (__pyx_v_f_i - 1); + + /* "_splitter.pyx":1465 + * else: + * f_i -= 1 + * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< + * + * # Draw a random threshold + */ + __pyx_t_8 = (__pyx_v_features[__pyx_v_f_j]); + __pyx_t_2 = (__pyx_v_features[__pyx_v_f_i]); + (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_8; + (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2; + + /* "_splitter.pyx":1468 + * + * # Draw a random threshold + * current.threshold = rand_uniform(min_feature_value, # <<<<<<<<<<<<<< + * max_feature_value, + * random_state) + */ + __pyx_v_current.threshold = __pyx_f_7sklearn_4tree_6_utils_rand_uniform(__pyx_v_min_feature_value, __pyx_v_max_feature_value, __pyx_v_random_state); + + /* "_splitter.pyx":1472 + * random_state) + * + * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< + * current.threshold = min_feature_value + * + */ + __pyx_t_6 = ((__pyx_v_current.threshold == __pyx_v_max_feature_value) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1473 + * + * if current.threshold == max_feature_value: + * current.threshold = min_feature_value # <<<<<<<<<<<<<< + * + * # Partition + */ + __pyx_v_current.threshold = __pyx_v_min_feature_value; + + /* "_splitter.pyx":1472 + * random_state) + * + * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< + * current.threshold = min_feature_value + * + */ + } + + /* "_splitter.pyx":1476 + * + * # Partition + * current.pos = self._partition(current.threshold, # <<<<<<<<<<<<<< + * end_negative, + * start_positive, + */ + __pyx_v_current.pos = __pyx_f_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.threshold, __pyx_v_end_negative, __pyx_v_start_positive, (__pyx_v_start_positive + ((__pyx_v_Xf[__pyx_v_start_positive]) == 0.))); + + /* "_splitter.pyx":1483 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + __pyx_t_7 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0); + if (!__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L20_bool_binop_done; + } + + /* "_splitter.pyx":1484 + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or + * ((end - current.pos) < min_samples_leaf)): # <<<<<<<<<<<<<< + * continue + * + */ + __pyx_t_7 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0); + __pyx_t_6 = __pyx_t_7; + __pyx_L20_bool_binop_done:; + + /* "_splitter.pyx":1483 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + if (__pyx_t_6) { + + /* "_splitter.pyx":1485 + * if (((current.pos - start) < min_samples_leaf) or + * ((end - current.pos) < min_samples_leaf)): + * continue # <<<<<<<<<<<<<< + * + * # Evaluate split + */ + goto __pyx_L3_continue; + + /* "_splitter.pyx":1483 + * + * # Reject if min_samples_leaf is not guaranteed + * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< + * ((end - current.pos) < min_samples_leaf)): + * continue + */ + } + + /* "_splitter.pyx":1488 + * + * # Evaluate split + * self.criterion.reset() # <<<<<<<<<<<<<< + * self.criterion.update(current.pos) + * + */ + __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1488, __pyx_L1_error) + + /* "_splitter.pyx":1489 + * # Evaluate split + * self.criterion.reset() + * self.criterion.update(current.pos) # <<<<<<<<<<<<<< + * + * # Reject if min_weight_leaf is not satisfied + */ + __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1489, __pyx_L1_error) + + /* "_splitter.pyx":1492 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + __pyx_t_7 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_left < __pyx_v_min_weight_leaf) != 0); + if (!__pyx_t_7) { + } else { + __pyx_t_6 = __pyx_t_7; + goto __pyx_L23_bool_binop_done; + } + + /* "_splitter.pyx":1493 + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or + * (self.criterion.weighted_n_right < min_weight_leaf)): # <<<<<<<<<<<<<< + * continue + * + */ + __pyx_t_7 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_right < __pyx_v_min_weight_leaf) != 0); + __pyx_t_6 = __pyx_t_7; + __pyx_L23_bool_binop_done:; + + /* "_splitter.pyx":1492 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + if (__pyx_t_6) { + + /* "_splitter.pyx":1494 + * if ((self.criterion.weighted_n_left < min_weight_leaf) or + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue # <<<<<<<<<<<<<< + * + * current_proxy_improvement = self.criterion.proxy_impurity_improvement() + */ + goto __pyx_L3_continue; + + /* "_splitter.pyx":1492 + * + * # Reject if min_weight_leaf is not satisfied + * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< + * (self.criterion.weighted_n_right < min_weight_leaf)): + * continue + */ + } + + /* "_splitter.pyx":1496 + * continue + * + * current_proxy_improvement = self.criterion.proxy_impurity_improvement() # <<<<<<<<<<<<<< + * + * if current_proxy_improvement > best_proxy_improvement: + */ + __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); + + /* "_splitter.pyx":1498 + * current_proxy_improvement = self.criterion.proxy_impurity_improvement() + * + * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< + * best_proxy_improvement = current_proxy_improvement + * current.improvement = self.criterion.impurity_improvement(impurity) + */ + __pyx_t_6 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0); + if (__pyx_t_6) { + + /* "_splitter.pyx":1499 + * + * if current_proxy_improvement > best_proxy_improvement: + * best_proxy_improvement = current_proxy_improvement # <<<<<<<<<<<<<< + * current.improvement = self.criterion.impurity_improvement(impurity) + * + */ + __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement; + + /* "_splitter.pyx":1500 + * if current_proxy_improvement > best_proxy_improvement: + * best_proxy_improvement = current_proxy_improvement + * current.improvement = self.criterion.impurity_improvement(impurity) # <<<<<<<<<<<<<< + * + * self.criterion.children_impurity(¤t.impurity_left, + */ + __pyx_v_current.improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); + + /* "_splitter.pyx":1502 + * current.improvement = self.criterion.impurity_improvement(impurity) + * + * self.criterion.children_impurity(¤t.impurity_left, # <<<<<<<<<<<<<< + * ¤t.impurity_right) + * best = current + */ + ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_current.impurity_left), (&__pyx_v_current.impurity_right)); + + /* "_splitter.pyx":1504 + * self.criterion.children_impurity(¤t.impurity_left, + * ¤t.impurity_right) + * best = current # <<<<<<<<<<<<<< + * + * # Reorganize into samples[start:best.pos] + samples[best.pos:end] + */ + __pyx_v_best = __pyx_v_current; + + /* "_splitter.pyx":1498 + * current_proxy_improvement = self.criterion.proxy_impurity_improvement() + * + * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< + * best_proxy_improvement = current_proxy_improvement + * current.improvement = self.criterion.impurity_improvement(impurity) + */ + } + } + __pyx_L17:; + } + __pyx_L8:; + __pyx_L3_continue:; + } + + /* "_splitter.pyx":1507 + * + * # Reorganize into samples[start:best.pos] + samples[best.pos:end] + * if best.pos < end: # <<<<<<<<<<<<<< + * if current.feature != best.feature: + * self.extract_nnz(best.feature, &end_negative, &start_positive, + */ + __pyx_t_6 = ((__pyx_v_best.pos < __pyx_v_end) != 0); + if (__pyx_t_6) { 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__Pyx_AddTraceback("View.MemoryView.memview_slice", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = 0; + __pyx_L0:; + __Pyx_XDECREF((PyObject *)__pyx_v_memviewsliceobj); + __Pyx_XDECREF(__pyx_v_index); + __Pyx_XGIVEREF((PyObject *)__pyx_r); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +/* "View.MemoryView":807 + * + * @cname('__pyx_memoryview_slice_memviewslice') + * cdef int slice_memviewslice( # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset, + */ + +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, Py_ssize_t __pyx_v_shape, Py_ssize_t __pyx_v_stride, Py_ssize_t __pyx_v_suboffset, int __pyx_v_dim, int __pyx_v_new_ndim, int *__pyx_v_suboffset_dim, Py_ssize_t __pyx_v_start, Py_ssize_t __pyx_v_stop, Py_ssize_t __pyx_v_step, int __pyx_v_have_start, int __pyx_v_have_stop, int __pyx_v_have_step, int __pyx_v_is_slice) { + Py_ssize_t __pyx_v_new_shape; + int __pyx_v_negative_step; + int __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "View.MemoryView":827 + * cdef bint negative_step + * + * if not is_slice: # <<<<<<<<<<<<<< + * + * if start < 0: + */ + __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":829 + * if not is_slice: + * + * if start < 0: # <<<<<<<<<<<<<< + * start += shape + * if not 0 <= start < shape: + */ + __pyx_t_1 = ((__pyx_v_start < 0) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":830 + * + * if start < 0: + * start += shape # <<<<<<<<<<<<<< + * if not 0 <= start < shape: + * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) + */ + __pyx_v_start = (__pyx_v_start + __pyx_v_shape); + + /* "View.MemoryView":829 + * if not is_slice: + * + * if start < 0: # <<<<<<<<<<<<<< + * start += shape + * if not 0 <= start < shape: + */ + } + + /* "View.MemoryView":831 + * if start < 0: + * start += shape + * if not 0 <= start < shape: # <<<<<<<<<<<<<< + * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) + * else: + */ + __pyx_t_1 = (0 <= __pyx_v_start); + if (__pyx_t_1) { + __pyx_t_1 = (__pyx_v_start < __pyx_v_shape); + } + __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":832 + * start += shape + * if not 0 <= start < shape: + * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) # <<<<<<<<<<<<<< + * else: + * + */ + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"Index out of bounds (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(1, 832, __pyx_L1_error) + + /* "View.MemoryView":831 + * if start < 0: + * start += shape + * if not 0 <= start < shape: # <<<<<<<<<<<<<< + * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) + * else: + */ + } + + /* "View.MemoryView":827 + * cdef bint negative_step + * + * if not is_slice: # <<<<<<<<<<<<<< + * + * if start < 0: + */ + goto __pyx_L3; + } + + /* "View.MemoryView":835 + * else: + * + * negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<< + * + * if have_step and step == 0: + */ + /*else*/ { + __pyx_t_1 = ((__pyx_v_have_step != 0) != 0); + if (__pyx_t_1) { + } else { + __pyx_t_2 = __pyx_t_1; + goto __pyx_L6_bool_binop_done; + } + __pyx_t_1 = ((__pyx_v_step < 0) != 0); + __pyx_t_2 = __pyx_t_1; + __pyx_L6_bool_binop_done:; + __pyx_v_negative_step = __pyx_t_2; + + /* "View.MemoryView":837 + * negative_step = have_step != 0 and step < 0 + * + * if have_step and step == 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) + * + */ + __pyx_t_1 = (__pyx_v_have_step != 0); + if (__pyx_t_1) { + } else { + __pyx_t_2 = __pyx_t_1; + goto __pyx_L9_bool_binop_done; + } + __pyx_t_1 = ((__pyx_v_step == 0) != 0); + __pyx_t_2 = __pyx_t_1; + __pyx_L9_bool_binop_done:; + if (__pyx_t_2) { + + /* "View.MemoryView":838 + * + * if have_step and step == 0: + * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Step may not be zero (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(1, 838, __pyx_L1_error) + + /* "View.MemoryView":837 + * negative_step = have_step != 0 and step < 0 + * + * if have_step and step == 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) + * + */ + } + + /* "View.MemoryView":841 + * + * + * if have_start: # <<<<<<<<<<<<<< + * if start < 0: + * start += shape + */ + __pyx_t_2 = (__pyx_v_have_start != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":842 + * + * if have_start: + * if start < 0: # <<<<<<<<<<<<<< + * start += shape + * if start < 0: + */ + __pyx_t_2 = ((__pyx_v_start < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":843 + * if have_start: + * if start < 0: + * start += shape # <<<<<<<<<<<<<< + * if start < 0: + * start = 0 + */ + __pyx_v_start = (__pyx_v_start + __pyx_v_shape); + + /* "View.MemoryView":844 + * if start < 0: + * start += shape + * if start < 0: # <<<<<<<<<<<<<< + * start = 0 + * elif start >= shape: + */ + __pyx_t_2 = ((__pyx_v_start < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":845 + * start += shape + * if start < 0: + * start = 0 # <<<<<<<<<<<<<< + * elif start >= shape: + * if negative_step: + */ + __pyx_v_start = 0; + + /* "View.MemoryView":844 + * if start < 0: + * start += shape + * if start < 0: # <<<<<<<<<<<<<< + * start = 0 + * elif start >= shape: + */ + } + + /* "View.MemoryView":842 + * + * if have_start: + * if start < 0: # <<<<<<<<<<<<<< + * start += shape + * if start < 0: + */ + goto __pyx_L12; + } + + /* "View.MemoryView":846 + * if start < 0: + * start = 0 + * elif start >= shape: # <<<<<<<<<<<<<< + * if negative_step: + * start = shape - 1 + */ + __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":847 + * start = 0 + * elif start >= shape: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":848 + * elif start >= shape: + * if negative_step: + * start = shape - 1 # <<<<<<<<<<<<<< + * else: + * start = shape + */ + __pyx_v_start = (__pyx_v_shape - 1); + + /* "View.MemoryView":847 + * start = 0 + * elif start >= shape: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + goto __pyx_L14; + } + + /* "View.MemoryView":850 + * start = shape - 1 + * else: + * start = shape # <<<<<<<<<<<<<< + * else: + * if negative_step: + */ + /*else*/ { + __pyx_v_start = __pyx_v_shape; + } + __pyx_L14:; + + /* "View.MemoryView":846 + * if start < 0: + * start = 0 + * elif start >= shape: # <<<<<<<<<<<<<< + * if negative_step: + * start = shape - 1 + */ + } + __pyx_L12:; + + /* "View.MemoryView":841 + * + * + * if have_start: # <<<<<<<<<<<<<< + * if start < 0: + * start += shape + */ + goto __pyx_L11; + } + + /* "View.MemoryView":852 + * start = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + /*else*/ { + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":853 + * else: + * if negative_step: + * start = shape - 1 # <<<<<<<<<<<<<< + * else: + * start = 0 + */ + __pyx_v_start = (__pyx_v_shape - 1); + + /* "View.MemoryView":852 + * start = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + goto __pyx_L15; + } + + /* "View.MemoryView":855 + * start = shape - 1 + * else: + * start = 0 # <<<<<<<<<<<<<< + * + * if have_stop: + */ + /*else*/ { + __pyx_v_start = 0; + } + __pyx_L15:; + } + __pyx_L11:; + + /* "View.MemoryView":857 + * start = 0 + * + * if have_stop: # <<<<<<<<<<<<<< + * if stop < 0: + * stop += shape + */ + __pyx_t_2 = (__pyx_v_have_stop != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":858 + * + * if have_stop: + * if stop < 0: # <<<<<<<<<<<<<< + * stop += shape + * if stop < 0: + */ + __pyx_t_2 = ((__pyx_v_stop < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":859 + * if have_stop: + * if stop < 0: + * stop += shape # <<<<<<<<<<<<<< + * if stop < 0: + * stop = 0 + */ + __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape); + + /* "View.MemoryView":860 + * if stop < 0: + * stop += shape + * if stop < 0: # <<<<<<<<<<<<<< + * stop = 0 + * elif stop > shape: + */ + __pyx_t_2 = ((__pyx_v_stop < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":861 + * stop += shape + * if stop < 0: + * stop = 0 # <<<<<<<<<<<<<< + * elif stop > shape: + * stop = shape + */ + __pyx_v_stop = 0; + + /* "View.MemoryView":860 + * if stop < 0: + * stop += shape + * if stop < 0: # <<<<<<<<<<<<<< + * stop = 0 + * elif stop > shape: + */ + } + + /* "View.MemoryView":858 + * + * if have_stop: + * if stop < 0: # <<<<<<<<<<<<<< + * stop += shape + * if stop < 0: + */ + goto __pyx_L17; + } + + /* "View.MemoryView":862 + * if stop < 0: + * stop = 0 + * elif stop > shape: # <<<<<<<<<<<<<< + * stop = shape + * else: + */ + __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":863 + * stop = 0 + * elif stop > shape: + * stop = shape # <<<<<<<<<<<<<< + * else: + * if negative_step: + */ + __pyx_v_stop = __pyx_v_shape; + + /* "View.MemoryView":862 + * if stop < 0: + * stop = 0 + * elif stop > shape: # <<<<<<<<<<<<<< + * stop = shape + * else: + */ + } + __pyx_L17:; + + /* "View.MemoryView":857 + * start = 0 + * + * if have_stop: # <<<<<<<<<<<<<< + * if stop < 0: + * stop += shape + */ + goto __pyx_L16; + } + + /* "View.MemoryView":865 + * stop = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * stop = -1 + * else: + */ + /*else*/ { + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":866 + * else: + * if negative_step: + * stop = -1 # <<<<<<<<<<<<<< + * else: + * stop = shape + */ + __pyx_v_stop = -1L; + + /* "View.MemoryView":865 + * stop = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * stop = -1 + * else: + */ + goto __pyx_L19; + } + + /* "View.MemoryView":868 + * stop = -1 + * else: + * stop = shape # <<<<<<<<<<<<<< + * + * if not have_step: + */ + /*else*/ { + __pyx_v_stop = __pyx_v_shape; + } + __pyx_L19:; + } + __pyx_L16:; + + /* "View.MemoryView":870 + * stop = shape + * + * if not have_step: # <<<<<<<<<<<<<< + * step = 1 + * + */ + __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":871 + * + * if not have_step: + * step = 1 # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_step = 1; + + /* "View.MemoryView":870 + * stop = shape + * + * if not have_step: # <<<<<<<<<<<<<< + * step = 1 + * + */ + } + + /* "View.MemoryView":875 + * + * with cython.cdivision(True): + * new_shape = (stop - start) // step # <<<<<<<<<<<<<< + * + * if (stop - start) - step * new_shape: + */ + __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step); + + /* "View.MemoryView":877 + * new_shape = (stop - start) // step + * + * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< + * new_shape += 1 + * + */ + __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":878 + * + * if (stop - start) - step * new_shape: + * new_shape += 1 # <<<<<<<<<<<<<< + * + * if new_shape < 0: + */ + __pyx_v_new_shape = (__pyx_v_new_shape + 1); + + /* "View.MemoryView":877 + * new_shape = (stop - start) // step + * + * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< + * new_shape += 1 + * + */ + } + + /* "View.MemoryView":880 + * new_shape += 1 + * + * if new_shape < 0: # <<<<<<<<<<<<<< + * new_shape = 0 + * + */ + __pyx_t_2 = ((__pyx_v_new_shape < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":881 + * + * if new_shape < 0: + * new_shape = 0 # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_new_shape = 0; + + /* "View.MemoryView":880 + * new_shape += 1 + * + * if new_shape < 0: # <<<<<<<<<<<<<< + * new_shape = 0 + * + */ + } + + /* "View.MemoryView":884 + * + * + * dst.strides[new_ndim] = stride * step # <<<<<<<<<<<<<< + * dst.shape[new_ndim] = new_shape + * dst.suboffsets[new_ndim] = suboffset + */ + (__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step); + + /* "View.MemoryView":885 + * + * dst.strides[new_ndim] = stride * step + * dst.shape[new_ndim] = new_shape # <<<<<<<<<<<<<< + * dst.suboffsets[new_ndim] = suboffset + * + */ + (__pyx_v_dst->shape[__pyx_v_new_ndim]) = __pyx_v_new_shape; + + /* "View.MemoryView":886 + * dst.strides[new_ndim] = stride * step + * dst.shape[new_ndim] = new_shape + * dst.suboffsets[new_ndim] = suboffset # <<<<<<<<<<<<<< + * + * + */ + (__pyx_v_dst->suboffsets[__pyx_v_new_ndim]) = __pyx_v_suboffset; + } + __pyx_L3:; + + /* "View.MemoryView":889 + * + * + * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< + * dst.data += start * stride + * else: + */ + __pyx_t_2 = (((__pyx_v_suboffset_dim[0]) < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":890 + * + * if suboffset_dim[0] < 0: + * dst.data += start * stride # <<<<<<<<<<<<<< + * else: + * dst.suboffsets[suboffset_dim[0]] += start * stride + */ + __pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride)); + + /* "View.MemoryView":889 + * + * + * if suboffset_dim[0] < 0: # <<<<<<<<<<<<<< + * dst.data += start * stride + * else: + */ + goto __pyx_L23; + } + + /* "View.MemoryView":892 + * dst.data += start * stride + * else: + * dst.suboffsets[suboffset_dim[0]] += start * stride # <<<<<<<<<<<<<< + * + * if suboffset >= 0: + */ + /*else*/ { + __pyx_t_3 = (__pyx_v_suboffset_dim[0]); + (__pyx_v_dst->suboffsets[__pyx_t_3]) = ((__pyx_v_dst->suboffsets[__pyx_t_3]) + (__pyx_v_start * __pyx_v_stride)); + } + __pyx_L23:; + + /* "View.MemoryView":894 + * dst.suboffsets[suboffset_dim[0]] += start * stride + * + * if suboffset >= 0: # <<<<<<<<<<<<<< + * if not is_slice: + * if new_ndim == 0: + */ + __pyx_t_2 = ((__pyx_v_suboffset >= 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":895 + * + * if suboffset >= 0: + * if not is_slice: # <<<<<<<<<<<<<< + * if new_ndim == 0: + * dst.data = ( dst.data)[0] + suboffset + */ + __pyx_t_2 = ((!(__pyx_v_is_slice != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":896 + * if suboffset >= 0: + * if not is_slice: + * if new_ndim == 0: # <<<<<<<<<<<<<< + * dst.data = ( dst.data)[0] + suboffset + * else: + */ + __pyx_t_2 = ((__pyx_v_new_ndim == 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":897 + * if not is_slice: + * if new_ndim == 0: + * dst.data = ( dst.data)[0] + suboffset # <<<<<<<<<<<<<< + * else: + * _err_dim(IndexError, "All dimensions preceding dimension %d " + */ + __pyx_v_dst->data = ((((char **)__pyx_v_dst->data)[0]) + __pyx_v_suboffset); + + /* "View.MemoryView":896 + * if suboffset >= 0: + * if not is_slice: + * if new_ndim == 0: # <<<<<<<<<<<<<< + * dst.data = ( dst.data)[0] + suboffset + * else: + */ + goto __pyx_L26; + } + + /* "View.MemoryView":899 + * dst.data = ( dst.data)[0] + suboffset + * else: + * _err_dim(IndexError, "All dimensions preceding dimension %d " # <<<<<<<<<<<<<< + * "must be indexed and not sliced", dim) + * else: + */ + /*else*/ { + + /* "View.MemoryView":900 + * else: + * _err_dim(IndexError, "All dimensions preceding dimension %d " + * "must be indexed and not sliced", dim) # <<<<<<<<<<<<<< + * else: + * suboffset_dim[0] = new_ndim + */ + __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"All dimensions preceding dimension %d must be indexed and not sliced"), __pyx_v_dim); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(1, 899, __pyx_L1_error) + } + __pyx_L26:; + + /* "View.MemoryView":895 + * + * if suboffset >= 0: + * if not is_slice: # <<<<<<<<<<<<<< + * if new_ndim == 0: + * dst.data = ( dst.data)[0] + suboffset + */ + goto __pyx_L25; + } + + /* "View.MemoryView":902 + * "must be indexed and not sliced", dim) + * else: + * suboffset_dim[0] = new_ndim # <<<<<<<<<<<<<< + * + * return 0 + */ + /*else*/ { + 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memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< + * """ + * Create a new memoryview object from a given memoryview object and slice. + */ + + /* function exit code */ + __pyx_L1_error:; + __Pyx_XDECREF(__pyx_t_5); + __Pyx_AddTraceback("View.MemoryView.memoryview_copy_from_slice", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = 0; + __pyx_L0:; + __Pyx_XGIVEREF(__pyx_r); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +/* "View.MemoryView":1109 + * + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< + * if arg < 0: + * return -arg + */ + +static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { + Py_ssize_t __pyx_r; + int __pyx_t_1; + + /* "View.MemoryView":1110 + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: # <<<<<<<<<<<<<< + * return -arg + * else: + */ + __pyx_t_1 = ((__pyx_v_arg < 0) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1111 + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: + * return -arg # <<<<<<<<<<<<<< + * else: + * return arg + */ + __pyx_r = (-__pyx_v_arg); + goto __pyx_L0; + + /* "View.MemoryView":1110 + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: # <<<<<<<<<<<<<< + * return -arg + * else: + */ + } + + /* "View.MemoryView":1113 + * return -arg + * else: + * return arg # <<<<<<<<<<<<<< + * + * @cname('__pyx_get_best_slice_order') + */ + /*else*/ { + __pyx_r = __pyx_v_arg; + goto __pyx_L0; + } + + /* "View.MemoryView":1109 + * + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< + * if arg < 0: + * return -arg + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1116 + * + * @cname('__pyx_get_best_slice_order') + * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< + * """ + * Figure out the best memory access order for a given slice. + */ + +static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim) { + int __pyx_v_i; + Py_ssize_t __pyx_v_c_stride; + Py_ssize_t __pyx_v_f_stride; + char __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_t_4; + + /* "View.MemoryView":1121 + * """ + * cdef int i + * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< + * cdef Py_ssize_t f_stride = 0 + * + */ + __pyx_v_c_stride = 0; + + /* "View.MemoryView":1122 + * cdef int i + * cdef Py_ssize_t c_stride = 0 + * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< + * + * for i in range(ndim - 1, -1, -1): + */ + __pyx_v_f_stride = 0; + + /* "View.MemoryView":1124 + * cdef Py_ssize_t f_stride = 0 + * + * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] + */ + for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { + __pyx_v_i = __pyx_t_1; + + /* "View.MemoryView":1125 + * + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * c_stride = mslice.strides[i] + * break + */ + __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1126 + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1127 + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] + * break # <<<<<<<<<<<<<< + * + * for i in range(ndim): + */ + goto __pyx_L4_break; + + /* "View.MemoryView":1125 + * + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * c_stride = mslice.strides[i] + * break + */ + } + } + __pyx_L4_break:; + + /* "View.MemoryView":1129 + * break + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] + */ + __pyx_t_1 = __pyx_v_ndim; + __pyx_t_3 = __pyx_t_1; + for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { + __pyx_v_i = __pyx_t_4; + + /* "View.MemoryView":1130 + * + * for i in range(ndim): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * f_stride = mslice.strides[i] + * break + */ + __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1131 + * for i in range(ndim): + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1132 + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] + * break # <<<<<<<<<<<<<< + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): + */ + goto __pyx_L7_break; + + /* "View.MemoryView":1130 + * + * for i in range(ndim): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * f_stride = mslice.strides[i] + * break + */ + } + } + __pyx_L7_break:; + + /* "View.MemoryView":1134 + * break + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< + * return 'C' + * else: + */ + __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1135 + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): + * return 'C' # <<<<<<<<<<<<<< + * else: + * return 'F' + */ + __pyx_r = 'C'; + goto __pyx_L0; + + /* "View.MemoryView":1134 + * break + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< + * return 'C' + * else: + */ + } + + /* "View.MemoryView":1137 + * return 'C' + * else: + * return 'F' # <<<<<<<<<<<<<< + * + * @cython.cdivision(True) + */ + /*else*/ { + __pyx_r = 'F'; + goto __pyx_L0; + } + + /* "View.MemoryView":1116 + * + * @cname('__pyx_get_best_slice_order') + * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< + * """ + * Figure out the best memory access order for a given slice. + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1140 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + +static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + CYTHON_UNUSED Py_ssize_t __pyx_v_i; + CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; + Py_ssize_t __pyx_v_dst_extent; + Py_ssize_t __pyx_v_src_stride; + Py_ssize_t __pyx_v_dst_stride; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + Py_ssize_t __pyx_t_4; + Py_ssize_t __pyx_t_5; + Py_ssize_t __pyx_t_6; + + /* "View.MemoryView":1147 + * + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + */ + __pyx_v_src_extent = (__pyx_v_src_shape[0]); + + /* "View.MemoryView":1148 + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] + */ + __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); + + /* "View.MemoryView":1149 + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + */ + __pyx_v_src_stride = (__pyx_v_src_strides[0]); + + /* "View.MemoryView":1150 + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< + * + * if ndim == 1: + */ + __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); + + /* "View.MemoryView":1152 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + + /* "View.MemoryView":1154 + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + */ + __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); + if (__pyx_t_2) { + __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); + } + __pyx_t_3 = (__pyx_t_2 != 0); + __pyx_t_1 = __pyx_t_3; + __pyx_L5_bool_binop_done:; + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + if (__pyx_t_1) { + + /* "View.MemoryView":1155 + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + goto __pyx_L4; + } + + /* "View.MemoryView":1157 + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + */ + /*else*/ { + __pyx_t_4 = __pyx_v_dst_extent; + __pyx_t_5 = __pyx_t_4; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1158 + * else: + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< + * src_data += src_stride + * dst_data += dst_stride + */ + (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize)); + + /* "View.MemoryView":1159 + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * else: + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1160 + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L4:; + + /* "View.MemoryView":1152 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1162 + * dst_data += dst_stride + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * _copy_strided_to_strided(src_data, src_strides + 1, + * dst_data, dst_strides + 1, + */ + /*else*/ { + __pyx_t_4 = __pyx_v_dst_extent; + __pyx_t_5 = __pyx_t_4; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1163 + * else: + * for i in range(dst_extent): + * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< + * dst_data, dst_strides + 1, + * src_shape + 1, dst_shape + 1, + */ + _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); + + /* "View.MemoryView":1167 + * src_shape + 1, dst_shape + 1, + * ndim - 1, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1168 + * ndim - 1, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L3:; + + /* "View.MemoryView":1140 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + + /* function exit code */ +} + +/* "View.MemoryView":1170 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + +static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + + /* "View.MemoryView":1173 + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< + * src.shape, dst.shape, ndim, itemsize) + * + */ + _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1170 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + + /* function exit code */ +} + +/* "View.MemoryView":1177 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + */ + +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { + Py_ssize_t __pyx_v_shape; + Py_ssize_t __pyx_v_size; + Py_ssize_t __pyx_r; + Py_ssize_t __pyx_t_1; + Py_ssize_t *__pyx_t_2; + Py_ssize_t *__pyx_t_3; + Py_ssize_t *__pyx_t_4; + + /* "View.MemoryView":1179 + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize # <<<<<<<<<<<<<< + * + * for shape in src.shape[:ndim]: + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; + __pyx_v_size = __pyx_t_1; + + /* "View.MemoryView":1181 + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + * + * for shape in src.shape[:ndim]: # <<<<<<<<<<<<<< + * size *= shape + * + */ + __pyx_t_3 = (__pyx_v_src->shape + __pyx_v_ndim); + for (__pyx_t_4 = __pyx_v_src->shape; __pyx_t_4 < __pyx_t_3; __pyx_t_4++) { + __pyx_t_2 = __pyx_t_4; + __pyx_v_shape = (__pyx_t_2[0]); + + /* "View.MemoryView":1182 + * + * for shape in src.shape[:ndim]: + * size *= shape # <<<<<<<<<<<<<< + * + * return size + */ + __pyx_v_size = (__pyx_v_size * __pyx_v_shape); + } + + /* "View.MemoryView":1184 + * size *= shape + * + * return size # <<<<<<<<<<<<<< + * + * @cname('__pyx_fill_contig_strides_array') + */ + __pyx_r = __pyx_v_size; + goto __pyx_L0; + + /* "View.MemoryView":1177 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1187 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { + int __pyx_v_idx; + Py_ssize_t __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_t_4; + + /* "View.MemoryView":1196 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + __pyx_t_1 = ((__pyx_v_order == 'F') != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1197 + * + * if order == 'F': + * for idx in range(ndim): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride *= shape[idx] + */ + __pyx_t_2 = __pyx_v_ndim; + __pyx_t_3 = __pyx_t_2; + for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { + __pyx_v_idx = __pyx_t_4; + + /* "View.MemoryView":1198 + * if order == 'F': + * for idx in range(ndim): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride *= shape[idx] + * else: + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1199 + * for idx in range(ndim): + * strides[idx] = stride + * stride *= shape[idx] # <<<<<<<<<<<<<< + * else: + * for idx in range(ndim - 1, -1, -1): + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + } + + /* "View.MemoryView":1196 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1201 + * stride *= shape[idx] + * else: + * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride *= shape[idx] + */ + 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PyObject *a, PyObject *k) { + struct __pyx_obj_9_splitter_Splitter *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_9_splitter_Splitter *)o); + p->__pyx_vtab = __pyx_vtabptr_9_splitter_Splitter; + p->criterion = ((struct __pyx_obj_10_criterion_Criterion *)Py_None); Py_INCREF(Py_None); + p->random_state = Py_None; Py_INCREF(Py_None); + p->y.data = NULL; + p->y.memview = NULL; + if (unlikely(__pyx_pw_9_splitter_8Splitter_1__cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_9_splitter_Splitter(PyObject *o) { + struct __pyx_obj_9_splitter_Splitter *p = (struct __pyx_obj_9_splitter_Splitter *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_pw_9_splitter_8Splitter_3__dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->criterion); + Py_CLEAR(p->random_state); + __PYX_XDEC_MEMVIEW(&p->y, 1); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_9_splitter_Splitter(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_obj_9_splitter_Splitter *p = (struct __pyx_obj_9_splitter_Splitter *)o; + if (p->criterion) { + e = (*v)(((PyObject *)p->criterion), a); if (e) return e; + } + if (p->random_state) { + e = (*v)(p->random_state, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_9_splitter_Splitter(PyObject *o) { + PyObject* tmp; + struct __pyx_obj_9_splitter_Splitter *p = (struct __pyx_obj_9_splitter_Splitter *)o; + tmp = ((PyObject*)p->criterion); + p->criterion = ((struct __pyx_obj_10_criterion_Criterion *)Py_None); Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->random_state); + p->random_state = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + return 0; +} + +static PyObject *__pyx_getprop_9_splitter_8Splitter_criterion(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_9_splitter_8Splitter_9criterion_1__get__(o); +} + +static int __pyx_setprop_9_splitter_8Splitter_criterion(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { + if (v) { + return __pyx_pw_9_splitter_8Splitter_9criterion_3__set__(o, v); + } + else { + return __pyx_pw_9_splitter_8Splitter_9criterion_5__del__(o); + } +} + +static PyObject *__pyx_getprop_9_splitter_8Splitter_max_features(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_9_splitter_8Splitter_12max_features_1__get__(o); +} + +static int __pyx_setprop_9_splitter_8Splitter_max_features(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { + if (v) { + return __pyx_pw_9_splitter_8Splitter_12max_features_3__set__(o, v); + } + else { + PyErr_SetString(PyExc_NotImplementedError, "__del__"); + return -1; + } +} + +static PyObject *__pyx_getprop_9_splitter_8Splitter_min_samples_leaf(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_9_splitter_8Splitter_16min_samples_leaf_1__get__(o); +} + +static int __pyx_setprop_9_splitter_8Splitter_min_samples_leaf(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { + if (v) { + return __pyx_pw_9_splitter_8Splitter_16min_samples_leaf_3__set__(o, v); + } + else { + PyErr_SetString(PyExc_NotImplementedError, "__del__"); + return -1; + } +} + +static PyObject *__pyx_getprop_9_splitter_8Splitter_min_weight_leaf(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_9_splitter_8Splitter_15min_weight_leaf_1__get__(o); +} + +static int __pyx_setprop_9_splitter_8Splitter_min_weight_leaf(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { + if (v) { + return __pyx_pw_9_splitter_8Splitter_15min_weight_leaf_3__set__(o, v); + } + else { + PyErr_SetString(PyExc_NotImplementedError, "__del__"); + return -1; + } +} + +static PyMethodDef __pyx_methods_9_splitter_Splitter[] = { + {"__getstate__", (PyCFunction)__pyx_pw_9_splitter_8Splitter_5__getstate__, METH_NOARGS, 0}, + {"__setstate__", (PyCFunction)__pyx_pw_9_splitter_8Splitter_7__setstate__, METH_O, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_9_splitter_8Splitter_9__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_9_splitter_8Splitter_11__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_9_splitter_Splitter[] = { + {(char *)"criterion", __pyx_getprop_9_splitter_8Splitter_criterion, __pyx_setprop_9_splitter_8Splitter_criterion, (char *)0, 0}, + {(char *)"max_features", __pyx_getprop_9_splitter_8Splitter_max_features, __pyx_setprop_9_splitter_8Splitter_max_features, (char *)0, 0}, + {(char *)"min_samples_leaf", __pyx_getprop_9_splitter_8Splitter_min_samples_leaf, __pyx_setprop_9_splitter_8Splitter_min_samples_leaf, (char *)0, 0}, + {(char *)"min_weight_leaf", __pyx_getprop_9_splitter_8Splitter_min_weight_leaf, __pyx_setprop_9_splitter_8Splitter_min_weight_leaf, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_9_splitter_Splitter = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter.Splitter", /*tp_name*/ + sizeof(struct __pyx_obj_9_splitter_Splitter), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_9_splitter_Splitter, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Abstract splitter class.\n\n Splitters are called by tree builders to find the best splits on both\n sparse and dense data, one split at a time.\n ", /*tp_doc*/ + __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_9_splitter_Splitter, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_9_splitter_Splitter, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_9_splitter_Splitter, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter __pyx_vtable_9_splitter_BaseDenseSplitter; + +static PyObject *__pyx_tp_new_9_splitter_BaseDenseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_9_splitter_BaseDenseSplitter *p; + PyObject *o = __pyx_tp_new_9_splitter_Splitter(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_9_splitter_BaseDenseSplitter *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_BaseDenseSplitter; + p->X.data = NULL; + p->X.memview = NULL; + return o; +} + +static void __pyx_tp_dealloc_9_splitter_BaseDenseSplitter(PyObject *o) { + struct __pyx_obj_9_splitter_BaseDenseSplitter *p = (struct __pyx_obj_9_splitter_BaseDenseSplitter *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + __PYX_XDEC_MEMVIEW(&p->X, 1); + PyObject_GC_Track(o); + __pyx_tp_dealloc_9_splitter_Splitter(o); +} + +static PyMethodDef __pyx_methods_9_splitter_BaseDenseSplitter[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_9_splitter_17BaseDenseSplitter_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_9_splitter_17BaseDenseSplitter_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_9_splitter_BaseDenseSplitter = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter.BaseDenseSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_9_splitter_BaseDenseSplitter), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_9_splitter_BaseDenseSplitter, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_9_splitter_BaseDenseSplitter, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_9_splitter_BaseDenseSplitter, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_9_splitter_BestSplitter __pyx_vtable_9_splitter_BestSplitter; + +static PyObject *__pyx_tp_new_9_splitter_BestSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_9_splitter_BestSplitter *p; + PyObject *o = __pyx_tp_new_9_splitter_BaseDenseSplitter(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_9_splitter_BestSplitter *)o); + p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_BestSplitter; + return o; +} + +static PyMethodDef __pyx_methods_9_splitter_BestSplitter[] = { + {"__reduce__", (PyCFunction)__pyx_pw_9_splitter_12BestSplitter_1__reduce__, METH_NOARGS, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_9_splitter_BestSplitter = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter.BestSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_9_splitter_BestSplitter), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_9_splitter_BaseDenseSplitter, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Splitter for finding the best split.", /*tp_doc*/ + __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_9_splitter_BestSplitter, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_9_splitter_BestSplitter, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_9_splitter_RandomSplitter __pyx_vtable_9_splitter_RandomSplitter; + +static PyObject *__pyx_tp_new_9_splitter_RandomSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_9_splitter_RandomSplitter *p; + PyObject *o = __pyx_tp_new_9_splitter_BaseDenseSplitter(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_9_splitter_RandomSplitter *)o); + p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_RandomSplitter; + return o; +} + +static PyMethodDef __pyx_methods_9_splitter_RandomSplitter[] = { + {"__reduce__", (PyCFunction)__pyx_pw_9_splitter_14RandomSplitter_1__reduce__, METH_NOARGS, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_9_splitter_RandomSplitter = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter.RandomSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_9_splitter_RandomSplitter), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_9_splitter_BaseDenseSplitter, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Splitter for finding the best random split.", /*tp_doc*/ + __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_9_splitter_RandomSplitter, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_9_splitter_RandomSplitter, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_9_splitter_BaseSparseSplitter __pyx_vtable_9_splitter_BaseSparseSplitter; + +static PyObject *__pyx_tp_new_9_splitter_BaseSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_9_splitter_BaseSparseSplitter *p; + PyObject *o = __pyx_tp_new_9_splitter_Splitter(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_9_splitter_BaseSparseSplitter *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_BaseSparseSplitter; + if (unlikely(__pyx_pw_9_splitter_18BaseSparseSplitter_1__cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_9_splitter_BaseSparseSplitter(PyObject *o) { + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_pw_9_splitter_18BaseSparseSplitter_3__dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + PyObject_GC_Track(o); + __pyx_tp_dealloc_9_splitter_Splitter(o); +} + +static PyMethodDef __pyx_methods_9_splitter_BaseSparseSplitter[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_9_splitter_18BaseSparseSplitter_5__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_9_splitter_18BaseSparseSplitter_7__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_9_splitter_BaseSparseSplitter = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter.BaseSparseSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_9_splitter_BaseSparseSplitter), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_9_splitter_BaseSparseSplitter, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_9_splitter_BaseSparseSplitter, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_9_splitter_BaseSparseSplitter, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_9_splitter_BestSparseSplitter __pyx_vtable_9_splitter_BestSparseSplitter; + +static PyObject *__pyx_tp_new_9_splitter_BestSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_9_splitter_BestSparseSplitter *p; + PyObject *o = __pyx_tp_new_9_splitter_BaseSparseSplitter(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_9_splitter_BestSparseSplitter *)o); + p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_BestSparseSplitter; + return o; +} + +static PyMethodDef __pyx_methods_9_splitter_BestSparseSplitter[] = { + {"__reduce__", (PyCFunction)__pyx_pw_9_splitter_18BestSparseSplitter_1__reduce__, METH_NOARGS, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_9_splitter_BestSparseSplitter = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter.BestSparseSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_9_splitter_BestSparseSplitter), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_9_splitter_BaseSparseSplitter, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Splitter for finding the best split, using the sparse data.", /*tp_doc*/ + __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_9_splitter_BestSparseSplitter, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_9_splitter_BestSparseSplitter, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_9_splitter_RandomSparseSplitter __pyx_vtable_9_splitter_RandomSparseSplitter; + +static PyObject *__pyx_tp_new_9_splitter_RandomSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_9_splitter_RandomSparseSplitter *p; + PyObject *o = __pyx_tp_new_9_splitter_BaseSparseSplitter(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_9_splitter_RandomSparseSplitter *)o); + p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_RandomSparseSplitter; + return o; +} + +static PyMethodDef __pyx_methods_9_splitter_RandomSparseSplitter[] = { + {"__reduce__", (PyCFunction)__pyx_pw_9_splitter_20RandomSparseSplitter_1__reduce__, METH_NOARGS, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_9_splitter_RandomSparseSplitter = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter.RandomSparseSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_9_splitter_RandomSparseSplitter), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_9_splitter_BaseSparseSplitter, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Splitter for finding a random split, using the sparse data.", /*tp_doc*/ + __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_9_splitter_RandomSparseSplitter, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_9_splitter_RandomSparseSplitter, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_array __pyx_vtable_array; + +static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_array_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_array_obj *)o); + p->__pyx_vtab = __pyx_vtabptr_array; + p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None); + p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None); + if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_array(PyObject *o) { + struct __pyx_array_obj *p = (struct __pyx_array_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_array___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->mode); + Py_CLEAR(p->_format); + (*Py_TYPE(o)->tp_free)(o); +} +static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_array___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) { + PyObject *v = __Pyx_PyObject_GenericGetAttr(o, n); + if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Clear(); + v = __pyx_array___getattr__(o, n); + } + return v; +} + +static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_5array_7memview_1__get__(o); +} + +static PyMethodDef __pyx_methods_array[] = { + {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_array_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_array_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_array[] = { + {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_array = { + __pyx_array___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_array, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_array = { + __pyx_array___len__, /*mp_length*/ + __pyx_array___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_array = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_array_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_array = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter.array", /*tp_name*/ + sizeof(struct __pyx_array_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_array, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_array, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_array, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + __pyx_tp_getattro_array, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_array, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + 0, /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_array, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_array, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_array, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; + +static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + struct __pyx_MemviewEnum_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_MemviewEnum_obj *)o); + p->name = Py_None; Py_INCREF(Py_None); + return o; +} + +static void __pyx_tp_dealloc_Enum(PyObject *o) { + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + Py_CLEAR(p->name); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + if (p->name) { + e = (*v)(p->name, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_Enum(PyObject *o) { + PyObject* tmp; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + tmp = ((PyObject*)p->name); + p->name = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + return 0; +} + +static PyMethodDef __pyx_methods_Enum[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_MemviewEnum = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter.Enum", /*tp_name*/ + sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_Enum, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + __pyx_MemviewEnum___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_Enum, /*tp_traverse*/ + __pyx_tp_clear_Enum, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_Enum, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + __pyx_MemviewEnum___init__, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_Enum, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview; + +static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryview_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryview_obj *)o); + p->__pyx_vtab = __pyx_vtabptr_memoryview; + p->obj = Py_None; Py_INCREF(Py_None); + p->_size = Py_None; Py_INCREF(Py_None); + p->_array_interface = Py_None; Py_INCREF(Py_None); + p->view.obj = NULL; + if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_memoryview(PyObject *o) { + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_memoryview___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->obj); + Py_CLEAR(p->_size); + Py_CLEAR(p->_array_interface); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + if (p->obj) { + e = (*v)(p->obj, a); if (e) return e; + } + if (p->_size) { + e = (*v)(p->_size, a); if (e) return e; + } + if (p->_array_interface) { + e = (*v)(p->_array_interface, a); if (e) return e; + } + if (p->view.obj) { + e = (*v)(p->view.obj, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_memoryview(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + tmp = ((PyObject*)p->obj); + p->obj = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_size); + p->_size = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_array_interface); + p->_array_interface = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + Py_CLEAR(p->view.obj); + return 0; +} +static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_memoryview___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_1T_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4base_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_5shape_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_7strides_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_10suboffsets_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4ndim_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_8itemsize_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_6nbytes_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4size_1__get__(o); +} + +static PyMethodDef __pyx_methods_memoryview[] = { + {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0}, + {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0}, + {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0}, + {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_memoryview[] = { + {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, (char *)0, 0}, + {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, (char *)0, 0}, + {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, (char *)0, 0}, + {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, (char *)0, 0}, + {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, (char *)0, 0}, + {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, (char *)0, 0}, + {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, (char *)0, 0}, + {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, (char *)0, 0}, + {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_memoryview = { + __pyx_memoryview___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_memoryview, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_memoryview = { + __pyx_memoryview___len__, /*mp_length*/ + __pyx_memoryview___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_memoryview = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_memoryview_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_memoryview = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter.memoryview", /*tp_name*/ + sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_memoryview, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + __pyx_memoryview___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + __pyx_memoryview___str__, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_memoryview, /*tp_traverse*/ + __pyx_tp_clear_memoryview, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_memoryview, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_memoryview, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_memoryview, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice; + +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryviewslice_obj *p; + PyObject *o = __pyx_tp_new_memoryview(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryviewslice_obj *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice; + p->from_object = Py_None; Py_INCREF(Py_None); + p->from_slice.memview = NULL; + return o; +} + +static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) { + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_memoryviewslice___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->from_object); + PyObject_GC_Track(o); + __pyx_tp_dealloc_memoryview(o); +} + +static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e; + if (p->from_object) { + e = (*v)(p->from_object, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear__memoryviewslice(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + __pyx_tp_clear_memoryview(o); + tmp = ((PyObject*)p->from_object); + p->from_object = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + __PYX_XDEC_MEMVIEW(&p->from_slice, 1); + return 0; +} + +static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_16_memoryviewslice_4base_1__get__(o); +} + +static PyMethodDef __pyx_methods__memoryviewslice[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = { + {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_memoryviewslice = { + PyVarObject_HEAD_INIT(0, 0) + "_splitter._memoryviewslice", /*tp_name*/ + sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___repr__, /*tp_repr*/ + #else + 0, /*tp_repr*/ + #endif + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___str__, /*tp_str*/ + #else + 0, /*tp_str*/ + #endif + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Internal class for passing memoryview slices to Python", /*tp_doc*/ + __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/ + __pyx_tp_clear__memoryviewslice, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods__memoryviewslice, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets__memoryviewslice, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new__memoryviewslice, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; + +static PyMethodDef __pyx_methods[] = { + {0, 0, 0, 0} +}; + +#if PY_MAJOR_VERSION >= 3 +#if CYTHON_PEP489_MULTI_PHASE_INIT +static PyObject* __pyx_pymod_create(PyObject *spec, PyModuleDef *def); /*proto*/ +static int __pyx_pymod_exec__splitter(PyObject* module); /*proto*/ +static PyModuleDef_Slot __pyx_moduledef_slots[] = { + {Py_mod_create, (void*)__pyx_pymod_create}, + {Py_mod_exec, (void*)__pyx_pymod_exec__splitter}, + {0, NULL} +}; +#endif + +static struct PyModuleDef __pyx_moduledef = { + PyModuleDef_HEAD_INIT, + "_splitter", + 0, /* m_doc */ + #if CYTHON_PEP489_MULTI_PHASE_INIT + 0, /* m_size */ + #else + -1, /* m_size */ + #endif + __pyx_methods /* m_methods */, + #if CYTHON_PEP489_MULTI_PHASE_INIT + __pyx_moduledef_slots, /* m_slots */ + #else + NULL, /* m_reload */ + #endif + NULL, /* m_traverse */ + NULL, /* m_clear */ + NULL /* m_free */ +}; +#endif +#ifndef 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+ #else + return; + #endif +} + +/* --- Runtime support code --- */ +/* Refnanny */ +#if CYTHON_REFNANNY +static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) { + PyObject *m = NULL, *p = NULL; + void *r = NULL; + m = PyImport_ImportModule(modname); + if (!m) goto end; + p = PyObject_GetAttrString(m, "RefNannyAPI"); + if (!p) goto end; + r = PyLong_AsVoidPtr(p); +end: + Py_XDECREF(p); + Py_XDECREF(m); + return (__Pyx_RefNannyAPIStruct *)r; +} +#endif + +/* PyObjectGetAttrStr */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) { + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro)) + return tp->tp_getattro(obj, attr_name); +#if PY_MAJOR_VERSION < 3 + if (likely(tp->tp_getattr)) + return tp->tp_getattr(obj, PyString_AS_STRING(attr_name)); +#endif + return PyObject_GetAttr(obj, attr_name); +} +#endif + +/* GetBuiltinName */ +static PyObject *__Pyx_GetBuiltinName(PyObject *name) { + PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name); + if (unlikely(!result)) { + PyErr_Format(PyExc_NameError, +#if PY_MAJOR_VERSION >= 3 + "name '%U' is not defined", name); +#else + "name '%.200s' is not defined", PyString_AS_STRING(name)); +#endif + } + return result; +} + +/* RaiseArgTupleInvalid */ +static void __Pyx_RaiseArgtupleInvalid( + const char* func_name, + int exact, + Py_ssize_t num_min, + Py_ssize_t num_max, + Py_ssize_t num_found) +{ + Py_ssize_t num_expected; + const char *more_or_less; + if (num_found < num_min) { + num_expected = num_min; + more_or_less = "at least"; + } else { + num_expected = num_max; + more_or_less = "at most"; + } + if (exact) { + more_or_less = "exactly"; + } + PyErr_Format(PyExc_TypeError, + "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", + func_name, more_or_less, num_expected, + (num_expected == 1) ? "" : "s", num_found); +} + +/* RaiseDoubleKeywords */ +static void __Pyx_RaiseDoubleKeywordsError( + const char* func_name, + PyObject* kw_name) +{ + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION >= 3 + "%s() got multiple values for keyword argument '%U'", func_name, kw_name); + #else + "%s() got multiple values for keyword argument '%s'", func_name, + PyString_AsString(kw_name)); + #endif +} + +/* ParseKeywords */ +static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + continue; + } + name = first_kw_arg; + #if PY_MAJOR_VERSION < 3 + if (likely(PyString_Check(key))) { + while (*name) { + if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) + && _PyString_Eq(**name, key)) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + if ((**argname == key) || ( + (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) + && _PyString_Eq(**argname, key))) { + goto arg_passed_twice; + } + argname++; + } + } + } else + #endif + if (likely(PyUnicode_Check(key))) { + while (*name) { + int cmp = (**name == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**name, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + int cmp = (**argname == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**argname, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) goto arg_passed_twice; + argname++; + } + } + } else + goto invalid_keyword_type; + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, key); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%.200s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%.200s() got an unexpected keyword argument '%.200s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +/* ArgTypeTest */ +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) +{ + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + else if (exact) { + #if PY_MAJOR_VERSION == 2 + if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; + #endif + } + else { + if (likely(__Pyx_TypeCheck(obj, type))) return 1; + } + PyErr_Format(PyExc_TypeError, + "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); + return 0; +} + +/* PyFunctionFastCall */ +#if CYTHON_FAST_PYCALL +static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, + PyObject *globals) { + PyFrameObject *f; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject **fastlocals; + Py_ssize_t i; + PyObject *result; + assert(globals != NULL); + /* XXX Perhaps we should create a specialized + PyFrame_New() that doesn't take locals, but does + take builtins without sanity checking them. + */ + assert(tstate != NULL); + f = PyFrame_New(tstate, co, globals, NULL); + if (f == NULL) { + return NULL; + } + fastlocals = __Pyx_PyFrame_GetLocalsplus(f); + for (i = 0; i < na; i++) { + Py_INCREF(*args); + fastlocals[i] = *args++; + } + result = PyEval_EvalFrameEx(f,0); + ++tstate->recursion_depth; + Py_DECREF(f); + --tstate->recursion_depth; + return result; +} +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { + PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); + PyObject *globals = PyFunction_GET_GLOBALS(func); + PyObject *argdefs = PyFunction_GET_DEFAULTS(func); + PyObject *closure; +#if PY_MAJOR_VERSION >= 3 + PyObject *kwdefs; +#endif + PyObject *kwtuple, **k; + PyObject **d; + Py_ssize_t nd; + Py_ssize_t nk; + PyObject *result; + assert(kwargs == NULL || PyDict_Check(kwargs)); + nk = kwargs ? PyDict_Size(kwargs) : 0; + if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { + return NULL; + } + if ( +#if PY_MAJOR_VERSION >= 3 + co->co_kwonlyargcount == 0 && +#endif + likely(kwargs == NULL || nk == 0) && + co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { + if (argdefs == NULL && co->co_argcount == nargs) { + result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); + goto done; + } + else if (nargs == 0 && argdefs != NULL + && co->co_argcount == Py_SIZE(argdefs)) { + /* function called with no arguments, but all parameters have + a default value: use default values as arguments .*/ + args = &PyTuple_GET_ITEM(argdefs, 0); + result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); + goto done; + } + } + if (kwargs != NULL) { + Py_ssize_t pos, i; + kwtuple = PyTuple_New(2 * nk); + if (kwtuple == NULL) { + result = NULL; + goto done; + } + k = &PyTuple_GET_ITEM(kwtuple, 0); + pos = i = 0; + while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { + Py_INCREF(k[i]); + Py_INCREF(k[i+1]); + i += 2; + } + nk = i / 2; + } + else { + kwtuple = NULL; + k = NULL; + } + closure = PyFunction_GET_CLOSURE(func); +#if PY_MAJOR_VERSION >= 3 + kwdefs = PyFunction_GET_KW_DEFAULTS(func); +#endif + if (argdefs != NULL) { + d = &PyTuple_GET_ITEM(argdefs, 0); + nd = Py_SIZE(argdefs); + } + else { + d = NULL; + nd = 0; + } +#if PY_MAJOR_VERSION >= 3 + result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, kwdefs, closure); +#else + result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, closure); +#endif + Py_XDECREF(kwtuple); +done: + Py_LeaveRecursiveCall(); + return result; +} +#endif +#endif + +/* PyCFunctionFastCall */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { + PyCFunctionObject *func = (PyCFunctionObject*)func_obj; + PyCFunction meth = PyCFunction_GET_FUNCTION(func); + PyObject *self = PyCFunction_GET_SELF(func); + int flags = PyCFunction_GET_FLAGS(func); + assert(PyCFunction_Check(func)); + assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); + assert(nargs >= 0); + assert(nargs == 0 || args != NULL); + /* _PyCFunction_FastCallDict() must not be called with an exception set, + because it may clear it (directly or indirectly) and so the + caller loses its exception */ + assert(!PyErr_Occurred()); + if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { + return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); + } else { + return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); + } +} +#endif + +/* PyObjectCall */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { + PyObject *result; + ternaryfunc call = func->ob_type->tp_call; + if (unlikely(!call)) + return PyObject_Call(func, arg, kw); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = (*call)(func, arg, kw); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* GetItemInt */ +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { + PyObject *r; + if (!j) return NULL; + r = PyObject_GetItem(o, j); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyList_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { + PyObject *r = PyList_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyTuple_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); + if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { + PyObject *r = PyList_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } + else if (PyTuple_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + return NULL; + PyErr_Clear(); + } + } + return m->sq_item(o, i); + } + } +#else + if (is_list || PySequence_Check(o)) { + return PySequence_GetItem(o, i); + } +#endif + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +} + +/* MemviewSliceInit */ +static int +__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference) +{ + __Pyx_RefNannyDeclarations + int i, retval=-1; + Py_buffer *buf = &memview->view; + __Pyx_RefNannySetupContext("init_memviewslice", 0); + if (unlikely(memviewslice->memview || memviewslice->data)) { + PyErr_SetString(PyExc_ValueError, + "memviewslice is already initialized!"); + goto fail; + } + if (buf->strides) { + for (i = 0; i < ndim; i++) { + memviewslice->strides[i] = buf->strides[i]; + } + } else { + Py_ssize_t stride = buf->itemsize; + for (i = ndim - 1; i >= 0; i--) { + memviewslice->strides[i] = stride; + stride *= buf->shape[i]; + } + } + for (i = 0; i < ndim; i++) { + memviewslice->shape[i] = buf->shape[i]; + if (buf->suboffsets) { + memviewslice->suboffsets[i] = buf->suboffsets[i]; + } else { + memviewslice->suboffsets[i] = -1; + } + } + memviewslice->memview = memview; + memviewslice->data = (char *)buf->buf; + if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { + Py_INCREF(memview); + } + retval = 0; + goto no_fail; +fail: + memviewslice->memview = 0; + memviewslice->data = 0; + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} +#ifndef Py_NO_RETURN +#define Py_NO_RETURN +#endif +static void __pyx_fatalerror(const char *fmt, ...) Py_NO_RETURN { + va_list vargs; + char msg[200]; +#ifdef HAVE_STDARG_PROTOTYPES + va_start(vargs, fmt); +#else + va_start(vargs); +#endif + vsnprintf(msg, 200, fmt, vargs); + va_end(vargs); + Py_FatalError(msg); +} +static CYTHON_INLINE int +__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)++; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE int +__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)--; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE void +__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) +{ + int first_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (unlikely(!memview || (PyObject *) memview == Py_None)) + return; + if (unlikely(__pyx_get_slice_count(memview) < 0)) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + first_time = __pyx_add_acquisition_count(memview) == 0; + if (unlikely(first_time)) { + if (have_gil) { + Py_INCREF((PyObject *) memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_INCREF((PyObject *) memview); + PyGILState_Release(_gilstate); + } + } +} +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, + int have_gil, int lineno) { + int last_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (unlikely(!memview || (PyObject *) memview == Py_None)) { + memslice->memview = NULL; + return; + } + if (unlikely(__pyx_get_slice_count(memview) <= 0)) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + last_time = __pyx_sub_acquisition_count(memview) == 1; + memslice->data = NULL; + if (unlikely(last_time)) { + if (have_gil) { + Py_CLEAR(memslice->memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_CLEAR(memslice->memview); + PyGILState_Release(_gilstate); + } + } else { + memslice->memview = NULL; + } +} + +/* ExtTypeTest */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +/* PyErrFetchRestore */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} +#endif + +/* RaiseException */ +#if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + __Pyx_PyThreadState_declare + Py_XINCREF(type); + if (!value || value == Py_None) + value = NULL; + else + Py_INCREF(value); + if (!tb || tb == Py_None) + tb = NULL; + else { + Py_INCREF(tb); + if (!PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + } + if (PyType_Check(type)) { +#if CYTHON_COMPILING_IN_PYPY + if (!value) { + Py_INCREF(Py_None); + value = Py_None; + } +#endif + PyErr_NormalizeException(&type, &value, &tb); + } else { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + value = type; + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + } + __Pyx_PyThreadState_assign + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + PyObject* owned_instance = NULL; + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (PyExceptionClass_Check(type)) { + PyObject *instance_class = NULL; + if (value && PyExceptionInstance_Check(value)) { + instance_class = (PyObject*) Py_TYPE(value); + if (instance_class != type) { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { + instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; + } + } + } + if (!instance_class) { + PyObject *args; + if (!value) + args = PyTuple_New(0); + else if (PyTuple_Check(value)) { + Py_INCREF(value); + args = value; + } else + args = PyTuple_Pack(1, value); + if (!args) + goto bad; + owned_instance = PyObject_Call(type, args, NULL); + Py_DECREF(args); + if (!owned_instance) + goto bad; + value = owned_instance; + if (!PyExceptionInstance_Check(value)) { + PyErr_Format(PyExc_TypeError, + "calling %R should have returned an instance of " + "BaseException, not %R", + type, Py_TYPE(value)); + goto bad; + } + } + } else { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + if (cause == Py_None) { + fixed_cause = NULL; + } else if (PyExceptionClass_Check(cause)) { + fixed_cause = PyObject_CallObject(cause, NULL); + if (fixed_cause == NULL) + goto bad; + } else if (PyExceptionInstance_Check(cause)) { + fixed_cause = cause; + Py_INCREF(fixed_cause); + } else { + PyErr_SetString(PyExc_TypeError, + "exception causes must derive from " + "BaseException"); + goto bad; + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } +#endif + } +bad: + Py_XDECREF(owned_instance); + return; +} +#endif + +/* PyObjectCallMethO */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallNoArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, NULL, 0); + } +#endif +#ifdef __Pyx_CyFunction_USED + if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) +#else + if (likely(PyCFunction_Check(func))) +#endif + { + if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { + return __Pyx_PyObject_CallMethO(func, NULL); + } + } + return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); +} +#endif + +/* PyObjectCallOneArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, &arg, 1); + } +#endif + if (likely(PyCFunction_Check(func))) { + if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { + return __Pyx_PyObject_CallMethO(func, arg); +#if CYTHON_FAST_PYCCALL + } else if (__Pyx_PyFastCFunction_Check(func)) { + return __Pyx_PyCFunction_FastCall(func, &arg, 1); +#endif + } + } + return __Pyx__PyObject_CallOneArg(func, arg); +} +#else +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_Pack(1, arg); + if (unlikely(!args)) return NULL; + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +#endif + +/* PyDictVersioning */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + +/* GetModuleGlobalName */ +#if CYTHON_USE_DICT_VERSIONS +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) +#else +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) +#endif +{ + PyObject *result; +#if !CYTHON_AVOID_BORROWED_REFS +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 + result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } else if (unlikely(PyErr_Occurred())) { + return NULL; + } +#else + result = PyDict_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } +#endif +#else + result = PyObject_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } + PyErr_Clear(); +#endif + return __Pyx_GetBuiltinName(name); +} + +/* IsLittleEndian */ +static CYTHON_INLINE int __Pyx_Is_Little_Endian(void) +{ + union { + uint32_t u32; + uint8_t u8[4]; + } S; + S.u32 = 0x01020304; + return S.u8[0] == 4; +} + +/* BufferFormatCheck */ +static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type) { + stack[0].field = &ctx->root; + stack[0].parent_offset = 0; + ctx->root.type = type; + ctx->root.name = "buffer dtype"; + ctx->root.offset = 0; + ctx->head = stack; + ctx->head->field = &ctx->root; + ctx->fmt_offset = 0; + ctx->head->parent_offset = 0; + ctx->new_packmode = '@'; + ctx->enc_packmode = '@'; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->is_complex = 0; + ctx->is_valid_array = 0; + ctx->struct_alignment = 0; + while (type->typegroup == 'S') { + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = 0; + type = type->fields->type; + } +} +static int __Pyx_BufFmt_ParseNumber(const char** ts) { + int count; + const char* t = *ts; + if (*t < '0' || *t > '9') { + return -1; + } else { + count = *t++ - '0'; + while (*t >= '0' && *t <= '9') { + count *= 10; + count += *t++ - '0'; + } + } + *ts = t; + return count; +} +static int __Pyx_BufFmt_ExpectNumber(const char **ts) { + int number = __Pyx_BufFmt_ParseNumber(ts); + if (number == -1) + PyErr_Format(PyExc_ValueError,\ + "Does not understand character buffer dtype format string ('%c')", **ts); + return number; +} +static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { + PyErr_Format(PyExc_ValueError, + "Unexpected format string character: '%c'", ch); +} +static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { + switch (ch) { + case '?': return "'bool'"; + case 'c': return "'char'"; + case 'b': return "'signed char'"; + case 'B': return "'unsigned char'"; + case 'h': return "'short'"; + case 'H': return "'unsigned short'"; + case 'i': return "'int'"; + case 'I': return "'unsigned int'"; + case 'l': return "'long'"; + case 'L': return "'unsigned long'"; + case 'q': return "'long long'"; + case 'Q': return "'unsigned long long'"; + case 'f': return (is_complex ? "'complex float'" : "'float'"); + case 'd': return (is_complex ? "'complex double'" : "'double'"); + case 'g': return (is_complex ? "'complex long double'" : "'long double'"); + case 'T': return "a struct"; + case 'O': return "Python object"; + case 'P': return "a pointer"; + case 's': case 'p': return "a string"; + case 0: return "end"; + default: return "unparseable format string"; + } +} +static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return 2; + case 'i': case 'I': case 'l': case 'L': return 4; + case 'q': case 'Q': return 8; + case 'f': return (is_complex ? 8 : 4); + case 'd': return (is_complex ? 16 : 8); + case 'g': { + PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); + return 0; + } + case 'O': case 'P': return sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(short); + case 'i': case 'I': return sizeof(int); + case 'l': case 'L': return sizeof(long); + #ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(PY_LONG_LONG); + #endif + case 'f': return sizeof(float) * (is_complex ? 2 : 1); + case 'd': return sizeof(double) * (is_complex ? 2 : 1); + case 'g': return sizeof(long double) * (is_complex ? 2 : 1); + case 'O': case 'P': return sizeof(void*); + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +typedef struct { char c; short x; } __Pyx_st_short; +typedef struct { char c; int x; } __Pyx_st_int; +typedef struct { char c; long x; } __Pyx_st_long; +typedef struct { char c; float x; } __Pyx_st_float; +typedef struct { char c; double x; } __Pyx_st_double; +typedef struct { char c; long double x; } __Pyx_st_longdouble; +typedef struct { char c; void *x; } __Pyx_st_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_st_float) - sizeof(float); + case 'd': return sizeof(__Pyx_st_double) - sizeof(double); + case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +/* These are for computing the padding at the end of the struct to align + on the first member of the struct. This will probably the same as above, + but we don't have any guarantees. + */ +typedef struct { short x; char c; } __Pyx_pad_short; +typedef struct { int x; char c; } __Pyx_pad_int; +typedef struct { long x; char c; } __Pyx_pad_long; +typedef struct { float x; char c; } __Pyx_pad_float; +typedef struct { double x; char c; } __Pyx_pad_double; +typedef struct { long double x; char c; } __Pyx_pad_longdouble; +typedef struct { void *x; char c; } __Pyx_pad_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); + case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); + case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { + switch (ch) { + case 'c': + return 'H'; + case 'b': case 'h': case 'i': + case 'l': case 'q': case 's': case 'p': + return 'I'; + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': + return 'U'; + case 'f': case 'd': case 'g': + return (is_complex ? 'C' : 'R'); + case 'O': + return 'O'; + case 'P': + return 'P'; + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { + if (ctx->head == NULL || ctx->head->field == &ctx->root) { + const char* expected; + const char* quote; + if (ctx->head == NULL) { + expected = "end"; + quote = ""; + } else { + expected = ctx->head->field->type->name; + quote = "'"; + } + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected %s%s%s but got %s", + quote, expected, quote, + __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); + } else { + __Pyx_StructField* field = ctx->head->field; + __Pyx_StructField* parent = (ctx->head - 1)->field; + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", + field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), + parent->type->name, field->name); + } +} +static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { + char group; + size_t size, offset, arraysize = 1; + if (ctx->enc_type == 0) return 0; + if (ctx->head->field->type->arraysize[0]) { + int i, ndim = 0; + if (ctx->enc_type == 's' || ctx->enc_type == 'p') { + ctx->is_valid_array = ctx->head->field->type->ndim == 1; + ndim = 1; + if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { + PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %zu", + ctx->head->field->type->arraysize[0], ctx->enc_count); + return -1; + } + } + if (!ctx->is_valid_array) { + PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", + ctx->head->field->type->ndim, ndim); + return -1; + } + for (i = 0; i < ctx->head->field->type->ndim; i++) { + arraysize *= ctx->head->field->type->arraysize[i]; + } + ctx->is_valid_array = 0; + ctx->enc_count = 1; + } + group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); + do { + __Pyx_StructField* field = ctx->head->field; + __Pyx_TypeInfo* type = field->type; + if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { + size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); + } else { + size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); + } + if (ctx->enc_packmode == '@') { + size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); + size_t align_mod_offset; + if (align_at == 0) return -1; + align_mod_offset = ctx->fmt_offset % align_at; + if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; + if (ctx->struct_alignment == 0) + ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, + ctx->is_complex); + } + if (type->size != size || type->typegroup != group) { + if (type->typegroup == 'C' && type->fields != NULL) { + size_t parent_offset = ctx->head->parent_offset + field->offset; + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = parent_offset; + continue; + } + if ((type->typegroup == 'H' || group == 'H') && type->size == size) { + } else { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + } + offset = ctx->head->parent_offset + field->offset; + if (ctx->fmt_offset != offset) { + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", + (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); + return -1; + } + ctx->fmt_offset += size; + if (arraysize) + ctx->fmt_offset += (arraysize - 1) * size; + --ctx->enc_count; + while (1) { + if (field == &ctx->root) { + ctx->head = NULL; + if (ctx->enc_count != 0) { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + break; + } + ctx->head->field = ++field; + if (field->type == NULL) { + --ctx->head; + field = ctx->head->field; + continue; + } else if (field->type->typegroup == 'S') { + size_t parent_offset = ctx->head->parent_offset + field->offset; + if (field->type->fields->type == NULL) continue; + field = field->type->fields; + ++ctx->head; + ctx->head->field = field; + ctx->head->parent_offset = parent_offset; + break; + } else { + break; + } + } + } while (ctx->enc_count); + ctx->enc_type = 0; + ctx->is_complex = 0; + return 0; +} +static PyObject * +__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) +{ + const char *ts = *tsp; + int i = 0, number, ndim; + ++ts; + if (ctx->new_count != 1) { + PyErr_SetString(PyExc_ValueError, + "Cannot handle repeated arrays in format string"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; + while (*ts && *ts != ')') { + switch (*ts) { + case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; + default: break; + } + number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) + return PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %d", + ctx->head->field->type->arraysize[i], number); + if (*ts != ',' && *ts != ')') + return PyErr_Format(PyExc_ValueError, + "Expected a comma in format string, got '%c'", *ts); + if (*ts == ',') ts++; + i++; + } + if (i != ndim) + return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", + ctx->head->field->type->ndim, i); + if (!*ts) { + PyErr_SetString(PyExc_ValueError, + "Unexpected end of format string, expected ')'"); + return NULL; + } + ctx->is_valid_array = 1; + ctx->new_count = 1; + *tsp = ++ts; + return Py_None; +} +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { + int got_Z = 0; + while (1) { + switch(*ts) { + case 0: + if (ctx->enc_type != 0 && ctx->head == NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + if (ctx->head != NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + return ts; + case ' ': + case '\r': + case '\n': + ++ts; + break; + case '<': + if (!__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '>': + case '!': + if (__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '=': + case '@': + case '^': + ctx->new_packmode = *ts++; + break; + case 'T': + { + const char* ts_after_sub; + size_t i, struct_count = ctx->new_count; + size_t struct_alignment = ctx->struct_alignment; + ctx->new_count = 1; + ++ts; + if (*ts != '{') { + PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + ctx->enc_count = 0; + ctx->struct_alignment = 0; + ++ts; + ts_after_sub = ts; + for (i = 0; i != struct_count; ++i) { + ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); + if (!ts_after_sub) return NULL; + } + ts = ts_after_sub; + if (struct_alignment) ctx->struct_alignment = struct_alignment; + } + break; + case '}': + { + size_t alignment = ctx->struct_alignment; + ++ts; + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + if (alignment && ctx->fmt_offset % alignment) { + ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); + } + } + return ts; + case 'x': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->fmt_offset += ctx->new_count; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->enc_packmode = ctx->new_packmode; + ++ts; + break; + case 'Z': + got_Z = 1; + ++ts; + if (*ts != 'f' && *ts != 'd' && *ts != 'g') { + __Pyx_BufFmt_RaiseUnexpectedChar('Z'); + return NULL; + } + CYTHON_FALLTHROUGH; + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case 'l': case 'L': case 'q': case 'Q': + case 'f': case 'd': case 'g': + case 'O': case 'p': + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { + ctx->enc_count += ctx->new_count; + ctx->new_count = 1; + got_Z = 0; + ++ts; + break; + } + CYTHON_FALLTHROUGH; + case 's': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_count = ctx->new_count; + ctx->enc_packmode = ctx->new_packmode; + ctx->enc_type = *ts; + ctx->is_complex = got_Z; + ++ts; + ctx->new_count = 1; + got_Z = 0; + break; + case ':': + ++ts; + while(*ts != ':') ++ts; + ++ts; + break; + case '(': + if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; + break; + default: + { + int number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + ctx->new_count = (size_t)number; + } + } + } +} + +/* BufferGetAndValidate */ + static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { + if (unlikely(info->buf == NULL)) return; + if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; + __Pyx_ReleaseBuffer(info); +} +static void __Pyx_ZeroBuffer(Py_buffer* buf) { + buf->buf = NULL; + buf->obj = NULL; + buf->strides = __Pyx_zeros; + buf->shape = __Pyx_zeros; + buf->suboffsets = __Pyx_minusones; +} +static int __Pyx__GetBufferAndValidate( + Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, + int nd, int cast, __Pyx_BufFmt_StackElem* stack) +{ + buf->buf = NULL; + if (unlikely(__Pyx_GetBuffer(obj, buf, flags) == -1)) { + __Pyx_ZeroBuffer(buf); + return -1; + } + if (unlikely(buf->ndim != nd)) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + nd, buf->ndim); + goto fail; + } + if (!cast) { + __Pyx_BufFmt_Context ctx; + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + } + if (unlikely((size_t)buf->itemsize != dtype->size)) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", + buf->itemsize, (buf->itemsize > 1) ? "s" : "", + dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); + goto fail; + } + if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; + return 0; +fail:; + __Pyx_SafeReleaseBuffer(buf); + return -1; +} + +/* GetTopmostException */ + #if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +/* PyObjectCall2Args */ + static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { + PyObject *args, *result = NULL; + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyFunction_FastCall(function, args, 2); + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyCFunction_FastCall(function, args, 2); + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(arg1); + PyTuple_SET_ITEM(args, 0, arg1); + Py_INCREF(arg2); + PyTuple_SET_ITEM(args, 1, arg2); + Py_INCREF(function); + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); +done: + return result; +} + +/* BytesEquals */ + static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else + if (s1 == s2) { + return (equals == Py_EQ); + } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { + const char *ps1, *ps2; + Py_ssize_t length = PyBytes_GET_SIZE(s1); + if (length != PyBytes_GET_SIZE(s2)) + return (equals == Py_NE); + ps1 = PyBytes_AS_STRING(s1); + ps2 = PyBytes_AS_STRING(s2); + if (ps1[0] != ps2[0]) { + return (equals == Py_NE); + } else if (length == 1) { + return (equals == Py_EQ); + } else { + int result; +#if CYTHON_USE_UNICODE_INTERNALS + Py_hash_t hash1, hash2; + hash1 = ((PyBytesObject*)s1)->ob_shash; + hash2 = ((PyBytesObject*)s2)->ob_shash; + if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { + return (equals == Py_NE); + } +#endif + result = memcmp(ps1, ps2, (size_t)length); + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { + return (equals == Py_NE); + } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { + return (equals == Py_NE); + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +#endif +} + +/* UnicodeEquals */ + static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else +#if PY_MAJOR_VERSION < 3 + PyObject* owned_ref = NULL; +#endif + int s1_is_unicode, s2_is_unicode; + if (s1 == s2) { + goto return_eq; + } + s1_is_unicode = PyUnicode_CheckExact(s1); + s2_is_unicode = PyUnicode_CheckExact(s2); +#if PY_MAJOR_VERSION < 3 + if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { + owned_ref = PyUnicode_FromObject(s2); + if (unlikely(!owned_ref)) + return -1; + s2 = owned_ref; + s2_is_unicode = 1; + } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { + owned_ref = PyUnicode_FromObject(s1); + if (unlikely(!owned_ref)) + return -1; + s1 = owned_ref; + s1_is_unicode = 1; + } else if (((!s2_is_unicode) & (!s1_is_unicode))) { + return __Pyx_PyBytes_Equals(s1, s2, equals); + } +#endif + if (s1_is_unicode & s2_is_unicode) { + Py_ssize_t length; + int kind; + void *data1, *data2; + if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) + return -1; + length = __Pyx_PyUnicode_GET_LENGTH(s1); + if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { + goto return_ne; + } +#if CYTHON_USE_UNICODE_INTERNALS + { + Py_hash_t hash1, hash2; + #if CYTHON_PEP393_ENABLED + hash1 = ((PyASCIIObject*)s1)->hash; + hash2 = ((PyASCIIObject*)s2)->hash; + #else + hash1 = ((PyUnicodeObject*)s1)->hash; + hash2 = ((PyUnicodeObject*)s2)->hash; + #endif + if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { + goto return_ne; + } + } +#endif + kind = __Pyx_PyUnicode_KIND(s1); + if (kind != __Pyx_PyUnicode_KIND(s2)) { + goto return_ne; + } + data1 = __Pyx_PyUnicode_DATA(s1); + data2 = __Pyx_PyUnicode_DATA(s2); + if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { + goto return_ne; + } else if (length == 1) { + goto return_eq; + } else { + int result = memcmp(data1, data2, (size_t)(length * kind)); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & s2_is_unicode) { + goto return_ne; + } else if ((s2 == Py_None) & s1_is_unicode) { + goto return_ne; + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +return_eq: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ); +return_ne: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_NE); +#endif +} + +/* GetAttr */ + static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { +#if CYTHON_USE_TYPE_SLOTS +#if PY_MAJOR_VERSION >= 3 + if (likely(PyUnicode_Check(n))) +#else + if (likely(PyString_Check(n))) +#endif + return __Pyx_PyObject_GetAttrStr(o, n); +#endif + return PyObject_GetAttr(o, n); +} + +/* ObjectGetItem */ + #if CYTHON_USE_TYPE_SLOTS +static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { + PyObject *runerr; + Py_ssize_t key_value; + PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; + if (unlikely(!(m && m->sq_item))) { + PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); + return NULL; + } + key_value = __Pyx_PyIndex_AsSsize_t(index); + if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { + return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); + } + if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { + PyErr_Clear(); + PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); + } + return NULL; +} +static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { + PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; + if (likely(m && m->mp_subscript)) { + return m->mp_subscript(obj, key); + } + return __Pyx_PyObject_GetIndex(obj, key); +} +#endif + +/* decode_c_string */ + static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { + Py_ssize_t length; + if (unlikely((start < 0) | (stop < 0))) { + size_t slen = strlen(cstring); + if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { + PyErr_SetString(PyExc_OverflowError, + "c-string too long to convert to Python"); + return NULL; + } + length = (Py_ssize_t) slen; + if (start < 0) { + start += length; + if (start < 0) + start = 0; + } + if (stop < 0) + stop += length; + } + if (unlikely(stop <= start)) + return __Pyx_NewRef(__pyx_empty_unicode); + length = stop - start; + cstring += start; + if (decode_func) { + return decode_func(cstring, length, errors); + } else { + return PyUnicode_Decode(cstring, length, encoding, errors); + } +} + +/* GetAttr3 */ + static PyObject *__Pyx_GetAttr3Default(PyObject *d) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + return NULL; + __Pyx_PyErr_Clear(); + Py_INCREF(d); + return d; +} +static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) { + PyObject *r = __Pyx_GetAttr(o, n); + return (likely(r)) ? r : __Pyx_GetAttr3Default(d); +} + +/* RaiseTooManyValuesToUnpack */ + static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { + PyErr_Format(PyExc_ValueError, + "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); +} + +/* RaiseNeedMoreValuesToUnpack */ + static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { + PyErr_Format(PyExc_ValueError, + "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", + index, (index == 1) ? "" : "s"); +} + +/* RaiseNoneIterError */ + static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); +} + +/* SwapException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = *type; + exc_info->exc_value = *value; + exc_info->exc_traceback = *tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = *type; + tstate->exc_value = *value; + tstate->exc_traceback = *tb; + #endif + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} +#else +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); + PyErr_SetExcInfo(*type, *value, *tb); + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} +#endif + +/* Import */ + static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_MAJOR_VERSION < 3 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_MAJOR_VERSION < 3 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + +/* FastTypeChecks */ + #if CYTHON_COMPILING_IN_CPYTHON +static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { + while (a) { + a = a->tp_base; + if (a == b) + return 1; + } + return b == &PyBaseObject_Type; +} +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { + PyObject *mro; + if (a == b) return 1; + mro = a->tp_mro; + if (likely(mro)) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(mro); + for (i = 0; i < n; i++) { + if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) + return 1; + } + return 0; + } + return __Pyx_InBases(a, b); +} +#if PY_MAJOR_VERSION == 2 +static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { + PyObject *exception, *value, *tb; + int res; + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&exception, &value, &tb); + res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + if (!res) { + res = PyObject_IsSubclass(err, exc_type2); + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + } + __Pyx_ErrRestore(exception, value, tb); + return res; +} +#else +static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { + int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; + if (!res) { + res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); + } + return res; +} +#endif +static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + assert(PyExceptionClass_Check(exc_type)); + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; i= 0 || (x^b) >= 0)) + return PyInt_FromLong(x); + return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + #endif + #if CYTHON_USE_PYLONG_INTERNALS + if (likely(PyLong_CheckExact(op1))) { + const long b = intval; + long a, x; +#ifdef HAVE_LONG_LONG + const PY_LONG_LONG llb = intval; + PY_LONG_LONG lla, llx; +#endif + const digit* digits = ((PyLongObject*)op1)->ob_digit; + const Py_ssize_t size = Py_SIZE(op1); + if (likely(__Pyx_sst_abs(size) <= 1)) { + a = likely(size) ? digits[0] : 0; + if (size == -1) a = -a; + } else { + switch (size) { + case -2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + default: return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + } + x = a + b; + return PyLong_FromLong(x); +#ifdef HAVE_LONG_LONG + long_long: + llx = lla + llb; + return PyLong_FromLongLong(llx); +#endif + + + } + #endif + if (PyFloat_CheckExact(op1)) { + const long b = intval; + double a = PyFloat_AS_DOUBLE(op1); + double result; + PyFPE_START_PROTECT("add", return NULL) + result = ((double)a) + (double)b; + PyFPE_END_PROTECT(result) + return PyFloat_FromDouble(result); + } + return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); +} +#endif + +/* None */ + static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { + PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); +} + +/* ImportFrom */ + static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { + PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); + if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Format(PyExc_ImportError, + #if PY_MAJOR_VERSION < 3 + "cannot import name %.230s", PyString_AS_STRING(name)); + #else + "cannot import name %S", name); + #endif + } + return value; +} + +/* HasAttr */ + static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) { + PyObject *r; + if (unlikely(!__Pyx_PyBaseString_Check(n))) { + PyErr_SetString(PyExc_TypeError, + "hasattr(): attribute name must be string"); + return -1; + } + r = __Pyx_GetAttr(o, n); + if (unlikely(!r)) { + PyErr_Clear(); + return 0; + } else { + Py_DECREF(r); + return 1; + } +} + +/* PyObject_GenericGetAttrNoDict */ + #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) { + PyErr_Format(PyExc_AttributeError, +#if PY_MAJOR_VERSION >= 3 + "'%.50s' object has no attribute '%U'", + tp->tp_name, attr_name); +#else + "'%.50s' object has no attribute '%.400s'", + tp->tp_name, PyString_AS_STRING(attr_name)); +#endif + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) { + PyObject *descr; + PyTypeObject *tp = Py_TYPE(obj); + if (unlikely(!PyString_Check(attr_name))) { + return PyObject_GenericGetAttr(obj, attr_name); + } + assert(!tp->tp_dictoffset); + descr = _PyType_Lookup(tp, attr_name); + if (unlikely(!descr)) { + return __Pyx_RaiseGenericGetAttributeError(tp, attr_name); + } + Py_INCREF(descr); + #if PY_MAJOR_VERSION < 3 + if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS))) + #endif + { + descrgetfunc f = Py_TYPE(descr)->tp_descr_get; + if (unlikely(f)) { + PyObject *res = f(descr, obj, (PyObject *)tp); + Py_DECREF(descr); + return res; + } + } + return descr; +} +#endif + +/* PyObject_GenericGetAttr */ + #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) { + if (unlikely(Py_TYPE(obj)->tp_dictoffset)) { + return PyObject_GenericGetAttr(obj, attr_name); + } + return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name); +} +#endif + +/* SetVTable */ + static int __Pyx_SetVtable(PyObject *dict, void *vtable) { +#if PY_VERSION_HEX >= 0x02070000 + PyObject *ob = PyCapsule_New(vtable, 0, 0); +#else + PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); +#endif + if (!ob) + goto bad; + if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) + goto bad; + Py_DECREF(ob); + return 0; +bad: + Py_XDECREF(ob); + return -1; +} + +/* PyObjectGetAttrStrNoError */ + static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + __Pyx_PyErr_Clear(); +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { + PyObject *result; +#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { + return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); + } +#endif + result = __Pyx_PyObject_GetAttrStr(obj, attr_name); + if (unlikely(!result)) { + __Pyx_PyObject_GetAttrStr_ClearAttributeError(); + } + return result; +} + +/* SetupReduce */ + static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { + int ret; + PyObject *name_attr; + name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2); + if (likely(name_attr)) { + ret = PyObject_RichCompareBool(name_attr, name, Py_EQ); + } else { + ret = -1; + } + if (unlikely(ret < 0)) { + PyErr_Clear(); + ret = 0; + } + Py_XDECREF(name_attr); + return ret; +} +static int __Pyx_setup_reduce(PyObject* type_obj) { + int ret = 0; + PyObject *object_reduce = NULL; + PyObject *object_reduce_ex = NULL; + PyObject *reduce = NULL; + PyObject *reduce_ex = NULL; + PyObject *reduce_cython = NULL; + PyObject *setstate = NULL; + PyObject *setstate_cython = NULL; +#if CYTHON_USE_PYTYPE_LOOKUP + if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#else + if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#endif +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#else + object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#endif + reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; + if (reduce_ex == object_reduce_ex) { +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#else + object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#endif + reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; + if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { + reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); + if (likely(reduce_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (reduce == object_reduce || PyErr_Occurred()) { + goto __PYX_BAD; + } + setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); + if (!setstate) PyErr_Clear(); + if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { + setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); + if (likely(setstate_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (!setstate || PyErr_Occurred()) { + goto __PYX_BAD; + } + } + PyType_Modified((PyTypeObject*)type_obj); + } + } + goto __PYX_GOOD; +__PYX_BAD: + if (!PyErr_Occurred()) + PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); + ret = -1; +__PYX_GOOD: +#if !CYTHON_USE_PYTYPE_LOOKUP + Py_XDECREF(object_reduce); + Py_XDECREF(object_reduce_ex); +#endif + Py_XDECREF(reduce); + Py_XDECREF(reduce_ex); + Py_XDECREF(reduce_cython); + Py_XDECREF(setstate); + Py_XDECREF(setstate_cython); + return ret; +} + +/* TypeImport */ + #ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, + size_t size, enum __Pyx_ImportType_CheckSize check_size) +{ + PyObject *result = 0; + char warning[200]; + Py_ssize_t basicsize; +#ifdef Py_LIMITED_API + PyObject *py_basicsize; +#endif + result = PyObject_GetAttrString(module, class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%.200s.%.200s is not a type object", + module_name, class_name); + goto bad; + } +#ifndef Py_LIMITED_API + basicsize = ((PyTypeObject *)result)->tp_basicsize; +#else + py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); + if (!py_basicsize) + goto bad; + basicsize = PyLong_AsSsize_t(py_basicsize); + Py_DECREF(py_basicsize); + py_basicsize = 0; + if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) + goto bad; +#endif + if ((size_t)basicsize < size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(result); + return NULL; +} +#endif + +/* GetVTable */ + static void* __Pyx_GetVtable(PyObject *dict) { + void* ptr; + PyObject *ob = PyObject_GetItem(dict, __pyx_n_s_pyx_vtable); + if (!ob) + goto bad; +#if PY_VERSION_HEX >= 0x02070000 + ptr = PyCapsule_GetPointer(ob, 0); +#else + ptr = PyCObject_AsVoidPtr(ob); +#endif + if (!ptr && !PyErr_Occurred()) + PyErr_SetString(PyExc_RuntimeError, "invalid vtable found for imported type"); + Py_DECREF(ob); + return ptr; +bad: + Py_XDECREF(ob); + return NULL; +} + +/* CLineInTraceback */ + #ifndef CYTHON_CLINE_IN_TRACEBACK +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { + PyObject *use_cline; + PyObject *ptype, *pvalue, *ptraceback; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject **cython_runtime_dict; +#endif + if (unlikely(!__pyx_cython_runtime)) { + return c_line; + } + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); +#if CYTHON_COMPILING_IN_CPYTHON + cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); + if (likely(cython_runtime_dict)) { + __PYX_PY_DICT_LOOKUP_IF_MODIFIED( + use_cline, *cython_runtime_dict, + __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) + } else +#endif + { + PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); + if (use_cline_obj) { + use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; + Py_DECREF(use_cline_obj); + } else { + PyErr_Clear(); + use_cline = NULL; + } + } + if (!use_cline) { + c_line = 0; + PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); + } + else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { + c_line = 0; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + return c_line; +} +#endif + +/* CodeObjectCache */ + static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = start + (end - start) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +/* AddTraceback */ + #include "compile.h" +#include "frameobject.h" +#include "traceback.h" +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyObject *py_srcfile = 0; + PyObject *py_funcname = 0; + #if PY_MAJOR_VERSION < 3 + py_srcfile = PyString_FromString(filename); + #else + py_srcfile = PyUnicode_FromString(filename); + #endif + if (!py_srcfile) goto bad; + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + #else + py_funcname = PyUnicode_FromString(funcname); + #endif + } + if (!py_funcname) goto bad; + py_code = __Pyx_PyCode_New( + 0, + 0, + 0, + 0, + 0, + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + Py_DECREF(py_funcname); + return py_code; +bad: + Py_XDECREF(py_srcfile); + Py_XDECREF(py_funcname); + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + if (c_line) { + c_line = __Pyx_CLineForTraceback(tstate, c_line); + } + py_code = __pyx_find_code_object(c_line ? -c_line : py_line); + if (!py_code) { + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) goto bad; + __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); + } + py_frame = PyFrame_New( + tstate, /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + __pyx_d, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + __Pyx_PyFrame_SetLineNumber(py_frame, py_line); + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { + if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); + if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); + if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); + PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); + return -1; +} +static void __Pyx_ReleaseBuffer(Py_buffer *view) { + PyObject *obj = view->obj; + if (!obj) return; + if (PyObject_CheckBuffer(obj)) { + PyBuffer_Release(view); + return; + } + if ((0)) {} + view->obj = NULL; + Py_DECREF(obj); +} +#endif + + + /* MemviewSliceIsContig */ + static int +__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) +{ + int i, index, step, start; + Py_ssize_t itemsize = mvs.memview->view.itemsize; + if (order == 'F') { + step = 1; + start = 0; + } else { + step = -1; + start = ndim - 1; + } + for (i = 0; i < ndim; i++) { + index = start + step * i; + if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) + return 0; + itemsize *= mvs.shape[index]; + } + return 1; +} + +/* OverlappingSlices */ + static void +__pyx_get_array_memory_extents(__Pyx_memviewslice *slice, + void **out_start, void **out_end, + int ndim, size_t itemsize) +{ + char *start, *end; + int i; + start = end = slice->data; + for (i = 0; i < ndim; i++) { + Py_ssize_t stride = slice->strides[i]; + Py_ssize_t extent = slice->shape[i]; + if (extent == 0) { + *out_start = *out_end = start; + return; + } else { + if (stride > 0) + end += stride * (extent - 1); + else + start += stride * (extent - 1); + } + } + *out_start = start; + *out_end = end + itemsize; +} +static int +__pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize) +{ + void *start1, *end1, *start2, *end2; + __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); + __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); + return (start1 < end2) && (start2 < end1); +} + +/* Capsule */ + static CYTHON_INLINE PyObject * +__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) +{ + PyObject *cobj; +#if PY_VERSION_HEX >= 0x02070000 + cobj = PyCapsule_New(p, sig, NULL); +#else + cobj = PyCObject_FromVoidPtr(p, NULL); +#endif + return cobj; +} + +/* CIntFromPyVerify */ + #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ + } + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabsf(b.real) >= fabsf(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + float r = b.imag / b.real; + float s = (float)(1.0) / (b.real + b.imag * r); + return __pyx_t_float_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + float r = b.real / b.imag; + float s = (float)(1.0) / (b.imag + b.real * r); + return __pyx_t_float_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + float denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_float_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_float(a, a); + case 3: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, a); + case 4: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = powf(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2f(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_float(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabs(b.real) >= fabs(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + double r = b.imag / b.real; + double s = (double)(1.0) / (b.real + b.imag * r); + return __pyx_t_double_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + double r = b.real / b.imag; + double s = (double)(1.0) / (b.imag + b.real * r); + return __pyx_t_double_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + double denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_double_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_double(a, a); + case 3: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, a); + case 4: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = pow(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_double(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +/* MemviewSliceCopyTemplate */ + static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object) +{ + __Pyx_RefNannyDeclarations + int i; + __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; + struct __pyx_memoryview_obj *from_memview = from_mvs->memview; + Py_buffer *buf = &from_memview->view; + PyObject *shape_tuple = NULL; + PyObject *temp_int = NULL; + struct __pyx_array_obj *array_obj = NULL; + struct __pyx_memoryview_obj *memview_obj = NULL; + __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); + for (i = 0; i < ndim; i++) { + if (unlikely(from_mvs->suboffsets[i] >= 0)) { + PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " + "indirect dimensions (axis %d)", i); + goto fail; + } + } + shape_tuple = PyTuple_New(ndim); + if (unlikely(!shape_tuple)) { + goto fail; + } + __Pyx_GOTREF(shape_tuple); + for(i = 0; i < ndim; i++) { + temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); + if(unlikely(!temp_int)) { + goto fail; + } else { + PyTuple_SET_ITEM(shape_tuple, i, temp_int); + temp_int = NULL; + } + } + array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); + if (unlikely(!array_obj)) { + goto fail; + } + __Pyx_GOTREF(array_obj); + memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + (PyObject *) array_obj, contig_flag, + dtype_is_object, + from_mvs->memview->typeinfo); + if (unlikely(!memview_obj)) + goto fail; + if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) + goto fail; + if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, + dtype_is_object) < 0)) + goto fail; + goto no_fail; +fail: + __Pyx_XDECREF(new_mvs.memview); + new_mvs.memview = NULL; + new_mvs.data = NULL; +no_fail: + __Pyx_XDECREF(shape_tuple); + __Pyx_XDECREF(temp_int); + __Pyx_XDECREF(array_obj); + __Pyx_RefNannyFinishContext(); + return new_mvs; +} + +/* CIntFromPy */ + static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(Py_intptr_t) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (Py_intptr_t) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (Py_intptr_t) 0; + case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, digits[0]) + case 2: + if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 2 * PyLong_SHIFT) { + return (Py_intptr_t) (((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 3 * PyLong_SHIFT) { + return (Py_intptr_t) (((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 4 * PyLong_SHIFT) { + return (Py_intptr_t) (((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (Py_intptr_t) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (Py_intptr_t) 0; + case -1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, +digits[0]) + case -2: + if (8 * sizeof(Py_intptr_t) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + } +#endif + if (sizeof(Py_intptr_t) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + Py_intptr_t val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (Py_intptr_t) -1; + } + } else { + Py_intptr_t val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (Py_intptr_t) -1; + val = __Pyx_PyInt_As_Py_intptr_t(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to Py_intptr_t"); + return (Py_intptr_t) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to Py_intptr_t"); + return (Py_intptr_t) -1; +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(int) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(int) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(int) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(int), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE npy_uint32 __Pyx_PyInt_As_npy_uint32(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const npy_uint32 neg_one = (npy_uint32) -1, const_zero = (npy_uint32) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(npy_uint32) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(npy_uint32, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (npy_uint32) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (npy_uint32) 0; + case 1: __PYX_VERIFY_RETURN_INT(npy_uint32, digit, digits[0]) + case 2: + if (8 * sizeof(npy_uint32) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_uint32) >= 2 * PyLong_SHIFT) { + return (npy_uint32) (((((npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(npy_uint32) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_uint32) >= 3 * PyLong_SHIFT) { + return (npy_uint32) (((((((npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(npy_uint32) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_uint32) >= 4 * PyLong_SHIFT) { + return (npy_uint32) (((((((((npy_uint32)digits[3]) << PyLong_SHIFT) | (npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (npy_uint32) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(npy_uint32) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_uint32) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (npy_uint32) 0; + case -1: __PYX_VERIFY_RETURN_INT(npy_uint32, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(npy_uint32, digit, +digits[0]) + case -2: + if (8 * sizeof(npy_uint32) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_uint32, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_uint32) - 1 > 2 * PyLong_SHIFT) { + return (npy_uint32) (((npy_uint32)-1)*(((((npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(npy_uint32) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_uint32) - 1 > 2 * PyLong_SHIFT) { + return (npy_uint32) ((((((npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(npy_uint32) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_uint32, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_uint32) - 1 > 3 * PyLong_SHIFT) { + return (npy_uint32) (((npy_uint32)-1)*(((((((npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(npy_uint32) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_uint32) - 1 > 3 * PyLong_SHIFT) { + return (npy_uint32) ((((((((npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(npy_uint32) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_uint32, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_uint32) - 1 > 4 * PyLong_SHIFT) { + return (npy_uint32) (((npy_uint32)-1)*(((((((((npy_uint32)digits[3]) << PyLong_SHIFT) | (npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(npy_uint32) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_uint32) - 1 > 4 * PyLong_SHIFT) { + return (npy_uint32) ((((((((((npy_uint32)digits[3]) << PyLong_SHIFT) | (npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]))); + } + } + break; + } +#endif + if (sizeof(npy_uint32) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_uint32) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + npy_uint32 val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (npy_uint32) -1; + } + } else { + npy_uint32 val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (npy_uint32) -1; + val = __Pyx_PyInt_As_npy_uint32(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to npy_uint32"); + return (npy_uint32) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to npy_uint32"); + return (npy_uint32) -1; +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(long) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(long) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(long) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(long), + little, !is_unsigned); + } +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(Py_intptr_t) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(Py_intptr_t) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(Py_intptr_t), + little, !is_unsigned); + } +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_int32(npy_int32 value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(npy_int32) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(npy_int32) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(npy_int32) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(npy_int32), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(npy_int32) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (npy_int32) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (npy_int32) 0; + case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, digits[0]) + case 2: + if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) >= 2 * PyLong_SHIFT) { + return (npy_int32) (((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) >= 3 * PyLong_SHIFT) { + return (npy_int32) (((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) >= 4 * PyLong_SHIFT) { + return (npy_int32) (((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (npy_int32) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(npy_int32) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (npy_int32) 0; + case -1: __PYX_VERIFY_RETURN_INT(npy_int32, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, +digits[0]) + case -2: + if (8 * sizeof(npy_int32) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { + return (npy_int32) (((npy_int32)-1)*(((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { + return (npy_int32) ((((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { + return (npy_int32) (((npy_int32)-1)*(((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { + return (npy_int32) ((((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) { + return (npy_int32) (((npy_int32)-1)*(((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) { + return (npy_int32) ((((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + } +#endif + if (sizeof(npy_int32) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + npy_int32 val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (npy_int32) -1; + } + } else { + npy_int32 val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (npy_int32) -1; + val = __Pyx_PyInt_As_npy_int32(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to npy_int32"); + return (npy_int32) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to npy_int32"); + return (npy_int32) -1; +} + +/* CIntFromPy */ + static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + } +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +/* CIntFromPy */ + static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(long) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (long) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(long) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + } +#endif + if (sizeof(long) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + long val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (long) -1; + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (long) -1; + val = __Pyx_PyInt_As_long(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to long"); + return (long) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long) -1; +} + +/* CIntFromPy */ + static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const char neg_one = (char) -1, const_zero = (char) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(char) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (char) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (char) 0; + case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { + return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { + return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { + return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (char) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(char) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (char) 0; + case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) + case -2: + if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + } +#endif + if (sizeof(char) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + char val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (char) -1; + } + } else { + char val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (char) -1; + val = __Pyx_PyInt_As_char(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to char"); + return (char) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to char"); + return (char) -1; +} + +/* TypeInfoCompare */ + static int +__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) +{ + int i; + if (!a || !b) + return 0; + if (a == b) + return 1; + if (a->size != b->size || a->typegroup != b->typegroup || + a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { + if (a->typegroup == 'H' || b->typegroup == 'H') { + return a->size == b->size; + } else { + return 0; + } + } + if (a->ndim) { + for (i = 0; i < a->ndim; i++) + if (a->arraysize[i] != b->arraysize[i]) + return 0; + } + if (a->typegroup == 'S') { + if (a->flags != b->flags) + return 0; + if (a->fields || b->fields) { + if (!(a->fields && b->fields)) + return 0; + for (i = 0; a->fields[i].type && b->fields[i].type; i++) { + __Pyx_StructField *field_a = a->fields + i; + __Pyx_StructField *field_b = b->fields + i; + if (field_a->offset != field_b->offset || + !__pyx_typeinfo_cmp(field_a->type, field_b->type)) + return 0; + } + return !a->fields[i].type && !b->fields[i].type; + } + } + return 1; +} + +/* MemviewSliceValidateAndInit */ + static int +__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) +{ + if (buf->shape[dim] <= 1) + return 1; + if (buf->strides) { + if (spec & __Pyx_MEMVIEW_CONTIG) { + if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { + if (unlikely(buf->strides[dim] != sizeof(void *))) { + PyErr_Format(PyExc_ValueError, + "Buffer is not indirectly contiguous " + "in dimension %d.", dim); + goto fail; + } + } else if (unlikely(buf->strides[dim] != buf->itemsize)) { + PyErr_SetString(PyExc_ValueError, + "Buffer and memoryview are not contiguous " + "in the same dimension."); + goto fail; + } + } + if (spec & __Pyx_MEMVIEW_FOLLOW) { + Py_ssize_t stride = buf->strides[dim]; + if (stride < 0) + stride = -stride; + if (unlikely(stride < buf->itemsize)) { + PyErr_SetString(PyExc_ValueError, + "Buffer and memoryview are not contiguous " + "in the same dimension."); + goto fail; + } + } + } else { + if (unlikely(spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1)) { + PyErr_Format(PyExc_ValueError, + "C-contiguous buffer is not contiguous in " + "dimension %d", dim); + goto fail; + } else if (unlikely(spec & (__Pyx_MEMVIEW_PTR))) { + PyErr_Format(PyExc_ValueError, + "C-contiguous buffer is not indirect in " + "dimension %d", dim); + goto fail; + } else if (unlikely(buf->suboffsets)) { + PyErr_SetString(PyExc_ValueError, + "Buffer exposes suboffsets but no strides"); + goto fail; + } + } + return 1; +fail: + return 0; +} +static int +__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) +{ + if (spec & __Pyx_MEMVIEW_DIRECT) { + if (unlikely(buf->suboffsets && buf->suboffsets[dim] >= 0)) { + PyErr_Format(PyExc_ValueError, + "Buffer not compatible with direct access " + "in dimension %d.", dim); + goto fail; + } + } + if (spec & __Pyx_MEMVIEW_PTR) { + if (unlikely(!buf->suboffsets || (buf->suboffsets[dim] < 0))) { + PyErr_Format(PyExc_ValueError, + "Buffer is not indirectly accessible " + "in dimension %d.", dim); + goto fail; + } + } + return 1; +fail: + return 0; +} +static int +__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) +{ + int i; + if (c_or_f_flag & __Pyx_IS_F_CONTIG) { + Py_ssize_t stride = 1; + for (i = 0; i < ndim; i++) { + if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { + PyErr_SetString(PyExc_ValueError, + "Buffer not fortran contiguous."); + goto fail; + } + stride = stride * buf->shape[i]; + } + } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { + Py_ssize_t stride = 1; + for (i = ndim - 1; i >- 1; i--) { + if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { + PyErr_SetString(PyExc_ValueError, + "Buffer not C contiguous."); + goto fail; + } + stride = stride * buf->shape[i]; + } + } + return 1; +fail: + return 0; +} +static int __Pyx_ValidateAndInit_memviewslice( + int *axes_specs, + int c_or_f_flag, + int buf_flags, + int ndim, + __Pyx_TypeInfo *dtype, + __Pyx_BufFmt_StackElem stack[], + __Pyx_memviewslice *memviewslice, + PyObject *original_obj) +{ + struct __pyx_memoryview_obj *memview, *new_memview; + __Pyx_RefNannyDeclarations + Py_buffer *buf; + int i, spec = 0, retval = -1; + __Pyx_BufFmt_Context ctx; + int from_memoryview = __pyx_memoryview_check(original_obj); + __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0); + if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) + original_obj)->typeinfo)) { + memview = (struct __pyx_memoryview_obj *) original_obj; + new_memview = NULL; + } else { + memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + original_obj, buf_flags, 0, dtype); + new_memview = memview; + if (unlikely(!memview)) + goto fail; + } + buf = &memview->view; + if (unlikely(buf->ndim != ndim)) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + ndim, buf->ndim); + goto fail; + } + if (new_memview) { + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (unlikely(!__Pyx_BufFmt_CheckString(&ctx, buf->format))) goto fail; + } + if (unlikely((unsigned) buf->itemsize != dtype->size)) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " + "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", + buf->itemsize, + (buf->itemsize > 1) ? "s" : "", + dtype->name, + dtype->size, + (dtype->size > 1) ? "s" : ""); + goto fail; + } + if (buf->len > 0) { + for (i = 0; i < ndim; i++) { + spec = axes_specs[i]; + if (unlikely(!__pyx_check_strides(buf, i, ndim, spec))) + goto fail; + if (unlikely(!__pyx_check_suboffsets(buf, i, ndim, spec))) + goto fail; + } + if (unlikely(buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))) + goto fail; + } + if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, + new_memview != NULL) == -1)) { + goto fail; + } + retval = 0; + goto no_fail; +fail: + Py_XDECREF(new_memview); + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} + +/* ObjectToMemviewSlice */ + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t__const__(PyObject *obj, int writable_flag) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS_RO | writable_flag, 2, + &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t__const__, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +/* CheckBinaryVersion */ + static int __Pyx_check_binary_version(void) { + char ctversion[4], rtversion[4]; + PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); + PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); + if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { + char message[200]; + PyOS_snprintf(message, sizeof(message), + "compiletime version %s of module '%.100s' " + "does not match runtime version %s", + ctversion, __Pyx_MODULE_NAME, rtversion); + return PyErr_WarnEx(NULL, message, 1); + } + return 0; +} + +/* VoidPtrImport */ + #ifndef __PYX_HAVE_RT_ImportVoidPtr +#define __PYX_HAVE_RT_ImportVoidPtr +static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig) { + PyObject *d = 0; + PyObject *cobj = 0; + d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); + if (!d) + goto bad; + cobj = PyDict_GetItemString(d, name); + if (!cobj) { + PyErr_Format(PyExc_ImportError, + "%.200s does not export expected C variable %.200s", + PyModule_GetName(module), name); + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + if (!PyCapsule_IsValid(cobj, sig)) { + PyErr_Format(PyExc_TypeError, + "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), name, sig, PyCapsule_GetName(cobj)); + goto bad; + } + *p = PyCapsule_GetPointer(cobj, sig); +#else + {const char *desc, *s1, *s2; + desc = (const char *)PyCObject_GetDesc(cobj); + if (!desc) + goto bad; + s1 = desc; s2 = sig; + while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } + if (*s1 != *s2) { + PyErr_Format(PyExc_TypeError, + "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), name, sig, desc); + goto bad; + } + *p = PyCObject_AsVoidPtr(cobj);} +#endif + if (!(*p)) + goto bad; + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(d); + return -1; +} +#endif + +/* FunctionImport */ + #ifndef __PYX_HAVE_RT_ImportFunction +#define __PYX_HAVE_RT_ImportFunction +static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig) { + PyObject *d = 0; + PyObject *cobj = 0; + union { + void (*fp)(void); + void *p; + } tmp; + d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); + if (!d) + goto bad; + cobj = PyDict_GetItemString(d, funcname); + if (!cobj) { + PyErr_Format(PyExc_ImportError, + "%.200s does not export expected C function %.200s", + PyModule_GetName(module), funcname); + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + if (!PyCapsule_IsValid(cobj, sig)) { + PyErr_Format(PyExc_TypeError, + "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), funcname, sig, PyCapsule_GetName(cobj)); + goto bad; + } + tmp.p = PyCapsule_GetPointer(cobj, sig); +#else + {const char *desc, *s1, *s2; + desc = (const char *)PyCObject_GetDesc(cobj); + if (!desc) + goto bad; + s1 = desc; s2 = sig; + while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } + if (*s1 != *s2) { + PyErr_Format(PyExc_TypeError, + "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), funcname, sig, desc); + goto bad; + } + tmp.p = PyCObject_AsVoidPtr(cobj);} +#endif + *f = tmp.fp; + if (!(*f)) + goto bad; + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(d); + return -1; +} +#endif + +/* InitStrings */ + static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + if (PyObject_Hash(*t->p) == -1) + return -1; + ++t; + } + return 0; +} + +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { + return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); +} +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { + Py_ssize_t ignore; + return __Pyx_PyObject_AsStringAndSize(o, &ignore); +} +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if !CYTHON_PEP393_ENABLED +static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + char* defenc_c; + PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); + if (!defenc) return NULL; + defenc_c = PyBytes_AS_STRING(defenc); +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + { + char* end = defenc_c + PyBytes_GET_SIZE(defenc); + char* c; + for (c = defenc_c; c < end; c++) { + if ((unsigned char) (*c) >= 128) { + PyUnicode_AsASCIIString(o); + return NULL; + } + } + } +#endif + *length = PyBytes_GET_SIZE(defenc); + return defenc_c; +} +#else +static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + if (likely(PyUnicode_IS_ASCII(o))) { + *length = PyUnicode_GET_LENGTH(o); + return PyUnicode_AsUTF8(o); + } else { + PyUnicode_AsASCIIString(o); + return NULL; + } +#else + return PyUnicode_AsUTF8AndSize(o, length); +#endif +} +#endif +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT + if ( +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + __Pyx_sys_getdefaultencoding_not_ascii && +#endif + PyUnicode_Check(o)) { + return __Pyx_PyUnicode_AsStringAndSize(o, length); + } else +#endif +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) + if (PyByteArray_Check(o)) { + *length = PyByteArray_GET_SIZE(o); + return PyByteArray_AS_STRING(o); + } else +#endif + { + char* result; + int r = PyBytes_AsStringAndSize(o, &result, length); + if (unlikely(r < 0)) { + return NULL; + } else { + return result; + } + } +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { + int retval; + if (unlikely(!x)) return -1; + retval = __Pyx_PyObject_IsTrue(x); + Py_DECREF(x); + return retval; +} +static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { +#if PY_MAJOR_VERSION >= 3 + if (PyLong_Check(result)) { + if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, + "__int__ returned non-int (type %.200s). " + "The ability to return an instance of a strict subclass of int " + "is deprecated, and may be removed in a future version of Python.", + Py_TYPE(result)->tp_name)) { + Py_DECREF(result); + return NULL; + } + return result; + } +#endif + PyErr_Format(PyExc_TypeError, + "__%.4s__ returned non-%.4s (type %.200s)", + type_name, type_name, Py_TYPE(result)->tp_name); + Py_DECREF(result); + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { +#if CYTHON_USE_TYPE_SLOTS + PyNumberMethods *m; +#endif + const char *name = NULL; + PyObject *res = NULL; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x) || PyLong_Check(x))) +#else + if (likely(PyLong_Check(x))) +#endif + return __Pyx_NewRef(x); +#if CYTHON_USE_TYPE_SLOTS + m = Py_TYPE(x)->tp_as_number; + #if PY_MAJOR_VERSION < 3 + if (m && m->nb_int) { + name = "int"; + res = m->nb_int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = m->nb_long(x); + } + #else + if (likely(m && m->nb_int)) { + name = "int"; + res = m->nb_int(x); + } + #endif +#else + if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { + res = PyNumber_Int(x); + } +#endif + if (likely(res)) { +#if PY_MAJOR_VERSION < 3 + if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { +#else + if (unlikely(!PyLong_CheckExact(res))) { +#endif + return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject *x; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(b); + } +#endif + if (likely(PyLong_CheckExact(b))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + } + } + #endif + return PyLong_AsSsize_t(b); + } + x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { + return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); +} +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { + return PyInt_FromSize_t(ival); +} + + +#endif /* Py_PYTHON_H */ diff --git a/stpredictions/models/OK3/extra/_splitter.pxd b/stpredictions/models/OK3/_splitter.pxd similarity index 62% rename from stpredictions/models/OK3/extra/_splitter.pxd rename to stpredictions/models/OK3/_splitter.pxd index 13fec5974..836e59d38 100644 --- a/stpredictions/models/OK3/extra/_splitter.pxd +++ b/stpredictions/models/OK3/_splitter.pxd @@ -1,21 +1,15 @@ -# Authors: Gilles Louppe -# Peter Prettenhofer -# Brian Holt -# Joel Nothman -# Arnaud Joly -# Jacob Schreiber -# -# License: BSD 3 clause - # See _splitter.pyx for details. -from ._criterion cimport Criterion +import numpy as np +cimport numpy as np + +from _criterion cimport Criterion -from ._tree cimport DTYPE_t # Type of X -from ._tree cimport DOUBLE_t # Type of y, sample_weight -from ._tree cimport SIZE_t # Type for indices and counters -from ._tree cimport INT32_t # Signed 32 bit integer -from ._tree cimport UINT32_t # Unsigned 32 bit integer +from sklearn.tree._tree cimport DTYPE_t # Type of X +from sklearn.tree._tree cimport DOUBLE_t # Type of y, sample_weight +from sklearn.tree._tree cimport SIZE_t # Type for indices and counters +from sklearn.tree._tree cimport INT32_t # Signed 32 bit integer +from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer cdef struct SplitRecord: # Data to track sample split @@ -43,19 +37,19 @@ cdef class Splitter: cdef object random_state # Random state cdef UINT32_t rand_r_state # sklearn_rand_r random number state - cdef SIZE_t[::1] samples # Sample indices in X, y + cdef SIZE_t* samples # Sample indices in X, y cdef SIZE_t n_samples # X.shape[0] cdef double weighted_n_samples # Weighted number of samples - cdef SIZE_t[::1] features # Feature indices in X - cdef SIZE_t[::1] constant_features # Constant features indices + cdef SIZE_t* features # Feature indices in X + cdef SIZE_t* constant_features # Constant features indices cdef SIZE_t n_features # X.shape[1] - cdef DTYPE_t[::1] feature_values # temp. array holding feature values + cdef DTYPE_t* feature_values # temp. array holding feature values cdef SIZE_t start # Start position for the current node cdef SIZE_t end # End position for the current node cdef const DOUBLE_t[:, ::1] y - cdef const DOUBLE_t[:] sample_weight + cdef DOUBLE_t* sample_weight # The samples vector `samples` is maintained by the Splitter object such # that the samples contained in a node are contiguous. With this setting, @@ -74,27 +68,17 @@ cdef class Splitter: # This allows optimization with depth-based tree building. # Methods - cdef int init( - self, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight - ) except -1 - - cdef int node_reset( - self, - SIZE_t start, - SIZE_t end, - double* weighted_n_node_samples - ) except -1 nogil - - cdef int node_split( - self, - double impurity, # Impurity of the node - SplitRecord* split, - SIZE_t* n_constant_features - ) except -1 nogil - - cdef void node_value(self, double* dest) noexcept nogil - - cdef double node_impurity(self) noexcept nogil + cdef int init(self, object X, const DOUBLE_t[:, ::1] y, + DOUBLE_t* sample_weight) except -1 + + cdef int node_reset(self, SIZE_t start, SIZE_t end, + double* weighted_n_node_samples) nogil except -1 + + cdef int node_split(self, + double impurity, # Impurity of the node + SplitRecord* split, + SIZE_t* n_constant_features) nogil except -1 + + cdef void node_value(self, double* dest) nogil + + cdef double node_impurity(self) nogil diff --git a/stpredictions/models/OK3/_splitter.pyx b/stpredictions/models/OK3/_splitter.pyx index 83a80d90c..e55695070 100644 --- a/stpredictions/models/OK3/_splitter.pyx +++ b/stpredictions/models/OK3/_splitter.pyx @@ -1,30 +1,25 @@ -# Authors: Gilles Louppe -# Peter Prettenhofer -# Brian Holt -# Noel Dawe -# Satrajit Gosh -# Lars Buitinck -# Arnaud Joly -# Joel Nothman -# Fares Hedayati -# Jacob Schreiber -# -# License: BSD 3 clause - -from ._criterion cimport Criterion +# cython: cdivision=True +# cython: boundscheck=False +# cython: wraparound=False +from _criterion cimport Criterion + +from libc.stdlib cimport free from libc.stdlib cimport qsort from libc.string cimport memcpy -from cython cimport final +from libc.string cimport memset import numpy as np +cimport numpy as np +np.import_array() from scipy.sparse import csc_matrix -from ._utils cimport log -from ._utils cimport rand_int -from ._utils cimport rand_uniform -from ._utils cimport RAND_R_MAX +from sklearn.tree._utils cimport log +from sklearn.tree._utils cimport rand_int +from sklearn.tree._utils cimport rand_uniform +from sklearn.tree._utils cimport RAND_R_MAX +from sklearn.tree._utils cimport safe_realloc cdef double INFINITY = np.inf @@ -32,10 +27,10 @@ cdef double INFINITY = np.inf cdef DTYPE_t FEATURE_THRESHOLD = 1e-7 # Constant to switch between algorithm non zero value extract algorithm -# in SparsePartitioner +# in SparseSplitter cdef DTYPE_t EXTRACT_NNZ_SWITCH = 0.1 -cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) noexcept nogil: +cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) nogil: self.impurity_left = INFINITY self.impurity_right = INFINITY self.pos = start_pos @@ -78,33 +73,37 @@ cdef class Splitter: self.criterion = criterion + self.samples = NULL self.n_samples = 0 + self.features = NULL self.n_features = 0 + self.feature_values = NULL + + self.sample_weight = NULL self.max_features = max_features self.min_samples_leaf = min_samples_leaf self.min_weight_leaf = min_weight_leaf self.random_state = random_state + def __dealloc__(self): + """Destructor.""" + + free(self.samples) + free(self.features) + free(self.constant_features) + free(self.feature_values) + def __getstate__(self): return {} def __setstate__(self, d): pass - def __reduce__(self): - return (type(self), (self.criterion, - self.max_features, - self.min_samples_leaf, - self.min_weight_leaf, - self.random_state), self.__getstate__()) - - cdef int init( - self, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight - ) except -1: + cdef int init(self, + object X, + const DOUBLE_t[:, ::1] y, + DOUBLE_t* sample_weight) except -1: """Initialize the splitter. Take in the input data X, the target Y, and optional sample weights. @@ -118,14 +117,12 @@ cdef class Splitter: This contains the inputs. Usually it is a 2d numpy array. y : ndarray, dtype=DOUBLE_t - This is the vector of targets, or true labels, for the samples represented - as a Cython memoryview. + This is the vector of targets, or true labels, for the samples - sample_weight : ndarray, dtype=DOUBLE_t + sample_weight : DOUBLE_t* The weights of the samples, where higher weighted samples are fit closer than lower weight samples. If not provided, all samples - are assumed to have uniform weight. This is represented - as a Cython memoryview. + are assumed to have uniform weight. """ self.rand_r_state = self.random_state.randint(0, RAND_R_MAX) @@ -133,8 +130,7 @@ cdef class Splitter: # Create a new array which will be used to store nonzero # samples from the feature of interest - self.samples = np.empty(n_samples, dtype=np.intp) - cdef SIZE_t[::1] samples = self.samples + cdef SIZE_t* samples = safe_realloc(&self.samples, n_samples) cdef SIZE_t i, j cdef double weighted_n_samples = 0.0 @@ -142,11 +138,11 @@ cdef class Splitter: for i in range(n_samples): # Only work with positively weighted samples - if sample_weight is None or sample_weight[i] != 0.0: + if sample_weight == NULL or sample_weight[i] != 0.0: samples[j] = i j += 1 - if sample_weight is not None: + if sample_weight != NULL: weighted_n_samples += sample_weight[i] else: weighted_n_samples += 1.0 @@ -156,11 +152,15 @@ cdef class Splitter: self.weighted_n_samples = weighted_n_samples cdef SIZE_t n_features = X.shape[1] - self.features = np.arange(n_features, dtype=np.intp) + cdef SIZE_t* features = safe_realloc(&self.features, n_features) + + for i in range(n_features): + features[i] = i + self.n_features = n_features - self.feature_values = np.empty(n_samples, dtype=np.float32) - self.constant_features = np.empty(n_features, dtype=np.intp) + safe_realloc(&self.feature_values, n_samples) + safe_realloc(&self.constant_features, n_features) self.y = y @@ -168,7 +168,7 @@ cdef class Splitter: return 0 cdef int node_reset(self, SIZE_t start, SIZE_t end, - double* weighted_n_node_samples) except -1 nogil: + double* weighted_n_node_samples) nogil except -1: """Reset splitter on node samples[start:end]. Returns -1 in case of failure to allocate memory (and raise MemoryError) @@ -187,20 +187,18 @@ cdef class Splitter: self.start = start self.end = end - self.criterion.init( - self.y, - self.sample_weight, - self.weighted_n_samples, - self.samples, - start, - end - ) + self.criterion.init(self.y, + self.sample_weight, + self.weighted_n_samples, + self.samples, + start, + end) weighted_n_node_samples[0] = self.criterion.weighted_n_node_samples return 0 cdef int node_split(self, double impurity, SplitRecord* split, - SIZE_t* n_constant_features) except -1 nogil: + SIZE_t* n_constant_features) nogil except -1: """Find the best split on node samples[start:end]. This is a placeholder method. The majority of computation will be done @@ -211,228 +209,264 @@ cdef class Splitter: pass - cdef void node_value(self, double* dest) noexcept nogil: + cdef void node_value(self, double* dest) nogil: """Copy the value of node samples[start:end] into dest.""" self.criterion.node_value(dest) - cdef double node_impurity(self) noexcept nogil: + cdef double node_impurity(self) nogil: """Return the impurity of the current node.""" return self.criterion.node_impurity() -# Introduce a fused-class to make it possible to share the split implementation -# between the dense and sparse cases in the node_split_best and node_split_random -# functions. The alternative would have been to use inheritance-based polymorphism -# but it would have resulted in a ~10% overall tree fitting performance -# degradation caused by the overhead frequent virtual method lookups. -ctypedef fused Partitioner: - DensePartitioner - SparsePartitioner - -cdef inline int node_split_best( - Splitter splitter, - Partitioner partitioner, - Criterion criterion, - double impurity, - SplitRecord* split, - SIZE_t* n_constant_features, -) except -1 nogil: - """Find the best split on node samples[start:end] - - Returns -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - # Find the best split - cdef SIZE_t start = splitter.start - cdef SIZE_t end = splitter.end - - cdef SIZE_t[::1] features = splitter.features - cdef SIZE_t[::1] constant_features = splitter.constant_features - cdef SIZE_t n_features = splitter.n_features - - cdef DTYPE_t[::1] feature_values = splitter.feature_values - cdef SIZE_t max_features = splitter.max_features - cdef SIZE_t min_samples_leaf = splitter.min_samples_leaf - cdef double min_weight_leaf = splitter.min_weight_leaf - cdef UINT32_t* random_state = &splitter.rand_r_state - - cdef SplitRecord best_split, current_split - cdef double current_proxy_improvement = -INFINITY - cdef double best_proxy_improvement = -INFINITY - - cdef SIZE_t f_i = n_features - cdef SIZE_t f_j - cdef SIZE_t p - cdef SIZE_t p_prev - - cdef SIZE_t n_visited_features = 0 - # Number of features discovered to be constant during the split search - cdef SIZE_t n_found_constants = 0 - # Number of features known to be constant and drawn without replacement - cdef SIZE_t n_drawn_constants = 0 - cdef SIZE_t n_known_constants = n_constant_features[0] - # n_total_constants = n_known_constants + n_found_constants - cdef SIZE_t n_total_constants = n_known_constants - - _init_split(&best_split, end) - - partitioner.init_node_split(start, end) - - # Sample up to max_features without replacement using a - # Fisher-Yates-based algorithm (using the local variables `f_i` and - # `f_j` to compute a permutation of the `features` array). - # - # Skip the CPU intensive evaluation of the impurity criterion for - # features that were already detected as constant (hence not suitable - # for good splitting) by ancestor nodes and save the information on - # newly discovered constant features to spare computation on descendant - # nodes. - while (f_i > n_total_constants and # Stop early if remaining features - # are constant - (n_visited_features < max_features or - # At least one drawn features must be non constant - n_visited_features <= n_found_constants + n_drawn_constants)): - - n_visited_features += 1 - - # Loop invariant: elements of features in - # - [:n_drawn_constant[ holds drawn and known constant features; - # - [n_drawn_constant:n_known_constant[ holds known constant - # features that haven't been drawn yet; - # - [n_known_constant:n_total_constant[ holds newly found constant - # features; - # - [n_total_constant:f_i[ holds features that haven't been drawn - # yet and aren't constant apriori. - # - [f_i:n_features[ holds features that have been drawn - # and aren't constant. - - # Draw a feature at random - f_j = rand_int(n_drawn_constants, f_i - n_found_constants, - random_state) - - if f_j < n_known_constants: - # f_j in the interval [n_drawn_constants, n_known_constants[ - features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] - - n_drawn_constants += 1 - continue - - # f_j in the interval [n_known_constants, f_i - n_found_constants[ - f_j += n_found_constants - # f_j in the interval [n_total_constants, f_i[ - current_split.feature = features[f_j] - partitioner.sort_samples_and_feature_values(current_split.feature) - - if feature_values[end - 1] <= feature_values[start] + FEATURE_THRESHOLD: - features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] - - n_found_constants += 1 - n_total_constants += 1 - continue - - f_i -= 1 - features[f_i], features[f_j] = features[f_j], features[f_i] - - # Evaluate all splits - # At this point, the criterion has a view into the samples that was sorted - # by the partitioner. The criterion will use that ordering when evaluating the splits. - criterion.reset() - p = start - - while p < end: - partitioner.next_p(&p_prev, &p) - - if p >= end: - continue - - current_split.pos = p - - # Reject if min_samples_leaf is not guaranteed - if (((current_split.pos - start) < min_samples_leaf) or - ((end - current_split.pos) < min_samples_leaf)): - continue - - criterion.update(current_split.pos) - - # Reject if min_weight_leaf is not satisfied - if ((criterion.weighted_n_left < min_weight_leaf) or - (criterion.weighted_n_right < min_weight_leaf)): - continue - - current_proxy_improvement = criterion.proxy_impurity_improvement() - - if current_proxy_improvement > best_proxy_improvement: - best_proxy_improvement = current_proxy_improvement - # sum of halves is used to avoid infinite value - current_split.threshold = ( - feature_values[p_prev] / 2.0 + feature_values[p] / 2.0 - ) - - if ( - current_split.threshold == feature_values[p] or - current_split.threshold == INFINITY or - current_split.threshold == -INFINITY - ): - current_split.threshold = feature_values[p_prev] - - # This creates a SplitRecord copy - best_split = current_split - - # Reorganize into samples[start:best_split.pos] + samples[best_split.pos:end] - if best_split.pos < end: - partitioner.partition_samples_final( - best_split.pos, - best_split.threshold, - best_split.feature - ) - criterion.reset() - criterion.update(best_split.pos) - criterion.children_impurity( - &best_split.impurity_left, &best_split.impurity_right - ) - best_split.improvement = criterion.impurity_improvement( - impurity, - best_split.impurity_left, - best_split.impurity_right - ) - - # Respect invariant for constant features: the original order of - # element in features[:n_known_constants] must be preserved for sibling - # and child nodes - memcpy(&features[0], &constant_features[0], sizeof(SIZE_t) * n_known_constants) - - # Copy newly found constant features - memcpy(&constant_features[n_known_constants], - &features[n_known_constants], - sizeof(SIZE_t) * n_found_constants) - - # Return values - split[0] = best_split - n_constant_features[0] = n_total_constants - return 0 - - -# Sort n-element arrays pointed to by feature_values and samples, simultaneously, -# by the values in feature_values. Algorithm: Introsort (Musser, SP&E, 1997). -cdef inline void sort(DTYPE_t* feature_values, SIZE_t* samples, SIZE_t n) noexcept nogil: + +cdef class BaseDenseSplitter(Splitter): + cdef const DTYPE_t[:, :] X + + cdef SIZE_t n_total_samples + + cdef int init(self, + object X, + const DOUBLE_t[:, ::1] y, + DOUBLE_t* sample_weight) except -1: + """Initialize the splitter + + Returns -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + + # Call parent init + Splitter.init(self, X, y, sample_weight) + + self.X = X + return 0 + + +cdef class BestSplitter(BaseDenseSplitter): + """Splitter for finding the best split.""" + def __reduce__(self): + return (BestSplitter, (self.criterion, + self.max_features, + self.min_samples_leaf, + self.min_weight_leaf, + self.random_state), self.__getstate__()) + + cdef int node_split(self, double impurity, SplitRecord* split, + SIZE_t* n_constant_features) nogil except -1: + """Find the best split on node samples[start:end] + + Returns -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + # Find the best split + cdef SIZE_t* samples = self.samples + cdef SIZE_t start = self.start + cdef SIZE_t end = self.end + + cdef SIZE_t* features = self.features + cdef SIZE_t* constant_features = self.constant_features + cdef SIZE_t n_features = self.n_features + + cdef DTYPE_t* Xf = self.feature_values + cdef SIZE_t max_features = self.max_features + cdef SIZE_t min_samples_leaf = self.min_samples_leaf + cdef double min_weight_leaf = self.min_weight_leaf + cdef UINT32_t* random_state = &self.rand_r_state + + cdef SplitRecord best, current + cdef double current_proxy_improvement = -INFINITY + cdef double best_proxy_improvement = -INFINITY + + cdef SIZE_t f_i = n_features + cdef SIZE_t f_j + cdef SIZE_t p + cdef SIZE_t feature_idx_offset + cdef SIZE_t feature_offset + cdef SIZE_t i + cdef SIZE_t j + + cdef SIZE_t n_visited_features = 0 + # Number of features discovered to be constant during the split search + cdef SIZE_t n_found_constants = 0 + # Number of features known to be constant and drawn without replacement + cdef SIZE_t n_drawn_constants = 0 + cdef SIZE_t n_known_constants = n_constant_features[0] + # n_total_constants = n_known_constants + n_found_constants + cdef SIZE_t n_total_constants = n_known_constants + cdef DTYPE_t current_feature_value + cdef SIZE_t partition_end + + _init_split(&best, end) + + # Sample up to max_features without replacement using a + # Fisher-Yates-based algorithm (using the local variables `f_i` and + # `f_j` to compute a permutation of the `features` array). + # + # Skip the CPU intensive evaluation of the impurity criterion for + # features that were already detected as constant (hence not suitable + # for good splitting) by ancestor nodes and save the information on + # newly discovered constant features to spare computation on descendant + # nodes. + while (f_i > n_total_constants and # Stop early if remaining features + # are constant + (n_visited_features < max_features or + # At least one drawn features must be non constant + n_visited_features <= n_found_constants + n_drawn_constants)): + + n_visited_features += 1 + + # Loop invariant: elements of features in + # - [:n_drawn_constant[ holds drawn and known constant features; + # - [n_drawn_constant:n_known_constant[ holds known constant + # features that haven't been drawn yet; + # - [n_known_constant:n_total_constant[ holds newly found constant + # features; + # - [n_total_constant:f_i[ holds features that haven't been drawn + # yet and aren't constant apriori. + # - [f_i:n_features[ holds features that have been drawn + # and aren't constant. + + # Draw a feature at random + f_j = rand_int(n_drawn_constants, f_i - n_found_constants, + random_state) + + if f_j < n_known_constants: + # f_j in the interval [n_drawn_constants, n_known_constants[ + features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] + + n_drawn_constants += 1 + + else: + # f_j in the interval [n_known_constants, f_i - n_found_constants[ + f_j += n_found_constants + # f_j in the interval [n_total_constants, f_i[ + current.feature = features[f_j] + + # Sort samples along that feature; by + # copying the values into an array and + # sorting the array in a manner which utilizes the cache more + # effectively. + for i in range(start, end): + Xf[i] = self.X[samples[i], current.feature] + + sort(Xf + start, samples + start, end - start) + + if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: + features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] + + n_found_constants += 1 + n_total_constants += 1 + + else: + f_i -= 1 + features[f_i], features[f_j] = features[f_j], features[f_i] + + # Evaluate all splits + self.criterion.reset() + p = start + + while p < end: + while (p + 1 < end and + Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): + p += 1 + + # (p + 1 >= end) or (X[samples[p + 1], current.feature] > + # X[samples[p], current.feature]) + p += 1 + # (p >= end) or (X[samples[p], current.feature] > + # X[samples[p - 1], current.feature]) + + if p < end: + current.pos = p + + # Reject if min_samples_leaf is not guaranteed + if (((current.pos - start) < min_samples_leaf) or + ((end - current.pos) < min_samples_leaf)): + continue + + self.criterion.update(current.pos) + + # Reject if min_weight_leaf is not satisfied + if ((self.criterion.weighted_n_left < min_weight_leaf) or + (self.criterion.weighted_n_right < min_weight_leaf)): + continue + + current_proxy_improvement = self.criterion.proxy_impurity_improvement() + + # with gil: + # print("feature ", current.feature) + # print("threshold ", current.threshold) + # print("proxy ", current_proxy_improvement) + # print() + + if current_proxy_improvement > best_proxy_improvement: + best_proxy_improvement = current_proxy_improvement + # sum of halves is used to avoid infinite value + current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 + + if ((current.threshold == Xf[p]) or + (current.threshold == INFINITY) or + (current.threshold == -INFINITY)): + current.threshold = Xf[p - 1] + + best = current # copy + + # Reorganize into samples[start:best.pos] + samples[best.pos:end] + if best.pos < end: + partition_end = end + p = start + + while p < partition_end: + if self.X[samples[p], best.feature] <= best.threshold: + p += 1 + + else: + partition_end -= 1 + + samples[p], samples[partition_end] = samples[partition_end], samples[p] + + self.criterion.reset() + self.criterion.update(best.pos) + best.improvement = self.criterion.impurity_improvement(impurity) + self.criterion.children_impurity(&best.impurity_left, + &best.impurity_right) + + # Respect invariant for constant features: the original order of + # element in features[:n_known_constants] must be preserved for sibling + # and child nodes + memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) + + # Copy newly found constant features + memcpy(constant_features + n_known_constants, + features + n_known_constants, + sizeof(SIZE_t) * n_found_constants) + + # Return values + split[0] = best + n_constant_features[0] = n_total_constants + return 0 + + +# Sort n-element arrays pointed to by Xf and samples, simultaneously, +# by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). +cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: if n == 0: return cdef int maxd = 2 * log(n) - introsort(feature_values, samples, n, maxd) + introsort(Xf, samples, n, maxd) -cdef inline void swap(DTYPE_t* feature_values, SIZE_t* samples, - SIZE_t i, SIZE_t j) noexcept nogil: +cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples, + SIZE_t i, SIZE_t j) nogil: # Helper for sort - feature_values[i], feature_values[j] = feature_values[j], feature_values[i] + Xf[i], Xf[j] = Xf[j], Xf[i] samples[i], samples[j] = samples[j], samples[i] -cdef inline DTYPE_t median3(DTYPE_t* feature_values, SIZE_t n) noexcept nogil: +cdef inline DTYPE_t median3(DTYPE_t* Xf, SIZE_t n) nogil: # Median of three pivot selection, after Bentley and McIlroy (1993). # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. - cdef DTYPE_t a = feature_values[0], b = feature_values[n / 2], c = feature_values[n - 1] + cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] if a < b: if b < c: return b @@ -451,42 +485,42 @@ cdef inline DTYPE_t median3(DTYPE_t* feature_values, SIZE_t n) noexcept nogil: # Introsort with median of 3 pivot selection and 3-way partition function # (robust to repeated elements, e.g. lots of zero features). -cdef void introsort(DTYPE_t* feature_values, SIZE_t *samples, - SIZE_t n, int maxd) noexcept nogil: +cdef void introsort(DTYPE_t* Xf, SIZE_t *samples, + SIZE_t n, int maxd) nogil: cdef DTYPE_t pivot cdef SIZE_t i, l, r while n > 1: if maxd <= 0: # max depth limit exceeded ("gone quadratic") - heapsort(feature_values, samples, n) + heapsort(Xf, samples, n) return maxd -= 1 - pivot = median3(feature_values, n) + pivot = median3(Xf, n) # Three-way partition. i = l = 0 r = n while i < r: - if feature_values[i] < pivot: - swap(feature_values, samples, i, l) + if Xf[i] < pivot: + swap(Xf, samples, i, l) i += 1 l += 1 - elif feature_values[i] > pivot: + elif Xf[i] > pivot: r -= 1 - swap(feature_values, samples, i, r) + swap(Xf, samples, i, r) else: i += 1 - introsort(feature_values, samples, l, maxd) - feature_values += r + introsort(Xf, samples, l, maxd) + Xf += r samples += r n -= r -cdef inline void sift_down(DTYPE_t* feature_values, SIZE_t* samples, - SIZE_t start, SIZE_t end) noexcept nogil: - # Restore heap order in feature_values[start:end] by moving the max element to start. +cdef inline void sift_down(DTYPE_t* Xf, SIZE_t* samples, + SIZE_t start, SIZE_t end) nogil: + # Restore heap order in Xf[start:end] by moving the max element to start. cdef SIZE_t child, maxind, root root = start @@ -495,26 +529,26 @@ cdef inline void sift_down(DTYPE_t* feature_values, SIZE_t* samples, # find max of root, left child, right child maxind = root - if child < end and feature_values[maxind] < feature_values[child]: + if child < end and Xf[maxind] < Xf[child]: maxind = child - if child + 1 < end and feature_values[maxind] < feature_values[child + 1]: + if child + 1 < end and Xf[maxind] < Xf[child + 1]: maxind = child + 1 if maxind == root: break else: - swap(feature_values, samples, root, maxind) + swap(Xf, samples, root, maxind) root = maxind -cdef void heapsort(DTYPE_t* feature_values, SIZE_t* samples, SIZE_t n) noexcept nogil: +cdef void heapsort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: cdef SIZE_t start, end # heapify start = (n - 2) / 2 end = n while True: - sift_down(feature_values, samples, start, end) + sift_down(Xf, samples, start, end) if start == 0: break start -= 1 @@ -522,522 +556,321 @@ cdef void heapsort(DTYPE_t* feature_values, SIZE_t* samples, SIZE_t n) noexcept # sort by shrinking the heap, putting the max element immediately after it end = n - 1 while end > 0: - swap(feature_values, samples, 0, end) - sift_down(feature_values, samples, 0, end) + swap(Xf, samples, 0, end) + sift_down(Xf, samples, 0, end) end = end - 1 -cdef inline int node_split_random( - Splitter splitter, - Partitioner partitioner, - Criterion criterion, - double impurity, - SplitRecord* split, - SIZE_t* n_constant_features -) except -1 nogil: - """Find the best random split on node samples[start:end] - - Returns -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - # Draw random splits and pick the best - cdef SIZE_t start = splitter.start - cdef SIZE_t end = splitter.end - - cdef SIZE_t[::1] features = splitter.features - cdef SIZE_t[::1] constant_features = splitter.constant_features - cdef SIZE_t n_features = splitter.n_features - - cdef SIZE_t max_features = splitter.max_features - cdef SIZE_t min_samples_leaf = splitter.min_samples_leaf - cdef double min_weight_leaf = splitter.min_weight_leaf - cdef UINT32_t* random_state = &splitter.rand_r_state - - cdef SplitRecord best_split, current_split - cdef double current_proxy_improvement = - INFINITY - cdef double best_proxy_improvement = - INFINITY - - cdef SIZE_t f_i = n_features - cdef SIZE_t f_j - # Number of features discovered to be constant during the split search - cdef SIZE_t n_found_constants = 0 - # Number of features known to be constant and drawn without replacement - cdef SIZE_t n_drawn_constants = 0 - cdef SIZE_t n_known_constants = n_constant_features[0] - # n_total_constants = n_known_constants + n_found_constants - cdef SIZE_t n_total_constants = n_known_constants - cdef SIZE_t n_visited_features = 0 - cdef DTYPE_t min_feature_value - cdef DTYPE_t max_feature_value - - _init_split(&best_split, end) - - partitioner.init_node_split(start, end) - - # Sample up to max_features without replacement using a - # Fisher-Yates-based algorithm (using the local variables `f_i` and - # `f_j` to compute a permutation of the `features` array). - # - # Skip the CPU intensive evaluation of the impurity criterion for - # features that were already detected as constant (hence not suitable - # for good splitting) by ancestor nodes and save the information on - # newly discovered constant features to spare computation on descendant - # nodes. - while (f_i > n_total_constants and # Stop early if remaining features - # are constant - (n_visited_features < max_features or - # At least one drawn features must be non constant - n_visited_features <= n_found_constants + n_drawn_constants)): - n_visited_features += 1 - - # Loop invariant: elements of features in - # - [:n_drawn_constant[ holds drawn and known constant features; - # - [n_drawn_constant:n_known_constant[ holds known constant - # features that haven't been drawn yet; - # - [n_known_constant:n_total_constant[ holds newly found constant - # features; - # - [n_total_constant:f_i[ holds features that haven't been drawn - # yet and aren't constant apriori. - # - [f_i:n_features[ holds features that have been drawn - # and aren't constant. - - # Draw a feature at random - f_j = rand_int(n_drawn_constants, f_i - n_found_constants, - random_state) - - if f_j < n_known_constants: - # f_j in the interval [n_drawn_constants, n_known_constants[ - features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] - n_drawn_constants += 1 - continue - - # f_j in the interval [n_known_constants, f_i - n_found_constants[ - f_j += n_found_constants - # f_j in the interval [n_total_constants, f_i[ - - current_split.feature = features[f_j] - - # Find min, max - partitioner.find_min_max( - current_split.feature, &min_feature_value, &max_feature_value - ) - - if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: - features[f_j], features[n_total_constants] = features[n_total_constants], current_split.feature - - n_found_constants += 1 - n_total_constants += 1 - continue - - f_i -= 1 - features[f_i], features[f_j] = features[f_j], features[f_i] - - # Draw a random threshold - current_split.threshold = rand_uniform( - min_feature_value, - max_feature_value, - random_state, - ) - - if current_split.threshold == max_feature_value: - current_split.threshold = min_feature_value - - # Partition - current_split.pos = partitioner.partition_samples(current_split.threshold) - - # Reject if min_samples_leaf is not guaranteed - if (((current_split.pos - start) < min_samples_leaf) or - ((end - current_split.pos) < min_samples_leaf)): - continue - - # Evaluate split - # At this point, the criterion has a view into the samples that was partitioned - # by the partitioner. The criterion will use the parition to evaluating the split. - criterion.reset() - criterion.update(current_split.pos) - - # Reject if min_weight_leaf is not satisfied - if ((criterion.weighted_n_left < min_weight_leaf) or - (criterion.weighted_n_right < min_weight_leaf)): - continue - - current_proxy_improvement = criterion.proxy_impurity_improvement() - - if current_proxy_improvement > best_proxy_improvement: - best_proxy_improvement = current_proxy_improvement - best_split = current_split # copy - - # Reorganize into samples[start:best_split.pos] + samples[best_split.pos:end] - if best_split.pos < end: - if current_split.feature != best_split.feature: - partitioner.partition_samples_final( - best_split.pos, best_split.threshold, best_split.feature - ) - - criterion.reset() - criterion.update(best_split.pos) - criterion.children_impurity( - &best_split.impurity_left, &best_split.impurity_right - ) - best_split.improvement = criterion.impurity_improvement( - impurity, best_split.impurity_left, best_split.impurity_right - ) - - # Respect invariant for constant features: the original order of - # element in features[:n_known_constants] must be preserved for sibling - # and child nodes - memcpy(&features[0], &constant_features[0], sizeof(SIZE_t) * n_known_constants) - - # Copy newly found constant features - memcpy(&constant_features[n_known_constants], - &features[n_known_constants], - sizeof(SIZE_t) * n_found_constants) - - # Return values - split[0] = best_split - n_constant_features[0] = n_total_constants - return 0 - - -@final -cdef class DensePartitioner: - """Partitioner specialized for dense data. - - Note that this partitioner is agnostic to the splitting strategy (best vs. random). - """ - cdef: - const DTYPE_t[:, :] X - cdef SIZE_t[::1] samples - cdef DTYPE_t[::1] feature_values - cdef SIZE_t start - cdef SIZE_t end - - def __init__( - self, - const DTYPE_t[:, :] X, - SIZE_t[::1] samples, - DTYPE_t[::1] feature_values, - ): - self.X = X - self.samples = samples - self.feature_values = feature_values - cdef inline void init_node_split(self, SIZE_t start, SIZE_t end) noexcept nogil: - """Initialize splitter at the beginning of node_split.""" - self.start = start - self.end = end +cdef class RandomSplitter(BaseDenseSplitter): + """Splitter for finding the best random split.""" + def __reduce__(self): + return (RandomSplitter, (self.criterion, + self.max_features, + self.min_samples_leaf, + self.min_weight_leaf, + self.random_state), self.__getstate__()) - cdef inline void sort_samples_and_feature_values( - self, SIZE_t current_feature - ) noexcept nogil: - """Simultaneously sort based on the feature_values.""" - cdef: - SIZE_t i - DTYPE_t[::1] feature_values = self.feature_values - const DTYPE_t[:, :] X = self.X - SIZE_t[::1] samples = self.samples - - # Sort samples along that feature; by - # copying the values into an array and - # sorting the array in a manner which utilizes the cache more - # effectively. - for i in range(self.start, self.end): - feature_values[i] = X[samples[i], current_feature] - sort(&feature_values[self.start], &samples[self.start], self.end - self.start) - - cdef inline void find_min_max( - self, - SIZE_t current_feature, - DTYPE_t* min_feature_value_out, - DTYPE_t* max_feature_value_out, - ) noexcept nogil: - """Find the minimum and maximum value for current_feature.""" - cdef: - SIZE_t p - DTYPE_t current_feature_value - const DTYPE_t[:, :] X = self.X - SIZE_t[::1] samples = self.samples - DTYPE_t min_feature_value = X[samples[self.start], current_feature] - DTYPE_t max_feature_value = min_feature_value - DTYPE_t[::1] feature_values = self.feature_values - - feature_values[self.start] = min_feature_value - - for p in range(self.start + 1, self.end): - current_feature_value = X[samples[p], current_feature] - feature_values[p] = current_feature_value - - if current_feature_value < min_feature_value: - min_feature_value = current_feature_value - elif current_feature_value > max_feature_value: - max_feature_value = current_feature_value - - min_feature_value_out[0] = min_feature_value - max_feature_value_out[0] = max_feature_value - - cdef inline void next_p(self, SIZE_t* p_prev, SIZE_t* p) noexcept nogil: - """Compute the next p_prev and p for iteratiing over feature values.""" - cdef DTYPE_t[::1] feature_values = self.feature_values - - while ( - p[0] + 1 < self.end and - feature_values[p[0] + 1] <= feature_values[p[0]] + FEATURE_THRESHOLD - ): - p[0] += 1 - - p_prev[0] = p[0] - - # By adding 1, we have - # (feature_values[p] >= end) or (feature_values[p] > feature_values[p - 1]) - p[0] += 1 - - cdef inline SIZE_t partition_samples(self, double current_threshold) noexcept nogil: - """Partition samples for feature_values at the current_threshold.""" - cdef: - SIZE_t p = self.start - SIZE_t partition_end = self.end - SIZE_t[::1] samples = self.samples - DTYPE_t[::1] feature_values = self.feature_values + cdef int node_split(self, double impurity, SplitRecord* split, + SIZE_t* n_constant_features) nogil except -1: + """Find the best random split on node samples[start:end] + + Returns -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + # Draw random splits and pick the best + cdef SIZE_t* samples = self.samples + cdef SIZE_t start = self.start + cdef SIZE_t end = self.end + + cdef SIZE_t* features = self.features + cdef SIZE_t* constant_features = self.constant_features + cdef SIZE_t n_features = self.n_features + + cdef DTYPE_t* Xf = self.feature_values + cdef SIZE_t max_features = self.max_features + cdef SIZE_t min_samples_leaf = self.min_samples_leaf + cdef double min_weight_leaf = self.min_weight_leaf + cdef UINT32_t* random_state = &self.rand_r_state + + cdef SplitRecord best, current + cdef double current_proxy_improvement = - INFINITY + cdef double best_proxy_improvement = - INFINITY + + cdef SIZE_t f_i = n_features + cdef SIZE_t f_j + cdef SIZE_t p + cdef SIZE_t partition_end + cdef SIZE_t feature_stride + # Number of features discovered to be constant during the split search + cdef SIZE_t n_found_constants = 0 + # Number of features known to be constant and drawn without replacement + cdef SIZE_t n_drawn_constants = 0 + cdef SIZE_t n_known_constants = n_constant_features[0] + # n_total_constants = n_known_constants + n_found_constants + cdef SIZE_t n_total_constants = n_known_constants + cdef SIZE_t n_visited_features = 0 + cdef DTYPE_t min_feature_value + cdef DTYPE_t max_feature_value + cdef DTYPE_t current_feature_value + + _init_split(&best, end) + + # Sample up to max_features without replacement using a + # Fisher-Yates-based algorithm (using the local variables `f_i` and + # `f_j` to compute a permutation of the `features` array). + # + # Skip the CPU intensive evaluation of the impurity criterion for + # features that were already detected as constant (hence not suitable + # for good splitting) by ancestor nodes and save the information on + # newly discovered constant features to spare computation on descendant + # nodes. + while (f_i > n_total_constants and # Stop early if remaining features + # are constant + (n_visited_features < max_features or + # At least one drawn features must be non constant + n_visited_features <= n_found_constants + n_drawn_constants)): + n_visited_features += 1 + + # Loop invariant: elements of features in + # - [:n_drawn_constant[ holds drawn and known constant features; + # - [n_drawn_constant:n_known_constant[ holds known constant + # features that haven't been drawn yet; + # - [n_known_constant:n_total_constant[ holds newly found constant + # features; + # - [n_total_constant:f_i[ holds features that haven't been drawn + # yet and aren't constant apriori. + # - [f_i:n_features[ holds features that have been drawn + # and aren't constant. + + # Draw a feature at random + f_j = rand_int(n_drawn_constants, f_i - n_found_constants, + random_state) + + if f_j < n_known_constants: + # f_j in the interval [n_drawn_constants, n_known_constants[ + features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] + n_drawn_constants += 1 - while p < partition_end: - if feature_values[p] <= current_threshold: - p += 1 else: - partition_end -= 1 + # f_j in the interval [n_known_constants, f_i - n_found_constants[ + f_j += n_found_constants + # f_j in the interval [n_total_constants, f_i[ + + current.feature = features[f_j] + + # Find min, max + min_feature_value = self.X[samples[start], current.feature] + max_feature_value = min_feature_value + Xf[start] = min_feature_value + + for p in range(start + 1, end): + current_feature_value = self.X[samples[p], current.feature] + Xf[p] = current_feature_value + + if current_feature_value < min_feature_value: + min_feature_value = current_feature_value + elif current_feature_value > max_feature_value: + max_feature_value = current_feature_value + + if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: + features[f_j], features[n_total_constants] = features[n_total_constants], current.feature + + n_found_constants += 1 + n_total_constants += 1 + + else: + f_i -= 1 + features[f_i], features[f_j] = features[f_j], features[f_i] + + # Draw a random threshold + current.threshold = rand_uniform(min_feature_value, + max_feature_value, + random_state) + + if current.threshold == max_feature_value: + current.threshold = min_feature_value + + # Partition + p, partition_end = start, end + while p < partition_end: + if Xf[p] <= current.threshold: + p += 1 + else: + partition_end -= 1 + + Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] + samples[p], samples[partition_end] = samples[partition_end], samples[p] + + current.pos = partition_end + + # Reject if min_samples_leaf is not guaranteed + if (((current.pos - start) < min_samples_leaf) or + ((end - current.pos) < min_samples_leaf)): + continue + + # Evaluate split + self.criterion.reset() + self.criterion.update(current.pos) + + # Reject if min_weight_leaf is not satisfied + if ((self.criterion.weighted_n_left < min_weight_leaf) or + (self.criterion.weighted_n_right < min_weight_leaf)): + continue + + current_proxy_improvement = self.criterion.proxy_impurity_improvement() + + if current_proxy_improvement > best_proxy_improvement: + best_proxy_improvement = current_proxy_improvement + best = current # copy + + # Reorganize into samples[start:best.pos] + samples[best.pos:end] + if best.pos < end: + if current.feature != best.feature: + p, partition_end = start, end + + while p < partition_end: + if self.X[samples[p], best.feature] <= best.threshold: + p += 1 + else: + partition_end -= 1 + + samples[p], samples[partition_end] = samples[partition_end], samples[p] + + self.criterion.reset() + self.criterion.update(best.pos) + best.improvement = self.criterion.impurity_improvement(impurity) + self.criterion.children_impurity(&best.impurity_left, + &best.impurity_right) + + # Respect invariant for constant features: the original order of + # element in features[:n_known_constants] must be preserved for sibling + # and child nodes + memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) + + # Copy newly found constant features + memcpy(constant_features + n_known_constants, + features + n_known_constants, + sizeof(SIZE_t) * n_found_constants) + + # Return values + split[0] = best + n_constant_features[0] = n_total_constants + return 0 - feature_values[p], feature_values[partition_end] = ( - feature_values[partition_end], feature_values[p] - ) - samples[p], samples[partition_end] = samples[partition_end], samples[p] - return partition_end +cdef class BaseSparseSplitter(Splitter): + # The sparse splitter works only with csc sparse matrix format + cdef DTYPE_t* X_data + cdef INT32_t* X_indices + cdef INT32_t* X_indptr - cdef inline void partition_samples_final( - self, - SIZE_t best_pos, - double best_threshold, - SIZE_t best_feature, - ) noexcept nogil: - """Partition samples for X at the best_threshold and best_feature.""" - cdef: - SIZE_t p = self.start - SIZE_t partition_end = self.end - SIZE_t[::1] samples = self.samples - const DTYPE_t[:, :] X = self.X + cdef SIZE_t n_total_samples - while p < partition_end: - if X[samples[p], best_feature] <= best_threshold: - p += 1 - else: - partition_end -= 1 - samples[p], samples[partition_end] = samples[partition_end], samples[p] + cdef SIZE_t* index_to_samples + cdef SIZE_t* sorted_samples -@final -cdef class SparsePartitioner: - """Partitioner specialized for sparse CSC data. + def __cinit__(self, Criterion criterion, SIZE_t max_features, + SIZE_t min_samples_leaf, double min_weight_leaf, + object random_state): + # Parent __cinit__ is automatically called - Note that this partitioner is agnostic to the splitting strategy (best vs. random). - """ - cdef SIZE_t[::1] samples - cdef DTYPE_t[::1] feature_values - cdef SIZE_t start - cdef SIZE_t end + self.X_data = NULL + self.X_indices = NULL + self.X_indptr = NULL - cdef const DTYPE_t[::1] X_data - cdef const INT32_t[::1] X_indices - cdef const INT32_t[::1] X_indptr + self.n_total_samples = 0 - cdef SIZE_t n_total_samples + self.index_to_samples = NULL + self.sorted_samples = NULL - cdef SIZE_t[::1] index_to_samples - cdef SIZE_t[::1] sorted_samples + def __dealloc__(self): + """Deallocate memory.""" + free(self.index_to_samples) + free(self.sorted_samples) - cdef SIZE_t start_positive - cdef SIZE_t end_negative - cdef bint is_samples_sorted + cdef int init(self, + object X, + const DOUBLE_t[:, ::1] y, + DOUBLE_t* sample_weight) except -1: + """Initialize the splitter + + Returns -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + # Call parent init + Splitter.init(self, X, y, sample_weight) - def __init__( - self, - object X, - SIZE_t[::1] samples, - SIZE_t n_samples, - DTYPE_t[::1] feature_values, - ): if not isinstance(X, csc_matrix): raise ValueError("X should be in csc format") - self.samples = samples - self.feature_values = feature_values + cdef SIZE_t* samples = self.samples + cdef SIZE_t n_samples = self.n_samples # Initialize X + cdef np.ndarray[dtype=DTYPE_t, ndim=1] data = X.data + cdef np.ndarray[dtype=INT32_t, ndim=1] indices = X.indices + cdef np.ndarray[dtype=INT32_t, ndim=1] indptr = X.indptr cdef SIZE_t n_total_samples = X.shape[0] - self.X_data = X.data - self.X_indices = X.indices - self.X_indptr = X.indptr + self.X_data = data.data + self.X_indices = indices.data + self.X_indptr = indptr.data self.n_total_samples = n_total_samples # Initialize auxiliary array used to perform split - self.index_to_samples = np.full(n_total_samples, fill_value=-1, dtype=np.intp) - self.sorted_samples = np.empty(n_samples, dtype=np.intp) + safe_realloc(&self.index_to_samples, n_total_samples) + safe_realloc(&self.sorted_samples, n_samples) + cdef SIZE_t* index_to_samples = self.index_to_samples cdef SIZE_t p - for p in range(n_samples): - self.index_to_samples[samples[p]] = p + for p in range(n_total_samples): + index_to_samples[p] = -1 - cdef inline void init_node_split(self, SIZE_t start, SIZE_t end) noexcept nogil: - """Initialize splitter at the beginning of node_split.""" - self.start = start - self.end = end - self.is_samples_sorted = 0 - - cdef inline void sort_samples_and_feature_values( - self, SIZE_t current_feature - ) noexcept nogil: - """Simultaneously sort based on the feature_values.""" - cdef: - DTYPE_t[::1] feature_values = self.feature_values - SIZE_t[::1] index_to_samples = self.index_to_samples - SIZE_t[::1] samples = self.samples - - self.extract_nnz(current_feature) - # Sort the positive and negative parts of `feature_values` - sort(&feature_values[self.start], &samples[self.start], self.end_negative - self.start) - if self.start_positive < self.end: - sort(&feature_values[self.start_positive], &samples[self.start_positive], - self.end - self.start_positive) - - # Update index_to_samples to take into account the sort - for p in range(self.start, self.end_negative): - index_to_samples[samples[p]] = p - for p in range(self.start_positive, self.end): + for p in range(n_samples): index_to_samples[samples[p]] = p + return 0 - # Add one or two zeros in feature_values, if there is any - if self.end_negative < self.start_positive: - self.start_positive -= 1 - feature_values[self.start_positive] = 0. - - if self.end_negative != self.start_positive: - feature_values[self.end_negative] = 0. - self.end_negative += 1 - - cdef inline void find_min_max( - self, - SIZE_t current_feature, - DTYPE_t* min_feature_value_out, - DTYPE_t* max_feature_value_out, - ) noexcept nogil: - """Find the minimum and maximum value for current_feature.""" - cdef: - SIZE_t p - DTYPE_t current_feature_value, min_feature_value, max_feature_value - DTYPE_t[::1] feature_values = self.feature_values - - self.extract_nnz(current_feature) - - if self.end_negative != self.start_positive: - # There is a zero - min_feature_value = 0 - max_feature_value = 0 - else: - min_feature_value = feature_values[self.start] - max_feature_value = min_feature_value - - # Find min, max in feature_values[start:end_negative] - for p in range(self.start, self.end_negative): - current_feature_value = feature_values[p] - - if current_feature_value < min_feature_value: - min_feature_value = current_feature_value - elif current_feature_value > max_feature_value: - max_feature_value = current_feature_value - - # Update min, max given feature_values[start_positive:end] - for p in range(self.start_positive, self.end): - current_feature_value = feature_values[p] - - if current_feature_value < min_feature_value: - min_feature_value = current_feature_value - elif current_feature_value > max_feature_value: - max_feature_value = current_feature_value - - min_feature_value_out[0] = min_feature_value - max_feature_value_out[0] = max_feature_value - - cdef inline void next_p(self, SIZE_t* p_prev, SIZE_t* p) noexcept nogil: - """Compute the next p_prev and p for iteratiing over feature values.""" - cdef: - SIZE_t p_next - DTYPE_t[::1] feature_values = self.feature_values - - if p[0] + 1 != self.end_negative: - p_next = p[0] + 1 - else: - p_next = self.start_positive - - while (p_next < self.end and - feature_values[p_next] <= feature_values[p[0]] + FEATURE_THRESHOLD): - p[0] = p_next - if p[0] + 1 != self.end_negative: - p_next = p[0] + 1 - else: - p_next = self.start_positive - - p_prev[0] = p[0] - p[0] = p_next - - cdef inline SIZE_t partition_samples(self, double current_threshold) noexcept nogil: - """Partition samples for feature_values at the current_threshold.""" - return self._partition(current_threshold, self.start_positive) - - cdef inline void partition_samples_final( - self, - SIZE_t best_pos, - double best_threshold, - SIZE_t best_feature, - ) noexcept nogil: - """Partition samples for X at the best_threshold and best_feature.""" - self.extract_nnz(best_feature) - self._partition(best_threshold, best_pos) - - cdef inline SIZE_t _partition(self, double threshold, SIZE_t zero_pos) noexcept nogil: + cdef inline SIZE_t _partition(self, double threshold, + SIZE_t end_negative, SIZE_t start_positive, + SIZE_t zero_pos) nogil: """Partition samples[start:end] based on threshold.""" - cdef: - SIZE_t p, partition_end - SIZE_t[::1] index_to_samples = self.index_to_samples - DTYPE_t[::1] feature_values = self.feature_values - SIZE_t[::1] samples = self.samples + + cdef SIZE_t p + cdef SIZE_t partition_end + + cdef DTYPE_t* Xf = self.feature_values + cdef SIZE_t* samples = self.samples + cdef SIZE_t* index_to_samples = self.index_to_samples if threshold < 0.: p = self.start - partition_end = self.end_negative + partition_end = end_negative elif threshold > 0.: - p = self.start_positive + p = start_positive partition_end = self.end else: # Data are already split return zero_pos while p < partition_end: - if feature_values[p] <= threshold: + if Xf[p] <= threshold: p += 1 else: partition_end -= 1 - feature_values[p], feature_values[partition_end] = ( - feature_values[partition_end], feature_values[p] - ) + Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] sparse_swap(index_to_samples, samples, p, partition_end) return partition_end - cdef inline void extract_nnz(self, SIZE_t feature) noexcept nogil: + cdef inline void extract_nnz(self, SIZE_t feature, + SIZE_t* end_negative, SIZE_t* start_positive, + bint* is_samples_sorted) nogil: """Extract and partition values for a given feature. The extracted values are partitioned between negative values - feature_values[start:end_negative[0]] and positive values - feature_values[start_positive[0]:end]. + Xf[start:end_negative[0]] and positive values Xf[start_positive[0]:end]. The samples and index_to_samples are modified according to this partition. @@ -1050,53 +883,59 @@ cdef class SparsePartitioner: ---------- feature : SIZE_t, Index of the feature we want to extract non zero value. + + + end_negative, start_positive : SIZE_t*, SIZE_t*, + Return extracted non zero values in self.samples[start:end] where + negative values are in self.feature_values[start:end_negative[0]] + and positive values are in + self.feature_values[start_positive[0]:end]. + + is_samples_sorted : bint*, + If is_samples_sorted, then self.sorted_samples[start:end] will be + the sorted version of self.samples[start:end]. + """ - cdef SIZE_t[::1] samples = self.samples - cdef DTYPE_t[::1] feature_values = self.feature_values cdef SIZE_t indptr_start = self.X_indptr[feature], cdef SIZE_t indptr_end = self.X_indptr[feature + 1] cdef SIZE_t n_indices = (indptr_end - indptr_start) cdef SIZE_t n_samples = self.end - self.start - cdef SIZE_t[::1] index_to_samples = self.index_to_samples - cdef SIZE_t[::1] sorted_samples = self.sorted_samples - cdef const INT32_t[::1] X_indices = self.X_indices - cdef const DTYPE_t[::1] X_data = self.X_data # Use binary search if n_samples * log(n_indices) < # n_indices and index_to_samples approach otherwise. # O(n_samples * log(n_indices)) is the running time of binary # search and O(n_indices) is the running time of index_to_samples # approach. - if ((1 - self.is_samples_sorted) * n_samples * log(n_samples) + + if ((1 - is_samples_sorted[0]) * n_samples * log(n_samples) + n_samples * log(n_indices) < EXTRACT_NNZ_SWITCH * n_indices): - extract_nnz_binary_search(X_indices, X_data, + extract_nnz_binary_search(self.X_indices, self.X_data, indptr_start, indptr_end, - samples, self.start, self.end, - index_to_samples, - feature_values, - &self.end_negative, &self.start_positive, - sorted_samples, &self.is_samples_sorted) + self.samples, self.start, self.end, + self.index_to_samples, + self.feature_values, + end_negative, start_positive, + self.sorted_samples, is_samples_sorted) # Using an index to samples technique to extract non zero values # index_to_samples is a mapping from X_indices to samples else: - extract_nnz_index_to_samples(X_indices, X_data, + extract_nnz_index_to_samples(self.X_indices, self.X_data, indptr_start, indptr_end, - samples, self.start, self.end, - index_to_samples, - feature_values, - &self.end_negative, &self.start_positive) + self.samples, self.start, self.end, + self.index_to_samples, + self.feature_values, + end_negative, start_positive) -cdef int compare_SIZE_t(const void* a, const void* b) noexcept nogil: +cdef int compare_SIZE_t(const void* a, const void* b) nogil: """Comparison function for sort.""" return ((a)[0] - (b)[0]) -cdef inline void binary_search(const INT32_t[::1] sorted_array, +cdef inline void binary_search(INT32_t* sorted_array, INT32_t start, INT32_t end, SIZE_t value, SIZE_t* index, - INT32_t* new_start) noexcept nogil: + INT32_t* new_start) nogil: """Return the index of value in the sorted array. If not found, return -1. new_start is the last pivot + 1 @@ -1118,17 +957,17 @@ cdef inline void binary_search(const INT32_t[::1] sorted_array, new_start[0] = start -cdef inline void extract_nnz_index_to_samples(const INT32_t[::1] X_indices, - const DTYPE_t[::1] X_data, +cdef inline void extract_nnz_index_to_samples(INT32_t* X_indices, + DTYPE_t* X_data, INT32_t indptr_start, INT32_t indptr_end, - SIZE_t[::1] samples, + SIZE_t* samples, SIZE_t start, SIZE_t end, - SIZE_t[::1] index_to_samples, - DTYPE_t[::1] feature_values, + SIZE_t* index_to_samples, + DTYPE_t* Xf, SIZE_t* end_negative, - SIZE_t* start_positive) noexcept nogil: + SIZE_t* start_positive) nogil: """Extract and partition values for a feature using index_to_samples. Complexity is O(indptr_end - indptr_start). @@ -1142,13 +981,13 @@ cdef inline void extract_nnz_index_to_samples(const INT32_t[::1] X_indices, if start <= index_to_samples[X_indices[k]] < end: if X_data[k] > 0: start_positive_ -= 1 - feature_values[start_positive_] = X_data[k] + Xf[start_positive_] = X_data[k] index = index_to_samples[X_indices[k]] sparse_swap(index_to_samples, samples, index, start_positive_) elif X_data[k] < 0: - feature_values[end_negative_] = X_data[k] + Xf[end_negative_] = X_data[k] index = index_to_samples[X_indices[k]] sparse_swap(index_to_samples, samples, index, end_negative_) end_negative_ += 1 @@ -1158,19 +997,19 @@ cdef inline void extract_nnz_index_to_samples(const INT32_t[::1] X_indices, start_positive[0] = start_positive_ -cdef inline void extract_nnz_binary_search(const INT32_t[::1] X_indices, - const DTYPE_t[::1] X_data, +cdef inline void extract_nnz_binary_search(INT32_t* X_indices, + DTYPE_t* X_data, INT32_t indptr_start, INT32_t indptr_end, - SIZE_t[::1] samples, + SIZE_t* samples, SIZE_t start, SIZE_t end, - SIZE_t[::1] index_to_samples, - DTYPE_t[::1] feature_values, + SIZE_t* index_to_samples, + DTYPE_t* Xf, SIZE_t* end_negative, SIZE_t* start_positive, - SIZE_t[::1] sorted_samples, - bint* is_samples_sorted) noexcept nogil: + SIZE_t* sorted_samples, + bint* is_samples_sorted) nogil: """Extract and partition values for a given feature using binary search. If n_samples = end - start and n_indices = indptr_end - indptr_start, @@ -1183,9 +1022,9 @@ cdef inline void extract_nnz_binary_search(const INT32_t[::1] X_indices, if not is_samples_sorted[0]: n_samples = end - start - memcpy(&sorted_samples[start], &samples[start], + memcpy(sorted_samples + start, samples + start, n_samples * sizeof(SIZE_t)) - qsort(&sorted_samples[start], n_samples, sizeof(SIZE_t), + qsort(sorted_samples + start, n_samples, sizeof(SIZE_t), compare_SIZE_t) is_samples_sorted[0] = 1 @@ -1213,13 +1052,13 @@ cdef inline void extract_nnz_binary_search(const INT32_t[::1] X_indices, if X_data[k] > 0: start_positive_ -= 1 - feature_values[start_positive_] = X_data[k] + Xf[start_positive_] = X_data[k] index = index_to_samples[X_indices[k]] sparse_swap(index_to_samples, samples, index, start_positive_) elif X_data[k] < 0: - feature_values[end_negative_] = X_data[k] + Xf[end_negative_] = X_data[k] index = index_to_samples[X_indices[k]] sparse_swap(index_to_samples, samples, index, end_negative_) end_negative_ += 1 @@ -1230,106 +1069,466 @@ cdef inline void extract_nnz_binary_search(const INT32_t[::1] X_indices, start_positive[0] = start_positive_ -cdef inline void sparse_swap(SIZE_t[::1] index_to_samples, SIZE_t[::1] samples, - SIZE_t pos_1, SIZE_t pos_2) noexcept nogil: +cdef inline void sparse_swap(SIZE_t* index_to_samples, SIZE_t* samples, + SIZE_t pos_1, SIZE_t pos_2) nogil: """Swap sample pos_1 and pos_2 preserving sparse invariant.""" samples[pos_1], samples[pos_2] = samples[pos_2], samples[pos_1] index_to_samples[samples[pos_1]] = pos_1 index_to_samples[samples[pos_2]] = pos_2 -cdef class BestSplitter(Splitter): - """Splitter for finding the best split on dense data.""" - cdef DensePartitioner partitioner - cdef int init( - self, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight - ) except -1: - Splitter.init(self, X, y, sample_weight) - self.partitioner = DensePartitioner(X, self.samples, self.feature_values) - - cdef int node_split(self, double impurity, SplitRecord* split, - SIZE_t* n_constant_features) except -1 nogil: - return node_split_best( - self, - self.partitioner, - self.criterion, - impurity, - split, - n_constant_features, - ) - -cdef class BestSparseSplitter(Splitter): +cdef class BestSparseSplitter(BaseSparseSplitter): """Splitter for finding the best split, using the sparse data.""" - cdef SparsePartitioner partitioner - cdef int init( - self, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight - ) except -1: - Splitter.init(self, X, y, sample_weight) - self.partitioner = SparsePartitioner( - X, self.samples, self.n_samples, self.feature_values - ) - cdef int node_split(self, double impurity, SplitRecord* split, - SIZE_t* n_constant_features) except -1 nogil: - return node_split_best( - self, - self.partitioner, - self.criterion, - impurity, - split, - n_constant_features, - ) - -cdef class RandomSplitter(Splitter): - """Splitter for finding the best random split on dense data.""" - cdef DensePartitioner partitioner - cdef int init( - self, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight - ) except -1: - Splitter.init(self, X, y, sample_weight) - self.partitioner = DensePartitioner(X, self.samples, self.feature_values) + def __reduce__(self): + return (BestSparseSplitter, (self.criterion, + self.max_features, + self.min_samples_leaf, + self.min_weight_leaf, + self.random_state), self.__getstate__()) cdef int node_split(self, double impurity, SplitRecord* split, - SIZE_t* n_constant_features) except -1 nogil: - return node_split_random( - self, - self.partitioner, - self.criterion, - impurity, - split, - n_constant_features, - ) - -cdef class RandomSparseSplitter(Splitter): - """Splitter for finding the best random split, using the sparse data.""" - cdef SparsePartitioner partitioner - cdef int init( - self, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight - ) except -1: - Splitter.init(self, X, y, sample_weight) - self.partitioner = SparsePartitioner( - X, self.samples, self.n_samples, self.feature_values - ) + SIZE_t* n_constant_features) nogil except -1: + """Find the best split on node samples[start:end], using sparse features + + Returns -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + # Find the best split + cdef SIZE_t* samples = self.samples + cdef SIZE_t start = self.start + cdef SIZE_t end = self.end + + cdef INT32_t* X_indices = self.X_indices + cdef INT32_t* X_indptr = self.X_indptr + cdef DTYPE_t* X_data = self.X_data + + cdef SIZE_t* features = self.features + cdef SIZE_t* constant_features = self.constant_features + cdef SIZE_t n_features = self.n_features + + cdef DTYPE_t* Xf = self.feature_values + cdef SIZE_t* sorted_samples = self.sorted_samples + cdef SIZE_t* index_to_samples = self.index_to_samples + cdef SIZE_t max_features = self.max_features + cdef SIZE_t min_samples_leaf = self.min_samples_leaf + cdef double min_weight_leaf = self.min_weight_leaf + cdef UINT32_t* random_state = &self.rand_r_state + + cdef SplitRecord best, current + _init_split(&best, end) + cdef double current_proxy_improvement = - INFINITY + cdef double best_proxy_improvement = - INFINITY + + cdef SIZE_t f_i = n_features + cdef SIZE_t f_j, p + cdef SIZE_t n_visited_features = 0 + # Number of features discovered to be constant during the split search + cdef SIZE_t n_found_constants = 0 + # Number of features known to be constant and drawn without replacement + cdef SIZE_t n_drawn_constants = 0 + cdef SIZE_t n_known_constants = n_constant_features[0] + # n_total_constants = n_known_constants + n_found_constants + cdef SIZE_t n_total_constants = n_known_constants + cdef DTYPE_t current_feature_value + + cdef SIZE_t p_next + cdef SIZE_t p_prev + cdef bint is_samples_sorted = 0 # indicate is sorted_samples is + # inititialized + + # We assume implicitly that end_positive = end and + # start_negative = start + cdef SIZE_t start_positive + cdef SIZE_t end_negative + + # Sample up to max_features without replacement using a + # Fisher-Yates-based algorithm (using the local variables `f_i` and + # `f_j` to compute a permutation of the `features` array). + # + # Skip the CPU intensive evaluation of the impurity criterion for + # features that were already detected as constant (hence not suitable + # for good splitting) by ancestor nodes and save the information on + # newly discovered constant features to spare computation on descendant + # nodes. + while (f_i > n_total_constants and # Stop early if remaining features + # are constant + (n_visited_features < max_features or + # At least one drawn features must be non constant + n_visited_features <= n_found_constants + n_drawn_constants)): + + n_visited_features += 1 + + # Loop invariant: elements of features in + # - [:n_drawn_constant[ holds drawn and known constant features; + # - [n_drawn_constant:n_known_constant[ holds known constant + # features that haven't been drawn yet; + # - [n_known_constant:n_total_constant[ holds newly found constant + # features; + # - [n_total_constant:f_i[ holds features that haven't been drawn + # yet and aren't constant apriori. + # - [f_i:n_features[ holds features that have been drawn + # and aren't constant. + + # Draw a feature at random + f_j = rand_int(n_drawn_constants, f_i - n_found_constants, + random_state) + + if f_j < n_known_constants: + # f_j in the interval [n_drawn_constants, n_known_constants[ + features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] + + n_drawn_constants += 1 + + else: + # f_j in the interval [n_known_constants, f_i - n_found_constants[ + f_j += n_found_constants + # f_j in the interval [n_total_constants, f_i[ + + current.feature = features[f_j] + self.extract_nnz(current.feature, + &end_negative, &start_positive, + &is_samples_sorted) + + # Sort the positive and negative parts of `Xf` + sort(Xf + start, samples + start, end_negative - start) + sort(Xf + start_positive, samples + start_positive, + end - start_positive) + + # Update index_to_samples to take into account the sort + for p in range(start, end_negative): + index_to_samples[samples[p]] = p + for p in range(start_positive, end): + index_to_samples[samples[p]] = p + + # Add one or two zeros in Xf, if there is any + if end_negative < start_positive: + start_positive -= 1 + Xf[start_positive] = 0. + + if end_negative != start_positive: + Xf[end_negative] = 0. + end_negative += 1 + + if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: + features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] + + n_found_constants += 1 + n_total_constants += 1 + + else: + f_i -= 1 + features[f_i], features[f_j] = features[f_j], features[f_i] + + # Evaluate all splits + self.criterion.reset() + p = start + + while p < end: + if p + 1 != end_negative: + p_next = p + 1 + else: + p_next = start_positive + + while (p_next < end and + Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): + p = p_next + if p + 1 != end_negative: + p_next = p + 1 + else: + p_next = start_positive + + + # (p_next >= end) or (X[samples[p_next], current.feature] > + # X[samples[p], current.feature]) + p_prev = p + p = p_next + # (p >= end) or (X[samples[p], current.feature] > + # X[samples[p_prev], current.feature]) + + + if p < end: + current.pos = p + + # Reject if min_samples_leaf is not guaranteed + if (((current.pos - start) < min_samples_leaf) or + ((end - current.pos) < min_samples_leaf)): + continue + + self.criterion.update(current.pos) + + # Reject if min_weight_leaf is not satisfied + if ((self.criterion.weighted_n_left < min_weight_leaf) or + (self.criterion.weighted_n_right < min_weight_leaf)): + continue + + current_proxy_improvement = self.criterion.proxy_impurity_improvement() + + if current_proxy_improvement > best_proxy_improvement: + best_proxy_improvement = current_proxy_improvement + # sum of halves used to avoid infinite values + current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0 + + if ((current.threshold == Xf[p]) or + (current.threshold == INFINITY) or + (current.threshold == -INFINITY)): + current.threshold = Xf[p_prev] + + best = current + + # Reorganize into samples[start:best.pos] + samples[best.pos:end] + if best.pos < end: + self.extract_nnz(best.feature, &end_negative, &start_positive, + &is_samples_sorted) + + self._partition(best.threshold, end_negative, start_positive, + best.pos) + + self.criterion.reset() + self.criterion.update(best.pos) + best.improvement = self.criterion.impurity_improvement(impurity) + self.criterion.children_impurity(&best.impurity_left, + &best.impurity_right) + + # Respect invariant for constant features: the original order of + # element in features[:n_known_constants] must be preserved for sibling + # and child nodes + memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) + + # Copy newly found constant features + memcpy(constant_features + n_known_constants, + features + n_known_constants, + sizeof(SIZE_t) * n_found_constants) + + # Return values + split[0] = best + n_constant_features[0] = n_total_constants + return 0 + + +cdef class RandomSparseSplitter(BaseSparseSplitter): + """Splitter for finding a random split, using the sparse data.""" + + def __reduce__(self): + return (RandomSparseSplitter, (self.criterion, + self.max_features, + self.min_samples_leaf, + self.min_weight_leaf, + self.random_state), self.__getstate__()) cdef int node_split(self, double impurity, SplitRecord* split, - SIZE_t* n_constant_features) except -1 nogil: - return node_split_random( - self, - self.partitioner, - self.criterion, - impurity, - split, - n_constant_features, - ) + SIZE_t* n_constant_features) nogil except -1: + """Find a random split on node samples[start:end], using sparse features + + Returns -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + # Find the best split + cdef SIZE_t* samples = self.samples + cdef SIZE_t start = self.start + cdef SIZE_t end = self.end + + cdef INT32_t* X_indices = self.X_indices + cdef INT32_t* X_indptr = self.X_indptr + cdef DTYPE_t* X_data = self.X_data + + cdef SIZE_t* features = self.features + cdef SIZE_t* constant_features = self.constant_features + cdef SIZE_t n_features = self.n_features + + cdef DTYPE_t* Xf = self.feature_values + cdef SIZE_t* sorted_samples = self.sorted_samples + cdef SIZE_t* index_to_samples = self.index_to_samples + cdef SIZE_t max_features = self.max_features + cdef SIZE_t min_samples_leaf = self.min_samples_leaf + cdef double min_weight_leaf = self.min_weight_leaf + cdef UINT32_t* random_state = &self.rand_r_state + + cdef SplitRecord best, current + _init_split(&best, end) + cdef double current_proxy_improvement = - INFINITY + cdef double best_proxy_improvement = - INFINITY + + cdef DTYPE_t current_feature_value + + cdef SIZE_t f_i = n_features + cdef SIZE_t f_j, p + cdef SIZE_t n_visited_features = 0 + # Number of features discovered to be constant during the split search + cdef SIZE_t n_found_constants = 0 + # Number of features known to be constant and drawn without replacement + cdef SIZE_t n_drawn_constants = 0 + cdef SIZE_t n_known_constants = n_constant_features[0] + # n_total_constants = n_known_constants + n_found_constants + cdef SIZE_t n_total_constants = n_known_constants + cdef SIZE_t partition_end + + cdef DTYPE_t min_feature_value + cdef DTYPE_t max_feature_value + + cdef bint is_samples_sorted = 0 # indicate that sorted_samples is + # inititialized + + # We assume implicitly that end_positive = end and + # start_negative = start + cdef SIZE_t start_positive + cdef SIZE_t end_negative + + # Sample up to max_features without replacement using a + # Fisher-Yates-based algorithm (using the local variables `f_i` and + # `f_j` to compute a permutation of the `features` array). + # + # Skip the CPU intensive evaluation of the impurity criterion for + # features that were already detected as constant (hence not suitable + # for good splitting) by ancestor nodes and save the information on + # newly discovered constant features to spare computation on descendant + # nodes. + while (f_i > n_total_constants and # Stop early if remaining features + # are constant + (n_visited_features < max_features or + # At least one drawn features must be non constant + n_visited_features <= n_found_constants + n_drawn_constants)): + + n_visited_features += 1 + + # Loop invariant: elements of features in + # - [:n_drawn_constant[ holds drawn and known constant features; + # - [n_drawn_constant:n_known_constant[ holds known constant + # features that haven't been drawn yet; + # - [n_known_constant:n_total_constant[ holds newly found constant + # features; + # - [n_total_constant:f_i[ holds features that haven't been drawn + # yet and aren't constant apriori. + # - [f_i:n_features[ holds features that have been drawn + # and aren't constant. + + # Draw a feature at random + f_j = rand_int(n_drawn_constants, f_i - n_found_constants, + random_state) + + if f_j < n_known_constants: + # f_j in the interval [n_drawn_constants, n_known_constants[ + features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] + + n_drawn_constants += 1 + + else: + # f_j in the interval [n_known_constants, f_i - n_found_constants[ + f_j += n_found_constants + # f_j in the interval [n_total_constants, f_i[ + + current.feature = features[f_j] + + self.extract_nnz(current.feature, + &end_negative, &start_positive, + &is_samples_sorted) + + # Add one or two zeros in Xf, if there is any + if end_negative < start_positive: + start_positive -= 1 + Xf[start_positive] = 0. + + if end_negative != start_positive: + Xf[end_negative] = 0. + end_negative += 1 + + # Find min, max in Xf[start:end_negative] + min_feature_value = Xf[start] + max_feature_value = min_feature_value + + for p in range(start, end_negative): + current_feature_value = Xf[p] + + if current_feature_value < min_feature_value: + min_feature_value = current_feature_value + elif current_feature_value > max_feature_value: + max_feature_value = current_feature_value + + # Update min, max given Xf[start_positive:end] + for p in range(start_positive, end): + current_feature_value = Xf[p] + + if current_feature_value < min_feature_value: + min_feature_value = current_feature_value + elif current_feature_value > max_feature_value: + max_feature_value = current_feature_value + + if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: + features[f_j] = features[n_total_constants] + features[n_total_constants] = current.feature + + n_found_constants += 1 + n_total_constants += 1 + + else: + f_i -= 1 + features[f_i], features[f_j] = features[f_j], features[f_i] + + # Draw a random threshold + current.threshold = rand_uniform(min_feature_value, + max_feature_value, + random_state) + + if current.threshold == max_feature_value: + current.threshold = min_feature_value + + # Partition + current.pos = self._partition(current.threshold, + end_negative, + start_positive, + start_positive + + (Xf[start_positive] == 0.)) + + # Reject if min_samples_leaf is not guaranteed + if (((current.pos - start) < min_samples_leaf) or + ((end - current.pos) < min_samples_leaf)): + continue + + # Evaluate split + self.criterion.reset() + self.criterion.update(current.pos) + + # Reject if min_weight_leaf is not satisfied + if ((self.criterion.weighted_n_left < min_weight_leaf) or + (self.criterion.weighted_n_right < min_weight_leaf)): + continue + + current_proxy_improvement = self.criterion.proxy_impurity_improvement() + + if current_proxy_improvement > best_proxy_improvement: + best_proxy_improvement = current_proxy_improvement + current.improvement = self.criterion.impurity_improvement(impurity) + + self.criterion.children_impurity(¤t.impurity_left, + ¤t.impurity_right) + best = current + + # Reorganize into samples[start:best.pos] + samples[best.pos:end] + if best.pos < end: + if current.feature != best.feature: + self.extract_nnz(best.feature, &end_negative, &start_positive, + &is_samples_sorted) + + self._partition(best.threshold, end_negative, start_positive, + best.pos) + + self.criterion.reset() + self.criterion.update(best.pos) + best.improvement = self.criterion.impurity_improvement(impurity) + self.criterion.children_impurity(&best.impurity_left, + &best.impurity_right) + + # Respect invariant for constant features: the original order of + # element in features[:n_known_constants] must be preserved for sibling + # and child nodes + memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) + + # Copy newly found constant features + memcpy(constant_features + n_known_constants, + features + n_known_constants, + sizeof(SIZE_t) * n_found_constants) + + # Return values + split[0] = best + n_constant_features[0] = n_total_constants + return 0 diff --git a/stpredictions/models/OK3/_tree.c b/stpredictions/models/OK3/_tree.c new file mode 100644 index 000000000..cbf514ea2 --- /dev/null +++ b/stpredictions/models/OK3/_tree.c @@ -0,0 +1,48004 @@ +/* Generated by Cython 0.29.23 */ + +/* BEGIN: Cython Metadata +{ + "distutils": { + "depends": [ + "/home/asani/anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/core/include/numpy/arrayobject.h", + "/home/asani/anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/core/include/numpy/ufuncobject.h" + ], + "extra_compile_args": [ + "-O3", + "-fopenmp", + "-DOMP" + ], + "extra_link_args": [ + "-fopenmp" + ], + "include_dirs": [ + "/home/asani/anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/core/include", + "/home/asani/Documents/Hi_Paris_Code_Projects/Florence/structured-predictions/stpredictions/models/OK3/test" + ], + "name": "_tree", + "sources": [ + "stpredictions/models/OK3/_tree.pyx" + ] + }, + "module_name": "_tree" +} +END: Cython Metadata */ + +#ifndef PY_SSIZE_T_CLEAN +#define PY_SSIZE_T_CLEAN +#endif /* PY_SSIZE_T_CLEAN */ +#include "Python.h" +#ifndef Py_PYTHON_H + #error Python headers needed to compile C extensions, please install development version of Python. +#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) + #error Cython requires Python 2.6+ or Python 3.3+. +#else +#define CYTHON_ABI "0_29_23" +#define CYTHON_HEX_VERSION 0x001D17F0 +#define CYTHON_FUTURE_DIVISION 0 +#include +#ifndef offsetof + #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) +#endif +#if !defined(WIN32) && !defined(MS_WINDOWS) + #ifndef __stdcall + #define __stdcall + #endif + #ifndef __cdecl + #define __cdecl + #endif + #ifndef __fastcall + #define __fastcall + #endif +#endif +#ifndef DL_IMPORT + #define DL_IMPORT(t) t +#endif +#ifndef DL_EXPORT + #define DL_EXPORT(t) t +#endif +#define __PYX_COMMA , +#ifndef HAVE_LONG_LONG + #if PY_VERSION_HEX >= 0x02070000 + #define HAVE_LONG_LONG + #endif +#endif +#ifndef PY_LONG_LONG + #define PY_LONG_LONG LONG_LONG +#endif +#ifndef Py_HUGE_VAL + #define Py_HUGE_VAL HUGE_VAL +#endif +#ifdef PYPY_VERSION + #define CYTHON_COMPILING_IN_PYPY 1 + #define CYTHON_COMPILING_IN_PYSTON 0 + #define CYTHON_COMPILING_IN_CPYTHON 0 + #undef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 0 + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #if PY_VERSION_HEX < 0x03050000 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #elif !defined(CYTHON_USE_ASYNC_SLOTS) + #define CYTHON_USE_ASYNC_SLOTS 1 + #endif + #undef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 0 + #undef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 0 + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #undef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 1 + #undef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 0 + #undef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 0 + #undef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 0 + #undef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 0 + #undef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT 0 + #undef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE 0 + #undef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS 0 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 +#elif defined(PYSTON_VERSION) + #define CYTHON_COMPILING_IN_PYPY 0 + #define CYTHON_COMPILING_IN_PYSTON 1 + #define CYTHON_COMPILING_IN_CPYTHON 0 + #ifndef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 1 + #endif + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #undef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 0 + #ifndef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 1 + #endif + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #ifndef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 0 + #endif + #ifndef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 1 + #endif + #ifndef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 1 + #endif + #undef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 0 + #undef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 0 + #undef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT 0 + #undef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE 0 + #undef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS 0 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 +#else + #define CYTHON_COMPILING_IN_PYPY 0 + #define CYTHON_COMPILING_IN_PYSTON 0 + #define CYTHON_COMPILING_IN_CPYTHON 1 + #ifndef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 1 + #endif + #if PY_VERSION_HEX < 0x02070000 + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #elif !defined(CYTHON_USE_PYTYPE_LOOKUP) + #define CYTHON_USE_PYTYPE_LOOKUP 1 + #endif + #if PY_MAJOR_VERSION < 3 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #elif !defined(CYTHON_USE_ASYNC_SLOTS) + #define CYTHON_USE_ASYNC_SLOTS 1 + #endif + #if PY_VERSION_HEX < 0x02070000 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #elif !defined(CYTHON_USE_PYLONG_INTERNALS) + #define CYTHON_USE_PYLONG_INTERNALS 1 + #endif + #ifndef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 1 + #endif + #ifndef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 1 + #endif + #if PY_VERSION_HEX < 0x030300F0 + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #elif !defined(CYTHON_USE_UNICODE_WRITER) + #define CYTHON_USE_UNICODE_WRITER 1 + #endif + #ifndef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 0 + #endif + #ifndef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 1 + #endif + #ifndef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 1 + #endif + #ifndef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 1 + #endif + #ifndef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 1 + #endif + #ifndef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT (PY_VERSION_HEX >= 0x03050000) + #endif + #ifndef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE (PY_VERSION_HEX >= 0x030400a1) + #endif + #ifndef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS (PY_VERSION_HEX >= 0x030600B1) + #endif + #ifndef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK (PY_VERSION_HEX >= 0x030700A3) + #endif +#endif +#if !defined(CYTHON_FAST_PYCCALL) +#define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) +#endif +#if CYTHON_USE_PYLONG_INTERNALS + #include "longintrepr.h" + #undef SHIFT + #undef BASE + #undef MASK + #ifdef SIZEOF_VOID_P + enum { __pyx_check_sizeof_voidp = 1 / (int)(SIZEOF_VOID_P == sizeof(void*)) }; + #endif +#endif +#ifndef __has_attribute + #define __has_attribute(x) 0 +#endif +#ifndef __has_cpp_attribute + #define __has_cpp_attribute(x) 0 +#endif +#ifndef CYTHON_RESTRICT + #if defined(__GNUC__) + #define CYTHON_RESTRICT __restrict__ + #elif defined(_MSC_VER) && _MSC_VER >= 1400 + #define CYTHON_RESTRICT __restrict + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_RESTRICT restrict + #else + #define CYTHON_RESTRICT + #endif +#endif +#ifndef CYTHON_UNUSED +# if defined(__GNUC__) +# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +#endif +#ifndef CYTHON_MAYBE_UNUSED_VAR +# if defined(__cplusplus) + template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } +# else +# define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) +# endif +#endif +#ifndef CYTHON_NCP_UNUSED +# if CYTHON_COMPILING_IN_CPYTHON +# define CYTHON_NCP_UNUSED +# else +# define CYTHON_NCP_UNUSED CYTHON_UNUSED +# endif +#endif +#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) +#ifdef _MSC_VER + #ifndef _MSC_STDINT_H_ + #if _MSC_VER < 1300 + typedef unsigned char uint8_t; + typedef unsigned int uint32_t; + #else + typedef unsigned __int8 uint8_t; + typedef unsigned __int32 uint32_t; + #endif + #endif +#else + #include +#endif +#ifndef CYTHON_FALLTHROUGH + #if defined(__cplusplus) && __cplusplus >= 201103L + #if __has_cpp_attribute(fallthrough) + #define CYTHON_FALLTHROUGH [[fallthrough]] + #elif __has_cpp_attribute(clang::fallthrough) + #define CYTHON_FALLTHROUGH [[clang::fallthrough]] + #elif __has_cpp_attribute(gnu::fallthrough) + #define CYTHON_FALLTHROUGH [[gnu::fallthrough]] + #endif + #endif + #ifndef CYTHON_FALLTHROUGH + #if __has_attribute(fallthrough) + #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) + #else + #define CYTHON_FALLTHROUGH + #endif + #endif + #if defined(__clang__ ) && defined(__apple_build_version__) + #if __apple_build_version__ < 7000000 + #undef CYTHON_FALLTHROUGH + #define CYTHON_FALLTHROUGH + #endif + #endif +#endif + +#ifndef CYTHON_INLINE + #if defined(__clang__) + #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) + #elif defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_INLINE inline + #else + #define CYTHON_INLINE + #endif +#endif + +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) + #define Py_OptimizeFlag 0 +#endif +#define __PYX_BUILD_PY_SSIZE_T "n" +#define CYTHON_FORMAT_SSIZE_T "z" +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) + #define __Pyx_DefaultClassType PyClass_Type +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#endif + #define __Pyx_DefaultClassType PyType_Type +#endif +#ifndef Py_TPFLAGS_CHECKTYPES + #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif +#ifndef Py_TPFLAGS_HAVE_FINALIZE + #define Py_TPFLAGS_HAVE_FINALIZE 0 +#endif +#ifndef METH_STACKLESS + #define METH_STACKLESS 0 +#endif +#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) + #ifndef METH_FASTCALL + #define METH_FASTCALL 0x80 + #endif + typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); + typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, + Py_ssize_t nargs, PyObject *kwnames); +#else + #define __Pyx_PyCFunctionFast _PyCFunctionFast + #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords +#endif +#if CYTHON_FAST_PYCCALL +#define __Pyx_PyFastCFunction_Check(func)\ + ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) +#else +#define __Pyx_PyFastCFunction_Check(func) 0 +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) + #define PyObject_Malloc(s) PyMem_Malloc(s) + #define PyObject_Free(p) PyMem_Free(p) + #define PyObject_Realloc(p) PyMem_Realloc(p) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 + #define PyMem_RawMalloc(n) PyMem_Malloc(n) + #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) + #define PyMem_RawFree(p) PyMem_Free(p) +#endif +#if CYTHON_COMPILING_IN_PYSTON + #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) +#else + #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) +#endif +#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#elif PY_VERSION_HEX >= 0x03060000 + #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() +#elif PY_VERSION_HEX >= 0x03000000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#else + #define __Pyx_PyThreadState_Current _PyThreadState_Current +#endif +#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) +#include "pythread.h" +#define Py_tss_NEEDS_INIT 0 +typedef int Py_tss_t; +static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { + *key = PyThread_create_key(); + return 0; +} +static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { + Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); + *key = Py_tss_NEEDS_INIT; + return key; +} +static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { + PyObject_Free(key); +} +static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { + return *key != Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { + PyThread_delete_key(*key); + *key = Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { + return PyThread_set_key_value(*key, value); +} +static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { + return PyThread_get_key_value(*key); +} +#endif +#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) +#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) +#else +#define __Pyx_PyDict_NewPresized(n) PyDict_New() +#endif +#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS +#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) +#else +#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) +#endif +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) + #define CYTHON_PEP393_ENABLED 1 + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ + 0 : _PyUnicode_Ready((PyObject *)(op))) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) + #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) + #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) + #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif +#else + #define CYTHON_PEP393_ENABLED 0 + #define PyUnicode_1BYTE_KIND 1 + #define PyUnicode_2BYTE_KIND 2 + #define PyUnicode_4BYTE_KIND 4 + #define __Pyx_PyUnicode_READY(op) (0) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) + #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) + #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) + #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) +#endif +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) +#else + #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ + PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) + #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) + #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) +#endif +#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) +#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) +#else + #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) +#endif +#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) + #define PyObject_ASCII(o) PyObject_Repr(o) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode + #define PyObject_Unicode PyObject_Str +#endif +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) + #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) +#else + #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) + #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif +#if CYTHON_ASSUME_SAFE_MACROS + #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) +#else + #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define PyNumber_Int PyNumber_Long +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif +#if PY_VERSION_HEX < 0x030200A4 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t PyInt_AsLong +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) +#endif +#if CYTHON_USE_ASYNC_SLOTS + #if PY_VERSION_HEX >= 0x030500B1 + #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods + #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) + #else + #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) + #endif +#else + #define __Pyx_PyType_AsAsync(obj) NULL +#endif +#ifndef __Pyx_PyAsyncMethodsStruct + typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; + } __Pyx_PyAsyncMethodsStruct; +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include +#ifdef NAN +#define __PYX_NAN() ((float) NAN) +#else +static CYTHON_INLINE float __PYX_NAN() { + float value; + memset(&value, 0xFF, sizeof(value)); + return value; +} +#endif +#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) +#define __Pyx_truncl trunc +#else +#define __Pyx_truncl truncl +#endif + +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } +#define __PYX_ERR(f_index, lineno, Ln_error) \ + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#define __PYX_HAVE___tree +#define __PYX_HAVE_API___tree +/* Early includes */ +#include +#include +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + +#include "pythread.h" +#include +#include +#include +#include "pystate.h" +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) +#define CYTHON_WITHOUT_ASSERTIONS +#endif + +typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; + const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; + +#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) +#define __PYX_DEFAULT_STRING_ENCODING "" +#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString +#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX))) ) +static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { + return (size_t) i < (size_t) limit; +} +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (_MSC_VER) + #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); +#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) +#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); +#if PY_MAJOR_VERSION < 3 + #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#else + #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize +#endif +#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { + const Py_UNICODE *u_end = u; + while (*u_end++) ; + return (size_t)(u_end - u - 1); +} +#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) +#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode +#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); +#define __Pyx_PySequence_Tuple(obj)\ + (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +#if CYTHON_ASSUME_SAFE_MACROS +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#else +#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) +#endif +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) +#else +#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) +#endif +#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII +static int __Pyx_sys_getdefaultencoding_not_ascii; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + PyObject* ascii_chars_u = NULL; + PyObject* ascii_chars_b = NULL; + const char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + if (strcmp(default_encoding_c, "ascii") == 0) { + __Pyx_sys_getdefaultencoding_not_ascii = 0; + } else { + char ascii_chars[128]; + int c; + for (c = 0; c < 128; c++) { + ascii_chars[c] = c; + } + __Pyx_sys_getdefaultencoding_not_ascii = 1; + ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); + if (!ascii_chars_u) goto bad; + ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); + if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { + PyErr_Format( + PyExc_ValueError, + "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", + default_encoding_c); + goto bad; + } + Py_DECREF(ascii_chars_u); + Py_DECREF(ascii_chars_b); + } + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + Py_XDECREF(ascii_chars_u); + Py_XDECREF(ascii_chars_b); + return -1; +} +#endif +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) +#else +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +static char* __PYX_DEFAULT_STRING_ENCODING; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); + if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; + strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + return -1; +} +#endif +#endif + + +/* Test for GCC > 2.95 */ +#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) +#else /* !__GNUC__ or GCC < 2.95 */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ +static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } + +static PyObject *__pyx_m = NULL; +static PyObject *__pyx_d; +static PyObject *__pyx_b; +static PyObject *__pyx_cython_runtime = NULL; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static PyObject *__pyx_empty_unicode; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +/* Header.proto */ +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + + +static const char *__pyx_f[] = { + "stpredictions/models/OK3/_tree.pyx", + "stringsource", + "stpredictions/models/OK3/_tree.pxd", + "__init__.pxd", + "type.pxd", + "bool.pxd", + "complex.pxd", + "_criterion.pxd", + "_splitter.pxd", + "_tree.pxd", + "stpredictions/models/OK3/_criterion.pxd", + "stpredictions/models/OK3/_splitter.pxd", + "_quad_tree.pxd", + "_utils.pxd", +}; +/* MemviewSliceStruct.proto */ +struct __pyx_memoryview_obj; +typedef struct { + struct __pyx_memoryview_obj *memview; + char *data; + Py_ssize_t shape[8]; + Py_ssize_t strides[8]; + Py_ssize_t suboffsets[8]; +} __Pyx_memviewslice; +#define __Pyx_MemoryView_Len(m) (m.shape[0]) + +/* Atomics.proto */ +#include +#ifndef CYTHON_ATOMICS + #define CYTHON_ATOMICS 1 +#endif +#define __pyx_atomic_int_type int +#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\ + (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\ + !defined(__i386__) + #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) + #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using GNU atomics" + #endif +#elif CYTHON_ATOMICS && defined(_MSC_VER) && 0 + #include + #undef __pyx_atomic_int_type + #define __pyx_atomic_int_type LONG + #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #pragma message ("Using MSVC atomics") + #endif +#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 + #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using Intel atomics" + #endif +#else + #undef CYTHON_ATOMICS + #define CYTHON_ATOMICS 0 + #ifdef __PYX_DEBUG_ATOMICS + #warning "Not using atomics" + #endif +#endif +typedef volatile __pyx_atomic_int_type __pyx_atomic_int; +#if CYTHON_ATOMICS + #define __pyx_add_acquisition_count(memview)\ + __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview)\ + __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) +#else + #define __pyx_add_acquisition_count(memview)\ + __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview)\ + __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) +#endif + +/* NoFastGil.proto */ +#define __Pyx_PyGILState_Ensure PyGILState_Ensure +#define __Pyx_PyGILState_Release PyGILState_Release +#define __Pyx_FastGIL_Remember() +#define __Pyx_FastGIL_Forget() +#define __Pyx_FastGilFuncInit() + +/* ForceInitThreads.proto */ +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + +/* BufferFormatStructs.proto */ +#define IS_UNSIGNED(type) (((type) -1) > 0) +struct __Pyx_StructField_; +#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) +typedef struct { + const char* name; + struct __Pyx_StructField_* fields; + size_t size; + size_t arraysize[8]; + int ndim; + char typegroup; + char is_unsigned; + int flags; +} __Pyx_TypeInfo; +typedef struct __Pyx_StructField_ { + __Pyx_TypeInfo* type; + const char* name; + size_t offset; +} __Pyx_StructField; +typedef struct { + __Pyx_StructField* field; + size_t parent_offset; +} __Pyx_BufFmt_StackElem; +typedef struct { + __Pyx_StructField root; + __Pyx_BufFmt_StackElem* head; + size_t fmt_offset; + size_t new_count, enc_count; + size_t struct_alignment; + int is_complex; + char enc_type; + char new_packmode; + char enc_packmode; + char is_valid_array; +} __Pyx_BufFmt_Context; + + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":689 + * # in Cython to enable them only on the right systems. + * + * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + */ +typedef npy_int8 __pyx_t_5numpy_int8_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":690 + * + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t + */ +typedef npy_int16 __pyx_t_5numpy_int16_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":691 + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< + * ctypedef npy_int64 int64_t + * #ctypedef npy_int96 int96_t + */ +typedef npy_int32 __pyx_t_5numpy_int32_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":692 + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< + * #ctypedef npy_int96 int96_t + * #ctypedef npy_int128 int128_t + */ +typedef npy_int64 __pyx_t_5numpy_int64_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":696 + * #ctypedef npy_int128 int128_t + * + * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + */ +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":697 + * + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t + */ +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":698 + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< + * ctypedef npy_uint64 uint64_t + * #ctypedef npy_uint96 uint96_t + */ +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":699 + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< + * #ctypedef npy_uint96 uint96_t + * #ctypedef npy_uint128 uint128_t + */ +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":703 + * #ctypedef npy_uint128 uint128_t + * + * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< + * ctypedef npy_float64 float64_t + * #ctypedef npy_float80 float80_t + */ +typedef npy_float32 __pyx_t_5numpy_float32_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":704 + * + * ctypedef npy_float32 float32_t + * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< + * #ctypedef npy_float80 float80_t + * #ctypedef npy_float128 float128_t + */ +typedef npy_float64 __pyx_t_5numpy_float64_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":713 + * # The int types are mapped a bit surprising -- + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t + */ +typedef npy_long __pyx_t_5numpy_int_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":714 + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong longlong_t + * + */ +typedef npy_longlong __pyx_t_5numpy_long_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":715 + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_ulong uint_t + */ +typedef npy_longlong __pyx_t_5numpy_longlong_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":717 + * ctypedef npy_longlong longlong_t + * + * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t + */ +typedef npy_ulong __pyx_t_5numpy_uint_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":718 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":719 + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_intp intp_t + */ +typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":721 + * ctypedef npy_ulonglong ulonglong_t + * + * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< + * ctypedef npy_uintp uintp_t + * + */ +typedef npy_intp __pyx_t_5numpy_intp_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":722 + * + * ctypedef npy_intp intp_t + * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< + * + * ctypedef npy_double float_t + */ +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":724 + * ctypedef npy_uintp uintp_t + * + * ctypedef npy_double float_t # <<<<<<<<<<<<<< + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t + */ +typedef npy_double __pyx_t_5numpy_float_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":725 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":726 + * ctypedef npy_double float_t + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cfloat cfloat_t + */ +typedef npy_longdouble __pyx_t_5numpy_longdouble_t; + +/* "sklearn/tree/_tree.pxd":16 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_7sklearn_4tree_5_tree_DTYPE_t; + +/* "sklearn/tree/_tree.pxd":17 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t; + +/* "sklearn/tree/_tree.pxd":18 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_7sklearn_4tree_5_tree_SIZE_t; + +/* "sklearn/tree/_tree.pxd":19 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_7sklearn_4tree_5_tree_INT32_t; + +/* "sklearn/tree/_tree.pxd":20 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * from ._splitter cimport Splitter + */ +typedef npy_uint32 __pyx_t_7sklearn_4tree_5_tree_UINT32_t; + +/* "neighbors/_quad_tree.pxd":13 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float32 __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t; + +/* "neighbors/_quad_tree.pxd":14 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t; + +/* "neighbors/_quad_tree.pxd":15 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_7sklearn_9neighbors_10_quad_tree_INT32_t; + +/* "neighbors/_quad_tree.pxd":16 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * # This is effectively an ifdef statement in Cython + */ +typedef npy_uint32 __pyx_t_7sklearn_9neighbors_10_quad_tree_UINT32_t; + +/* "sklearn/tree/_utils.pxd":16 + * from ..neighbors._quad_tree cimport Cell + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_7sklearn_4tree_6_utils_DTYPE_t; + +/* "sklearn/tree/_utils.pxd":17 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t; + +/* "sklearn/tree/_utils.pxd":18 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_7sklearn_4tree_6_utils_SIZE_t; + +/* "sklearn/tree/_utils.pxd":19 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_7sklearn_4tree_6_utils_INT32_t; + +/* "sklearn/tree/_utils.pxd":20 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * + */ +typedef npy_uint32 __pyx_t_7sklearn_4tree_6_utils_UINT32_t; + +/* "_tree.pxd":7 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_5_tree_DTYPE_t; + +/* "_tree.pxd":8 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_5_tree_DOUBLE_t; + +/* "_tree.pxd":9 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_5_tree_SIZE_t; + +/* "_tree.pxd":10 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_5_tree_INT32_t; + +/* "_tree.pxd":11 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * from _splitter cimport Splitter + */ +typedef npy_uint32 __pyx_t_5_tree_UINT32_t; +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< float > __pyx_t_float_complex; + #else + typedef float _Complex __pyx_t_float_complex; + #endif +#else + typedef struct { float real, imag; } __pyx_t_float_complex; +#endif +static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); + +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< double > __pyx_t_double_complex; + #else + typedef double _Complex __pyx_t_double_complex; + #endif +#else + typedef struct { double real, imag; } __pyx_t_double_complex; +#endif +static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); + + +/*--- Type declarations ---*/ +struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion; +struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion; +struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion; +struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter; +struct __pyx_obj_7sklearn_4tree_5_tree_Tree; +struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder; +struct __pyx_obj_10_criterion_Criterion; +struct __pyx_obj_10_criterion_KernelizedRegressionCriterion; +struct __pyx_obj_9_splitter_Splitter; +struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree; +struct __pyx_obj_7sklearn_4tree_6_utils_Stack; +struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap; +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue; +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator; +struct __pyx_obj_5_tree_Tree; +struct __pyx_obj_5_tree_TreeBuilder; +struct __pyx_obj_5_tree_DepthFirstTreeBuilder; +struct __pyx_obj_5_tree_BestFirstTreeBuilder; +struct __pyx_obj_5_tree__CCPPruneController; +struct __pyx_obj_5_tree__AlphaPruner; +struct __pyx_obj_5_tree__PathFinder; +struct __pyx_array_obj; +struct __pyx_MemviewEnum_obj; +struct __pyx_memoryview_obj; +struct __pyx_memoryviewslice_obj; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":728 + * ctypedef npy_longdouble longdouble_t + * + * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t + */ +typedef npy_cfloat __pyx_t_5numpy_cfloat_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":729 + * + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< + * ctypedef npy_clongdouble clongdouble_t + * + */ +typedef npy_cdouble __pyx_t_5numpy_cdouble_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":730 + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cdouble complex_t + */ +typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; + +/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":732 + * ctypedef npy_clongdouble clongdouble_t + * + * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< + * + * cdef inline object PyArray_MultiIterNew1(a): + */ +typedef npy_cdouble __pyx_t_5numpy_complex_t; +struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord; + +/* "_splitter.pxd":23 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef struct SplitRecord: # <<<<<<<<<<<<<< + * # Data to track sample split + * SIZE_t feature # Which feature to split on. + */ +struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + double threshold; + double improvement; + double impurity_left; + double impurity_right; +}; +struct __pyx_t_7sklearn_4tree_5_tree_Node; +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c; +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances; +struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build; + +/* "sklearn/tree/_tree.pxd":25 + * from ._splitter cimport SplitRecord + * + * cdef struct Node: # <<<<<<<<<<<<<< + * # Base storage structure for the nodes in a Tree object + * + */ +struct __pyx_t_7sklearn_4tree_5_tree_Node { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t left_child; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t right_child; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t threshold; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t impurity; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t weighted_n_node_samples; +}; + +/* "sklearn/tree/_tree.pxd":63 + * double weighted_n_samples) nogil except -1 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * + * cdef np.ndarray _get_value_ndarray(self) + */ +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c { + int __pyx_n; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; +}; + +/* "sklearn/tree/_tree.pxd":78 + * cdef object _decision_path_sparse_csr(self, object X) + * + * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< + * + * + */ +struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances { + int __pyx_n; + PyObject *normalize; +}; + +/* "sklearn/tree/_tree.pxd":102 + * cdef double min_impurity_decrease # Impurity threshold for early stopping + * + * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< + * np.ndarray sample_weight=*) + * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) + */ +struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build { + int __pyx_n; + PyArrayObject *sample_weight; +}; +struct __pyx_t_9_splitter_SplitRecord; + +/* "_splitter.pxd":14 + * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef struct SplitRecord: # <<<<<<<<<<<<<< + * # Data to track sample split + * SIZE_t feature # Which feature to split on. + */ +struct __pyx_t_9_splitter_SplitRecord { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + double threshold; + double improvement; + double impurity_left; + double impurity_right; +}; +struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c; +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; + +/* "neighbors/_quad_tree.pxd":21 + * # It allows us to write printf debugging lines + * # and remove them at compile time + * cdef enum: # <<<<<<<<<<<<<< + * DEBUGFLAG = 0 + * + */ +enum { + __pyx_e_7sklearn_9neighbors_10_quad_tree_DEBUGFLAG = 0 +}; + +/* "neighbors/_quad_tree.pxd":29 + * # have is_leaf and max_width consecutive as it permits to avoid padding by + * # the compiler and keep the size coherent for both C and numpy data structures. + * cdef struct Cell: # <<<<<<<<<<<<<< + * # Base storage structure for cells in a QuadTree object + * + */ +struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell { + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t parent; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t children[8]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t point_index; + int is_leaf; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t squared_max_width; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t depth; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cumulative_size; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t center[3]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t barycenter[3]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t min_bounds[3]; + __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t max_bounds[3]; +}; + +/* "neighbors/_quad_tree.pxd":75 + * + * # Point insertion methods + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< + * SIZE_t cell_id=*) nogil except -1 + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; +}; + +/* "neighbors/_quad_tree.pxd":77 + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, + * SIZE_t cell_id=*) nogil except -1 + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< + * SIZE_t point_index, SIZE_t size=* + * ) nogil + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t size; +}; + +/* "neighbors/_quad_tree.pxd":84 + * + * # Create a summary of the Tree compare to a query point + * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< + * float squared_theta=*, SIZE_t cell_id=*, long idx=* + * ) nogil + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize { + int __pyx_n; + float squared_theta; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + long idx; +}; + +/* "neighbors/_quad_tree.pxd":99 + * # Private array manipulation to manage the ``cells`` array + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 + * cdef np.ndarray _get_cell_ndarray(self) + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; +}; + +/* "neighbors/_quad_tree.pxd":100 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 + * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< + * cdef np.ndarray _get_cell_ndarray(self) + */ +struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell { + int __pyx_n; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; +}; +struct __pyx_t_7sklearn_4tree_6_utils_StackRecord; +struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord; +struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; + +/* "sklearn/tree/_utils.pxd":23 + * + * + * cdef enum: # <<<<<<<<<<<<<< + * # Max value for our rand_r replacement (near the bottom). + * # We don't use RAND_MAX because it's different across platforms and + */ +enum { + __pyx_e_7sklearn_4tree_6_utils_RAND_R_MAX = 0x7FFFFFFF +}; + +/* "sklearn/tree/_utils.pxd":70 + * + * # A record on the stack for depth-first tree growing + * cdef struct StackRecord: # <<<<<<<<<<<<<< + * SIZE_t start + * SIZE_t end + */ +struct __pyx_t_7sklearn_4tree_6_utils_StackRecord { + __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t parent; + int is_left; + double impurity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t n_constant_features; +}; + +/* "sklearn/tree/_utils.pxd":96 + * + * # A record on the frontier for best-first tree growing + * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< + * SIZE_t node_id + * SIZE_t start + */ +struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { + __pyx_t_7sklearn_4tree_6_utils_SIZE_t node_id; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t pos; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; + int is_leaf; + double impurity; + double impurity_left; + double impurity_right; + double improvement; +}; + +/* "sklearn/tree/_utils.pxd":127 + * + * # A record stored in the WeightedPQueue + * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< + * DOUBLE_t data + * DOUBLE_t weight + */ +struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord { + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t data; + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t weight; +}; +struct __pyx_t_5_tree_Node; +struct __pyx_opt_args_5_tree_4Tree__resize_c; +struct __pyx_opt_args_5_tree_4Tree_compute_feature_importances; +struct __pyx_opt_args_5_tree_11TreeBuilder_build; +struct __pyx_opt_args_5_tree_21DepthFirstTreeBuilder_build; +struct __pyx_opt_args_5_tree_20BestFirstTreeBuilder_build; + +/* "_tree.pxd":16 + * from _splitter cimport SplitRecord + * + * cdef struct Node: # <<<<<<<<<<<<<< + * # Base storage structure for the nodes in a Tree object + * + */ +struct __pyx_t_5_tree_Node { + __pyx_t_5_tree_SIZE_t left_child; + __pyx_t_5_tree_SIZE_t right_child; + __pyx_t_5_tree_SIZE_t feature; + __pyx_t_5_tree_DOUBLE_t threshold; + __pyx_t_5_tree_DOUBLE_t impurity; + __pyx_t_5_tree_SIZE_t n_node_samples; + __pyx_t_5_tree_DOUBLE_t weighted_n_node_samples; +}; + +/* "_tree.pxd":52 + * double weighted_n_samples) nogil except -1 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * + * cdef np.ndarray _get_value_ndarray(self) + */ +struct __pyx_opt_args_5_tree_4Tree__resize_c { + int __pyx_n; + __pyx_t_5_tree_SIZE_t capacity; +}; + +/* "_tree.pxd":68 + * cdef object _decision_path_sparse_csr(self, object X) + * + * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< + * + * + */ +struct __pyx_opt_args_5_tree_4Tree_compute_feature_importances { + int __pyx_n; + PyObject *normalize; +}; + +/* "_tree.pxd":92 + * cdef double min_impurity_decrease # Impurity threshold for early stopping + * + * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< + * np.ndarray sample_weight=*) + * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) + */ +struct __pyx_opt_args_5_tree_11TreeBuilder_build { + int __pyx_n; + PyArrayObject *sample_weight; +}; + +/* "_tree.pyx":129 + * self.min_impurity_split = min_impurity_split + * + * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< + * np.ndarray sample_weight=None): + * """Build a decision tree from the training set (X, y).""" + */ +struct __pyx_opt_args_5_tree_21DepthFirstTreeBuilder_build { + int __pyx_n; + PyArrayObject *sample_weight; +}; + +/* "_tree.pyx":303 + * self.min_impurity_split = min_impurity_split + * + * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< + * np.ndarray sample_weight=None): + * """Build a decision tree from the training set (X, y).""" + */ +struct __pyx_opt_args_5_tree_20BestFirstTreeBuilder_build { + int __pyx_n; + PyArrayObject *sample_weight; +}; + +/* "_criterion.pxd":21 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. It also computes the output statistics + */ +struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtab; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + double weighted_n_samples; + double weighted_n_node_samples; + double weighted_n_left; + double weighted_n_right; + double *sum_total; + double *sum_left; + double *sum_right; +}; + + +/* "_criterion.pxd":70 + * cdef double proxy_impurity_improvement(self) nogil + * + * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract criterion for classification.""" + * + */ +struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion { + struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t sum_stride; +}; + + +/* "_criterion.pxd":76 + * cdef SIZE_t sum_stride + * + * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract regression criterion.""" + * + */ +struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion { + struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; + double sq_sum_total; +}; + + +/* "_splitter.pxd":34 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ +struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtab; + struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *criterion; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + PyObject *random_state; + __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + double weighted_n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; +}; + + +/* "sklearn/tree/_tree.pxd":37 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. The tree structure is used for predictions and + */ +struct __pyx_obj_7sklearn_4tree_5_tree_Tree { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtab; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_n_classes; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t node_count; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; + struct __pyx_t_7sklearn_4tree_5_tree_Node *nodes; + double *value; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t value_stride; +}; + + +/* "sklearn/tree/_tree.pxd":85 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ +struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtab; + struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *splitter; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_split; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; + double min_impurity_split; + double min_impurity_decrease; +}; + + +/* "_criterion.pxd":12 + * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. + */ +struct __pyx_obj_10_criterion_Criterion { + PyObject_HEAD + struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtab; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + double weighted_n_samples; + double weighted_n_node_samples; + double weighted_n_left; + double weighted_n_right; +}; + + +/* "_criterion.pxd":50 + * + * + * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract kernelized output regression criterion.""" + * + */ +struct __pyx_obj_10_criterion_KernelizedRegressionCriterion { + struct __pyx_obj_10_criterion_Criterion __pyx_base; + double sum_diag_Gramm; + double sum_total_Gramm; + double sum_diag_Gramm_left; + double sum_diag_Gramm_right; + double sum_total_Gramm_left; + double sum_total_Gramm_right; +}; + + +/* "_splitter.pxd":25 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ +struct __pyx_obj_9_splitter_Splitter { + PyObject_HEAD + struct __pyx_vtabstruct_9_splitter_Splitter *__pyx_vtab; + struct __pyx_obj_10_criterion_Criterion *criterion; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + PyObject *random_state; + __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + double weighted_n_samples; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; + __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; + __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __Pyx_memviewslice y; + __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; +}; + + +/* "neighbors/_quad_tree.pxd":55 + * + * + * cdef class _QuadTree: # <<<<<<<<<<<<<< + * # The QuadTree object is a quad tree structure constructed by inserting + * # recursively points in the tree and splitting cells in 4 so that each + */ +struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtab; + int n_dimensions; + int verbose; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_cells_per_cell; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t max_depth; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_count; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_points; + struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *cells; +}; + + +/* "sklearn/tree/_utils.pxd":79 + * SIZE_t n_constant_features + * + * cdef class Stack: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t top + */ +struct __pyx_obj_7sklearn_4tree_6_utils_Stack { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t top; + struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *stack_; +}; + + +/* "sklearn/tree/_utils.pxd":108 + * double improvement + * + * cdef class PriorityHeap: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t heap_ptr + */ +struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t heap_ptr; + struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *heap_; +}; + + +/* "sklearn/tree/_utils.pxd":131 + * DOUBLE_t weight + * + * cdef class WeightedPQueue: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t array_ptr + */ +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t array_ptr; + struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *array_; +}; + + +/* "sklearn/tree/_utils.pxd":151 + * # ============================================================================= + * + * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< + * cdef SIZE_t initial_capacity + * cdef WeightedPQueue samples + */ +struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator { + PyObject_HEAD + struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtab; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t initial_capacity; + struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *samples; + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t total_weight; + __pyx_t_7sklearn_4tree_6_utils_SIZE_t k; + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t sum_w_0_k; +}; + + +/* "_tree.pxd":28 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. + */ +struct __pyx_obj_5_tree_Tree { + PyObject_HEAD + struct __pyx_vtabstruct_5_tree_Tree *__pyx_vtab; + __pyx_t_5_tree_SIZE_t n_features; + __pyx_t_5_tree_SIZE_t max_depth; + __pyx_t_5_tree_SIZE_t node_count; + __pyx_t_5_tree_SIZE_t capacity; + PyArrayObject *K_y; + PyArrayObject *y; + struct __pyx_t_5_tree_Node *nodes; + double *value; +}; + + +/* "_tree.pxd":75 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ +struct __pyx_obj_5_tree_TreeBuilder { + PyObject_HEAD + struct __pyx_vtabstruct_5_tree_TreeBuilder *__pyx_vtab; + struct __pyx_obj_9_splitter_Splitter *splitter; + __pyx_t_5_tree_SIZE_t min_samples_split; + __pyx_t_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + __pyx_t_5_tree_SIZE_t max_depth; + double min_impurity_split; + double min_impurity_decrease; +}; + + +/* "_tree.pyx":114 + * # Depth first builder --------------------------------------------------------- + * + * cdef class DepthFirstTreeBuilder(TreeBuilder): # <<<<<<<<<<<<<< + * """Build a decision tree in depth-first fashion.""" + * + */ +struct __pyx_obj_5_tree_DepthFirstTreeBuilder { + struct __pyx_obj_5_tree_TreeBuilder __pyx_base; +}; + + +/* "_tree.pyx":282 + * + * + * cdef class BestFirstTreeBuilder(TreeBuilder): # <<<<<<<<<<<<<< + * """Build a decision tree in best-first fashion. + * + */ +struct __pyx_obj_5_tree_BestFirstTreeBuilder { + struct __pyx_obj_5_tree_TreeBuilder __pyx_base; + __pyx_t_5_tree_SIZE_t max_leaf_nodes; +}; + + +/* "_tree.pyx":1316 + * + * + * cdef class _CCPPruneController: # <<<<<<<<<<<<<< + * """Base class used by build_pruned_tree_ccp and ccp_pruning_path + * to control pruning. + */ +struct __pyx_obj_5_tree__CCPPruneController { + PyObject_HEAD + struct __pyx_vtabstruct_5_tree__CCPPruneController *__pyx_vtab; +}; + + +/* "_tree.pyx":1334 + * + * + * cdef class _AlphaPruner(_CCPPruneController): # <<<<<<<<<<<<<< + * """Use alpha to control when to stop pruning.""" + * cdef DOUBLE_t ccp_alpha + */ +struct __pyx_obj_5_tree__AlphaPruner { + struct __pyx_obj_5_tree__CCPPruneController __pyx_base; + __pyx_t_5_tree_DOUBLE_t ccp_alpha; + __pyx_t_5_tree_SIZE_t capacity; +}; + + +/* "_tree.pyx":1355 + * + * + * cdef class _PathFinder(_CCPPruneController): # <<<<<<<<<<<<<< + * """Record metrics used to return the cost complexity path.""" + * cdef DOUBLE_t[:] ccp_alphas + */ +struct __pyx_obj_5_tree__PathFinder { + struct __pyx_obj_5_tree__CCPPruneController __pyx_base; + __Pyx_memviewslice ccp_alphas; + __Pyx_memviewslice impurities; + __pyx_t_5_tree_UINT32_t count; +}; + + +/* "View.MemoryView":105 + * + * @cname("__pyx_array") + * cdef class array: # <<<<<<<<<<<<<< + * + * cdef: + */ +struct __pyx_array_obj { + PyObject_HEAD + struct __pyx_vtabstruct_array *__pyx_vtab; + char *data; + Py_ssize_t len; + char *format; + int ndim; + Py_ssize_t *_shape; + Py_ssize_t *_strides; + Py_ssize_t itemsize; + PyObject *mode; + PyObject *_format; + void (*callback_free_data)(void *); + int free_data; + int dtype_is_object; +}; + + +/* "View.MemoryView":279 + * + * @cname('__pyx_MemviewEnum') + * cdef class Enum(object): # <<<<<<<<<<<<<< + * cdef object name + * def __init__(self, name): + */ +struct __pyx_MemviewEnum_obj { + PyObject_HEAD + PyObject *name; +}; + + +/* "View.MemoryView":330 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ +struct __pyx_memoryview_obj { + PyObject_HEAD + struct __pyx_vtabstruct_memoryview *__pyx_vtab; + PyObject *obj; + PyObject *_size; + PyObject *_array_interface; + PyThread_type_lock lock; + __pyx_atomic_int acquisition_count[2]; + __pyx_atomic_int *acquisition_count_aligned_p; + Py_buffer view; + int flags; + int dtype_is_object; + __Pyx_TypeInfo *typeinfo; +}; + + +/* "View.MemoryView":965 + * + * @cname('__pyx_memoryviewslice') + * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< + * "Internal class for passing memoryview slices to Python" + * + */ +struct __pyx_memoryviewslice_obj { + struct __pyx_memoryview_obj __pyx_base; + __Pyx_memviewslice from_slice; + PyObject *from_object; + PyObject *(*to_object_func)(char *); + int (*to_dtype_func)(char *, PyObject *); +}; + + + +/* "_criterion.pxd":21 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. It also computes the output statistics + */ + +struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion { + int (*init)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double, double, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_Criterion; + + +/* "_criterion.pxd":70 + * cdef double proxy_impurity_improvement(self) nogil + * + * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract criterion for classification.""" + * + */ + +struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion { + struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; +}; +static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_ClassificationCriterion; + + +/* "_criterion.pxd":76 + * cdef SIZE_t sum_stride + * + * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract regression criterion.""" + * + */ + +struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion { + struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; +}; +static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_RegressionCriterion; + + +/* "_splitter.pxd":34 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ + +struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter { + int (*init)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); + int (*node_reset)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); + int (*node_split)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double, struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); + void (*node_value)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double *); + double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtabptr_7sklearn_4tree_9_splitter_Splitter; + + +/* "sklearn/tree/_tree.pxd":37 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. The tree structure is used for predictions and + */ + +struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree { + __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double); + int (*_resize)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args); + PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); + PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); + PyArrayObject *(*predict)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*apply)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*_apply_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyObject *(*decision_path)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyObject *(*_decision_path_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); + PyObject *(*compute_feature_importances)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklearn_4tree_5_tree_Tree; + + +/* "sklearn/tree/_tree.pxd":85 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ + +struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder { + PyObject *(*build)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args); + PyObject *(*_check_input)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder; + + +/* "_criterion.pxd":12 + * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. + */ + +struct __pyx_vtabstruct_10_criterion_Criterion { + int (*init)(struct __pyx_obj_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *); +}; +static struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtabptr_10_criterion_Criterion; + + +/* "_criterion.pxd":50 + * + * + * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract kernelized output regression criterion.""" + * + */ + +struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion { + struct __pyx_vtabstruct_10_criterion_Criterion __pyx_base; +}; +static struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_10_criterion_KernelizedRegressionCriterion; + + +/* "_splitter.pxd":25 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ + +struct __pyx_vtabstruct_9_splitter_Splitter { + int (*init)(struct __pyx_obj_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); + int (*node_reset)(struct __pyx_obj_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); + int (*node_split)(struct __pyx_obj_9_splitter_Splitter *, double, struct __pyx_t_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); + void (*node_value)(struct __pyx_obj_9_splitter_Splitter *, double *); + double (*node_impurity)(struct __pyx_obj_9_splitter_Splitter *); +}; +static struct __pyx_vtabstruct_9_splitter_Splitter *__pyx_vtabptr_9_splitter_Splitter; + + +/* "neighbors/_quad_tree.pxd":55 + * + * + * cdef class _QuadTree: # <<<<<<<<<<<<<< + * # The QuadTree object is a quad tree structure constructed by inserting + * # recursively points in the tree and splitting cells in 4 so that each + */ + +struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree { + int (*insert_point)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); + __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); + int (*_is_duplicate)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); + long (*summarize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); + void (*_init_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); + void (*_init_root)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); + int (*_check_point_in_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); + int (*_resize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); + int (*_get_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); + PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *); +}; +static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtabptr_7sklearn_9neighbors_10_quad_tree__QuadTree; + + +/* "sklearn/tree/_utils.pxd":79 + * SIZE_t n_constant_features + * + * cdef class Stack: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t top + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack { + int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7sklearn_4tree_6_utils_Stack; + + +/* "sklearn/tree/_utils.pxd":108 + * double improvement + * + * cdef class PriorityHeap: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t heap_ptr + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap { + int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); + void (*heapify_up)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + void (*heapify_down)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, double, double, double); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabptr_7sklearn_4tree_6_utils_PriorityHeap; + + +/* "sklearn/tree/_utils.pxd":131 + * DOUBLE_t weight + * + * cdef class WeightedPQueue: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t array_ptr + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue { + int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); + int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); + __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); + int (*peek)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedPQueue; + + +/* "sklearn/tree/_utils.pxd":151 + * # ============================================================================= + * + * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< + * cdef SIZE_t initial_capacity + * cdef WeightedPQueue samples + */ + +struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator { + __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); + int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); + int (*update_median_parameters_post_push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); + int (*update_median_parameters_post_remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); + __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); +}; +static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedMedianCalculator; + + +/* "_tree.pyx":503 + * # ============================================================================= + * + * cdef class Tree: # <<<<<<<<<<<<<< + * """Array-based representation of a binary decision tree. + * + */ + +struct __pyx_vtabstruct_5_tree_Tree { + __pyx_t_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_5_tree_Tree *, __pyx_t_5_tree_SIZE_t, int, int, __pyx_t_5_tree_SIZE_t, double, double, __pyx_t_5_tree_SIZE_t, double); + int (*_resize)(struct __pyx_obj_5_tree_Tree *, __pyx_t_5_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_5_tree_Tree *, struct __pyx_opt_args_5_tree_4Tree__resize_c *__pyx_optional_args); + PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_5_tree_Tree *); + PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_5_tree_Tree *); + PyArrayObject *(*decode_tree)(struct __pyx_obj_5_tree_Tree *, PyArrayObject *, PyArrayObject *, PyObject *, PyObject *, __pyx_t_5_tree_SIZE_t, int __pyx_skip_dispatch); + PyArrayObject *(*predict)(struct __pyx_obj_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*apply)(struct __pyx_obj_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*_apply_dense)(struct __pyx_obj_5_tree_Tree *, PyObject *); + PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_5_tree_Tree *, PyObject *); + PyObject *(*decision_path)(struct __pyx_obj_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyObject *(*_decision_path_dense)(struct __pyx_obj_5_tree_Tree *, PyObject *); + PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_5_tree_Tree *, PyObject *); + PyObject *(*compute_feature_importances)(struct __pyx_obj_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); +}; +static struct __pyx_vtabstruct_5_tree_Tree *__pyx_vtabptr_5_tree_Tree; +static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_Tree *, PyObject *); +static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_tree_Tree *, PyObject *); +static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tree_Tree *, PyObject *); +static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj_5_tree_Tree *, PyObject *); + + +/* "_tree.pyx":75 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * """Interface for different tree building strategies.""" + * + */ + +struct __pyx_vtabstruct_5_tree_TreeBuilder { + PyObject *(*build)(struct __pyx_obj_5_tree_TreeBuilder *, struct __pyx_obj_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_11TreeBuilder_build *__pyx_optional_args); + PyObject *(*_check_input)(struct __pyx_obj_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); +}; +static struct __pyx_vtabstruct_5_tree_TreeBuilder *__pyx_vtabptr_5_tree_TreeBuilder; +static PyObject *__pyx_f_5_tree_11TreeBuilder__check_input(struct __pyx_obj_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); + + +/* "_tree.pyx":114 + * # Depth first builder --------------------------------------------------------- + * + * cdef class DepthFirstTreeBuilder(TreeBuilder): # <<<<<<<<<<<<<< + * """Build a decision tree in depth-first fashion.""" + * + */ + +struct __pyx_vtabstruct_5_tree_DepthFirstTreeBuilder { + struct __pyx_vtabstruct_5_tree_TreeBuilder __pyx_base; +}; +static struct __pyx_vtabstruct_5_tree_DepthFirstTreeBuilder *__pyx_vtabptr_5_tree_DepthFirstTreeBuilder; + + +/* "_tree.pyx":282 + * + * + * cdef class BestFirstTreeBuilder(TreeBuilder): # <<<<<<<<<<<<<< + * """Build a decision tree in best-first fashion. + * + */ + +struct __pyx_vtabstruct_5_tree_BestFirstTreeBuilder { + struct __pyx_vtabstruct_5_tree_TreeBuilder __pyx_base; + int (*_add_split_node)(struct __pyx_obj_5_tree_BestFirstTreeBuilder *, struct __pyx_obj_9_splitter_Splitter *, struct __pyx_obj_5_tree_Tree *, __pyx_t_5_tree_SIZE_t, __pyx_t_5_tree_SIZE_t, double, int, int, struct __pyx_t_5_tree_Node *, __pyx_t_5_tree_SIZE_t, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_5_tree_SIZE_t); +}; +static struct __pyx_vtabstruct_5_tree_BestFirstTreeBuilder *__pyx_vtabptr_5_tree_BestFirstTreeBuilder; +static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_5_tree_BestFirstTreeBuilder *, struct __pyx_obj_9_splitter_Splitter *, struct __pyx_obj_5_tree_Tree *, __pyx_t_5_tree_SIZE_t, __pyx_t_5_tree_SIZE_t, double, int, int, struct __pyx_t_5_tree_Node *, __pyx_t_5_tree_SIZE_t, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_5_tree_SIZE_t); + + +/* "_tree.pyx":1316 + * + * + * cdef class _CCPPruneController: # <<<<<<<<<<<<<< + * """Base class used by build_pruned_tree_ccp and ccp_pruning_path + * to control pruning. + */ + +struct __pyx_vtabstruct_5_tree__CCPPruneController { + int (*stop_pruning)(struct __pyx_obj_5_tree__CCPPruneController *, __pyx_t_5_tree_DOUBLE_t); + void (*save_metrics)(struct __pyx_obj_5_tree__CCPPruneController *, __pyx_t_5_tree_DOUBLE_t, __pyx_t_5_tree_DOUBLE_t); + void (*after_pruning)(struct __pyx_obj_5_tree__CCPPruneController *, __Pyx_memviewslice); 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+static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + +/* PyFunctionFastCall.proto */ +#if CYTHON_FAST_PYCALL +#define __Pyx_PyFunction_FastCall(func, args, nargs)\ + __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); +#else +#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) +#endif +#define __Pyx_BUILD_ASSERT_EXPR(cond)\ + (sizeof(char [1 - 2*!(cond)]) - 1) +#ifndef Py_MEMBER_SIZE +#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) +#endif + static size_t __pyx_pyframe_localsplus_offset = 0; + #include "frameobject.h" + #define __Pxy_PyFrame_Initialize_Offsets()\ + ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ + (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) + #define __Pyx_PyFrame_GetLocalsplus(frame)\ + (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) +#endif + +/* PyCFunctionFastCall.proto */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); +#else +#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) +#endif + +/* PyObjectCall.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); +#else +#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) +#endif + +/* RaiseArgTupleInvalid.proto */ +static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, + Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found); + +/* RaiseDoubleKeywords.proto */ +static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); + +/* ParseKeywords.proto */ +static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ + PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ + const char* function_name); + +/* ArgTypeTest.proto */ +#define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\ + ((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\ + __Pyx__ArgTypeTest(obj, type, name, exact)) +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact); + +/* GetModuleGlobalName.proto */ +#if CYTHON_USE_DICT_VERSIONS +#define __Pyx_GetModuleGlobalName(var, name) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + (var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\ + (likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\ + __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +#define __Pyx_GetModuleGlobalNameUncached(var, name) {\ + PY_UINT64_T __pyx_dict_version;\ + PyObject *__pyx_dict_cached_value;\ + (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value); +#else +#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) +#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); +#endif + +/* PyObjectCall2Args.proto */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); + +/* PyObjectCallMethO.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); +#endif + +/* PyObjectCallOneArg.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); + +/* PyObjectCallNoArg.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); +#else +#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) +#endif + +/* PyObjectSetAttrStr.proto */ +#if CYTHON_USE_TYPE_SLOTS +#define __Pyx_PyObject_DelAttrStr(o,n) __Pyx_PyObject_SetAttrStr(o, n, NULL) +static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value); +#else +#define __Pyx_PyObject_DelAttrStr(o,n) PyObject_DelAttr(o,n) +#define __Pyx_PyObject_SetAttrStr(o,n,v) PyObject_SetAttr(o,n,v) +#endif + +/* PyThreadStateGet.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate; +#define __Pyx_PyThreadState_assign __pyx_tstate = __Pyx_PyThreadState_Current; +#define __Pyx_PyErr_Occurred() __pyx_tstate->curexc_type +#else +#define __Pyx_PyThreadState_declare +#define __Pyx_PyThreadState_assign +#define __Pyx_PyErr_Occurred() PyErr_Occurred() +#endif + +/* PyErrFetchRestore.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL) +#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) +#else +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#endif +#else +#define __Pyx_PyErr_Clear() PyErr_Clear() +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) +#endif + +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + +/* PyErrExceptionMatches.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) +static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); +#else +#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) +#endif + +/* GetAttr.proto */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); + +/* GetAttr3.proto */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *); + +/* RaiseTooManyValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); + +/* RaiseNeedMoreValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); + +/* IterFinish.proto */ +static CYTHON_INLINE int __Pyx_IterFinish(void); + +/* UnpackItemEndCheck.proto */ +static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected); + +/* MemviewSliceInit.proto */ +#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d +#define __Pyx_MEMVIEW_DIRECT 1 +#define __Pyx_MEMVIEW_PTR 2 +#define __Pyx_MEMVIEW_FULL 4 +#define __Pyx_MEMVIEW_CONTIG 8 +#define __Pyx_MEMVIEW_STRIDED 16 +#define __Pyx_MEMVIEW_FOLLOW 32 +#define __Pyx_IS_C_CONTIG 1 +#define __Pyx_IS_F_CONTIG 2 +static int __Pyx_init_memviewslice( + struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference); +static CYTHON_INLINE int __pyx_add_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p) +#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview)) +#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__) +#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__) +static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); + +/* GetItemInt.proto */ +#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ + __Pyx_GetItemInt_Generic(o, to_py_func(i)))) +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck); + +/* ObjectGetItem.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key); +#else +#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) +#endif + +/* SliceObject.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice( + PyObject* obj, Py_ssize_t cstart, Py_ssize_t cstop, + PyObject** py_start, PyObject** py_stop, PyObject** py_slice, + int has_cstart, int has_cstop, int wraparound); + +/* PyIntCompare.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_EqObjC(PyObject *op1, PyObject *op2, long intval, long inplace); + +/* DictGetItem.proto */ +#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key); +#define __Pyx_PyObject_Dict_GetItem(obj, name)\ + (likely(PyDict_CheckExact(obj)) ?\ + __Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name)) +#else +#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) +#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name) +#endif + +/* PySequenceContains.proto */ +static CYTHON_INLINE int __Pyx_PySequence_ContainsTF(PyObject* item, PyObject* seq, int eq) { + int result = PySequence_Contains(seq, item); + return unlikely(result < 0) ? result : (result == (eq == Py_EQ)); +} + +/* PyIntCompare.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_NeObjC(PyObject *op1, PyObject *op2, long intval, long inplace); + +/* IncludeStringH.proto */ +#include + +/* BytesEquals.proto */ +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); + +/* UnicodeEquals.proto */ +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals); + +/* StrEquals.proto */ +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals +#else +#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals +#endif + +/* ListAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_PyList_Append(L,x) PyList_Append(L,x) +#endif + +/* PyObjectGetMethod.proto */ +static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method); + +/* PyObjectCallMethod1.proto */ +static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg); + +/* append.proto */ +static CYTHON_INLINE int __Pyx_PyObject_Append(PyObject* L, PyObject* x); + +/* PyIntBinop.proto */ +#if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); +#else +#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ + (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) +#endif + +/* ListCompAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len)) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) +#endif + +/* SliceObject.proto */ +#define __Pyx_PyObject_DelSlice(obj, cstart, cstop, py_start, py_stop, py_slice, has_cstart, has_cstop, wraparound)\ + __Pyx_PyObject_SetSlice(obj, (PyObject*)NULL, cstart, cstop, py_start, py_stop, py_slice, has_cstart, has_cstop, wraparound) +static CYTHON_INLINE int __Pyx_PyObject_SetSlice( + PyObject* obj, PyObject* value, Py_ssize_t cstart, Py_ssize_t cstop, + PyObject** py_start, PyObject** py_stop, PyObject** py_slice, + int has_cstart, int has_cstop, int wraparound); + +/* MatrixMultiply.proto */ +#if PY_VERSION_HEX >= 0x03050000 + #define __Pyx_PyNumber_MatrixMultiply(x,y) PyNumber_MatrixMultiply(x,y) + #define __Pyx_PyNumber_InPlaceMatrixMultiply(x,y) PyNumber_InPlaceMatrixMultiply(x,y) +#else +#define __Pyx_PyNumber_MatrixMultiply(x,y) __Pyx__PyNumber_MatrixMultiply(x, y, "@") +static PyObject* __Pyx__PyNumber_MatrixMultiply(PyObject* x, PyObject* y, const char* op_name); +static PyObject* __Pyx_PyNumber_InPlaceMatrixMultiply(PyObject* x, PyObject* y); +#endif + +/* IsLittleEndian.proto */ +static CYTHON_INLINE int __Pyx_Is_Little_Endian(void); + +/* BufferFormatCheck.proto */ +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts); +static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type); + +/* BufferGetAndValidate.proto */ +#define __Pyx_GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)\ + ((obj == Py_None || obj == NULL) ?\ + (__Pyx_ZeroBuffer(buf), 0) :\ + __Pyx__GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)) +static int __Pyx__GetBufferAndValidate(Py_buffer* buf, PyObject* obj, + __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack); +static void __Pyx_ZeroBuffer(Py_buffer* buf); +static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); +static Py_ssize_t __Pyx_minusones[] = { -1, -1, -1, -1, -1, -1, -1, -1 }; +static Py_ssize_t __Pyx_zeros[] = { 0, 0, 0, 0, 0, 0, 0, 0 }; + +#define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0) +/* BufferFallbackError.proto */ +static void __Pyx_RaiseBufferFallbackError(void); + +/* WriteUnraisableException.proto */ +static void __Pyx_WriteUnraisable(const char *name, int clineno, + int lineno, const char *filename, + int full_traceback, int nogil); + +/* SetItemInt.proto */ +#define __Pyx_SetItemInt(o, i, v, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_SetItemInt_Fast(o, (Py_ssize_t)i, v, is_list, wraparound, boundscheck) :\ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list assignment index out of range"), -1) :\ + __Pyx_SetItemInt_Generic(o, to_py_func(i), v))) +static int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v); +static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, + int is_list, int wraparound, int boundscheck); + +/* Import.proto */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + +/* ImportFrom.proto */ +static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); + +/* HasAttr.proto */ +static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *); + +/* GetTopmostException.proto */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); +#endif + +/* SaveResetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +#else +#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) +#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) +#endif + +/* GetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* UnaryNegOverflows.proto */ +#define UNARY_NEG_WOULD_OVERFLOW(x)\ + (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) + +static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/ +/* decode_c_string_utf16.proto */ +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 0; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = -1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} + +/* decode_c_string.proto */ +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); + +/* RaiseNoneIterError.proto */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); + +/* SwapException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* FastTypeChecks.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); +#else +#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) +#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) +#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) +#endif +#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) + +static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +/* ListExtend.proto */ +static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject* none = _PyList_Extend((PyListObject*)L, v); + if (unlikely(!none)) + return -1; + Py_DECREF(none); + return 0; +#else + return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v); +#endif +} + +/* None.proto */ +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); + +/* StringJoin.proto */ +#if PY_MAJOR_VERSION < 3 +#define __Pyx_PyString_Join __Pyx_PyBytes_Join +#define __Pyx_PyBaseString_Join(s, v) (PyUnicode_CheckExact(s) ? PyUnicode_Join(s, v) : __Pyx_PyBytes_Join(s, v)) +#else +#define __Pyx_PyString_Join PyUnicode_Join +#define __Pyx_PyBaseString_Join PyUnicode_Join +#endif +#if CYTHON_COMPILING_IN_CPYTHON + #if PY_MAJOR_VERSION < 3 + #define __Pyx_PyBytes_Join _PyString_Join + #else + #define __Pyx_PyBytes_Join _PyBytes_Join + #endif +#else +static CYTHON_INLINE PyObject* __Pyx_PyBytes_Join(PyObject* sep, PyObject* values); +#endif + +/* PyObject_Unicode.proto */ +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyObject_Unicode(obj)\ + (likely(PyUnicode_CheckExact(obj)) ? __Pyx_NewRef(obj) : PyObject_Str(obj)) +#else +#define __Pyx_PyObject_Unicode(obj)\ + (likely(PyUnicode_CheckExact(obj)) ? __Pyx_NewRef(obj) : PyObject_Unicode(obj)) +#endif + +/* PyObject_GenericGetAttrNoDict.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr +#endif + +/* PyObject_GenericGetAttr.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr +#endif + +/* SetVTable.proto */ +static int __Pyx_SetVtable(PyObject *dict, void *vtable); + +/* PyObjectGetAttrStrNoError.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); + +/* SetupReduce.proto */ +static int __Pyx_setup_reduce(PyObject* type_obj); + +/* TypeImport.proto */ +#ifndef __PYX_HAVE_RT_ImportType_proto +#define __PYX_HAVE_RT_ImportType_proto +enum __Pyx_ImportType_CheckSize { + __Pyx_ImportType_CheckSize_Error = 0, + __Pyx_ImportType_CheckSize_Warn = 1, + __Pyx_ImportType_CheckSize_Ignore = 2 +}; +static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); +#endif + +/* GetVTable.proto */ +static void* __Pyx_GetVtable(PyObject *dict); + +/* CLineInTraceback.proto */ +#ifdef CYTHON_CLINE_IN_TRACEBACK +#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) +#else +static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); +#endif + +/* CodeObjectCache.proto */ +typedef struct { + PyCodeObject* code_object; + int code_line; +} __Pyx_CodeObjectCacheEntry; +struct __Pyx_CodeObjectCache { + int count; + int max_count; + __Pyx_CodeObjectCacheEntry* entries; +}; +static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); +static PyCodeObject *__pyx_find_code_object(int code_line); +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); + +/* AddTraceback.proto */ +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename); + +#if PY_MAJOR_VERSION < 3 + static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); + static void __Pyx_ReleaseBuffer(Py_buffer *view); +#else + #define __Pyx_GetBuffer PyObject_GetBuffer + #define __Pyx_ReleaseBuffer PyBuffer_Release +#endif + + +/* BufferStructDeclare.proto */ +typedef struct { + Py_ssize_t shape, strides, suboffsets; +} __Pyx_Buf_DimInfo; +typedef struct { + size_t refcount; + Py_buffer pybuffer; +} __Pyx_Buffer; +typedef struct { + __Pyx_Buffer *rcbuffer; + char *data; + __Pyx_Buf_DimInfo diminfo[8]; +} __Pyx_LocalBuf_ND; + +/* MemviewSliceIsContig.proto */ +static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); + +/* OverlappingSlices.proto */ +static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize); + +/* Capsule.proto */ +static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); + +/* GCCDiagnostics.proto */ +#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) +#define __Pyx_HAS_GCC_DIAGNOSTIC +#endif + +struct __pyx_t_5_tree_Node; +static PyObject* __pyx_convert__to_py_struct____pyx_t_5_tree_Node(struct __pyx_t_5_tree_Node s); +/* MemviewDtypeToObject.proto */ +static CYTHON_INLINE PyObject *__pyx_memview_get_nn_struct____pyx_t_5_tree_Node(const char *itemp); +static CYTHON_INLINE int __pyx_memview_set_nn_struct____pyx_t_5_tree_Node(const char *itemp, PyObject *obj); + +/* None.proto */ +static CYTHON_INLINE long __Pyx_pow_long(long, long); + +/* None.proto */ +static CYTHON_INLINE int __Pyx_ErrOccurredWithGIL(void); /* proto */ + +/* RealImag.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #define __Pyx_CREAL(z) ((z).real()) + #define __Pyx_CIMAG(z) ((z).imag()) + #else + #define __Pyx_CREAL(z) (__real__(z)) + #define __Pyx_CIMAG(z) (__imag__(z)) + #endif +#else + #define __Pyx_CREAL(z) ((z).real) + #define __Pyx_CIMAG(z) ((z).imag) +#endif +#if defined(__cplusplus) && CYTHON_CCOMPLEX\ + && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) + #define __Pyx_SET_CREAL(z,x) ((z).real(x)) + #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) +#else + #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) + #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_float(a, b) ((a)==(b)) + #define __Pyx_c_sum_float(a, b) ((a)+(b)) + #define __Pyx_c_diff_float(a, b) ((a)-(b)) + #define __Pyx_c_prod_float(a, b) ((a)*(b)) + #define __Pyx_c_quot_float(a, b) ((a)/(b)) + #define __Pyx_c_neg_float(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_float(z) ((z)==(float)0) + #define __Pyx_c_conj_float(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_float(z) (::std::abs(z)) + #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_float(z) ((z)==0) + #define __Pyx_c_conj_float(z) (conjf(z)) + #if 1 + #define __Pyx_c_abs_float(z) (cabsf(z)) + #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); + #endif +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_double(a, b) ((a)==(b)) + #define __Pyx_c_sum_double(a, b) ((a)+(b)) + #define __Pyx_c_diff_double(a, b) ((a)-(b)) + #define __Pyx_c_prod_double(a, b) ((a)*(b)) + #define __Pyx_c_quot_double(a, b) ((a)/(b)) + #define __Pyx_c_neg_double(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_double(z) ((z)==(double)0) + #define __Pyx_c_conj_double(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (::std::abs(z)) + #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_double(z) ((z)==0) + #define __Pyx_c_conj_double(z) (conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (cabs(z)) + #define __Pyx_c_pow_double(a, b) (cpow(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); + #endif +#endif + +/* MemviewSliceCopyTemplate.proto */ +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object); + +/* TypeInfoToFormat.proto */ +struct __pyx_typeinfo_string { + char string[3]; +}; +static struct __pyx_typeinfo_string __Pyx_TypeInfoToFormat(__Pyx_TypeInfo *type); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_int32(npy_int32 value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_uint32(npy_uint32 value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); + +/* TypeInfoCompare.proto */ +static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); + +/* MemviewSliceValidateAndInit.proto */ +static int __Pyx_ValidateAndInit_memviewslice( + int *axes_specs, + int c_or_f_flag, + int buf_flags, + int ndim, + __Pyx_TypeInfo *dtype, + __Pyx_BufFmt_StackElem stack[], + __Pyx_memviewslice *memviewslice, + PyObject *original_obj); + +/* ObjectToMemviewSlice.proto */ +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__(PyObject *, int writable_flag); + +/* ObjectToMemviewSlice.proto */ +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_5_tree_DTYPE_t__const__(PyObject *, int writable_flag); + +/* ObjectToMemviewSlice.proto */ +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_DOUBLE_t(PyObject *, int writable_flag); + +/* ObjectToMemviewSlice.proto */ +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_SIZE_t(PyObject *, int writable_flag); + +/* ObjectToMemviewSlice.proto */ +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_unsigned_char(PyObject *, int writable_flag); + +/* CheckBinaryVersion.proto */ +static int __Pyx_check_binary_version(void); + +/* VoidPtrImport.proto */ +static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig); + +/* FunctionImport.proto */ +static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig); + +/* InitStrings.proto */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); + +static PyObject *__pyx_f_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_5_tree_Tree *__pyx_v_tree, CYTHON_UNUSED PyObject *__pyx_v_X, CYTHON_UNUSED PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_11TreeBuilder_build *__pyx_optional_args); /* proto*/ +static PyObject *__pyx_f_5_tree_11TreeBuilder__check_input(CYTHON_UNUSED struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto*/ +static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_21DepthFirstTreeBuilder_build *__pyx_optional_args); /* proto*/ +static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_20BestFirstTreeBuilder_build *__pyx_optional_args); /* proto*/ +static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, __pyx_t_5_tree_SIZE_t __pyx_v_start, __pyx_t_5_tree_SIZE_t __pyx_v_end, double __pyx_v_impurity, int __pyx_v_is_first, int __pyx_v_is_left, struct __pyx_t_5_tree_Node *__pyx_v_parent, __pyx_t_5_tree_SIZE_t __pyx_v_depth, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *__pyx_v_res, __pyx_t_5_tree_SIZE_t __pyx_v_n_samples); /* proto*/ +static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_self, __pyx_t_5_tree_SIZE_t __pyx_v_capacity); /* proto*/ +static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_self, struct __pyx_opt_args_5_tree_4Tree__resize_c *__pyx_optional_args); /* proto*/ +static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_tree_Tree *__pyx_v_self, __pyx_t_5_tree_SIZE_t __pyx_v_parent, int __pyx_v_is_left, int __pyx_v_is_leaf, __pyx_t_5_tree_SIZE_t __pyx_v_feature, double __pyx_v_threshold, double __pyx_v_impurity, __pyx_t_5_tree_SIZE_t __pyx_v_n_node_samples, double __pyx_v_weighted_n_node_samples); /* proto*/ +static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ +static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_K_cand_train, PyArrayObject *__pyx_v_sq_norms_cand, PyObject *__pyx_v_criterion, PyObject *__pyx_v_kernel, __pyx_t_5_tree_SIZE_t __pyx_v_return_top_k, int __pyx_skip_dispatch); /* proto*/ +static PyArrayObject *__pyx_f_5_tree_4Tree_apply(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ +static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ +static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ +static PyObject *__pyx_f_5_tree_4Tree_decision_path(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ +static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ +static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ +static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_obj_5_tree_Tree *__pyx_v_self, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); /* proto*/ +static PyArrayObject *__pyx_f_5_tree_4Tree__get_value_ndarray(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto*/ +static PyArrayObject *__pyx_f_5_tree_4Tree__get_node_ndarray(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto*/ +static int __pyx_f_5_tree_19_CCPPruneController_stop_pruning(CYTHON_UNUSED struct __pyx_obj_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __pyx_t_5_tree_DOUBLE_t __pyx_v_effective_alpha); /* proto*/ +static void __pyx_f_5_tree_19_CCPPruneController_save_metrics(CYTHON_UNUSED struct __pyx_obj_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __pyx_t_5_tree_DOUBLE_t __pyx_v_effective_alpha, CYTHON_UNUSED __pyx_t_5_tree_DOUBLE_t __pyx_v_subtree_impurities); /* proto*/ +static void __pyx_f_5_tree_19_CCPPruneController_after_pruning(CYTHON_UNUSED struct __pyx_obj_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_in_subtree); /* proto*/ +static int __pyx_f_5_tree_12_AlphaPruner_stop_pruning(struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_self, __pyx_t_5_tree_DOUBLE_t __pyx_v_effective_alpha); /* proto*/ +static void __pyx_f_5_tree_12_AlphaPruner_after_pruning(struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_self, __Pyx_memviewslice __pyx_v_in_subtree); /* proto*/ +static void __pyx_f_5_tree_11_PathFinder_save_metrics(struct __pyx_obj_5_tree__PathFinder *__pyx_v_self, __pyx_t_5_tree_DOUBLE_t __pyx_v_effective_alpha, __pyx_t_5_tree_DOUBLE_t __pyx_v_subtree_impurities); /* proto*/ +static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ +static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ +static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ + +/* Module declarations from 'cpython.buffer' */ + +/* Module declarations from 'libc.string' */ + +/* Module declarations from 'libc.stdio' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.type' */ +static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; + +/* Module declarations from 'cpython.version' */ + +/* Module declarations from 'cpython.exc' */ + +/* Module declarations from 'cpython.module' */ + +/* Module declarations from 'cpython.mem' */ + +/* Module declarations from 'cpython.tuple' */ + +/* Module declarations from 'cpython.list' */ + +/* Module declarations from 'cpython.sequence' */ + +/* Module declarations from 'cpython.mapping' */ + +/* Module declarations from 'cpython.iterator' */ + +/* Module declarations from 'cpython.number' */ + +/* Module declarations from 'cpython.int' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.bool' */ +static PyTypeObject *__pyx_ptype_7cpython_4bool_bool = 0; + +/* Module declarations from 'cpython.long' */ + +/* Module declarations from 'cpython.float' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.complex' */ +static PyTypeObject *__pyx_ptype_7cpython_7complex_complex = 0; + +/* Module declarations from 'cpython.string' */ + +/* Module declarations from 'cpython.unicode' */ + +/* Module declarations from 'cpython.dict' */ + +/* Module declarations from 'cpython.instance' */ + +/* Module declarations from 'cpython.function' */ + +/* Module declarations from 'cpython.method' */ + +/* Module declarations from 'cpython.weakref' */ + +/* Module declarations from 'cpython.getargs' */ + +/* Module declarations from 'cpython.pythread' */ + +/* Module declarations from 'cpython.pystate' */ + +/* Module declarations from 'cpython.cobject' */ + +/* Module declarations from 'cpython.oldbuffer' */ + +/* Module declarations from 'cpython.set' */ + +/* Module declarations from 'cpython.bytes' */ + +/* Module declarations from 'cpython.pycapsule' */ + +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + +/* Module declarations from 'numpy' */ + +/* Module declarations from 'numpy' */ +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; +static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; +static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; +static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; +static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; +static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ + +/* Module declarations from 'sklearn.tree._criterion' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_Criterion = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_ClassificationCriterion = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_RegressionCriterion = 0; + +/* Module declarations from 'sklearn.tree._splitter' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_9_splitter_Splitter = 0; + +/* Module declarations from 'sklearn.tree._tree' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_Tree = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_TreeBuilder = 0; + +/* Module declarations from '_criterion' */ +static PyTypeObject *__pyx_ptype_10_criterion_Criterion = 0; +static PyTypeObject *__pyx_ptype_10_criterion_KernelizedRegressionCriterion = 0; + +/* Module declarations from '_splitter' */ +static PyTypeObject *__pyx_ptype_9_splitter_Splitter = 0; + +/* Module declarations from 'libc.stdlib' */ + +/* Module declarations from 'libc.math' */ + +/* Module declarations from 'libc.stdint' */ + +/* Module declarations from 'sklearn.neighbors._quad_tree' */ +static PyTypeObject *__pyx_ptype_7sklearn_9neighbors_10_quad_tree__QuadTree = 0; +static float *__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON = 0; +#define __pyx_v_7sklearn_9neighbors_10_quad_tree_EPSILON (*__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON) + +/* Module declarations from 'sklearn.tree._utils' */ +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_Stack = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_PriorityHeap = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedPQueue = 0; +static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedMedianCalculator = 0; +static PyArrayObject *(*__pyx_f_7sklearn_4tree_6_utils_sizet_ptr_to_ndarray)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DTYPE_t **, size_t); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t **, size_t); /*proto*/ +static unsigned char *(*__pyx_fuse_2__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **, size_t); /*proto*/ +static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t ***, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_5_tree_Node *(*__pyx_fuse_6__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_5_tree_Node **(*__pyx_fuse_8__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node ***, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_StackRecord **, size_t); /*proto*/ +static struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord **, size_t); /*proto*/ + +/* Module declarations from '_tree' */ +static PyTypeObject *__pyx_ptype_5_tree_Tree = 0; +static PyTypeObject *__pyx_ptype_5_tree_TreeBuilder = 0; +static PyTypeObject *__pyx_ptype_5_tree_DepthFirstTreeBuilder = 0; +static PyTypeObject *__pyx_ptype_5_tree_BestFirstTreeBuilder = 0; +static PyTypeObject *__pyx_ptype_5_tree__CCPPruneController = 0; +static PyTypeObject *__pyx_ptype_5_tree__AlphaPruner = 0; +static PyTypeObject *__pyx_ptype_5_tree__PathFinder = 0; +static PyTypeObject *__pyx_array_type = 0; +static PyTypeObject *__pyx_MemviewEnum_type = 0; +static PyTypeObject *__pyx_memoryview_type = 0; +static PyTypeObject *__pyx_memoryviewslice_type = 0; +static double __pyx_v_5_tree_INFINITY; +static double __pyx_v_5_tree_EPSILON; +static int __pyx_v_5_tree_IS_FIRST; +static int __pyx_v_5_tree_IS_NOT_FIRST; +static int __pyx_v_5_tree_IS_LEFT; +static int __pyx_v_5_tree_IS_NOT_LEFT; +static __pyx_t_5_tree_SIZE_t __pyx_v_5_tree__TREE_LEAF; +static __pyx_t_5_tree_SIZE_t __pyx_v_5_tree__TREE_UNDEFINED; +static __pyx_t_5_tree_SIZE_t __pyx_v_5_tree_INITIAL_STACK_SIZE; +static struct __pyx_t_5_tree_Node __pyx_v_5_tree_dummy; +static PyObject *generic = 0; +static PyObject *strided = 0; +static PyObject *indirect = 0; +static PyObject *contiguous = 0; +static PyObject *indirect_contiguous = 0; +static int __pyx_memoryview_thread_locks_used; +static PyThread_type_lock __pyx_memoryview_thread_locks[8]; +static CYTHON_INLINE int __pyx_f_5_tree__add_to_frontier(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); /*proto*/ +static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice, struct __pyx_obj_5_tree_Tree *, struct __pyx_obj_5_tree__CCPPruneController *); /*proto*/ +static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree *, struct __pyx_obj_5_tree_Tree *, __Pyx_memviewslice, __pyx_t_5_tree_SIZE_t); /*proto*/ +static PyObject *__pyx_f_5_tree___pyx_unpickle_TreeBuilder__set_state(struct __pyx_obj_5_tree_TreeBuilder *, PyObject *); /*proto*/ +static PyObject *__pyx_f_5_tree___pyx_unpickle__CCPPruneController__set_state(struct __pyx_obj_5_tree__CCPPruneController *, PyObject *); /*proto*/ +static struct __pyx_t_5_tree_Node __pyx_convert__from_py_struct____pyx_t_5_tree_Node(PyObject *); /*proto*/ +static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ +static void *__pyx_align_pointer(void *, size_t); /*proto*/ +static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ +static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ +static PyObject *_unellipsify(PyObject *, int); /*proto*/ +static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ +static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ +static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ +static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ +static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ +static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ +static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ +static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ +static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ +static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ +static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ +static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ +static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ +static PyObject *__pyx_format_from_typeinfo(__Pyx_TypeInfo *); /*proto*/ +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t = { "SIZE_t", NULL, sizeof(__pyx_t_5_tree_SIZE_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_5_tree_SIZE_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_5_tree_SIZE_t), 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5_tree_DTYPE_t = { "DTYPE_t", NULL, sizeof(__pyx_t_5_tree_DTYPE_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5_tree_INT32_t = { "INT32_t", NULL, sizeof(__pyx_t_5_tree_INT32_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_5_tree_INT32_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_5_tree_INT32_t), 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t = { "float64_t", NULL, sizeof(__pyx_t_5numpy_float64_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5_tree_DOUBLE_t = { "DOUBLE_t", NULL, sizeof(__pyx_t_5_tree_DOUBLE_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_StructField __Pyx_StructFields_nn_struct____pyx_t_5_tree_Node[] = { + {&__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, "left_child", offsetof(struct __pyx_t_5_tree_Node, left_child)}, + {&__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, "right_child", offsetof(struct __pyx_t_5_tree_Node, right_child)}, + {&__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, "feature", offsetof(struct __pyx_t_5_tree_Node, feature)}, + {&__Pyx_TypeInfo_nn___pyx_t_5_tree_DOUBLE_t, "threshold", offsetof(struct __pyx_t_5_tree_Node, threshold)}, + {&__Pyx_TypeInfo_nn___pyx_t_5_tree_DOUBLE_t, "impurity", offsetof(struct __pyx_t_5_tree_Node, impurity)}, + {&__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, "n_node_samples", offsetof(struct __pyx_t_5_tree_Node, n_node_samples)}, + {&__Pyx_TypeInfo_nn___pyx_t_5_tree_DOUBLE_t, "weighted_n_node_samples", offsetof(struct __pyx_t_5_tree_Node, weighted_n_node_samples)}, + {NULL, NULL, 0} +}; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn_struct____pyx_t_5_tree_Node = { "Node", __Pyx_StructFields_nn_struct____pyx_t_5_tree_Node, sizeof(struct __pyx_t_5_tree_Node), { 0 }, 0, 'S', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__ = { "const DOUBLE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const ), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5_tree_DTYPE_t__const__ = { "const DTYPE_t", NULL, sizeof(__pyx_t_5_tree_DTYPE_t const ), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_unsigned_char = { "unsigned char", NULL, sizeof(unsigned char), { 0 }, 0, IS_UNSIGNED(unsigned char) ? 'U' : 'I', IS_UNSIGNED(unsigned char), 0 }; +#define __Pyx_MODULE_NAME "_tree" +extern int __pyx_module_is_main__tree; +int __pyx_module_is_main__tree = 0; + +/* Implementation of '_tree' */ +static PyObject *__pyx_builtin_ValueError; +static PyObject *__pyx_builtin_MemoryError; +static PyObject *__pyx_builtin_TypeError; +static PyObject *__pyx_builtin_range; +static PyObject *__pyx_builtin_enumerate; +static PyObject *__pyx_builtin_NotImplementedError; +static PyObject *__pyx_builtin_ImportError; +static PyObject *__pyx_builtin_KeyError; +static PyObject *__pyx_builtin_Ellipsis; +static PyObject *__pyx_builtin_id; +static PyObject *__pyx_builtin_IndexError; +static const char __pyx_k_C[] = "C"; +static const char __pyx_k_O[] = "O"; +static const char __pyx_k_T[] = "T{"; + static const char __pyx_k_X[] = "X"; + static const char __pyx_k_c[] = "c"; + static const char __pyx_k_s[] = "(%s)"; + static const char __pyx_k_y[] = "y"; + static const char __pyx_k_id[] = "id"; + static const char __pyx_k_np[] = "np"; + static const char __pyx_k_K_y[] = "K_y"; + static const char __pyx_k__43[] = "^"; + static const char __pyx_k__44[] = ""; + static const char __pyx_k__45[] = ":"; +static const char __pyx_k__46[] = "}"; +static const char __pyx_k__47[] = ","; +static const char __pyx_k_eps[] = "eps"; +static const char __pyx_k_inf[] = "inf"; +static const char __pyx_k_max[] = "max"; +static const char __pyx_k_new[] = "__new__"; +static const char __pyx_k_obj[] = "obj"; +static const char __pyx_k_sum[] = "sum"; +static const char __pyx_k_Tree[] = "Tree"; +static const char __pyx_k_base[] = "base"; +static const char __pyx_k_data[] = "data"; +static const char __pyx_k_dict[] = "__dict__"; +static const char __pyx_k_intp[] = "intp"; +static const char __pyx_k_join[] = "join"; +static const char __pyx_k_main[] = "__main__"; +static const char __pyx_k_mean[] = "mean"; +static const char __pyx_k_mode[] = "mode"; +static const char __pyx_k_name[] = "name"; +static const char __pyx_k_ndim[] = "ndim"; +static const char __pyx_k_ones[] = "ones"; +static const char __pyx_k_pack[] = "pack"; +static const char __pyx_k_size[] = "size"; +static const char __pyx_k_step[] = "step"; +static const char __pyx_k_stop[] = "stop"; +static const char __pyx_k_test[] = "__test__"; +static const char __pyx_k_tree[] = "tree"; +static const char __pyx_k_ASCII[] = "ASCII"; +static const char __pyx_k_DTYPE[] = "DTYPE"; +static const char __pyx_k_apply[] = "apply"; +static const char __pyx_k_array[] = "array"; +static const char __pyx_k_build[] = "build"; +static const char __pyx_k_class[] = "__class__"; +static const char __pyx_k_count[] = "count"; +static const char __pyx_k_dtype[] = "dtype"; +static const char __pyx_k_empty[] = "empty"; +static const char __pyx_k_error[] = "error"; +static const char __pyx_k_finfo[] = "finfo"; +static const char __pyx_k_flags[] = "flags"; +static const char __pyx_k_int32[] = "int32"; +static const char __pyx_k_nodes[] = "nodes"; +static const char __pyx_k_numpy[] = "numpy"; +static const char __pyx_k_order[] = "order"; +static const char __pyx_k_range[] = "range"; +static const char __pyx_k_shape[] = "shape"; +static const char __pyx_k_start[] = "start"; +static const char __pyx_k_tocsc[] = "tocsc"; +static const char __pyx_k_tocsr[] = "tocsr"; +static const char __pyx_k_uint8[] = "uint8"; +static const char __pyx_k_where[] = "where"; +static const char __pyx_k_zeros[] = "zeros"; +static const char __pyx_k_DOUBLE[] = "DOUBLE"; +static const char __pyx_k_append[] = "append"; +static const char __pyx_k_argmax[] = "argmax"; +static const char __pyx_k_double[] = "double"; +static const char __pyx_k_encode[] = "encode"; +static const char __pyx_k_format[] = "format"; +static const char __pyx_k_import[] = "__import__"; +static const char __pyx_k_indptr[] = "indptr"; +static const char __pyx_k_kernel[] = "kernel"; +static const char __pyx_k_matmul[] = "__matmul__"; +static const char __pyx_k_name_2[] = "__name__"; +static const char __pyx_k_pickle[] = "pickle"; +static const char __pyx_k_reduce[] = "__reduce__"; +static const char __pyx_k_struct[] = "struct"; +static const char __pyx_k_tree_2[] = "_tree"; +static const char __pyx_k_unique[] = "unique"; +static const char __pyx_k_unpack[] = "unpack"; +static const char __pyx_k_update[] = "update"; +static const char __pyx_k_values[] = "values"; +static const char __pyx_k_asarray[] = "asarray"; +static const char __pyx_k_feature[] = "feature"; +static const char __pyx_k_float32[] = "float32"; +static const char __pyx_k_float64[] = "float64"; +static const char __pyx_k_fortran[] = "fortran"; +static const char __pyx_k_imatmul[] = "__imatmul__"; +static const char __pyx_k_indices[] = "indices"; +static const char __pyx_k_memview[] = "memview"; +static const char __pyx_k_mse_reg[] = "mse_reg"; +static const char __pyx_k_n_nodes[] = "n_nodes"; +static const char __pyx_k_predict[] = "predict"; +static const char __pyx_k_product[] = "product"; +static const char __pyx_k_rmatmul[] = "__rmatmul__"; +static const char __pyx_k_Ellipsis[] = "Ellipsis"; +static const char __pyx_k_KeyError[] = "KeyError"; +static const char __pyx_k_getstate[] = "__getstate__"; +static const char __pyx_k_gini_clf[] = "gini_clf"; +static const char __pyx_k_impurity[] = "impurity"; +static const char __pyx_k_issparse[] = "issparse"; +static const char __pyx_k_itemsize[] = "itemsize"; +static const char __pyx_k_pyx_type[] = "__pyx_type"; +static const char __pyx_k_setstate[] = "__setstate__"; +static const char __pyx_k_splitter[] = "splitter"; +static const char __pyx_k_warnings[] = "warnings"; +static const char __pyx_k_Criterion[] = "Criterion"; +static const char __pyx_k_TREE_LEAF[] = "TREE_LEAF"; +static const char __pyx_k_TypeError[] = "TypeError"; +static const char __pyx_k_ccp_alpha[] = "ccp_alpha"; +static const char __pyx_k_criterion[] = "criterion"; +static const char __pyx_k_enumerate[] = "enumerate"; +static const char __pyx_k_itertools[] = "itertools"; +static const char __pyx_k_max_depth[] = "max_depth"; +static const char __pyx_k_n_samples[] = "n_samples"; +static const char __pyx_k_normalize[] = "normalize"; +static const char __pyx_k_orig_tree[] = "orig_tree"; +static const char __pyx_k_pyx_state[] = "__pyx_state"; +static const char __pyx_k_reduce_ex[] = "__reduce_ex__"; +static const char __pyx_k_threshold[] = "threshold"; +static const char __pyx_k_IndexError[] = "IndexError"; +static const char __pyx_k_NODE_DTYPE[] = "NODE_DTYPE"; +static const char __pyx_k_PathFinder[] = "_PathFinder"; +static const char __pyx_k_ValueError[] = "ValueError"; +static const char __pyx_k_ccp_alphas[] = "ccp_alphas"; +static const char __pyx_k_contiguous[] = "contiguous"; +static const char __pyx_k_csc_matrix[] = "csc_matrix"; +static const char __pyx_k_csr_matrix[] = "csr_matrix"; +static const char __pyx_k_impurities[] = "impurities"; +static const char __pyx_k_left_child[] = "left_child"; +static const char __pyx_k_n_features[] = "n_features"; +static const char __pyx_k_node_count[] = "node_count"; +static const char __pyx_k_pyx_result[] = "__pyx_result"; +static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; +static const char __pyx_k_AlphaPruner[] = "_AlphaPruner"; +static const char __pyx_k_ImportError[] = "ImportError"; +static const char __pyx_k_MemoryError[] = "MemoryError"; +static const char __pyx_k_PickleError[] = "PickleError"; +static const char __pyx_k_TreeBuilder[] = "TreeBuilder"; +static const char __pyx_k_criterion_2[] = "_criterion"; +static const char __pyx_k_decode_tree[] = "decode_tree"; +static const char __pyx_k_logical_and[] = "logical_and"; +static const char __pyx_k_path_finder[] = "path_finder"; +static const char __pyx_k_right_child[] = "right_child"; +static const char __pyx_k_total_items[] = "total_items"; +static const char __pyx_k_K_cand_train[] = "K_cand_train"; +static const char __pyx_k_argpartition[] = "argpartition"; +static const char __pyx_k_c_contiguous[] = "c_contiguous"; +static const char __pyx_k_pruning_tree[] = "pruning tree"; +static const char __pyx_k_pyx_checksum[] = "__pyx_checksum"; +static const char __pyx_k_return_top_k[] = "return_top_k"; +static const char __pyx_k_scipy_sparse[] = "scipy.sparse"; +static const char __pyx_k_sort_indices[] = "sort_indices"; +static const char __pyx_k_stringsource[] = "stringsource"; +static const char __pyx_k_KernelizedMSE[] = "KernelizedMSE"; +static const char __pyx_k_children_left[] = "children_left"; +static const char __pyx_k_decision_path[] = "decision_path"; +static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; +static const char __pyx_k_reduce_cython[] = "__reduce_cython__"; +static const char __pyx_k_sample_weight[] = "sample_weight"; +static const char __pyx_k_sq_norms_cand[] = "sq_norms_cand"; +static const char __pyx_k_TREE_UNDEFINED[] = "TREE_UNDEFINED"; +static const char __pyx_k_asfortranarray[] = "asfortranarray"; +static const char __pyx_k_children_right[] = "children_right"; +static const char __pyx_k_max_leaf_nodes[] = "max_leaf_nodes"; +static const char __pyx_k_n_node_samples[] = "n_node_samples"; +static const char __pyx_k_return_inverse[] = "return_inverse"; +static const char __pyx_k_View_MemoryView[] = "View.MemoryView"; +static const char __pyx_k_allocate_buffer[] = "allocate_buffer"; +static const char __pyx_k_dtype_is_object[] = "dtype_is_object"; +static const char __pyx_k_min_weight_leaf[] = "min_weight_leaf"; +static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError"; +static const char __pyx_k_setstate_cython[] = "__setstate_cython__"; +static const char __pyx_k_ccp_pruning_path[] = "ccp_pruning_path"; +static const char __pyx_k_min_samples_leaf[] = "min_samples_leaf"; +static const char __pyx_k_ascontiguousarray[] = "ascontiguousarray"; +static const char __pyx_k_leaves_in_subtree[] = "leaves_in_subtree"; +static const char __pyx_k_min_samples_split[] = "min_samples_split"; +static const char __pyx_k_pyx_unpickle_Enum[] = "__pyx_unpickle_Enum"; +static const char __pyx_k_CCPPruneController[] = "_CCPPruneController"; +static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; +static const char __pyx_k_min_impurity_split[] = "min_impurity_split"; +static const char __pyx_k_pruning_controller[] = "pruning_controller"; +static const char __pyx_k_resizing_tree_to_d[] = "resizing tree to %d"; +static const char __pyx_k_strided_and_direct[] = ""; +static const char __pyx_k_NotImplementedError[] = "NotImplementedError"; +static const char __pyx_k_BestFirstTreeBuilder[] = "BestFirstTreeBuilder"; +static const char __pyx_k_strided_and_indirect[] = ""; +static const char __pyx_k_DepthFirstTreeBuilder[] = "DepthFirstTreeBuilder"; +static const char __pyx_k_build_pruned_tree_ccp[] = "_build_pruned_tree_ccp"; +static const char __pyx_k_contiguous_and_direct[] = ""; +static const char __pyx_k_min_impurity_decrease[] = "min_impurity_decrease"; +static const char __pyx_k_Can_t_initialize_array[] = "Can't initialize array."; +static const char __pyx_k_MemoryView_of_r_object[] = ""; +static const char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; +static const char __pyx_k_contiguous_and_indirect[] = ""; +static const char __pyx_k_weighted_n_node_samples[] = "weighted_n_node_samples"; +static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; +static const char __pyx_k_pyx_unpickle_TreeBuilder[] = "__pyx_unpickle_TreeBuilder"; +static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; +static const char __pyx_k_compute_feature_importances[] = "compute_feature_importances"; +static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; +static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; +static const char __pyx_k_pyx_unpickle__CCPPruneControll[] = "__pyx_unpickle__CCPPruneController"; +static const char __pyx_k_strided_and_direct_or_indirect[] = ""; +static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; +static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; +static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; +static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview"; +static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview"; +static const char __pyx_k_Did_not_recognise_loaded_array_l[] = "Did not recognise loaded array layout"; +static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; +static const char __pyx_k_Incompatible_checksums_s_vs_0x57[] = "Incompatible checksums (%s vs 0x5739659 = (max_depth, min_impurity_decrease, min_impurity_split, min_samples_leaf, min_samples_split, min_weight_leaf, splitter))"; +static const char __pyx_k_Incompatible_checksums_s_vs_0xb0[] = "Incompatible checksums (%s vs 0xb068931 = (name))"; +static const char __pyx_k_Incompatible_checksums_s_vs_0xd4[] = "Incompatible checksums (%s vs 0xd41d8cd = ())"; +static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; +static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; +static const char __pyx_k_No_support_for_np_int64_index_ba[] = "No support for np.int64 index based sparse matrices"; +static const char __pyx_k_No_value_specified_for_struct_at[] = "No value specified for struct attribute 'left_child'"; +static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; +static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; +static const char __pyx_k_X_dtype_should_be_np_float32_got[] = "X.dtype should be np.float32, got %s"; +static const char __pyx_k_X_should_be_in_csr_matrix_format[] = "X should be in csr_matrix format, got %s"; +static const char __pyx_k_X_should_be_in_np_ndarray_format[] = "X should be in np.ndarray format, got %s"; +static const char __pyx_k_You_have_loaded_Tree_version_whi[] = "You have loaded Tree version which cannot be imported"; +static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; +static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; +static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; +static const char __pyx_k_only_the_KernelizedMSE_criterion[] = "only the \"KernelizedMSE\" criterion is supported"; +static const char __pyx_k_stpredictions_models_OK3__tree_p[] = "stpredictions/models/OK3/_tree.pyx"; +static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; +static const char __pyx_k_No_value_specified_for_struct_at_2[] = "No value specified for struct attribute 'right_child'"; +static const char __pyx_k_No_value_specified_for_struct_at_3[] = "No value specified for struct attribute 'feature'"; +static const char __pyx_k_No_value_specified_for_struct_at_4[] = "No value specified for struct attribute 'threshold'"; +static const char __pyx_k_No_value_specified_for_struct_at_5[] = "No value specified for struct attribute 'impurity'"; +static const char __pyx_k_No_value_specified_for_struct_at_6[] = "No value specified for struct attribute 'n_node_samples'"; +static const char __pyx_k_No_value_specified_for_struct_at_7[] = "No value specified for struct attribute 'weighted_n_node_samples'"; +static PyObject *__pyx_n_s_ASCII; +static PyObject *__pyx_n_s_AlphaPruner; +static PyObject *__pyx_n_s_BestFirstTreeBuilder; +static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; +static PyObject *__pyx_n_s_C; +static PyObject *__pyx_n_s_CCPPruneController; +static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; +static PyObject *__pyx_kp_s_Can_t_initialize_array; +static PyObject *__pyx_kp_s_Cannot_assign_to_read_only_memor; +static PyObject *__pyx_kp_s_Cannot_create_writable_memory_vi; +static PyObject *__pyx_kp_s_Cannot_index_with_type_s; +static PyObject *__pyx_n_s_Criterion; +static PyObject *__pyx_n_s_DOUBLE; +static PyObject *__pyx_n_s_DTYPE; +static PyObject *__pyx_n_s_DepthFirstTreeBuilder; +static PyObject *__pyx_kp_s_Did_not_recognise_loaded_array_l; +static PyObject *__pyx_n_s_Ellipsis; +static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; +static PyObject *__pyx_n_s_ImportError; +static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0x57; +static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xb0; +static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xd4; +static PyObject *__pyx_n_s_IndexError; +static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; +static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; +static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; +static PyObject *__pyx_n_s_K_cand_train; +static PyObject *__pyx_n_s_K_y; +static PyObject *__pyx_n_s_KernelizedMSE; +static PyObject *__pyx_n_s_KeyError; +static PyObject *__pyx_n_s_MemoryError; +static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; +static PyObject *__pyx_kp_s_MemoryView_of_r_object; +static PyObject *__pyx_n_s_NODE_DTYPE; +static PyObject *__pyx_kp_s_No_support_for_np_int64_index_ba; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_2; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_3; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_4; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_5; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_6; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_7; +static PyObject *__pyx_n_s_NotImplementedError; +static PyObject *__pyx_n_b_O; +static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; +static PyObject *__pyx_n_s_PathFinder; +static PyObject *__pyx_n_s_PickleError; +static PyObject *__pyx_kp_b_T; +static PyObject *__pyx_n_s_TREE_LEAF; +static PyObject *__pyx_n_s_TREE_UNDEFINED; +static PyObject *__pyx_n_s_Tree; +static PyObject *__pyx_n_s_TreeBuilder; +static PyObject *__pyx_n_s_TypeError; +static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; +static PyObject *__pyx_n_s_ValueError; +static PyObject *__pyx_n_s_View_MemoryView; +static PyObject *__pyx_n_s_X; +static PyObject *__pyx_kp_s_X_dtype_should_be_np_float32_got; +static PyObject *__pyx_kp_s_X_should_be_in_csr_matrix_format; +static PyObject *__pyx_kp_s_X_should_be_in_np_ndarray_format; +static PyObject *__pyx_kp_s_You_have_loaded_Tree_version_whi; +static PyObject *__pyx_kp_b__43; +static PyObject *__pyx_kp_b__44; +static PyObject *__pyx_kp_b__45; +static PyObject *__pyx_kp_b__46; +static PyObject *__pyx_kp_u__47; +static PyObject *__pyx_n_s_allocate_buffer; +static PyObject *__pyx_n_s_append; +static PyObject *__pyx_n_s_apply; +static PyObject *__pyx_n_s_argmax; +static PyObject *__pyx_n_s_argpartition; +static PyObject *__pyx_n_s_array; +static PyObject *__pyx_n_s_asarray; +static PyObject *__pyx_n_s_ascontiguousarray; +static PyObject *__pyx_n_s_asfortranarray; +static PyObject *__pyx_n_s_base; +static PyObject *__pyx_n_s_build; +static PyObject *__pyx_n_s_build_pruned_tree_ccp; +static PyObject *__pyx_n_s_c; +static PyObject *__pyx_n_u_c; +static PyObject *__pyx_n_s_c_contiguous; +static PyObject *__pyx_n_s_ccp_alpha; +static PyObject *__pyx_n_s_ccp_alphas; +static PyObject *__pyx_n_s_ccp_pruning_path; +static PyObject *__pyx_n_s_children_left; +static PyObject *__pyx_n_s_children_right; +static PyObject *__pyx_n_s_class; +static PyObject *__pyx_n_s_cline_in_traceback; +static PyObject *__pyx_n_s_compute_feature_importances; +static PyObject *__pyx_n_s_contiguous; +static PyObject *__pyx_kp_s_contiguous_and_direct; +static PyObject *__pyx_kp_s_contiguous_and_indirect; +static PyObject *__pyx_n_s_count; +static PyObject *__pyx_n_s_criterion; +static PyObject *__pyx_n_s_criterion_2; +static PyObject *__pyx_n_s_csc_matrix; +static PyObject *__pyx_n_s_csr_matrix; +static PyObject *__pyx_n_s_data; +static PyObject *__pyx_n_s_decision_path; +static PyObject *__pyx_n_s_decode_tree; +static PyObject *__pyx_n_s_dict; +static PyObject *__pyx_n_s_double; +static PyObject *__pyx_n_s_dtype; +static PyObject *__pyx_n_s_dtype_is_object; +static PyObject *__pyx_n_s_empty; +static PyObject *__pyx_n_s_encode; +static PyObject *__pyx_n_s_enumerate; +static PyObject *__pyx_n_s_eps; +static PyObject *__pyx_n_s_error; +static PyObject *__pyx_n_s_feature; +static PyObject *__pyx_n_s_finfo; +static PyObject *__pyx_n_s_flags; +static PyObject *__pyx_n_s_float32; +static PyObject *__pyx_n_s_float64; +static PyObject *__pyx_n_s_format; +static PyObject *__pyx_n_s_fortran; +static PyObject *__pyx_n_u_fortran; +static PyObject *__pyx_n_s_getstate; +static PyObject *__pyx_n_s_gini_clf; +static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; +static PyObject *__pyx_n_s_id; +static PyObject *__pyx_n_s_imatmul; +static PyObject *__pyx_n_s_import; +static PyObject *__pyx_n_s_impurities; +static PyObject *__pyx_n_s_impurity; +static PyObject *__pyx_n_s_indices; +static PyObject *__pyx_n_s_indptr; +static PyObject *__pyx_n_s_inf; +static PyObject *__pyx_n_s_int32; +static PyObject *__pyx_n_s_intp; +static PyObject *__pyx_n_s_issparse; +static PyObject *__pyx_n_s_itemsize; +static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; +static PyObject *__pyx_n_s_itertools; +static PyObject *__pyx_n_s_join; +static PyObject *__pyx_n_s_kernel; +static PyObject *__pyx_n_s_leaves_in_subtree; +static PyObject *__pyx_n_s_left_child; +static PyObject *__pyx_n_s_logical_and; +static PyObject *__pyx_n_s_main; +static PyObject *__pyx_n_s_matmul; +static PyObject *__pyx_n_s_max; +static PyObject *__pyx_n_s_max_depth; +static PyObject *__pyx_n_s_max_leaf_nodes; +static PyObject *__pyx_n_s_mean; +static PyObject *__pyx_n_s_memview; +static PyObject *__pyx_n_s_min_impurity_decrease; +static PyObject *__pyx_n_s_min_impurity_split; +static PyObject *__pyx_n_s_min_samples_leaf; +static PyObject *__pyx_n_s_min_samples_split; +static PyObject *__pyx_n_s_min_weight_leaf; +static PyObject *__pyx_n_s_mode; +static PyObject *__pyx_n_s_mse_reg; +static PyObject *__pyx_n_s_n_features; +static PyObject *__pyx_n_s_n_node_samples; +static PyObject *__pyx_n_s_n_nodes; +static PyObject *__pyx_n_s_n_samples; +static PyObject *__pyx_n_s_name; +static PyObject *__pyx_n_s_name_2; +static PyObject *__pyx_n_s_ndim; +static PyObject *__pyx_n_s_new; +static PyObject *__pyx_kp_s_no_default___reduce___due_to_non; +static PyObject *__pyx_n_s_node_count; +static PyObject *__pyx_n_s_nodes; +static PyObject *__pyx_n_s_normalize; +static PyObject *__pyx_n_s_np; +static PyObject *__pyx_n_s_numpy; +static PyObject *__pyx_kp_s_numpy_core_multiarray_failed_to; +static PyObject *__pyx_kp_s_numpy_core_umath_failed_to_impor; +static PyObject *__pyx_n_s_obj; +static PyObject *__pyx_n_s_ones; +static PyObject *__pyx_kp_s_only_the_KernelizedMSE_criterion; +static PyObject *__pyx_n_s_order; +static PyObject *__pyx_n_s_orig_tree; +static PyObject *__pyx_n_s_pack; +static PyObject *__pyx_n_s_path_finder; +static PyObject *__pyx_n_s_pickle; +static PyObject *__pyx_n_s_predict; +static PyObject *__pyx_n_s_product; +static PyObject *__pyx_n_s_pruning_controller; +static PyObject *__pyx_kp_s_pruning_tree; +static PyObject *__pyx_n_s_pyx_PickleError; +static PyObject *__pyx_n_s_pyx_checksum; +static PyObject *__pyx_n_s_pyx_getbuffer; +static PyObject *__pyx_n_s_pyx_result; +static PyObject *__pyx_n_s_pyx_state; +static PyObject *__pyx_n_s_pyx_type; +static PyObject *__pyx_n_s_pyx_unpickle_Enum; +static PyObject *__pyx_n_s_pyx_unpickle_TreeBuilder; +static PyObject *__pyx_n_s_pyx_unpickle__CCPPruneControll; +static PyObject *__pyx_n_s_pyx_vtable; +static PyObject *__pyx_n_s_range; +static PyObject *__pyx_n_s_reduce; +static PyObject *__pyx_n_s_reduce_cython; +static PyObject *__pyx_n_s_reduce_ex; +static PyObject *__pyx_kp_s_resizing_tree_to_d; +static PyObject *__pyx_n_s_return_inverse; +static PyObject *__pyx_n_s_return_top_k; +static PyObject *__pyx_n_s_right_child; +static PyObject *__pyx_n_s_rmatmul; +static PyObject *__pyx_kp_u_s; +static PyObject *__pyx_n_s_sample_weight; +static PyObject *__pyx_n_s_scipy_sparse; +static PyObject *__pyx_n_s_setstate; +static PyObject *__pyx_n_s_setstate_cython; +static PyObject *__pyx_n_s_shape; +static PyObject *__pyx_n_s_size; +static PyObject *__pyx_n_s_sort_indices; +static PyObject *__pyx_n_s_splitter; +static PyObject *__pyx_n_s_sq_norms_cand; +static PyObject *__pyx_n_s_start; +static PyObject *__pyx_n_s_step; +static PyObject *__pyx_n_s_stop; +static PyObject *__pyx_kp_s_stpredictions_models_OK3__tree_p; +static PyObject *__pyx_kp_s_strided_and_direct; +static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; +static PyObject *__pyx_kp_s_strided_and_indirect; +static PyObject *__pyx_kp_s_stringsource; +static PyObject *__pyx_n_s_struct; +static PyObject *__pyx_n_s_sum; +static PyObject *__pyx_n_s_test; +static PyObject *__pyx_n_s_threshold; +static PyObject *__pyx_n_s_tocsc; +static PyObject *__pyx_n_s_tocsr; +static PyObject *__pyx_n_s_total_items; +static PyObject *__pyx_n_s_tree; +static PyObject *__pyx_n_s_tree_2; +static PyObject *__pyx_n_s_uint8; +static PyObject *__pyx_kp_s_unable_to_allocate_array_data; +static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; +static PyObject *__pyx_n_s_unique; +static PyObject *__pyx_n_s_unpack; +static PyObject *__pyx_n_s_update; +static PyObject *__pyx_n_s_values; +static PyObject *__pyx_n_s_warnings; +static PyObject *__pyx_n_s_weighted_n_node_samples; +static PyObject *__pyx_n_s_where; +static PyObject *__pyx_n_s_y; +static PyObject *__pyx_n_s_zeros; +static PyObject *__pyx_pf_5_tree_11TreeBuilder_build(struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ +static PyObject *__pyx_pf_5_tree_11TreeBuilder_2__reduce_cython__(struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_11TreeBuilder_4__setstate_cython__(struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, __pyx_t_5_tree_SIZE_t __pyx_v_max_depth, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split); /* proto */ +static PyObject *__pyx_pf_5_tree_21DepthFirstTreeBuilder_2build(struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ +static PyObject *__pyx_pf_5_tree_21DepthFirstTreeBuilder_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_21DepthFirstTreeBuilder_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_leaf, PyObject *__pyx_v_min_weight_leaf, __pyx_t_5_tree_SIZE_t __pyx_v_max_depth, __pyx_t_5_tree_SIZE_t __pyx_v_max_leaf_nodes, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split); /* proto */ +static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ +static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_13children_left___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_14children_right___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_8n_leaves___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_7feature___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_9threshold___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_8impurity___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_14n_node_samples___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_23weighted_n_node_samples___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_5value___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_5_tree_4Tree___cinit__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, int __pyx_v_n_features, int __pyx_v_n_samples); /* proto */ +static void __pyx_pf_5_tree_4Tree_2__dealloc__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_4__reduce__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_6__getstate__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_d); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_10predict(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_12decode_tree(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_K_cand_train, PyArrayObject *__pyx_v_sq_norms_cand, PyObject *__pyx_v_criterion, PyObject *__pyx_v_kernel, __pyx_t_5_tree_SIZE_t __pyx_v_return_top_k); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_14apply(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_16decision_path(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_18compute_feature_importances(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_normalize); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_10n_features___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_5_tree_4Tree_10n_features_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_9max_depth___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_5_tree_4Tree_9max_depth_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_10node_count___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_5_tree_4Tree_10node_count_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_8capacity___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_5_tree_4Tree_8capacity_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_3K_y___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_5_tree_4Tree_3K_y_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static int __pyx_pf_5_tree_4Tree_3K_y_4__del__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_4Tree_1y___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_5_tree_4Tree_1y_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static int __pyx_pf_5_tree_4Tree_1y_4__del__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_19_CCPPruneController___reduce_cython__(struct __pyx_obj_5_tree__CCPPruneController *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_19_CCPPruneController_2__setstate_cython__(struct __pyx_obj_5_tree__CCPPruneController *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_5_tree_12_AlphaPruner___cinit__(struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_self, __pyx_t_5_tree_DOUBLE_t __pyx_v_ccp_alpha); /* proto */ +static PyObject *__pyx_pf_5_tree_12_AlphaPruner_2__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_12_AlphaPruner_4__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_5_tree_11_PathFinder___cinit__(struct __pyx_obj_5_tree__PathFinder *__pyx_v_self, int __pyx_v_node_count); /* proto */ +static PyObject *__pyx_pf_5_tree_11_PathFinder_2__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree__PathFinder *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_5_tree_11_PathFinder_4__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree__PathFinder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_5_tree__build_pruned_tree_ccp(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, struct __pyx_obj_5_tree_Tree *__pyx_v_orig_tree, __pyx_t_5_tree_DOUBLE_t __pyx_v_ccp_alpha); /* proto */ +static PyObject *__pyx_pf_5_tree_2ccp_pruning_path(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_5_tree_Tree *__pyx_v_orig_tree); /* proto */ +static PyObject *__pyx_pf_5_tree_4__pyx_unpickle_TreeBuilder(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_5_tree_6__pyx_unpickle__CCPPruneController(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_12__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf___pyx_array___reduce_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_array_2__setstate_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ +static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_MemviewEnum___reduce_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_MemviewEnum_2__setstate_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ +static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); 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if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 203, __pyx_L8_error) + + /* "_tree.pyx":205 + * splitter.node_reset(start, end, &weighted_n_node_samples) + * + * is_leaf = (depth >= max_depth or # <<<<<<<<<<<<<< + * n_node_samples < min_samples_split or + * n_node_samples < 2 * min_samples_leaf or + */ + __pyx_t_8 = ((__pyx_v_depth >= __pyx_v_max_depth) != 0); + if (!__pyx_t_8) { + } else { + __pyx_t_9 = __pyx_t_8; + goto __pyx_L16_bool_binop_done; + } + + /* "_tree.pyx":206 + * + * is_leaf = (depth >= max_depth or + * n_node_samples < min_samples_split or # <<<<<<<<<<<<<< + * n_node_samples < 2 * min_samples_leaf or + * weighted_n_node_samples < 2 * min_weight_leaf) + */ + __pyx_t_8 = ((__pyx_v_n_node_samples < __pyx_v_min_samples_split) != 0); + if (!__pyx_t_8) { + } else { + __pyx_t_9 = __pyx_t_8; + goto __pyx_L16_bool_binop_done; + } + + /* "_tree.pyx":207 + * is_leaf = (depth >= max_depth or + * n_node_samples < min_samples_split or + * n_node_samples < 2 * min_samples_leaf or # <<<<<<<<<<<<<< + * weighted_n_node_samples < 2 * min_weight_leaf) + * + */ + __pyx_t_8 = ((__pyx_v_n_node_samples < (2 * __pyx_v_min_samples_leaf)) != 0); 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+ + /* "_tree.pyx":332 + * cdef SIZE_t max_split_nodes = max_leaf_nodes - 1 + * cdef bint is_leaf + * cdef SIZE_t max_depth_seen = -1 # <<<<<<<<<<<<<< + * cdef int rc = 0 + * cdef Node* node + */ + __pyx_v_max_depth_seen = -1; + + /* "_tree.pyx":333 + * cdef bint is_leaf + * cdef SIZE_t max_depth_seen = -1 + * cdef int rc = 0 # <<<<<<<<<<<<<< + * cdef Node* node + * + */ + __pyx_v_rc = 0; + + /* "_tree.pyx":337 + * + * # Initial capacity + * cdef SIZE_t init_capacity = max_split_nodes + max_leaf_nodes # <<<<<<<<<<<<<< + * tree._resize(init_capacity) + * + */ + __pyx_v_init_capacity = (__pyx_v_max_split_nodes + __pyx_v_max_leaf_nodes); + + /* "_tree.pyx":338 + * # Initial capacity + * cdef SIZE_t init_capacity = max_split_nodes + max_leaf_nodes + * tree._resize(init_capacity) # <<<<<<<<<<<<<< + * + * with nogil: + */ + __pyx_t_5 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize(__pyx_v_tree, __pyx_v_init_capacity); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 338, __pyx_L1_error) + + /* "_tree.pyx":340 + * tree._resize(init_capacity) + * + * with nogil: # <<<<<<<<<<<<<< + * # add root to frontier + * rc = self._add_split_node(splitter, tree, 0, n_node_samples, + */ + { + #ifdef WITH_THREAD + PyThreadState *_save; + Py_UNBLOCK_THREADS + __Pyx_FastGIL_Remember(); + #endif + /*try:*/ { + + /* "_tree.pyx":342 + * with nogil: + * # add root to frontier + * rc = self._add_split_node(splitter, tree, 0, n_node_samples, # <<<<<<<<<<<<<< + * INFINITY, IS_FIRST, IS_LEFT, NULL, 0, + * &split_node_left, + */ + __pyx_t_5 = __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, 0, __pyx_v_n_node_samples, __pyx_v_5_tree_INFINITY, __pyx_v_5_tree_IS_FIRST, __pyx_v_5_tree_IS_LEFT, NULL, 0, (&__pyx_v_split_node_left), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 342, __pyx_L7_error) + __pyx_v_rc = __pyx_t_5; + + /* "_tree.pyx":346 + * &split_node_left, + * y.shape[0]) + * if rc >= 0: # <<<<<<<<<<<<<< + * rc = _add_to_frontier(&split_node_left, frontier) + * + */ + __pyx_t_9 = ((__pyx_v_rc >= 0) != 0); + if (__pyx_t_9) { + + /* "_tree.pyx":347 + * y.shape[0]) + * if rc >= 0: + * rc = _add_to_frontier(&split_node_left, frontier) # <<<<<<<<<<<<<< + * + * if rc == -1: + */ + __pyx_t_5 = __pyx_f_5_tree__add_to_frontier((&__pyx_v_split_node_left), __pyx_v_frontier); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 347, __pyx_L7_error) + __pyx_v_rc = __pyx_t_5; + + /* "_tree.pyx":346 + * &split_node_left, + * y.shape[0]) + * if rc >= 0: # <<<<<<<<<<<<<< + * rc = _add_to_frontier(&split_node_left, frontier) + * + */ + } + + /* "_tree.pyx":349 + * rc = _add_to_frontier(&split_node_left, frontier) + * + * if rc == -1: # <<<<<<<<<<<<<< + * with gil: + * raise MemoryError() + */ + __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); + if (__pyx_t_9) { + + /* "_tree.pyx":350 + * + * if rc == -1: + * with gil: # <<<<<<<<<<<<<< + * raise MemoryError() + * + */ + { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); + #endif + /*try:*/ { + + /* "_tree.pyx":351 + * if rc == -1: + * with gil: + * raise MemoryError() # <<<<<<<<<<<<<< + * + * while not frontier.is_empty(): + */ + PyErr_NoMemory(); __PYX_ERR(0, 351, __pyx_L12_error) + } + + /* "_tree.pyx":350 + * + * if rc == -1: + * with gil: # <<<<<<<<<<<<<< + * raise MemoryError() + * + */ + /*finally:*/ { + __pyx_L12_error: { + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + goto __pyx_L7_error; + } + } + } + + /* "_tree.pyx":349 + * rc = _add_to_frontier(&split_node_left, frontier) + * + * if rc == -1: # <<<<<<<<<<<<<< + * with gil: + * raise MemoryError() + */ + } + + /* "_tree.pyx":353 + * raise MemoryError() + * + * while not frontier.is_empty(): # <<<<<<<<<<<<<< + * frontier.pop(&record) + * + */ + while (1) { + __pyx_t_9 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->is_empty(__pyx_v_frontier) != 0)) != 0); + if (!__pyx_t_9) break; + + /* "_tree.pyx":354 + * + * while not frontier.is_empty(): + * frontier.pop(&record) # <<<<<<<<<<<<<< + * + * node = &tree.nodes[record.node_id] + */ + (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->pop(__pyx_v_frontier, (&__pyx_v_record))); + + /* "_tree.pyx":356 + * frontier.pop(&record) + * + * node = &tree.nodes[record.node_id] # <<<<<<<<<<<<<< + * is_leaf = (record.is_leaf or max_split_nodes <= 0) + * + */ + __pyx_v_node = (&(__pyx_v_tree->nodes[__pyx_v_record.node_id])); + + /* "_tree.pyx":357 + * + * node = &tree.nodes[record.node_id] + * is_leaf = (record.is_leaf or max_split_nodes <= 0) # <<<<<<<<<<<<<< + * + * if is_leaf: + */ + __pyx_t_8 = (__pyx_v_record.is_leaf != 0); + if (!__pyx_t_8) { + } else { + __pyx_t_9 = __pyx_t_8; + goto __pyx_L16_bool_binop_done; + } + __pyx_t_8 = ((__pyx_v_max_split_nodes <= 0) != 0); + __pyx_t_9 = __pyx_t_8; + __pyx_L16_bool_binop_done:; + __pyx_v_is_leaf = __pyx_t_9; + + /* "_tree.pyx":359 + * is_leaf = (record.is_leaf or max_split_nodes <= 0) + * + * if is_leaf: # <<<<<<<<<<<<<< + * # Node is not expandable; set node as leaf + * node.left_child = _TREE_LEAF + */ + __pyx_t_9 = (__pyx_v_is_leaf != 0); + if (__pyx_t_9) { + + /* "_tree.pyx":361 + * if is_leaf: + * # Node is not expandable; set node as leaf + * node.left_child = _TREE_LEAF # <<<<<<<<<<<<<< + * node.right_child = _TREE_LEAF + * node.feature = _TREE_UNDEFINED + */ + __pyx_v_node->left_child = __pyx_v_5_tree__TREE_LEAF; + + /* "_tree.pyx":362 + * # Node is not expandable; 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+ + /* "_tree.pyx":696 + * + * if capacity == SIZE_MAX: + * if self.capacity == 0: # <<<<<<<<<<<<<< + * capacity = 3 # default initial value + * else: + */ + goto __pyx_L7; + } + + /* "_tree.pyx":699 + * capacity = 3 # default initial value + * else: + * capacity = 2 * self.capacity # <<<<<<<<<<<<<< + * + * safe_realloc(&self.nodes, capacity) + */ + /*else*/ { + __pyx_v_capacity = (2 * __pyx_v_self->capacity); + } + __pyx_L7:; + + /* "_tree.pyx":695 + * return 0 + * + * if capacity == SIZE_MAX: # <<<<<<<<<<<<<< + * if self.capacity == 0: + * capacity = 3 # default initial value + */ + } + + /* "_tree.pyx":701 + * capacity = 2 * self.capacity + * + * safe_realloc(&self.nodes, capacity) # <<<<<<<<<<<<<< + * safe_realloc(&self.value, capacity * self.K_y.shape[0]) + * + */ + __pyx_fuse_6__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->nodes), __pyx_v_capacity); if (unlikely(__Pyx_ErrOccurredWithGIL())) __PYX_ERR(0, 701, __pyx_L1_error) + + /* "_tree.pyx":702 + * + * safe_realloc(&self.nodes, capacity) + * safe_realloc(&self.value, capacity * self.K_y.shape[0]) # <<<<<<<<<<<<<< + * + * # value memory is initialised to 0 to enable classifier argmax + */ + __pyx_fuse_4__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->value), (__pyx_v_capacity * (__pyx_v_self->K_y->dimensions[0]))); if (unlikely(__Pyx_ErrOccurredWithGIL())) __PYX_ERR(0, 702, __pyx_L1_error) + + /* "_tree.pyx":705 + * + * # value memory is initialised to 0 to enable classifier argmax + * if capacity > self.capacity: # <<<<<<<<<<<<<< + * memset((self.value + self.capacity * self.K_y.shape[0]), 0, + * (capacity - self.capacity) * self.K_y.shape[0] * + */ + __pyx_t_1 = ((__pyx_v_capacity > __pyx_v_self->capacity) != 0); + if (__pyx_t_1) { + + /* "_tree.pyx":706 + * # value memory is initialised to 0 to enable classifier argmax + * if capacity > self.capacity: + * memset((self.value + self.capacity * self.K_y.shape[0]), 0, # <<<<<<<<<<<<<< + * (capacity - self.capacity) * self.K_y.shape[0] * + * sizeof(double)) + */ + (void)(memset(((void *)(__pyx_v_self->value + (__pyx_v_self->capacity * (__pyx_v_self->K_y->dimensions[0])))), 0, (((__pyx_v_capacity - __pyx_v_self->capacity) * (__pyx_v_self->K_y->dimensions[0])) * (sizeof(double))))); + + /* "_tree.pyx":705 + * + * # value memory is initialised to 0 to enable classifier argmax + * if capacity > self.capacity: # <<<<<<<<<<<<<< + * memset((self.value + self.capacity * self.K_y.shape[0]), 0, + * (capacity - self.capacity) * self.K_y.shape[0] * + */ + } + + /* "_tree.pyx":711 + * + * # if capacity smaller than node_count, adjust the counter + * if capacity < self.node_count: # <<<<<<<<<<<<<< + * self.node_count = capacity + * + */ + __pyx_t_1 = ((__pyx_v_capacity < __pyx_v_self->node_count) != 0); 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if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1464, __pyx_L25_error) + __Pyx_GOTREF(__pyx_t_6); + __Pyx_Raise(__pyx_t_6, 0, 0, 0); + __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; + __PYX_ERR(0, 1464, __pyx_L25_error) + } + + /* "_tree.pyx":1463 + * rc = stack.push(child_r[node_idx], 0, 0, node_idx, 0, 0, 0) + * if rc == -1: + * with gil: # <<<<<<<<<<<<<< + * raise MemoryError("pruning tree") + * + */ + /*finally:*/ { + __pyx_L25_error: { + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + goto __pyx_L4_error; + } + } + } + + /* "_tree.pyx":1462 + * + * rc = stack.push(child_r[node_idx], 0, 0, node_idx, 0, 0, 0) + * if rc == -1: # <<<<<<<<<<<<<< + * with gil: + * raise MemoryError("pruning tree") + */ + } + } + __pyx_L14:; + } + + /* "_tree.pyx":1468 + * # computes number of leaves in all branches and the overall impurity of + * # the branch. The overall impurity is the sum of r_node in its leaves. + * for leaf_idx in range(leaves_in_subtree.shape[0]): # <<<<<<<<<<<<<< + * if not leaves_in_subtree[leaf_idx]: + * continue + */ + __pyx_t_11 = (__pyx_v_leaves_in_subtree.shape[0]); + __pyx_t_12 = __pyx_t_11; + for (__pyx_t_1 = 0; __pyx_t_1 < __pyx_t_12; __pyx_t_1+=1) { + __pyx_v_leaf_idx = __pyx_t_1; + + /* "_tree.pyx":1469 + * # the branch. The overall impurity is the sum of r_node in its leaves. + * for leaf_idx in range(leaves_in_subtree.shape[0]): + * if not leaves_in_subtree[leaf_idx]: # <<<<<<<<<<<<<< + * continue + * r_branch[leaf_idx] = r_node[leaf_idx] + */ + __pyx_t_13 = __pyx_v_leaf_idx; + __pyx_t_16 = ((!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_13 * __pyx_v_leaves_in_subtree.strides[0]) ))) != 0)) != 0); + if (__pyx_t_16) { + + /* "_tree.pyx":1470 + * for leaf_idx in range(leaves_in_subtree.shape[0]): + * if not leaves_in_subtree[leaf_idx]: + * continue # <<<<<<<<<<<<<< + * r_branch[leaf_idx] = r_node[leaf_idx] + * + */ + goto __pyx_L27_continue; + + /* "_tree.pyx":1469 + * # the branch. The overall impurity is the sum of r_node in its leaves. + * for leaf_idx in range(leaves_in_subtree.shape[0]): + * if not leaves_in_subtree[leaf_idx]: # <<<<<<<<<<<<<< + * continue + * r_branch[leaf_idx] = r_node[leaf_idx] + */ + } + + /* "_tree.pyx":1471 + * if not leaves_in_subtree[leaf_idx]: + * continue + * r_branch[leaf_idx] = r_node[leaf_idx] # <<<<<<<<<<<<<< + * + * # bubble up values to ancestor nodes + */ + __pyx_t_13 = __pyx_v_leaf_idx; + __pyx_t_4 = __pyx_v_leaf_idx; + *((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )) = (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))); + + /* "_tree.pyx":1474 + * + * # bubble up values to ancestor nodes + * current_r = r_node[leaf_idx] # <<<<<<<<<<<<<< + * while leaf_idx != 0: + * parent_idx = parent[leaf_idx] + */ + __pyx_t_13 = __pyx_v_leaf_idx; + __pyx_v_current_r = (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))); + + /* "_tree.pyx":1475 + * # bubble up values to ancestor nodes + * current_r = r_node[leaf_idx] + * while leaf_idx != 0: # <<<<<<<<<<<<<< + * parent_idx = parent[leaf_idx] + * r_branch[parent_idx] += current_r + */ + while (1) { + __pyx_t_16 = ((__pyx_v_leaf_idx != 0) != 0); + if (!__pyx_t_16) break; + + /* "_tree.pyx":1476 + * current_r = r_node[leaf_idx] + * while leaf_idx != 0: + * parent_idx = parent[leaf_idx] # <<<<<<<<<<<<<< + * r_branch[parent_idx] += current_r + * n_leaves[parent_idx] += 1 + */ + __pyx_t_13 = __pyx_v_leaf_idx; + __pyx_v_parent_idx = (*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_13 * __pyx_v_parent.strides[0]) ))); + + /* "_tree.pyx":1477 + * while leaf_idx != 0: + * parent_idx = parent[leaf_idx] + * r_branch[parent_idx] += current_r # <<<<<<<<<<<<<< + * n_leaves[parent_idx] += 1 + * leaf_idx = parent_idx + */ + __pyx_t_13 = __pyx_v_parent_idx; + *((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_13 * __pyx_v_r_branch.strides[0]) )) += __pyx_v_current_r; + + /* "_tree.pyx":1478 + * parent_idx = parent[leaf_idx] + * r_branch[parent_idx] += current_r + * n_leaves[parent_idx] += 1 # <<<<<<<<<<<<<< + * leaf_idx = parent_idx + * + */ + __pyx_t_13 = __pyx_v_parent_idx; + *((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_13 * __pyx_v_n_leaves.strides[0]) )) += 1; + + /* "_tree.pyx":1479 + * r_branch[parent_idx] += current_r + * n_leaves[parent_idx] += 1 + * leaf_idx = parent_idx # <<<<<<<<<<<<<< + * + * for i in range(leaves_in_subtree.shape[0]): + */ + __pyx_v_leaf_idx = __pyx_v_parent_idx; + } + __pyx_L27_continue:; + } + + /* "_tree.pyx":1481 + * leaf_idx = parent_idx + * + * for i in range(leaves_in_subtree.shape[0]): # <<<<<<<<<<<<<< + * candidate_nodes[i] = not leaves_in_subtree[i] + * + */ + __pyx_t_11 = (__pyx_v_leaves_in_subtree.shape[0]); + __pyx_t_12 = __pyx_t_11; + for (__pyx_t_1 = 0; __pyx_t_1 < __pyx_t_12; __pyx_t_1+=1) { + __pyx_v_i = __pyx_t_1; + + /* "_tree.pyx":1482 + * + * for i in range(leaves_in_subtree.shape[0]): + * candidate_nodes[i] = not leaves_in_subtree[i] # <<<<<<<<<<<<<< + * + * # save metrics before pruning + */ + __pyx_t_13 = __pyx_v_i; + __pyx_t_4 = __pyx_v_i; + *((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_4 * __pyx_v_candidate_nodes.strides[0]) )) = (!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_13 * __pyx_v_leaves_in_subtree.strides[0]) ))) != 0)); + } + + /* "_tree.pyx":1485 + * + * # save metrics before pruning + * controller.save_metrics(0.0, r_branch[0]) # <<<<<<<<<<<<<< + * + * # while root node is not a leaf + */ + __pyx_t_13 = 0; + ((struct __pyx_vtabstruct_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->save_metrics(__pyx_v_controller, 0.0, (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_13 * __pyx_v_r_branch.strides[0]) )))); + + /* "_tree.pyx":1488 + * + * # while root node is not a leaf + * while candidate_nodes[0]: # <<<<<<<<<<<<<< + * + * # computes ccp_alpha for subtrees and finds the minimal alpha + */ + while (1) { + __pyx_t_13 = 0; + __pyx_t_16 = ((*((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_13 * __pyx_v_candidate_nodes.strides[0]) ))) != 0); + if (!__pyx_t_16) break; + + /* "_tree.pyx":1491 + * + * # computes ccp_alpha for subtrees and finds the minimal alpha + * effective_alpha = max_float64 # <<<<<<<<<<<<<< + * for i in range(n_nodes): + * if not candidate_nodes[i]: + */ + __pyx_v_effective_alpha = __pyx_v_max_float64; + + /* "_tree.pyx":1492 + * # computes ccp_alpha for subtrees and finds the minimal alpha + * effective_alpha = max_float64 + * for i in range(n_nodes): # <<<<<<<<<<<<<< + * if not candidate_nodes[i]: + * continue + */ + __pyx_t_1 = __pyx_v_n_nodes; + __pyx_t_18 = __pyx_t_1; + for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) { + __pyx_v_i = __pyx_t_19; + + /* "_tree.pyx":1493 + * effective_alpha = max_float64 + * for i in range(n_nodes): + * if not candidate_nodes[i]: # <<<<<<<<<<<<<< + * continue + * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) + */ + __pyx_t_13 = __pyx_v_i; + __pyx_t_16 = ((!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_13 * __pyx_v_candidate_nodes.strides[0]) ))) != 0)) != 0); + if (__pyx_t_16) { + + /* "_tree.pyx":1494 + * for i in range(n_nodes): + * if not candidate_nodes[i]: + * continue # <<<<<<<<<<<<<< + * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) + * if subtree_alpha < effective_alpha: + */ + goto __pyx_L36_continue; + + /* "_tree.pyx":1493 + * effective_alpha = max_float64 + * for i in range(n_nodes): + * if not candidate_nodes[i]: # <<<<<<<<<<<<<< + * continue + * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) + */ + } + + /* "_tree.pyx":1495 + * if not candidate_nodes[i]: + * continue + * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) # <<<<<<<<<<<<<< + * if subtree_alpha < effective_alpha: + * effective_alpha = subtree_alpha + */ + __pyx_t_13 = __pyx_v_i; + __pyx_t_4 = __pyx_v_i; + __pyx_t_14 = __pyx_v_i; + __pyx_v_subtree_alpha = (((*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))) - (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )))) / ((*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) ))) - 1)); + + /* "_tree.pyx":1496 + * continue + * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) + * if subtree_alpha < effective_alpha: # <<<<<<<<<<<<<< + * effective_alpha = subtree_alpha + * pruned_branch_node_idx = i + */ + __pyx_t_16 = ((__pyx_v_subtree_alpha < __pyx_v_effective_alpha) != 0); + if (__pyx_t_16) { + + /* "_tree.pyx":1497 + * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) + * if subtree_alpha < effective_alpha: + * effective_alpha = subtree_alpha # <<<<<<<<<<<<<< + * pruned_branch_node_idx = i + * + */ + __pyx_v_effective_alpha = __pyx_v_subtree_alpha; + + /* "_tree.pyx":1498 + * if subtree_alpha < effective_alpha: + * effective_alpha = subtree_alpha + * pruned_branch_node_idx = i # <<<<<<<<<<<<<< + * + * if controller.stop_pruning(effective_alpha): + */ + __pyx_v_pruned_branch_node_idx = __pyx_v_i; + + /* "_tree.pyx":1496 + * continue + * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) + * if subtree_alpha < effective_alpha: # <<<<<<<<<<<<<< + * effective_alpha = subtree_alpha + * pruned_branch_node_idx = i + */ + } + __pyx_L36_continue:; + } + + /* "_tree.pyx":1500 + * pruned_branch_node_idx = i + * + * if controller.stop_pruning(effective_alpha): # <<<<<<<<<<<<<< + * break + * + */ + __pyx_t_16 = (((struct __pyx_vtabstruct_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->stop_pruning(__pyx_v_controller, __pyx_v_effective_alpha) != 0); + if (__pyx_t_16) { + + /* "_tree.pyx":1501 + * + * if controller.stop_pruning(effective_alpha): + * break # <<<<<<<<<<<<<< + * + * # stack uses only the start variable + */ + goto __pyx_L35_break; + + /* "_tree.pyx":1500 + * pruned_branch_node_idx = i + * + * if controller.stop_pruning(effective_alpha): # <<<<<<<<<<<<<< + * break + * + */ + } + + /* "_tree.pyx":1504 + * + * # stack uses only the start variable + * rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) # <<<<<<<<<<<<<< + * if rc == -1: + * with gil: + */ + __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_pruned_branch_node_idx, 0, 0, 0, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1504, __pyx_L4_error) + __pyx_v_rc = __pyx_t_15; + + /* "_tree.pyx":1505 + * # stack uses only the start variable + * rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) + * if rc == -1: # <<<<<<<<<<<<<< + * with gil: + * raise MemoryError("pruning tree") + */ + __pyx_t_16 = ((__pyx_v_rc == -1L) != 0); + if (__pyx_t_16) { + + /* "_tree.pyx":1506 + * rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) + * if rc == -1: + * with gil: # <<<<<<<<<<<<<< + * raise MemoryError("pruning tree") + * + */ + { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); + #endif + /*try:*/ { + + /* "_tree.pyx":1507 + * if rc == -1: + * with gil: + * raise MemoryError("pruning tree") # <<<<<<<<<<<<<< + * + * # descendants of branch are not in subtree + */ + __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_MemoryError, __pyx_tuple__16, NULL); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1507, __pyx_L45_error) + __Pyx_GOTREF(__pyx_t_6); + __Pyx_Raise(__pyx_t_6, 0, 0, 0); + __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; + __PYX_ERR(0, 1507, __pyx_L45_error) + } + + /* "_tree.pyx":1506 + * rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) + * if rc == -1: + * with gil: # <<<<<<<<<<<<<< + * raise MemoryError("pruning tree") + * + */ + /*finally:*/ { + __pyx_L45_error: { + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + goto __pyx_L4_error; + } + } + } + + /* "_tree.pyx":1505 + * # stack uses only the start variable + * rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) + * if rc == -1: # <<<<<<<<<<<<<< + * with gil: + * raise MemoryError("pruning tree") + */ + } + + /* "_tree.pyx":1510 + * + * # descendants of branch are not in subtree + * while not stack.is_empty(): # <<<<<<<<<<<<<< + * stack.pop(&stack_record) + * node_idx = stack_record.start + */ + while (1) { + __pyx_t_16 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0); + if (!__pyx_t_16) break; + + /* "_tree.pyx":1511 + * # descendants of branch are not in subtree + * while not stack.is_empty(): + * stack.pop(&stack_record) # <<<<<<<<<<<<<< + * node_idx = stack_record.start + * + */ + (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record))); + + /* "_tree.pyx":1512 + * while not stack.is_empty(): + * stack.pop(&stack_record) + * node_idx = stack_record.start # <<<<<<<<<<<<<< + * + * if not in_subtree[node_idx]: + */ + __pyx_t_17 = __pyx_v_stack_record.start; + __pyx_v_node_idx = __pyx_t_17; + + /* "_tree.pyx":1514 + * node_idx = stack_record.start + * + * if not in_subtree[node_idx]: # <<<<<<<<<<<<<< + * continue # branch has already been marked for pruning + * candidate_nodes[node_idx] = 0 + */ + __pyx_t_14 = __pyx_v_node_idx; + __pyx_t_16 = ((!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_in_subtree.data + __pyx_t_14 * __pyx_v_in_subtree.strides[0]) ))) != 0)) != 0); + if (__pyx_t_16) { + + /* "_tree.pyx":1515 + * + * if not in_subtree[node_idx]: + * continue # branch has already been marked for pruning # <<<<<<<<<<<<<< + * candidate_nodes[node_idx] = 0 + * leaves_in_subtree[node_idx] = 0 + */ + goto __pyx_L47_continue; + + /* "_tree.pyx":1514 + * node_idx = stack_record.start + * + * if not in_subtree[node_idx]: # <<<<<<<<<<<<<< + * continue # branch has already been marked for pruning + * candidate_nodes[node_idx] = 0 + */ + } + + /* "_tree.pyx":1516 + * if not in_subtree[node_idx]: + * continue # branch has already been marked for pruning + * candidate_nodes[node_idx] = 0 # <<<<<<<<<<<<<< + * leaves_in_subtree[node_idx] = 0 + * in_subtree[node_idx] = 0 + */ + __pyx_t_14 = __pyx_v_node_idx; + *((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_14 * __pyx_v_candidate_nodes.strides[0]) )) = 0; + + /* "_tree.pyx":1517 + * continue # branch has already been marked for pruning + * candidate_nodes[node_idx] = 0 + * leaves_in_subtree[node_idx] = 0 # <<<<<<<<<<<<<< + * in_subtree[node_idx] = 0 + * + */ + __pyx_t_14 = __pyx_v_node_idx; + *((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_14 * __pyx_v_leaves_in_subtree.strides[0]) )) = 0; + + /* "_tree.pyx":1518 + * candidate_nodes[node_idx] = 0 + * leaves_in_subtree[node_idx] = 0 + * in_subtree[node_idx] = 0 # <<<<<<<<<<<<<< + * + * if child_l[node_idx] != _TREE_LEAF: + */ + __pyx_t_14 = __pyx_v_node_idx; + *((unsigned char *) ( /* dim=0 */ (__pyx_v_in_subtree.data + __pyx_t_14 * __pyx_v_in_subtree.strides[0]) )) = 0; + + /* "_tree.pyx":1520 + * in_subtree[node_idx] = 0 + * + * if child_l[node_idx] != _TREE_LEAF: # <<<<<<<<<<<<<< + * # ... and child_r[node_idx] != _TREE_LEAF: + * rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) + */ + __pyx_t_14 = __pyx_v_node_idx; + __pyx_t_16 = (((*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_14 * __pyx_v_child_l.strides[0]) ))) != __pyx_v_5_tree__TREE_LEAF) != 0); + if (__pyx_t_16) { + + /* "_tree.pyx":1522 + * if child_l[node_idx] != _TREE_LEAF: + * # ... and child_r[node_idx] != _TREE_LEAF: + * rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) # <<<<<<<<<<<<<< + * if rc == -1: + * with gil: + */ + __pyx_t_14 = __pyx_v_node_idx; + __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_14 * __pyx_v_child_l.strides[0]) ))), 0, 0, 0, 0, 0.0, 0); 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if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1525, __pyx_L55_error) + __Pyx_GOTREF(__pyx_t_6); + __Pyx_Raise(__pyx_t_6, 0, 0, 0); + __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; + __PYX_ERR(0, 1525, __pyx_L55_error) + } + + /* "_tree.pyx":1524 + * rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) + * if rc == -1: + * with gil: # <<<<<<<<<<<<<< + * raise MemoryError("pruning tree") + * rc = stack.push(child_r[node_idx], 0, 0, 0, 0, 0, 0) + */ + /*finally:*/ { + __pyx_L55_error: { + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + goto __pyx_L4_error; + } + } + } + + /* "_tree.pyx":1523 + * # ... and child_r[node_idx] != _TREE_LEAF: + * rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) + * if rc == -1: # <<<<<<<<<<<<<< + * with gil: + * raise MemoryError("pruning tree") + */ + } + + /* "_tree.pyx":1526 + * with gil: + * raise MemoryError("pruning tree") + * rc = stack.push(child_r[node_idx], 0, 0, 0, 0, 0, 0) # <<<<<<<<<<<<<< + * if rc == -1: + * with gil: + */ + __pyx_t_14 = __pyx_v_node_idx; 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if (unlikely(!__pyx_t_3)) __PYX_ERR(1, 782, __pyx_L1_error) + __Pyx_GOTREF(__pyx_t_3); + + /* "View.MemoryView":782 + * memview.dtype_is_object) + * else: + * return memoryview_fromslice(dst, new_ndim, NULL, NULL, # <<<<<<<<<<<<<< + * memview.dtype_is_object) + * + */ + if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_memoryview_type))))) __PYX_ERR(1, 782, __pyx_L1_error) + __pyx_r = ((struct __pyx_memoryview_obj *)__pyx_t_3); + __pyx_t_3 = 0; + goto __pyx_L0; + } + + /* "View.MemoryView":710 + * + * @cname('__pyx_memview_slice') + * cdef memoryview memview_slice(memoryview memview, object indices): # <<<<<<<<<<<<<< + * cdef int new_ndim = 0, suboffset_dim = -1, dim + * cdef bint negative_step + */ + + /* function exit code */ + __pyx_L1_error:; + __Pyx_XDECREF(__pyx_t_3); + __Pyx_XDECREF(__pyx_t_9); + __Pyx_AddTraceback("View.MemoryView.memview_slice", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = 0; + __pyx_L0:; + __Pyx_XDECREF((PyObject *)__pyx_v_memviewsliceobj); + __Pyx_XDECREF(__pyx_v_index); + __Pyx_XGIVEREF((PyObject *)__pyx_r); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +/* "View.MemoryView":807 + * + * @cname('__pyx_memoryview_slice_memviewslice') + * cdef int slice_memviewslice( # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset, + */ + +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, Py_ssize_t __pyx_v_shape, Py_ssize_t __pyx_v_stride, Py_ssize_t __pyx_v_suboffset, int __pyx_v_dim, int __pyx_v_new_ndim, int *__pyx_v_suboffset_dim, Py_ssize_t __pyx_v_start, Py_ssize_t __pyx_v_stop, Py_ssize_t __pyx_v_step, int __pyx_v_have_start, int __pyx_v_have_stop, int __pyx_v_have_step, int __pyx_v_is_slice) { + Py_ssize_t __pyx_v_new_shape; + int __pyx_v_negative_step; + int __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "View.MemoryView":827 + * cdef bint negative_step + * + * if not is_slice: # <<<<<<<<<<<<<< + * + * if start < 0: + */ + __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0); 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if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(1, 832, __pyx_L1_error) + + /* "View.MemoryView":831 + * if start < 0: + * start += shape + * if not 0 <= start < shape: # <<<<<<<<<<<<<< + * _err_dim(IndexError, "Index out of bounds (axis %d)", dim) + * else: + */ + } + + /* "View.MemoryView":827 + * cdef bint negative_step + * + * if not is_slice: # <<<<<<<<<<<<<< + * + * if start < 0: + */ + goto __pyx_L3; + } + + /* "View.MemoryView":835 + * else: + * + * negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<< + * + * if have_step and step == 0: + */ + /*else*/ { + __pyx_t_1 = ((__pyx_v_have_step != 0) != 0); + if (__pyx_t_1) { + } else { + __pyx_t_2 = __pyx_t_1; + goto __pyx_L6_bool_binop_done; + } + __pyx_t_1 = ((__pyx_v_step < 0) != 0); + __pyx_t_2 = __pyx_t_1; + __pyx_L6_bool_binop_done:; + __pyx_v_negative_step = __pyx_t_2; + + /* "View.MemoryView":837 + * negative_step = have_step != 0 and step < 0 + * + * if have_step and step == 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Step may not be zero (axis %d)", dim) + * + */ + __pyx_t_1 = (__pyx_v_have_step != 0); 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+ if (__pyx_t_2) { + + /* "View.MemoryView":843 + * if have_start: + * if start < 0: + * start += shape # <<<<<<<<<<<<<< + * if start < 0: + * start = 0 + */ + __pyx_v_start = (__pyx_v_start + __pyx_v_shape); + + /* "View.MemoryView":844 + * if start < 0: + * start += shape + * if start < 0: # <<<<<<<<<<<<<< + * start = 0 + * elif start >= shape: + */ + __pyx_t_2 = ((__pyx_v_start < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":845 + * start += shape + * if start < 0: + * start = 0 # <<<<<<<<<<<<<< + * elif start >= shape: + * if negative_step: + */ + __pyx_v_start = 0; + + /* "View.MemoryView":844 + * if start < 0: + * start += shape + * if start < 0: # <<<<<<<<<<<<<< + * start = 0 + * elif start >= shape: + */ + } + + /* "View.MemoryView":842 + * + * if have_start: + * if start < 0: # <<<<<<<<<<<<<< + * start += shape + * if start < 0: + */ + goto __pyx_L12; + } + + /* "View.MemoryView":846 + * if start < 0: + * start = 0 + * elif start >= shape: # <<<<<<<<<<<<<< + * if negative_step: + * start = shape - 1 + */ + __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":847 + * start = 0 + * elif start >= shape: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":848 + * elif start >= shape: + * if negative_step: + * start = shape - 1 # <<<<<<<<<<<<<< + * else: + * start = shape + */ + __pyx_v_start = (__pyx_v_shape - 1); + + /* "View.MemoryView":847 + * start = 0 + * elif start >= shape: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + goto __pyx_L14; + } + + /* "View.MemoryView":850 + * start = shape - 1 + * else: + * start = shape # <<<<<<<<<<<<<< + * else: + * if negative_step: + */ + /*else*/ { + __pyx_v_start = __pyx_v_shape; + } + __pyx_L14:; + + /* "View.MemoryView":846 + * if start < 0: + * start = 0 + * elif start >= shape: # <<<<<<<<<<<<<< + * if negative_step: + * start = shape - 1 + */ + } + __pyx_L12:; + + /* "View.MemoryView":841 + * + * + * if have_start: # <<<<<<<<<<<<<< + * if start < 0: + * start += shape + */ + goto __pyx_L11; + } + + /* "View.MemoryView":852 + * start = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + /*else*/ { + __pyx_t_2 = (__pyx_v_negative_step != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":853 + * else: + * if negative_step: + * start = shape - 1 # <<<<<<<<<<<<<< + * else: + * start = 0 + */ + __pyx_v_start = (__pyx_v_shape - 1); + + /* "View.MemoryView":852 + * start = shape + * else: + * if negative_step: # <<<<<<<<<<<<<< + * start = shape - 1 + * else: + */ + goto __pyx_L15; + } + + /* "View.MemoryView":855 + * start = shape - 1 + * else: + * start = 0 # <<<<<<<<<<<<<< + * + * if have_stop: + */ + /*else*/ { + __pyx_v_start = 0; + } + __pyx_L15:; + } + __pyx_L11:; + + /* "View.MemoryView":857 + * start = 0 + * + * if have_stop: # <<<<<<<<<<<<<< + * if stop < 0: + * stop += shape + */ + __pyx_t_2 = (__pyx_v_have_stop != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":858 + * + * if have_stop: + * if stop < 0: # <<<<<<<<<<<<<< + * stop += shape + * if stop < 0: + */ + __pyx_t_2 = ((__pyx_v_stop < 0) != 0); 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+ } + __pyx_L19:; + } + __pyx_L16:; + + /* "View.MemoryView":870 + * stop = shape + * + * if not have_step: # <<<<<<<<<<<<<< + * step = 1 + * + */ + __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":871 + * + * if not have_step: + * step = 1 # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_step = 1; + + /* "View.MemoryView":870 + * stop = shape + * + * if not have_step: # <<<<<<<<<<<<<< + * step = 1 + * + */ + } + + /* "View.MemoryView":875 + * + * with cython.cdivision(True): + * new_shape = (stop - start) // step # <<<<<<<<<<<<<< + * + * if (stop - start) - step * new_shape: + */ + __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step); + + /* "View.MemoryView":877 + * new_shape = (stop - start) // step + * + * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< + * new_shape += 1 + * + */ + __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":878 + * + * if (stop - start) - step * new_shape: + * new_shape += 1 # <<<<<<<<<<<<<< + * + * if new_shape < 0: + */ + __pyx_v_new_shape = (__pyx_v_new_shape + 1); + + /* "View.MemoryView":877 + * new_shape = (stop - start) // step + * + * if (stop - start) - step * new_shape: # <<<<<<<<<<<<<< + * new_shape += 1 + * + */ + } + + /* "View.MemoryView":880 + * new_shape += 1 + * + * if new_shape < 0: # <<<<<<<<<<<<<< + * new_shape = 0 + * + */ + __pyx_t_2 = ((__pyx_v_new_shape < 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":881 + * + * if new_shape < 0: + * new_shape = 0 # <<<<<<<<<<<<<< + * + * + */ + __pyx_v_new_shape = 0; + + /* "View.MemoryView":880 + * new_shape += 1 + * + * if new_shape < 0: # <<<<<<<<<<<<<< + * new_shape = 0 + * + */ + } + + /* "View.MemoryView":884 + * + * + * dst.strides[new_ndim] = stride * step # <<<<<<<<<<<<<< + * dst.shape[new_ndim] = new_shape + * dst.suboffsets[new_ndim] = suboffset + */ + (__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step); + + /* "View.MemoryView":885 + * + * dst.strides[new_ndim] = stride * step + * dst.shape[new_ndim] = new_shape # <<<<<<<<<<<<<< + * dst.suboffsets[new_ndim] = suboffset + * + */ + (__pyx_v_dst->shape[__pyx_v_new_ndim]) = __pyx_v_new_shape; 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+ __pyx_t_2 = (__pyx_t_1 != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1095 + * + * if isinstance(memview, _memoryviewslice): + * to_object_func = (<_memoryviewslice> memview).to_object_func # <<<<<<<<<<<<<< + * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func + * else: + */ + __pyx_t_3 = ((struct __pyx_memoryviewslice_obj *)__pyx_v_memview)->to_object_func; + __pyx_v_to_object_func = __pyx_t_3; + + /* "View.MemoryView":1096 + * if isinstance(memview, _memoryviewslice): + * to_object_func = (<_memoryviewslice> memview).to_object_func + * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func # <<<<<<<<<<<<<< + * else: + * to_object_func = NULL + */ + __pyx_t_4 = ((struct __pyx_memoryviewslice_obj *)__pyx_v_memview)->to_dtype_func; + __pyx_v_to_dtype_func = __pyx_t_4; + + /* "View.MemoryView":1094 + * cdef int (*to_dtype_func)(char *, object) except 0 + * + * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< + * to_object_func = (<_memoryviewslice> memview).to_object_func + * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1098 + * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func + * else: + * to_object_func = NULL # <<<<<<<<<<<<<< + * to_dtype_func = NULL + * + */ + /*else*/ { + __pyx_v_to_object_func = NULL; + + /* "View.MemoryView":1099 + * else: + * to_object_func = NULL + * to_dtype_func = NULL # <<<<<<<<<<<<<< + * + * return memoryview_fromslice(memviewslice[0], memview.view.ndim, + */ + __pyx_v_to_dtype_func = NULL; + } + __pyx_L3:; + + /* "View.MemoryView":1101 + * to_dtype_func = NULL + * + * return memoryview_fromslice(memviewslice[0], memview.view.ndim, # <<<<<<<<<<<<<< + * to_object_func, to_dtype_func, + * memview.dtype_is_object) + */ + __Pyx_XDECREF(__pyx_r); + + /* "View.MemoryView":1103 + * return memoryview_fromslice(memviewslice[0], memview.view.ndim, + * to_object_func, to_dtype_func, + * memview.dtype_is_object) # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_5 = __pyx_memoryview_fromslice((__pyx_v_memviewslice[0]), __pyx_v_memview->view.ndim, __pyx_v_to_object_func, __pyx_v_to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_5)) __PYX_ERR(1, 1101, __pyx_L1_error) + __Pyx_GOTREF(__pyx_t_5); + __pyx_r = __pyx_t_5; + __pyx_t_5 = 0; + goto __pyx_L0; + + /* "View.MemoryView":1087 + * + * @cname('__pyx_memoryview_copy_object_from_slice') + * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< + * """ + * Create a new memoryview object from a given memoryview object and slice. + */ + + /* function exit code */ + __pyx_L1_error:; + __Pyx_XDECREF(__pyx_t_5); + __Pyx_AddTraceback("View.MemoryView.memoryview_copy_from_slice", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = 0; + __pyx_L0:; + __Pyx_XGIVEREF(__pyx_r); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +/* "View.MemoryView":1109 + * + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< + * if arg < 0: + * return -arg + */ + +static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) { + Py_ssize_t __pyx_r; + int __pyx_t_1; + + /* "View.MemoryView":1110 + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: # <<<<<<<<<<<<<< + * return -arg + * else: + */ + __pyx_t_1 = ((__pyx_v_arg < 0) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1111 + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: + * return -arg # <<<<<<<<<<<<<< + * else: + * return arg + */ + __pyx_r = (-__pyx_v_arg); + goto __pyx_L0; + + /* "View.MemoryView":1110 + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: + * if arg < 0: # <<<<<<<<<<<<<< + * return -arg + * else: + */ + } + + /* "View.MemoryView":1113 + * return -arg + * else: + * return arg # <<<<<<<<<<<<<< + * + * @cname('__pyx_get_best_slice_order') + */ + /*else*/ { + __pyx_r = __pyx_v_arg; + goto __pyx_L0; + } + + /* "View.MemoryView":1109 + * + * + * cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<< + * if arg < 0: + * return -arg + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1116 + * + * @cname('__pyx_get_best_slice_order') + * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< + * """ + * Figure out the best memory access order for a given slice. + */ + +static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim) { + int __pyx_v_i; + Py_ssize_t __pyx_v_c_stride; + Py_ssize_t __pyx_v_f_stride; + char __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_t_4; + + /* "View.MemoryView":1121 + * """ + * cdef int i + * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< + * cdef Py_ssize_t f_stride = 0 + * + */ + __pyx_v_c_stride = 0; + + /* "View.MemoryView":1122 + * cdef int i + * cdef Py_ssize_t c_stride = 0 + * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< + * + * for i in range(ndim - 1, -1, -1): + */ + __pyx_v_f_stride = 0; + + /* "View.MemoryView":1124 + * cdef Py_ssize_t f_stride = 0 + * + * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] + */ + for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { + __pyx_v_i = __pyx_t_1; + + /* "View.MemoryView":1125 + * + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * c_stride = mslice.strides[i] + * break + */ + __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1126 + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1127 + * if mslice.shape[i] > 1: + * c_stride = mslice.strides[i] + * break # <<<<<<<<<<<<<< + * + * for i in range(ndim): + */ + goto __pyx_L4_break; + + /* "View.MemoryView":1125 + * + * for i in range(ndim - 1, -1, -1): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * c_stride = mslice.strides[i] + * break + */ + } + } + __pyx_L4_break:; + + /* "View.MemoryView":1129 + * break + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] + */ + __pyx_t_1 = __pyx_v_ndim; + __pyx_t_3 = __pyx_t_1; + for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { + __pyx_v_i = __pyx_t_4; + + /* "View.MemoryView":1130 + * + * for i in range(ndim): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * f_stride = mslice.strides[i] + * break + */ + __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1131 + * for i in range(ndim): + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1132 + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] + * break # <<<<<<<<<<<<<< + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): + */ + goto __pyx_L7_break; + + /* "View.MemoryView":1130 + * + * for i in range(ndim): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * f_stride = mslice.strides[i] + * break + */ + } + } + __pyx_L7_break:; + + /* "View.MemoryView":1134 + * break + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< + * return 'C' + * else: + */ + __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1135 + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): + * return 'C' # <<<<<<<<<<<<<< + * else: + * return 'F' + */ + __pyx_r = 'C'; + goto __pyx_L0; + + /* "View.MemoryView":1134 + * break + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< + * return 'C' + * else: + */ + } + + /* "View.MemoryView":1137 + * return 'C' + * else: + * return 'F' # <<<<<<<<<<<<<< + * + * @cython.cdivision(True) + */ + /*else*/ { + __pyx_r = 'F'; + goto __pyx_L0; + } + + /* "View.MemoryView":1116 + * + * @cname('__pyx_get_best_slice_order') + * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< + * """ + * Figure out the best memory access order for a given slice. + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1140 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + +static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + CYTHON_UNUSED Py_ssize_t __pyx_v_i; + CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; + Py_ssize_t __pyx_v_dst_extent; + Py_ssize_t __pyx_v_src_stride; + Py_ssize_t __pyx_v_dst_stride; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + Py_ssize_t __pyx_t_4; + Py_ssize_t __pyx_t_5; + Py_ssize_t __pyx_t_6; + + /* "View.MemoryView":1147 + * + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + */ + __pyx_v_src_extent = (__pyx_v_src_shape[0]); + + /* "View.MemoryView":1148 + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] + */ + __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); + + /* "View.MemoryView":1149 + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + */ + __pyx_v_src_stride = (__pyx_v_src_strides[0]); + + /* "View.MemoryView":1150 + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< + * + * if ndim == 1: + */ + __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); + + /* "View.MemoryView":1152 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + + /* "View.MemoryView":1154 + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + */ + __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); + if (__pyx_t_2) { + __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); + } + __pyx_t_3 = (__pyx_t_2 != 0); + __pyx_t_1 = __pyx_t_3; + __pyx_L5_bool_binop_done:; + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + if (__pyx_t_1) { + + /* "View.MemoryView":1155 + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + goto __pyx_L4; + } + + /* "View.MemoryView":1157 + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + */ + /*else*/ { + __pyx_t_4 = __pyx_v_dst_extent; + __pyx_t_5 = __pyx_t_4; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1158 + * else: + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< + * src_data += src_stride + * dst_data += dst_stride + */ + (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize)); + + /* "View.MemoryView":1159 + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * else: + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1160 + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L4:; + + /* "View.MemoryView":1152 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1162 + * dst_data += dst_stride + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * _copy_strided_to_strided(src_data, src_strides + 1, + * dst_data, dst_strides + 1, + */ + /*else*/ { + __pyx_t_4 = __pyx_v_dst_extent; + __pyx_t_5 = __pyx_t_4; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1163 + * else: + * for i in range(dst_extent): + * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< + * dst_data, dst_strides + 1, + * src_shape + 1, dst_shape + 1, + */ + _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); + + /* "View.MemoryView":1167 + * src_shape + 1, dst_shape + 1, + * ndim - 1, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1168 + * ndim - 1, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L3:; + + /* "View.MemoryView":1140 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + + /* function exit code */ +} + +/* "View.MemoryView":1170 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + +static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + + /* "View.MemoryView":1173 + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< + * src.shape, dst.shape, ndim, itemsize) + * + */ + _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1170 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + + /* function exit code */ +} + +/* "View.MemoryView":1177 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + */ + +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { + Py_ssize_t __pyx_v_shape; + Py_ssize_t __pyx_v_size; + Py_ssize_t __pyx_r; + Py_ssize_t __pyx_t_1; + Py_ssize_t *__pyx_t_2; + Py_ssize_t *__pyx_t_3; + Py_ssize_t *__pyx_t_4; + + /* "View.MemoryView":1179 + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize # <<<<<<<<<<<<<< + * + * for shape in src.shape[:ndim]: + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; 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+ return __pyx_r; +} + +/* "View.MemoryView":1187 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { + int __pyx_v_idx; + Py_ssize_t __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_t_4; + + /* "View.MemoryView":1196 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + __pyx_t_1 = ((__pyx_v_order == 'F') != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1197 + * + * if order == 'F': + * for idx in range(ndim): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride *= shape[idx] + */ + __pyx_t_2 = __pyx_v_ndim; + __pyx_t_3 = __pyx_t_2; + for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { + __pyx_v_idx = __pyx_t_4; + + /* "View.MemoryView":1198 + * if order == 'F': + * for idx in range(ndim): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride *= shape[idx] + * else: + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1199 + * for idx in range(ndim): + * strides[idx] = stride + * stride *= shape[idx] # <<<<<<<<<<<<<< + * else: + * for idx in range(ndim - 1, -1, -1): + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + } + + /* "View.MemoryView":1196 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1201 + * stride *= shape[idx] + * else: + * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride *= shape[idx] + */ + /*else*/ { + for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) { + __pyx_v_idx = __pyx_t_2; + + /* "View.MemoryView":1202 + * else: + * for idx in range(ndim - 1, -1, -1): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride *= shape[idx] + * + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; 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if (unlikely(__pyx_t_7 == ((void *)NULL))) __PYX_ERR(1, 1307, __pyx_L1_error) + __pyx_v_tmpdata = __pyx_t_7; + + /* "View.MemoryView":1308 + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) + * src = tmp # <<<<<<<<<<<<<< + * + * if not broadcasting: + */ + __pyx_v_src = __pyx_v_tmp; + + /* "View.MemoryView":1302 + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< + * + * if not slice_is_contig(src, order, ndim): + */ + } + + /* "View.MemoryView":1310 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1313 + * + * + * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'C', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1314 + * + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) # <<<<<<<<<<<<<< + * elif slice_is_contig(src, 'F', ndim): + * direct_copy = slice_is_contig(dst, 'F', ndim) + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim); + + /* "View.MemoryView":1313 + * + * + * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + */ + goto __pyx_L12; + } + + /* "View.MemoryView":1315 + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'F', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1316 + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + * direct_copy = slice_is_contig(dst, 'F', ndim) # <<<<<<<<<<<<<< + * + * if direct_copy: + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim); + + /* "View.MemoryView":1315 + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + */ + } + __pyx_L12:; + + /* "View.MemoryView":1318 + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_2 = (__pyx_v_direct_copy != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1320 + * if direct_copy: + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1321 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + */ + (void)(memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim))); + + /* "View.MemoryView":1322 + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * free(tmpdata) + * return 0 + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1323 + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) # <<<<<<<<<<<<<< + * return 0 + * + */ + free(__pyx_v_tmpdata); + + /* "View.MemoryView":1324 + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + * return 0 # <<<<<<<<<<<<<< + * + * if order == 'F' == get_best_order(&dst, ndim): + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "View.MemoryView":1318 + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + } + + /* "View.MemoryView":1310 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + } + + /* "View.MemoryView":1326 + * return 0 + * + * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = (__pyx_v_order == 'F'); + if (__pyx_t_2) { + __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim)); 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+} + +static int __pyx_setprop_5_tree_4Tree_y(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { + if (v) { + return __pyx_pw_5_tree_4Tree_1y_3__set__(o, v); + } + else { + return __pyx_pw_5_tree_4Tree_1y_5__del__(o); + } +} + +static PyMethodDef __pyx_methods_5_tree_Tree[] = { + {"__reduce__", (PyCFunction)__pyx_pw_5_tree_4Tree_5__reduce__, METH_NOARGS, __pyx_doc_5_tree_4Tree_4__reduce__}, + {"__getstate__", (PyCFunction)__pyx_pw_5_tree_4Tree_7__getstate__, METH_NOARGS, __pyx_doc_5_tree_4Tree_6__getstate__}, + {"__setstate__", (PyCFunction)__pyx_pw_5_tree_4Tree_9__setstate__, METH_O, __pyx_doc_5_tree_4Tree_8__setstate__}, + {"predict", (PyCFunction)__pyx_pw_5_tree_4Tree_11predict, METH_O, __pyx_doc_5_tree_4Tree_10predict}, + {"decode_tree", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_4Tree_13decode_tree, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree_4Tree_12decode_tree}, + {"apply", (PyCFunction)__pyx_pw_5_tree_4Tree_15apply, METH_O, __pyx_doc_5_tree_4Tree_14apply}, + {"decision_path", (PyCFunction)__pyx_pw_5_tree_4Tree_17decision_path, METH_O, __pyx_doc_5_tree_4Tree_16decision_path}, + {"compute_feature_importances", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_4Tree_19compute_feature_importances, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree_4Tree_18compute_feature_importances}, + {0, 0, 0, 0} +}; 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+ +static PyTypeObject __pyx_type_5_tree_Tree = { + PyVarObject_HEAD_INIT(0, 0) + "_tree.Tree", /*tp_name*/ + sizeof(struct __pyx_obj_5_tree_Tree), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_5_tree_Tree, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Array-based representation of a binary decision tree.\n\n The binary tree is represented as a number of parallel arrays. 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Otherwise,\n children_left[i] > i. This child handles the case where\n X[:, feature[i]] <= threshold[i].\n\n children_right : array of int, shape [node_count]\n children_right[i] holds the node id of the right child of node i.\n For leaves, children_right[i] == TREE_LEAF. Otherwise,\n children_right[i] > i. This child handles the case where\n X[:, feature[i]] > threshold[i].\n\n feature : array of int, shape [node_count]\n feature[""i] holds the feature to split on, for the internal node i.\n\n threshold : array of double, shape [node_count]\n threshold[i] holds the threshold for the internal node i.\n\n impurity : array of double, shape [node_count]\n impurity[i] holds the impurity (i.e., the value of the splitting\n criterion) at node i.\n\n n_node_samples : array of int, shape [node_count]\n n_node_samples[i] holds the number of training samples reaching node i.\n\n weighted_n_node_samples : array of int, shape [node_count]\n weighted_n_node_samples[i] holds the weighted number of training samples\n reaching node i.\n ", /*tp_doc*/ + __pyx_tp_traverse_5_tree_Tree, /*tp_traverse*/ + __pyx_tp_clear_5_tree_Tree, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_5_tree_Tree, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_5_tree_Tree, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_5_tree_Tree, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_5_tree_TreeBuilder __pyx_vtable_5_tree_TreeBuilder; + +static PyObject *__pyx_tp_new_5_tree_TreeBuilder(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + struct __pyx_obj_5_tree_TreeBuilder *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_5_tree_TreeBuilder *)o); + p->__pyx_vtab = __pyx_vtabptr_5_tree_TreeBuilder; + p->splitter = ((struct __pyx_obj_9_splitter_Splitter *)Py_None); Py_INCREF(Py_None); + return o; +} + +static void __pyx_tp_dealloc_5_tree_TreeBuilder(PyObject *o) { + struct __pyx_obj_5_tree_TreeBuilder *p = (struct __pyx_obj_5_tree_TreeBuilder *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + Py_CLEAR(p->splitter); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_5_tree_TreeBuilder(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_obj_5_tree_TreeBuilder *p = (struct __pyx_obj_5_tree_TreeBuilder *)o; + if (p->splitter) { + e = (*v)(((PyObject *)p->splitter), a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_5_tree_TreeBuilder(PyObject *o) { + PyObject* tmp; + struct __pyx_obj_5_tree_TreeBuilder *p = (struct __pyx_obj_5_tree_TreeBuilder *)o; + tmp = ((PyObject*)p->splitter); + p->splitter = ((struct __pyx_obj_9_splitter_Splitter *)Py_None); Py_INCREF(Py_None); + Py_XDECREF(tmp); + return 0; +} + +static PyMethodDef __pyx_methods_5_tree_TreeBuilder[] = { + {"build", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_11TreeBuilder_1build, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree_11TreeBuilder_build}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_11TreeBuilder_3__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_11TreeBuilder_5__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_5_tree_TreeBuilder = { + PyVarObject_HEAD_INIT(0, 0) + "_tree.TreeBuilder", /*tp_name*/ + sizeof(struct __pyx_obj_5_tree_TreeBuilder), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_5_tree_TreeBuilder, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Interface for different tree building strategies.", /*tp_doc*/ + __pyx_tp_traverse_5_tree_TreeBuilder, /*tp_traverse*/ + __pyx_tp_clear_5_tree_TreeBuilder, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_5_tree_TreeBuilder, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_5_tree_TreeBuilder, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_5_tree_DepthFirstTreeBuilder __pyx_vtable_5_tree_DepthFirstTreeBuilder; + +static PyObject *__pyx_tp_new_5_tree_DepthFirstTreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_5_tree_DepthFirstTreeBuilder *p; + PyObject *o = __pyx_tp_new_5_tree_TreeBuilder(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_5_tree_DepthFirstTreeBuilder *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_5_tree_TreeBuilder*)__pyx_vtabptr_5_tree_DepthFirstTreeBuilder; + if (unlikely(__pyx_pw_5_tree_21DepthFirstTreeBuilder_1__cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static PyMethodDef __pyx_methods_5_tree_DepthFirstTreeBuilder[] = { + {"build", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_21DepthFirstTreeBuilder_3build, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree_21DepthFirstTreeBuilder_2build}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_21DepthFirstTreeBuilder_5__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_21DepthFirstTreeBuilder_7__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_5_tree_DepthFirstTreeBuilder = { + PyVarObject_HEAD_INIT(0, 0) + "_tree.DepthFirstTreeBuilder", /*tp_name*/ + sizeof(struct __pyx_obj_5_tree_DepthFirstTreeBuilder), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_5_tree_TreeBuilder, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Build a decision tree in depth-first fashion.", /*tp_doc*/ + __pyx_tp_traverse_5_tree_TreeBuilder, /*tp_traverse*/ + __pyx_tp_clear_5_tree_TreeBuilder, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_5_tree_DepthFirstTreeBuilder, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_5_tree_DepthFirstTreeBuilder, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_5_tree_BestFirstTreeBuilder __pyx_vtable_5_tree_BestFirstTreeBuilder; + +static PyObject *__pyx_tp_new_5_tree_BestFirstTreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_5_tree_BestFirstTreeBuilder *p; + PyObject *o = __pyx_tp_new_5_tree_TreeBuilder(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_5_tree_BestFirstTreeBuilder *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_5_tree_TreeBuilder*)__pyx_vtabptr_5_tree_BestFirstTreeBuilder; + if (unlikely(__pyx_pw_5_tree_20BestFirstTreeBuilder_1__cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static PyMethodDef __pyx_methods_5_tree_BestFirstTreeBuilder[] = { + {"build", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_20BestFirstTreeBuilder_3build, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree_20BestFirstTreeBuilder_2build}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_20BestFirstTreeBuilder_5__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_20BestFirstTreeBuilder_7__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_5_tree_BestFirstTreeBuilder = { + PyVarObject_HEAD_INIT(0, 0) + "_tree.BestFirstTreeBuilder", /*tp_name*/ + sizeof(struct __pyx_obj_5_tree_BestFirstTreeBuilder), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_5_tree_TreeBuilder, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Build a decision tree in best-first fashion.\n\n The best node to expand is given by the node at the frontier that has the\n highest impurity improvement.\n ", /*tp_doc*/ + __pyx_tp_traverse_5_tree_TreeBuilder, /*tp_traverse*/ + __pyx_tp_clear_5_tree_TreeBuilder, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_5_tree_BestFirstTreeBuilder, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_5_tree_BestFirstTreeBuilder, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_5_tree__CCPPruneController __pyx_vtable_5_tree__CCPPruneController; + +static PyObject *__pyx_tp_new_5_tree__CCPPruneController(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + struct __pyx_obj_5_tree__CCPPruneController *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_5_tree__CCPPruneController *)o); + p->__pyx_vtab = __pyx_vtabptr_5_tree__CCPPruneController; + return o; +} + +static void __pyx_tp_dealloc_5_tree__CCPPruneController(PyObject *o) { + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + (*Py_TYPE(o)->tp_free)(o); +} + +static PyMethodDef __pyx_methods_5_tree__CCPPruneController[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_19_CCPPruneController_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_19_CCPPruneController_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_5_tree__CCPPruneController = { + PyVarObject_HEAD_INIT(0, 0) + "_tree._CCPPruneController", /*tp_name*/ + sizeof(struct __pyx_obj_5_tree__CCPPruneController), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_5_tree__CCPPruneController, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "Base class used by build_pruned_tree_ccp and ccp_pruning_path\n to control pruning.\n ", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_5_tree__CCPPruneController, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_5_tree__CCPPruneController, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_5_tree__AlphaPruner __pyx_vtable_5_tree__AlphaPruner; + +static PyObject *__pyx_tp_new_5_tree__AlphaPruner(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_5_tree__AlphaPruner *p; + PyObject *o = __pyx_tp_new_5_tree__CCPPruneController(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_5_tree__AlphaPruner *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_5_tree__CCPPruneController*)__pyx_vtabptr_5_tree__AlphaPruner; + if (unlikely(__pyx_pw_5_tree_12_AlphaPruner_1__cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static PyMethodDef __pyx_methods_5_tree__AlphaPruner[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_12_AlphaPruner_3__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_12_AlphaPruner_5__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_5_tree__AlphaPruner = { + PyVarObject_HEAD_INIT(0, 0) + "_tree._AlphaPruner", /*tp_name*/ + sizeof(struct __pyx_obj_5_tree__AlphaPruner), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_5_tree__CCPPruneController, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "Use alpha to control when to stop pruning.", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_5_tree__AlphaPruner, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_5_tree__AlphaPruner, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_5_tree__PathFinder __pyx_vtable_5_tree__PathFinder; + +static PyObject *__pyx_tp_new_5_tree__PathFinder(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_5_tree__PathFinder *p; + PyObject *o = __pyx_tp_new_5_tree__CCPPruneController(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_5_tree__PathFinder *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_5_tree__CCPPruneController*)__pyx_vtabptr_5_tree__PathFinder; + p->ccp_alphas.data = NULL; + p->ccp_alphas.memview = NULL; + p->impurities.data = NULL; + p->impurities.memview = NULL; + if (unlikely(__pyx_pw_5_tree_11_PathFinder_1__cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_5_tree__PathFinder(PyObject *o) { + struct __pyx_obj_5_tree__PathFinder *p = (struct __pyx_obj_5_tree__PathFinder *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + __PYX_XDEC_MEMVIEW(&p->ccp_alphas, 1); + __PYX_XDEC_MEMVIEW(&p->impurities, 1); + __pyx_tp_dealloc_5_tree__CCPPruneController(o); +} + +static PyMethodDef __pyx_methods_5_tree__PathFinder[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_11_PathFinder_3__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_11_PathFinder_5__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_5_tree__PathFinder = { + PyVarObject_HEAD_INIT(0, 0) + "_tree._PathFinder", /*tp_name*/ + sizeof(struct __pyx_obj_5_tree__PathFinder), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_5_tree__PathFinder, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "Record metrics used to return the cost complexity path.", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_5_tree__PathFinder, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_5_tree__PathFinder, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_array __pyx_vtable_array; + +static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_array_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_array_obj *)o); + p->__pyx_vtab = __pyx_vtabptr_array; + p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None); + p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None); + if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_array(PyObject *o) { + struct __pyx_array_obj *p = (struct __pyx_array_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_array___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->mode); + Py_CLEAR(p->_format); + (*Py_TYPE(o)->tp_free)(o); +} +static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_array___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) { + PyObject *v = __Pyx_PyObject_GenericGetAttr(o, n); + if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Clear(); + v = __pyx_array___getattr__(o, n); + } + return v; +} + +static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_5array_7memview_1__get__(o); +} + +static PyMethodDef __pyx_methods_array[] = { + {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_array_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_array_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_array[] = { + {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_array = { + __pyx_array___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_array, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_array = { + __pyx_array___len__, /*mp_length*/ + __pyx_array___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_array = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_array_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_array = { + PyVarObject_HEAD_INIT(0, 0) + "_tree.array", /*tp_name*/ + sizeof(struct __pyx_array_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_array, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_array, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_array, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + __pyx_tp_getattro_array, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_array, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + 0, /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_array, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_array, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_array, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; + +static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + struct __pyx_MemviewEnum_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_MemviewEnum_obj *)o); + p->name = Py_None; Py_INCREF(Py_None); + return o; +} + +static void __pyx_tp_dealloc_Enum(PyObject *o) { + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + Py_CLEAR(p->name); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + if (p->name) { + e = (*v)(p->name, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_Enum(PyObject *o) { + PyObject* tmp; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + tmp = ((PyObject*)p->name); + p->name = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + return 0; +} + +static PyMethodDef __pyx_methods_Enum[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_MemviewEnum = { + PyVarObject_HEAD_INIT(0, 0) + "_tree.Enum", /*tp_name*/ + sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_Enum, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + __pyx_MemviewEnum___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_Enum, /*tp_traverse*/ + __pyx_tp_clear_Enum, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_Enum, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + __pyx_MemviewEnum___init__, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_Enum, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview; + +static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryview_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryview_obj *)o); + p->__pyx_vtab = __pyx_vtabptr_memoryview; + p->obj = Py_None; Py_INCREF(Py_None); + p->_size = Py_None; Py_INCREF(Py_None); + p->_array_interface = Py_None; Py_INCREF(Py_None); + p->view.obj = NULL; + if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_memoryview(PyObject *o) { + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_memoryview___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->obj); + Py_CLEAR(p->_size); + Py_CLEAR(p->_array_interface); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + if (p->obj) { + e = (*v)(p->obj, a); if (e) return e; + } + if (p->_size) { + e = (*v)(p->_size, a); if (e) return e; + } + if (p->_array_interface) { + e = (*v)(p->_array_interface, a); if (e) return e; + } + if (p->view.obj) { + e = (*v)(p->view.obj, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_memoryview(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + tmp = ((PyObject*)p->obj); + p->obj = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_size); + p->_size = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_array_interface); + p->_array_interface = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + Py_CLEAR(p->view.obj); + return 0; +} +static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_memoryview___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_1T_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4base_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_5shape_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_7strides_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_10suboffsets_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4ndim_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_8itemsize_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_6nbytes_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4size_1__get__(o); +} + +static PyMethodDef __pyx_methods_memoryview[] = { + {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0}, + {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0}, + {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0}, + {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_memoryview[] = { + {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, (char *)0, 0}, + {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, (char *)0, 0}, + {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, (char *)0, 0}, + {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, (char *)0, 0}, + {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, (char *)0, 0}, + {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, (char *)0, 0}, + {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, (char *)0, 0}, + {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, (char *)0, 0}, + {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_memoryview = { + __pyx_memoryview___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_memoryview, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_memoryview = { + __pyx_memoryview___len__, /*mp_length*/ + __pyx_memoryview___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_memoryview = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_memoryview_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_memoryview = { + PyVarObject_HEAD_INIT(0, 0) + "_tree.memoryview", /*tp_name*/ + sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_memoryview, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + __pyx_memoryview___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + __pyx_memoryview___str__, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_memoryview, /*tp_traverse*/ + __pyx_tp_clear_memoryview, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_memoryview, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_memoryview, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_memoryview, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice; + +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryviewslice_obj *p; + PyObject *o = __pyx_tp_new_memoryview(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryviewslice_obj *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice; + p->from_object = Py_None; Py_INCREF(Py_None); + p->from_slice.memview = NULL; + return o; +} + +static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) { + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_memoryviewslice___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->from_object); + PyObject_GC_Track(o); + __pyx_tp_dealloc_memoryview(o); +} + +static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e; + if (p->from_object) { + e = (*v)(p->from_object, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear__memoryviewslice(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + __pyx_tp_clear_memoryview(o); + tmp = ((PyObject*)p->from_object); + p->from_object = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + __PYX_XDEC_MEMVIEW(&p->from_slice, 1); + return 0; +} + +static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_16_memoryviewslice_4base_1__get__(o); +} + +static PyMethodDef __pyx_methods__memoryviewslice[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = { + {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_memoryviewslice = { + PyVarObject_HEAD_INIT(0, 0) + "_tree._memoryviewslice", /*tp_name*/ + sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___repr__, /*tp_repr*/ + #else + 0, /*tp_repr*/ + #endif + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___str__, /*tp_str*/ + #else + 0, /*tp_str*/ + #endif + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Internal class for passing memoryview slices to Python", /*tp_doc*/ + __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/ + __pyx_tp_clear__memoryviewslice, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods__memoryviewslice, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets__memoryviewslice, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new__memoryviewslice, 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(PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + +/* PyFunctionFastCall */ +#if CYTHON_FAST_PYCALL +static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, + PyObject *globals) { + PyFrameObject *f; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject **fastlocals; + Py_ssize_t i; + PyObject *result; + assert(globals != NULL); + /* XXX Perhaps we should create a specialized + PyFrame_New() that doesn't take locals, but does + take builtins without sanity checking them. + */ + assert(tstate != NULL); + f = PyFrame_New(tstate, co, globals, NULL); + if (f == NULL) { + return NULL; + } + fastlocals = __Pyx_PyFrame_GetLocalsplus(f); + for (i = 0; i < na; i++) { + Py_INCREF(*args); + fastlocals[i] = *args++; + } + result = PyEval_EvalFrameEx(f,0); + ++tstate->recursion_depth; + Py_DECREF(f); + --tstate->recursion_depth; + return result; +} +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { + PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); + PyObject *globals = PyFunction_GET_GLOBALS(func); + PyObject *argdefs = PyFunction_GET_DEFAULTS(func); + PyObject *closure; +#if PY_MAJOR_VERSION >= 3 + PyObject *kwdefs; +#endif + PyObject *kwtuple, **k; + PyObject **d; + Py_ssize_t nd; + Py_ssize_t nk; + PyObject *result; + assert(kwargs == NULL || PyDict_Check(kwargs)); + nk = kwargs ? PyDict_Size(kwargs) : 0; + if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { + return NULL; + } + if ( +#if PY_MAJOR_VERSION >= 3 + co->co_kwonlyargcount == 0 && +#endif + likely(kwargs == NULL || nk == 0) && + co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { + if (argdefs == NULL && co->co_argcount == nargs) { + result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); + goto done; + } + else if (nargs == 0 && argdefs != NULL + && co->co_argcount == Py_SIZE(argdefs)) { + /* function called with no arguments, but all parameters have + a default value: use default values as arguments .*/ + args = &PyTuple_GET_ITEM(argdefs, 0); + result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); + goto done; + } + } + if (kwargs != NULL) { + Py_ssize_t pos, i; + kwtuple = PyTuple_New(2 * nk); + if (kwtuple == NULL) { + result = NULL; + goto done; + } + k = &PyTuple_GET_ITEM(kwtuple, 0); + pos = i = 0; + while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { + Py_INCREF(k[i]); + Py_INCREF(k[i+1]); + i += 2; + } + nk = i / 2; + } + else { + kwtuple = NULL; + k = NULL; + } + closure = PyFunction_GET_CLOSURE(func); +#if PY_MAJOR_VERSION >= 3 + kwdefs = PyFunction_GET_KW_DEFAULTS(func); +#endif + if (argdefs != NULL) { + d = &PyTuple_GET_ITEM(argdefs, 0); + nd = Py_SIZE(argdefs); + } + else { + d = NULL; + nd = 0; + } +#if PY_MAJOR_VERSION >= 3 + result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, kwdefs, closure); +#else + result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, closure); +#endif + Py_XDECREF(kwtuple); +done: + Py_LeaveRecursiveCall(); + return result; +} +#endif +#endif + +/* PyCFunctionFastCall */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { + PyCFunctionObject *func = (PyCFunctionObject*)func_obj; + PyCFunction meth = PyCFunction_GET_FUNCTION(func); + PyObject *self = PyCFunction_GET_SELF(func); + int flags = PyCFunction_GET_FLAGS(func); + assert(PyCFunction_Check(func)); + assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); + assert(nargs >= 0); + assert(nargs == 0 || args != NULL); + /* _PyCFunction_FastCallDict() must not be called with an exception set, + because it may clear it (directly or indirectly) and so the + caller loses its exception */ + assert(!PyErr_Occurred()); + if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { + return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); + } else { + return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); + } +} +#endif + +/* PyObjectCall */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { + PyObject *result; + ternaryfunc call = func->ob_type->tp_call; + if (unlikely(!call)) + return PyObject_Call(func, arg, kw); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = (*call)(func, arg, kw); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* RaiseArgTupleInvalid */ +static void __Pyx_RaiseArgtupleInvalid( + const char* func_name, + int exact, + Py_ssize_t num_min, + Py_ssize_t num_max, + Py_ssize_t num_found) +{ + Py_ssize_t num_expected; + const char *more_or_less; + if (num_found < num_min) { + num_expected = num_min; + more_or_less = "at least"; + } else { + num_expected = num_max; + more_or_less = "at most"; + } + if (exact) { + more_or_less = "exactly"; + } + PyErr_Format(PyExc_TypeError, + "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", + func_name, more_or_less, num_expected, + (num_expected == 1) ? "" : "s", num_found); +} + +/* RaiseDoubleKeywords */ +static void __Pyx_RaiseDoubleKeywordsError( + const char* func_name, + PyObject* kw_name) +{ + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION >= 3 + "%s() got multiple values for keyword argument '%U'", func_name, kw_name); + #else + "%s() got multiple values for keyword argument '%s'", func_name, + PyString_AsString(kw_name)); + #endif +} + +/* ParseKeywords */ +static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + continue; + } + name = first_kw_arg; + #if PY_MAJOR_VERSION < 3 + if (likely(PyString_Check(key))) { + while (*name) { + if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) + && _PyString_Eq(**name, key)) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + if ((**argname == key) || ( + (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) + && _PyString_Eq(**argname, key))) { + goto arg_passed_twice; + } + argname++; + } + } + } else + #endif + if (likely(PyUnicode_Check(key))) { + while (*name) { + int cmp = (**name == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**name, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + int cmp = (**argname == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**argname, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) goto arg_passed_twice; + argname++; + } + } + } else + goto invalid_keyword_type; + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, key); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%.200s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%.200s() got an unexpected keyword argument '%.200s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +/* ArgTypeTest */ +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) +{ + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + else if (exact) { + #if PY_MAJOR_VERSION == 2 + if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; + #endif + } + else { + if (likely(__Pyx_TypeCheck(obj, type))) return 1; + } + PyErr_Format(PyExc_TypeError, + "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); + return 0; +} + +/* GetModuleGlobalName */ +#if CYTHON_USE_DICT_VERSIONS +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) +#else +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) +#endif +{ + PyObject *result; +#if !CYTHON_AVOID_BORROWED_REFS +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 + result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } else if (unlikely(PyErr_Occurred())) { + return NULL; + } +#else + result = PyDict_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } +#endif +#else + result = PyObject_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } + PyErr_Clear(); +#endif + return __Pyx_GetBuiltinName(name); +} + +/* PyObjectCall2Args */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { + PyObject *args, *result = NULL; + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyFunction_FastCall(function, args, 2); + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyCFunction_FastCall(function, args, 2); + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(arg1); + PyTuple_SET_ITEM(args, 0, arg1); + Py_INCREF(arg2); + PyTuple_SET_ITEM(args, 1, arg2); + Py_INCREF(function); + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); +done: + return result; +} + +/* PyObjectCallMethO */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallOneArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, &arg, 1); + } +#endif + if (likely(PyCFunction_Check(func))) { + if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { + return __Pyx_PyObject_CallMethO(func, arg); +#if CYTHON_FAST_PYCCALL + } else if (__Pyx_PyFastCFunction_Check(func)) { + return __Pyx_PyCFunction_FastCall(func, &arg, 1); +#endif + } + } + return __Pyx__PyObject_CallOneArg(func, arg); +} +#else +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_Pack(1, arg); + if (unlikely(!args)) return NULL; + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +#endif + +/* PyObjectCallNoArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, NULL, 0); + } +#endif +#ifdef __Pyx_CyFunction_USED + if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) +#else + if (likely(PyCFunction_Check(func))) +#endif + { + if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { + return __Pyx_PyObject_CallMethO(func, NULL); + } + } + return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); +} +#endif + +/* PyObjectSetAttrStr */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value) { + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_setattro)) + return tp->tp_setattro(obj, attr_name, value); +#if PY_MAJOR_VERSION < 3 + if (likely(tp->tp_setattr)) + return tp->tp_setattr(obj, PyString_AS_STRING(attr_name), value); +#endif + return PyObject_SetAttr(obj, attr_name, value); +} +#endif + +/* PyErrFetchRestore */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} +#endif + +/* RaiseException */ +#if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + __Pyx_PyThreadState_declare + Py_XINCREF(type); + if (!value || value == Py_None) + value = NULL; + else + Py_INCREF(value); + if (!tb || tb == Py_None) + tb = NULL; + else { + Py_INCREF(tb); + if (!PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + } + if (PyType_Check(type)) { +#if CYTHON_COMPILING_IN_PYPY + if (!value) { + Py_INCREF(Py_None); + value = Py_None; + } +#endif + PyErr_NormalizeException(&type, &value, &tb); + } else { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + value = type; + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + } + __Pyx_PyThreadState_assign + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + PyObject* owned_instance = NULL; + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (PyExceptionClass_Check(type)) { + PyObject *instance_class = NULL; + if (value && PyExceptionInstance_Check(value)) { + instance_class = (PyObject*) Py_TYPE(value); + if (instance_class != type) { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { + instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; + } + } + } + if (!instance_class) { + PyObject *args; + if (!value) + args = PyTuple_New(0); + else if (PyTuple_Check(value)) { + Py_INCREF(value); + args = value; + } else + args = PyTuple_Pack(1, value); + if (!args) + goto bad; + owned_instance = PyObject_Call(type, args, NULL); + Py_DECREF(args); + if (!owned_instance) + goto bad; + value = owned_instance; + if (!PyExceptionInstance_Check(value)) { + PyErr_Format(PyExc_TypeError, + "calling %R should have returned an instance of " + "BaseException, not %R", + type, Py_TYPE(value)); + goto bad; + } + } + } else { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + if (cause == Py_None) { + fixed_cause = NULL; + } else if (PyExceptionClass_Check(cause)) { + fixed_cause = PyObject_CallObject(cause, NULL); + if (fixed_cause == NULL) + goto bad; + } else if (PyExceptionInstance_Check(cause)) { + fixed_cause = cause; + Py_INCREF(fixed_cause); + } else { + PyErr_SetString(PyExc_TypeError, + "exception causes must derive from " + "BaseException"); + goto bad; + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } +#endif + } +bad: + Py_XDECREF(owned_instance); + return; +} +#endif + +/* ExtTypeTest */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +/* PyErrExceptionMatches */ +#if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetAttr */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { +#if CYTHON_USE_TYPE_SLOTS +#if PY_MAJOR_VERSION >= 3 + if (likely(PyUnicode_Check(n))) +#else + if (likely(PyString_Check(n))) +#endif + return __Pyx_PyObject_GetAttrStr(o, n); +#endif + return PyObject_GetAttr(o, n); +} + +/* GetAttr3 */ +static PyObject *__Pyx_GetAttr3Default(PyObject *d) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + return NULL; + __Pyx_PyErr_Clear(); + Py_INCREF(d); + return d; +} +static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) { + PyObject *r = __Pyx_GetAttr(o, n); + return (likely(r)) ? r : __Pyx_GetAttr3Default(d); +} + +/* RaiseTooManyValuesToUnpack */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { + PyErr_Format(PyExc_ValueError, + "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); +} + +/* RaiseNeedMoreValuesToUnpack */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { + PyErr_Format(PyExc_ValueError, + "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", + index, (index == 1) ? "" : "s"); +} + +/* IterFinish */ +static CYTHON_INLINE int __Pyx_IterFinish(void) { +#if CYTHON_FAST_THREAD_STATE + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* exc_type = tstate->curexc_type; + if (unlikely(exc_type)) { + if (likely(__Pyx_PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) { + PyObject *exc_value, *exc_tb; + exc_value = tstate->curexc_value; + exc_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; + Py_DECREF(exc_type); + Py_XDECREF(exc_value); + Py_XDECREF(exc_tb); + return 0; + } else { + return -1; + } + } + return 0; +#else + if (unlikely(PyErr_Occurred())) { + if (likely(PyErr_ExceptionMatches(PyExc_StopIteration))) { + PyErr_Clear(); + return 0; + } else { + return -1; + } + } + return 0; +#endif +} + +/* UnpackItemEndCheck */ +static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) { + if (unlikely(retval)) { + Py_DECREF(retval); + __Pyx_RaiseTooManyValuesError(expected); + return -1; + } else { + return __Pyx_IterFinish(); + } + return 0; +} + +/* MemviewSliceInit */ +static int +__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference) +{ + __Pyx_RefNannyDeclarations + int i, retval=-1; + Py_buffer *buf = &memview->view; + __Pyx_RefNannySetupContext("init_memviewslice", 0); + if (unlikely(memviewslice->memview || memviewslice->data)) { + PyErr_SetString(PyExc_ValueError, + "memviewslice is already initialized!"); + goto fail; + } + if (buf->strides) { + for (i = 0; i < ndim; i++) { + memviewslice->strides[i] = buf->strides[i]; + } + } else { + Py_ssize_t stride = buf->itemsize; + for (i = ndim - 1; i >= 0; i--) { + memviewslice->strides[i] = stride; + stride *= buf->shape[i]; + } + } + for (i = 0; i < ndim; i++) { + memviewslice->shape[i] = buf->shape[i]; + if (buf->suboffsets) { + memviewslice->suboffsets[i] = buf->suboffsets[i]; + } else { + memviewslice->suboffsets[i] = -1; + } + } + memviewslice->memview = memview; + memviewslice->data = (char *)buf->buf; + if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { + Py_INCREF(memview); + } + retval = 0; + goto no_fail; +fail: + memviewslice->memview = 0; + memviewslice->data = 0; + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} +#ifndef Py_NO_RETURN +#define Py_NO_RETURN +#endif +static void __pyx_fatalerror(const char *fmt, ...) Py_NO_RETURN { + va_list vargs; + char msg[200]; +#ifdef HAVE_STDARG_PROTOTYPES + va_start(vargs, fmt); +#else + va_start(vargs); +#endif + vsnprintf(msg, 200, fmt, vargs); + va_end(vargs); + Py_FatalError(msg); +} +static CYTHON_INLINE int +__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)++; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE int +__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)--; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE void +__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) +{ + int first_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (unlikely(!memview || (PyObject *) memview == Py_None)) + return; + if (unlikely(__pyx_get_slice_count(memview) < 0)) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + first_time = __pyx_add_acquisition_count(memview) == 0; + if (unlikely(first_time)) { + if (have_gil) { + Py_INCREF((PyObject *) memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_INCREF((PyObject *) memview); + PyGILState_Release(_gilstate); + } + } +} +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, + int have_gil, int lineno) { + int last_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (unlikely(!memview || (PyObject *) memview == Py_None)) { + memslice->memview = NULL; + return; + } + if (unlikely(__pyx_get_slice_count(memview) <= 0)) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + last_time = __pyx_sub_acquisition_count(memview) == 1; + memslice->data = NULL; + if (unlikely(last_time)) { + if (have_gil) { + Py_CLEAR(memslice->memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_CLEAR(memslice->memview); + PyGILState_Release(_gilstate); + } + } else { + memslice->memview = NULL; + } +} + +/* GetItemInt */ +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { + PyObject *r; + if (!j) return NULL; + r = PyObject_GetItem(o, j); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyList_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { + PyObject *r = PyList_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyTuple_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); + if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { + PyObject *r = PyList_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } + else if (PyTuple_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + return NULL; + PyErr_Clear(); + } + } + return m->sq_item(o, i); + } + } +#else + if (is_list || PySequence_Check(o)) { + return PySequence_GetItem(o, i); + } +#endif + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +} + +/* ObjectGetItem */ +#if CYTHON_USE_TYPE_SLOTS +static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { + PyObject *runerr; + Py_ssize_t key_value; + PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; + if (unlikely(!(m && m->sq_item))) { + PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); + return NULL; + } + key_value = __Pyx_PyIndex_AsSsize_t(index); + if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { + return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); + } + if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { + PyErr_Clear(); + PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); + } + return NULL; +} +static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { + PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; + if (likely(m && m->mp_subscript)) { + return m->mp_subscript(obj, key); + } + return __Pyx_PyObject_GetIndex(obj, key); +} +#endif + +/* SliceObject */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice(PyObject* obj, + Py_ssize_t cstart, Py_ssize_t cstop, + PyObject** _py_start, PyObject** _py_stop, PyObject** _py_slice, + int has_cstart, int has_cstop, CYTHON_UNUSED int wraparound) { +#if CYTHON_USE_TYPE_SLOTS + PyMappingMethods* mp; +#if PY_MAJOR_VERSION < 3 + PySequenceMethods* ms = Py_TYPE(obj)->tp_as_sequence; + if (likely(ms && ms->sq_slice)) { + if (!has_cstart) { + if (_py_start && (*_py_start != Py_None)) { + cstart = __Pyx_PyIndex_AsSsize_t(*_py_start); + if ((cstart == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad; + } else + cstart = 0; + } + if (!has_cstop) { + if (_py_stop && (*_py_stop != Py_None)) { + cstop = __Pyx_PyIndex_AsSsize_t(*_py_stop); + if ((cstop == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad; + } else + cstop = PY_SSIZE_T_MAX; + } + if (wraparound && unlikely((cstart < 0) | (cstop < 0)) && likely(ms->sq_length)) { + Py_ssize_t l = ms->sq_length(obj); + if (likely(l >= 0)) { + if (cstop < 0) { + cstop += l; + if (cstop < 0) cstop = 0; + } + if (cstart < 0) { + cstart += l; + if (cstart < 0) cstart = 0; + } + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + goto bad; + PyErr_Clear(); + } + } + return ms->sq_slice(obj, cstart, cstop); + } +#endif + mp = Py_TYPE(obj)->tp_as_mapping; + if (likely(mp && mp->mp_subscript)) +#endif + { + PyObject* result; + PyObject *py_slice, *py_start, *py_stop; + if (_py_slice) { + py_slice = *_py_slice; + } else { + PyObject* owned_start = NULL; + PyObject* owned_stop = NULL; + if (_py_start) { + py_start = *_py_start; + } else { + if (has_cstart) { + owned_start = py_start = PyInt_FromSsize_t(cstart); + if (unlikely(!py_start)) goto bad; + } else + py_start = Py_None; + } + if (_py_stop) { + py_stop = *_py_stop; + } else { + if (has_cstop) { + owned_stop = py_stop = PyInt_FromSsize_t(cstop); + if (unlikely(!py_stop)) { + Py_XDECREF(owned_start); + goto bad; + } + } else + py_stop = Py_None; + } + py_slice = PySlice_New(py_start, py_stop, Py_None); + Py_XDECREF(owned_start); + Py_XDECREF(owned_stop); + if (unlikely(!py_slice)) goto bad; + } +#if CYTHON_USE_TYPE_SLOTS + result = mp->mp_subscript(obj, py_slice); +#else + result = PyObject_GetItem(obj, py_slice); +#endif + if (!_py_slice) { + Py_DECREF(py_slice); + } + return result; + } + PyErr_Format(PyExc_TypeError, + "'%.200s' object is unsliceable", Py_TYPE(obj)->tp_name); +bad: + return NULL; +} + +/* PyIntCompare */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_EqObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED long inplace) { + if (op1 == op2) { + Py_RETURN_TRUE; + } + #if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(op1))) { + const long b = intval; + long a = PyInt_AS_LONG(op1); + if (a == b) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } + #endif + #if CYTHON_USE_PYLONG_INTERNALS + if (likely(PyLong_CheckExact(op1))) { + int unequal; + unsigned long uintval; + Py_ssize_t size = Py_SIZE(op1); + const digit* digits = ((PyLongObject*)op1)->ob_digit; + if (intval == 0) { + if (size == 0) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } else if (intval < 0) { + if (size >= 0) + Py_RETURN_FALSE; + intval = -intval; + size = -size; + } else { + if (size <= 0) + Py_RETURN_FALSE; + } + uintval = (unsigned long) intval; +#if PyLong_SHIFT * 4 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 4)) { + unequal = (size != 5) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[4] != ((uintval >> (4 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif +#if PyLong_SHIFT * 3 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 3)) { + unequal = (size != 4) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif +#if PyLong_SHIFT * 2 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 2)) { + unequal = (size != 3) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif +#if PyLong_SHIFT * 1 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 1)) { + unequal = (size != 2) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif + unequal = (size != 1) || (((unsigned long) digits[0]) != (uintval & (unsigned long) PyLong_MASK)); + if (unequal == 0) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } + #endif + if (PyFloat_CheckExact(op1)) { + const long b = intval; + double a = PyFloat_AS_DOUBLE(op1); + if ((double)a == (double)b) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } + return ( + PyObject_RichCompare(op1, op2, Py_EQ)); +} + +/* DictGetItem */ +#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { + PyObject *value; + value = PyDict_GetItemWithError(d, key); + if (unlikely(!value)) { + if (!PyErr_Occurred()) { + if (unlikely(PyTuple_Check(key))) { + PyObject* args = PyTuple_Pack(1, key); + if (likely(args)) { + PyErr_SetObject(PyExc_KeyError, args); + Py_DECREF(args); + } + } else { + PyErr_SetObject(PyExc_KeyError, key); + } + } + return NULL; + } + Py_INCREF(value); + return value; +} +#endif + +/* PyIntCompare */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_NeObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED long inplace) { + if (op1 == op2) { + Py_RETURN_FALSE; + } + #if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(op1))) { + const long b = intval; + long a = PyInt_AS_LONG(op1); + if (a != b) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } + #endif + #if CYTHON_USE_PYLONG_INTERNALS + if (likely(PyLong_CheckExact(op1))) { + int unequal; + unsigned long uintval; + Py_ssize_t size = Py_SIZE(op1); + const digit* digits = ((PyLongObject*)op1)->ob_digit; + if (intval == 0) { + if (size != 0) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } else if (intval < 0) { + if (size >= 0) + Py_RETURN_TRUE; + intval = -intval; + size = -size; + } else { + if (size <= 0) + Py_RETURN_TRUE; + } + uintval = (unsigned long) intval; +#if PyLong_SHIFT * 4 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 4)) { + unequal = (size != 5) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[4] != ((uintval >> (4 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif +#if PyLong_SHIFT * 3 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 3)) { + unequal = (size != 4) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif +#if PyLong_SHIFT * 2 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 2)) { + unequal = (size != 3) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif +#if PyLong_SHIFT * 1 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 1)) { + unequal = (size != 2) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif + unequal = (size != 1) || (((unsigned long) digits[0]) != (uintval & (unsigned long) PyLong_MASK)); + if (unequal != 0) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } + #endif + if (PyFloat_CheckExact(op1)) { + const long b = intval; + double a = PyFloat_AS_DOUBLE(op1); + if ((double)a != (double)b) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } + return ( + PyObject_RichCompare(op1, op2, Py_NE)); +} + +/* BytesEquals */ +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else + if (s1 == s2) { + return (equals == Py_EQ); + } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { + const char *ps1, *ps2; + Py_ssize_t length = PyBytes_GET_SIZE(s1); + if (length != PyBytes_GET_SIZE(s2)) + return (equals == Py_NE); + ps1 = PyBytes_AS_STRING(s1); + ps2 = PyBytes_AS_STRING(s2); + if (ps1[0] != ps2[0]) { + return (equals == Py_NE); + } else if (length == 1) { + return (equals == Py_EQ); + } else { + int result; +#if CYTHON_USE_UNICODE_INTERNALS + Py_hash_t hash1, hash2; + hash1 = ((PyBytesObject*)s1)->ob_shash; + hash2 = ((PyBytesObject*)s2)->ob_shash; + if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { + return (equals == Py_NE); + } +#endif + result = memcmp(ps1, ps2, (size_t)length); + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { + return (equals == Py_NE); + } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { + return (equals == Py_NE); + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +#endif +} + +/* UnicodeEquals */ +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else +#if PY_MAJOR_VERSION < 3 + PyObject* owned_ref = NULL; +#endif + int s1_is_unicode, s2_is_unicode; + if (s1 == s2) { + goto return_eq; + } + s1_is_unicode = PyUnicode_CheckExact(s1); + s2_is_unicode = PyUnicode_CheckExact(s2); +#if PY_MAJOR_VERSION < 3 + if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { + owned_ref = PyUnicode_FromObject(s2); + if (unlikely(!owned_ref)) + return -1; + s2 = owned_ref; + s2_is_unicode = 1; + } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { + owned_ref = PyUnicode_FromObject(s1); + if (unlikely(!owned_ref)) + return -1; + s1 = owned_ref; + s1_is_unicode = 1; + } else if (((!s2_is_unicode) & (!s1_is_unicode))) { + return __Pyx_PyBytes_Equals(s1, s2, equals); + } +#endif + if (s1_is_unicode & s2_is_unicode) { + Py_ssize_t length; + int kind; + void *data1, *data2; + if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) + return -1; + length = __Pyx_PyUnicode_GET_LENGTH(s1); + if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { + goto return_ne; + } +#if CYTHON_USE_UNICODE_INTERNALS + { + Py_hash_t hash1, hash2; + #if CYTHON_PEP393_ENABLED + hash1 = ((PyASCIIObject*)s1)->hash; + hash2 = ((PyASCIIObject*)s2)->hash; + #else + hash1 = ((PyUnicodeObject*)s1)->hash; + hash2 = ((PyUnicodeObject*)s2)->hash; + #endif + if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { + goto return_ne; + } + } +#endif + kind = __Pyx_PyUnicode_KIND(s1); + if (kind != __Pyx_PyUnicode_KIND(s2)) { + goto return_ne; + } + data1 = __Pyx_PyUnicode_DATA(s1); + data2 = __Pyx_PyUnicode_DATA(s2); + if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { + goto return_ne; + } else if (length == 1) { + goto return_eq; + } else { + int result = memcmp(data1, data2, (size_t)(length * kind)); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & s2_is_unicode) { + goto return_ne; + } else if ((s2 == Py_None) & s1_is_unicode) { + goto return_ne; + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +return_eq: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ); +return_ne: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_NE); +#endif +} + +/* PyObjectGetMethod */ +static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method) { + PyObject *attr; +#if CYTHON_UNPACK_METHODS && CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_PYTYPE_LOOKUP + PyTypeObject *tp = Py_TYPE(obj); + PyObject *descr; + descrgetfunc f = NULL; + PyObject **dictptr, *dict; + int meth_found = 0; + assert (*method == NULL); + if (unlikely(tp->tp_getattro != PyObject_GenericGetAttr)) { + attr = __Pyx_PyObject_GetAttrStr(obj, name); + goto try_unpack; + } + if (unlikely(tp->tp_dict == NULL) && unlikely(PyType_Ready(tp) < 0)) { + return 0; + } + descr = _PyType_Lookup(tp, name); + if (likely(descr != NULL)) { + Py_INCREF(descr); +#if PY_MAJOR_VERSION >= 3 + #ifdef __Pyx_CyFunction_USED + if (likely(PyFunction_Check(descr) || (Py_TYPE(descr) == &PyMethodDescr_Type) || __Pyx_CyFunction_Check(descr))) + #else + if (likely(PyFunction_Check(descr) || (Py_TYPE(descr) == &PyMethodDescr_Type))) + #endif +#else + #ifdef __Pyx_CyFunction_USED + if (likely(PyFunction_Check(descr) || __Pyx_CyFunction_Check(descr))) + #else + if (likely(PyFunction_Check(descr))) + #endif +#endif + { + meth_found = 1; + } else { + f = Py_TYPE(descr)->tp_descr_get; + if (f != NULL && PyDescr_IsData(descr)) { + attr = f(descr, obj, (PyObject *)Py_TYPE(obj)); + Py_DECREF(descr); + goto try_unpack; + } + } + } + dictptr = _PyObject_GetDictPtr(obj); + if (dictptr != NULL && (dict = *dictptr) != NULL) { + Py_INCREF(dict); + attr = __Pyx_PyDict_GetItemStr(dict, name); + if (attr != NULL) { + Py_INCREF(attr); + Py_DECREF(dict); + Py_XDECREF(descr); + goto try_unpack; + } + Py_DECREF(dict); + } + if (meth_found) { + *method = descr; + return 1; + } + if (f != NULL) { + attr = f(descr, obj, (PyObject *)Py_TYPE(obj)); + Py_DECREF(descr); + goto try_unpack; + } + if (descr != NULL) { + *method = descr; + return 0; + } + PyErr_Format(PyExc_AttributeError, +#if PY_MAJOR_VERSION >= 3 + "'%.50s' object has no attribute '%U'", + tp->tp_name, name); +#else + "'%.50s' object has no attribute '%.400s'", + tp->tp_name, PyString_AS_STRING(name)); +#endif + return 0; +#else + attr = __Pyx_PyObject_GetAttrStr(obj, name); + goto try_unpack; +#endif +try_unpack: +#if CYTHON_UNPACK_METHODS + if (likely(attr) && PyMethod_Check(attr) && likely(PyMethod_GET_SELF(attr) == obj)) { + PyObject *function = PyMethod_GET_FUNCTION(attr); + Py_INCREF(function); + Py_DECREF(attr); + *method = function; + return 1; + } +#endif + *method = attr; + return 0; +} + +/* PyObjectCallMethod1 */ +static PyObject* __Pyx__PyObject_CallMethod1(PyObject* method, PyObject* arg) { + PyObject *result = __Pyx_PyObject_CallOneArg(method, arg); + Py_DECREF(method); + return result; +} +static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg) { + PyObject *method = NULL, *result; + int is_method = __Pyx_PyObject_GetMethod(obj, method_name, &method); + if (likely(is_method)) { + result = __Pyx_PyObject_Call2Args(method, obj, arg); + Py_DECREF(method); + return result; + } + if (unlikely(!method)) return NULL; + return __Pyx__PyObject_CallMethod1(method, arg); +} + +/* append */ +static CYTHON_INLINE int __Pyx_PyObject_Append(PyObject* L, PyObject* x) { + if (likely(PyList_CheckExact(L))) { + if (unlikely(__Pyx_PyList_Append(L, x) < 0)) return -1; + } else { + PyObject* retval = __Pyx_PyObject_CallMethod1(L, __pyx_n_s_append, x); + if (unlikely(!retval)) + return -1; + Py_DECREF(retval); + } + return 0; +} + +/* PyIntBinop */ +#if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, int inplace, int zerodivision_check) { + (void)inplace; + (void)zerodivision_check; + #if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(op1))) { + const long b = intval; + long x; + long a = PyInt_AS_LONG(op1); + x = (long)((unsigned long)a + b); + if (likely((x^a) >= 0 || (x^b) >= 0)) + return PyInt_FromLong(x); + return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + #endif + #if CYTHON_USE_PYLONG_INTERNALS + if (likely(PyLong_CheckExact(op1))) { + const long b = intval; + long a, x; +#ifdef HAVE_LONG_LONG + const PY_LONG_LONG llb = intval; + PY_LONG_LONG lla, llx; +#endif + const digit* digits = ((PyLongObject*)op1)->ob_digit; + const Py_ssize_t size = Py_SIZE(op1); + if (likely(__Pyx_sst_abs(size) <= 1)) { + a = likely(size) ? digits[0] : 0; + if (size == -1) a = -a; + } else { + switch (size) { + case -2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + default: return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + } + x = a + b; + return PyLong_FromLong(x); +#ifdef HAVE_LONG_LONG + long_long: + llx = lla + llb; + return PyLong_FromLongLong(llx); +#endif + + + } + #endif + if (PyFloat_CheckExact(op1)) { + const long b = intval; + double a = PyFloat_AS_DOUBLE(op1); + double result; + PyFPE_START_PROTECT("add", return NULL) + result = ((double)a) + (double)b; + PyFPE_END_PROTECT(result) + return PyFloat_FromDouble(result); + } + return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); +} +#endif + +/* SliceObject */ +static CYTHON_INLINE int __Pyx_PyObject_SetSlice(PyObject* obj, PyObject* value, + Py_ssize_t cstart, Py_ssize_t cstop, + PyObject** _py_start, PyObject** _py_stop, PyObject** _py_slice, + int has_cstart, int has_cstop, CYTHON_UNUSED int wraparound) { +#if CYTHON_USE_TYPE_SLOTS + PyMappingMethods* mp; +#if PY_MAJOR_VERSION < 3 + PySequenceMethods* ms = Py_TYPE(obj)->tp_as_sequence; + if (likely(ms && ms->sq_ass_slice)) { + if (!has_cstart) { + if (_py_start && (*_py_start != Py_None)) { + cstart = __Pyx_PyIndex_AsSsize_t(*_py_start); + if ((cstart == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad; + } else + cstart = 0; + } + if (!has_cstop) { + if (_py_stop && (*_py_stop != Py_None)) { + cstop = __Pyx_PyIndex_AsSsize_t(*_py_stop); + if ((cstop == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad; + } else + cstop = PY_SSIZE_T_MAX; + } + if (wraparound && unlikely((cstart < 0) | (cstop < 0)) && likely(ms->sq_length)) { + Py_ssize_t l = ms->sq_length(obj); + if (likely(l >= 0)) { + if (cstop < 0) { + cstop += l; + if (cstop < 0) cstop = 0; + } + if (cstart < 0) { + cstart += l; + if (cstart < 0) cstart = 0; + } + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + goto bad; + PyErr_Clear(); + } + } + return ms->sq_ass_slice(obj, cstart, cstop, value); + } +#endif + mp = Py_TYPE(obj)->tp_as_mapping; + if (likely(mp && mp->mp_ass_subscript)) +#endif + { + int result; + PyObject *py_slice, *py_start, *py_stop; + if (_py_slice) { + py_slice = *_py_slice; + } else { + PyObject* owned_start = NULL; + PyObject* owned_stop = NULL; + if (_py_start) { + py_start = *_py_start; + } else { + if (has_cstart) { + owned_start = py_start = PyInt_FromSsize_t(cstart); + if (unlikely(!py_start)) goto bad; + } else + py_start = Py_None; + } + if (_py_stop) { + py_stop = *_py_stop; + } else { + if (has_cstop) { + owned_stop = py_stop = PyInt_FromSsize_t(cstop); + if (unlikely(!py_stop)) { + Py_XDECREF(owned_start); + goto bad; + } + } else + py_stop = Py_None; + } + py_slice = PySlice_New(py_start, py_stop, Py_None); + Py_XDECREF(owned_start); + Py_XDECREF(owned_stop); + if (unlikely(!py_slice)) goto bad; + } +#if CYTHON_USE_TYPE_SLOTS + result = mp->mp_ass_subscript(obj, py_slice, value); +#else + result = value ? PyObject_SetItem(obj, py_slice, value) : PyObject_DelItem(obj, py_slice); +#endif + if (!_py_slice) { + Py_DECREF(py_slice); + } + return result; + } + PyErr_Format(PyExc_TypeError, + "'%.200s' object does not support slice %.10s", + Py_TYPE(obj)->tp_name, value ? "assignment" : "deletion"); +bad: + return -1; +} + +/* MatrixMultiply */ +#if PY_VERSION_HEX < 0x03050000 +static PyObject* __Pyx_PyObject_CallMatrixMethod(PyObject* method, PyObject* arg) { + PyObject *result = NULL; +#if CYTHON_UNPACK_METHODS + if (likely(PyMethod_Check(method))) { + PyObject *self = PyMethod_GET_SELF(method); + if (likely(self)) { + PyObject *args; + PyObject *function = PyMethod_GET_FUNCTION(method); + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {self, arg}; + result = __Pyx_PyFunction_FastCall(function, args, 2); + goto done; + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {self, arg}; + result = __Pyx_PyCFunction_FastCall(function, args, 2); + goto done; + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(self); + PyTuple_SET_ITEM(args, 0, self); + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 1, arg); + Py_INCREF(function); + Py_DECREF(method); method = NULL; + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); + return result; + } + } +#endif + result = __Pyx_PyObject_CallOneArg(method, arg); +done: + Py_DECREF(method); + return result; +} +#define __Pyx_TryMatrixMethod(x, y, py_method_name) {\ + PyObject *func = __Pyx_PyObject_GetAttrStr(x, py_method_name);\ + if (func) {\ + PyObject *result = __Pyx_PyObject_CallMatrixMethod(func, y);\ + if (result != Py_NotImplemented)\ + return result;\ + Py_DECREF(result);\ + } else {\ + if (!PyErr_ExceptionMatches(PyExc_AttributeError))\ + return NULL;\ + PyErr_Clear();\ + }\ +} +static PyObject* __Pyx__PyNumber_MatrixMultiply(PyObject* x, PyObject* y, const char* op_name) { + int right_is_subtype = PyObject_IsSubclass((PyObject*)Py_TYPE(y), (PyObject*)Py_TYPE(x)); + if (unlikely(right_is_subtype == -1)) + return NULL; + if (right_is_subtype) { + __Pyx_TryMatrixMethod(y, x, __pyx_n_s_rmatmul) + } + __Pyx_TryMatrixMethod(x, y, __pyx_n_s_matmul) + if (!right_is_subtype) { + __Pyx_TryMatrixMethod(y, x, __pyx_n_s_rmatmul) + } + PyErr_Format(PyExc_TypeError, + "unsupported operand type(s) for %.2s: '%.100s' and '%.100s'", + op_name, + Py_TYPE(x)->tp_name, + Py_TYPE(y)->tp_name); + return NULL; +} +static PyObject* __Pyx_PyNumber_InPlaceMatrixMultiply(PyObject* x, PyObject* y) { + __Pyx_TryMatrixMethod(x, y, __pyx_n_s_imatmul) + return __Pyx__PyNumber_MatrixMultiply(x, y, "@="); +} +#undef __Pyx_TryMatrixMethod +#endif + +/* IsLittleEndian */ +static CYTHON_INLINE int __Pyx_Is_Little_Endian(void) +{ + union { + uint32_t u32; + uint8_t u8[4]; + } S; + S.u32 = 0x01020304; + return S.u8[0] == 4; +} + +/* BufferFormatCheck */ +static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type) { + stack[0].field = &ctx->root; + stack[0].parent_offset = 0; + ctx->root.type = type; + ctx->root.name = "buffer dtype"; + ctx->root.offset = 0; + ctx->head = stack; + ctx->head->field = &ctx->root; + ctx->fmt_offset = 0; + ctx->head->parent_offset = 0; + ctx->new_packmode = '@'; + ctx->enc_packmode = '@'; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->is_complex = 0; + ctx->is_valid_array = 0; + ctx->struct_alignment = 0; + while (type->typegroup == 'S') { + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = 0; + type = type->fields->type; + } +} +static int __Pyx_BufFmt_ParseNumber(const char** ts) { + int count; + const char* t = *ts; + if (*t < '0' || *t > '9') { + return -1; + } else { + count = *t++ - '0'; + while (*t >= '0' && *t <= '9') { + count *= 10; + count += *t++ - '0'; + } + } + *ts = t; + return count; +} +static int __Pyx_BufFmt_ExpectNumber(const char **ts) { + int number = __Pyx_BufFmt_ParseNumber(ts); + if (number == -1) + PyErr_Format(PyExc_ValueError,\ + "Does not understand character buffer dtype format string ('%c')", **ts); + return number; +} +static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { + PyErr_Format(PyExc_ValueError, + "Unexpected format string character: '%c'", ch); +} +static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { + switch (ch) { + case '?': return "'bool'"; + case 'c': return "'char'"; + case 'b': return "'signed char'"; + case 'B': return "'unsigned char'"; + case 'h': return "'short'"; + case 'H': return "'unsigned short'"; + case 'i': return "'int'"; + case 'I': return "'unsigned int'"; + case 'l': return "'long'"; + case 'L': return "'unsigned long'"; + case 'q': return "'long long'"; + case 'Q': return "'unsigned long long'"; + case 'f': return (is_complex ? "'complex float'" : "'float'"); + case 'd': return (is_complex ? "'complex double'" : "'double'"); + case 'g': return (is_complex ? "'complex long double'" : "'long double'"); + case 'T': return "a struct"; + case 'O': return "Python object"; + case 'P': return "a pointer"; + case 's': case 'p': return "a string"; + case 0: return "end"; + default: return "unparseable format string"; + } +} +static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return 2; + case 'i': case 'I': case 'l': case 'L': return 4; + case 'q': case 'Q': return 8; + case 'f': return (is_complex ? 8 : 4); + case 'd': return (is_complex ? 16 : 8); + case 'g': { + PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); + return 0; + } + case 'O': case 'P': return sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(short); + case 'i': case 'I': return sizeof(int); + case 'l': case 'L': return sizeof(long); + #ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(PY_LONG_LONG); + #endif + case 'f': return sizeof(float) * (is_complex ? 2 : 1); + case 'd': return sizeof(double) * (is_complex ? 2 : 1); + case 'g': return sizeof(long double) * (is_complex ? 2 : 1); + case 'O': case 'P': return sizeof(void*); + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +typedef struct { char c; short x; } __Pyx_st_short; +typedef struct { char c; int x; } __Pyx_st_int; +typedef struct { char c; long x; } __Pyx_st_long; +typedef struct { char c; float x; } __Pyx_st_float; +typedef struct { char c; double x; } __Pyx_st_double; +typedef struct { char c; long double x; } __Pyx_st_longdouble; +typedef struct { char c; void *x; } __Pyx_st_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_st_float) - sizeof(float); + case 'd': return sizeof(__Pyx_st_double) - sizeof(double); + case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +/* These are for computing the padding at the end of the struct to align + on the first member of the struct. This will probably the same as above, + but we don't have any guarantees. + */ +typedef struct { short x; char c; } __Pyx_pad_short; +typedef struct { int x; char c; } __Pyx_pad_int; +typedef struct { long x; char c; } __Pyx_pad_long; +typedef struct { float x; char c; } __Pyx_pad_float; +typedef struct { double x; char c; } __Pyx_pad_double; +typedef struct { long double x; char c; } __Pyx_pad_longdouble; +typedef struct { void *x; char c; } __Pyx_pad_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); + case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); + case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { + switch (ch) { + case 'c': + return 'H'; + case 'b': case 'h': case 'i': + case 'l': case 'q': case 's': case 'p': + return 'I'; + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': + return 'U'; + case 'f': case 'd': case 'g': + return (is_complex ? 'C' : 'R'); + case 'O': + return 'O'; + case 'P': + return 'P'; + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { + if (ctx->head == NULL || ctx->head->field == &ctx->root) { + const char* expected; + const char* quote; + if (ctx->head == NULL) { + expected = "end"; + quote = ""; + } else { + expected = ctx->head->field->type->name; + quote = "'"; + } + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected %s%s%s but got %s", + quote, expected, quote, + __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); + } else { + __Pyx_StructField* field = ctx->head->field; + __Pyx_StructField* parent = (ctx->head - 1)->field; + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", + field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), + parent->type->name, field->name); + } +} +static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { + char group; + size_t size, offset, arraysize = 1; + if (ctx->enc_type == 0) return 0; + if (ctx->head->field->type->arraysize[0]) { + int i, ndim = 0; + if (ctx->enc_type == 's' || ctx->enc_type == 'p') { + ctx->is_valid_array = ctx->head->field->type->ndim == 1; + ndim = 1; + if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { + PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %zu", + ctx->head->field->type->arraysize[0], ctx->enc_count); + return -1; + } + } + if (!ctx->is_valid_array) { + PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", + ctx->head->field->type->ndim, ndim); + return -1; + } + for (i = 0; i < ctx->head->field->type->ndim; i++) { + arraysize *= ctx->head->field->type->arraysize[i]; + } + ctx->is_valid_array = 0; + ctx->enc_count = 1; + } + group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); + do { + __Pyx_StructField* field = ctx->head->field; + __Pyx_TypeInfo* type = field->type; + if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { + size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); + } else { + size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); + } + if (ctx->enc_packmode == '@') { + size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); + size_t align_mod_offset; + if (align_at == 0) return -1; + align_mod_offset = ctx->fmt_offset % align_at; + if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; + if (ctx->struct_alignment == 0) + ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, + ctx->is_complex); + } + if (type->size != size || type->typegroup != group) { + if (type->typegroup == 'C' && type->fields != NULL) { + size_t parent_offset = ctx->head->parent_offset + field->offset; + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = parent_offset; + continue; + } + if ((type->typegroup == 'H' || group == 'H') && type->size == size) { + } else { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + } + offset = ctx->head->parent_offset + field->offset; + if (ctx->fmt_offset != offset) { + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", + (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); + return -1; + } + ctx->fmt_offset += size; + if (arraysize) + ctx->fmt_offset += (arraysize - 1) * size; + --ctx->enc_count; + while (1) { + if (field == &ctx->root) { + ctx->head = NULL; + if (ctx->enc_count != 0) { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + break; + } + ctx->head->field = ++field; + if (field->type == NULL) { + --ctx->head; + field = ctx->head->field; + continue; + } else if (field->type->typegroup == 'S') { + size_t parent_offset = ctx->head->parent_offset + field->offset; + if (field->type->fields->type == NULL) continue; + field = field->type->fields; + ++ctx->head; + ctx->head->field = field; + ctx->head->parent_offset = parent_offset; + break; + } else { + break; + } + } + } while (ctx->enc_count); + ctx->enc_type = 0; + ctx->is_complex = 0; + return 0; +} +static PyObject * +__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) +{ + const char *ts = *tsp; + int i = 0, number, ndim; + ++ts; + if (ctx->new_count != 1) { + PyErr_SetString(PyExc_ValueError, + "Cannot handle repeated arrays in format string"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; + while (*ts && *ts != ')') { + switch (*ts) { + case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; + default: break; + } + number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) + return PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %d", + ctx->head->field->type->arraysize[i], number); + if (*ts != ',' && *ts != ')') + return PyErr_Format(PyExc_ValueError, + "Expected a comma in format string, got '%c'", *ts); + if (*ts == ',') ts++; + i++; + } + if (i != ndim) + return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", + ctx->head->field->type->ndim, i); + if (!*ts) { + PyErr_SetString(PyExc_ValueError, + "Unexpected end of format string, expected ')'"); + return NULL; + } + ctx->is_valid_array = 1; + ctx->new_count = 1; + *tsp = ++ts; + return Py_None; +} +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { + int got_Z = 0; + while (1) { + switch(*ts) { + case 0: + if (ctx->enc_type != 0 && ctx->head == NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + if (ctx->head != NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + return ts; + case ' ': + case '\r': + case '\n': + ++ts; + break; + case '<': + if (!__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '>': + case '!': + if (__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '=': + case '@': + case '^': + ctx->new_packmode = *ts++; + break; + case 'T': + { + const char* ts_after_sub; + size_t i, struct_count = ctx->new_count; + size_t struct_alignment = ctx->struct_alignment; + ctx->new_count = 1; + ++ts; + if (*ts != '{') { + PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + ctx->enc_count = 0; + ctx->struct_alignment = 0; + ++ts; + ts_after_sub = ts; + for (i = 0; i != struct_count; ++i) { + ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); + if (!ts_after_sub) return NULL; + } + ts = ts_after_sub; + if (struct_alignment) ctx->struct_alignment = struct_alignment; + } + break; + case '}': + { + size_t alignment = ctx->struct_alignment; + ++ts; + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + if (alignment && ctx->fmt_offset % alignment) { + ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); + } + } + return ts; + case 'x': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->fmt_offset += ctx->new_count; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->enc_packmode = ctx->new_packmode; + ++ts; + break; + case 'Z': + got_Z = 1; + ++ts; + if (*ts != 'f' && *ts != 'd' && *ts != 'g') { + __Pyx_BufFmt_RaiseUnexpectedChar('Z'); + return NULL; + } + CYTHON_FALLTHROUGH; + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case 'l': case 'L': case 'q': case 'Q': + case 'f': case 'd': case 'g': + case 'O': case 'p': + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { + ctx->enc_count += ctx->new_count; + ctx->new_count = 1; + got_Z = 0; + ++ts; + break; + } + CYTHON_FALLTHROUGH; + case 's': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_count = ctx->new_count; + ctx->enc_packmode = ctx->new_packmode; + ctx->enc_type = *ts; + ctx->is_complex = got_Z; + ++ts; + ctx->new_count = 1; + got_Z = 0; + break; + case ':': + ++ts; + while(*ts != ':') ++ts; + ++ts; + break; + case '(': + if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; + break; + default: + { + int number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + ctx->new_count = (size_t)number; + } + } + } +} + +/* BufferGetAndValidate */ + static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { + if (unlikely(info->buf == NULL)) return; + if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; + __Pyx_ReleaseBuffer(info); +} +static void __Pyx_ZeroBuffer(Py_buffer* buf) { + buf->buf = NULL; + buf->obj = NULL; + buf->strides = __Pyx_zeros; + buf->shape = __Pyx_zeros; + buf->suboffsets = __Pyx_minusones; +} +static int __Pyx__GetBufferAndValidate( + Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, + int nd, int cast, __Pyx_BufFmt_StackElem* stack) +{ + buf->buf = NULL; + if (unlikely(__Pyx_GetBuffer(obj, buf, flags) == -1)) { + __Pyx_ZeroBuffer(buf); + return -1; + } + if (unlikely(buf->ndim != nd)) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + nd, buf->ndim); + goto fail; + } + if (!cast) { + __Pyx_BufFmt_Context ctx; + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + } + if (unlikely((size_t)buf->itemsize != dtype->size)) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", + buf->itemsize, (buf->itemsize > 1) ? "s" : "", + dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); + goto fail; + } + if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; + return 0; +fail:; + __Pyx_SafeReleaseBuffer(buf); + return -1; +} + +/* BufferFallbackError */ + static void __Pyx_RaiseBufferFallbackError(void) { + PyErr_SetString(PyExc_ValueError, + "Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!"); +} + +/* WriteUnraisableException */ + static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, + CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, + int full_traceback, CYTHON_UNUSED int nogil) { + PyObject *old_exc, *old_val, *old_tb; + PyObject *ctx; + __Pyx_PyThreadState_declare +#ifdef WITH_THREAD + PyGILState_STATE state; + if (nogil) + state = PyGILState_Ensure(); +#ifdef _MSC_VER + else state = (PyGILState_STATE)-1; +#endif +#endif + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); + if (full_traceback) { + Py_XINCREF(old_exc); + Py_XINCREF(old_val); + Py_XINCREF(old_tb); + __Pyx_ErrRestore(old_exc, old_val, old_tb); + PyErr_PrintEx(1); + } + #if PY_MAJOR_VERSION < 3 + ctx = PyString_FromString(name); + #else + ctx = PyUnicode_FromString(name); + #endif + __Pyx_ErrRestore(old_exc, old_val, old_tb); + if (!ctx) { + PyErr_WriteUnraisable(Py_None); + } else { + PyErr_WriteUnraisable(ctx); + Py_DECREF(ctx); + } +#ifdef WITH_THREAD + if (nogil) + PyGILState_Release(state); +#endif +} + +/* SetItemInt */ + static int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v) { + int r; + if (!j) return -1; + r = PyObject_SetItem(o, j, v); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, int is_list, + CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = (!wraparound) ? i : ((likely(i >= 0)) ? i : i + PyList_GET_SIZE(o)); + if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o)))) { + PyObject* old = PyList_GET_ITEM(o, n); + Py_INCREF(v); + PyList_SET_ITEM(o, n, v); + Py_DECREF(old); + return 1; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_ass_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + return -1; + PyErr_Clear(); + } + } + return m->sq_ass_item(o, i, v); + } + } +#else +#if CYTHON_COMPILING_IN_PYPY + if (is_list || (PySequence_Check(o) && !PyDict_Check(o))) +#else + if (is_list || PySequence_Check(o)) +#endif + { + return PySequence_SetItem(o, i, v); + } +#endif + return __Pyx_SetItemInt_Generic(o, PyInt_FromSsize_t(i), v); +} + +/* Import */ + static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_MAJOR_VERSION < 3 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_MAJOR_VERSION < 3 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + +/* ImportFrom */ + static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { + PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); + if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Format(PyExc_ImportError, + #if PY_MAJOR_VERSION < 3 + "cannot import name %.230s", PyString_AS_STRING(name)); + #else + "cannot import name %S", name); + #endif + } + return value; +} + +/* HasAttr */ + static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) { + PyObject *r; + if (unlikely(!__Pyx_PyBaseString_Check(n))) { + PyErr_SetString(PyExc_TypeError, + "hasattr(): attribute name must be string"); + return -1; + } + r = __Pyx_GetAttr(o, n); + if (unlikely(!r)) { + PyErr_Clear(); + return 0; + } else { + Py_DECREF(r); + return 1; + } +} + +/* GetTopmostException */ + #if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* GetException */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +/* decode_c_string */ + static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { + Py_ssize_t length; + if (unlikely((start < 0) | (stop < 0))) { + size_t slen = strlen(cstring); + if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { + PyErr_SetString(PyExc_OverflowError, + "c-string too long to convert to Python"); + return NULL; + } + length = (Py_ssize_t) slen; + if (start < 0) { + start += length; + if (start < 0) + start = 0; + } + if (stop < 0) + stop += length; + } + if (unlikely(stop <= start)) + return __Pyx_NewRef(__pyx_empty_unicode); + length = stop - start; + cstring += start; + if (decode_func) { + return decode_func(cstring, length, errors); + } else { + return PyUnicode_Decode(cstring, length, encoding, errors); + } +} + +/* RaiseNoneIterError */ + static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); +} + +/* SwapException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = *type; + exc_info->exc_value = *value; + exc_info->exc_traceback = *tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = *type; + tstate->exc_value = *value; + tstate->exc_traceback = *tb; + #endif + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} +#else +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); + PyErr_SetExcInfo(*type, *value, *tb); + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} +#endif + +/* FastTypeChecks */ + #if CYTHON_COMPILING_IN_CPYTHON +static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { + while (a) { + a = a->tp_base; + if (a == b) + return 1; + } + return b == &PyBaseObject_Type; +} +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { + PyObject *mro; + if (a == b) return 1; + mro = a->tp_mro; + if (likely(mro)) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(mro); + for (i = 0; i < n; i++) { + if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) + return 1; + } + return 0; + } + return __Pyx_InBases(a, b); +} +#if PY_MAJOR_VERSION == 2 +static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { + PyObject *exception, *value, *tb; + int res; + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&exception, &value, &tb); + res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + if (!res) { + res = PyObject_IsSubclass(err, exc_type2); + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + } + __Pyx_ErrRestore(exception, value, tb); + return res; +} +#else +static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { + int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; + if (!res) { + res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); + } + return res; +} +#endif +static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + assert(PyExceptionClass_Check(exc_type)); + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; i= 3 + "'%.50s' object has no attribute '%U'", + tp->tp_name, attr_name); +#else + "'%.50s' object has no attribute '%.400s'", + tp->tp_name, PyString_AS_STRING(attr_name)); +#endif + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) { + PyObject *descr; + PyTypeObject *tp = Py_TYPE(obj); + if (unlikely(!PyString_Check(attr_name))) { + return PyObject_GenericGetAttr(obj, attr_name); + } + assert(!tp->tp_dictoffset); + descr = _PyType_Lookup(tp, attr_name); + if (unlikely(!descr)) { + return __Pyx_RaiseGenericGetAttributeError(tp, attr_name); + } + Py_INCREF(descr); + #if PY_MAJOR_VERSION < 3 + if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS))) + #endif + { + descrgetfunc f = Py_TYPE(descr)->tp_descr_get; + if (unlikely(f)) { + PyObject *res = f(descr, obj, (PyObject *)tp); + Py_DECREF(descr); + return res; + } + } + return descr; +} +#endif + +/* PyObject_GenericGetAttr */ + #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) { + if (unlikely(Py_TYPE(obj)->tp_dictoffset)) { + return PyObject_GenericGetAttr(obj, attr_name); + } + return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name); +} +#endif + +/* SetVTable */ + static int __Pyx_SetVtable(PyObject *dict, void *vtable) { +#if PY_VERSION_HEX >= 0x02070000 + PyObject *ob = PyCapsule_New(vtable, 0, 0); +#else + PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); +#endif + if (!ob) + goto bad; + if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) + goto bad; + Py_DECREF(ob); + return 0; +bad: + Py_XDECREF(ob); + return -1; +} + +/* PyObjectGetAttrStrNoError */ + static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + __Pyx_PyErr_Clear(); +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { + PyObject *result; +#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { + return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); + } +#endif + result = __Pyx_PyObject_GetAttrStr(obj, attr_name); + if (unlikely(!result)) { + __Pyx_PyObject_GetAttrStr_ClearAttributeError(); + } + return result; +} + +/* SetupReduce */ + static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { + int ret; + PyObject *name_attr; + name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2); + if (likely(name_attr)) { + ret = PyObject_RichCompareBool(name_attr, name, Py_EQ); + } else { + ret = -1; + } + if (unlikely(ret < 0)) { + PyErr_Clear(); + ret = 0; + } + Py_XDECREF(name_attr); + return ret; +} +static int __Pyx_setup_reduce(PyObject* type_obj) { + int ret = 0; + PyObject *object_reduce = NULL; + PyObject *object_reduce_ex = NULL; + PyObject *reduce = NULL; + PyObject *reduce_ex = NULL; + PyObject *reduce_cython = NULL; + PyObject *setstate = NULL; + PyObject *setstate_cython = NULL; +#if CYTHON_USE_PYTYPE_LOOKUP + if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#else + if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#endif +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#else + object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#endif + reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; + if (reduce_ex == object_reduce_ex) { +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#else + object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#endif + reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; + if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { + reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); + if (likely(reduce_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (reduce == object_reduce || PyErr_Occurred()) { + goto __PYX_BAD; + } + setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); + if (!setstate) PyErr_Clear(); + if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { + setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); + if (likely(setstate_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (!setstate || PyErr_Occurred()) { + goto __PYX_BAD; + } + } + PyType_Modified((PyTypeObject*)type_obj); + } + } + goto __PYX_GOOD; +__PYX_BAD: + if (!PyErr_Occurred()) + PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); + ret = -1; +__PYX_GOOD: +#if !CYTHON_USE_PYTYPE_LOOKUP + Py_XDECREF(object_reduce); + Py_XDECREF(object_reduce_ex); +#endif + Py_XDECREF(reduce); + Py_XDECREF(reduce_ex); + Py_XDECREF(reduce_cython); + Py_XDECREF(setstate); + Py_XDECREF(setstate_cython); + return ret; +} + +/* TypeImport */ + #ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, + size_t size, enum __Pyx_ImportType_CheckSize check_size) +{ + PyObject *result = 0; + char warning[200]; + Py_ssize_t basicsize; +#ifdef Py_LIMITED_API + PyObject *py_basicsize; +#endif + result = PyObject_GetAttrString(module, class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%.200s.%.200s is not a type object", + module_name, class_name); + goto bad; + } +#ifndef Py_LIMITED_API + basicsize = ((PyTypeObject *)result)->tp_basicsize; +#else + py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); + if (!py_basicsize) + goto bad; + basicsize = PyLong_AsSsize_t(py_basicsize); + Py_DECREF(py_basicsize); + py_basicsize = 0; + if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) + goto bad; +#endif + if ((size_t)basicsize < size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(result); + return NULL; +} +#endif + +/* GetVTable */ + static void* __Pyx_GetVtable(PyObject *dict) { + void* ptr; + PyObject *ob = PyObject_GetItem(dict, __pyx_n_s_pyx_vtable); + if (!ob) + goto bad; +#if PY_VERSION_HEX >= 0x02070000 + ptr = PyCapsule_GetPointer(ob, 0); +#else + ptr = PyCObject_AsVoidPtr(ob); +#endif + if (!ptr && !PyErr_Occurred()) + PyErr_SetString(PyExc_RuntimeError, "invalid vtable found for imported type"); + Py_DECREF(ob); + return ptr; +bad: + Py_XDECREF(ob); + return NULL; +} + +/* CLineInTraceback */ + #ifndef CYTHON_CLINE_IN_TRACEBACK +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { + PyObject *use_cline; + PyObject *ptype, *pvalue, *ptraceback; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject **cython_runtime_dict; +#endif + if (unlikely(!__pyx_cython_runtime)) { + return c_line; + } + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); +#if CYTHON_COMPILING_IN_CPYTHON + cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); + if (likely(cython_runtime_dict)) { + __PYX_PY_DICT_LOOKUP_IF_MODIFIED( + use_cline, *cython_runtime_dict, + __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) + } else +#endif + { + PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); + if (use_cline_obj) { + use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; + Py_DECREF(use_cline_obj); + } else { + PyErr_Clear(); + use_cline = NULL; + } + } + if (!use_cline) { + c_line = 0; + PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); + } + else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { + c_line = 0; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + return c_line; +} +#endif + +/* CodeObjectCache */ + static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = start + (end - start) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +/* AddTraceback */ + #include "compile.h" +#include "frameobject.h" +#include "traceback.h" +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyObject *py_srcfile = 0; + PyObject *py_funcname = 0; + #if PY_MAJOR_VERSION < 3 + py_srcfile = PyString_FromString(filename); + #else + py_srcfile = PyUnicode_FromString(filename); + #endif + if (!py_srcfile) goto bad; + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + #else + py_funcname = PyUnicode_FromString(funcname); + #endif + } + if (!py_funcname) goto bad; + py_code = __Pyx_PyCode_New( + 0, + 0, + 0, + 0, + 0, + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + Py_DECREF(py_funcname); + return py_code; +bad: + Py_XDECREF(py_srcfile); + Py_XDECREF(py_funcname); + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + if (c_line) { + c_line = __Pyx_CLineForTraceback(tstate, c_line); + } + py_code = __pyx_find_code_object(c_line ? -c_line : py_line); + if (!py_code) { + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) goto bad; + __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); + } + py_frame = PyFrame_New( + tstate, /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + __pyx_d, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + __Pyx_PyFrame_SetLineNumber(py_frame, py_line); + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { + if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); + if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); + if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); + PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); + return -1; +} +static void __Pyx_ReleaseBuffer(Py_buffer *view) { + PyObject *obj = view->obj; + if (!obj) return; + if (PyObject_CheckBuffer(obj)) { + PyBuffer_Release(view); + return; + } + if ((0)) {} + view->obj = NULL; + Py_DECREF(obj); +} +#endif + + + /* MemviewSliceIsContig */ + static int +__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) +{ + int i, index, step, start; + Py_ssize_t itemsize = mvs.memview->view.itemsize; + if (order == 'F') { + step = 1; + start = 0; + } else { + step = -1; + start = ndim - 1; + } + for (i = 0; i < ndim; i++) { + index = start + step * i; + if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) + return 0; + itemsize *= mvs.shape[index]; + } + return 1; +} + +/* OverlappingSlices */ + static void +__pyx_get_array_memory_extents(__Pyx_memviewslice *slice, + void **out_start, void **out_end, + int ndim, size_t itemsize) +{ + char *start, *end; + int i; + start = end = slice->data; + for (i = 0; i < ndim; i++) { + Py_ssize_t stride = slice->strides[i]; + Py_ssize_t extent = slice->shape[i]; + if (extent == 0) { + *out_start = *out_end = start; + return; + } else { + if (stride > 0) + end += stride * (extent - 1); + else + start += stride * (extent - 1); + } + } + *out_start = start; + *out_end = end + itemsize; +} +static int +__pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize) +{ + void *start1, *end1, *start2, *end2; + __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); + __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); + return (start1 < end2) && (start2 < end1); +} + +/* Capsule */ + static CYTHON_INLINE PyObject * +__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) +{ + PyObject *cobj; +#if PY_VERSION_HEX >= 0x02070000 + cobj = PyCapsule_New(p, sig, NULL); +#else + cobj = PyCObject_FromVoidPtr(p, NULL); +#endif + return cobj; +} + +/* CIntFromPyVerify */ + #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ + } + +static PyObject* __pyx_convert__to_py_struct____pyx_t_5_tree_Node(struct __pyx_t_5_tree_Node s) { + PyObject* res; + PyObject* member; + res = __Pyx_PyDict_NewPresized(7); if (unlikely(!res)) return NULL; + member = __Pyx_PyInt_From_Py_intptr_t(s.left_child); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_left_child, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_PyInt_From_Py_intptr_t(s.right_child); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_right_child, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_PyInt_From_Py_intptr_t(s.feature); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_feature, member) < 0)) goto bad; + Py_DECREF(member); + member = PyFloat_FromDouble(s.threshold); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_threshold, member) < 0)) goto bad; + Py_DECREF(member); + member = PyFloat_FromDouble(s.impurity); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_impurity, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_PyInt_From_Py_intptr_t(s.n_node_samples); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_n_node_samples, member) < 0)) goto bad; + Py_DECREF(member); + member = PyFloat_FromDouble(s.weighted_n_node_samples); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_weighted_n_node_samples, member) < 0)) goto bad; + Py_DECREF(member); + return res; + bad: + Py_XDECREF(member); + Py_DECREF(res); + return NULL; + } + /* MemviewDtypeToObject */ + static CYTHON_INLINE PyObject *__pyx_memview_get_nn_struct____pyx_t_5_tree_Node(const char *itemp) { + return (PyObject *) __pyx_convert__to_py_struct____pyx_t_5_tree_Node(*(struct __pyx_t_5_tree_Node *) itemp); +} +static CYTHON_INLINE int __pyx_memview_set_nn_struct____pyx_t_5_tree_Node(const char *itemp, PyObject *obj) { + struct __pyx_t_5_tree_Node value = __pyx_convert__from_py_struct____pyx_t_5_tree_Node(obj); + if (PyErr_Occurred()) + return 0; + *(struct __pyx_t_5_tree_Node *) itemp = value; + return 1; +} + +/* None */ + static CYTHON_INLINE long __Pyx_pow_long(long b, long e) { + long t = b; + switch (e) { + case 3: + t *= b; + CYTHON_FALLTHROUGH; + case 2: + t *= b; + CYTHON_FALLTHROUGH; + case 1: + return t; + case 0: + return 1; + } + #if 1 + if (unlikely(e<0)) return 0; + #endif + t = 1; + while (likely(e)) { + t *= (b * (e&1)) | ((~e)&1); + b *= b; + e >>= 1; + } + return t; +} + +/* None */ + static CYTHON_INLINE int __Pyx_ErrOccurredWithGIL(void) { + int err; + #ifdef WITH_THREAD + PyGILState_STATE _save = PyGILState_Ensure(); + #endif + err = !!PyErr_Occurred(); + #ifdef WITH_THREAD + PyGILState_Release(_save); + #endif + return err; +} + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabsf(b.real) >= fabsf(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + float r = b.imag / b.real; + float s = (float)(1.0) / (b.real + b.imag * r); + return __pyx_t_float_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + float r = b.real / b.imag; + float s = (float)(1.0) / (b.imag + b.real * r); + return __pyx_t_float_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + float denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_float_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_float(a, a); + case 3: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, a); + case 4: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = powf(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2f(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_float(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabs(b.real) >= fabs(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + double r = b.imag / b.real; + double s = (double)(1.0) / (b.real + b.imag * r); + return __pyx_t_double_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + double r = b.real / b.imag; + double s = (double)(1.0) / (b.imag + b.real * r); + return __pyx_t_double_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + double denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_double_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_double(a, a); + case 3: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, a); + case 4: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = pow(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_double(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +/* MemviewSliceCopyTemplate */ + static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object) +{ + __Pyx_RefNannyDeclarations + int i; + __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; + struct __pyx_memoryview_obj *from_memview = from_mvs->memview; + Py_buffer *buf = &from_memview->view; + PyObject *shape_tuple = NULL; + PyObject *temp_int = NULL; + struct __pyx_array_obj *array_obj = NULL; + struct __pyx_memoryview_obj *memview_obj = NULL; + __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); + for (i = 0; i < ndim; i++) { + if (unlikely(from_mvs->suboffsets[i] >= 0)) { + PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " + "indirect dimensions (axis %d)", i); + goto fail; + } + } + shape_tuple = PyTuple_New(ndim); + if (unlikely(!shape_tuple)) { + goto fail; + } + __Pyx_GOTREF(shape_tuple); + for(i = 0; i < ndim; i++) { + temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); + if(unlikely(!temp_int)) { + goto fail; + } else { + PyTuple_SET_ITEM(shape_tuple, i, temp_int); + temp_int = NULL; + } + } + array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); + if (unlikely(!array_obj)) { + goto fail; + } + __Pyx_GOTREF(array_obj); + memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + (PyObject *) array_obj, contig_flag, + dtype_is_object, + from_mvs->memview->typeinfo); + if (unlikely(!memview_obj)) + goto fail; + if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) + goto fail; + if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, + dtype_is_object) < 0)) + goto fail; + goto no_fail; +fail: + __Pyx_XDECREF(new_mvs.memview); + new_mvs.memview = NULL; + new_mvs.data = NULL; +no_fail: + __Pyx_XDECREF(shape_tuple); + __Pyx_XDECREF(temp_int); + __Pyx_XDECREF(array_obj); + __Pyx_RefNannyFinishContext(); + return new_mvs; +} + +/* TypeInfoToFormat */ + static struct __pyx_typeinfo_string __Pyx_TypeInfoToFormat(__Pyx_TypeInfo *type) { + struct __pyx_typeinfo_string result = { {0} }; + char *buf = (char *) result.string; + size_t size = type->size; + switch (type->typegroup) { + case 'H': + *buf = 'c'; + break; + case 'I': + case 'U': + if (size == 1) + *buf = (type->is_unsigned) ? 'B' : 'b'; + else if (size == 2) + *buf = (type->is_unsigned) ? 'H' : 'h'; + else if (size == 4) + *buf = (type->is_unsigned) ? 'I' : 'i'; + else if (size == 8) + *buf = (type->is_unsigned) ? 'Q' : 'q'; + break; + case 'P': + *buf = 'P'; + break; + case 'C': + { + __Pyx_TypeInfo complex_type = *type; + complex_type.typegroup = 'R'; + complex_type.size /= 2; + *buf++ = 'Z'; + *buf = __Pyx_TypeInfoToFormat(&complex_type).string[0]; + break; + } + case 'R': + if (size == 4) + *buf = 'f'; + else if (size == 8) + *buf = 'd'; + else + *buf = 'g'; + break; + } + return result; +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(Py_intptr_t) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(Py_intptr_t) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(Py_intptr_t), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(Py_intptr_t) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (Py_intptr_t) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (Py_intptr_t) 0; + case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, digits[0]) + case 2: + if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 2 * PyLong_SHIFT) { + return (Py_intptr_t) (((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 3 * PyLong_SHIFT) { + return (Py_intptr_t) (((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 4 * PyLong_SHIFT) { + return (Py_intptr_t) (((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (Py_intptr_t) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (Py_intptr_t) 0; + case -1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, +digits[0]) + case -2: + if (8 * sizeof(Py_intptr_t) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + } +#endif + if (sizeof(Py_intptr_t) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + Py_intptr_t val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (Py_intptr_t) -1; + } + } else { + Py_intptr_t val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (Py_intptr_t) -1; + val = __Pyx_PyInt_As_Py_intptr_t(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to Py_intptr_t"); + return (Py_intptr_t) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to Py_intptr_t"); + return (Py_intptr_t) -1; +} + +/* CIntFromPy */ + static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + } +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +/* CIntFromPy */ + static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(long) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (long) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(long) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + } +#endif + if (sizeof(long) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + long val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (long) -1; + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (long) -1; + val = __Pyx_PyInt_As_long(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to long"); + return (long) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long) -1; +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(int) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(int) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(int) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(int), + little, !is_unsigned); + } +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(long) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(long) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(long) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(long), + little, !is_unsigned); + } +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_int32(npy_int32 value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(npy_int32) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(npy_int32) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(npy_int32) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(npy_int32), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(npy_int32) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (npy_int32) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (npy_int32) 0; + case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, digits[0]) + case 2: + if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) >= 2 * PyLong_SHIFT) { + return (npy_int32) (((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) >= 3 * PyLong_SHIFT) { + return (npy_int32) (((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) >= 4 * PyLong_SHIFT) { + return (npy_int32) (((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (npy_int32) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(npy_int32) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (npy_int32) 0; + case -1: __PYX_VERIFY_RETURN_INT(npy_int32, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, +digits[0]) + case -2: + if (8 * sizeof(npy_int32) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { + return (npy_int32) (((npy_int32)-1)*(((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { + return (npy_int32) ((((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { + return (npy_int32) (((npy_int32)-1)*(((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { + return (npy_int32) ((((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) { + return (npy_int32) (((npy_int32)-1)*(((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) { + return (npy_int32) ((((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + } +#endif + if (sizeof(npy_int32) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + npy_int32 val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (npy_int32) -1; + } + } else { + npy_int32 val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (npy_int32) -1; + val = __Pyx_PyInt_As_npy_int32(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to npy_int32"); + return (npy_int32) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to npy_int32"); + return (npy_int32) -1; +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_uint32(npy_uint32 value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const npy_uint32 neg_one = (npy_uint32) -1, const_zero = (npy_uint32) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(npy_uint32) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(npy_uint32) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_uint32) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(npy_uint32) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_uint32) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(npy_uint32), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const char neg_one = (char) -1, const_zero = (char) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(char) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (char) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (char) 0; + case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { + return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { + return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { + return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (char) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(char) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (char) 0; + case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) + case -2: + if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + } +#endif + if (sizeof(char) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + char val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (char) -1; + } + } else { + char val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (char) -1; + val = __Pyx_PyInt_As_char(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to char"); + return (char) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to char"); + return (char) -1; +} + +/* TypeInfoCompare */ + static int +__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) +{ + int i; + if (!a || !b) + return 0; + if (a == b) + return 1; + if (a->size != b->size || a->typegroup != b->typegroup || + a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { + if (a->typegroup == 'H' || b->typegroup == 'H') { + return a->size == b->size; + } else { + return 0; + } + } + if (a->ndim) { + for (i = 0; i < a->ndim; i++) + if (a->arraysize[i] != b->arraysize[i]) + return 0; + } + if (a->typegroup == 'S') { + if (a->flags != b->flags) + return 0; + if (a->fields || b->fields) { + if (!(a->fields && b->fields)) + return 0; + for (i = 0; a->fields[i].type && b->fields[i].type; i++) { + __Pyx_StructField *field_a = a->fields + i; + __Pyx_StructField *field_b = b->fields + i; + if (field_a->offset != field_b->offset || + !__pyx_typeinfo_cmp(field_a->type, field_b->type)) + return 0; + } + return !a->fields[i].type && !b->fields[i].type; + } + } + return 1; +} + +/* MemviewSliceValidateAndInit */ + static int +__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) +{ + if (buf->shape[dim] <= 1) + return 1; + if (buf->strides) { + if (spec & __Pyx_MEMVIEW_CONTIG) { + if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { + if (unlikely(buf->strides[dim] != sizeof(void *))) { + PyErr_Format(PyExc_ValueError, + "Buffer is not indirectly contiguous " + "in dimension %d.", dim); + goto fail; + } + } else if (unlikely(buf->strides[dim] != buf->itemsize)) { + PyErr_SetString(PyExc_ValueError, + "Buffer and memoryview are not contiguous " + "in the same dimension."); + goto fail; + } + } + if (spec & __Pyx_MEMVIEW_FOLLOW) { + Py_ssize_t stride = buf->strides[dim]; + if (stride < 0) + stride = -stride; + if (unlikely(stride < buf->itemsize)) { + PyErr_SetString(PyExc_ValueError, + "Buffer and memoryview are not contiguous " + "in the same dimension."); + goto fail; + } + } + } else { + if (unlikely(spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1)) { + PyErr_Format(PyExc_ValueError, + "C-contiguous buffer is not contiguous in " + "dimension %d", dim); + goto fail; + } else if (unlikely(spec & (__Pyx_MEMVIEW_PTR))) { + PyErr_Format(PyExc_ValueError, + "C-contiguous buffer is not indirect in " + "dimension %d", dim); + goto fail; + } else if (unlikely(buf->suboffsets)) { + PyErr_SetString(PyExc_ValueError, + "Buffer exposes suboffsets but no strides"); + goto fail; + } + } + return 1; +fail: + return 0; +} +static int +__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) +{ + if (spec & __Pyx_MEMVIEW_DIRECT) { + if (unlikely(buf->suboffsets && buf->suboffsets[dim] >= 0)) { + PyErr_Format(PyExc_ValueError, + "Buffer not compatible with direct access " + "in dimension %d.", dim); + goto fail; + } + } + if (spec & __Pyx_MEMVIEW_PTR) { + if (unlikely(!buf->suboffsets || (buf->suboffsets[dim] < 0))) { + PyErr_Format(PyExc_ValueError, + "Buffer is not indirectly accessible " + "in dimension %d.", dim); + goto fail; + } + } + return 1; +fail: + return 0; +} +static int +__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) +{ + int i; + if (c_or_f_flag & __Pyx_IS_F_CONTIG) { + Py_ssize_t stride = 1; + for (i = 0; i < ndim; i++) { + if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { + PyErr_SetString(PyExc_ValueError, + "Buffer not fortran contiguous."); + goto fail; + } + stride = stride * buf->shape[i]; + } + } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { + Py_ssize_t stride = 1; + for (i = ndim - 1; i >- 1; i--) { + if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { + PyErr_SetString(PyExc_ValueError, + "Buffer not C contiguous."); + goto fail; + } + stride = stride * buf->shape[i]; + } + } + return 1; +fail: + return 0; +} +static int __Pyx_ValidateAndInit_memviewslice( + int *axes_specs, + int c_or_f_flag, + int buf_flags, + int ndim, + __Pyx_TypeInfo *dtype, + __Pyx_BufFmt_StackElem stack[], + __Pyx_memviewslice *memviewslice, + PyObject *original_obj) +{ + struct __pyx_memoryview_obj *memview, *new_memview; + __Pyx_RefNannyDeclarations + Py_buffer *buf; + int i, spec = 0, retval = -1; + __Pyx_BufFmt_Context ctx; + int from_memoryview = __pyx_memoryview_check(original_obj); + __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0); + if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) + original_obj)->typeinfo)) { + memview = (struct __pyx_memoryview_obj *) original_obj; + new_memview = NULL; + } else { + memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + original_obj, buf_flags, 0, dtype); + new_memview = memview; + if (unlikely(!memview)) + goto fail; + } + buf = &memview->view; + if (unlikely(buf->ndim != ndim)) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + ndim, buf->ndim); + goto fail; + } + if (new_memview) { + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (unlikely(!__Pyx_BufFmt_CheckString(&ctx, buf->format))) goto fail; + } + if (unlikely((unsigned) buf->itemsize != dtype->size)) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " + "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", + buf->itemsize, + (buf->itemsize > 1) ? "s" : "", + dtype->name, + dtype->size, + (dtype->size > 1) ? "s" : ""); + goto fail; + } + if (buf->len > 0) { + for (i = 0; i < ndim; i++) { + spec = axes_specs[i]; + if (unlikely(!__pyx_check_strides(buf, i, ndim, spec))) + goto fail; + if (unlikely(!__pyx_check_suboffsets(buf, i, ndim, spec))) + goto fail; + } + if (unlikely(buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))) + goto fail; + } + if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, + new_memview != NULL) == -1)) { + goto fail; + } + retval = 0; + goto no_fail; +fail: + Py_XDECREF(new_memview); + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} + +/* ObjectToMemviewSlice */ + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__(PyObject *obj, int writable_flag) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG, + (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT) | writable_flag, 2, + &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +/* ObjectToMemviewSlice */ + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_5_tree_DTYPE_t__const__(PyObject *obj, int writable_flag) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS_RO | writable_flag, 2, + &__Pyx_TypeInfo_nn___pyx_t_5_tree_DTYPE_t__const__, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +/* ObjectToMemviewSlice */ + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_DOUBLE_t(PyObject *obj, int writable_flag) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS_RO | writable_flag, 1, + &__Pyx_TypeInfo_nn___pyx_t_5_tree_DOUBLE_t, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +/* ObjectToMemviewSlice */ + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_SIZE_t(PyObject *obj, int writable_flag) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS_RO | writable_flag, 1, + &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +/* ObjectToMemviewSlice */ + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_unsigned_char(PyObject *obj, int writable_flag) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS_RO | writable_flag, 1, + &__Pyx_TypeInfo_unsigned_char, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +/* CheckBinaryVersion */ + static int __Pyx_check_binary_version(void) { + char ctversion[4], rtversion[4]; + PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); + PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); + if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { + char message[200]; + PyOS_snprintf(message, sizeof(message), + "compiletime version %s of module '%.100s' " + "does not match runtime version %s", + ctversion, __Pyx_MODULE_NAME, rtversion); + return PyErr_WarnEx(NULL, message, 1); + } + return 0; +} + +/* VoidPtrImport */ + #ifndef __PYX_HAVE_RT_ImportVoidPtr +#define __PYX_HAVE_RT_ImportVoidPtr +static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig) { + PyObject *d = 0; + PyObject *cobj = 0; + d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); + if (!d) + goto bad; + cobj = PyDict_GetItemString(d, name); + if (!cobj) { + PyErr_Format(PyExc_ImportError, + "%.200s does not export expected C variable %.200s", + PyModule_GetName(module), name); + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + if (!PyCapsule_IsValid(cobj, sig)) { + PyErr_Format(PyExc_TypeError, + "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), name, sig, PyCapsule_GetName(cobj)); + goto bad; + } + *p = PyCapsule_GetPointer(cobj, sig); +#else + {const char *desc, *s1, *s2; + desc = (const char *)PyCObject_GetDesc(cobj); + if (!desc) + goto bad; + s1 = desc; s2 = sig; + while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } + if (*s1 != *s2) { + PyErr_Format(PyExc_TypeError, + "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), name, sig, desc); + goto bad; + } + *p = PyCObject_AsVoidPtr(cobj);} +#endif + if (!(*p)) + goto bad; + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(d); + return -1; +} +#endif + +/* FunctionImport */ + #ifndef __PYX_HAVE_RT_ImportFunction +#define __PYX_HAVE_RT_ImportFunction +static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig) { + PyObject *d = 0; + PyObject *cobj = 0; + union { + void (*fp)(void); + void *p; + } tmp; + d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); + if (!d) + goto bad; + cobj = PyDict_GetItemString(d, funcname); + if (!cobj) { + PyErr_Format(PyExc_ImportError, + "%.200s does not export expected C function %.200s", + PyModule_GetName(module), funcname); + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + if (!PyCapsule_IsValid(cobj, sig)) { + PyErr_Format(PyExc_TypeError, + "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), funcname, sig, PyCapsule_GetName(cobj)); + goto bad; + } + tmp.p = PyCapsule_GetPointer(cobj, sig); +#else + {const char *desc, *s1, *s2; + desc = (const char *)PyCObject_GetDesc(cobj); + if (!desc) + goto bad; + s1 = desc; s2 = sig; + while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } + if (*s1 != *s2) { + PyErr_Format(PyExc_TypeError, + "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), funcname, sig, desc); + goto bad; + } + tmp.p = PyCObject_AsVoidPtr(cobj);} +#endif + *f = tmp.fp; + if (!(*f)) + goto bad; + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(d); + return -1; +} +#endif + +/* InitStrings */ + static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + if (PyObject_Hash(*t->p) == -1) + return -1; + ++t; + } + return 0; +} + +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { + return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); +} +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { + Py_ssize_t ignore; + return __Pyx_PyObject_AsStringAndSize(o, &ignore); +} +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if !CYTHON_PEP393_ENABLED +static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + char* defenc_c; + PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); + if (!defenc) return NULL; + defenc_c = PyBytes_AS_STRING(defenc); +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + { + char* end = defenc_c + PyBytes_GET_SIZE(defenc); + char* c; + for (c = defenc_c; c < end; c++) { + if ((unsigned char) (*c) >= 128) { + PyUnicode_AsASCIIString(o); + return NULL; + } + } + } +#endif + *length = PyBytes_GET_SIZE(defenc); + return defenc_c; +} +#else +static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + if (likely(PyUnicode_IS_ASCII(o))) { + *length = PyUnicode_GET_LENGTH(o); + return PyUnicode_AsUTF8(o); + } else { + PyUnicode_AsASCIIString(o); + return NULL; + } +#else + return PyUnicode_AsUTF8AndSize(o, length); +#endif +} +#endif +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT + if ( +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + __Pyx_sys_getdefaultencoding_not_ascii && +#endif + PyUnicode_Check(o)) { + return __Pyx_PyUnicode_AsStringAndSize(o, length); + } else +#endif +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) + if (PyByteArray_Check(o)) { + *length = PyByteArray_GET_SIZE(o); + return PyByteArray_AS_STRING(o); + } else +#endif + { + char* result; + int r = PyBytes_AsStringAndSize(o, &result, length); + if (unlikely(r < 0)) { + return NULL; + } else { + return result; + } + } +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { + int retval; + if (unlikely(!x)) return -1; + retval = __Pyx_PyObject_IsTrue(x); + Py_DECREF(x); + return retval; +} +static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { +#if PY_MAJOR_VERSION >= 3 + if (PyLong_Check(result)) { + if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, + "__int__ returned non-int (type %.200s). " + "The ability to return an instance of a strict subclass of int " + "is deprecated, and may be removed in a future version of Python.", + Py_TYPE(result)->tp_name)) { + Py_DECREF(result); + return NULL; + } + return result; + } +#endif + PyErr_Format(PyExc_TypeError, + "__%.4s__ returned non-%.4s (type %.200s)", + type_name, type_name, Py_TYPE(result)->tp_name); + Py_DECREF(result); + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { +#if CYTHON_USE_TYPE_SLOTS + PyNumberMethods *m; +#endif + const char *name = NULL; + PyObject *res = NULL; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x) || PyLong_Check(x))) +#else + if (likely(PyLong_Check(x))) +#endif + return __Pyx_NewRef(x); +#if CYTHON_USE_TYPE_SLOTS + m = Py_TYPE(x)->tp_as_number; + #if PY_MAJOR_VERSION < 3 + if (m && m->nb_int) { + name = "int"; + res = m->nb_int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = m->nb_long(x); + } + #else + if (likely(m && m->nb_int)) { + name = "int"; + res = m->nb_int(x); + } + #endif +#else + if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { + res = PyNumber_Int(x); + } +#endif + if (likely(res)) { +#if PY_MAJOR_VERSION < 3 + if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { +#else + if (unlikely(!PyLong_CheckExact(res))) { +#endif + return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject *x; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(b); + } +#endif + if (likely(PyLong_CheckExact(b))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + } + } + #endif + return PyLong_AsSsize_t(b); + } + x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { + return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); +} +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { + return PyInt_FromSize_t(ival); +} + + +#endif /* Py_PYTHON_H */ diff --git a/stpredictions/models/OK3/extra/_tree.pxd b/stpredictions/models/OK3/_tree.pxd similarity index 58% rename from stpredictions/models/OK3/extra/_tree.pxd rename to stpredictions/models/OK3/_tree.pxd index 1966651d8..7a5a82cc3 100644 --- a/stpredictions/models/OK3/extra/_tree.pxd +++ b/stpredictions/models/OK3/_tree.pxd @@ -1,26 +1,17 @@ -# Authors: Gilles Louppe -# Peter Prettenhofer -# Brian Holt -# Joel Nothman -# Arnaud Joly -# Jacob Schreiber -# Nelson Liu -# -# License: BSD 3 clause # See _tree.pyx for details. import numpy as np -cimport numpy as cnp +cimport numpy as np -ctypedef cnp.npy_float32 DTYPE_t # Type of X -ctypedef cnp.npy_float64 DOUBLE_t # Type of y, sample_weight -ctypedef cnp.npy_intp SIZE_t # Type for indices and counters -ctypedef cnp.npy_int32 INT32_t # Signed 32 bit integer -ctypedef cnp.npy_uint32 UINT32_t # Unsigned 32 bit integer +ctypedef np.npy_float32 DTYPE_t # Type of X +ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight +ctypedef np.npy_intp SIZE_t # Type for indices and counters +ctypedef np.npy_int32 INT32_t # Signed 32 bit integer +ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer -from ._splitter cimport Splitter -from ._splitter cimport SplitRecord +from _splitter cimport Splitter +from _splitter cimport SplitRecord cdef struct Node: # Base storage structure for the nodes in a Tree object @@ -36,46 +27,44 @@ cdef struct Node: cdef class Tree: # The Tree object is a binary tree structure constructed by the - # TreeBuilder. The tree structure is used for predictions and - # feature importances. + # TreeBuilder. # Input/Output layout cdef public SIZE_t n_features # Number of features in X - cdef SIZE_t* n_classes # Number of classes in y[:, k] - cdef public SIZE_t n_outputs # Number of outputs in y - cdef public SIZE_t max_n_classes # max(n_classes) # Inner structures: values are stored separately from node structure, # since size is determined at runtime. cdef public SIZE_t max_depth # Max depth of the tree cdef public SIZE_t node_count # Counter for node IDs cdef public SIZE_t capacity # Capacity of tree, in terms of nodes + # cdef public np.ndarray leaf_to_train_exs # Array indicating for each leaf (node actually) which training samples fall in it (boolean list) + cdef public np.ndarray K_y # The training Gramm matrix , anciennement DOUBLE_t[:, ::1] mais impossible à initialiser sous NULL + cdef public np.ndarray y # The set of candidate outputs for the tree cdef Node* nodes # Array of nodes - cdef double* value # (capacity, n_outputs, max_n_classes) array of values - cdef SIZE_t value_stride # = n_outputs * max_n_classes + cdef double* value # (capacity, n_training_samples) array of weights (wrt the training samples) for the prediction of each leaf # Methods cdef SIZE_t _add_node(self, SIZE_t parent, bint is_left, bint is_leaf, SIZE_t feature, double threshold, double impurity, SIZE_t n_node_samples, - double weighted_n_node_samples) except -1 nogil - cdef int _resize(self, SIZE_t capacity) except -1 nogil - cdef int _resize_c(self, SIZE_t capacity=*) except -1 nogil + double weighted_n_samples) nogil except -1 + cdef int _resize(self, SIZE_t capacity) nogil except -1 + cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 - cdef cnp.ndarray _get_value_ndarray(self) - cdef cnp.ndarray _get_node_ndarray(self) + cdef np.ndarray _get_value_ndarray(self) + cdef np.ndarray _get_node_ndarray(self) - cpdef cnp.ndarray predict(self, object X) + cpdef np.ndarray decode_tree(self, np.ndarray K_cand_train, np.ndarray sq_norms_cand, object criterion, str kernel, SIZE_t return_top_k) + cpdef np.ndarray predict(self, object X) - cpdef cnp.ndarray apply(self, object X) - cdef cnp.ndarray _apply_dense(self, object X) - cdef cnp.ndarray _apply_sparse_csr(self, object X) + cpdef np.ndarray apply(self, object X) + cdef np.ndarray _apply_dense(self, object X) + cdef np.ndarray _apply_sparse_csr(self, object X) cpdef object decision_path(self, object X) cdef object _decision_path_dense(self, object X) cdef object _decision_path_sparse_csr(self, object X) - cpdef compute_node_depths(self) cpdef compute_feature_importances(self, normalize=*) @@ -97,19 +86,9 @@ cdef class TreeBuilder: cdef SIZE_t min_samples_leaf # Minimum number of samples in a leaf cdef double min_weight_leaf # Minimum weight in a leaf cdef SIZE_t max_depth # Maximal tree depth + cdef double min_impurity_split cdef double min_impurity_decrease # Impurity threshold for early stopping - cpdef build( - self, - Tree tree, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight=*, - ) - - cdef _check_input( - self, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight, - ) + cpdef build(self, Tree tree, object X, np.ndarray y, + np.ndarray sample_weight=*) + cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) diff --git a/stpredictions/models/OK3/_tree.pyx b/stpredictions/models/OK3/_tree.pyx index 75eed058b..4ac23b7b6 100644 --- a/stpredictions/models/OK3/_tree.pyx +++ b/stpredictions/models/OK3/_tree.pyx @@ -1,55 +1,43 @@ -# Authors: Gilles Louppe -# Peter Prettenhofer -# Brian Holt -# Noel Dawe -# Satrajit Gosh -# Lars Buitinck -# Arnaud Joly -# Joel Nothman -# Fares Hedayati -# Jacob Schreiber -# Nelson Liu -# -# License: BSD 3 clause +# cython: cdivision=True +# cython: boundscheck=False +# cython: wraparound=False from cpython cimport Py_INCREF, PyObject, PyTypeObject from libc.stdlib cimport free +from libc.math cimport fabs from libc.string cimport memcpy from libc.string cimport memset -from libc.stdint cimport INTPTR_MAX -from libcpp.vector cimport vector -from libcpp.algorithm cimport pop_heap -from libcpp.algorithm cimport push_heap -from libcpp cimport bool - -import struct +from libc.stdint cimport SIZE_MAX import numpy as np -cimport numpy as cnp -cnp.import_array() +cimport numpy as np +np.import_array() + +import warnings + +import itertools from scipy.sparse import issparse +from scipy.sparse import csc_matrix from scipy.sparse import csr_matrix -from ._utils cimport safe_realloc -from ._utils cimport sizet_ptr_to_ndarray +from sklearn.tree._utils cimport Stack +from sklearn.tree._utils cimport StackRecord +from sklearn.tree._utils cimport PriorityHeap +from sklearn.tree._utils cimport PriorityHeapRecord +from sklearn.tree._utils cimport safe_realloc +from sklearn.tree._utils cimport sizet_ptr_to_ndarray + +from _criterion import Criterion +from _criterion import KernelizedMSE cdef extern from "numpy/arrayobject.h": - object PyArray_NewFromDescr(PyTypeObject* subtype, cnp.dtype descr, - int nd, cnp.npy_intp* dims, - cnp.npy_intp* strides, + object PyArray_NewFromDescr(PyTypeObject* subtype, np.dtype descr, + int nd, np.npy_intp* dims, + np.npy_intp* strides, void* data, int flags, object obj) - int PyArray_SetBaseObject(cnp.ndarray arr, PyObject* obj) - -cdef extern from "" namespace "std" nogil: - cdef cppclass stack[T]: - ctypedef T value_type - stack() except + - bint empty() - void pop() - void push(T&) except + # Raise c++ exception for bad_alloc -> MemoryError - T& top() + int PyArray_SetBaseObject(np.ndarray arr, PyObject* obj) # ============================================================================= # Types and constants @@ -71,6 +59,7 @@ TREE_LEAF = -1 TREE_UNDEFINED = -2 cdef SIZE_t _TREE_LEAF = TREE_LEAF cdef SIZE_t _TREE_UNDEFINED = TREE_UNDEFINED +cdef SIZE_t INITIAL_STACK_SIZE = 10 # Build the corresponding numpy dtype for Node. # This works by casting `dummy` to an array of Node of length 1, which numpy @@ -85,23 +74,14 @@ NODE_DTYPE = np.asarray((&dummy)).dtype cdef class TreeBuilder: """Interface for different tree building strategies.""" - - cpdef build( - self, - Tree tree, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight=None, - ): + + cpdef build(self, Tree tree, object X, np.ndarray y, + np.ndarray sample_weight=None): """Build a decision tree from the training set (X, y).""" pass - cdef inline _check_input( - self, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight, - ): + cdef inline _check_input(self, object X, np.ndarray y, + np.ndarray sample_weight): """Check input dtype, layout and format""" if issparse(X): X = X.tocsc() @@ -118,61 +98,50 @@ cdef class TreeBuilder: # since we have to copy we will make it fortran for efficiency X = np.asfortranarray(X, dtype=DTYPE) - # TODO: This check for y seems to be redundant, as it is also - # present in the BaseDecisionTree's fit method, and therefore - # can be removed. - if y.base.dtype != DOUBLE or not y.base.flags.contiguous: + if y.dtype != DOUBLE or not y.flags.contiguous: y = np.ascontiguousarray(y, dtype=DOUBLE) if (sample_weight is not None and - (sample_weight.base.dtype != DOUBLE or - not sample_weight.base.flags.contiguous)): + (sample_weight.dtype != DOUBLE or + not sample_weight.flags.contiguous)): sample_weight = np.asarray(sample_weight, dtype=DOUBLE, order="C") return X, y, sample_weight # Depth first builder --------------------------------------------------------- -# A record on the stack for depth-first tree growing -cdef struct StackRecord: - SIZE_t start - SIZE_t end - SIZE_t depth - SIZE_t parent - bint is_left - double impurity - SIZE_t n_constant_features cdef class DepthFirstTreeBuilder(TreeBuilder): """Build a decision tree in depth-first fashion.""" def __cinit__(self, Splitter splitter, SIZE_t min_samples_split, SIZE_t min_samples_leaf, double min_weight_leaf, - SIZE_t max_depth, double min_impurity_decrease): + SIZE_t max_depth, double min_impurity_decrease, + double min_impurity_split): self.splitter = splitter self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_weight_leaf = min_weight_leaf self.max_depth = max_depth self.min_impurity_decrease = min_impurity_decrease + self.min_impurity_split = min_impurity_split - cpdef build( - self, - Tree tree, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight=None, - ): + cpdef build(self, Tree tree, object X, np.ndarray y, + np.ndarray sample_weight=None): """Build a decision tree from the training set (X, y).""" # check input X, y, sample_weight = self._check_input(X, y, sample_weight) + cdef DOUBLE_t* sample_weight_ptr = NULL + if sample_weight is not None: + sample_weight_ptr = sample_weight.data + # Initial capacity cdef int init_capacity if tree.max_depth <= 10: - init_capacity = (2 ** (tree.max_depth + 1)) - 1 + init_capacity = (2 ** (tree.max_depth + 1)) - 1 else: init_capacity = 2047 @@ -185,9 +154,10 @@ cdef class DepthFirstTreeBuilder(TreeBuilder): cdef double min_weight_leaf = self.min_weight_leaf cdef SIZE_t min_samples_split = self.min_samples_split cdef double min_impurity_decrease = self.min_impurity_decrease + cdef double min_impurity_split = self.min_impurity_split # Recursive partition (without actual recursion) - splitter.init(X, y, sample_weight) + splitter.init(X, y, sample_weight_ptr) cdef SIZE_t start cdef SIZE_t end @@ -195,6 +165,7 @@ cdef class DepthFirstTreeBuilder(TreeBuilder): cdef SIZE_t parent cdef bint is_left cdef SIZE_t n_node_samples = splitter.n_samples + cdef double weighted_n_samples = splitter.weighted_n_samples cdef double weighted_n_node_samples cdef SplitRecord split cdef SIZE_t node_id @@ -206,23 +177,19 @@ cdef class DepthFirstTreeBuilder(TreeBuilder): cdef SIZE_t max_depth_seen = -1 cdef int rc = 0 - cdef stack[StackRecord] builder_stack + cdef Stack stack = Stack(INITIAL_STACK_SIZE) cdef StackRecord stack_record - + with nogil: # push root node onto stack - builder_stack.push({ - "start": 0, - "end": n_node_samples, - "depth": 0, - "parent": _TREE_UNDEFINED, - "is_left": 0, - "impurity": INFINITY, - "n_constant_features": 0}) - - while not builder_stack.empty(): - stack_record = builder_stack.top() - builder_stack.pop() + rc = stack.push(0, n_node_samples, 0, _TREE_UNDEFINED, 0, INFINITY, 0) + if rc == -1: + # got return code -1 - out-of-memory + with gil: + raise MemoryError() + + while not stack.is_empty(): + stack.pop(&stack_record) start = stack_record.start end = stack_record.end @@ -244,8 +211,8 @@ cdef class DepthFirstTreeBuilder(TreeBuilder): impurity = splitter.node_impurity() first = 0 - # impurity == 0 with tolerance due to rounding errors - is_leaf = is_leaf or impurity <= EPSILON + is_leaf = (is_leaf or + (impurity <= min_impurity_split)) if not is_leaf: splitter.node_split(impurity, &split, &n_constant_features) @@ -260,34 +227,26 @@ cdef class DepthFirstTreeBuilder(TreeBuilder): split.threshold, impurity, n_node_samples, weighted_n_node_samples) - if node_id == INTPTR_MAX: + if node_id == SIZE_MAX: rc = -1 break # Store value for all nodes, to facilitate tree/model # inspection and interpretation - splitter.node_value(tree.value + node_id * tree.value_stride) - + splitter.node_value(tree.value + node_id * y.shape[0]) + if not is_leaf: # Push right child on stack - builder_stack.push({ - "start": split.pos, - "end": end, - "depth": depth + 1, - "parent": node_id, - "is_left": 0, - "impurity": split.impurity_right, - "n_constant_features": n_constant_features}) + rc = stack.push(split.pos, end, depth + 1, node_id, 0, + split.impurity_right, n_constant_features) + if rc == -1: + break # Push left child on stack - builder_stack.push({ - "start": start, - "end": split.pos, - "depth": depth + 1, - "parent": node_id, - "is_left": 1, - "impurity": split.impurity_left, - "n_constant_features": n_constant_features}) + rc = stack.push(start, split.pos, depth + 1, node_id, 1, + split.impurity_left, n_constant_features) + if rc == -1: + break if depth > max_depth_seen: max_depth_seen = depth @@ -297,39 +256,27 @@ cdef class DepthFirstTreeBuilder(TreeBuilder): if rc >= 0: tree.max_depth = max_depth_seen + if rc == -1: raise MemoryError() + + # feed the tree attribute 'K_y' + + tree.K_y = y # Best first builder ---------------------------------------------------------- -cdef struct FrontierRecord: - # Record of information of a Node, the frontier for a split. Those records are - # maintained in a heap to access the Node with the best improvement in impurity, - # allowing growing trees greedily on this improvement. - SIZE_t node_id - SIZE_t start - SIZE_t end - SIZE_t pos - SIZE_t depth - bint is_leaf - double impurity - double impurity_left - double impurity_right - double improvement - -cdef inline bool _compare_records( - const FrontierRecord& left, - const FrontierRecord& right, -): - return left.improvement < right.improvement - -cdef inline void _add_to_frontier( - FrontierRecord rec, - vector[FrontierRecord]& frontier, -) noexcept nogil: - """Adds record `rec` to the priority queue `frontier`.""" - frontier.push_back(rec) - push_heap(frontier.begin(), frontier.end(), &_compare_records) + +cdef inline int _add_to_frontier(PriorityHeapRecord* rec, + PriorityHeap frontier) nogil except -1: + """Adds record ``rec`` to the priority queue ``frontier`` + + Returns -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + return frontier.push(rec.node_id, rec.start, rec.end, rec.pos, rec.depth, + rec.is_leaf, rec.improvement, rec.impurity, + rec.impurity_left, rec.impurity_right) cdef class BestFirstTreeBuilder(TreeBuilder): @@ -343,7 +290,7 @@ cdef class BestFirstTreeBuilder(TreeBuilder): def __cinit__(self, Splitter splitter, SIZE_t min_samples_split, SIZE_t min_samples_leaf, min_weight_leaf, SIZE_t max_depth, SIZE_t max_leaf_nodes, - double min_impurity_decrease): + double min_impurity_decrease, double min_impurity_split): self.splitter = splitter self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf @@ -351,30 +298,33 @@ cdef class BestFirstTreeBuilder(TreeBuilder): self.max_depth = max_depth self.max_leaf_nodes = max_leaf_nodes self.min_impurity_decrease = min_impurity_decrease + self.min_impurity_split = min_impurity_split - cpdef build( - self, - Tree tree, - object X, - const DOUBLE_t[:, ::1] y, - const DOUBLE_t[:] sample_weight=None, - ): + cpdef build(self, Tree tree, object X, np.ndarray y, + np.ndarray sample_weight=None): """Build a decision tree from the training set (X, y).""" # check input X, y, sample_weight = self._check_input(X, y, sample_weight) + cdef DOUBLE_t* sample_weight_ptr = NULL + if sample_weight is not None: + sample_weight_ptr = sample_weight.data + # Parameters cdef Splitter splitter = self.splitter cdef SIZE_t max_leaf_nodes = self.max_leaf_nodes + cdef SIZE_t min_samples_leaf = self.min_samples_leaf + cdef double min_weight_leaf = self.min_weight_leaf + cdef SIZE_t min_samples_split = self.min_samples_split # Recursive partition (without actual recursion) - splitter.init(X, y, sample_weight) + splitter.init(X, y, sample_weight_ptr) - cdef vector[FrontierRecord] frontier - cdef FrontierRecord record - cdef FrontierRecord split_node_left - cdef FrontierRecord split_node_right + cdef PriorityHeap frontier = PriorityHeap(INITIAL_STACK_SIZE) + cdef PriorityHeapRecord record + cdef PriorityHeapRecord split_node_left + cdef PriorityHeapRecord split_node_right cdef SIZE_t n_node_samples = splitter.n_samples cdef SIZE_t max_split_nodes = max_leaf_nodes - 1 @@ -391,14 +341,17 @@ cdef class BestFirstTreeBuilder(TreeBuilder): # add root to frontier rc = self._add_split_node(splitter, tree, 0, n_node_samples, INFINITY, IS_FIRST, IS_LEFT, NULL, 0, - &split_node_left) + &split_node_left, + y.shape[0]) if rc >= 0: - _add_to_frontier(split_node_left, frontier) + rc = _add_to_frontier(&split_node_left, frontier) + + if rc == -1: + with gil: + raise MemoryError() - while not frontier.empty(): - pop_heap(frontier.begin(), frontier.end(), &_compare_records) - record = frontier.back() - frontier.pop_back() + while not frontier.is_empty(): + frontier.pop(&record) node = &tree.nodes[record.node_id] is_leaf = (record.is_leaf or max_split_nodes <= 0) @@ -422,7 +375,8 @@ cdef class BestFirstTreeBuilder(TreeBuilder): record.impurity_left, IS_NOT_FIRST, IS_LEFT, node, record.depth + 1, - &split_node_left) + &split_node_left, + y.shape[0]) if rc == -1: break @@ -435,13 +389,19 @@ cdef class BestFirstTreeBuilder(TreeBuilder): record.impurity_right, IS_NOT_FIRST, IS_NOT_LEFT, node, record.depth + 1, - &split_node_right) + &split_node_right, + y.shape[0]) if rc == -1: break # Add nodes to queue - _add_to_frontier(split_node_left, frontier) - _add_to_frontier(split_node_right, frontier) + rc = _add_to_frontier(&split_node_left, frontier) + if rc == -1: + break + + rc = _add_to_frontier(&split_node_right, frontier) + if rc == -1: + break if record.depth > max_depth_seen: max_depth_seen = record.depth @@ -455,19 +415,30 @@ cdef class BestFirstTreeBuilder(TreeBuilder): if rc == -1: raise MemoryError() + + # feed the tree attribute 'K_y' + + tree.K_y = y + + cdef inline int _add_split_node(self, Splitter splitter, Tree tree, SIZE_t start, SIZE_t end, double impurity, bint is_first, bint is_left, Node* parent, SIZE_t depth, - FrontierRecord* res) except -1 nogil: + PriorityHeapRecord* res, + SIZE_t n_samples) nogil except -1: """Adds node w/ partition ``[start, end)`` to the frontier. """ cdef SplitRecord split cdef SIZE_t node_id cdef SIZE_t n_node_samples cdef SIZE_t n_constant_features = 0 + cdef double weighted_n_samples = splitter.weighted_n_samples cdef double min_impurity_decrease = self.min_impurity_decrease + cdef double min_impurity_split = self.min_impurity_split cdef double weighted_n_node_samples cdef bint is_leaf + cdef SIZE_t n_left, n_right + cdef double imp_diff splitter.node_reset(start, end, &weighted_n_node_samples) @@ -479,8 +450,7 @@ cdef class BestFirstTreeBuilder(TreeBuilder): n_node_samples < self.min_samples_split or n_node_samples < 2 * self.min_samples_leaf or weighted_n_node_samples < 2 * self.min_weight_leaf or - impurity <= EPSILON # impurity == 0 with tolerance - ) + impurity <= min_impurity_split) if not is_leaf: splitter.node_split(impurity, &split, &n_constant_features) @@ -495,11 +465,11 @@ cdef class BestFirstTreeBuilder(TreeBuilder): is_left, is_leaf, split.feature, split.threshold, impurity, n_node_samples, weighted_n_node_samples) - if node_id == INTPTR_MAX: + if node_id == SIZE_MAX: return -1 # compute values also for split nodes (might become leafs later). - splitter.node_value(tree.value + node_id * tree.value_stride) + splitter.node_value(tree.value + node_id * n_samples) res.node_id = node_id res.start = start @@ -551,6 +521,17 @@ cdef class Tree: max_depth : int The depth of the tree, i.e. the maximum depth of its leaves. + + value : array of double, shape [node_count, n_train_samples] + Gives for each node, the weighted list of training samples + falling in the leaf/leaves bellow the leaf/node. + (Kind of invert the array given by the 'apply' function.) + + K_y : array of double, shape [n_train_samples, n_train_samples] + The training output Gramm matrix (used to compute the predictions) + + y : array of double, shape [n_train_samples, output_vetor_length] + The training output matrix children_left : array of int, shape [node_count] children_left[i] holds the node id of the left child of node i. @@ -570,9 +551,6 @@ cdef class Tree: threshold : array of double, shape [node_count] threshold[i] holds the threshold for the internal node i. - value : array of double, shape [node_count, n_outputs, max_n_classes] - Contains the constant prediction value of each node. - impurity : array of double, shape [node_count] impurity[i] holds the impurity (i.e., the value of the splitting criterion) at node i. @@ -580,17 +558,14 @@ cdef class Tree: n_node_samples : array of int, shape [node_count] n_node_samples[i] holds the number of training samples reaching node i. - weighted_n_node_samples : array of double, shape [node_count] + weighted_n_node_samples : array of int, shape [node_count] weighted_n_node_samples[i] holds the weighted number of training samples reaching node i. """ # Wrap for outside world. - # WARNING: these reference the current `nodes` and `value` buffers, which + # WARNING: these reference the current `nodes` buffers, which # must not be freed by a subsequent memory allocation. # (i.e. through `_resize` or `__setstate__`) - property n_classes: - def __get__(self): - return sizet_ptr_to_ndarray(self.n_classes, self.n_outputs) property children_left: def __get__(self): @@ -605,7 +580,6 @@ cdef class Tree: return np.sum(np.logical_and( self.children_left == -1, self.children_right == -1)) - property feature: def __get__(self): return self._get_node_ndarray()['feature'][:self.node_count] @@ -630,47 +604,29 @@ cdef class Tree: def __get__(self): return self._get_value_ndarray()[:self.node_count] - # TODO: Convert n_classes to cython.integral memory view once - # https://github.com/cython/cython/issues/5243 is fixed - def __cinit__(self, int n_features, cnp.ndarray n_classes, int n_outputs): + def __cinit__(self, int n_features, int n_samples): """Constructor.""" - cdef SIZE_t dummy = 0 - size_t_dtype = np.array(dummy).dtype - - n_classes = _check_n_classes(n_classes, size_t_dtype) - # Input/Output layout self.n_features = n_features - self.n_outputs = n_outputs - self.n_classes = NULL - safe_realloc(&self.n_classes, n_outputs) - - self.max_n_classes = np.max(n_classes) - self.value_stride = n_outputs * self.max_n_classes - - cdef SIZE_t k - for k in range(n_outputs): - self.n_classes[k] = n_classes[k] # Inner structures self.max_depth = 0 self.node_count = 0 self.capacity = 0 - self.value = NULL + self.K_y = np.zeros((n_samples,), dtype=DOUBLE) + self.y = None self.nodes = NULL + self.value = NULL def __dealloc__(self): """Destructor.""" # Free all inner structures - free(self.n_classes) - free(self.value) free(self.nodes) + free(self.value) def __reduce__(self): """Reduce re-implementation, for pickling.""" - return (Tree, (self.n_features, - sizet_ptr_to_ndarray(self.n_classes, self.n_outputs), - self.n_outputs), self.__getstate__()) + return (Tree, (self.n_features,self.K_y.shape[0]), self.__getstate__()) def __getstate__(self): """Getstate re-implementation, for pickling.""" @@ -680,12 +636,16 @@ cdef class Tree: d["node_count"] = self.node_count d["nodes"] = self._get_node_ndarray() d["values"] = self._get_value_ndarray() + d["K_y"] = self.K_y + d["y"] = self.y return d def __setstate__(self, d): """Setstate re-implementation, for unpickling.""" self.max_depth = d["max_depth"] self.node_count = d["node_count"] + self.K_y = d["K_y"] + self.y = d["y"] if 'nodes' not in d: raise ValueError('You have loaded Tree version which ' @@ -694,26 +654,24 @@ cdef class Tree: node_ndarray = d['nodes'] value_ndarray = d['values'] - value_shape = (node_ndarray.shape[0], self.n_outputs, - self.max_n_classes) - - node_ndarray = _check_node_ndarray(node_ndarray, expected_dtype=NODE_DTYPE) - value_ndarray = _check_value_ndarray( - value_ndarray, - expected_dtype=np.dtype(np.float64), - expected_shape=value_shape - ) + value_shape = (node_ndarray.shape[0], self.K_y.shape[0]) + if (node_ndarray.ndim != 1 or + node_ndarray.dtype != NODE_DTYPE or + not node_ndarray.flags.c_contiguous or + value_ndarray.shape != value_shape or + not value_ndarray.flags.c_contiguous or + value_ndarray.dtype != np.float64): + raise ValueError('Did not recognise loaded array layout') self.capacity = node_ndarray.shape[0] if self._resize_c(self.capacity) != 0: raise MemoryError("resizing tree to %d" % self.capacity) - - nodes = memcpy(self.nodes, cnp.PyArray_DATA(node_ndarray), + nodes = memcpy(self.nodes, ( node_ndarray).data, self.capacity * sizeof(Node)) - value = memcpy(self.value, cnp.PyArray_DATA(value_ndarray), - self.capacity * self.value_stride * sizeof(double)) + value = memcpy(self.value, ( value_ndarray).data, + self.capacity * self.K_y.shape[0] * sizeof(double)) - cdef int _resize(self, SIZE_t capacity) except -1 nogil: + cdef int _resize(self, SIZE_t capacity) nogil except -1: """Resize all inner arrays to `capacity`, if `capacity` == -1, then double the size of the inner arrays. @@ -725,7 +683,7 @@ cdef class Tree: with gil: raise MemoryError() - cdef int _resize_c(self, SIZE_t capacity=INTPTR_MAX) except -1 nogil: + cdef int _resize_c(self, SIZE_t capacity=SIZE_MAX) nogil except -1: """Guts of _resize Returns -1 in case of failure to allocate memory (and raise MemoryError) @@ -734,19 +692,19 @@ cdef class Tree: if capacity == self.capacity and self.nodes != NULL: return 0 - if capacity == INTPTR_MAX: + if capacity == SIZE_MAX: if self.capacity == 0: capacity = 3 # default initial value else: capacity = 2 * self.capacity safe_realloc(&self.nodes, capacity) - safe_realloc(&self.value, capacity * self.value_stride) + safe_realloc(&self.value, capacity * self.K_y.shape[0]) # value memory is initialised to 0 to enable classifier argmax if capacity > self.capacity: - memset((self.value + self.capacity * self.value_stride), 0, - (capacity - self.capacity) * self.value_stride * + memset((self.value + self.capacity * self.K_y.shape[0]), 0, + (capacity - self.capacity) * self.K_y.shape[0] * sizeof(double)) # if capacity smaller than node_count, adjust the counter @@ -759,7 +717,7 @@ cdef class Tree: cdef SIZE_t _add_node(self, SIZE_t parent, bint is_left, bint is_leaf, SIZE_t feature, double threshold, double impurity, SIZE_t n_node_samples, - double weighted_n_node_samples) except -1 nogil: + double weighted_n_node_samples) nogil except -1: """Add a node to the tree. The new node registers itself as the child of its parent. @@ -770,7 +728,7 @@ cdef class Tree: if node_id >= self.capacity: if self._resize_c() != 0: - return INTPTR_MAX + return SIZE_MAX cdef Node* node = &self.nodes[node_id] node.impurity = impurity @@ -797,23 +755,212 @@ cdef class Tree: self.node_count += 1 return node_id - - cpdef cnp.ndarray predict(self, object X): - """Predict target for X.""" - out = self._get_value_ndarray().take(self.apply(X), axis=0, - mode='clip') - if self.n_outputs == 1: - out = out.reshape(X.shape[0], self.max_n_classes) + + cpdef np.ndarray predict(self, object X): + """Returns the weighted training samples falling in the leaves X falls in. + It is an array with for each row positive weights for the training indices in the same leaf. + (the prediction in the Hilbert space is the weighted mean of these sample's outputs) + + Parameters + ---------- + X : {array-like, sparse matrix} of shape (n_samples, n_features) + The input samples. + + Returns + -------- + A (n_test_samples, n_train_samples) array + """ + # get the leaves X falls in + ex_to_leaf = self.apply(X) + # get the list of the training examples each leaf + leaf_to_train_exs = self._get_value_ndarray() + + out = np.zeros((X.shape[0], leaf_to_train_exs.shape[1]), dtype=DOUBLE) + # assign the right list of training samples to the right input + for ex in range(X.shape[0]): + out[ex] = leaf_to_train_exs[ex_to_leaf[ex]] + return out + + cpdef np.ndarray decode_tree(self, np.ndarray K_cand_train, np.ndarray sq_norms_cand, object criterion, str kernel, SIZE_t return_top_k): + """shape (node_count,) + + Decode using the search for the output the closer to the mean of the + input's leaf in the embedding Hilbert space + corresponds to the KernelizedMSE criterion + + out[i] is the index of the example whose + output has been chosen to represent the output of the leaf i + (if i is a leaf, otherwise it is -1). + + Parameters + ---------- + K_cand_train : array of shape (n_candidates, n_train_samples) + The Kernel matrix between the candidates outputs and the training outputs. + + sq_norms_cand : array of shape (n_candidates,) + The list of the kernel values of the candidates computed againt themselves + (square L2 norm in the Hilbert space). + + criterion : {"mse"}, default="mse" + The function to measure the quality of a split (in the Hilbert space). + + kernel : string + The type of kernel to use to compare the output data. + Used only to check wether we want to do classic classification or regression or a general case. + + return_top_k : int (>0) + The number of output to return for each leaf (the size of the set of the best candidates outputs) + + Returns + ------- + An array of shape (node_count * return_top_k, n_candidates) + describing for each LEAF the indices in candidates of the selected output(s), + minimizing the "distance" with the "true" predisction in the Hilbert space. + + Note : + The returned array has an arbitrary value of -1 for the lines corresponding to non-leaf nodes. + """ + if isinstance(criterion, KernelizedMSE): + + # Cas particulier de la classification : recherche EXHAUSTIVE + if kernel == "gini_clf": + + # rechercher la meilleure combinaison de labels parmis toutes celles possible + + y_train = self.y + n_outputs = y_train.shape[1] + + classes = [] + n_classes = [] + + y_train_encoded = np.zeros((y_train.shape[0], n_outputs), dtype=int) + + for l in range(n_outputs): + classes_l, y_train_encoded[:, l] = np.unique(y_train[:, l], return_inverse=True) + classes.append(classes_l) + n_classes.append(classes_l.shape[0]) + + n_classes = np.array(n_classes, dtype=np.intp) + + + + leaf_to_train_exs = self._get_value_ndarray() + + out = np.ones((self.node_count*return_top_k,n_outputs), dtype=np.intp) * (-1) + + nb_candidates = 1 + for nb_classes in n_classes: + nb_candidates *= nb_classes + # array to store the value of the criteria to minimize, for each training sample + value = np.zeros((nb_candidates,), dtype=np.float64) + + recherche_exhaustive_equivalente = False + + # node k + for k in range(self.node_count): + # ne considérer que les feuilles pour y calculer une output + if self.nodes[k].left_child == _TREE_LEAF: + + if recherche_exhaustive_equivalente or return_top_k > 1: # n_outputs boucles sur les classes de chaque output imbriquées dans le product --> long + + for ind, candidate in enumerate(list(itertools.product(*classes))): + + # la valeur a minimiser est k(candidate,candidate) - 2 * moyenne_des_Kernel(candidate,train_exs_in_same_leaf) + # dans le cas de gini, k(candidate,candidate) est toujours égal à 1 peu importe candidate + # on peut donc plutôt maximiser la quantité somme_des_Kernel(candidate,train_exs_in_same_leaf) + + value[ind] = np.sum([ leaf_to_train_exs[k,ex] * (y_train[ex] == candidate).mean() for ex in range(leaf_to_train_exs.shape[1])]) + + ind_top_candidates = np.argpartition(value, - return_top_k)[- return_top_k:] + + top_candidates = list(itertools.product(*classes))[ind_top_candidates] + top_candidates = np.array(top_candidates, dtype=int) + + out[k*return_top_k : (k+1)*return_top_k] = top_candidates + + else: + + for l in range(n_outputs): + + major_class = np.argmax( [ np.sum( leaf_to_train_exs[k, np.where( y_train[:,l] == class_i )[0] ] ) for class_i in classes[l] ] ) + + out[k,l] = classes[l][ major_class ] + + # Cas particulier de la régression : Recherche EXACTE + elif kernel == "mse_reg": + + # rechercher la meilleure combinaison de labels parmis toutes celles possible + # avec un critère MSE et donc un kernel linéaire, + # la solution exacte (argmin_y [k(y,y) - 2 moyenne_i(k(y,y_leaf_i))]) peut être calculée : + # c'est la moyenne des sorties de chaque feuille + # + # On ne peut pas rechercher les k meilleurs candidats car l'ensemble de recherche de candidats pour la régression est infini (R^d) + + y_train = self.y + n_outputs = y_train.shape[1] + + leaf_to_train_exs = self._get_value_ndarray() + + out = leaf_to_train_exs @ y_train + + # out = np.ones((self.node_count,n_outputs), dtype=y_train.dtype) * (-1) + + # # node k + # for k in range(self.node_count): + # # ne considérer que les feuilles pour y calculer une output + # if self.nodes[k].left_child == _TREE_LEAF: + + # out[k] = np.sum(np.array([ leaf_to_train_exs[k,ex] * y_train[ex] for ex in range(leaf_to_train_exs.shape[1])]), axis=0) + + + # Dans ce else, on a donc une matrice de Gram de candidats fournie + else: # cas général : pas de classification ou de régression mais recherche de l'argmin dans l'ensemble de candidats fourni + + # on a comme candidats une matrice de Gram des des candidats contre les training (+contre soi meme). + + # on renvoie l'indce du candidat représentant le mieux la feuille (on ne check pas les training examples, ils sont à mettre dans les candidats) + + leaf_to_train_exs = self._get_value_ndarray() + + out = np.ones((self.node_count*return_top_k,), dtype=np.intp) * (-1) + + # array to store the value of the criteria to minimize, for each training sample + value = np.zeros((K_cand_train.shape[0],), dtype=np.float64) + + # node k + for k in range(self.node_count): + # ne considérer que les feuilles pour y calculer une output + if self.nodes[k].left_child == _TREE_LEAF: + # parmi les candidats, calculer k[candidat,candidat] - 2/self.n_node_samples * sum_i=0^self.n_node_samples k[candidat,i] + for candidate in range(K_cand_train.shape[0]): + + value[candidate] = sq_norms_cand[candidate] - 2 * np.sum([leaf_to_train_exs[k,ex] * K_cand_train[candidate,ex] for ex in range(leaf_to_train_exs.shape[1])]) + + # choisir l'entrée ex* qui donnait la plus petite valeur + ind_top_candidates = np.argpartition(value, return_top_k)[:return_top_k] + + out[k*return_top_k : (k+1)*return_top_k] = ind_top_candidates + + + return out + + + else: + raise NotImplementedError('only the "KernelizedMSE" criterion is supported') + - cpdef cnp.ndarray apply(self, object X): + cpdef np.ndarray apply(self, object X): """Finds the terminal region (=leaf node) for each sample in X.""" if issparse(X): - return self._apply_sparse_csr(X) + if type(X) == csc_matrix: + return self._apply_sparse_csr(X.tocsr()) + else: + return self._apply_sparse_csr(X) else: return self._apply_dense(X) - cdef inline cnp.ndarray _apply_dense(self, object X): + cdef inline np.ndarray _apply_dense(self, object X): """Finds the terminal region (=leaf node) for each sample in X.""" # Check input @@ -829,7 +976,8 @@ cdef class Tree: cdef SIZE_t n_samples = X.shape[0] # Initialize output - cdef SIZE_t[:] out = np.zeros(n_samples, dtype=np.intp) + cdef np.ndarray[SIZE_t] out = np.zeros((n_samples,), dtype=np.intp) + cdef SIZE_t* out_ptr = out.data # Initialize auxiliary data-structure cdef Node* node = NULL @@ -846,11 +994,11 @@ cdef class Tree: else: node = &self.nodes[node.right_child] - out[i] = (node - self.nodes) # node offset + out_ptr[i] = (node - self.nodes) # node offset - return np.asarray(out) + return out - cdef inline cnp.ndarray _apply_sparse_csr(self, object X): + cdef inline np.ndarray _apply_sparse_csr(self, object X): """Finds the terminal region (=leaf node) for each sample in sparse X. """ # Check input @@ -862,15 +1010,21 @@ cdef class Tree: raise ValueError("X.dtype should be np.float32, got %s" % X.dtype) # Extract input - cdef const DTYPE_t[:] X_data = X.data - cdef const INT32_t[:] X_indices = X.indices - cdef const INT32_t[:] X_indptr = X.indptr + cdef np.ndarray[ndim=1, dtype=DTYPE_t] X_data_ndarray = X.data + cdef np.ndarray[ndim=1, dtype=INT32_t] X_indices_ndarray = X.indices + cdef np.ndarray[ndim=1, dtype=INT32_t] X_indptr_ndarray = X.indptr + + cdef DTYPE_t* X_data = X_data_ndarray.data + cdef INT32_t* X_indices = X_indices_ndarray.data + cdef INT32_t* X_indptr = X_indptr_ndarray.data cdef SIZE_t n_samples = X.shape[0] cdef SIZE_t n_features = X.shape[1] # Initialize output - cdef SIZE_t[:] out = np.zeros(n_samples, dtype=np.intp) + cdef np.ndarray[SIZE_t, ndim=1] out = np.zeros((n_samples,), + dtype=np.intp) + cdef SIZE_t* out_ptr = out.data # Initialize auxiliary data-structure cdef DTYPE_t feature_value = 0. @@ -911,13 +1065,13 @@ cdef class Tree: else: node = &self.nodes[node.right_child] - out[i] = (node - self.nodes) # node offset + out_ptr[i] = (node - self.nodes) # node offset # Free auxiliary arrays free(X_sample) free(feature_to_sample) - return np.asarray(out) + return out cpdef object decision_path(self, object X): """Finds the decision path (=node) for each sample in X.""" @@ -942,10 +1096,13 @@ cdef class Tree: cdef SIZE_t n_samples = X.shape[0] # Initialize output - cdef SIZE_t[:] indptr = np.zeros(n_samples + 1, dtype=np.intp) - cdef SIZE_t[:] indices = np.zeros( - n_samples * (1 + self.max_depth), dtype=np.intp - ) + cdef np.ndarray[SIZE_t] indptr = np.zeros(n_samples + 1, dtype=np.intp) + cdef SIZE_t* indptr_ptr = indptr.data + + cdef np.ndarray[SIZE_t] indices = np.zeros(n_samples * + (1 + self.max_depth), + dtype=np.intp) + cdef SIZE_t* indices_ptr = indices.data # Initialize auxiliary data-structure cdef Node* node = NULL @@ -954,13 +1111,13 @@ cdef class Tree: with nogil: for i in range(n_samples): node = self.nodes - indptr[i + 1] = indptr[i] + indptr_ptr[i + 1] = indptr_ptr[i] # Add all external nodes while node.left_child != _TREE_LEAF: # ... and node.right_child != _TREE_LEAF: - indices[indptr[i + 1]] = (node - self.nodes) - indptr[i + 1] += 1 + indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) + indptr_ptr[i + 1] += 1 if X_ndarray[i, node.feature] <= node.threshold: node = &self.nodes[node.left_child] @@ -968,11 +1125,12 @@ cdef class Tree: node = &self.nodes[node.right_child] # Add the leave node - indices[indptr[i + 1]] = (node - self.nodes) - indptr[i + 1] += 1 + indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) + indptr_ptr[i + 1] += 1 indices = indices[:indptr[n_samples]] - cdef SIZE_t[:] data = np.ones(shape=len(indices), dtype=np.intp) + cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), + dtype=np.intp) out = csr_matrix((data, indices, indptr), shape=(n_samples, self.node_count)) @@ -990,18 +1148,25 @@ cdef class Tree: raise ValueError("X.dtype should be np.float32, got %s" % X.dtype) # Extract input - cdef const DTYPE_t[:] X_data = X.data - cdef const INT32_t[:] X_indices = X.indices - cdef const INT32_t[:] X_indptr = X.indptr + cdef np.ndarray[ndim=1, dtype=DTYPE_t] X_data_ndarray = X.data + cdef np.ndarray[ndim=1, dtype=INT32_t] X_indices_ndarray = X.indices + cdef np.ndarray[ndim=1, dtype=INT32_t] X_indptr_ndarray = X.indptr + + cdef DTYPE_t* X_data = X_data_ndarray.data + cdef INT32_t* X_indices = X_indices_ndarray.data + cdef INT32_t* X_indptr = X_indptr_ndarray.data cdef SIZE_t n_samples = X.shape[0] cdef SIZE_t n_features = X.shape[1] # Initialize output - cdef SIZE_t[:] indptr = np.zeros(n_samples + 1, dtype=np.intp) - cdef SIZE_t[:] indices = np.zeros( - n_samples * (1 + self.max_depth), dtype=np.intp - ) + cdef np.ndarray[SIZE_t] indptr = np.zeros(n_samples + 1, dtype=np.intp) + cdef SIZE_t* indptr_ptr = indptr.data + + cdef np.ndarray[SIZE_t] indices = np.zeros(n_samples * + (1 + self.max_depth), + dtype=np.intp) + cdef SIZE_t* indices_ptr = indices.data # Initialize auxiliary data-structure cdef DTYPE_t feature_value = 0. @@ -1023,7 +1188,7 @@ cdef class Tree: for i in range(n_samples): node = self.nodes - indptr[i + 1] = indptr[i] + indptr_ptr[i + 1] = indptr_ptr[i] for k in range(X_indptr[i], X_indptr[i + 1]): feature_to_sample[X_indices[k]] = i @@ -1033,8 +1198,8 @@ cdef class Tree: while node.left_child != _TREE_LEAF: # ... and node.right_child != _TREE_LEAF: - indices[indptr[i + 1]] = (node - self.nodes) - indptr[i + 1] += 1 + indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) + indptr_ptr[i + 1] += 1 if feature_to_sample[node.feature] == i: feature_value = X_sample[node.feature] @@ -1048,46 +1213,21 @@ cdef class Tree: node = &self.nodes[node.right_child] # Add the leave node - indices[indptr[i + 1]] = (node - self.nodes) - indptr[i + 1] += 1 + indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) + indptr_ptr[i + 1] += 1 # Free auxiliary arrays free(X_sample) free(feature_to_sample) indices = indices[:indptr[n_samples]] - cdef SIZE_t[:] data = np.ones(shape=len(indices), dtype=np.intp) + cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), + dtype=np.intp) out = csr_matrix((data, indices, indptr), shape=(n_samples, self.node_count)) return out - cpdef compute_node_depths(self): - """Compute the depth of each node in a tree. - - .. versionadded:: 1.3 - - Returns - ------- - depths : ndarray of shape (self.node_count,), dtype=np.int64 - The depth of each node in the tree. - """ - cdef: - cnp.int64_t[::1] depths = np.empty(self.node_count, dtype=np.int64) - cnp.npy_intp[:] children_left = self.children_left - cnp.npy_intp[:] children_right = self.children_right - cnp.npy_intp node_id - cnp.npy_intp node_count = self.node_count - cnp.int64_t depth - - depths[0] = 1 # init root node - for node_id in range(node_count): - if children_left[node_id] != _TREE_LEAF: - depth = depths[node_id] + 1 - depths[children_left[node_id]] = depth - depths[children_right[node_id]] = depth - - return depths.base cpdef compute_feature_importances(self, normalize=True): """Computes the importance of each feature (aka variable).""" @@ -1099,7 +1239,9 @@ cdef class Tree: cdef double normalizer = 0. - cdef cnp.float64_t[:] importances = np.zeros(self.n_features) + cdef np.ndarray[np.float64_t, ndim=1] importances + importances = np.zeros((self.n_features,)) + cdef DOUBLE_t* importance_data = importances.data with nogil: while node != end_node: @@ -1108,297 +1250,62 @@ cdef class Tree: left = &nodes[node.left_child] right = &nodes[node.right_child] - importances[node.feature] += ( + importance_data[node.feature] += ( node.weighted_n_node_samples * node.impurity - left.weighted_n_node_samples * left.impurity - right.weighted_n_node_samples * right.impurity) node += 1 - for i in range(self.n_features): - importances[i] /= nodes[0].weighted_n_node_samples + importances /= nodes[0].weighted_n_node_samples if normalize: normalizer = np.sum(importances) if normalizer > 0.0: # Avoid dividing by zero (e.g., when root is pure) - for i in range(self.n_features): - importances[i] /= normalizer + importances /= normalizer - return np.asarray(importances) + return importances - cdef cnp.ndarray _get_value_ndarray(self): - """Wraps value as a 3-d NumPy array. + cdef np.ndarray _get_value_ndarray(self): + """Wraps value as a 2-d NumPy array. The array keeps a reference to this Tree, which manages the underlying memory. """ - cdef cnp.npy_intp shape[3] - shape[0] = self.node_count - shape[1] = self.n_outputs - shape[2] = self.max_n_classes - cdef cnp.ndarray arr - arr = cnp.PyArray_SimpleNewFromData(3, shape, cnp.NPY_DOUBLE, self.value) + cdef np.npy_intp shape[2] + shape[0] = self.node_count + shape[1] = self.K_y.shape[0] + cdef np.ndarray arr + arr = np.PyArray_SimpleNewFromData(2, shape, np.NPY_DOUBLE, self.value) Py_INCREF(self) if PyArray_SetBaseObject(arr, self) < 0: raise ValueError("Can't initialize array.") return arr - cdef cnp.ndarray _get_node_ndarray(self): + cdef np.ndarray _get_node_ndarray(self): """Wraps nodes as a NumPy struct array. The array keeps a reference to this Tree, which manages the underlying memory. Individual fields are publicly accessible as properties of the Tree. """ - cdef cnp.npy_intp shape[1] - shape[0] = self.node_count - cdef cnp.npy_intp strides[1] + cdef np.npy_intp shape[1] + shape[0] = self.node_count + cdef np.npy_intp strides[1] strides[0] = sizeof(Node) - cdef cnp.ndarray arr + cdef np.ndarray arr Py_INCREF(NODE_DTYPE) - arr = PyArray_NewFromDescr( cnp.ndarray, - NODE_DTYPE, 1, shape, + arr = PyArray_NewFromDescr( np.ndarray, + NODE_DTYPE, 1, shape, strides, self.nodes, - cnp.NPY_ARRAY_DEFAULT, None) + np.NPY_DEFAULT, None) Py_INCREF(self) if PyArray_SetBaseObject(arr, self) < 0: raise ValueError("Can't initialize array.") return arr - def compute_partial_dependence(self, DTYPE_t[:, ::1] X, - int[::1] target_features, - double[::1] out): - """Partial dependence of the response on the ``target_feature`` set. - - For each sample in ``X`` a tree traversal is performed. - Each traversal starts from the root with weight 1.0. - - At each non-leaf node that splits on a target feature, either - the left child or the right child is visited based on the feature - value of the current sample, and the weight is not modified. - At each non-leaf node that splits on a complementary feature, - both children are visited and the weight is multiplied by the fraction - of training samples which went to each child. - - At each leaf, the value of the node is multiplied by the current - weight (weights sum to 1 for all visited terminal nodes). - Parameters - ---------- - X : view on 2d ndarray, shape (n_samples, n_target_features) - The grid points on which the partial dependence should be - evaluated. - target_features : view on 1d ndarray, shape (n_target_features) - The set of target features for which the partial dependence - should be evaluated. - out : view on 1d ndarray, shape (n_samples) - The value of the partial dependence function on each grid - point. - """ - cdef: - double[::1] weight_stack = np.zeros(self.node_count, - dtype=np.float64) - SIZE_t[::1] node_idx_stack = np.zeros(self.node_count, - dtype=np.intp) - SIZE_t sample_idx - SIZE_t feature_idx - int stack_size - double left_sample_frac - double current_weight - double total_weight # used for sanity check only - Node *current_node # use a pointer to avoid copying attributes - SIZE_t current_node_idx - bint is_target_feature - SIZE_t _TREE_LEAF = TREE_LEAF # to avoid python interactions - - for sample_idx in range(X.shape[0]): - # init stacks for current sample - stack_size = 1 - node_idx_stack[0] = 0 # root node - weight_stack[0] = 1 # all the samples are in the root node - total_weight = 0 - - while stack_size > 0: - # pop the stack - stack_size -= 1 - current_node_idx = node_idx_stack[stack_size] - current_node = &self.nodes[current_node_idx] - - if current_node.left_child == _TREE_LEAF: - # leaf node - out[sample_idx] += (weight_stack[stack_size] * - self.value[current_node_idx]) - total_weight += weight_stack[stack_size] - else: - # non-leaf node - - # determine if the split feature is a target feature - is_target_feature = False - for feature_idx in range(target_features.shape[0]): - if target_features[feature_idx] == current_node.feature: - is_target_feature = True - break - - if is_target_feature: - # In this case, we push left or right child on stack - if X[sample_idx, feature_idx] <= current_node.threshold: - node_idx_stack[stack_size] = current_node.left_child - else: - node_idx_stack[stack_size] = current_node.right_child - stack_size += 1 - else: - # In this case, we push both children onto the stack, - # and give a weight proportional to the number of - # samples going through each branch. - - # push left child - node_idx_stack[stack_size] = current_node.left_child - left_sample_frac = ( - self.nodes[current_node.left_child].weighted_n_node_samples / - current_node.weighted_n_node_samples) - current_weight = weight_stack[stack_size] - weight_stack[stack_size] = current_weight * left_sample_frac - stack_size += 1 - - # push right child - node_idx_stack[stack_size] = current_node.right_child - weight_stack[stack_size] = ( - current_weight * (1 - left_sample_frac)) - stack_size += 1 - - # Sanity check. Should never happen. - if not (0.999 < total_weight < 1.001): - raise ValueError("Total weight should be 1.0 but was %.9f" % - total_weight) - - -def _check_n_classes(n_classes, expected_dtype): - if n_classes.ndim != 1: - raise ValueError( - f"Wrong dimensions for n_classes from the pickle: " - f"expected 1, got {n_classes.ndim}" - ) - - if n_classes.dtype == expected_dtype: - return n_classes - - # Handles both different endianness and different bitness - if n_classes.dtype.kind == "i" and n_classes.dtype.itemsize in [4, 8]: - return n_classes.astype(expected_dtype, casting="same_kind") - - raise ValueError( - "n_classes from the pickle has an incompatible dtype:\n" - f"- expected: {expected_dtype}\n" - f"- got: {n_classes.dtype}" - ) - - -def _check_value_ndarray(value_ndarray, expected_dtype, expected_shape): - if value_ndarray.shape != expected_shape: - raise ValueError( - "Wrong shape for value array from the pickle: " - f"expected {expected_shape}, got {value_ndarray.shape}" - ) - - if not value_ndarray.flags.c_contiguous: - raise ValueError( - "value array from the pickle should be a C-contiguous array" - ) - - if value_ndarray.dtype == expected_dtype: - return value_ndarray - - # Handles different endianness - if value_ndarray.dtype.str.endswith('f8'): - return value_ndarray.astype(expected_dtype, casting='equiv') - - raise ValueError( - "value array from the pickle has an incompatible dtype:\n" - f"- expected: {expected_dtype}\n" - f"- got: {value_ndarray.dtype}" - ) - - -def _dtype_to_dict(dtype): - return {name: dt.str for name, (dt, *rest) in dtype.fields.items()} - - -def _dtype_dict_with_modified_bitness(dtype_dict): - # field names in Node struct with SIZE_t types (see sklearn/tree/_tree.pxd) - indexing_field_names = ["left_child", "right_child", "feature", "n_node_samples"] - - expected_dtype_size = str(struct.calcsize("P")) - allowed_dtype_size = "8" if expected_dtype_size == "4" else "4" - - allowed_dtype_dict = dtype_dict.copy() - for name in indexing_field_names: - allowed_dtype_dict[name] = allowed_dtype_dict[name].replace( - expected_dtype_size, allowed_dtype_size - ) - - return allowed_dtype_dict - - -def _all_compatible_dtype_dicts(dtype): - # The Cython code for decision trees uses platform-specific SIZE_t - # typed indexing fields that correspond to either i4 or i8 dtypes for - # the matching fields in the numpy array depending on the bitness of - # the platform (32 bit or 64 bit respectively). - # - # We need to cast the indexing fields of the NODE_DTYPE-dtyped array at - # pickle load time to enable cross-bitness deployment scenarios. We - # typically want to make it possible to run the expensive fit method of - # a tree estimator on a 64 bit server platform, pickle the estimator - # for deployment and run the predict method of a low power 32 bit edge - # platform. - # - # A similar thing happens for endianness, the machine where the pickle was - # saved can have a different endianness than the machine where the pickle - # is loaded - - dtype_dict = _dtype_to_dict(dtype) - dtype_dict_with_modified_bitness = _dtype_dict_with_modified_bitness(dtype_dict) - dtype_dict_with_modified_endianness = _dtype_to_dict(dtype.newbyteorder()) - dtype_dict_with_modified_bitness_and_endianness = _dtype_dict_with_modified_bitness( - dtype_dict_with_modified_endianness - ) - - return [ - dtype_dict, - dtype_dict_with_modified_bitness, - dtype_dict_with_modified_endianness, - dtype_dict_with_modified_bitness_and_endianness, - ] - - -def _check_node_ndarray(node_ndarray, expected_dtype): - if node_ndarray.ndim != 1: - raise ValueError( - "Wrong dimensions for node array from the pickle: " - f"expected 1, got {node_ndarray.ndim}" - ) - - if not node_ndarray.flags.c_contiguous: - raise ValueError( - "node array from the pickle should be a C-contiguous array" - ) - - node_ndarray_dtype = node_ndarray.dtype - if node_ndarray_dtype == expected_dtype: - return node_ndarray - - node_ndarray_dtype_dict = _dtype_to_dict(node_ndarray_dtype) - all_compatible_dtype_dicts = _all_compatible_dtype_dicts(expected_dtype) - - if node_ndarray_dtype_dict not in all_compatible_dtype_dicts: - raise ValueError( - "node array from the pickle has an incompatible dtype:\n" - f"- expected: {expected_dtype}\n" - f"- got : {node_ndarray_dtype}" - ) - - return node_ndarray.astype(expected_dtype, casting="same_kind") # ============================================================================= @@ -1410,16 +1317,16 @@ cdef class _CCPPruneController: """Base class used by build_pruned_tree_ccp and ccp_pruning_path to control pruning. """ - cdef bint stop_pruning(self, DOUBLE_t effective_alpha) noexcept nogil: + cdef bint stop_pruning(self, DOUBLE_t effective_alpha) nogil: """Return 1 to stop pruning and 0 to continue pruning""" return 0 cdef void save_metrics(self, DOUBLE_t effective_alpha, - DOUBLE_t subtree_impurities) noexcept nogil: + DOUBLE_t subtree_impurities) nogil: """Save metrics when pruning""" pass - cdef void after_pruning(self, unsigned char[:] in_subtree) noexcept nogil: + cdef void after_pruning(self, unsigned char[:] in_subtree) nogil: """Called after pruning""" pass @@ -1433,12 +1340,12 @@ cdef class _AlphaPruner(_CCPPruneController): self.ccp_alpha = ccp_alpha self.capacity = 0 - cdef bint stop_pruning(self, DOUBLE_t effective_alpha) noexcept nogil: + cdef bint stop_pruning(self, DOUBLE_t effective_alpha) nogil: # The subtree on the previous iteration has the greatest ccp_alpha # less than or equal to self.ccp_alpha return self.ccp_alpha < effective_alpha - cdef void after_pruning(self, unsigned char[:] in_subtree) noexcept nogil: + cdef void after_pruning(self, unsigned char[:] in_subtree) nogil: """Updates the number of leaves in subtree""" for i in range(in_subtree.shape[0]): if in_subtree[i]: @@ -1458,26 +1365,21 @@ cdef class _PathFinder(_CCPPruneController): cdef void save_metrics(self, DOUBLE_t effective_alpha, - DOUBLE_t subtree_impurities) noexcept nogil: + DOUBLE_t subtree_impurities) nogil: self.ccp_alphas[self.count] = effective_alpha self.impurities[self.count] = subtree_impurities self.count += 1 -cdef struct CostComplexityPruningRecord: - SIZE_t node_idx - SIZE_t parent - cdef _cost_complexity_prune(unsigned char[:] leaves_in_subtree, # OUT Tree orig_tree, _CCPPruneController controller): """Perform cost complexity pruning. This function takes an already grown tree, `orig_tree` and outputs a - boolean mask `leaves_in_subtree` which are the leaves in the pruned tree. - During the pruning process, the controller is passed the effective alpha and - the subtree impurities. Furthermore, the controller signals when to stop - pruning. + boolean mask `leaves_in_subtree` to are the leaves in the pruned tree. The + controller signals when the pruning should stop and is passed the + metrics of the subtrees during the pruning process. Parameters ---------- @@ -1503,10 +1405,11 @@ cdef _cost_complexity_prune(unsigned char[:] leaves_in_subtree, # OUT SIZE_t[:] child_r = orig_tree.children_right SIZE_t[:] parent = np.zeros(shape=n_nodes, dtype=np.intp) - stack[CostComplexityPruningRecord] ccp_stack - CostComplexityPruningRecord stack_record + # Only uses the start and parent variables + Stack stack = Stack(INITIAL_STACK_SIZE) + StackRecord stack_record + int rc = 0 SIZE_t node_idx - stack[SIZE_t] node_indices_stack SIZE_t[:] n_leaves = np.zeros(shape=n_nodes, dtype=np.intp) DOUBLE_t[:] r_branch = np.zeros(shape=n_nodes, dtype=np.float64) @@ -1519,9 +1422,12 @@ cdef _cost_complexity_prune(unsigned char[:] leaves_in_subtree, # OUT dtype=np.uint8) # nodes in subtree unsigned char[:] in_subtree = np.ones(shape=n_nodes, dtype=np.uint8) + DOUBLE_t[:] g_node = np.zeros(shape=n_nodes, dtype=np.float64) SIZE_t pruned_branch_node_idx DOUBLE_t subtree_alpha DOUBLE_t effective_alpha + SIZE_t child_l_idx + SIZE_t child_r_idx SIZE_t n_pruned_leaves DOUBLE_t r_diff DOUBLE_t max_float64 = np.finfo(np.float64).max @@ -1533,22 +1439,29 @@ cdef _cost_complexity_prune(unsigned char[:] leaves_in_subtree, # OUT r_node[i] = ( weighted_n_node_samples[i] * impurity[i] / total_sum_weights) - # Push the root node - ccp_stack.push({"node_idx": 0, "parent": _TREE_UNDEFINED}) - - while not ccp_stack.empty(): - stack_record = ccp_stack.top() - ccp_stack.pop() + # Push root node, using StackRecord.start as node id + rc = stack.push(0, 0, 0, -1, 0, 0, 0) + if rc == -1: + with gil: + raise MemoryError("pruning tree") - node_idx = stack_record.node_idx + while not stack.is_empty(): + stack.pop(&stack_record) + node_idx = stack_record.start parent[node_idx] = stack_record.parent - if child_l[node_idx] == _TREE_LEAF: # ... and child_r[node_idx] == _TREE_LEAF: leaves_in_subtree[node_idx] = 1 else: - ccp_stack.push({"node_idx": child_l[node_idx], "parent": node_idx}) - ccp_stack.push({"node_idx": child_r[node_idx], "parent": node_idx}) + rc = stack.push(child_l[node_idx], 0, 0, node_idx, 0, 0, 0) + if rc == -1: + with gil: + raise MemoryError("pruning tree") + + rc = stack.push(child_r[node_idx], 0, 0, node_idx, 0, 0, 0) + if rc == -1: + with gil: + raise MemoryError("pruning tree") # computes number of leaves in all branches and the overall impurity of # the branch. The overall impurity is the sum of r_node in its leaves. @@ -1587,12 +1500,16 @@ cdef _cost_complexity_prune(unsigned char[:] leaves_in_subtree, # OUT if controller.stop_pruning(effective_alpha): break - node_indices_stack.push(pruned_branch_node_idx) + # stack uses only the start variable + rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) + if rc == -1: + with gil: + raise MemoryError("pruning tree") # descendants of branch are not in subtree - while not node_indices_stack.empty(): - node_idx = node_indices_stack.top() - node_indices_stack.pop() + while not stack.is_empty(): + stack.pop(&stack_record) + node_idx = stack_record.start if not in_subtree[node_idx]: continue # branch has already been marked for pruning @@ -1602,8 +1519,14 @@ cdef _cost_complexity_prune(unsigned char[:] leaves_in_subtree, # OUT if child_l[node_idx] != _TREE_LEAF: # ... and child_r[node_idx] != _TREE_LEAF: - node_indices_stack.push(child_l[node_idx]) - node_indices_stack.push(child_r[node_idx]) + rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) + if rc == -1: + with gil: + raise MemoryError("pruning tree") + rc = stack.push(child_r[node_idx], 0, 0, 0, 0, 0, 0) + if rc == -1: + with gil: + raise MemoryError("pruning tree") leaves_in_subtree[pruned_branch_node_idx] = 1 in_subtree[pruned_branch_node_idx] = 1 @@ -1617,7 +1540,7 @@ cdef _cost_complexity_prune(unsigned char[:] leaves_in_subtree, # OUT # bubble up values to ancestors node_idx = parent[pruned_branch_node_idx] - while node_idx != _TREE_UNDEFINED: + while node_idx != -1: n_leaves[node_idx] -= n_pruned_leaves r_branch[node_idx] += r_diff node_idx = parent[node_idx] @@ -1692,8 +1615,10 @@ def ccp_pruning_path(Tree orig_tree): cdef: UINT32_t total_items = path_finder.count - DOUBLE_t[:] ccp_alphas = np.empty(shape=total_items, dtype=np.float64) - DOUBLE_t[:] impurities = np.empty(shape=total_items, dtype=np.float64) + np.ndarray ccp_alphas = np.empty(shape=total_items, + dtype=np.float64) + np.ndarray impurities = np.empty(shape=total_items, + dtype=np.float64) UINT32_t count = 0 while count < total_items: @@ -1701,17 +1626,8 @@ def ccp_pruning_path(Tree orig_tree): impurities[count] = path_finder.impurities[count] count += 1 - return { - 'ccp_alphas': np.asarray(ccp_alphas), - 'impurities': np.asarray(impurities), - } - + return {'ccp_alphas': ccp_alphas, 'impurities': impurities} -cdef struct BuildPrunedRecord: - SIZE_t start - SIZE_t depth - SIZE_t parent - bint is_left cdef _build_pruned_tree( Tree tree, # OUT @@ -1744,24 +1660,25 @@ cdef _build_pruned_tree( bint is_left bint is_leaf - # value_stride for original tree and new tree are the same - SIZE_t value_stride = orig_tree.value_stride SIZE_t max_depth_seen = -1 int rc = 0 Node* node double* orig_value_ptr double* new_value_ptr - stack[BuildPrunedRecord] prune_stack - BuildPrunedRecord stack_record + # Only uses the start, depth, parent, and is_left variables + Stack stack = Stack(INITIAL_STACK_SIZE) + StackRecord stack_record with nogil: # push root node onto stack - prune_stack.push({"start": 0, "depth": 0, "parent": _TREE_UNDEFINED, "is_left": 0}) + rc = stack.push(0, 0, 0, _TREE_UNDEFINED, 0, 0.0, 0) + if rc == -1: + with gil: + raise MemoryError("pruning tree") - while not prune_stack.empty(): - stack_record = prune_stack.top() - prune_stack.pop() + while not stack.is_empty(): + stack.pop(&stack_record) orig_node_id = stack_record.start depth = stack_record.depth @@ -1776,27 +1693,35 @@ cdef _build_pruned_tree( node.impurity, node.n_node_samples, node.weighted_n_node_samples) - if new_node_id == INTPTR_MAX: + if new_node_id == SIZE_MAX: rc = -1 break # copy value from original tree to new tree - orig_value_ptr = orig_tree.value + value_stride * orig_node_id - new_value_ptr = tree.value + value_stride * new_node_id - memcpy(new_value_ptr, orig_value_ptr, sizeof(double) * value_stride) + orig_value_ptr = orig_tree.value + tree.K_y.shape[0] * orig_node_id + new_value_ptr = tree.value + tree.K_y.shape[0] * new_node_id + memcpy(new_value_ptr, orig_value_ptr, sizeof(double) * tree.K_y.shape[0]) if not is_leaf: # Push right child on stack - prune_stack.push({"start": node.right_child, "depth": depth + 1, - "parent": new_node_id, "is_left": 0}) + rc = stack.push( + node.right_child, 0, depth + 1, new_node_id, 0, 0.0, 0) + if rc == -1: + break + # push left child on stack - prune_stack.push({"start": node.left_child, "depth": depth + 1, - "parent": new_node_id, "is_left": 1}) + rc = stack.push( + node.left_child, 0, depth + 1, new_node_id, 1, 0.0, 0) + if rc == -1: + break if depth > max_depth_seen: max_depth_seen = depth if rc >= 0: tree.max_depth = max_depth_seen + + tree.K_y = orig_tree.K_y + tree.y = orig_tree.y if rc == -1: raise MemoryError("pruning tree") diff --git a/stpredictions/models/OK3/_utils.pyx b/stpredictions/models/OK3/_utils.pyx deleted file mode 100644 index 0bde50c31..000000000 --- a/stpredictions/models/OK3/_utils.pyx +++ /dev/null @@ -1,447 +0,0 @@ -# Authors: Gilles Louppe -# Peter Prettenhofer -# Arnaud Joly -# Jacob Schreiber -# Nelson Liu -# -# -# License: BSD 3 clause - -from libc.stdlib cimport free -from libc.stdlib cimport realloc -from libc.math cimport log as ln - -cimport numpy as cnp -cnp.import_array() - -from ..utils._random cimport our_rand_r - -# ============================================================================= -# Helper functions -# ============================================================================= - -cdef realloc_ptr safe_realloc(realloc_ptr* p, size_t nelems) except * nogil: - # sizeof(realloc_ptr[0]) would be more like idiomatic C, but causes Cython - # 0.20.1 to crash. - cdef size_t nbytes = nelems * sizeof(p[0][0]) - if nbytes / sizeof(p[0][0]) != nelems: - # Overflow in the multiplication - with gil: - raise MemoryError("could not allocate (%d * %d) bytes" - % (nelems, sizeof(p[0][0]))) - cdef realloc_ptr tmp = realloc(p[0], nbytes) - if tmp == NULL: - with gil: - raise MemoryError("could not allocate %d bytes" % nbytes) - - p[0] = tmp - return tmp # for convenience - - -def _realloc_test(): - # Helper for tests. Tries to allocate (-1) / 2 * sizeof(size_t) - # bytes, which will always overflow. - cdef SIZE_t* p = NULL - safe_realloc(&p, (-1) / 2) - if p != NULL: - free(p) - assert False - - -cdef inline cnp.ndarray sizet_ptr_to_ndarray(SIZE_t* data, SIZE_t size): - """Return copied data as 1D numpy array of intp's.""" - cdef cnp.npy_intp shape[1] - shape[0] = size - return cnp.PyArray_SimpleNewFromData(1, shape, cnp.NPY_INTP, data).copy() - - -cdef inline SIZE_t rand_int(SIZE_t low, SIZE_t high, - UINT32_t* random_state) noexcept nogil: - """Generate a random integer in [low; end).""" - return low + our_rand_r(random_state) % (high - low) - - -cdef inline double rand_uniform(double low, double high, - UINT32_t* random_state) noexcept nogil: - """Generate a random double in [low; high).""" - return ((high - low) * our_rand_r(random_state) / - RAND_R_MAX) + low - - -cdef inline double log(double x) noexcept nogil: - return ln(x) / ln(2.0) - -# ============================================================================= -# WeightedPQueue data structure -# ============================================================================= - -cdef class WeightedPQueue: - """A priority queue class, always sorted in increasing order. - - Attributes - ---------- - capacity : SIZE_t - The capacity of the priority queue. - - array_ptr : SIZE_t - The water mark of the priority queue; the priority queue grows from - left to right in the array ``array_``. ``array_ptr`` is always - less than ``capacity``. - - array_ : WeightedPQueueRecord* - The array of priority queue records. The minimum element is on the - left at index 0, and the maximum element is on the right at index - ``array_ptr-1``. - """ - - def __cinit__(self, SIZE_t capacity): - self.capacity = capacity - self.array_ptr = 0 - safe_realloc(&self.array_, capacity) - - def __dealloc__(self): - free(self.array_) - - cdef int reset(self) except -1 nogil: - """Reset the WeightedPQueue to its state at construction - - Return -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - self.array_ptr = 0 - # Since safe_realloc can raise MemoryError, use `except *` - safe_realloc(&self.array_, self.capacity) - return 0 - - cdef bint is_empty(self) noexcept nogil: - return self.array_ptr <= 0 - - cdef SIZE_t size(self) noexcept nogil: - return self.array_ptr - - cdef int push(self, DOUBLE_t data, DOUBLE_t weight) except -1 nogil: - """Push record on the array. - - Return -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - cdef SIZE_t array_ptr = self.array_ptr - cdef WeightedPQueueRecord* array = NULL - cdef SIZE_t i - - # Resize if capacity not sufficient - if array_ptr >= self.capacity: - self.capacity *= 2 - # Since safe_realloc can raise MemoryError, use `except -1` - safe_realloc(&self.array_, self.capacity) - - # Put element as last element of array - array = self.array_ - array[array_ptr].data = data - array[array_ptr].weight = weight - - # bubble last element up according until it is sorted - # in ascending order - i = array_ptr - while(i != 0 and array[i].data < array[i-1].data): - array[i], array[i-1] = array[i-1], array[i] - i -= 1 - - # Increase element count - self.array_ptr = array_ptr + 1 - return 0 - - cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) noexcept nogil: - """Remove a specific value/weight record from the array. - Returns 0 if successful, -1 if record not found.""" - cdef SIZE_t array_ptr = self.array_ptr - cdef WeightedPQueueRecord* array = self.array_ - cdef SIZE_t idx_to_remove = -1 - cdef SIZE_t i - - if array_ptr <= 0: - return -1 - - # find element to remove - for i in range(array_ptr): - if array[i].data == data and array[i].weight == weight: - idx_to_remove = i - break - - if idx_to_remove == -1: - return -1 - - # shift the elements after the removed element - # to the left. - for i in range(idx_to_remove, array_ptr-1): - array[i] = array[i+1] - - self.array_ptr = array_ptr - 1 - return 0 - - cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) noexcept nogil: - """Remove the top (minimum) element from array. - Returns 0 if successful, -1 if nothing to remove.""" - cdef SIZE_t array_ptr = self.array_ptr - cdef WeightedPQueueRecord* array = self.array_ - cdef SIZE_t i - - if array_ptr <= 0: - return -1 - - data[0] = array[0].data - weight[0] = array[0].weight - - # shift the elements after the removed element - # to the left. - for i in range(0, array_ptr-1): - array[i] = array[i+1] - - self.array_ptr = array_ptr - 1 - return 0 - - cdef int peek(self, DOUBLE_t* data, DOUBLE_t* weight) noexcept nogil: - """Write the top element from array to a pointer. - Returns 0 if successful, -1 if nothing to write.""" - cdef WeightedPQueueRecord* array = self.array_ - if self.array_ptr <= 0: - return -1 - # Take first value - data[0] = array[0].data - weight[0] = array[0].weight - return 0 - - cdef DOUBLE_t get_weight_from_index(self, SIZE_t index) noexcept nogil: - """Given an index between [0,self.current_capacity], access - the appropriate heap and return the requested weight""" - cdef WeightedPQueueRecord* array = self.array_ - - # get weight at index - return array[index].weight - - cdef DOUBLE_t get_value_from_index(self, SIZE_t index) noexcept nogil: - """Given an index between [0,self.current_capacity], access - the appropriate heap and return the requested value""" - cdef WeightedPQueueRecord* array = self.array_ - - # get value at index - return array[index].data - -# ============================================================================= -# WeightedMedianCalculator data structure -# ============================================================================= - -cdef class WeightedMedianCalculator: - """A class to handle calculation of the weighted median from streams of - data. To do so, it maintains a parameter ``k`` such that the sum of the - weights in the range [0,k) is greater than or equal to half of the total - weight. By minimizing the value of ``k`` that fulfills this constraint, - calculating the median is done by either taking the value of the sample - at index ``k-1`` of ``samples`` (samples[k-1].data) or the average of - the samples at index ``k-1`` and ``k`` of ``samples`` - ((samples[k-1] + samples[k]) / 2). - - Attributes - ---------- - initial_capacity : SIZE_t - The initial capacity of the WeightedMedianCalculator. - - samples : WeightedPQueue - Holds the samples (consisting of values and their weights) used in the - weighted median calculation. - - total_weight : DOUBLE_t - The sum of the weights of items in ``samples``. Represents the total - weight of all samples used in the median calculation. - - k : SIZE_t - Index used to calculate the median. - - sum_w_0_k : DOUBLE_t - The sum of the weights from samples[0:k]. Used in the weighted - median calculation; minimizing the value of ``k`` such that - ``sum_w_0_k`` >= ``total_weight / 2`` provides a mechanism for - calculating the median in constant time. - - """ - - def __cinit__(self, SIZE_t initial_capacity): - self.initial_capacity = initial_capacity - self.samples = WeightedPQueue(initial_capacity) - self.total_weight = 0 - self.k = 0 - self.sum_w_0_k = 0 - - cdef SIZE_t size(self) noexcept nogil: - """Return the number of samples in the - WeightedMedianCalculator""" - return self.samples.size() - - cdef int reset(self) except -1 nogil: - """Reset the WeightedMedianCalculator to its state at construction - - Return -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - # samples.reset (WeightedPQueue.reset) uses safe_realloc, hence - # except -1 - self.samples.reset() - self.total_weight = 0 - self.k = 0 - self.sum_w_0_k = 0 - return 0 - - cdef int push(self, DOUBLE_t data, DOUBLE_t weight) except -1 nogil: - """Push a value and its associated weight to the WeightedMedianCalculator - - Return -1 in case of failure to allocate memory (and raise MemoryError) - or 0 otherwise. - """ - cdef int return_value - cdef DOUBLE_t original_median = 0.0 - - if self.size() != 0: - original_median = self.get_median() - # samples.push (WeightedPQueue.push) uses safe_realloc, hence except -1 - return_value = self.samples.push(data, weight) - self.update_median_parameters_post_push(data, weight, - original_median) - return return_value - - cdef int update_median_parameters_post_push( - self, DOUBLE_t data, DOUBLE_t weight, - DOUBLE_t original_median) noexcept nogil: - """Update the parameters used in the median calculation, - namely `k` and `sum_w_0_k` after an insertion""" - - # trivial case of one element. - if self.size() == 1: - self.k = 1 - self.total_weight = weight - self.sum_w_0_k = self.total_weight - return 0 - - # get the original weighted median - self.total_weight += weight - - if data < original_median: - # inserting below the median, so increment k and - # then update self.sum_w_0_k accordingly by adding - # the weight that was added. - self.k += 1 - # update sum_w_0_k by adding the weight added - self.sum_w_0_k += weight - - # minimize k such that sum(W[0:k]) >= total_weight / 2 - # minimum value of k is 1 - while(self.k > 1 and ((self.sum_w_0_k - - self.samples.get_weight_from_index(self.k-1)) - >= self.total_weight / 2.0)): - self.k -= 1 - self.sum_w_0_k -= self.samples.get_weight_from_index(self.k) - return 0 - - if data >= original_median: - # inserting above or at the median - # minimize k such that sum(W[0:k]) >= total_weight / 2 - while(self.k < self.samples.size() and - (self.sum_w_0_k < self.total_weight / 2.0)): - self.k += 1 - self.sum_w_0_k += self.samples.get_weight_from_index(self.k-1) - return 0 - - cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) noexcept nogil: - """Remove a value from the MedianHeap, removing it - from consideration in the median calculation - """ - cdef int return_value - cdef DOUBLE_t original_median = 0.0 - - if self.size() != 0: - original_median = self.get_median() - - return_value = self.samples.remove(data, weight) - self.update_median_parameters_post_remove(data, weight, - original_median) - return return_value - - cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) noexcept nogil: - """Pop a value from the MedianHeap, starting from the - left and moving to the right. - """ - cdef int return_value - cdef double original_median = 0.0 - - if self.size() != 0: - original_median = self.get_median() - - # no elements to pop - if self.samples.size() == 0: - return -1 - - return_value = self.samples.pop(data, weight) - self.update_median_parameters_post_remove(data[0], - weight[0], - original_median) - return return_value - - cdef int update_median_parameters_post_remove( - self, DOUBLE_t data, DOUBLE_t weight, - double original_median) noexcept nogil: - """Update the parameters used in the median calculation, - namely `k` and `sum_w_0_k` after a removal""" - # reset parameters because it there are no elements - if self.samples.size() == 0: - self.k = 0 - self.total_weight = 0 - self.sum_w_0_k = 0 - return 0 - - # trivial case of one element. - if self.samples.size() == 1: - self.k = 1 - self.total_weight -= weight - self.sum_w_0_k = self.total_weight - return 0 - - # get the current weighted median - self.total_weight -= weight - - if data < original_median: - # removing below the median, so decrement k and - # then update self.sum_w_0_k accordingly by subtracting - # the removed weight - - self.k -= 1 - # update sum_w_0_k by removing the weight at index k - self.sum_w_0_k -= weight - - # minimize k such that sum(W[0:k]) >= total_weight / 2 - # by incrementing k and updating sum_w_0_k accordingly - # until the condition is met. - while(self.k < self.samples.size() and - (self.sum_w_0_k < self.total_weight / 2.0)): - self.k += 1 - self.sum_w_0_k += self.samples.get_weight_from_index(self.k-1) - return 0 - - if data >= original_median: - # removing above the median - # minimize k such that sum(W[0:k]) >= total_weight / 2 - while(self.k > 1 and ((self.sum_w_0_k - - self.samples.get_weight_from_index(self.k-1)) - >= self.total_weight / 2.0)): - self.k -= 1 - self.sum_w_0_k -= self.samples.get_weight_from_index(self.k) - return 0 - - cdef DOUBLE_t get_median(self) noexcept nogil: - """Write the median to a pointer, taking into account - sample weights.""" - if self.sum_w_0_k == (self.total_weight / 2.0): - # split median - return (self.samples.get_value_from_index(self.k) + - self.samples.get_value_from_index(self.k-1)) / 2.0 - if self.sum_w_0_k > (self.total_weight / 2.0): - # whole median - return self.samples.get_value_from_index(self.k-1) diff --git a/stpredictions/models/OK3/extra/_criterion.c b/stpredictions/models/OK3/extra/_criterion.c deleted file mode 100644 index 06f2230dd..000000000 --- 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Raw output: _criterion.c

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+001: # cython: cdivision=True
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 002: # cython: boundscheck=False
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 003: # cython: wraparound=False
-
 004:
-
 005: from libc.stdlib cimport calloc
-
 006: from libc.stdlib cimport free
-
 007: from libc.string cimport memcpy
-
 008: from libc.string cimport memset
-
 009: from libc.math cimport fabs
-
 010:
-
+011: import numpy as np
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  __pyx_t_1 = __Pyx_Import(__pyx_n_s_numpy, 0, -1); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 11, __pyx_L1_error)
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-  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
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 012: cimport numpy as np
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+013: np.import_array()
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-
 014:
-
 015: from sklearn.tree._utils cimport log
-
 016: from sklearn.tree._utils cimport safe_realloc
-
 017: from sklearn.tree._utils cimport sizet_ptr_to_ndarray
-
 018: from sklearn.tree._utils cimport WeightedMedianCalculator
-
 019:
-
 020: # from kernel import Kernel
-
 021:
-
+022: cdef class Criterion:
-
struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion {
-  int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t);
-  int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *);
-  int (*reverse_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *);
-  int (*update)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t);
-  double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *);
-  void (*children_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *, double *);
-  void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *);
-  double (*impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double);
-  double (*proxy_impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *);
-};
-static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion;
-
-
 023:     """Interface for impurity criteria.
-
 024:
-
 025:     This object stores methods on how to calculate how good a split is using
-
 026:     different metrics.
-
 027:     """
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 028:
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+029:     def __dealloc__(self):
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 030:         """Destructor."""
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 031:
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 032:         pass
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 033:
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+037:     def __setstate__(self, d):
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/* Python wrapper */
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 038:         pass
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 039:
-
+040:     cdef int init(self, const DOUBLE_t[:, ::1] y, DOUBLE_t* sample_weight,
-
static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_init(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_y, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, CYTHON_UNUSED double __pyx_v_weighted_n_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end) {
-  int __pyx_r;
-
-  /* function exit code */
-  __pyx_r = 0;
-  return __pyx_r;
-}
-
 041:                   double weighted_n_samples, SIZE_t* samples, SIZE_t start,
-
 042:                   SIZE_t end) nogil except -1:
-
 043:         """Placeholder for a method which will initialize the criterion.
-
 044:
-
 045:         Returns -1 in case of failure to allocate memory (and raise MemoryError)
-
 046:         or 0 otherwise.
-
 047:
-
 048:         Parameters
-
 049:         ----------
-
 050:         y : array-like, dtype=DOUBLE_t
-
 051:             y is a buffer that stores values of the output Gramm matrix of the samples
-
 052:         sample_weight : array-like, dtype=DOUBLE_t
-
 053:             The weight of each sample
-
 054:         weighted_n_samples : double
-
 055:             The total weight of the samples being considered
-
 056:         samples : array-like, dtype=SIZE_t
-
 057:             Indices of the samples in X and y, where samples[start:end]
-
 058:             correspond to the samples in this node
-
 059:         start : SIZE_t
-
 060:             The first sample to be used on this node
-
 061:         end : SIZE_t
-
 062:             The last sample used on this node
-
 063:
-
 064:         """
-
 065:
-
 066:         pass
-
 067:
-
+068:     cdef int reset(self) nogil except -1:
-
static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_reset(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self) {
-  int __pyx_r;
-
-  /* function exit code */
-  __pyx_r = 0;
-  return __pyx_r;
-}
-
 069:         """Reset the criterion at pos=start.
-
 070:
-
 071:         This method must be implemented by the subclass.
-
 072:         """
-
 073:
-
 074:         pass
-
 075:
-
+076:     cdef int reverse_reset(self) nogil except -1:
-
static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_reverse_reset(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self) {
-  int __pyx_r;
-
-  /* function exit code */
-  __pyx_r = 0;
-  return __pyx_r;
-}
-
 077:         """Reset the criterion at pos=end.
-
 078:
-
 079:         This method must be implemented by the subclass.
-
 080:         """
-
 081:         pass
-
 082:
-
+083:     cdef int update(self, SIZE_t new_pos) nogil except -1:
-
static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_update(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos) {
-  int __pyx_r;
-
-  /* function exit code */
-  __pyx_r = 0;
-  return __pyx_r;
-}
-
 084:         """Updated statistics by moving samples[pos:new_pos] to the left child.
-
 085:
-
 086:         This updates the collected statistics by moving samples[pos:new_pos]
-
 087:         from the right child to the left child. It must be implemented by
-
 088:         the subclass.
-
 089:
-
 090:         Parameters
-
 091:         ----------
-
 092:         new_pos : SIZE_t
-
 093:             New starting index position of the samples in the right child
-
 094:         """
-
 095:
-
 096:         pass
-
 097:
-
+098:     cdef double node_impurity(self) nogil:
-
static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self) {
-  double __pyx_r;
-
-  /* function exit code */
-  __pyx_r = 0;
-  return __pyx_r;
-}
-
 099:         """Placeholder for calculating the impurity of the node.
-
 100:
-
 101:         Placeholder for a method which will evaluate the impurity of
-
 102:         the current node, i.e. the impurity of samples[start:end]. This is the
-
 103:         primary function of the criterion class.
-
 104:         """
-
 105:
-
 106:         pass
-
 107:
-
+108:     cdef void children_impurity(self, double* impurity_left,
-
static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) {
-
-  /* function exit code */
-}
-
 109:                                 double* impurity_right) nogil:
-
 110:         """Placeholder for calculating the impurity of children.
-
 111:
-
 112:         Placeholder for a method which evaluates the impurity in
-
 113:         children nodes, i.e. the impurity of samples[start:pos] + the impurity
-
 114:         of samples[pos:end].
-
 115:
-
 116:         Parameters
-
 117:         ----------
-
 118:         impurity_left : double pointer
-
 119:             The memory address where the impurity of the left child should be
-
 120:             stored.
-
 121:         impurity_right : double pointer
-
 122:             The memory address where the impurity of the right child should be
-
 123:             stored
-
 124:         """
-
 125:
-
 126:         pass
-
 127:
-
+128:     cdef void node_value(self, double* dest) nogil:
-
static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_node_value(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_dest) {
-
-  /* function exit code */
-}
-
 129:         """Placeholder for storing the node value.
-
 130:
-
 131:         Placeholder for a method which will save the weighted
-
 132:         samples[start:end] into dest.
-
 133:
-
 134:         Parameters
-
 135:         ----------
-
 136:         dest : double pointer
-
 137:             The memory address where the node value should be stored.
-
 138:         """
-
 139:
-
 140:         pass
-
 141:
-
+142:     cdef double proxy_impurity_improvement(self) nogil:
-
static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_proxy_impurity_improvement(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self) {
-  double __pyx_r;
-
-  /* function exit code */
-  __pyx_r = 0;
-  return __pyx_r;
-}
-
 143:         """Compute a proxy of the impurity reduction
-
 144:
-
 145:         This method is used to speed up the search for the best split.
-
 146:         It is a proxy quantity such that the split that maximizes this value
-
 147:         also maximizes the impurity improvement. It neglects all constant terms
-
 148:         of the impurity decrease for a given split.
-
 149:
-
 150:         The absolute impurity improvement is only computed by the
-
 151:         impurity_improvement method once the best split has been found.
-
 152:         """
-
 153:         # cdef double impurity_left
-
 154:         # cdef double impurity_right
-
 155:         # self.children_impurity(&impurity_left, &impurity_right)
-
 156:
-
 157:         # return (- self.weighted_n_right * impurity_right
-
 158:         #         - self.weighted_n_left * impurity_left)
-
 159:
-
 160:         pass
-
 161:
-
+162:     cdef double impurity_improvement(self, double impurity) nogil:
-
static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_impurity_improvement(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, double __pyx_v_impurity) {
-  double __pyx_v_impurity_left;
-  double __pyx_v_impurity_right;
-  double __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 163:         """Compute the improvement in impurity
-
 164:
-
 165:         This method computes the improvement in impurity when a split occurs.
-
 166:         The weighted impurity improvement equation is the following:
-
 167:
-
 168:             N_t / N * (impurity - N_t_R / N_t * right_impurity
-
 169:                                 - N_t_L / N_t * left_impurity)
-
 170:
-
 171:         where N is the total number of samples, N_t is the number of samples
-
 172:         at the current node, N_t_L is the number of samples in the left child,
-
 173:         and N_t_R is the number of samples in the right child,
-
 174:
-
 175:         Parameters
-
 176:         ----------
-
 177:         impurity : double
-
 178:             The initial impurity of the node before the split
-
 179:
-
 180:         Return
-
 181:         ------
-
 182:         double : improvement in impurity after the split occurs
-
 183:         """
-
 184:
-
 185:         cdef double impurity_left
-
 186:         cdef double impurity_right
-
 187:
-
+188:         self.children_impurity(&impurity_left, &impurity_right)
-
-  /* "stpredictions/models/OK3/_criterion.pyx":188
- *         cdef double impurity_right
- * 
- *         self.children_impurity(&impurity_left, &impurity_right)             # <<<<<<<<<<<<<<
- * 
- *         return ((self.weighted_n_node_samples / self.weighted_n_samples) *
- */
-  ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_vtab)->children_impurity(__pyx_v_self, (&__pyx_v_impurity_left), (&__pyx_v_impurity_right));
-
 189:
-
+190:         return ((self.weighted_n_node_samples / self.weighted_n_samples) *
-
  __pyx_r = ((__pyx_v_self->weighted_n_node_samples / __pyx_v_self->weighted_n_samples) * ((__pyx_v_impurity - ((__pyx_v_self->weighted_n_right / __pyx_v_self->weighted_n_node_samples) * __pyx_v_impurity_right)) - ((__pyx_v_self->weighted_n_left / __pyx_v_self->weighted_n_node_samples) * __pyx_v_impurity_left)));
-  goto __pyx_L0;
-
 191:                 (impurity - (self.weighted_n_right /
-
 192:                              self.weighted_n_node_samples * impurity_right)
-
 193:                           - (self.weighted_n_left /
-
 194:                              self.weighted_n_node_samples * impurity_left)))
-
 195:
-
 196:
-
 197:
-
 198:
-
 199:
-
 200:
-
 201:
-
 202:
-
 203:
-
 204:
-
 205:
-
 206:
-
 207:
-
 208:
-
+209: cdef class KernelizedRegressionCriterion(Criterion):
-
struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion {
-  struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base;
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-static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion;
-
-
 210:     r"""Abstract kernelized output regression criterion.
-
 211:
-
 212:     This handles cases where the target is a structured object and the Gramm
-
 213:     matrix (the matrix of the kernel evaluated at the output samples) is given
-
 214:     as y. The impurity is evaluated by computing the variance of the target
-
 215:     values (embedded in a larger Hilbert space) left and right of the split point.
-
 216:     """
-
 217:
-
+218:     def __cinit__(self, SIZE_t n_samples):
-
/* Python wrapper */
-static int __pyx_pw_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
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-      values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
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 219:         """Initialize parameters for this criterion.
-
 220:
-
 221:         Parameters
-
 222:         ----------
-
 223:         n_samples : SIZE_t
-
 224:             The total number of samples to fit on
-
 225:         """
-
 226:
-
 227:         # Default values
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+228:         self.sample_weight = NULL
-
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-
 229:
-
+230:         self.samples = NULL
-
  __pyx_v_self->__pyx_base.samples = NULL;
-
+231:         self.start = 0
-
  __pyx_v_self->__pyx_base.start = 0;
-
+232:         self.pos = 0
-
  __pyx_v_self->__pyx_base.pos = 0;
-
+233:         self.end = 0
-
  __pyx_v_self->__pyx_base.end = 0;
-
 234:
-
+235:         self.n_samples = n_samples
-
  __pyx_v_self->__pyx_base.n_samples = __pyx_v_n_samples;
-
+236:         self.n_node_samples = 0
-
  __pyx_v_self->__pyx_base.n_node_samples = 0;
-
+237:         self.weighted_n_node_samples = 0.0
-
  __pyx_v_self->__pyx_base.weighted_n_node_samples = 0.0;
-
+238:         self.weighted_n_left = 0.0
-
  __pyx_v_self->__pyx_base.weighted_n_left = 0.0;
-
+239:         self.weighted_n_right = 0.0
-
  __pyx_v_self->__pyx_base.weighted_n_right = 0.0;
-
 240:
-
+241:         self.sum_diag_Gramm = 0.0
-
  __pyx_v_self->sum_diag_Gramm = 0.0;
-
+242:         self.sum_total_Gramm = 0.0
-
  __pyx_v_self->sum_total_Gramm = 0.0;
-
 243:
-
+244:         self.sum_diag_Gramm_left = 0.0
-
  __pyx_v_self->sum_diag_Gramm_left = 0.0;
-
+245:         self.sum_diag_Gramm_right = 0.0
-
  __pyx_v_self->sum_diag_Gramm_right = 0.0;
-
 246:
-
+247:         self.sum_total_Gramm_left = 0.0
-
  __pyx_v_self->sum_total_Gramm_left = 0.0;
-
+248:         self.sum_total_Gramm_right = 0.0
-
  __pyx_v_self->sum_total_Gramm_right = 0.0;
-
 249:
-
 250:
-
+251:     def __reduce__(self):
-
/* Python wrapper */
-static PyObject *__pyx_pw_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_3__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
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 253:
-
+254:     cdef int init(self, const DOUBLE_t[:, ::1] y, DOUBLE_t* sample_weight,
-
static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_init(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, double __pyx_v_weighted_n_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end) {
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_q;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_i;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_j;
-  int __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L1_error:;
-  {
-    #ifdef WITH_THREAD
-    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
-    #endif
-    __Pyx_AddTraceback("stpredictions.models.OK3._criterion.KernelizedRegressionCriterion.init", __pyx_clineno, __pyx_lineno, __pyx_filename);
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-    __Pyx_PyGILState_Release(__pyx_gilstate_save);
-    #endif
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-  __pyx_r = -1;
-  __pyx_L0:;
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-}
-
 255:                   double weighted_n_samples, SIZE_t* samples, SIZE_t start,
-
 256:                   SIZE_t end) nogil except -1:
-
 257:         """Initialize the criterion at node samples[start:end] and
-
 258:            children samples[start:start] and samples[start:end]."""
-
 259:         # Initialize fields
-
+260:         self.y = y
-
  __PYX_XDEC_MEMVIEW(&__pyx_v_self->__pyx_base.y, 0);
-  __PYX_INC_MEMVIEW(&__pyx_v_y, 1);
-  __pyx_v_self->__pyx_base.y = __pyx_v_y;
-
+261:         self.sample_weight = sample_weight
-
  __pyx_v_self->__pyx_base.sample_weight = __pyx_v_sample_weight;
-
+262:         self.samples = samples
-
  __pyx_v_self->__pyx_base.samples = __pyx_v_samples;
-
+263:         self.start = start
-
  __pyx_v_self->__pyx_base.start = __pyx_v_start;
-
+264:         self.end = end
-
  __pyx_v_self->__pyx_base.end = __pyx_v_end;
-
+265:         self.n_node_samples = end - start
-
  __pyx_v_self->__pyx_base.n_node_samples = (__pyx_v_end - __pyx_v_start);
-
+266:         self.weighted_n_samples = weighted_n_samples
-
  __pyx_v_self->__pyx_base.weighted_n_samples = __pyx_v_weighted_n_samples;
-
+267:         self.weighted_n_node_samples = 0.
-
  __pyx_v_self->__pyx_base.weighted_n_node_samples = 0.;
-
 268:
-
 269:         cdef SIZE_t i
-
 270:         cdef SIZE_t j
-
 271:         cdef SIZE_t p
-
 272:         cdef SIZE_t q
-
+273:         cdef DOUBLE_t w_i = 1.0
-
  __pyx_v_w_i = 1.0;
-
+274:         cdef DOUBLE_t w_j = 1.0
-
  __pyx_v_w_j = 1.0;
-
 275:
-
+276:         self.sum_diag_Gramm = 0.0
-
  __pyx_v_self->sum_diag_Gramm = 0.0;
-
+277:         self.sum_total_Gramm = 0.0
-
  __pyx_v_self->sum_total_Gramm = 0.0;
-
 278:
-
+279:         self.sum_diag_Gramm_left = 0.0
-
  __pyx_v_self->sum_diag_Gramm_left = 0.0;
-
+280:         self.sum_diag_Gramm_right = 0.0
-
  __pyx_v_self->sum_diag_Gramm_right = 0.0;
-
 281:
-
+282:         self.sum_total_Gramm_left = 0.0
-
  __pyx_v_self->sum_total_Gramm_left = 0.0;
-
+283:         self.sum_total_Gramm_right = 0.0
-
  __pyx_v_self->sum_total_Gramm_right = 0.0;
-
 284:
-
+285:         for p in range(start, end):
-
  __pyx_t_1 = __pyx_v_end;
-  __pyx_t_2 = __pyx_t_1;
-  for (__pyx_t_3 = __pyx_v_start; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
-    __pyx_v_p = __pyx_t_3;
-
+286:             i = samples[p]
-
    __pyx_v_i = (__pyx_v_samples[__pyx_v_p]);
-
 287:             # with gil:
-
 288:             #     print("print samples :",i)
-
 289:
-
+290:             if sample_weight != NULL:
-
    __pyx_t_4 = ((__pyx_v_sample_weight != NULL) != 0);
-    if (__pyx_t_4) {
-/* … */
-    }
-
+291:                 w_i = sample_weight[i]
-
      __pyx_v_w_i = (__pyx_v_sample_weight[__pyx_v_i]);
-
 292:
-
+293:             self.weighted_n_node_samples += w_i
-
    __pyx_v_self->__pyx_base.weighted_n_node_samples = (__pyx_v_self->__pyx_base.weighted_n_node_samples + __pyx_v_w_i);
-
 294:
-
+295:             self.sum_diag_Gramm += w_i * self.y[i,i]
-
    if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 295, __pyx_L1_error)}
-    __pyx_t_5 = __pyx_v_i;
-    __pyx_t_6 = __pyx_v_i;
-    __pyx_v_self->sum_diag_Gramm = (__pyx_v_self->sum_diag_Gramm + (__pyx_v_w_i * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_5 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_6)) )))));
-
 296:
-
+297:             for q in range(start, end):
-
    __pyx_t_7 = __pyx_v_end;
-    __pyx_t_8 = __pyx_t_7;
-    for (__pyx_t_9 = __pyx_v_start; __pyx_t_9 < __pyx_t_8; __pyx_t_9+=1) {
-      __pyx_v_q = __pyx_t_9;
-
+298:                 j = samples[q]
-
      __pyx_v_j = (__pyx_v_samples[__pyx_v_q]);
-
 299:
-
+300:                 if sample_weight != NULL:
-
      __pyx_t_4 = ((__pyx_v_sample_weight != NULL) != 0);
-      if (__pyx_t_4) {
-/* … */
-      }
-
+301:                     w_j = sample_weight[j]
-
        __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]);
-
 302:
-
+303:                 self.sum_total_Gramm += w_i * w_j * self.y[i,j]
-
      if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 303, __pyx_L1_error)}
-      __pyx_t_6 = __pyx_v_i;
-      __pyx_t_5 = __pyx_v_j;
-      __pyx_v_self->sum_total_Gramm = (__pyx_v_self->sum_total_Gramm + ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_6 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_5)) )))));
-    }
-  }
-
 304:
-
 305:         # Reset to pos=start
-
+306:         self.reset()
-
  __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.reset(((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self)); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(1, 306, __pyx_L1_error)
-
 307:         # with gil:
-
 308:         #     print("print sum diag  :",self.sum_diag_Gramm)
-
 309:         #     print("print sum total :",self.sum_total_Gramm)
-
 310:         #     print("print weighted_n_node_samples :",self.weighted_n_node_samples)
-
+311:         return 0
-
  __pyx_r = 0;
-  goto __pyx_L0;
-
 312:
-
+313:     cdef int reset(self) nogil except -1:
-
static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_reset(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) {
-  int __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 314:         """Reset the criterion at pos=start."""
-
 315:
-
+316:         self.sum_diag_Gramm_left = 0.0
-
  __pyx_v_self->sum_diag_Gramm_left = 0.0;
-
+317:         self.sum_diag_Gramm_right = self.sum_diag_Gramm
-
  __pyx_t_1 = __pyx_v_self->sum_diag_Gramm;
-  __pyx_v_self->sum_diag_Gramm_right = __pyx_t_1;
-
 318:
-
+319:         self.sum_total_Gramm_left = 0.0
-
  __pyx_v_self->sum_total_Gramm_left = 0.0;
-
+320:         self.sum_total_Gramm_right = self.sum_total_Gramm
-
  __pyx_t_1 = __pyx_v_self->sum_total_Gramm;
-  __pyx_v_self->sum_total_Gramm_right = __pyx_t_1;
-
 321:
-
+322:         self.weighted_n_left = 0.0
-
  __pyx_v_self->__pyx_base.weighted_n_left = 0.0;
-
+323:         self.weighted_n_right = self.weighted_n_node_samples
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.weighted_n_node_samples;
-  __pyx_v_self->__pyx_base.weighted_n_right = __pyx_t_1;
-
+324:         self.pos = self.start
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.start;
-  __pyx_v_self->__pyx_base.pos = __pyx_t_2;
-
+325:         return 0
-
  __pyx_r = 0;
-  goto __pyx_L0;
-
 326:
-
+327:     cdef int reverse_reset(self) nogil except -1:
-
static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_reverse_reset(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) {
-  int __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 328:         """Reset the criterion at pos=end."""
-
 329:
-
+330:         self.sum_diag_Gramm_right = 0.0
-
  __pyx_v_self->sum_diag_Gramm_right = 0.0;
-
+331:         self.sum_diag_Gramm_left = self.sum_diag_Gramm
-
  __pyx_t_1 = __pyx_v_self->sum_diag_Gramm;
-  __pyx_v_self->sum_diag_Gramm_left = __pyx_t_1;
-
 332:
-
+333:         self.sum_total_Gramm_right = 0.0
-
  __pyx_v_self->sum_total_Gramm_right = 0.0;
-
+334:         self.sum_total_Gramm_left = self.sum_total_Gramm
-
  __pyx_t_1 = __pyx_v_self->sum_total_Gramm;
-  __pyx_v_self->sum_total_Gramm_left = __pyx_t_1;
-
 335:
-
+336:         self.weighted_n_right = 0.0
-
  __pyx_v_self->__pyx_base.weighted_n_right = 0.0;
-
+337:         self.weighted_n_left = self.weighted_n_node_samples
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.weighted_n_node_samples;
-  __pyx_v_self->__pyx_base.weighted_n_left = __pyx_t_1;
-
+338:         self.pos = self.end
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.end;
-  __pyx_v_self->__pyx_base.pos = __pyx_t_2;
-
+339:         return 0
-
  __pyx_r = 0;
-  goto __pyx_L0;
-
 340:
-
+341:     cdef int update(self, SIZE_t new_pos) nogil except -1:
-
static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_update(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos) {
-  double *__pyx_v_sample_weight;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_q;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_i;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_j;
-  int __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L1_error:;
-  {
-    #ifdef WITH_THREAD
-    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
-    #endif
-    __Pyx_AddTraceback("stpredictions.models.OK3._criterion.KernelizedRegressionCriterion.update", __pyx_clineno, __pyx_lineno, __pyx_filename);
-    #ifdef WITH_THREAD
-    __Pyx_PyGILState_Release(__pyx_gilstate_save);
-    #endif
-  }
-  __pyx_r = -1;
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 342:         """Updated statistics by moving samples[pos:new_pos] to the left."""
-
 343:
-
+344:         cdef double* sample_weight = self.sample_weight
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.sample_weight;
-  __pyx_v_sample_weight = __pyx_t_1;
-
+345:         cdef SIZE_t* samples = self.samples
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.samples;
-  __pyx_v_samples = __pyx_t_2;
-
 346:
-
+347:         cdef SIZE_t start = self.start
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.start;
-  __pyx_v_start = __pyx_t_3;
-
+348:         cdef SIZE_t pos = self.pos
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.pos;
-  __pyx_v_pos = __pyx_t_3;
-
+349:         cdef SIZE_t end = self.end
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.end;
-  __pyx_v_end = __pyx_t_3;
-
 350:
-
 351:         cdef SIZE_t i
-
 352:         cdef SIZE_t j
-
 353:         cdef SIZE_t p
-
 354:         cdef SIZE_t q
-
+355:         cdef DOUBLE_t w_i = 1.0
-
  __pyx_v_w_i = 1.0;
-
+356:         cdef DOUBLE_t w_j = 1.0
-
  __pyx_v_w_j = 1.0;
-
 357:
-
 358:         # Update statistics up to new_pos
-
 359:
-
+360:         for p in range(pos, new_pos):
-
  __pyx_t_3 = __pyx_v_new_pos;
-  __pyx_t_4 = __pyx_t_3;
-  for (__pyx_t_5 = __pyx_v_pos; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
-    __pyx_v_p = __pyx_t_5;
-
+361:             i = samples[p]
-
    __pyx_v_i = (__pyx_v_samples[__pyx_v_p]);
-
 362:
-
+363:             if sample_weight != NULL:
-
    __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0);
-    if (__pyx_t_6) {
-/* … */
-    }
-
+364:                 w_i = sample_weight[i]
-
      __pyx_v_w_i = (__pyx_v_sample_weight[__pyx_v_i]);
-
 365:
-
+366:             self.sum_diag_Gramm_left += w_i * self.y[i,i]
-
    if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 366, __pyx_L1_error)}
-    __pyx_t_7 = __pyx_v_i;
-    __pyx_t_8 = __pyx_v_i;
-    __pyx_v_self->sum_diag_Gramm_left = (__pyx_v_self->sum_diag_Gramm_left + (__pyx_v_w_i * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) )))));
-
 367:
-
+368:             self.sum_diag_Gramm_right -= w_i * self.y[i,i]
-
    if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 368, __pyx_L1_error)}
-    __pyx_t_8 = __pyx_v_i;
-    __pyx_t_7 = __pyx_v_i;
-    __pyx_v_self->sum_diag_Gramm_right = (__pyx_v_self->sum_diag_Gramm_right - (__pyx_v_w_i * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) )))));
-
 369:
-
+370:             self.weighted_n_left += w_i
-
    __pyx_v_self->__pyx_base.weighted_n_left = (__pyx_v_self->__pyx_base.weighted_n_left + __pyx_v_w_i);
-
 371:
-
+372:             self.weighted_n_right -= w_i
-
    __pyx_v_self->__pyx_base.weighted_n_right = (__pyx_v_self->__pyx_base.weighted_n_right - __pyx_v_w_i);
-
 373:
-
+374:             for q in range(start, pos):
-
    __pyx_t_9 = __pyx_v_pos;
-    __pyx_t_10 = __pyx_t_9;
-    for (__pyx_t_11 = __pyx_v_start; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) {
-      __pyx_v_q = __pyx_t_11;
-
+375:                 j = samples[q]
-
      __pyx_v_j = (__pyx_v_samples[__pyx_v_q]);
-
 376:
-
+377:                 if sample_weight != NULL:
-
      __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0);
-      if (__pyx_t_6) {
-/* … */
-      }
-
+378:                     w_j = sample_weight[j]
-
        __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]);
-
 379:
-
+380:                 self.sum_total_Gramm_left += 2 * w_i * w_j * self.y[i,j]
-
      if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 380, __pyx_L1_error)}
-      __pyx_t_7 = __pyx_v_i;
-      __pyx_t_8 = __pyx_v_j;
-      __pyx_v_self->sum_total_Gramm_left = (__pyx_v_self->sum_total_Gramm_left + (((2.0 * __pyx_v_w_i) * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) )))));
-    }
-
 381:
-
+382:             for q in range(pos, new_pos):
-
    __pyx_t_9 = __pyx_v_new_pos;
-    __pyx_t_10 = __pyx_t_9;
-    for (__pyx_t_11 = __pyx_v_pos; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) {
-      __pyx_v_q = __pyx_t_11;
-
+383:                 j = samples[q]
-
      __pyx_v_j = (__pyx_v_samples[__pyx_v_q]);
-
 384:
-
+385:                 if sample_weight != NULL:
-
      __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0);
-      if (__pyx_t_6) {
-/* … */
-      }
-
+386:                     w_j = sample_weight[j]
-
        __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]);
-
 387:
-
+388:                 self.sum_total_Gramm_left += w_i * w_j * self.y[i,j]
-
      if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 388, __pyx_L1_error)}
-      __pyx_t_8 = __pyx_v_i;
-      __pyx_t_7 = __pyx_v_j;
-      __pyx_v_self->sum_total_Gramm_left = (__pyx_v_self->sum_total_Gramm_left + ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) )))));
-
 389:
-
+390:                 self.sum_total_Gramm_right -= w_i * w_j * self.y[i,j]
-
      if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 390, __pyx_L1_error)}
-      __pyx_t_7 = __pyx_v_i;
-      __pyx_t_8 = __pyx_v_j;
-      __pyx_v_self->sum_total_Gramm_right = (__pyx_v_self->sum_total_Gramm_right - ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) )))));
-    }
-  }
-
 391:
-
+392:         for p in range(new_pos, end):
-
  __pyx_t_3 = __pyx_v_end;
-  __pyx_t_4 = __pyx_t_3;
-  for (__pyx_t_5 = __pyx_v_new_pos; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
-    __pyx_v_p = __pyx_t_5;
-
+393:             i = samples[p]
-
    __pyx_v_i = (__pyx_v_samples[__pyx_v_p]);
-
 394:
-
+395:             if sample_weight != NULL:
-
    __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0);
-    if (__pyx_t_6) {
-/* … */
-    }
-
+396:                 w_i = sample_weight[i]
-
      __pyx_v_w_i = (__pyx_v_sample_weight[__pyx_v_i]);
-
 397:
-
+398:             for q in range(pos, new_pos):
-
    __pyx_t_9 = __pyx_v_new_pos;
-    __pyx_t_10 = __pyx_t_9;
-    for (__pyx_t_11 = __pyx_v_pos; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) {
-      __pyx_v_q = __pyx_t_11;
-
+399:                 j = samples[q]
-
      __pyx_v_j = (__pyx_v_samples[__pyx_v_q]);
-
 400:
-
+401:                 if sample_weight != NULL:
-
      __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0);
-      if (__pyx_t_6) {
-/* … */
-      }
-
+402:                     w_j = sample_weight[j]
-
        __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]);
-
 403:
-
+404:                 self.sum_total_Gramm_right -= 2 * w_i * w_j * self.y[i,j]
-
      if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 404, __pyx_L1_error)}
-      __pyx_t_8 = __pyx_v_i;
-      __pyx_t_7 = __pyx_v_j;
-      __pyx_v_self->sum_total_Gramm_right = (__pyx_v_self->sum_total_Gramm_right - (((2.0 * __pyx_v_w_i) * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const  *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) )))));
-    }
-  }
-
 405:
-
+406:         self.pos = new_pos
-
  __pyx_v_self->__pyx_base.pos = __pyx_v_new_pos;
-
+407:         return 0
-
  __pyx_r = 0;
-  goto __pyx_L0;
-
 408:
-
+409:     cdef double node_impurity(self) nogil:
-
static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) {
-  double __pyx_r;
-
-  /* function exit code */
-  __pyx_r = 0;
-  return __pyx_r;
-}
-
 410:         pass
-
 411:
-
+412:     cdef void children_impurity(self, double* impurity_left, double* impurity_right) nogil:
-
static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) {
-
-  /* function exit code */
-}
-
 413:         pass
-
 414:
-
+415:     cdef void node_value(self, double* dest) nogil:
-
static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_node_value(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, double *__pyx_v_dest) {
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
-  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w;
-/* … */
-  /* function exit code */
-}
-
 416:         """Compute the node value of samples[start:end] into dest."""
-
 417:
-
 418:         cdef SIZE_t p
-
 419:         cdef SIZE_t k
-
+420:         cdef DOUBLE_t w = 1.0
-
  __pyx_v_w = 1.0;
-
 421:
-
+422:         for p in range(self.start, self.end):
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.end;
-  __pyx_t_2 = __pyx_t_1;
-  for (__pyx_t_3 = __pyx_v_self->__pyx_base.start; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
-    __pyx_v_p = __pyx_t_3;
-
 423:
-
+424:             k = self.samples[p]
-
    __pyx_v_k = (__pyx_v_self->__pyx_base.samples[__pyx_v_p]);
-
 425:
-
+426:             if self.sample_weight != NULL:
-
    __pyx_t_4 = ((__pyx_v_self->__pyx_base.sample_weight != NULL) != 0);
-    if (__pyx_t_4) {
-/* … */
-    }
-
+427:                 w = self.sample_weight[k]
-
      __pyx_v_w = (__pyx_v_self->__pyx_base.sample_weight[__pyx_v_k]);
-
 428:
-
+429:             dest[k] = w / self.weighted_n_node_samples
-
    (__pyx_v_dest[__pyx_v_k]) = (__pyx_v_w / __pyx_v_self->__pyx_base.weighted_n_node_samples);
-  }
-
 430:
-
 431:
-
 432:
-
 433:
-
 434:
-
 435:
-
 436:
-
 437:
-
 438:
-
 439:
-
 440:
-
 441:
-
 442:
-
 443:
-
 444:
-
+445: cdef class KernelizedMSE(KernelizedRegressionCriterion):
-
struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE {
-  struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion __pyx_base;
-};
-/* … */
-struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE {
-  struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion __pyx_base;
-};
-static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE;
-
-
 446:     """Mean squared error impurity criterion.
-
 447:
-
 448:         var = \sum_i^n (phi(y_i) - phi(y)_bar) ** 2
-
 449:             = (\sum_i^n phi(y_i) ** 2) - n_samples * phi(y)_bar ** 2
-
 450:
-
 451:         MSE = var_left + var_right
-
 452:     """
-
 453:
-
+454:     cdef double node_impurity(self) nogil:
-
static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self) {
-  double __pyx_v_impurity;
-  double __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 455:         """Evaluate the impurity of the current node, i.e. the impurity of
-
 456:            samples[start:end]."""
-
 457:
-
 458:         cdef double impurity
-
 459:
-
+460:         impurity = self.sum_diag_Gramm / self.weighted_n_node_samples - self.sum_total_Gramm / (self.weighted_n_node_samples)**2
-
  __pyx_v_impurity = ((__pyx_v_self->__pyx_base.sum_diag_Gramm / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples) - (__pyx_v_self->__pyx_base.sum_total_Gramm / pow(__pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples, 2.0)));
-
 461:
-
+462:         return impurity
-
  __pyx_r = __pyx_v_impurity;
-  goto __pyx_L0;
-
 463:
-
+464:     cdef double proxy_impurity_improvement(self) nogil:
-
static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_proxy_impurity_improvement(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self) {
-  double __pyx_v_proxy_impurity_left;
-  double __pyx_v_proxy_impurity_right;
-  double __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 465:         """Compute a proxy of the impurity reduction
-
 466:
-
 467:         This method is used to speed up the search for the best split.
-
 468:         It is a proxy quantity such that the split that maximizes this value
-
 469:         also maximizes the impurity improvement. It neglects all constant terms
-
 470:         of the impurity decrease for a given split.
-
 471:
-
 472:         The absolute impurity improvement is only computed by the
-
 473:         impurity_improvement method once the best split has been found.
-
 474:         """
-
 475:
-
+476:         cdef double proxy_impurity_left = self.sum_diag_Gramm_left - self.sum_total_Gramm_left / self.weighted_n_left
-
  __pyx_v_proxy_impurity_left = (__pyx_v_self->__pyx_base.sum_diag_Gramm_left - (__pyx_v_self->__pyx_base.sum_total_Gramm_left / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_left));
-
+477:         cdef double proxy_impurity_right = self.sum_diag_Gramm_right - self.sum_total_Gramm_right / self.weighted_n_right
-
  __pyx_v_proxy_impurity_right = (__pyx_v_self->__pyx_base.sum_diag_Gramm_right - (__pyx_v_self->__pyx_base.sum_total_Gramm_right / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_right));
-
 478:
-
+479:         return (- proxy_impurity_left - proxy_impurity_right)
-
  __pyx_r = ((-__pyx_v_proxy_impurity_left) - __pyx_v_proxy_impurity_right);
-  goto __pyx_L0;
-
 480:
-
+481:     cdef void children_impurity(self, double* impurity_left, double* impurity_right) nogil:
-
static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right) {
-  double __pyx_v_sum_diag_Gramm_left;
-  double __pyx_v_sum_diag_Gramm_right;
-  double __pyx_v_sum_total_Gramm_left;
-  double __pyx_v_sum_total_Gramm_right;
-/* … */
-  /* function exit code */
-}
-
 482:         """Evaluate the impurity in children nodes, i.e. the impurity of the
-
 483:            left child (samples[start:pos]) and the impurity the right child
-
 484:            (samples[pos:end])."""
-
 485:
-
+486:         cdef double sum_diag_Gramm_left = self.sum_diag_Gramm_left
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.sum_diag_Gramm_left;
-  __pyx_v_sum_diag_Gramm_left = __pyx_t_1;
-
+487:         cdef double sum_diag_Gramm_right = self.sum_diag_Gramm_right
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.sum_diag_Gramm_right;
-  __pyx_v_sum_diag_Gramm_right = __pyx_t_1;
-
 488:
-
+489:         cdef double sum_total_Gramm_left = self.sum_total_Gramm_left
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.sum_total_Gramm_left;
-  __pyx_v_sum_total_Gramm_left = __pyx_t_1;
-
+490:         cdef double sum_total_Gramm_right = self.sum_total_Gramm_right
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.sum_total_Gramm_right;
-  __pyx_v_sum_total_Gramm_right = __pyx_t_1;
-
 491:
-
+492:         impurity_left[0] = sum_diag_Gramm_left / self.weighted_n_left - sum_total_Gramm_left / (self.weighted_n_left)**2
-
  (__pyx_v_impurity_left[0]) = ((__pyx_v_sum_diag_Gramm_left / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_left) - (__pyx_v_sum_total_Gramm_left / pow(__pyx_v_self->__pyx_base.__pyx_base.weighted_n_left, 2.0)));
-
+493:         impurity_right[0] = sum_diag_Gramm_right / self.weighted_n_right - sum_total_Gramm_right / (self.weighted_n_right)**2
-
  (__pyx_v_impurity_right[0]) = ((__pyx_v_sum_diag_Gramm_right / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_right) - (__pyx_v_sum_total_Gramm_right / pow(__pyx_v_self->__pyx_base.__pyx_base.weighted_n_right, 2.0)));
-
 494:
-
 495:
-
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Raw output: _splitter.c

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+0001: # cython: cdivision=True
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 0002: # cython: boundscheck=False
-
 0003: # cython: wraparound=False
-
 0004:
-
 0005: from _criterion cimport Criterion
-
 0006:
-
 0007: from libc.stdlib cimport free
-
 0008: from libc.stdlib cimport qsort
-
 0009: from libc.string cimport memcpy
-
 0010: from libc.string cimport memset
-
 0011:
-
+0012: import numpy as np
-
  __pyx_t_1 = __Pyx_Import(__pyx_n_s_numpy, 0, -1); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 12, __pyx_L1_error)
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-  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
-
 0013: cimport numpy as np
-
+0014: np.import_array()
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  __pyx_t_2 = __pyx_f_5numpy_import_array(); if (unlikely(__pyx_t_2 == ((int)-1))) __PYX_ERR(0, 14, __pyx_L1_error)
-
 0015:
-
+0016: from scipy.sparse import csc_matrix
-
  __pyx_t_1 = PyList_New(1); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 16, __pyx_L1_error)
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-  __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
-
 0017:
-
 0018: from sklearn.tree._utils cimport log
-
 0019: from sklearn.tree._utils cimport rand_int
-
 0020: from sklearn.tree._utils cimport rand_uniform
-
 0021: from sklearn.tree._utils cimport RAND_R_MAX
-
 0022: from sklearn.tree._utils cimport safe_realloc
-
 0023:
-
+0024: cdef double INFINITY = np.inf
-
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 0130:
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 0131:         # Create a new array which will be used to store nonzero
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 0134:
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 0135:         cdef SIZE_t i, j
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 0138:
-
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 0140:             # Only work with positively weighted samples
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 0147:             else:
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 0150:         # Number of samples is number of positively weighted samples
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 0153:
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 0156:
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+0158:             features[i] = i
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 0159:
-
+0160:         self.n_features = n_features
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 0161:
-
+0162:         safe_realloc(&self.feature_values, n_samples)
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 0164:
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 0166:
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 0169:
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+0170:     cdef int node_reset(self, SIZE_t start, SIZE_t end,
-
static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_reset(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, double *__pyx_v_weighted_n_node_samples) {
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 0171:                         double* weighted_n_node_samples) nogil except -1:
-
 0172:         """Reset splitter on node samples[start:end].
-
 0173:
-
 0174:         Returns -1 in case of failure to allocate memory (and raise MemoryError)
-
 0175:         or 0 otherwise.
-
 0176:
-
 0177:         Parameters
-
 0178:         ----------
-
 0179:         start : SIZE_t
-
 0180:             The index of the first sample to consider
-
 0181:         end : SIZE_t
-
 0182:             The index of the last sample to consider
-
 0183:         weighted_n_node_samples : ndarray, dtype=double pointer
-
 0184:             The total weight of those samples
-
 0185:         """
-
 0186:
-
+0187:         self.start = start
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+0188:         self.end = end
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 0189:
-
+0190:         self.criterion.init(self.y,
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 0191:                             self.sample_weight,
-
 0192:                             self.weighted_n_samples,
-
 0193:                             self.samples,
-
 0194:                             start,
-
 0195:                             end)
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 0196:
-
+0197:         weighted_n_node_samples[0] = self.criterion.weighted_n_node_samples
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+0198:         return 0
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-
 0199:
-
+0200:     cdef int node_split(self, double impurity, SplitRecord* split,
-
static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_split(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED double __pyx_v_impurity, CYTHON_UNUSED struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features) {
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 0201:                         SIZE_t* n_constant_features) nogil except -1:
-
 0202:         """Find the best split on node samples[start:end].
-
 0203:
-
 0204:         This is a placeholder method. The majority of computation will be done
-
 0205:         here.
-
 0206:
-
 0207:         It should return -1 upon errors.
-
 0208:         """
-
 0209:
-
 0210:         pass
-
 0211:
-
+0212:     cdef void node_value(self, double* dest) nogil:
-
static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_value(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, double *__pyx_v_dest) {
-/* … */
-  /* function exit code */
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-
 0213:         """Copy the value of node samples[start:end] into dest."""
-
 0214:
-
+0215:         self.criterion.node_value(dest)
-
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-
 0216:
-
+0217:     cdef double node_impurity(self) nogil:
-
static double __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self) {
-  double __pyx_r;
-/* … */
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-  __pyx_L0:;
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 0218:         """Return the impurity of the current node."""
-
 0219:
-
+0220:         return self.criterion.node_impurity()
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-  goto __pyx_L0;
-
 0221:
-
 0222:
-
+0223: cdef class BaseDenseSplitter(Splitter):
-
struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter {
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-/* … */
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-  struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter __pyx_base;
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-
-
 0224:     cdef const DTYPE_t[:, :] X
-
 0225:
-
 0226:     cdef SIZE_t n_total_samples
-
 0227:
-
+0228:     cdef int init(self,
-
static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter_init(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight) {
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 0229:                   object X,
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 0230:                   const DOUBLE_t[:, ::1] y,
-
 0231:                   DOUBLE_t* sample_weight) except -1:
-
 0232:         """Initialize the splitter
-
 0233:
-
 0234:         Returns -1 in case of failure to allocate memory (and raise MemoryError)
-
 0235:         or 0 otherwise.
-
 0236:         """
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 0237:
-
 0238:         # Call parent init
-
+0239:         Splitter.init(self, X, y, sample_weight)
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+0242:         return 0
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 0243:
-
 0244:
-
+0245: cdef class BestSplitter(BaseDenseSplitter):
-
struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter {
-  struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter __pyx_base;
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-/* … */
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-
 0246:     """Splitter for finding the best split."""
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+0247:     def __reduce__(self):
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/* Python wrapper */
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+0250:                                self.min_samples_leaf,
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+0251:                                self.min_weight_leaf,
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+0252:                                self.random_state), self.__getstate__())
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 0253:
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+0254:     cdef int node_split(self, double impurity, SplitRecord* split,
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static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_12BestSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features) {
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-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_features;
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features;
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-  __pyx_t_7sklearn_4tree_5_tree_UINT32_t *__pyx_v_random_state;
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 0255:                         SIZE_t* n_constant_features) nogil except -1:
-
 0256:         """Find the best split on node samples[start:end]
-
 0257:
-
 0258:         Returns -1 in case of failure to allocate memory (and raise MemoryError)
-
 0259:         or 0 otherwise.
-
 0260:         """
-
 0261:         # Find the best split
-
+0262:         cdef SIZE_t* samples = self.samples
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.samples;
-  __pyx_v_samples = __pyx_t_1;
-
+0263:         cdef SIZE_t start = self.start
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.start;
-  __pyx_v_start = __pyx_t_2;
-
+0264:         cdef SIZE_t end = self.end
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end;
-  __pyx_v_end = __pyx_t_2;
-
 0265:
-
+0266:         cdef SIZE_t* features = self.features
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.features;
-  __pyx_v_features = __pyx_t_1;
-
+0267:         cdef SIZE_t* constant_features = self.constant_features
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.constant_features;
-  __pyx_v_constant_features = __pyx_t_1;
-
+0268:         cdef SIZE_t n_features = self.n_features
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_features;
-  __pyx_v_n_features = __pyx_t_2;
-
 0269:
-
+0270:         cdef DTYPE_t* Xf = self.feature_values
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.feature_values;
-  __pyx_v_Xf = __pyx_t_3;
-
+0271:         cdef SIZE_t max_features = self.max_features
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features;
-  __pyx_v_max_features = __pyx_t_2;
-
+0272:         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf;
-  __pyx_v_min_samples_leaf = __pyx_t_2;
-
+0273:         cdef double min_weight_leaf = self.min_weight_leaf
-
  __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf;
-  __pyx_v_min_weight_leaf = __pyx_t_4;
-
+0274:         cdef UINT32_t* random_state = &self.rand_r_state
-
  __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state);
-
 0275:
-
 0276:         cdef SplitRecord best, current
-
+0277:         cdef double current_proxy_improvement = -INFINITY
-
  __pyx_v_current_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY);
-
+0278:         cdef double best_proxy_improvement = -INFINITY
-
  __pyx_v_best_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY);
-
 0279:
-
+0280:         cdef SIZE_t f_i = n_features
-
  __pyx_v_f_i = __pyx_v_n_features;
-
 0281:         cdef SIZE_t f_j
-
 0282:         cdef SIZE_t p
-
 0283:         cdef SIZE_t feature_idx_offset
-
 0284:         cdef SIZE_t feature_offset
-
 0285:         cdef SIZE_t i
-
 0286:         cdef SIZE_t j
-
 0287:
-
+0288:         cdef SIZE_t n_visited_features = 0
-
  __pyx_v_n_visited_features = 0;
-
 0289:         # Number of features discovered to be constant during the split search
-
+0290:         cdef SIZE_t n_found_constants = 0
-
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-
 0291:         # Number of features known to be constant and drawn without replacement
-
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-
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-
+0293:         cdef SIZE_t n_known_constants = n_constant_features[0]
-
  __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]);
-
 0294:         # n_total_constants = n_known_constants + n_found_constants
-
+0295:         cdef SIZE_t n_total_constants = n_known_constants
-
  __pyx_v_n_total_constants = __pyx_v_n_known_constants;
-
 0296:         cdef DTYPE_t current_feature_value
-
 0297:         cdef SIZE_t partition_end
-
 0298:
-
+0299:         _init_split(&best, end)
-
  __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end);
-
 0300:
-
 0301:         # Sample up to max_features without replacement using a
-
 0302:         # Fisher-Yates-based algorithm (using the local variables `f_i` and
-
 0303:         # `f_j` to compute a permutation of the `features` array).
-
 0304:         #
-
 0305:         # Skip the CPU intensive evaluation of the impurity criterion for
-
 0306:         # features that were already detected as constant (hence not suitable
-
 0307:         # for good splitting) by ancestor nodes and save the information on
-
 0308:         # newly discovered constant features to spare computation on descendant
-
 0309:         # nodes.
-
+0310:         while (f_i > n_total_constants and  # Stop early if remaining features
-
  while (1) {
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-
 0311:                                             # are constant
-
+0312:                 (n_visited_features < max_features or
-
    __pyx_t_6 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0);
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-
 0313:                  # At least one drawn features must be non constant
-
+0314:                  n_visited_features <= n_found_constants + n_drawn_constants)):
-
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-
 0315:
-
+0316:             n_visited_features += 1
-
    __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1);
-
 0317:
-
 0318:             # Loop invariant: elements of features in
-
 0319:             # - [:n_drawn_constant[ holds drawn and known constant features;
-
 0320:             # - [n_drawn_constant:n_known_constant[ holds known constant
-
 0321:             #   features that haven't been drawn yet;
-
 0322:             # - [n_known_constant:n_total_constant[ holds newly found constant
-
 0323:             #   features;
-
 0324:             # - [n_total_constant:f_i[ holds features that haven't been drawn
-
 0325:             #   yet and aren't constant apriori.
-
 0326:             # - [f_i:n_features[ holds features that have been drawn
-
 0327:             #   and aren't constant.
-
 0328:
-
 0329:             # Draw a feature at random
-
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-
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-
 0331:                            random_state)
-
 0332:
-
+0333:             if f_j < n_known_constants:
-
    __pyx_t_5 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0);
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-
 0334:                 # f_j in the interval [n_drawn_constants, n_known_constants[
-
+0335:                 features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants]
-
      __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]);
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-      (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7;
-
 0336:
-
+0337:                 n_drawn_constants += 1
-
      __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1);
-
 0338:
-
 0339:             else:
-
 0340:                 # f_j in the interval [n_known_constants, f_i - n_found_constants[
-
+0341:                 f_j += n_found_constants
-
    /*else*/ {
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-
 0342:                 # f_j in the interval [n_total_constants, f_i[
-
+0343:                 current.feature = features[f_j]
-
      __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]);
-
 0344:
-
 0345:                 # Sort samples along that feature; by
-
 0346:                 # copying the values into an array and
-
 0347:                 # sorting the array in a manner which utilizes the cache more
-
 0348:                 # effectively.
-
+0349:                 for i in range(start, end):
-
      __pyx_t_7 = __pyx_v_end;
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-      for (__pyx_t_8 = __pyx_v_start; __pyx_t_8 < __pyx_t_2; __pyx_t_8+=1) {
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-
+0350:                     Xf[i] = self.X[samples[i], current.feature]
-
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-      }
-
 0351:
-
+0352:                 sort(Xf + start, samples + start, end - start)
-
      __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end - __pyx_v_start));
-
 0353:
-
+0354:                 if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD:
-
      __pyx_t_5 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0);
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-
+0355:                     features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j]
-
        __pyx_t_7 = (__pyx_v_features[__pyx_v_n_total_constants]);
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-        (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2;
-
 0356:
-
+0357:                     n_found_constants += 1
-
        __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1);
-
+0358:                     n_total_constants += 1
-
        __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1);
-
 0359:
-
 0360:                 else:
-
+0361:                     f_i -= 1
-
      /*else*/ {
-        __pyx_v_f_i = (__pyx_v_f_i - 1);
-
+0362:                     features[f_i], features[f_j] = features[f_j], features[f_i]
-
        __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]);
-        __pyx_t_7 = (__pyx_v_features[__pyx_v_f_i]);
-        (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2;
-        (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7;
-
 0363:
-
 0364:                     # Evaluate all splits
-
+0365:                     self.criterion.reset()
-
        __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 365, __pyx_L1_error)
-
+0366:                     p = start
-
        __pyx_v_p = __pyx_v_start;
-
 0367:
-
+0368:                     while p < end:
-
        while (1) {
-          __pyx_t_5 = ((__pyx_v_p < __pyx_v_end) != 0);
-          if (!__pyx_t_5) break;
-
+0369:                         while (p + 1 < end and
-
          while (1) {
-            __pyx_t_6 = (((__pyx_v_p + 1) < __pyx_v_end) != 0);
-            if (__pyx_t_6) {
-            } else {
-              __pyx_t_5 = __pyx_t_6;
-              goto __pyx_L16_bool_binop_done;
-            }
-
+0370:                                Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD):
-
            __pyx_t_6 = (((__pyx_v_Xf[(__pyx_v_p + 1)]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0);
-            __pyx_t_5 = __pyx_t_6;
-            __pyx_L16_bool_binop_done:;
-            if (!__pyx_t_5) break;
-
+0371:                             p += 1
-
            __pyx_v_p = (__pyx_v_p + 1);
-          }
-
 0372:
-
 0373:                         # (p + 1 >= end) or (X[samples[p + 1], current.feature] >
-
 0374:                         #                    X[samples[p], current.feature])
-
+0375:                         p += 1
-
          __pyx_v_p = (__pyx_v_p + 1);
-
 0376:                         # (p >= end) or (X[samples[p], current.feature] >
-
 0377:                         #                X[samples[p - 1], current.feature])
-
 0378:
-
+0379:                         if p < end:
-
          __pyx_t_5 = ((__pyx_v_p < __pyx_v_end) != 0);
-          if (__pyx_t_5) {
-/* … */
-          }
-          __pyx_L12_continue:;
-        }
-      }
-      __pyx_L11:;
-    }
-    __pyx_L8:;
-  }
-
+0380:                             current.pos = p
-
            __pyx_v_current.pos = __pyx_v_p;
-
 0381:
-
 0382:                             # Reject if min_samples_leaf is not guaranteed
-
+0383:                             if (((current.pos - start) < min_samples_leaf) or
-
            __pyx_t_6 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0);
-            if (!__pyx_t_6) {
-            } else {
-              __pyx_t_5 = __pyx_t_6;
-              goto __pyx_L20_bool_binop_done;
-            }
-/* … */
-            if (__pyx_t_5) {
-/* … */
-            }
-
+0384:                                     ((end - current.pos) < min_samples_leaf)):
-
            __pyx_t_6 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0);
-            __pyx_t_5 = __pyx_t_6;
-            __pyx_L20_bool_binop_done:;
-
+0385:                                 continue
-
              goto __pyx_L12_continue;
-
 0386:
-
+0387:                             self.criterion.update(current.pos)
-
            __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 387, __pyx_L1_error)
-
 0388:
-
 0389:                             # Reject if min_weight_leaf is not satisfied
-
+0390:                             if ((self.criterion.weighted_n_left < min_weight_leaf) or
-
            __pyx_t_6 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_left < __pyx_v_min_weight_leaf) != 0);
-            if (!__pyx_t_6) {
-            } else {
-              __pyx_t_5 = __pyx_t_6;
-              goto __pyx_L23_bool_binop_done;
-            }
-/* … */
-            if (__pyx_t_5) {
-/* … */
-            }
-
+0391:                                     (self.criterion.weighted_n_right < min_weight_leaf)):
-
            __pyx_t_6 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_right < __pyx_v_min_weight_leaf) != 0);
-            __pyx_t_5 = __pyx_t_6;
-            __pyx_L23_bool_binop_done:;
-
+0392:                                 continue
-
              goto __pyx_L12_continue;
-
 0393:
-
+0394:                             current_proxy_improvement = self.criterion.proxy_impurity_improvement()
-
            __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion);
-
 0395:
-
 0396:                             # with gil:
-
 0397:                             #     print("feature ", current.feature)
-
 0398:                             #     print("threshold ", current.threshold)
-
 0399:                             #     print("proxy ", current_proxy_improvement)
-
 0400:                             #     print()
-
 0401:
-
+0402:                             if current_proxy_improvement > best_proxy_improvement:
-
            __pyx_t_5 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0);
-            if (__pyx_t_5) {
-/* … */
-            }
-
+0403:                                 best_proxy_improvement = current_proxy_improvement
-
              __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement;
-
 0404:                                 # sum of halves is used to avoid infinite value
-
+0405:                                 current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0
-
              __pyx_v_current.threshold = (((__pyx_v_Xf[(__pyx_v_p - 1)]) / 2.0) + ((__pyx_v_Xf[__pyx_v_p]) / 2.0));
-
 0406:
-
+0407:                                 if ((current.threshold == Xf[p]) or
-
              __pyx_t_6 = ((__pyx_v_current.threshold == (__pyx_v_Xf[__pyx_v_p])) != 0);
-              if (!__pyx_t_6) {
-              } else {
-                __pyx_t_5 = __pyx_t_6;
-                goto __pyx_L27_bool_binop_done;
-              }
-/* … */
-              if (__pyx_t_5) {
-/* … */
-              }
-
+0408:                                     (current.threshold == INFINITY) or
-
              __pyx_t_6 = ((__pyx_v_current.threshold == __pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY) != 0);
-              if (!__pyx_t_6) {
-              } else {
-                __pyx_t_5 = __pyx_t_6;
-                goto __pyx_L27_bool_binop_done;
-              }
-
+0409:                                     (current.threshold == -INFINITY)):
-
              __pyx_t_6 = ((__pyx_v_current.threshold == (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY)) != 0);
-              __pyx_t_5 = __pyx_t_6;
-              __pyx_L27_bool_binop_done:;
-
+0410:                                     current.threshold = Xf[p - 1]
-
                __pyx_v_current.threshold = (__pyx_v_Xf[(__pyx_v_p - 1)]);
-
 0411:
-
+0412:                                 best = current  # copy
-
              __pyx_v_best = __pyx_v_current;
-
 0413:
-
 0414:         # Reorganize into samples[start:best.pos] + samples[best.pos:end]
-
+0415:         if best.pos < end:
-
  __pyx_t_5 = ((__pyx_v_best.pos < __pyx_v_end) != 0);
-  if (__pyx_t_5) {
-/* … */
-  }
-
+0416:             partition_end = end
-
    __pyx_v_partition_end = __pyx_v_end;
-
+0417:             p = start
-
    __pyx_v_p = __pyx_v_start;
-
 0418:
-
+0419:             while p < partition_end:
-
    while (1) {
-      __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0);
-      if (!__pyx_t_5) break;
-
+0420:                 if self.X[samples[p], best.feature] <= best.threshold:
-
      if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 420, __pyx_L1_error)}
-      __pyx_t_10 = (__pyx_v_samples[__pyx_v_p]);
-      __pyx_t_9 = __pyx_v_best.feature;
-      __pyx_t_5 = (((*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const  *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_10 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))) <= __pyx_v_best.threshold) != 0);
-      if (__pyx_t_5) {
-/* … */
-        goto __pyx_L33;
-      }
-
+0421:                     p += 1
-
        __pyx_v_p = (__pyx_v_p + 1);
-
 0422:
-
 0423:                 else:
-
+0424:                     partition_end -= 1
-
      /*else*/ {
-        __pyx_v_partition_end = (__pyx_v_partition_end - 1);
-
 0425:
-
+0426:                     samples[p], samples[partition_end] = samples[partition_end], samples[p]
-
        __pyx_t_7 = (__pyx_v_samples[__pyx_v_partition_end]);
-        __pyx_t_2 = (__pyx_v_samples[__pyx_v_p]);
-        (__pyx_v_samples[__pyx_v_p]) = __pyx_t_7;
-        (__pyx_v_samples[__pyx_v_partition_end]) = __pyx_t_2;
-      }
-      __pyx_L33:;
-    }
-
 0427:
-
+0428:             self.criterion.reset()
-
    __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 428, __pyx_L1_error)
-
+0429:             self.criterion.update(best.pos)
-
    __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 429, __pyx_L1_error)
-
+0430:             best.improvement = self.criterion.impurity_improvement(impurity)
-
    __pyx_v_best.improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity);
-
+0431:             self.criterion.children_impurity(&best.impurity_left,
-
    ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right));
-
 0432:                                              &best.impurity_right)
-
 0433:
-
 0434:         # Respect invariant for constant features: the original order of
-
 0435:         # element in features[:n_known_constants] must be preserved for sibling
-
 0436:         # and child nodes
-
+0437:         memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants)
-
  (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants)));
-
 0438:
-
 0439:         # Copy newly found constant features
-
+0440:         memcpy(constant_features + n_known_constants,
-
  (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants)));
-
 0441:                features + n_known_constants,
-
 0442:                sizeof(SIZE_t) * n_found_constants)
-
 0443:
-
 0444:         # Return values
-
+0445:         split[0] = best
-
  (__pyx_v_split[0]) = __pyx_v_best;
-
+0446:         n_constant_features[0] = n_total_constants
-
  (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants;
-
+0447:         return 0
-
  __pyx_r = 0;
-  goto __pyx_L0;
-
 0448:
-
 0449:
-
 0450: # Sort n-element arrays pointed to by Xf and samples, simultaneously,
-
 0451: # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997).
-
+0452: cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil:
-
static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) {
-  int __pyx_v_maxd;
-/* … */
-  /* function exit code */
-  __pyx_L0:;
-}
-
+0453:     if n == 0:
-
  __pyx_t_1 = ((__pyx_v_n == 0) != 0);
-  if (__pyx_t_1) {
-/* … */
-  }
-
+0454:       return
-
    goto __pyx_L0;
-
+0455:     cdef int maxd = 2 * <int>log(n)
-
  __pyx_v_maxd = (2 * ((int)__pyx_f_7sklearn_4tree_6_utils_log(__pyx_v_n)));
-
+0456:     introsort(Xf, samples, n, maxd)
-
  __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n, __pyx_v_maxd);
-
 0457:
-
 0458:
-
+0459: cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples,
-
static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j) {
-/* … */
-  /* function exit code */
-}
-
 0460:         SIZE_t i, SIZE_t j) nogil:
-
 0461:     # Helper for sort
-
+0462:     Xf[i], Xf[j] = Xf[j], Xf[i]
-
  __pyx_t_1 = (__pyx_v_Xf[__pyx_v_j]);
-  __pyx_t_2 = (__pyx_v_Xf[__pyx_v_i]);
-  (__pyx_v_Xf[__pyx_v_i]) = __pyx_t_1;
-  (__pyx_v_Xf[__pyx_v_j]) = __pyx_t_2;
-
+0463:     samples[i], samples[j] = samples[j], samples[i]
-
  __pyx_t_3 = (__pyx_v_samples[__pyx_v_j]);
-  __pyx_t_4 = (__pyx_v_samples[__pyx_v_i]);
-  (__pyx_v_samples[__pyx_v_i]) = __pyx_t_3;
-  (__pyx_v_samples[__pyx_v_j]) = __pyx_t_4;
-
 0464:
-
 0465:
-
+0466: cdef inline DTYPE_t median3(DTYPE_t* Xf, SIZE_t n) nogil:
-
static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_median3(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) {
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_a;
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_b;
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_c;
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 0467:     # Median of three pivot selection, after Bentley and McIlroy (1993).
-
 0468:     # Engineering a sort function. SP&E. Requires 8/3 comparisons on average.
-
+0469:     cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1]
-
  __pyx_v_a = (__pyx_v_Xf[0]);
-  __pyx_v_b = (__pyx_v_Xf[(__pyx_v_n / 2)]);
-  __pyx_v_c = (__pyx_v_Xf[(__pyx_v_n - 1)]);
-
+0470:     if a < b:
-
  __pyx_t_1 = ((__pyx_v_a < __pyx_v_b) != 0);
-  if (__pyx_t_1) {
-/* … */
-  }
-
+0471:         if b < c:
-
    __pyx_t_1 = ((__pyx_v_b < __pyx_v_c) != 0);
-    if (__pyx_t_1) {
-/* … */
-    }
-
+0472:             return b
-
      __pyx_r = __pyx_v_b;
-      goto __pyx_L0;
-
+0473:         elif a < c:
-
    __pyx_t_1 = ((__pyx_v_a < __pyx_v_c) != 0);
-    if (__pyx_t_1) {
-/* … */
-    }
-
+0474:             return c
-
      __pyx_r = __pyx_v_c;
-      goto __pyx_L0;
-
 0475:         else:
-
+0476:             return a
-
    /*else*/ {
-      __pyx_r = __pyx_v_a;
-      goto __pyx_L0;
-    }
-
+0477:     elif b < c:
-
  __pyx_t_1 = ((__pyx_v_b < __pyx_v_c) != 0);
-  if (__pyx_t_1) {
-/* … */
-  }
-
+0478:         if a < c:
-
    __pyx_t_1 = ((__pyx_v_a < __pyx_v_c) != 0);
-    if (__pyx_t_1) {
-/* … */
-    }
-
+0479:             return a
-
      __pyx_r = __pyx_v_a;
-      goto __pyx_L0;
-
 0480:         else:
-
+0481:             return c
-
    /*else*/ {
-      __pyx_r = __pyx_v_c;
-      goto __pyx_L0;
-    }
-
 0482:     else:
-
+0483:         return b
-
  /*else*/ {
-    __pyx_r = __pyx_v_b;
-    goto __pyx_L0;
-  }
-
 0484:
-
 0485:
-
 0486: # Introsort with median of 3 pivot selection and 3-way partition function
-
 0487: # (robust to repeated elements, e.g. lots of zero features).
-
+0488: cdef void introsort(DTYPE_t* Xf, SIZE_t *samples,
-
static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n, int __pyx_v_maxd) {
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_pivot;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_l;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_r;
-/* … */
-  /* function exit code */
-  __pyx_L0:;
-}
-
 0489:                     SIZE_t n, int maxd) nogil:
-
 0490:     cdef DTYPE_t pivot
-
 0491:     cdef SIZE_t i, l, r
-
 0492:
-
+0493:     while n > 1:
-
  while (1) {
-    __pyx_t_1 = ((__pyx_v_n > 1) != 0);
-    if (!__pyx_t_1) break;
-
+0494:         if maxd <= 0:   # max depth limit exceeded ("gone quadratic")
-
    __pyx_t_1 = ((__pyx_v_maxd <= 0) != 0);
-    if (__pyx_t_1) {
-/* … */
-    }
-
+0495:             heapsort(Xf, samples, n)
-
      __pyx_f_13stpredictions_6models_3OK3_9_splitter_heapsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n);
-
+0496:             return
-
      goto __pyx_L0;
-
+0497:         maxd -= 1
-
    __pyx_v_maxd = (__pyx_v_maxd - 1);
-
 0498:
-
+0499:         pivot = median3(Xf, n)
-
    __pyx_v_pivot = __pyx_f_13stpredictions_6models_3OK3_9_splitter_median3(__pyx_v_Xf, __pyx_v_n);
-
 0500:
-
 0501:         # Three-way partition.
-
+0502:         i = l = 0
-
    __pyx_v_i = 0;
-    __pyx_v_l = 0;
-
+0503:         r = n
-
    __pyx_v_r = __pyx_v_n;
-
+0504:         while i < r:
-
    while (1) {
-      __pyx_t_1 = ((__pyx_v_i < __pyx_v_r) != 0);
-      if (!__pyx_t_1) break;
-
+0505:             if Xf[i] < pivot:
-
      __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_i]) < __pyx_v_pivot) != 0);
-      if (__pyx_t_1) {
-/* … */
-        goto __pyx_L8;
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-
+0506:                 swap(Xf, samples, i, l)
-
        __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_l);
-
+0507:                 i += 1
-
        __pyx_v_i = (__pyx_v_i + 1);
-
+0508:                 l += 1
-
        __pyx_v_l = (__pyx_v_l + 1);
-
+0509:             elif Xf[i] > pivot:
-
      __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_i]) > __pyx_v_pivot) != 0);
-      if (__pyx_t_1) {
-/* … */
-        goto __pyx_L8;
-      }
-
+0510:                 r -= 1
-
        __pyx_v_r = (__pyx_v_r - 1);
-
+0511:                 swap(Xf, samples, i, r)
-
        __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_r);
-
 0512:             else:
-
+0513:                 i += 1
-
      /*else*/ {
-        __pyx_v_i = (__pyx_v_i + 1);
-      }
-      __pyx_L8:;
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-
 0514:
-
+0515:         introsort(Xf, samples, l, maxd)
-
    __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_l, __pyx_v_maxd);
-
+0516:         Xf += r
-
    __pyx_v_Xf = (__pyx_v_Xf + __pyx_v_r);
-
+0517:         samples += r
-
    __pyx_v_samples = (__pyx_v_samples + __pyx_v_r);
-
+0518:         n -= r
-
    __pyx_v_n = (__pyx_v_n - __pyx_v_r);
-  }
-
 0519:
-
 0520:
-
+0521: cdef inline void sift_down(DTYPE_t* Xf, SIZE_t* samples,
-
static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end) {
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-/* … */
-  /* function exit code */
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-
 0522:                            SIZE_t start, SIZE_t end) nogil:
-
 0523:     # Restore heap order in Xf[start:end] by moving the max element to start.
-
 0524:     cdef SIZE_t child, maxind, root
-
 0525:
-
+0526:     root = start
-
  __pyx_v_root = __pyx_v_start;
-
+0527:     while True:
-
  while (1) {
-
+0528:         child = root * 2 + 1
-
    __pyx_v_child = ((__pyx_v_root * 2) + 1);
-
 0529:
-
 0530:         # find max of root, left child, right child
-
+0531:         maxind = root
-
    __pyx_v_maxind = __pyx_v_root;
-
+0532:         if child < end and Xf[maxind] < Xf[child]:
-
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-    __pyx_t_1 = __pyx_t_2;
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-/* … */
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-
+0533:             maxind = child
-
      __pyx_v_maxind = __pyx_v_child;
-
+0534:         if child + 1 < end and Xf[maxind] < Xf[child + 1]:
-
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-/* … */
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-
+0535:             maxind = child + 1
-
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-
 0536:
-
+0537:         if maxind == root:
-
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-/* … */
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-
+0538:             break
-
      goto __pyx_L4_break;
-
 0539:         else:
-
+0540:             swap(Xf, samples, root, maxind)
-
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-      __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_root, __pyx_v_maxind);
-
+0541:             root = maxind
-
      __pyx_v_root = __pyx_v_maxind;
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-
 0542:
-
 0543:
-
+0544: cdef void heapsort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil:
-
static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) {
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-/* … */
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 0545:     cdef SIZE_t start, end
-
 0546:
-
 0547:     # heapify
-
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-
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-
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-
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-
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-
  while (1) {
-
+0551:         sift_down(Xf, samples, start, end)
-
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-
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-
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-/* … */
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+0553:             break
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 0555:
-
 0556:     # sort by shrinking the heap, putting the max element immediately after it
-
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-
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-
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+0559:         swap(Xf, samples, 0, end)
-
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-
+0560:         sift_down(Xf, samples, 0, end)
-
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+0561:         end = end - 1
-
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 0562:
-
 0563:
-
+0564: cdef class RandomSplitter(BaseDenseSplitter):
-
struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter {
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-/* … */
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-
 0565:     """Splitter for finding the best random split."""
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+0566:     def __reduce__(self):
-
/* Python wrapper */
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+0571:                                  self.random_state), self.__getstate__())
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 0572:
-
+0573:     cdef int node_split(self, double impurity, SplitRecord* split,
-
static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features) {
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-  __pyx_t_7sklearn_4tree_5_tree_UINT32_t *__pyx_v_random_state;
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-  struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_current;
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-  double __pyx_v_best_proxy_improvement;
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-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_j;
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-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_drawn_constants;
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-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_current_feature_value;
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-  __pyx_L0:;
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 0574:                         SIZE_t* n_constant_features) nogil except -1:
-
 0575:         """Find the best random split on node samples[start:end]
-
 0576:
-
 0577:         Returns -1 in case of failure to allocate memory (and raise MemoryError)
-
 0578:         or 0 otherwise.
-
 0579:         """
-
 0580:         # Draw random splits and pick the best
-
+0581:         cdef SIZE_t* samples = self.samples
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.samples;
-  __pyx_v_samples = __pyx_t_1;
-
+0582:         cdef SIZE_t start = self.start
-
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-  __pyx_v_start = __pyx_t_2;
-
+0583:         cdef SIZE_t end = self.end
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end;
-  __pyx_v_end = __pyx_t_2;
-
 0584:
-
+0585:         cdef SIZE_t* features = self.features
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.features;
-  __pyx_v_features = __pyx_t_1;
-
+0586:         cdef SIZE_t* constant_features = self.constant_features
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.constant_features;
-  __pyx_v_constant_features = __pyx_t_1;
-
+0587:         cdef SIZE_t n_features = self.n_features
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_features;
-  __pyx_v_n_features = __pyx_t_2;
-
 0588:
-
+0589:         cdef DTYPE_t* Xf = self.feature_values
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.feature_values;
-  __pyx_v_Xf = __pyx_t_3;
-
+0590:         cdef SIZE_t max_features = self.max_features
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features;
-  __pyx_v_max_features = __pyx_t_2;
-
+0591:         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf;
-  __pyx_v_min_samples_leaf = __pyx_t_2;
-
+0592:         cdef double min_weight_leaf = self.min_weight_leaf
-
  __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf;
-  __pyx_v_min_weight_leaf = __pyx_t_4;
-
+0593:         cdef UINT32_t* random_state = &self.rand_r_state
-
  __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state);
-
 0594:
-
 0595:         cdef SplitRecord best, current
-
+0596:         cdef double current_proxy_improvement = - INFINITY
-
  __pyx_v_current_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY);
-
+0597:         cdef double best_proxy_improvement = - INFINITY
-
  __pyx_v_best_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY);
-
 0598:
-
+0599:         cdef SIZE_t f_i = n_features
-
  __pyx_v_f_i = __pyx_v_n_features;
-
 0600:         cdef SIZE_t f_j
-
 0601:         cdef SIZE_t p
-
 0602:         cdef SIZE_t partition_end
-
 0603:         cdef SIZE_t feature_stride
-
 0604:         # Number of features discovered to be constant during the split search
-
+0605:         cdef SIZE_t n_found_constants = 0
-
  __pyx_v_n_found_constants = 0;
-
 0606:         # Number of features known to be constant and drawn without replacement
-
+0607:         cdef SIZE_t n_drawn_constants = 0
-
  __pyx_v_n_drawn_constants = 0;
-
+0608:         cdef SIZE_t n_known_constants = n_constant_features[0]
-
  __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]);
-
 0609:         # n_total_constants = n_known_constants + n_found_constants
-
+0610:         cdef SIZE_t n_total_constants = n_known_constants
-
  __pyx_v_n_total_constants = __pyx_v_n_known_constants;
-
+0611:         cdef SIZE_t n_visited_features = 0
-
  __pyx_v_n_visited_features = 0;
-
 0612:         cdef DTYPE_t min_feature_value
-
 0613:         cdef DTYPE_t max_feature_value
-
 0614:         cdef DTYPE_t current_feature_value
-
 0615:
-
+0616:         _init_split(&best, end)
-
  __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end);
-
 0617:
-
 0618:         # Sample up to max_features without replacement using a
-
 0619:         # Fisher-Yates-based algorithm (using the local variables `f_i` and
-
 0620:         # `f_j` to compute a permutation of the `features` array).
-
 0621:         #
-
 0622:         # Skip the CPU intensive evaluation of the impurity criterion for
-
 0623:         # features that were already detected as constant (hence not suitable
-
 0624:         # for good splitting) by ancestor nodes and save the information on
-
 0625:         # newly discovered constant features to spare computation on descendant
-
 0626:         # nodes.
-
+0627:         while (f_i > n_total_constants and  # Stop early if remaining features
-
  while (1) {
-    __pyx_t_6 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0);
-    if (__pyx_t_6) {
-    } else {
-      __pyx_t_5 = __pyx_t_6;
-      goto __pyx_L5_bool_binop_done;
-    }
-
 0628:                                             # are constant
-
+0629:                 (n_visited_features < max_features or
-
    __pyx_t_6 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0);
-    if (!__pyx_t_6) {
-    } else {
-      __pyx_t_5 = __pyx_t_6;
-      goto __pyx_L5_bool_binop_done;
-    }
-
 0630:                  # At least one drawn features must be non constant
-
+0631:                  n_visited_features <= n_found_constants + n_drawn_constants)):
-
    __pyx_t_6 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0);
-    __pyx_t_5 = __pyx_t_6;
-    __pyx_L5_bool_binop_done:;
-    if (!__pyx_t_5) break;
-
+0632:             n_visited_features += 1
-
    __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1);
-
 0633:
-
 0634:             # Loop invariant: elements of features in
-
 0635:             # - [:n_drawn_constant[ holds drawn and known constant features;
-
 0636:             # - [n_drawn_constant:n_known_constant[ holds known constant
-
 0637:             #   features that haven't been drawn yet;
-
 0638:             # - [n_known_constant:n_total_constant[ holds newly found constant
-
 0639:             #   features;
-
 0640:             # - [n_total_constant:f_i[ holds features that haven't been drawn
-
 0641:             #   yet and aren't constant apriori.
-
 0642:             # - [f_i:n_features[ holds features that have been drawn
-
 0643:             #   and aren't constant.
-
 0644:
-
 0645:             # Draw a feature at random
-
+0646:             f_j = rand_int(n_drawn_constants, f_i - n_found_constants,
-
    __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state);
-
 0647:                            random_state)
-
 0648:
-
+0649:             if f_j < n_known_constants:
-
    __pyx_t_5 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0);
-    if (__pyx_t_5) {
-/* … */
-      goto __pyx_L8;
-    }
-
 0650:                 # f_j in the interval [n_drawn_constants, n_known_constants[
-
+0651:                 features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants]
-
      __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]);
-      __pyx_t_7 = (__pyx_v_features[__pyx_v_n_drawn_constants]);
-      (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_2;
-      (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7;
-
+0652:                 n_drawn_constants += 1
-
      __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1);
-
 0653:
-
 0654:             else:
-
 0655:                 # f_j in the interval [n_known_constants, f_i - n_found_constants[
-
+0656:                 f_j += n_found_constants
-
    /*else*/ {
-      __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants);
-
 0657:                 # f_j in the interval [n_total_constants, f_i[
-
 0658:
-
+0659:                 current.feature = features[f_j]
-
      __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]);
-
 0660:
-
 0661:                 # Find min, max
-
+0662:                 min_feature_value = self.X[samples[start], current.feature]
-
      if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 662, __pyx_L1_error)}
-      __pyx_t_8 = (__pyx_v_samples[__pyx_v_start]);
-      __pyx_t_9 = __pyx_v_current.feature;
-      __pyx_v_min_feature_value = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const  *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) )));
-
+0663:                 max_feature_value = min_feature_value
-
      __pyx_v_max_feature_value = __pyx_v_min_feature_value;
-
+0664:                 Xf[start] = min_feature_value
-
      (__pyx_v_Xf[__pyx_v_start]) = __pyx_v_min_feature_value;
-
 0665:
-
+0666:                 for p in range(start + 1, end):
-
      __pyx_t_7 = __pyx_v_end;
-      __pyx_t_2 = __pyx_t_7;
-      for (__pyx_t_10 = (__pyx_v_start + 1); __pyx_t_10 < __pyx_t_2; __pyx_t_10+=1) {
-        __pyx_v_p = __pyx_t_10;
-
+0667:                     current_feature_value = self.X[samples[p], current.feature]
-
        if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 667, __pyx_L1_error)}
-        __pyx_t_9 = (__pyx_v_samples[__pyx_v_p]);
-        __pyx_t_8 = __pyx_v_current.feature;
-        __pyx_v_current_feature_value = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const  *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[1]) )));
-
+0668:                     Xf[p] = current_feature_value
-
        (__pyx_v_Xf[__pyx_v_p]) = __pyx_v_current_feature_value;
-
 0669:
-
+0670:                     if current_feature_value < min_feature_value:
-
        __pyx_t_5 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0);
-        if (__pyx_t_5) {
-/* … */
-          goto __pyx_L11;
-        }
-
+0671:                         min_feature_value = current_feature_value
-
          __pyx_v_min_feature_value = __pyx_v_current_feature_value;
-
+0672:                     elif current_feature_value > max_feature_value:
-
        __pyx_t_5 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0);
-        if (__pyx_t_5) {
-/* … */
-        }
-        __pyx_L11:;
-      }
-
+0673:                         max_feature_value = current_feature_value
-
          __pyx_v_max_feature_value = __pyx_v_current_feature_value;
-
 0674:
-
+0675:                 if max_feature_value <= min_feature_value + FEATURE_THRESHOLD:
-
      __pyx_t_5 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0);
-      if (__pyx_t_5) {
-/* … */
-        goto __pyx_L12;
-      }
-
+0676:                     features[f_j], features[n_total_constants] = features[n_total_constants], current.feature
-
        __pyx_t_7 = (__pyx_v_features[__pyx_v_n_total_constants]);
-        __pyx_t_2 = __pyx_v_current.feature;
-        (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7;
-        (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2;
-
 0677:
-
+0678:                     n_found_constants += 1
-
        __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1);
-
+0679:                     n_total_constants += 1
-
        __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1);
-
 0680:
-
 0681:                 else:
-
+0682:                     f_i -= 1
-
      /*else*/ {
-        __pyx_v_f_i = (__pyx_v_f_i - 1);
-
+0683:                     features[f_i], features[f_j] = features[f_j], features[f_i]
-
        __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]);
-        __pyx_t_7 = (__pyx_v_features[__pyx_v_f_i]);
-        (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2;
-        (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7;
-
 0684:
-
 0685:                     # Draw a random threshold
-
+0686:                     current.threshold = rand_uniform(min_feature_value,
-
        __pyx_v_current.threshold = __pyx_f_7sklearn_4tree_6_utils_rand_uniform(__pyx_v_min_feature_value, __pyx_v_max_feature_value, __pyx_v_random_state);
-
 0687:                                                      max_feature_value,
-
 0688:                                                      random_state)
-
 0689:
-
+0690:                     if current.threshold == max_feature_value:
-
        __pyx_t_5 = ((__pyx_v_current.threshold == __pyx_v_max_feature_value) != 0);
-        if (__pyx_t_5) {
-/* … */
-        }
-
+0691:                         current.threshold = min_feature_value
-
          __pyx_v_current.threshold = __pyx_v_min_feature_value;
-
 0692:
-
 0693:                     # Partition
-
+0694:                     p, partition_end = start, end
-
        __pyx_t_7 = __pyx_v_start;
-        __pyx_t_2 = __pyx_v_end;
-        __pyx_v_p = __pyx_t_7;
-        __pyx_v_partition_end = __pyx_t_2;
-
+0695:                     while p < partition_end:
-
        while (1) {
-          __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0);
-          if (!__pyx_t_5) break;
-
+0696:                         if Xf[p] <= current.threshold:
-
          __pyx_t_5 = (((__pyx_v_Xf[__pyx_v_p]) <= __pyx_v_current.threshold) != 0);
-          if (__pyx_t_5) {
-/* … */
-            goto __pyx_L16;
-          }
-
+0697:                             p += 1
-
            __pyx_v_p = (__pyx_v_p + 1);
-
 0698:                         else:
-
+0699:                             partition_end -= 1
-
          /*else*/ {
-            __pyx_v_partition_end = (__pyx_v_partition_end - 1);
-
 0700:
-
+0701:                             Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p]
-
            __pyx_t_11 = (__pyx_v_Xf[__pyx_v_partition_end]);
-            __pyx_t_12 = (__pyx_v_Xf[__pyx_v_p]);
-            (__pyx_v_Xf[__pyx_v_p]) = __pyx_t_11;
-            (__pyx_v_Xf[__pyx_v_partition_end]) = __pyx_t_12;
-
+0702:                             samples[p], samples[partition_end] = samples[partition_end], samples[p]
-
            __pyx_t_2 = (__pyx_v_samples[__pyx_v_partition_end]);
-            __pyx_t_7 = (__pyx_v_samples[__pyx_v_p]);
-            (__pyx_v_samples[__pyx_v_p]) = __pyx_t_2;
-            (__pyx_v_samples[__pyx_v_partition_end]) = __pyx_t_7;
-          }
-          __pyx_L16:;
-        }
-
 0703:
-
+0704:                     current.pos = partition_end
-
        __pyx_v_current.pos = __pyx_v_partition_end;
-
 0705:
-
 0706:                     # Reject if min_samples_leaf is not guaranteed
-
+0707:                     if (((current.pos - start) < min_samples_leaf) or
-
        __pyx_t_6 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0);
-        if (!__pyx_t_6) {
-        } else {
-          __pyx_t_5 = __pyx_t_6;
-          goto __pyx_L18_bool_binop_done;
-        }
-/* … */
-        if (__pyx_t_5) {
-/* … */
-        }
-
+0708:                             ((end - current.pos) < min_samples_leaf)):
-
        __pyx_t_6 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0);
-        __pyx_t_5 = __pyx_t_6;
-        __pyx_L18_bool_binop_done:;
-
+0709:                         continue
-
          goto __pyx_L3_continue;
-
 0710:
-
 0711:                     # Evaluate split
-
+0712:                     self.criterion.reset()
-
        __pyx_t_13 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 712, __pyx_L1_error)
-
+0713:                     self.criterion.update(current.pos)
-
        __pyx_t_13 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 713, __pyx_L1_error)
-
 0714:
-
 0715:                     # Reject if min_weight_leaf is not satisfied
-
+0716:                     if ((self.criterion.weighted_n_left < min_weight_leaf) or
-
        __pyx_t_6 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_left < __pyx_v_min_weight_leaf) != 0);
-        if (!__pyx_t_6) {
-        } else {
-          __pyx_t_5 = __pyx_t_6;
-          goto __pyx_L21_bool_binop_done;
-        }
-/* … */
-        if (__pyx_t_5) {
-/* … */
-        }
-
+0717:                             (self.criterion.weighted_n_right < min_weight_leaf)):
-
        __pyx_t_6 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_right < __pyx_v_min_weight_leaf) != 0);
-        __pyx_t_5 = __pyx_t_6;
-        __pyx_L21_bool_binop_done:;
-
+0718:                         continue
-
          goto __pyx_L3_continue;
-
 0719:
-
+0720:                     current_proxy_improvement = self.criterion.proxy_impurity_improvement()
-
        __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion);
-
 0721:
-
+0722:                     if current_proxy_improvement > best_proxy_improvement:
-
        __pyx_t_5 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0);
-        if (__pyx_t_5) {
-/* … */
-        }
-      }
-      __pyx_L12:;
-    }
-    __pyx_L8:;
-    __pyx_L3_continue:;
-  }
-
+0723:                         best_proxy_improvement = current_proxy_improvement
-
          __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement;
-
+0724:                         best = current  # copy
-
          __pyx_v_best = __pyx_v_current;
-
 0725:
-
 0726:         # Reorganize into samples[start:best.pos] + samples[best.pos:end]
-
+0727:         if best.pos < end:
-
  __pyx_t_5 = ((__pyx_v_best.pos < __pyx_v_end) != 0);
-  if (__pyx_t_5) {
-/* … */
-  }
-
+0728:             if current.feature != best.feature:
-
    __pyx_t_5 = ((__pyx_v_current.feature != __pyx_v_best.feature) != 0);
-    if (__pyx_t_5) {
-/* … */
-    }
-
+0729:                 p, partition_end = start, end
-
      __pyx_t_7 = __pyx_v_start;
-      __pyx_t_2 = __pyx_v_end;
-      __pyx_v_p = __pyx_t_7;
-      __pyx_v_partition_end = __pyx_t_2;
-
 0730:
-
+0731:                 while p < partition_end:
-
      while (1) {
-        __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0);
-        if (!__pyx_t_5) break;
-
+0732:                     if self.X[samples[p], best.feature] <= best.threshold:
-
        if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 732, __pyx_L1_error)}
-        __pyx_t_8 = (__pyx_v_samples[__pyx_v_p]);
-        __pyx_t_9 = __pyx_v_best.feature;
-        __pyx_t_5 = (((*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const  *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))) <= __pyx_v_best.threshold) != 0);
-        if (__pyx_t_5) {
-/* … */
-          goto __pyx_L28;
-        }
-
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-
+0737:                         samples[p], samples[partition_end] = samples[partition_end], samples[p]
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 0744:
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-
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-
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-
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-
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-
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-
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-
-
 0762:     # The sparse splitter works only with csc sparse matrix format
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-
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-
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-  __pyx_t_3 = PyObject_IsInstance(__pyx_v_X, __pyx_t_2); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(0, 803, __pyx_L1_error)
-  __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
-  __pyx_t_4 = ((!(__pyx_t_3 != 0)) != 0);
-  if (unlikely(__pyx_t_4)) {
-/* … */
-  }
-
+0804:             raise ValueError("X should be in csc format")
-
    __pyx_t_2 = __Pyx_PyObject_Call(__pyx_builtin_ValueError, __pyx_tuple__5, NULL); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 804, __pyx_L1_error)
-    __Pyx_GOTREF(__pyx_t_2);
-    __Pyx_Raise(__pyx_t_2, 0, 0, 0);
-    __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
-    __PYX_ERR(0, 804, __pyx_L1_error)
-/* … */
-  __pyx_tuple__5 = PyTuple_Pack(1, __pyx_kp_s_X_should_be_in_csc_format); if (unlikely(!__pyx_tuple__5)) __PYX_ERR(0, 804, __pyx_L1_error)
-  __Pyx_GOTREF(__pyx_tuple__5);
-  __Pyx_GIVEREF(__pyx_tuple__5);
-
 0805:
-
+0806:         cdef SIZE_t* samples = self.samples
-
  __pyx_t_5 = __pyx_v_self->__pyx_base.samples;
-  __pyx_v_samples = __pyx_t_5;
-
+0807:         cdef SIZE_t n_samples = self.n_samples
-
  __pyx_t_6 = __pyx_v_self->__pyx_base.n_samples;
-  __pyx_v_n_samples = __pyx_t_6;
-
 0808:
-
 0809:         # Initialize X
-
+0810:         cdef np.ndarray[dtype=DTYPE_t, ndim=1] data = X.data
-
  __pyx_t_2 = __Pyx_PyObject_GetAttrStr(__pyx_v_X, __pyx_n_s_data); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 810, __pyx_L1_error)
-  __Pyx_GOTREF(__pyx_t_2);
-  if (!(likely(((__pyx_t_2) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_2, __pyx_ptype_5numpy_ndarray))))) __PYX_ERR(0, 810, __pyx_L1_error)
-  __pyx_t_7 = ((PyArrayObject *)__pyx_t_2);
-  {
-    __Pyx_BufFmt_StackElem __pyx_stack[1];
-    if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_data.rcbuffer->pybuffer, (PyObject*)__pyx_t_7, &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {
-      __pyx_v_data = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_data.rcbuffer->pybuffer.buf = NULL;
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-    }
-  }
-  __pyx_t_7 = 0;
-  __pyx_v_data = ((PyArrayObject *)__pyx_t_2);
-  __pyx_t_2 = 0;
-
+0811:         cdef np.ndarray[dtype=INT32_t, ndim=1] indices = X.indices
-
  __pyx_t_2 = __Pyx_PyObject_GetAttrStr(__pyx_v_X, __pyx_n_s_indices); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 811, __pyx_L1_error)
-  __Pyx_GOTREF(__pyx_t_2);
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-  __pyx_t_8 = ((PyArrayObject *)__pyx_t_2);
-  {
-    __Pyx_BufFmt_StackElem __pyx_stack[1];
-    if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_t_8, &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_INT32_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {
-      __pyx_v_indices = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_indices.rcbuffer->pybuffer.buf = NULL;
-      __PYX_ERR(0, 811, __pyx_L1_error)
-    } else {__pyx_pybuffernd_indices.diminfo[0].strides = __pyx_pybuffernd_indices.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_indices.diminfo[0].shape = __pyx_pybuffernd_indices.rcbuffer->pybuffer.shape[0];
-    }
-  }
-  __pyx_t_8 = 0;
-  __pyx_v_indices = ((PyArrayObject *)__pyx_t_2);
-  __pyx_t_2 = 0;
-
+0812:         cdef np.ndarray[dtype=INT32_t, ndim=1] indptr = X.indptr
-
  __pyx_t_2 = __Pyx_PyObject_GetAttrStr(__pyx_v_X, __pyx_n_s_indptr); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 812, __pyx_L1_error)
-  __Pyx_GOTREF(__pyx_t_2);
-  if (!(likely(((__pyx_t_2) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_2, __pyx_ptype_5numpy_ndarray))))) __PYX_ERR(0, 812, __pyx_L1_error)
-  __pyx_t_9 = ((PyArrayObject *)__pyx_t_2);
-  {
-    __Pyx_BufFmt_StackElem __pyx_stack[1];
-    if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indptr.rcbuffer->pybuffer, (PyObject*)__pyx_t_9, &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_INT32_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {
-      __pyx_v_indptr = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_indptr.rcbuffer->pybuffer.buf = NULL;
-      __PYX_ERR(0, 812, __pyx_L1_error)
-    } else {__pyx_pybuffernd_indptr.diminfo[0].strides = __pyx_pybuffernd_indptr.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_indptr.diminfo[0].shape = __pyx_pybuffernd_indptr.rcbuffer->pybuffer.shape[0];
-    }
-  }
-  __pyx_t_9 = 0;
-  __pyx_v_indptr = ((PyArrayObject *)__pyx_t_2);
-  __pyx_t_2 = 0;
-
+0813:         cdef SIZE_t n_total_samples = X.shape[0]
-
  __pyx_t_2 = __Pyx_PyObject_GetAttrStr(__pyx_v_X, __pyx_n_s_shape); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 813, __pyx_L1_error)
-  __Pyx_GOTREF(__pyx_t_2);
-  __pyx_t_10 = __Pyx_GetItemInt(__pyx_t_2, 0, long, 1, __Pyx_PyInt_From_long, 0, 0, 0); if (unlikely(!__pyx_t_10)) __PYX_ERR(0, 813, __pyx_L1_error)
-  __Pyx_GOTREF(__pyx_t_10);
-  __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
-  __pyx_t_6 = __Pyx_PyInt_As_Py_intptr_t(__pyx_t_10); if (unlikely((__pyx_t_6 == ((npy_intp)-1)) && PyErr_Occurred())) __PYX_ERR(0, 813, __pyx_L1_error)
-  __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0;
-  __pyx_v_n_total_samples = __pyx_t_6;
-
 0814:
-
+0815:         self.X_data = <DTYPE_t*> data.data
-
  __pyx_v_self->X_data = ((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *)__pyx_v_data->data);
-
+0816:         self.X_indices = <INT32_t*> indices.data
-
  __pyx_v_self->X_indices = ((__pyx_t_7sklearn_4tree_5_tree_INT32_t *)__pyx_v_indices->data);
-
+0817:         self.X_indptr = <INT32_t*> indptr.data
-
  __pyx_v_self->X_indptr = ((__pyx_t_7sklearn_4tree_5_tree_INT32_t *)__pyx_v_indptr->data);
-
+0818:         self.n_total_samples = n_total_samples
-
  __pyx_v_self->n_total_samples = __pyx_v_n_total_samples;
-
 0819:
-
 0820:         # Initialize auxiliary array used to perform split
-
+0821:         safe_realloc(&self.index_to_samples, n_total_samples)
-
  __pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->index_to_samples), __pyx_v_n_total_samples); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 821, __pyx_L1_error)
-
+0822:         safe_realloc(&self.sorted_samples, n_samples)
-
  __pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->sorted_samples), __pyx_v_n_samples); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 822, __pyx_L1_error)
-
 0823:
-
+0824:         cdef SIZE_t* index_to_samples = self.index_to_samples
-
  __pyx_t_5 = __pyx_v_self->index_to_samples;
-  __pyx_v_index_to_samples = __pyx_t_5;
-
 0825:         cdef SIZE_t p
-
+0826:         for p in range(n_total_samples):
-
  __pyx_t_6 = __pyx_v_n_total_samples;
-  __pyx_t_11 = __pyx_t_6;
-  for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) {
-    __pyx_v_p = __pyx_t_12;
-
+0827:             index_to_samples[p] = -1
-
    (__pyx_v_index_to_samples[__pyx_v_p]) = -1;
-  }
-
 0828:
-
+0829:         for p in range(n_samples):
-
  __pyx_t_6 = __pyx_v_n_samples;
-  __pyx_t_11 = __pyx_t_6;
-  for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) {
-    __pyx_v_p = __pyx_t_12;
-
+0830:             index_to_samples[samples[p]] = p
-
    (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_p])]) = __pyx_v_p;
-  }
-
+0831:         return 0
-
  __pyx_r = 0;
-  goto __pyx_L0;
-
 0832:
-
+0833:     cdef inline SIZE_t _partition(self, double threshold,
-
static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, double __pyx_v_threshold, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_zero_pos) {
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_partition_end;
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 0834:                                   SIZE_t end_negative, SIZE_t start_positive,
-
 0835:                                   SIZE_t zero_pos) nogil:
-
 0836:         """Partition samples[start:end] based on threshold."""
-
 0837:
-
 0838:         cdef SIZE_t p
-
 0839:         cdef SIZE_t partition_end
-
 0840:
-
+0841:         cdef DTYPE_t* Xf = self.feature_values
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.feature_values;
-  __pyx_v_Xf = __pyx_t_1;
-
+0842:         cdef SIZE_t* samples = self.samples
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.samples;
-  __pyx_v_samples = __pyx_t_2;
-
+0843:         cdef SIZE_t* index_to_samples = self.index_to_samples
-
  __pyx_t_2 = __pyx_v_self->index_to_samples;
-  __pyx_v_index_to_samples = __pyx_t_2;
-
 0844:
-
+0845:         if threshold < 0.:
-
  __pyx_t_3 = ((__pyx_v_threshold < 0.) != 0);
-  if (__pyx_t_3) {
-/* … */
-    goto __pyx_L3;
-  }
-
+0846:             p = self.start
-
    __pyx_t_4 = __pyx_v_self->__pyx_base.start;
-    __pyx_v_p = __pyx_t_4;
-
+0847:             partition_end = end_negative
-
    __pyx_v_partition_end = __pyx_v_end_negative;
-
+0848:         elif threshold > 0.:
-
  __pyx_t_3 = ((__pyx_v_threshold > 0.) != 0);
-  if (__pyx_t_3) {
-/* … */
-    goto __pyx_L3;
-  }
-
+0849:             p = start_positive
-
    __pyx_v_p = __pyx_v_start_positive;
-
+0850:             partition_end = self.end
-
    __pyx_t_4 = __pyx_v_self->__pyx_base.end;
-    __pyx_v_partition_end = __pyx_t_4;
-
 0851:         else:
-
 0852:             # Data are already split
-
+0853:             return zero_pos
-
  /*else*/ {
-    __pyx_r = __pyx_v_zero_pos;
-    goto __pyx_L0;
-  }
-  __pyx_L3:;
-
 0854:
-
+0855:         while p < partition_end:
-
  while (1) {
-    __pyx_t_3 = ((__pyx_v_p < __pyx_v_partition_end) != 0);
-    if (!__pyx_t_3) break;
-
+0856:             if Xf[p] <= threshold:
-
    __pyx_t_3 = (((__pyx_v_Xf[__pyx_v_p]) <= __pyx_v_threshold) != 0);
-    if (__pyx_t_3) {
-/* … */
-      goto __pyx_L6;
-    }
-
+0857:                 p += 1
-
      __pyx_v_p = (__pyx_v_p + 1);
-
 0858:
-
 0859:             else:
-
+0860:                 partition_end -= 1
-
    /*else*/ {
-      __pyx_v_partition_end = (__pyx_v_partition_end - 1);
-
 0861:
-
+0862:                 Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p]
-
      __pyx_t_5 = (__pyx_v_Xf[__pyx_v_partition_end]);
-      __pyx_t_6 = (__pyx_v_Xf[__pyx_v_p]);
-      (__pyx_v_Xf[__pyx_v_p]) = __pyx_t_5;
-      (__pyx_v_Xf[__pyx_v_partition_end]) = __pyx_t_6;
-
+0863:                 sparse_swap(index_to_samples, samples, p, partition_end)
-
      __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_p, __pyx_v_partition_end);
-    }
-    __pyx_L6:;
-  }
-
 0864:
-
+0865:         return partition_end
-
  __pyx_r = __pyx_v_partition_end;
-  goto __pyx_L0;
-
 0866:
-
+0867:     cdef inline void extract_nnz(self, SIZE_t feature,
-
static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_feature, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive, int *__pyx_v_is_samples_sorted) {
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_indptr_start;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_indptr_end;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_indices;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_samples;
-/* … */
-  /* function exit code */
-}
-
 0868:                                  SIZE_t* end_negative, SIZE_t* start_positive,
-
 0869:                                  bint* is_samples_sorted) nogil:
-
 0870:         """Extract and partition values for a given feature.
-
 0871:
-
 0872:         The extracted values are partitioned between negative values
-
 0873:         Xf[start:end_negative[0]] and positive values Xf[start_positive[0]:end].
-
 0874:         The samples and index_to_samples are modified according to this
-
 0875:         partition.
-
 0876:
-
 0877:         The extraction corresponds to the intersection between the arrays
-
 0878:         X_indices[indptr_start:indptr_end] and samples[start:end].
-
 0879:         This is done efficiently using either an index_to_samples based approach
-
 0880:         or binary search based approach.
-
 0881:
-
 0882:         Parameters
-
 0883:         ----------
-
 0884:         feature : SIZE_t,
-
 0885:             Index of the feature we want to extract non zero value.
-
 0886:
-
 0887:
-
 0888:         end_negative, start_positive : SIZE_t*, SIZE_t*,
-
 0889:             Return extracted non zero values in self.samples[start:end] where
-
 0890:             negative values are in self.feature_values[start:end_negative[0]]
-
 0891:             and positive values are in
-
 0892:             self.feature_values[start_positive[0]:end].
-
 0893:
-
 0894:         is_samples_sorted : bint*,
-
 0895:             If is_samples_sorted, then self.sorted_samples[start:end] will be
-
 0896:             the sorted version of self.samples[start:end].
-
 0897:
-
 0898:         """
-
+0899:         cdef SIZE_t indptr_start = self.X_indptr[feature],
-
  __pyx_v_indptr_start = (__pyx_v_self->X_indptr[__pyx_v_feature]);
-
+0900:         cdef SIZE_t indptr_end = self.X_indptr[feature + 1]
-
  __pyx_v_indptr_end = (__pyx_v_self->X_indptr[(__pyx_v_feature + 1)]);
-
+0901:         cdef SIZE_t n_indices = <SIZE_t>(indptr_end - indptr_start)
-
  __pyx_v_n_indices = ((__pyx_t_7sklearn_4tree_5_tree_SIZE_t)(__pyx_v_indptr_end - __pyx_v_indptr_start));
-
+0902:         cdef SIZE_t n_samples = self.end - self.start
-
  __pyx_v_n_samples = (__pyx_v_self->__pyx_base.end - __pyx_v_self->__pyx_base.start);
-
 0903:
-
 0904:         # Use binary search if n_samples * log(n_indices) <
-
 0905:         # n_indices and index_to_samples approach otherwise.
-
 0906:         # O(n_samples * log(n_indices)) is the running time of binary
-
 0907:         # search and O(n_indices) is the running time of index_to_samples
-
 0908:         # approach.
-
+0909:         if ((1 - is_samples_sorted[0]) * n_samples * log(n_samples) +
-
  if (__pyx_t_1) {
-/* … */
-    goto __pyx_L3;
-  }
-
+0910:                 n_samples * log(n_indices) < EXTRACT_NNZ_SWITCH * n_indices):
-
  __pyx_t_1 = ((((((1 - (__pyx_v_is_samples_sorted[0])) * __pyx_v_n_samples) * __pyx_f_7sklearn_4tree_6_utils_log(__pyx_v_n_samples)) + (__pyx_v_n_samples * __pyx_f_7sklearn_4tree_6_utils_log(__pyx_v_n_indices))) < (__pyx_v_13stpredictions_6models_3OK3_9_splitter_EXTRACT_NNZ_SWITCH * __pyx_v_n_indices)) != 0);
-
+0911:             extract_nnz_binary_search(self.X_indices, self.X_data,
-
    __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_binary_search(__pyx_v_self->X_indices, __pyx_v_self->X_data, __pyx_v_indptr_start, __pyx_v_indptr_end, __pyx_v_self->__pyx_base.samples, __pyx_v_self->__pyx_base.start, __pyx_v_self->__pyx_base.end, __pyx_v_self->index_to_samples, __pyx_v_self->__pyx_base.feature_values, __pyx_v_end_negative, __pyx_v_start_positive, __pyx_v_self->sorted_samples, __pyx_v_is_samples_sorted);
-
 0912:                                       indptr_start, indptr_end,
-
 0913:                                       self.samples, self.start, self.end,
-
 0914:                                       self.index_to_samples,
-
 0915:                                       self.feature_values,
-
 0916:                                       end_negative, start_positive,
-
 0917:                                       self.sorted_samples, is_samples_sorted)
-
 0918:
-
 0919:         # Using an index to samples  technique to extract non zero values
-
 0920:         # index_to_samples is a mapping from X_indices to samples
-
 0921:         else:
-
+0922:             extract_nnz_index_to_samples(self.X_indices, self.X_data,
-
  /*else*/ {
-/* … */
-    __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_index_to_samples(__pyx_v_self->X_indices, __pyx_v_self->X_data, __pyx_v_indptr_start, __pyx_v_indptr_end, __pyx_v_self->__pyx_base.samples, __pyx_v_self->__pyx_base.start, __pyx_v_self->__pyx_base.end, __pyx_v_self->index_to_samples, __pyx_v_self->__pyx_base.feature_values, __pyx_v_end_negative, __pyx_v_start_positive);
-  }
-  __pyx_L3:;
-
 0923:                                          indptr_start, indptr_end,
-
 0924:                                          self.samples, self.start, self.end,
-
 0925:                                          self.index_to_samples,
-
 0926:                                          self.feature_values,
-
 0927:                                          end_negative, start_positive)
-
 0928:
-
 0929:
-
+0930: cdef int compare_SIZE_t(const void* a, const void* b) nogil:
-
static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_compare_SIZE_t(void const *__pyx_v_a, void const *__pyx_v_b) {
-  int __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 0931:     """Comparison function for sort."""
-
+0932:     return <int>((<SIZE_t*>a)[0] - (<SIZE_t*>b)[0])
-
  __pyx_r = ((int)((((__pyx_t_7sklearn_4tree_5_tree_SIZE_t *)__pyx_v_a)[0]) - (((__pyx_t_7sklearn_4tree_5_tree_SIZE_t *)__pyx_v_b)[0])));
-  goto __pyx_L0;
-
 0933:
-
 0934:
-
+0935: cdef inline void binary_search(INT32_t* sorted_array,
-
static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_sorted_array, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_value, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index, __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_new_start) {
-  __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_pivot;
-/* … */
-  /* function exit code */
-}
-
 0936:                                INT32_t start, INT32_t end,
-
 0937:                                SIZE_t value, SIZE_t* index,
-
 0938:                                INT32_t* new_start) nogil:
-
 0939:     """Return the index of value in the sorted array.
-
 0940:
-
 0941:     If not found, return -1. new_start is the last pivot + 1
-
 0942:     """
-
 0943:     cdef INT32_t pivot
-
+0944:     index[0] = -1
-
  (__pyx_v_index[0]) = -1;
-
+0945:     while start < end:
-
  while (1) {
-    __pyx_t_1 = ((__pyx_v_start < __pyx_v_end) != 0);
-    if (!__pyx_t_1) break;
-
+0946:         pivot = start + (end - start) / 2
-
    __pyx_v_pivot = (__pyx_v_start + ((__pyx_v_end - __pyx_v_start) / 2));
-
 0947:
-
+0948:         if sorted_array[pivot] == value:
-
    __pyx_t_1 = (((__pyx_v_sorted_array[__pyx_v_pivot]) == __pyx_v_value) != 0);
-    if (__pyx_t_1) {
-/* … */
-    }
-
+0949:             index[0] = pivot
-
      (__pyx_v_index[0]) = __pyx_v_pivot;
-
+0950:             start = pivot + 1
-
      __pyx_v_start = (__pyx_v_pivot + 1);
-
+0951:             break
-
      goto __pyx_L4_break;
-
 0952:
-
+0953:         if sorted_array[pivot] < value:
-
    __pyx_t_1 = (((__pyx_v_sorted_array[__pyx_v_pivot]) < __pyx_v_value) != 0);
-    if (__pyx_t_1) {
-/* … */
-      goto __pyx_L6;
-    }
-
+0954:             start = pivot + 1
-
      __pyx_v_start = (__pyx_v_pivot + 1);
-
 0955:         else:
-
+0956:             end = pivot
-
    /*else*/ {
-      __pyx_v_end = __pyx_v_pivot;
-    }
-    __pyx_L6:;
-  }
-  __pyx_L4_break:;
-
+0957:     new_start[0] = start
-
  (__pyx_v_new_start[0]) = __pyx_v_start;
-
 0958:
-
 0959:
-
+0960: cdef inline void extract_nnz_index_to_samples(INT32_t* X_indices,
-
static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_index_to_samples(__pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indices, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X_data, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_start, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive) {
-  __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_k;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_index;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative_;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive_;
-/* … */
-  /* function exit code */
-}
-
 0961:                                               DTYPE_t* X_data,
-
 0962:                                               INT32_t indptr_start,
-
 0963:                                               INT32_t indptr_end,
-
 0964:                                               SIZE_t* samples,
-
 0965:                                               SIZE_t start,
-
 0966:                                               SIZE_t end,
-
 0967:                                               SIZE_t* index_to_samples,
-
 0968:                                               DTYPE_t* Xf,
-
 0969:                                               SIZE_t* end_negative,
-
 0970:                                               SIZE_t* start_positive) nogil:
-
 0971:     """Extract and partition values for a feature using index_to_samples.
-
 0972:
-
 0973:     Complexity is O(indptr_end - indptr_start).
-
 0974:     """
-
 0975:     cdef INT32_t k
-
 0976:     cdef SIZE_t index
-
+0977:     cdef SIZE_t end_negative_ = start
-
  __pyx_v_end_negative_ = __pyx_v_start;
-
+0978:     cdef SIZE_t start_positive_ = end
-
  __pyx_v_start_positive_ = __pyx_v_end;
-
 0979:
-
+0980:     for k in range(indptr_start, indptr_end):
-
  __pyx_t_1 = __pyx_v_indptr_end;
-  __pyx_t_2 = __pyx_t_1;
-  for (__pyx_t_3 = __pyx_v_indptr_start; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
-    __pyx_v_k = __pyx_t_3;
-
+0981:         if start <= index_to_samples[X_indices[k]] < end:
-
    __pyx_t_4 = (__pyx_v_start <= (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]));
-    if (__pyx_t_4) {
-      __pyx_t_4 = ((__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]) < __pyx_v_end);
-    }
-    __pyx_t_5 = (__pyx_t_4 != 0);
-    if (__pyx_t_5) {
-/* … */
-    }
-  }
-
+0982:             if X_data[k] > 0:
-
      __pyx_t_5 = (((__pyx_v_X_data[__pyx_v_k]) > 0.0) != 0);
-      if (__pyx_t_5) {
-/* … */
-        goto __pyx_L6;
-      }
-
+0983:                 start_positive_ -= 1
-
        __pyx_v_start_positive_ = (__pyx_v_start_positive_ - 1);
-
+0984:                 Xf[start_positive_] = X_data[k]
-
        (__pyx_v_Xf[__pyx_v_start_positive_]) = (__pyx_v_X_data[__pyx_v_k]);
-
+0985:                 index = index_to_samples[X_indices[k]]
-
        __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]);
-
+0986:                 sparse_swap(index_to_samples, samples, index, start_positive_)
-
        __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_start_positive_);
-
 0987:
-
 0988:
-
+0989:             elif X_data[k] < 0:
-
      __pyx_t_5 = (((__pyx_v_X_data[__pyx_v_k]) < 0.0) != 0);
-      if (__pyx_t_5) {
-/* … */
-      }
-      __pyx_L6:;
-
+0990:                 Xf[end_negative_] = X_data[k]
-
        (__pyx_v_Xf[__pyx_v_end_negative_]) = (__pyx_v_X_data[__pyx_v_k]);
-
+0991:                 index = index_to_samples[X_indices[k]]
-
        __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]);
-
+0992:                 sparse_swap(index_to_samples, samples, index, end_negative_)
-
        __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_end_negative_);
-
+0993:                 end_negative_ += 1
-
        __pyx_v_end_negative_ = (__pyx_v_end_negative_ + 1);
-
 0994:
-
 0995:     # Returned values
-
+0996:     end_negative[0] = end_negative_
-
  (__pyx_v_end_negative[0]) = __pyx_v_end_negative_;
-
+0997:     start_positive[0] = start_positive_
-
  (__pyx_v_start_positive[0]) = __pyx_v_start_positive_;
-
 0998:
-
 0999:
-
+1000: cdef inline void extract_nnz_binary_search(INT32_t* X_indices,
-
static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indices, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X_data, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_start, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_sorted_samples, int *__pyx_v_is_samples_sorted) {
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_samples;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_index;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative_;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive_;
-/* … */
-  /* function exit code */
-}
-
 1001:                                            DTYPE_t* X_data,
-
 1002:                                            INT32_t indptr_start,
-
 1003:                                            INT32_t indptr_end,
-
 1004:                                            SIZE_t* samples,
-
 1005:                                            SIZE_t start,
-
 1006:                                            SIZE_t end,
-
 1007:                                            SIZE_t* index_to_samples,
-
 1008:                                            DTYPE_t* Xf,
-
 1009:                                            SIZE_t* end_negative,
-
 1010:                                            SIZE_t* start_positive,
-
 1011:                                            SIZE_t* sorted_samples,
-
 1012:                                            bint* is_samples_sorted) nogil:
-
 1013:     """Extract and partition values for a given feature using binary search.
-
 1014:
-
 1015:     If n_samples = end - start and n_indices = indptr_end - indptr_start,
-
 1016:     the complexity is
-
 1017:
-
 1018:         O((1 - is_samples_sorted[0]) * n_samples * log(n_samples) +
-
 1019:           n_samples * log(n_indices)).
-
 1020:     """
-
 1021:     cdef SIZE_t n_samples
-
 1022:
-
+1023:     if not is_samples_sorted[0]:
-
  __pyx_t_1 = ((!((__pyx_v_is_samples_sorted[0]) != 0)) != 0);
-  if (__pyx_t_1) {
-/* … */
-  }
-
+1024:         n_samples = end - start
-
    __pyx_v_n_samples = (__pyx_v_end - __pyx_v_start);
-
+1025:         memcpy(sorted_samples + start, samples + start,
-
    (void)(memcpy((__pyx_v_sorted_samples + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_n_samples * (sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)))));
-
 1026:                n_samples * sizeof(SIZE_t))
-
+1027:         qsort(sorted_samples + start, n_samples, sizeof(SIZE_t),
-
    qsort((__pyx_v_sorted_samples + __pyx_v_start), __pyx_v_n_samples, (sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)), __pyx_f_13stpredictions_6models_3OK3_9_splitter_compare_SIZE_t);
-
 1028:               compare_SIZE_t)
-
+1029:         is_samples_sorted[0] = 1
-
    (__pyx_v_is_samples_sorted[0]) = 1;
-
 1030:
-
+1031:     while (indptr_start < indptr_end and
-
  while (1) {
-    __pyx_t_2 = ((__pyx_v_indptr_start < __pyx_v_indptr_end) != 0);
-    if (__pyx_t_2) {
-    } else {
-      __pyx_t_1 = __pyx_t_2;
-      goto __pyx_L6_bool_binop_done;
-    }
-
+1032:            sorted_samples[start] > X_indices[indptr_start]):
-
    __pyx_t_2 = (((__pyx_v_sorted_samples[__pyx_v_start]) > (__pyx_v_X_indices[__pyx_v_indptr_start])) != 0);
-    __pyx_t_1 = __pyx_t_2;
-    __pyx_L6_bool_binop_done:;
-    if (!__pyx_t_1) break;
-
+1033:         indptr_start += 1
-
    __pyx_v_indptr_start = (__pyx_v_indptr_start + 1);
-  }
-
 1034:
-
+1035:     while (indptr_start < indptr_end and
-
  while (1) {
-    __pyx_t_2 = ((__pyx_v_indptr_start < __pyx_v_indptr_end) != 0);
-    if (__pyx_t_2) {
-    } else {
-      __pyx_t_1 = __pyx_t_2;
-      goto __pyx_L10_bool_binop_done;
-    }
-
+1036:            sorted_samples[end - 1] < X_indices[indptr_end - 1]):
-
    __pyx_t_2 = (((__pyx_v_sorted_samples[(__pyx_v_end - 1)]) < (__pyx_v_X_indices[(__pyx_v_indptr_end - 1)])) != 0);
-    __pyx_t_1 = __pyx_t_2;
-    __pyx_L10_bool_binop_done:;
-    if (!__pyx_t_1) break;
-
+1037:         indptr_end -= 1
-
    __pyx_v_indptr_end = (__pyx_v_indptr_end - 1);
-  }
-
 1038:
-
+1039:     cdef SIZE_t p = start
-
  __pyx_v_p = __pyx_v_start;
-
 1040:     cdef SIZE_t index
-
 1041:     cdef SIZE_t k
-
+1042:     cdef SIZE_t end_negative_ = start
-
  __pyx_v_end_negative_ = __pyx_v_start;
-
+1043:     cdef SIZE_t start_positive_ = end
-
  __pyx_v_start_positive_ = __pyx_v_end;
-
 1044:
-
+1045:     while (p < end and indptr_start < indptr_end):
-
  while (1) {
-    __pyx_t_2 = ((__pyx_v_p < __pyx_v_end) != 0);
-    if (__pyx_t_2) {
-    } else {
-      __pyx_t_1 = __pyx_t_2;
-      goto __pyx_L14_bool_binop_done;
-    }
-    __pyx_t_2 = ((__pyx_v_indptr_start < __pyx_v_indptr_end) != 0);
-    __pyx_t_1 = __pyx_t_2;
-    __pyx_L14_bool_binop_done:;
-    if (!__pyx_t_1) break;
-
 1046:         # Find index of sorted_samples[p] in X_indices
-
+1047:         binary_search(X_indices, indptr_start, indptr_end,
-
    __pyx_f_13stpredictions_6models_3OK3_9_splitter_binary_search(__pyx_v_X_indices, __pyx_v_indptr_start, __pyx_v_indptr_end, (__pyx_v_sorted_samples[__pyx_v_p]), (&__pyx_v_k), (&__pyx_v_indptr_start));
-
 1048:                       sorted_samples[p], &k, &indptr_start)
-
 1049:
-
+1050:         if k != -1:
-
    __pyx_t_1 = ((__pyx_v_k != -1L) != 0);
-    if (__pyx_t_1) {
-/* … */
-    }
-
 1051:              # If k != -1, we have found a non zero value
-
 1052:
-
+1053:             if X_data[k] > 0:
-
      __pyx_t_1 = (((__pyx_v_X_data[__pyx_v_k]) > 0.0) != 0);
-      if (__pyx_t_1) {
-/* … */
-        goto __pyx_L17;
-      }
-
+1054:                 start_positive_ -= 1
-
        __pyx_v_start_positive_ = (__pyx_v_start_positive_ - 1);
-
+1055:                 Xf[start_positive_] = X_data[k]
-
        (__pyx_v_Xf[__pyx_v_start_positive_]) = (__pyx_v_X_data[__pyx_v_k]);
-
+1056:                 index = index_to_samples[X_indices[k]]
-
        __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]);
-
+1057:                 sparse_swap(index_to_samples, samples, index, start_positive_)
-
        __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_start_positive_);
-
 1058:
-
 1059:
-
+1060:             elif X_data[k] < 0:
-
      __pyx_t_1 = (((__pyx_v_X_data[__pyx_v_k]) < 0.0) != 0);
-      if (__pyx_t_1) {
-/* … */
-      }
-      __pyx_L17:;
-
+1061:                 Xf[end_negative_] = X_data[k]
-
        (__pyx_v_Xf[__pyx_v_end_negative_]) = (__pyx_v_X_data[__pyx_v_k]);
-
+1062:                 index = index_to_samples[X_indices[k]]
-
        __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]);
-
+1063:                 sparse_swap(index_to_samples, samples, index, end_negative_)
-
        __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_end_negative_);
-
+1064:                 end_negative_ += 1
-
        __pyx_v_end_negative_ = (__pyx_v_end_negative_ + 1);
-
+1065:         p += 1
-
    __pyx_v_p = (__pyx_v_p + 1);
-  }
-
 1066:
-
 1067:     # Returned values
-
+1068:     end_negative[0] = end_negative_
-
  (__pyx_v_end_negative[0]) = __pyx_v_end_negative_;
-
+1069:     start_positive[0] = start_positive_
-
  (__pyx_v_start_positive[0]) = __pyx_v_start_positive_;
-
 1070:
-
 1071:
-
+1072: cdef inline void sparse_swap(SIZE_t* index_to_samples, SIZE_t* samples,
-
static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos_1, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos_2) {
-/* … */
-  /* function exit code */
-}
-
 1073:                              SIZE_t pos_1, SIZE_t pos_2) nogil:
-
 1074:     """Swap sample pos_1 and pos_2 preserving sparse invariant."""
-
+1075:     samples[pos_1], samples[pos_2] =  samples[pos_2], samples[pos_1]
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 1078:
-
 1079:
-
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-
struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter {
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-
 1081:     """Splitter for finding the best split, using the sparse data."""
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 1082:
-
+1083:     def __reduce__(self):
-
/* Python wrapper */
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+1088:                                      self.random_state), self.__getstate__())
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 1089:
-
+1090:     cdef int node_split(self, double impurity, SplitRecord* split,
-
static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features) {
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end;
-  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indices;
-  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indptr;
-  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X_data;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_features;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_constant_features;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_features;
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf;
-  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_sorted_samples;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf;
-  double __pyx_v_min_weight_leaf;
-  __pyx_t_7sklearn_4tree_5_tree_UINT32_t *__pyx_v_random_state;
-  struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_best;
-  struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_current;
-  double __pyx_v_current_proxy_improvement;
-  double __pyx_v_best_proxy_improvement;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_i;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_j;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_visited_features;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_found_constants;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_drawn_constants;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_known_constants;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_total_constants;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p_next;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p_prev;
-  int __pyx_v_is_samples_sorted;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative;
-  int __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L1_error:;
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-    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
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-  __pyx_r = -1;
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-
 1091:                         SIZE_t* n_constant_features) nogil except -1:
-
 1092:         """Find the best split on node samples[start:end], using sparse features
-
 1093:
-
 1094:         Returns -1 in case of failure to allocate memory (and raise MemoryError)
-
 1095:         or 0 otherwise.
-
 1096:         """
-
 1097:         # Find the best split
-
+1098:         cdef SIZE_t* samples = self.samples
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.samples;
-  __pyx_v_samples = __pyx_t_1;
-
+1099:         cdef SIZE_t start = self.start
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.start;
-  __pyx_v_start = __pyx_t_2;
-
+1100:         cdef SIZE_t end = self.end
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end;
-  __pyx_v_end = __pyx_t_2;
-
 1101:
-
+1102:         cdef INT32_t* X_indices = self.X_indices
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.X_indices;
-  __pyx_v_X_indices = __pyx_t_3;
-
+1103:         cdef INT32_t* X_indptr = self.X_indptr
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.X_indptr;
-  __pyx_v_X_indptr = __pyx_t_3;
-
+1104:         cdef DTYPE_t* X_data = self.X_data
-
  __pyx_t_4 = __pyx_v_self->__pyx_base.X_data;
-  __pyx_v_X_data = __pyx_t_4;
-
 1105:
-
+1106:         cdef SIZE_t* features = self.features
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.features;
-  __pyx_v_features = __pyx_t_1;
-
+1107:         cdef SIZE_t* constant_features = self.constant_features
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.constant_features;
-  __pyx_v_constant_features = __pyx_t_1;
-
+1108:         cdef SIZE_t n_features = self.n_features
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_features;
-  __pyx_v_n_features = __pyx_t_2;
-
 1109:
-
+1110:         cdef DTYPE_t* Xf = self.feature_values
-
  __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.feature_values;
-  __pyx_v_Xf = __pyx_t_4;
-
+1111:         cdef SIZE_t* sorted_samples = self.sorted_samples
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.sorted_samples;
-  __pyx_v_sorted_samples = __pyx_t_1;
-
+1112:         cdef SIZE_t* index_to_samples = self.index_to_samples
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.index_to_samples;
-  __pyx_v_index_to_samples = __pyx_t_1;
-
+1113:         cdef SIZE_t max_features = self.max_features
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features;
-  __pyx_v_max_features = __pyx_t_2;
-
+1114:         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf;
-  __pyx_v_min_samples_leaf = __pyx_t_2;
-
+1115:         cdef double min_weight_leaf = self.min_weight_leaf
-
  __pyx_t_5 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf;
-  __pyx_v_min_weight_leaf = __pyx_t_5;
-
+1116:         cdef UINT32_t* random_state = &self.rand_r_state
-
  __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state);
-
 1117:
-
 1118:         cdef SplitRecord best, current
-
+1119:         _init_split(&best, end)
-
  __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end);
-
+1120:         cdef double current_proxy_improvement = - INFINITY
-
  __pyx_v_current_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY);
-
+1121:         cdef double best_proxy_improvement = - INFINITY
-
  __pyx_v_best_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY);
-
 1122:
-
+1123:         cdef SIZE_t f_i = n_features
-
  __pyx_v_f_i = __pyx_v_n_features;
-
 1124:         cdef SIZE_t f_j, p
-
+1125:         cdef SIZE_t n_visited_features = 0
-
  __pyx_v_n_visited_features = 0;
-
 1126:         # Number of features discovered to be constant during the split search
-
+1127:         cdef SIZE_t n_found_constants = 0
-
  __pyx_v_n_found_constants = 0;
-
 1128:         # Number of features known to be constant and drawn without replacement
-
+1129:         cdef SIZE_t n_drawn_constants = 0
-
  __pyx_v_n_drawn_constants = 0;
-
+1130:         cdef SIZE_t n_known_constants = n_constant_features[0]
-
  __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]);
-
 1131:         # n_total_constants = n_known_constants + n_found_constants
-
+1132:         cdef SIZE_t n_total_constants = n_known_constants
-
  __pyx_v_n_total_constants = __pyx_v_n_known_constants;
-
 1133:         cdef DTYPE_t current_feature_value
-
 1134:
-
 1135:         cdef SIZE_t p_next
-
 1136:         cdef SIZE_t p_prev
-
+1137:         cdef bint is_samples_sorted = 0  # indicate is sorted_samples is
-
  __pyx_v_is_samples_sorted = 0;
-
 1138:                                          # inititialized
-
 1139:
-
 1140:         # We assume implicitly that end_positive = end and
-
 1141:         # start_negative = start
-
 1142:         cdef SIZE_t start_positive
-
 1143:         cdef SIZE_t end_negative
-
 1144:
-
 1145:         # Sample up to max_features without replacement using a
-
 1146:         # Fisher-Yates-based algorithm (using the local variables `f_i` and
-
 1147:         # `f_j` to compute a permutation of the `features` array).
-
 1148:         #
-
 1149:         # Skip the CPU intensive evaluation of the impurity criterion for
-
 1150:         # features that were already detected as constant (hence not suitable
-
 1151:         # for good splitting) by ancestor nodes and save the information on
-
 1152:         # newly discovered constant features to spare computation on descendant
-
 1153:         # nodes.
-
+1154:         while (f_i > n_total_constants and  # Stop early if remaining features
-
  while (1) {
-    __pyx_t_7 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0);
-    if (__pyx_t_7) {
-    } else {
-      __pyx_t_6 = __pyx_t_7;
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-
 1155:                                             # are constant
-
+1156:                 (n_visited_features < max_features or
-
    __pyx_t_7 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0);
-    if (!__pyx_t_7) {
-    } else {
-      __pyx_t_6 = __pyx_t_7;
-      goto __pyx_L5_bool_binop_done;
-    }
-
 1157:                  # At least one drawn features must be non constant
-
+1158:                  n_visited_features <= n_found_constants + n_drawn_constants)):
-
    __pyx_t_7 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0);
-    __pyx_t_6 = __pyx_t_7;
-    __pyx_L5_bool_binop_done:;
-    if (!__pyx_t_6) break;
-
 1159:
-
+1160:             n_visited_features += 1
-
    __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1);
-
 1161:
-
 1162:             # Loop invariant: elements of features in
-
 1163:             # - [:n_drawn_constant[ holds drawn and known constant features;
-
 1164:             # - [n_drawn_constant:n_known_constant[ holds known constant
-
 1165:             #   features that haven't been drawn yet;
-
 1166:             # - [n_known_constant:n_total_constant[ holds newly found constant
-
 1167:             #   features;
-
 1168:             # - [n_total_constant:f_i[ holds features that haven't been drawn
-
 1169:             #   yet and aren't constant apriori.
-
 1170:             # - [f_i:n_features[ holds features that have been drawn
-
 1171:             #   and aren't constant.
-
 1172:
-
 1173:             # Draw a feature at random
-
+1174:             f_j = rand_int(n_drawn_constants, f_i - n_found_constants,
-
    __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state);
-
 1175:                            random_state)
-
 1176:
-
+1177:             if f_j < n_known_constants:
-
    __pyx_t_6 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0);
-    if (__pyx_t_6) {
-/* … */
-      goto __pyx_L8;
-    }
-
 1178:                 # f_j in the interval [n_drawn_constants, n_known_constants[
-
+1179:                 features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j]
-
      __pyx_t_2 = (__pyx_v_features[__pyx_v_n_drawn_constants]);
-      __pyx_t_8 = (__pyx_v_features[__pyx_v_f_j]);
-      (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2;
-      (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_8;
-
 1180:
-
+1181:                 n_drawn_constants += 1
-
      __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1);
-
 1182:
-
 1183:             else:
-
 1184:                 # f_j in the interval [n_known_constants, f_i - n_found_constants[
-
+1185:                 f_j += n_found_constants
-
    /*else*/ {
-      __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants);
-
 1186:                 # f_j in the interval [n_total_constants, f_i[
-
 1187:
-
+1188:                 current.feature = features[f_j]
-
      __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]);
-
+1189:                 self.extract_nnz(current.feature,
-
      __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted));
-
 1190:                                  &end_negative, &start_positive,
-
 1191:                                  &is_samples_sorted)
-
 1192:
-
 1193:                 # Sort the positive and negative parts of `Xf`
-
+1194:                 sort(Xf + start, samples + start, end_negative - start)
-
      __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end_negative - __pyx_v_start));
-
+1195:                 sort(Xf + start_positive, samples + start_positive,
-
      __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort((__pyx_v_Xf + __pyx_v_start_positive), (__pyx_v_samples + __pyx_v_start_positive), (__pyx_v_end - __pyx_v_start_positive));
-
 1196:                      end - start_positive)
-
 1197:
-
 1198:                 # Update index_to_samples to take into account the sort
-
+1199:                 for p in range(start, end_negative):
-
      __pyx_t_8 = __pyx_v_end_negative;
-      __pyx_t_2 = __pyx_t_8;
-      for (__pyx_t_9 = __pyx_v_start; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) {
-        __pyx_v_p = __pyx_t_9;
-
+1200:                     index_to_samples[samples[p]] = p
-
        (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_p])]) = __pyx_v_p;
-      }
-
+1201:                 for p in range(start_positive, end):
-
      __pyx_t_8 = __pyx_v_end;
-      __pyx_t_2 = __pyx_t_8;
-      for (__pyx_t_9 = __pyx_v_start_positive; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) {
-        __pyx_v_p = __pyx_t_9;
-
+1202:                     index_to_samples[samples[p]] = p
-
        (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_p])]) = __pyx_v_p;
-      }
-
 1203:
-
 1204:                 # Add one or two zeros in Xf, if there is any
-
+1205:                 if end_negative < start_positive:
-
      __pyx_t_6 = ((__pyx_v_end_negative < __pyx_v_start_positive) != 0);
-      if (__pyx_t_6) {
-/* … */
-      }
-
+1206:                     start_positive -= 1
-
        __pyx_v_start_positive = (__pyx_v_start_positive - 1);
-
+1207:                     Xf[start_positive] = 0.
-
        (__pyx_v_Xf[__pyx_v_start_positive]) = 0.;
-
 1208:
-
+1209:                     if end_negative != start_positive:
-
        __pyx_t_6 = ((__pyx_v_end_negative != __pyx_v_start_positive) != 0);
-        if (__pyx_t_6) {
-/* … */
-        }
-
+1210:                         Xf[end_negative] = 0.
-
          (__pyx_v_Xf[__pyx_v_end_negative]) = 0.;
-
+1211:                         end_negative += 1
-
          __pyx_v_end_negative = (__pyx_v_end_negative + 1);
-
 1212:
-
+1213:                 if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD:
-
      __pyx_t_6 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0);
-      if (__pyx_t_6) {
-/* … */
-        goto __pyx_L15;
-      }
-
+1214:                     features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j]
-
        __pyx_t_8 = (__pyx_v_features[__pyx_v_n_total_constants]);
-        __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]);
-        (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_8;
-        (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2;
-
 1215:
-
+1216:                     n_found_constants += 1
-
        __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1);
-
+1217:                     n_total_constants += 1
-
        __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1);
-
 1218:
-
 1219:                 else:
-
+1220:                     f_i -= 1
-
      /*else*/ {
-        __pyx_v_f_i = (__pyx_v_f_i - 1);
-
+1221:                     features[f_i], features[f_j] = features[f_j], features[f_i]
-
        __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]);
-        __pyx_t_8 = (__pyx_v_features[__pyx_v_f_i]);
-        (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2;
-        (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_8;
-
 1222:
-
 1223:                     # Evaluate all splits
-
+1224:                     self.criterion.reset()
-
        __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1224, __pyx_L1_error)
-
+1225:                     p = start
-
        __pyx_v_p = __pyx_v_start;
-
 1226:
-
+1227:                     while p < end:
-
        while (1) {
-          __pyx_t_6 = ((__pyx_v_p < __pyx_v_end) != 0);
-          if (!__pyx_t_6) break;
-
+1228:                         if p + 1 != end_negative:
-
          __pyx_t_6 = (((__pyx_v_p + 1) != __pyx_v_end_negative) != 0);
-          if (__pyx_t_6) {
-/* … */
-            goto __pyx_L18;
-          }
-
+1229:                             p_next = p + 1
-
            __pyx_v_p_next = (__pyx_v_p + 1);
-
 1230:                         else:
-
+1231:                             p_next = start_positive
-
          /*else*/ {
-            __pyx_v_p_next = __pyx_v_start_positive;
-          }
-          __pyx_L18:;
-
 1232:
-
+1233:                         while (p_next < end and
-
          while (1) {
-            __pyx_t_7 = ((__pyx_v_p_next < __pyx_v_end) != 0);
-            if (__pyx_t_7) {
-            } else {
-              __pyx_t_6 = __pyx_t_7;
-              goto __pyx_L21_bool_binop_done;
-            }
-
+1234:                                Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD):
-
            __pyx_t_7 = (((__pyx_v_Xf[__pyx_v_p_next]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0);
-            __pyx_t_6 = __pyx_t_7;
-            __pyx_L21_bool_binop_done:;
-            if (!__pyx_t_6) break;
-
+1235:                             p = p_next
-
            __pyx_v_p = __pyx_v_p_next;
-
+1236:                             if p + 1 != end_negative:
-
            __pyx_t_6 = (((__pyx_v_p + 1) != __pyx_v_end_negative) != 0);
-            if (__pyx_t_6) {
-/* … */
-              goto __pyx_L23;
-            }
-
+1237:                                 p_next = p + 1
-
              __pyx_v_p_next = (__pyx_v_p + 1);
-
 1238:                             else:
-
+1239:                                 p_next = start_positive
-
            /*else*/ {
-              __pyx_v_p_next = __pyx_v_start_positive;
-            }
-            __pyx_L23:;
-          }
-
 1240:
-
 1241:
-
 1242:                         # (p_next >= end) or (X[samples[p_next], current.feature] >
-
 1243:                         #                     X[samples[p], current.feature])
-
+1244:                         p_prev = p
-
          __pyx_v_p_prev = __pyx_v_p;
-
+1245:                         p = p_next
-
          __pyx_v_p = __pyx_v_p_next;
-
 1246:                         # (p >= end) or (X[samples[p], current.feature] >
-
 1247:                         #                X[samples[p_prev], current.feature])
-
 1248:
-
 1249:
-
+1250:                         if p < end:
-
          __pyx_t_6 = ((__pyx_v_p < __pyx_v_end) != 0);
-          if (__pyx_t_6) {
-/* … */
-          }
-          __pyx_L16_continue:;
-        }
-      }
-      __pyx_L15:;
-    }
-    __pyx_L8:;
-  }
-
+1251:                             current.pos = p
-
            __pyx_v_current.pos = __pyx_v_p;
-
 1252:
-
 1253:                             # Reject if min_samples_leaf is not guaranteed
-
+1254:                             if (((current.pos - start) < min_samples_leaf) or
-
            __pyx_t_7 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0);
-            if (!__pyx_t_7) {
-            } else {
-              __pyx_t_6 = __pyx_t_7;
-              goto __pyx_L26_bool_binop_done;
-            }
-/* … */
-            if (__pyx_t_6) {
-/* … */
-            }
-
+1255:                                     ((end - current.pos) < min_samples_leaf)):
-
            __pyx_t_7 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0);
-            __pyx_t_6 = __pyx_t_7;
-            __pyx_L26_bool_binop_done:;
-
+1256:                                 continue
-
              goto __pyx_L16_continue;
-
 1257:
-
+1258:                             self.criterion.update(current.pos)
-
            __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1258, __pyx_L1_error)
-
 1259:
-
 1260:                             # Reject if min_weight_leaf is not satisfied
-
+1261:                             if ((self.criterion.weighted_n_left < min_weight_leaf) or
-
            __pyx_t_7 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_left < __pyx_v_min_weight_leaf) != 0);
-            if (!__pyx_t_7) {
-            } else {
-              __pyx_t_6 = __pyx_t_7;
-              goto __pyx_L29_bool_binop_done;
-            }
-/* … */
-            if (__pyx_t_6) {
-/* … */
-            }
-
+1262:                                     (self.criterion.weighted_n_right < min_weight_leaf)):
-
            __pyx_t_7 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_right < __pyx_v_min_weight_leaf) != 0);
-            __pyx_t_6 = __pyx_t_7;
-            __pyx_L29_bool_binop_done:;
-
+1263:                                 continue
-
              goto __pyx_L16_continue;
-
 1264:
-
+1265:                             current_proxy_improvement = self.criterion.proxy_impurity_improvement()
-
            __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion);
-
 1266:
-
+1267:                             if current_proxy_improvement > best_proxy_improvement:
-
            __pyx_t_6 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0);
-            if (__pyx_t_6) {
-/* … */
-            }
-
+1268:                                 best_proxy_improvement = current_proxy_improvement
-
              __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement;
-
 1269:                                 # sum of halves used to avoid infinite values
-
+1270:                                 current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0
-
              __pyx_v_current.threshold = (((__pyx_v_Xf[__pyx_v_p_prev]) / 2.0) + ((__pyx_v_Xf[__pyx_v_p]) / 2.0));
-
 1271:
-
+1272:                                 if ((current.threshold == Xf[p]) or
-
              __pyx_t_7 = ((__pyx_v_current.threshold == (__pyx_v_Xf[__pyx_v_p])) != 0);
-              if (!__pyx_t_7) {
-              } else {
-                __pyx_t_6 = __pyx_t_7;
-                goto __pyx_L33_bool_binop_done;
-              }
-/* … */
-              if (__pyx_t_6) {
-/* … */
-              }
-
+1273:                                     (current.threshold == INFINITY) or
-
              __pyx_t_7 = ((__pyx_v_current.threshold == __pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY) != 0);
-              if (!__pyx_t_7) {
-              } else {
-                __pyx_t_6 = __pyx_t_7;
-                goto __pyx_L33_bool_binop_done;
-              }
-
+1274:                                     (current.threshold == -INFINITY)):
-
              __pyx_t_7 = ((__pyx_v_current.threshold == (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY)) != 0);
-              __pyx_t_6 = __pyx_t_7;
-              __pyx_L33_bool_binop_done:;
-
+1275:                                     current.threshold = Xf[p_prev]
-
                __pyx_v_current.threshold = (__pyx_v_Xf[__pyx_v_p_prev]);
-
 1276:
-
+1277:                                 best = current
-
              __pyx_v_best = __pyx_v_current;
-
 1278:
-
 1279:         # Reorganize into samples[start:best.pos] + samples[best.pos:end]
-
+1280:         if best.pos < end:
-
  __pyx_t_6 = ((__pyx_v_best.pos < __pyx_v_end) != 0);
-  if (__pyx_t_6) {
-/* … */
-  }
-
+1281:             self.extract_nnz(best.feature, &end_negative, &start_positive,
-
    __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted));
-
 1282:                              &is_samples_sorted)
-
 1283:
-
+1284:             self._partition(best.threshold, end_negative, start_positive,
-
    (void)(__pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.threshold, __pyx_v_end_negative, __pyx_v_start_positive, __pyx_v_best.pos));
-
 1285:                             best.pos)
-
 1286:
-
+1287:             self.criterion.reset()
-
    __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1287, __pyx_L1_error)
-
+1288:             self.criterion.update(best.pos)
-
    __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1288, __pyx_L1_error)
-
+1289:             best.improvement = self.criterion.impurity_improvement(impurity)
-
    __pyx_v_best.improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity);
-
+1290:             self.criterion.children_impurity(&best.impurity_left,
-
    ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right));
-
 1291:                                              &best.impurity_right)
-
 1292:
-
 1293:         # Respect invariant for constant features: the original order of
-
 1294:         # element in features[:n_known_constants] must be preserved for sibling
-
 1295:         # and child nodes
-
+1296:         memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants)
-
  (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants)));
-
 1297:
-
 1298:         # Copy newly found constant features
-
+1299:         memcpy(constant_features + n_known_constants,
-
  (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants)));
-
 1300:                features + n_known_constants,
-
 1301:                sizeof(SIZE_t) * n_found_constants)
-
 1302:
-
 1303:         # Return values
-
+1304:         split[0] = best
-
  (__pyx_v_split[0]) = __pyx_v_best;
-
+1305:         n_constant_features[0] = n_total_constants
-
  (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants;
-
+1306:         return 0
-
  __pyx_r = 0;
-  goto __pyx_L0;
-
 1307:
-
 1308:
-
+1309: cdef class RandomSparseSplitter(BaseSparseSplitter):
-
struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter {
-  struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_base;
-};
-/* … */
-struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter {
-  struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_base;
-};
-static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter;
-
-
 1310:     """Splitter for finding a random split, using the sparse data."""
-
 1311:
-
+1312:     def __reduce__(self):
-
/* Python wrapper */
-static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
-static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) {
-  PyObject *__pyx_r = 0;
-  __Pyx_RefNannyDeclarations
-  __Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0);
-  __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter___reduce__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *)__pyx_v_self));
-
-  /* function exit code */
-  __Pyx_RefNannyFinishContext();
-  return __pyx_r;
-}
-
-static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_v_self) {
-  PyObject *__pyx_r = NULL;
-  __Pyx_RefNannyDeclarations
-  __Pyx_RefNannySetupContext("__reduce__", 0);
-/* … */
-  /* function exit code */
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+1317:                                        self.random_state), self.__getstate__())
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 1318:
-
+1319:     cdef int node_split(self, double impurity, SplitRecord* split,
-
static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features) {
-  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples;
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-  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indices;
-  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indptr;
-  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X_data;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_features;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_constant_features;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_features;
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf;
-  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_sorted_samples;
-  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples;
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-  double __pyx_v_min_weight_leaf;
-  __pyx_t_7sklearn_4tree_5_tree_UINT32_t *__pyx_v_random_state;
-  struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_best;
-  struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_current;
-  double __pyx_v_current_proxy_improvement;
-  double __pyx_v_best_proxy_improvement;
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_current_feature_value;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_i;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_j;
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-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_total_constants;
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_min_feature_value;
-  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_max_feature_value;
-  int __pyx_v_is_samples_sorted;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive;
-  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative;
-  int __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L1_error:;
-  {
-    #ifdef WITH_THREAD
-    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
-    #endif
-    __Pyx_AddTraceback("stpredictions.models.OK3._splitter.RandomSparseSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename);
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-  __pyx_r = -1;
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-  return __pyx_r;
-}
-
 1320:                         SIZE_t* n_constant_features) nogil except -1:
-
 1321:         """Find a random split on node samples[start:end], using sparse features
-
 1322:
-
 1323:         Returns -1 in case of failure to allocate memory (and raise MemoryError)
-
 1324:         or 0 otherwise.
-
 1325:         """
-
 1326:         # Find the best split
-
+1327:         cdef SIZE_t* samples = self.samples
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.samples;
-  __pyx_v_samples = __pyx_t_1;
-
+1328:         cdef SIZE_t start = self.start
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.start;
-  __pyx_v_start = __pyx_t_2;
-
+1329:         cdef SIZE_t end = self.end
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end;
-  __pyx_v_end = __pyx_t_2;
-
 1330:
-
+1331:         cdef INT32_t* X_indices = self.X_indices
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.X_indices;
-  __pyx_v_X_indices = __pyx_t_3;
-
+1332:         cdef INT32_t* X_indptr = self.X_indptr
-
  __pyx_t_3 = __pyx_v_self->__pyx_base.X_indptr;
-  __pyx_v_X_indptr = __pyx_t_3;
-
+1333:         cdef DTYPE_t* X_data = self.X_data
-
  __pyx_t_4 = __pyx_v_self->__pyx_base.X_data;
-  __pyx_v_X_data = __pyx_t_4;
-
 1334:
-
+1335:         cdef SIZE_t* features = self.features
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.features;
-  __pyx_v_features = __pyx_t_1;
-
+1336:         cdef SIZE_t* constant_features = self.constant_features
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.constant_features;
-  __pyx_v_constant_features = __pyx_t_1;
-
+1337:         cdef SIZE_t n_features = self.n_features
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_features;
-  __pyx_v_n_features = __pyx_t_2;
-
 1338:
-
+1339:         cdef DTYPE_t* Xf = self.feature_values
-
  __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.feature_values;
-  __pyx_v_Xf = __pyx_t_4;
-
+1340:         cdef SIZE_t* sorted_samples = self.sorted_samples
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.sorted_samples;
-  __pyx_v_sorted_samples = __pyx_t_1;
-
+1341:         cdef SIZE_t* index_to_samples = self.index_to_samples
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.index_to_samples;
-  __pyx_v_index_to_samples = __pyx_t_1;
-
+1342:         cdef SIZE_t max_features = self.max_features
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features;
-  __pyx_v_max_features = __pyx_t_2;
-
+1343:         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
-
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf;
-  __pyx_v_min_samples_leaf = __pyx_t_2;
-
+1344:         cdef double min_weight_leaf = self.min_weight_leaf
-
  __pyx_t_5 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf;
-  __pyx_v_min_weight_leaf = __pyx_t_5;
-
+1345:         cdef UINT32_t* random_state = &self.rand_r_state
-
  __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state);
-
 1346:
-
 1347:         cdef SplitRecord best, current
-
+1348:         _init_split(&best, end)
-
  __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end);
-
+1349:         cdef double current_proxy_improvement = - INFINITY
-
  __pyx_v_current_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY);
-
+1350:         cdef double best_proxy_improvement = - INFINITY
-
  __pyx_v_best_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY);
-
 1351:
-
 1352:         cdef DTYPE_t current_feature_value
-
 1353:
-
+1354:         cdef SIZE_t f_i = n_features
-
  __pyx_v_f_i = __pyx_v_n_features;
-
 1355:         cdef SIZE_t f_j, p
-
+1356:         cdef SIZE_t n_visited_features = 0
-
  __pyx_v_n_visited_features = 0;
-
 1357:         # Number of features discovered to be constant during the split search
-
+1358:         cdef SIZE_t n_found_constants = 0
-
  __pyx_v_n_found_constants = 0;
-
 1359:         # Number of features known to be constant and drawn without replacement
-
+1360:         cdef SIZE_t n_drawn_constants = 0
-
  __pyx_v_n_drawn_constants = 0;
-
+1361:         cdef SIZE_t n_known_constants = n_constant_features[0]
-
  __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]);
-
 1362:         # n_total_constants = n_known_constants + n_found_constants
-
+1363:         cdef SIZE_t n_total_constants = n_known_constants
-
  __pyx_v_n_total_constants = __pyx_v_n_known_constants;
-
 1364:         cdef SIZE_t partition_end
-
 1365:
-
 1366:         cdef DTYPE_t min_feature_value
-
 1367:         cdef DTYPE_t max_feature_value
-
 1368:
-
+1369:         cdef bint is_samples_sorted = 0  # indicate that sorted_samples is
-
  __pyx_v_is_samples_sorted = 0;
-
 1370:                                          # inititialized
-
 1371:
-
 1372:         # We assume implicitly that end_positive = end and
-
 1373:         # start_negative = start
-
 1374:         cdef SIZE_t start_positive
-
 1375:         cdef SIZE_t end_negative
-
 1376:
-
 1377:         # Sample up to max_features without replacement using a
-
 1378:         # Fisher-Yates-based algorithm (using the local variables `f_i` and
-
 1379:         # `f_j` to compute a permutation of the `features` array).
-
 1380:         #
-
 1381:         # Skip the CPU intensive evaluation of the impurity criterion for
-
 1382:         # features that were already detected as constant (hence not suitable
-
 1383:         # for good splitting) by ancestor nodes and save the information on
-
 1384:         # newly discovered constant features to spare computation on descendant
-
 1385:         # nodes.
-
+1386:         while (f_i > n_total_constants and  # Stop early if remaining features
-
  while (1) {
-    __pyx_t_7 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0);
-    if (__pyx_t_7) {
-    } else {
-      __pyx_t_6 = __pyx_t_7;
-      goto __pyx_L5_bool_binop_done;
-    }
-
 1387:                                             # are constant
-
+1388:                 (n_visited_features < max_features or
-
    __pyx_t_7 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0);
-    if (!__pyx_t_7) {
-    } else {
-      __pyx_t_6 = __pyx_t_7;
-      goto __pyx_L5_bool_binop_done;
-    }
-
 1389:                  # At least one drawn features must be non constant
-
+1390:                  n_visited_features <= n_found_constants + n_drawn_constants)):
-
    __pyx_t_7 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0);
-    __pyx_t_6 = __pyx_t_7;
-    __pyx_L5_bool_binop_done:;
-    if (!__pyx_t_6) break;
-
 1391:
-
+1392:             n_visited_features += 1
-
    __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1);
-
 1393:
-
 1394:             # Loop invariant: elements of features in
-
 1395:             # - [:n_drawn_constant[ holds drawn and known constant features;
-
 1396:             # - [n_drawn_constant:n_known_constant[ holds known constant
-
 1397:             #   features that haven't been drawn yet;
-
 1398:             # - [n_known_constant:n_total_constant[ holds newly found constant
-
 1399:             #   features;
-
 1400:             # - [n_total_constant:f_i[ holds features that haven't been drawn
-
 1401:             #   yet and aren't constant apriori.
-
 1402:             # - [f_i:n_features[ holds features that have been drawn
-
 1403:             #   and aren't constant.
-
 1404:
-
 1405:             # Draw a feature at random
-
+1406:             f_j = rand_int(n_drawn_constants, f_i - n_found_constants,
-
    __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state);
-
 1407:                            random_state)
-
 1408:
-
+1409:             if f_j < n_known_constants:
-
    __pyx_t_6 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0);
-    if (__pyx_t_6) {
-/* … */
-      goto __pyx_L8;
-    }
-
 1410:                 # f_j in the interval [n_drawn_constants, n_known_constants[
-
+1411:                 features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j]
-
      __pyx_t_2 = (__pyx_v_features[__pyx_v_n_drawn_constants]);
-      __pyx_t_8 = (__pyx_v_features[__pyx_v_f_j]);
-      (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2;
-      (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_8;
-
 1412:
-
+1413:                 n_drawn_constants += 1
-
      __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1);
-
 1414:
-
 1415:             else:
-
 1416:                 # f_j in the interval [n_known_constants, f_i - n_found_constants[
-
+1417:                 f_j += n_found_constants
-
    /*else*/ {
-      __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants);
-
 1418:                 # f_j in the interval [n_total_constants, f_i[
-
 1419:
-
+1420:                 current.feature = features[f_j]
-
      __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]);
-
 1421:
-
+1422:                 self.extract_nnz(current.feature,
-
      __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted));
-
 1423:                                  &end_negative, &start_positive,
-
 1424:                                  &is_samples_sorted)
-
 1425:
-
 1426:                 # Add one or two zeros in Xf, if there is any
-
+1427:                 if end_negative < start_positive:
-
      __pyx_t_6 = ((__pyx_v_end_negative < __pyx_v_start_positive) != 0);
-      if (__pyx_t_6) {
-/* … */
-      }
-
+1428:                     start_positive -= 1
-
        __pyx_v_start_positive = (__pyx_v_start_positive - 1);
-
+1429:                     Xf[start_positive] = 0.
-
        (__pyx_v_Xf[__pyx_v_start_positive]) = 0.;
-
 1430:
-
+1431:                     if end_negative != start_positive:
-
        __pyx_t_6 = ((__pyx_v_end_negative != __pyx_v_start_positive) != 0);
-        if (__pyx_t_6) {
-/* … */
-        }
-
+1432:                         Xf[end_negative] = 0.
-
          (__pyx_v_Xf[__pyx_v_end_negative]) = 0.;
-
+1433:                         end_negative += 1
-
          __pyx_v_end_negative = (__pyx_v_end_negative + 1);
-
 1434:
-
 1435:                 # Find min, max in Xf[start:end_negative]
-
+1436:                 min_feature_value = Xf[start]
-
      __pyx_v_min_feature_value = (__pyx_v_Xf[__pyx_v_start]);
-
+1437:                 max_feature_value = min_feature_value
-
      __pyx_v_max_feature_value = __pyx_v_min_feature_value;
-
 1438:
-
+1439:                 for p in range(start, end_negative):
-
      __pyx_t_8 = __pyx_v_end_negative;
-      __pyx_t_2 = __pyx_t_8;
-      for (__pyx_t_9 = __pyx_v_start; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) {
-        __pyx_v_p = __pyx_t_9;
-
+1440:                     current_feature_value = Xf[p]
-
        __pyx_v_current_feature_value = (__pyx_v_Xf[__pyx_v_p]);
-
 1441:
-
+1442:                     if current_feature_value < min_feature_value:
-
        __pyx_t_6 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0);
-        if (__pyx_t_6) {
-/* … */
-          goto __pyx_L13;
-        }
-
+1443:                         min_feature_value = current_feature_value
-
          __pyx_v_min_feature_value = __pyx_v_current_feature_value;
-
+1444:                     elif current_feature_value > max_feature_value:
-
        __pyx_t_6 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0);
-        if (__pyx_t_6) {
-/* … */
-        }
-        __pyx_L13:;
-      }
-
+1445:                         max_feature_value = current_feature_value
-
          __pyx_v_max_feature_value = __pyx_v_current_feature_value;
-
 1446:
-
 1447:                 # Update min, max given Xf[start_positive:end]
-
+1448:                 for p in range(start_positive, end):
-
      __pyx_t_8 = __pyx_v_end;
-      __pyx_t_2 = __pyx_t_8;
-      for (__pyx_t_9 = __pyx_v_start_positive; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) {
-        __pyx_v_p = __pyx_t_9;
-
+1449:                     current_feature_value = Xf[p]
-
        __pyx_v_current_feature_value = (__pyx_v_Xf[__pyx_v_p]);
-
 1450:
-
+1451:                     if current_feature_value < min_feature_value:
-
        __pyx_t_6 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0);
-        if (__pyx_t_6) {
-/* … */
-          goto __pyx_L16;
-        }
-
+1452:                         min_feature_value = current_feature_value
-
          __pyx_v_min_feature_value = __pyx_v_current_feature_value;
-
+1453:                     elif current_feature_value > max_feature_value:
-
        __pyx_t_6 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0);
-        if (__pyx_t_6) {
-/* … */
-        }
-        __pyx_L16:;
-      }
-
+1454:                         max_feature_value = current_feature_value
-
          __pyx_v_max_feature_value = __pyx_v_current_feature_value;
-
 1455:
-
+1456:                 if max_feature_value <= min_feature_value + FEATURE_THRESHOLD:
-
      __pyx_t_6 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0);
-      if (__pyx_t_6) {
-/* … */
-        goto __pyx_L17;
-      }
-
+1457:                     features[f_j] = features[n_total_constants]
-
        (__pyx_v_features[__pyx_v_f_j]) = (__pyx_v_features[__pyx_v_n_total_constants]);
-
+1458:                     features[n_total_constants] = current.feature
-
        __pyx_t_8 = __pyx_v_current.feature;
-        (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_8;
-
 1459:
-
+1460:                     n_found_constants += 1
-
        __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1);
-
+1461:                     n_total_constants += 1
-
        __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1);
-
 1462:
-
 1463:                 else:
-
+1464:                     f_i -= 1
-
      /*else*/ {
-        __pyx_v_f_i = (__pyx_v_f_i - 1);
-
+1465:                     features[f_i], features[f_j] = features[f_j], features[f_i]
-
        __pyx_t_8 = (__pyx_v_features[__pyx_v_f_j]);
-        __pyx_t_2 = (__pyx_v_features[__pyx_v_f_i]);
-        (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_8;
-        (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2;
-
 1466:
-
 1467:                     # Draw a random threshold
-
+1468:                     current.threshold = rand_uniform(min_feature_value,
-
        __pyx_v_current.threshold = __pyx_f_7sklearn_4tree_6_utils_rand_uniform(__pyx_v_min_feature_value, __pyx_v_max_feature_value, __pyx_v_random_state);
-
 1469:                                                      max_feature_value,
-
 1470:                                                      random_state)
-
 1471:
-
+1472:                     if current.threshold == max_feature_value:
-
        __pyx_t_6 = ((__pyx_v_current.threshold == __pyx_v_max_feature_value) != 0);
-        if (__pyx_t_6) {
-/* … */
-        }
-
+1473:                         current.threshold = min_feature_value
-
          __pyx_v_current.threshold = __pyx_v_min_feature_value;
-
 1474:
-
 1475:                     # Partition
-
+1476:                     current.pos = self._partition(current.threshold,
-
        __pyx_v_current.pos = __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.threshold, __pyx_v_end_negative, __pyx_v_start_positive, (__pyx_v_start_positive + ((__pyx_v_Xf[__pyx_v_start_positive]) == 0.)));
-
 1477:                                                   end_negative,
-
 1478:                                                   start_positive,
-
 1479:                                                   start_positive +
-
 1480:                                                   (Xf[start_positive] == 0.))
-
 1481:
-
 1482:                     # Reject if min_samples_leaf is not guaranteed
-
+1483:                     if (((current.pos - start) < min_samples_leaf) or
-
        __pyx_t_7 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0);
-        if (!__pyx_t_7) {
-        } else {
-          __pyx_t_6 = __pyx_t_7;
-          goto __pyx_L20_bool_binop_done;
-        }
-/* … */
-        if (__pyx_t_6) {
-/* … */
-        }
-
+1484:                             ((end - current.pos) < min_samples_leaf)):
-
        __pyx_t_7 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0);
-        __pyx_t_6 = __pyx_t_7;
-        __pyx_L20_bool_binop_done:;
-
+1485:                         continue
-
          goto __pyx_L3_continue;
-
 1486:
-
 1487:                     # Evaluate split
-
+1488:                     self.criterion.reset()
-
        __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1488, __pyx_L1_error)
-
+1489:                     self.criterion.update(current.pos)
-
        __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1489, __pyx_L1_error)
-
 1490:
-
 1491:                     # Reject if min_weight_leaf is not satisfied
-
+1492:                     if ((self.criterion.weighted_n_left < min_weight_leaf) or
-
        __pyx_t_7 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_left < __pyx_v_min_weight_leaf) != 0);
-        if (!__pyx_t_7) {
-        } else {
-          __pyx_t_6 = __pyx_t_7;
-          goto __pyx_L23_bool_binop_done;
-        }
-/* … */
-        if (__pyx_t_6) {
-/* … */
-        }
-
+1493:                             (self.criterion.weighted_n_right < min_weight_leaf)):
-
        __pyx_t_7 = ((__pyx_v_self->__pyx_base.__pyx_base.criterion->weighted_n_right < __pyx_v_min_weight_leaf) != 0);
-        __pyx_t_6 = __pyx_t_7;
-        __pyx_L23_bool_binop_done:;
-
+1494:                         continue
-
          goto __pyx_L3_continue;
-
 1495:
-
+1496:                     current_proxy_improvement = self.criterion.proxy_impurity_improvement()
-
        __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion);
-
 1497:
-
+1498:                     if current_proxy_improvement > best_proxy_improvement:
-
        __pyx_t_6 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0);
-        if (__pyx_t_6) {
-/* … */
-        }
-      }
-      __pyx_L17:;
-    }
-    __pyx_L8:;
-    __pyx_L3_continue:;
-  }
-
+1499:                         best_proxy_improvement = current_proxy_improvement
-
          __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement;
-
+1500:                         current.improvement = self.criterion.impurity_improvement(impurity)
-
          __pyx_v_current.improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity);
-
 1501:
-
+1502:                         self.criterion.children_impurity(&current.impurity_left,
-
          ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_current.impurity_left), (&__pyx_v_current.impurity_right));
-
 1503:                                                          &current.impurity_right)
-
+1504:                         best = current
-
          __pyx_v_best = __pyx_v_current;
-
 1505:
-
 1506:         # Reorganize into samples[start:best.pos] + samples[best.pos:end]
-
+1507:         if best.pos < end:
-
  __pyx_t_6 = ((__pyx_v_best.pos < __pyx_v_end) != 0);
-  if (__pyx_t_6) {
-/* … */
-  }
-
+1508:             if current.feature != best.feature:
-
    __pyx_t_6 = ((__pyx_v_current.feature != __pyx_v_best.feature) != 0);
-    if (__pyx_t_6) {
-/* … */
-    }
-
+1509:                 self.extract_nnz(best.feature, &end_negative, &start_positive,
-
      __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted));
-
 1510:                                  &is_samples_sorted)
-
 1511:
-
+1512:                 self._partition(best.threshold, end_negative, start_positive,
-
      (void)(__pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.threshold, __pyx_v_end_negative, __pyx_v_start_positive, __pyx_v_best.pos));
-
 1513:                                 best.pos)
-
 1514:
-
+1515:             self.criterion.reset()
-
    __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1515, __pyx_L1_error)
-
+1516:             self.criterion.update(best.pos)
-
    __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1516, __pyx_L1_error)
-
+1517:             best.improvement = self.criterion.impurity_improvement(impurity)
-
    __pyx_v_best.improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity);
-
+1518:             self.criterion.children_impurity(&best.impurity_left,
-
    ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right));
-
 1519:                                              &best.impurity_right)
-
 1520:
-
 1521:         # Respect invariant for constant features: the original order of
-
 1522:         # element in features[:n_known_constants] must be preserved for sibling
-
 1523:         # and child nodes
-
+1524:         memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants)
-
  (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants)));
-
 1525:
-
 1526:         # Copy newly found constant features
-
+1527:         memcpy(constant_features + n_known_constants,
-
  (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants)));
-
 1528:                features + n_known_constants,
-
 1529:                sizeof(SIZE_t) * n_found_constants)
-
 1530:
-
 1531:         # Return values
-
+1532:         split[0] = best
-
  (__pyx_v_split[0]) = __pyx_v_best;
-
+1533:         n_constant_features[0] = n_total_constants
-
  (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants;
-
+1534:         return 0
-
  __pyx_r = 0;
-  goto __pyx_L0;
-
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+0001: # cython: cdivision=True
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 0002: # cython: boundscheck=False
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 0003: # cython: wraparound=False
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 0004:
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 0005: from cpython cimport Py_INCREF, PyObject, PyTypeObject
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 0006:
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 0007: from libc.stdlib cimport free
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 0008: from libc.math cimport fabs
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 0009: from libc.string cimport memcpy
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 0010: from libc.string cimport memset
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 0011: from libc.stdint cimport SIZE_MAX
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 0012:
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+0013: import numpy as np
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 0014: cimport numpy as np
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 0016:
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+0017: import warnings
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-
 0025: from sklearn.tree._utils cimport Stack
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 0026: from sklearn.tree._utils cimport StackRecord
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 0027: from sklearn.tree._utils cimport PriorityHeap
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 0028: from sklearn.tree._utils cimport PriorityHeapRecord
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 0029: from sklearn.tree._utils cimport safe_realloc
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 0030: from sklearn.tree._utils cimport sizet_ptr_to_ndarray
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 0031:
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+0185:             rc = stack.push(0, n_node_samples, 0, _TREE_UNDEFINED, 0, INFINITY, 0)
-
        __pyx_t_5 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, 0, __pyx_v_n_node_samples, 0, __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED, 0, __pyx_v_13stpredictions_6models_3OK3_5_tree_INFINITY, 0); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 185, __pyx_L8_error)
-        __pyx_v_rc = __pyx_t_5;
-
+0186:             if rc == -1:
-
        __pyx_t_9 = ((__pyx_v_rc == -1L) != 0);
-        if (__pyx_t_9) {
-/* … */
-        }
-
 0187:                 # got return code -1 - out-of-memory
-
+0188:                 with gil:
-
          {
-              #ifdef WITH_THREAD
-              PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
-              #endif
-              /*try:*/ {
-/* … */
-              /*finally:*/ {
-                __pyx_L12_error: {
-                  #ifdef WITH_THREAD
-                  __Pyx_PyGILState_Release(__pyx_gilstate_save);
-                  #endif
-                  goto __pyx_L8_error;
-                }
-              }
-          }
-
+0189:                     raise MemoryError()
-
                PyErr_NoMemory(); __PYX_ERR(0, 189, __pyx_L12_error)
-              }
-
 0190:
-
+0191:             while not stack.is_empty():
-
        while (1) {
-          __pyx_t_9 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0);
-          if (!__pyx_t_9) break;
-
+0192:                 stack.pop(&stack_record)
-
          (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record)));
-
 0193:
-
+0194:                 start = stack_record.start
-
          __pyx_t_14 = __pyx_v_stack_record.start;
-          __pyx_v_start = __pyx_t_14;
-
+0195:                 end = stack_record.end
-
          __pyx_t_14 = __pyx_v_stack_record.end;
-          __pyx_v_end = __pyx_t_14;
-
+0196:                 depth = stack_record.depth
-
          __pyx_t_14 = __pyx_v_stack_record.depth;
-          __pyx_v_depth = __pyx_t_14;
-
+0197:                 parent = stack_record.parent
-
          __pyx_t_14 = __pyx_v_stack_record.parent;
-          __pyx_v_parent = __pyx_t_14;
-
+0198:                 is_left = stack_record.is_left
-
          __pyx_t_9 = __pyx_v_stack_record.is_left;
-          __pyx_v_is_left = __pyx_t_9;
-
+0199:                 impurity = stack_record.impurity
-
          __pyx_t_11 = __pyx_v_stack_record.impurity;
-          __pyx_v_impurity = __pyx_t_11;
-
+0200:                 n_constant_features = stack_record.n_constant_features
-
          __pyx_t_14 = __pyx_v_stack_record.n_constant_features;
-          __pyx_v_n_constant_features = __pyx_t_14;
-
 0201:
-
+0202:                 n_node_samples = end - start
-
          __pyx_v_n_node_samples = (__pyx_v_end - __pyx_v_start);
-
+0203:                 splitter.node_reset(start, end, &weighted_n_node_samples)
-
          __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_reset(__pyx_v_splitter, __pyx_v_start, __pyx_v_end, (&__pyx_v_weighted_n_node_samples)); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 203, __pyx_L8_error)
-
 0204:
-
+0205:                 is_leaf = (depth >= max_depth or
-
          __pyx_t_8 = ((__pyx_v_depth >= __pyx_v_max_depth) != 0);
-          if (!__pyx_t_8) {
-          } else {
-            __pyx_t_9 = __pyx_t_8;
-            goto __pyx_L16_bool_binop_done;
-          }
-
+0206:                            n_node_samples < min_samples_split or
-
          __pyx_t_8 = ((__pyx_v_n_node_samples < __pyx_v_min_samples_split) != 0);
-          if (!__pyx_t_8) {
-          } else {
-            __pyx_t_9 = __pyx_t_8;
-            goto __pyx_L16_bool_binop_done;
-          }
-
+0207:                            n_node_samples < 2 * min_samples_leaf or
-
          __pyx_t_8 = ((__pyx_v_n_node_samples < (2 * __pyx_v_min_samples_leaf)) != 0);
-          if (!__pyx_t_8) {
-          } else {
-            __pyx_t_9 = __pyx_t_8;
-            goto __pyx_L16_bool_binop_done;
-          }
-
+0208:                            weighted_n_node_samples < 2 * min_weight_leaf)
-
          __pyx_t_8 = ((__pyx_v_weighted_n_node_samples < (2.0 * __pyx_v_min_weight_leaf)) != 0);
-          __pyx_t_9 = __pyx_t_8;
-          __pyx_L16_bool_binop_done:;
-          __pyx_v_is_leaf = __pyx_t_9;
-
 0209:
-
+0210:                 if first:
-
          __pyx_t_9 = (__pyx_v_first != 0);
-          if (__pyx_t_9) {
-/* … */
-          }
-
+0211:                     impurity = splitter.node_impurity()
-
            __pyx_v_impurity = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_impurity(__pyx_v_splitter);
-
+0212:                     first = 0
-
            __pyx_v_first = 0;
-
 0213:
-
+0214:                 is_leaf = (is_leaf or
-
          __pyx_t_8 = (__pyx_v_is_leaf != 0);
-          if (!__pyx_t_8) {
-          } else {
-            __pyx_t_9 = __pyx_t_8;
-            goto __pyx_L21_bool_binop_done;
-          }
-
+0215:                            (impurity <= min_impurity_split))
-
          __pyx_t_8 = ((__pyx_v_impurity <= __pyx_v_min_impurity_split) != 0);
-          __pyx_t_9 = __pyx_t_8;
-          __pyx_L21_bool_binop_done:;
-          __pyx_v_is_leaf = __pyx_t_9;
-
 0216:
-
+0217:                 if not is_leaf:
-
          __pyx_t_9 = ((!(__pyx_v_is_leaf != 0)) != 0);
-          if (__pyx_t_9) {
-/* … */
-          }
-
+0218:                     splitter.node_split(impurity, &split, &n_constant_features)
-
            __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_split(__pyx_v_splitter, __pyx_v_impurity, (&__pyx_v_split), (&__pyx_v_n_constant_features)); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 218, __pyx_L8_error)
-
 0219:                     # If EPSILON=0 in the below comparison, float precision
-
 0220:                     # issues stop splitting, producing trees that are
-
 0221:                     # dissimilar to v0.18
-
+0222:                     is_leaf = (is_leaf or split.pos >= end or
-
            __pyx_t_8 = (__pyx_v_is_leaf != 0);
-            if (!__pyx_t_8) {
-            } else {
-              __pyx_t_9 = __pyx_t_8;
-              goto __pyx_L24_bool_binop_done;
-            }
-            __pyx_t_8 = ((__pyx_v_split.pos >= __pyx_v_end) != 0);
-            if (!__pyx_t_8) {
-            } else {
-              __pyx_t_9 = __pyx_t_8;
-              goto __pyx_L24_bool_binop_done;
-            }
-
+0223:                                (split.improvement + EPSILON <
-
            __pyx_t_8 = (((__pyx_v_split.improvement + __pyx_v_13stpredictions_6models_3OK3_5_tree_EPSILON) < __pyx_v_min_impurity_decrease) != 0);
-            __pyx_t_9 = __pyx_t_8;
-            __pyx_L24_bool_binop_done:;
-            __pyx_v_is_leaf = __pyx_t_9;
-
 0224:                                 min_impurity_decrease))
-
 0225:
-
+0226:                 node_id = tree._add_node(parent, is_left, is_leaf, split.feature,
-
          __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_add_node(__pyx_v_tree, __pyx_v_parent, __pyx_v_is_left, __pyx_v_is_leaf, __pyx_v_split.feature, __pyx_v_split.threshold, __pyx_v_impurity, __pyx_v_n_node_samples, __pyx_v_weighted_n_node_samples); if (unlikely(__pyx_t_10 == ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)-1))) __PYX_ERR(0, 226, __pyx_L8_error)
-          __pyx_v_node_id = __pyx_t_10;
-
 0227:                                          split.threshold, impurity, n_node_samples,
-
 0228:                                          weighted_n_node_samples)
-
 0229:
-
+0230:                 if node_id == SIZE_MAX:
-
          __pyx_t_9 = ((__pyx_v_node_id == SIZE_MAX) != 0);
-          if (__pyx_t_9) {
-/* … */
-          }
-
+0231:                     rc = -1
-
            __pyx_v_rc = -1;
-
+0232:                     break
-
            goto __pyx_L15_break;
-
 0233:
-
 0234:                 # Store value for all nodes, to facilitate tree/model
-
 0235:                 # inspection and interpretation
-
+0236:                 splitter.node_value(tree.value + node_id * y.shape[0])
-
          ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_value(__pyx_v_splitter, (__pyx_v_tree->value + (__pyx_v_node_id * (__pyx_v_y->dimensions[0]))));
-
 0237:
-
+0238:                 if not is_leaf:
-
          __pyx_t_9 = ((!(__pyx_v_is_leaf != 0)) != 0);
-          if (__pyx_t_9) {
-/* … */
-          }
-
 0239:                     # Push right child on stack
-
+0240:                     rc = stack.push(split.pos, end, depth + 1, node_id, 0,
-
            __pyx_t_5 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_split.pos, __pyx_v_end, (__pyx_v_depth + 1), __pyx_v_node_id, 0, __pyx_v_split.impurity_right, __pyx_v_n_constant_features); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 240, __pyx_L8_error)
-            __pyx_v_rc = __pyx_t_5;
-
 0241:                                     split.impurity_right, n_constant_features)
-
+0242:                     if rc == -1:
-
            __pyx_t_9 = ((__pyx_v_rc == -1L) != 0);
-            if (__pyx_t_9) {
-/* … */
-            }
-
+0243:                         break
-
              goto __pyx_L15_break;
-
 0244:
-
 0245:                     # Push left child on stack
-
+0246:                     rc = stack.push(start, split.pos, depth + 1, node_id, 1,
-
            __pyx_t_5 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_start, __pyx_v_split.pos, (__pyx_v_depth + 1), __pyx_v_node_id, 1, __pyx_v_split.impurity_left, __pyx_v_n_constant_features); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 246, __pyx_L8_error)
-            __pyx_v_rc = __pyx_t_5;
-
 0247:                                     split.impurity_left, n_constant_features)
-
+0248:                     if rc == -1:
-
            __pyx_t_9 = ((__pyx_v_rc == -1L) != 0);
-            if (__pyx_t_9) {
-/* … */
-            }
-
+0249:                         break
-
              goto __pyx_L15_break;
-
 0250:
-
+0251:                 if depth > max_depth_seen:
-
          __pyx_t_9 = ((__pyx_v_depth > __pyx_v_max_depth_seen) != 0);
-          if (__pyx_t_9) {
-/* … */
-          }
-        }
-        __pyx_L15_break:;
-
+0252:                     max_depth_seen = depth
-
            __pyx_v_max_depth_seen = __pyx_v_depth;
-
 0253:
-
+0254:             if rc >= 0:
-
        __pyx_t_9 = ((__pyx_v_rc >= 0) != 0);
-        if (__pyx_t_9) {
-/* … */
-        }
-
+0255:                 rc = tree._resize_c(tree.node_count)
-
          __pyx_t_15.__pyx_n = 1;
-          __pyx_t_15.capacity = __pyx_v_tree->node_count;
-          __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize_c(__pyx_v_tree, &__pyx_t_15); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 255, __pyx_L8_error)
-          __pyx_v_rc = __pyx_t_5;
-
 0256:
-
+0257:             if rc >= 0:
-
        __pyx_t_9 = ((__pyx_v_rc >= 0) != 0);
-        if (__pyx_t_9) {
-/* … */
-        }
-      }
-
+0258:                 tree.max_depth = max_depth_seen
-
          __pyx_v_tree->max_depth = __pyx_v_max_depth_seen;
-
 0259:
-
+0260:         if rc == -1:
-
  __pyx_t_9 = ((__pyx_v_rc == -1L) != 0);
-  if (unlikely(__pyx_t_9)) {
-/* … */
-  }
-
+0261:             raise MemoryError()
-
    PyErr_NoMemory(); __PYX_ERR(0, 261, __pyx_L1_error)
-
 0262:
-
 0263:
-
 0264:         # feed the tree attribute 'K_y'
-
 0265:
-
+0266:         tree.K_y = y
-
  __Pyx_INCREF(((PyObject *)__pyx_v_y));
-  __Pyx_GIVEREF(((PyObject *)__pyx_v_y));
-  __Pyx_GOTREF(__pyx_v_tree->K_y);
-  __Pyx_DECREF(((PyObject *)__pyx_v_tree->K_y));
-  __pyx_v_tree->K_y = __pyx_v_y;
-
 0267:
-
 0268: # Best first builder ----------------------------------------------------------
-
 0269:
-
+0270: cdef inline int _add_to_frontier(PriorityHeapRecord* rec,
-
static CYTHON_INLINE int __pyx_f_13stpredictions_6models_3OK3_5_tree__add_to_frontier(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *__pyx_v_rec, struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *__pyx_v_frontier) {
-  int __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L1_error:;
-  {
-    #ifdef WITH_THREAD
-    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
-    #endif
-    __Pyx_AddTraceback("stpredictions.models.OK3._tree._add_to_frontier", __pyx_clineno, __pyx_lineno, __pyx_filename);
-    #ifdef WITH_THREAD
-    __Pyx_PyGILState_Release(__pyx_gilstate_save);
-    #endif
-  }
-  __pyx_r = -1;
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 0271:                                  PriorityHeap frontier) nogil except -1:
-
 0272:     """Adds record ``rec`` to the priority queue ``frontier``
-
 0273:
-
 0274:     Returns -1 in case of failure to allocate memory (and raise MemoryError)
-
 0275:     or 0 otherwise.
-
 0276:     """
-
+0277:     return frontier.push(rec.node_id, rec.start, rec.end, rec.pos, rec.depth,
-
  __pyx_t_1 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->push(__pyx_v_frontier, __pyx_v_rec->node_id, __pyx_v_rec->start, __pyx_v_rec->end, __pyx_v_rec->pos, __pyx_v_rec->depth, __pyx_v_rec->is_leaf, __pyx_v_rec->improvement, __pyx_v_rec->impurity, __pyx_v_rec->impurity_left, __pyx_v_rec->impurity_right); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 277, __pyx_L1_error)
-  __pyx_r = __pyx_t_1;
-  goto __pyx_L0;
-
 0278:                          rec.is_leaf, rec.improvement, rec.impurity,
-
 0279:                          rec.impurity_left, rec.impurity_right)
-
 0280:
-
 0281:
-
+0282: cdef class BestFirstTreeBuilder(TreeBuilder):
-
struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder {
-  struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder __pyx_base;
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_leaf_nodes;
-};
-/* … */
-struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder {
-  struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder __pyx_base;
-  int (*_add_split_node)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, int, int, struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t);
-};
-static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder;
-static CYTHON_INLINE int __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, int, int, struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t);
-
-
 0283:     """Build a decision tree in best-first fashion.
-
 0284:
-
 0285:     The best node to expand is given by the node at the frontier that has the
-
 0286:     highest impurity improvement.
-
 0287:     """
-
 0288:     cdef SIZE_t max_leaf_nodes
-
 0289:
-
+0290:     def __cinit__(self, Splitter splitter, SIZE_t min_samples_split,
-
/* Python wrapper */
-static int __pyx_pw_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
-static int __pyx_pw_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
-  struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter = 0;
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_split;
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf;
-  PyObject *__pyx_v_min_weight_leaf = 0;
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth;
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_leaf_nodes;
-  double __pyx_v_min_impurity_decrease;
-  double __pyx_v_min_impurity_split;
-  int __pyx_r;
-  __Pyx_RefNannyDeclarations
-  __Pyx_RefNannySetupContext("__cinit__ (wrapper)", 0);
-  {
-    static PyObject **__pyx_pyargnames[] = {&__pyx_n_s_splitter,&__pyx_n_s_min_samples_split,&__pyx_n_s_min_samples_leaf,&__pyx_n_s_min_weight_leaf,&__pyx_n_s_max_depth,&__pyx_n_s_max_leaf_nodes,&__pyx_n_s_min_impurity_decrease,&__pyx_n_s_min_impurity_split,0};
-    PyObject* values[8] = {0,0,0,0,0,0,0,0};
-    if (unlikely(__pyx_kwds)) {
-      Py_ssize_t kw_args;
-      const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
-      switch (pos_args) {
-        case  8: values[7] = PyTuple_GET_ITEM(__pyx_args, 7);
-        CYTHON_FALLTHROUGH;
-        case  7: values[6] = PyTuple_GET_ITEM(__pyx_args, 6);
-        CYTHON_FALLTHROUGH;
-        case  6: values[5] = PyTuple_GET_ITEM(__pyx_args, 5);
-        CYTHON_FALLTHROUGH;
-        case  5: values[4] = PyTuple_GET_ITEM(__pyx_args, 4);
-        CYTHON_FALLTHROUGH;
-        case  4: values[3] = PyTuple_GET_ITEM(__pyx_args, 3);
-        CYTHON_FALLTHROUGH;
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 0325:         cdef PriorityHeapRecord record
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 0326:         cdef PriorityHeapRecord split_node_left
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 0327:         cdef PriorityHeapRecord split_node_right
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 0331:         cdef bint is_leaf
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            __pyx_v_node->right_child = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF;
-
+0363:                     node.feature = _TREE_UNDEFINED
-
            __pyx_v_node->feature = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED;
-
+0364:                     node.threshold = _TREE_UNDEFINED
-
            __pyx_v_node->threshold = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED;
-
 0365:
-
 0366:                 else:
-
 0367:                     # Node is expandable
-
 0368:
-
 0369:                     # Decrement number of split nodes available
-
+0370:                     max_split_nodes -= 1
-
          /*else*/ {
-            __pyx_v_max_split_nodes = (__pyx_v_max_split_nodes - 1);
-
 0371:
-
 0372:                     # Compute left split node
-
+0373:                     rc = self._add_split_node(splitter, tree,
-
            __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, __pyx_v_record.start, __pyx_v_record.pos, __pyx_v_record.impurity_left, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_FIRST, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_LEFT, __pyx_v_node, (__pyx_v_record.depth + 1), (&__pyx_v_split_node_left), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 373, __pyx_L7_error)
-            __pyx_v_rc = __pyx_t_5;
-
 0374:                                               record.start, record.pos,
-
 0375:                                               record.impurity_left,
-
 0376:                                               IS_NOT_FIRST, IS_LEFT, node,
-
 0377:                                               record.depth + 1,
-
 0378:                                               &split_node_left,
-
 0379:                                               y.shape[0])
-
+0380:                     if rc == -1:
-
            __pyx_t_9 = ((__pyx_v_rc == -1L) != 0);
-            if (__pyx_t_9) {
-/* … */
-            }
-
+0381:                         break
-
              goto __pyx_L15_break;
-
 0382:
-
 0383:                     # tree.nodes may have changed
-
+0384:                     node = &tree.nodes[record.node_id]
-
            __pyx_v_node = (&(__pyx_v_tree->nodes[__pyx_v_record.node_id]));
-
 0385:
-
 0386:                     # Compute right split node
-
+0387:                     rc = self._add_split_node(splitter, tree, record.pos,
-
            __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, __pyx_v_record.pos, __pyx_v_record.end, __pyx_v_record.impurity_right, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_FIRST, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_LEFT, __pyx_v_node, (__pyx_v_record.depth + 1), (&__pyx_v_split_node_right), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 387, __pyx_L7_error)
-            __pyx_v_rc = __pyx_t_5;
-
 0388:                                               record.end,
-
 0389:                                               record.impurity_right,
-
 0390:                                               IS_NOT_FIRST, IS_NOT_LEFT, node,
-
 0391:                                               record.depth + 1,
-
 0392:                                               &split_node_right,
-
 0393:                                               y.shape[0])
-
+0394:                     if rc == -1:
-
            __pyx_t_9 = ((__pyx_v_rc == -1L) != 0);
-            if (__pyx_t_9) {
-/* … */
-            }
-
+0395:                         break
-
              goto __pyx_L15_break;
-
 0396:
-
 0397:                     # Add nodes to queue
-
+0398:                     rc = _add_to_frontier(&split_node_left, frontier)
-
            __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree__add_to_frontier((&__pyx_v_split_node_left), __pyx_v_frontier); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 398, __pyx_L7_error)
-            __pyx_v_rc = __pyx_t_5;
-
+0399:                     if rc == -1:
-
            __pyx_t_9 = ((__pyx_v_rc == -1L) != 0);
-            if (__pyx_t_9) {
-/* … */
-            }
-
+0400:                         break
-
              goto __pyx_L15_break;
-
 0401:
-
+0402:                     rc = _add_to_frontier(&split_node_right, frontier)
-
            __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree__add_to_frontier((&__pyx_v_split_node_right), __pyx_v_frontier); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 402, __pyx_L7_error)
-            __pyx_v_rc = __pyx_t_5;
-
+0403:                     if rc == -1:
-
            __pyx_t_9 = ((__pyx_v_rc == -1L) != 0);
-            if (__pyx_t_9) {
-/* … */
-            }
-          }
-          __pyx_L18:;
-
+0404:                         break
-
              goto __pyx_L15_break;
-
 0405:
-
+0406:                 if record.depth > max_depth_seen:
-
          __pyx_t_9 = ((__pyx_v_record.depth > __pyx_v_max_depth_seen) != 0);
-          if (__pyx_t_9) {
-/* … */
-          }
-        }
-        __pyx_L15_break:;
-
+0407:                     max_depth_seen = record.depth
-
            __pyx_t_14 = __pyx_v_record.depth;
-            __pyx_v_max_depth_seen = __pyx_t_14;
-
 0408:
-
+0409:             if rc >= 0:
-
        __pyx_t_9 = ((__pyx_v_rc >= 0) != 0);
-        if (__pyx_t_9) {
-/* … */
-        }
-
+0410:                 rc = tree._resize_c(tree.node_count)
-
          __pyx_t_15.__pyx_n = 1;
-          __pyx_t_15.capacity = __pyx_v_tree->node_count;
-          __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize_c(__pyx_v_tree, &__pyx_t_15); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 410, __pyx_L7_error)
-          __pyx_v_rc = __pyx_t_5;
-
 0411:
-
+0412:             if rc >= 0:
-
        __pyx_t_9 = ((__pyx_v_rc >= 0) != 0);
-        if (__pyx_t_9) {
-/* … */
-        }
-      }
-
+0413:                 tree.max_depth = max_depth_seen
-
          __pyx_v_tree->max_depth = __pyx_v_max_depth_seen;
-
 0414:
-
+0415:         if rc == -1:
-
  __pyx_t_9 = ((__pyx_v_rc == -1L) != 0);
-  if (unlikely(__pyx_t_9)) {
-/* … */
-  }
-
+0416:             raise MemoryError()
-
    PyErr_NoMemory(); __PYX_ERR(0, 416, __pyx_L1_error)
-
 0417:
-
 0418:
-
 0419:         # feed the tree attribute 'K_y'
-
 0420:
-
+0421:         tree.K_y = y
-
  __Pyx_INCREF(((PyObject *)__pyx_v_y));
-  __Pyx_GIVEREF(((PyObject *)__pyx_v_y));
-  __Pyx_GOTREF(__pyx_v_tree->K_y);
-  __Pyx_DECREF(((PyObject *)__pyx_v_tree->K_y));
-  __pyx_v_tree->K_y = __pyx_v_y;
-
 0422:
-
 0423:
-
+0424:     cdef inline int _add_split_node(self, Splitter splitter, Tree tree,
-
static CYTHON_INLINE int __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end, double __pyx_v_impurity, int __pyx_v_is_first, int __pyx_v_is_left, struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_parent, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_depth, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *__pyx_v_res, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_samples) {
-  struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_split;
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_node_id;
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_node_samples;
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_constant_features;
-  CYTHON_UNUSED double __pyx_v_weighted_n_samples;
-  double __pyx_v_min_impurity_decrease;
-  double __pyx_v_min_impurity_split;
-  double __pyx_v_weighted_n_node_samples;
-  int __pyx_v_is_leaf;
-  int __pyx_r;
-/* … */
-  /* function exit code */
-  __pyx_L1_error:;
-  {
-    #ifdef WITH_THREAD
-    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
-    #endif
-    __Pyx_AddTraceback("stpredictions.models.OK3._tree.BestFirstTreeBuilder._add_split_node", __pyx_clineno, __pyx_lineno, __pyx_filename);
-    #ifdef WITH_THREAD
-    __Pyx_PyGILState_Release(__pyx_gilstate_save);
-    #endif
-  }
-  __pyx_r = -1;
-  __pyx_L0:;
-  return __pyx_r;
-}
-
 0425:                                     SIZE_t start, SIZE_t end, double impurity,
-
 0426:                                     bint is_first, bint is_left, Node* parent,
-
 0427:                                     SIZE_t depth,
-
 0428:                                     PriorityHeapRecord* res,
-
 0429:                                     SIZE_t n_samples) nogil except -1:
-
 0430:         """Adds node w/ partition ``[start, end)`` to the frontier. """
-
 0431:         cdef SplitRecord split
-
 0432:         cdef SIZE_t node_id
-
 0433:         cdef SIZE_t n_node_samples
-
+0434:         cdef SIZE_t n_constant_features = 0
-
  __pyx_v_n_constant_features = 0;
-
+0435:         cdef double weighted_n_samples = splitter.weighted_n_samples
-
  __pyx_t_1 = __pyx_v_splitter->weighted_n_samples;
-  __pyx_v_weighted_n_samples = __pyx_t_1;
-
+0436:         cdef double min_impurity_decrease = self.min_impurity_decrease
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.min_impurity_decrease;
-  __pyx_v_min_impurity_decrease = __pyx_t_1;
-
+0437:         cdef double min_impurity_split = self.min_impurity_split
-
  __pyx_t_1 = __pyx_v_self->__pyx_base.min_impurity_split;
-  __pyx_v_min_impurity_split = __pyx_t_1;
-
 0438:         cdef double weighted_n_node_samples
-
 0439:         cdef bint is_leaf
-
 0440:         cdef SIZE_t n_left, n_right
-
 0441:         cdef double imp_diff
-
 0442:
-
+0443:         splitter.node_reset(start, end, &weighted_n_node_samples)
-
  __pyx_t_2 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_reset(__pyx_v_splitter, __pyx_v_start, __pyx_v_end, (&__pyx_v_weighted_n_node_samples)); if (unlikely(__pyx_t_2 == ((int)-1))) __PYX_ERR(0, 443, __pyx_L1_error)
-
 0444:
-
+0445:         if is_first:
-
  __pyx_t_3 = (__pyx_v_is_first != 0);
-  if (__pyx_t_3) {
-/* … */
-  }
-
+0446:             impurity = splitter.node_impurity()
-
    __pyx_v_impurity = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_impurity(__pyx_v_splitter);
-
 0447:
-
+0448:         n_node_samples = end - start
-
  __pyx_v_n_node_samples = (__pyx_v_end - __pyx_v_start);
-
+0449:         is_leaf = (depth >= self.max_depth or
-
  __pyx_t_4 = ((__pyx_v_depth >= __pyx_v_self->__pyx_base.max_depth) != 0);
-  if (!__pyx_t_4) {
-  } else {
-    __pyx_t_3 = __pyx_t_4;
-    goto __pyx_L4_bool_binop_done;
-  }
-
+0450:                    n_node_samples < self.min_samples_split or
-
  __pyx_t_4 = ((__pyx_v_n_node_samples < __pyx_v_self->__pyx_base.min_samples_split) != 0);
-  if (!__pyx_t_4) {
-  } else {
-    __pyx_t_3 = __pyx_t_4;
-    goto __pyx_L4_bool_binop_done;
-  }
-
+0451:                    n_node_samples < 2 * self.min_samples_leaf or
-
  __pyx_t_4 = ((__pyx_v_n_node_samples < (2 * __pyx_v_self->__pyx_base.min_samples_leaf)) != 0);
-  if (!__pyx_t_4) {
-  } else {
-    __pyx_t_3 = __pyx_t_4;
-    goto __pyx_L4_bool_binop_done;
-  }
-
+0452:                    weighted_n_node_samples < 2 * self.min_weight_leaf or
-
  __pyx_t_4 = ((__pyx_v_weighted_n_node_samples < (2.0 * __pyx_v_self->__pyx_base.min_weight_leaf)) != 0);
-  if (!__pyx_t_4) {
-  } else {
-    __pyx_t_3 = __pyx_t_4;
-    goto __pyx_L4_bool_binop_done;
-  }
-
+0453:                    impurity <= min_impurity_split)
-
  __pyx_t_4 = ((__pyx_v_impurity <= __pyx_v_min_impurity_split) != 0);
-  __pyx_t_3 = __pyx_t_4;
-  __pyx_L4_bool_binop_done:;
-  __pyx_v_is_leaf = __pyx_t_3;
-
 0454:
-
+0455:         if not is_leaf:
-
  __pyx_t_3 = ((!(__pyx_v_is_leaf != 0)) != 0);
-  if (__pyx_t_3) {
-/* … */
-  }
-
+0456:             splitter.node_split(impurity, &split, &n_constant_features)
-
    __pyx_t_2 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_split(__pyx_v_splitter, __pyx_v_impurity, (&__pyx_v_split), (&__pyx_v_n_constant_features)); if (unlikely(__pyx_t_2 == ((int)-1))) __PYX_ERR(0, 456, __pyx_L1_error)
-
 0457:             # If EPSILON=0 in the below comparison, float precision issues stop
-
 0458:             # splitting early, producing trees that are dissimilar to v0.18
-
+0459:             is_leaf = (is_leaf or split.pos >= end or
-
    __pyx_t_4 = (__pyx_v_is_leaf != 0);
-    if (!__pyx_t_4) {
-    } else {
-      __pyx_t_3 = __pyx_t_4;
-      goto __pyx_L10_bool_binop_done;
-    }
-    __pyx_t_4 = ((__pyx_v_split.pos >= __pyx_v_end) != 0);
-    if (!__pyx_t_4) {
-    } else {
-      __pyx_t_3 = __pyx_t_4;
-      goto __pyx_L10_bool_binop_done;
-    }
-
+0460:                        split.improvement + EPSILON < min_impurity_decrease)
-
    __pyx_t_4 = (((__pyx_v_split.improvement + __pyx_v_13stpredictions_6models_3OK3_5_tree_EPSILON) < __pyx_v_min_impurity_decrease) != 0);
-    __pyx_t_3 = __pyx_t_4;
-    __pyx_L10_bool_binop_done:;
-    __pyx_v_is_leaf = __pyx_t_3;
-
 0461:
-
+0462:         node_id = tree._add_node(parent - tree.nodes
-
    __pyx_t_5 = (__pyx_v_parent - __pyx_v_tree->nodes);
-  } else {
-/* … */
-  __pyx_t_6 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_add_node(__pyx_v_tree, __pyx_t_5, __pyx_v_is_left, __pyx_v_is_leaf, __pyx_v_split.feature, __pyx_v_split.threshold, __pyx_v_impurity, __pyx_v_n_node_samples, __pyx_v_weighted_n_node_samples); if (unlikely(__pyx_t_6 == ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)-1))) __PYX_ERR(0, 462, __pyx_L1_error)
-  __pyx_v_node_id = __pyx_t_6;
-
+0463:                                  if parent != NULL
-
  if (((__pyx_v_parent != NULL) != 0)) {
-
+0464:                                  else _TREE_UNDEFINED,
-
    __pyx_t_5 = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED;
-  }
-
 0465:                                  is_left, is_leaf,
-
 0466:                                  split.feature, split.threshold, impurity, n_node_samples,
-
 0467:                                  weighted_n_node_samples)
-
+0468:         if node_id == SIZE_MAX:
-
  __pyx_t_3 = ((__pyx_v_node_id == SIZE_MAX) != 0);
-  if (__pyx_t_3) {
-/* … */
-  }
-
+0469:             return -1
-
    __pyx_r = -1;
-    goto __pyx_L0;
-
 0470:
-
 0471:         # compute values also for split nodes (might become leafs later).
-
+0472:         splitter.node_value(tree.value + node_id * n_samples)
-
  ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_value(__pyx_v_splitter, (__pyx_v_tree->value + (__pyx_v_node_id * __pyx_v_n_samples)));
-
 0473:
-
+0474:         res.node_id = node_id
-
  __pyx_v_res->node_id = __pyx_v_node_id;
-
+0475:         res.start = start
-
  __pyx_v_res->start = __pyx_v_start;
-
+0476:         res.end = end
-
  __pyx_v_res->end = __pyx_v_end;
-
+0477:         res.depth = depth
-
  __pyx_v_res->depth = __pyx_v_depth;
-
+0478:         res.impurity = impurity
-
  __pyx_v_res->impurity = __pyx_v_impurity;
-
 0479:
-
+0480:         if not is_leaf:
-
  __pyx_t_3 = ((!(__pyx_v_is_leaf != 0)) != 0);
-  if (__pyx_t_3) {
-/* … */
-    goto __pyx_L14;
-  }
-
 0481:             # is split node
-
+0482:             res.pos = split.pos
-
    __pyx_t_7 = __pyx_v_split.pos;
-    __pyx_v_res->pos = __pyx_t_7;
-
+0483:             res.is_leaf = 0
-
    __pyx_v_res->is_leaf = 0;
-
+0484:             res.improvement = split.improvement
-
    __pyx_t_1 = __pyx_v_split.improvement;
-    __pyx_v_res->improvement = __pyx_t_1;
-
+0485:             res.impurity_left = split.impurity_left
-
    __pyx_t_1 = __pyx_v_split.impurity_left;
-    __pyx_v_res->impurity_left = __pyx_t_1;
-
+0486:             res.impurity_right = split.impurity_right
-
    __pyx_t_1 = __pyx_v_split.impurity_right;
-    __pyx_v_res->impurity_right = __pyx_t_1;
-
 0487:
-
 0488:         else:
-
 0489:             # is leaf => 0 improvement
-
+0490:             res.pos = end
-
  /*else*/ {
-    __pyx_v_res->pos = __pyx_v_end;
-
+0491:             res.is_leaf = 1
-
    __pyx_v_res->is_leaf = 1;
-
+0492:             res.improvement = 0.0
-
    __pyx_v_res->improvement = 0.0;
-
+0493:             res.impurity_left = impurity
-
    __pyx_v_res->impurity_left = __pyx_v_impurity;
-
+0494:             res.impurity_right = impurity
-
    __pyx_v_res->impurity_right = __pyx_v_impurity;
-  }
-  __pyx_L14:;
-
 0495:
-
+0496:         return 0
-
  __pyx_r = 0;
-  goto __pyx_L0;
-
 0497:
-
 0498:
-
 0499: # =============================================================================
-
 0500: # Tree
-
 0501: # =============================================================================
-
 0502:
-
+0503: cdef class Tree:
-
struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree {
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int, int, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double);
-  int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t);
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 0513:     Attributes
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 0517:
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 0518:     capacity : int
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 0520:         great as `node_count`.
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 0522:     max_depth : int
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 0523:         The depth of the tree, i.e. the maximum depth of its leaves.
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 0524:
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 0526:         Gives for each node, the weighted list of training samples
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 0527:         falling in the leaf/leaves bellow the leaf/node.
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 0528:         (Kind of invert the array given by the 'apply' function.)
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 0529:
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 0530:     K_y : array of double, shape [n_train_samples, n_train_samples]
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 0531:         The training output Gramm matrix (used to compute the predictions)
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 0539:         children_left[i] > i. This child handles the case where
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 0551:     threshold : array of double, shape [node_count]
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 0552:         threshold[i] holds the threshold for the internal node i.
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 0690:         or 0 otherwise.
-
 0691:         """
-
+0692:         if capacity == self.capacity and self.nodes != NULL:
-
  __pyx_t_2 = ((__pyx_v_capacity == __pyx_v_self->capacity) != 0);
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-  __pyx_t_2 = ((__pyx_v_self->nodes != NULL) != 0);
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-/* … */
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-
+0693:             return 0
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-
+0695:         if capacity == SIZE_MAX:
-
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+0696:             if self.capacity == 0:
-
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+0697:                 capacity = 3  # default initial value
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-
 0698:             else:
-
+0699:                 capacity = 2 * self.capacity
-
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 0700:
-
+0701:         safe_realloc(&self.nodes, capacity)
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-
+0702:         safe_realloc(&self.value, capacity * self.K_y.shape[0])
-
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-
 0703:
-
 0704:         # value memory is initialised to 0 to enable classifier argmax
-
+0705:         if capacity > self.capacity:
-
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- *         # value memory is initialised to 0 to enable classifier argmax
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-
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-
+0706:             memset(<void*>(self.value + self.capacity * self.K_y.shape[0]), 0,
-
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-
 0707:                    (capacity - self.capacity) * self.K_y.shape[0] *
-
 0708:                    sizeof(double))
-
 0709:
-
 0710:         # if capacity smaller than node_count, adjust the counter
-
+0711:         if capacity < self.node_count:
-
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-
+0712:             self.node_count = capacity
-
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 0713:
-
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-
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-
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-
+0717:     cdef SIZE_t _add_node(self, SIZE_t parent, bint is_left, bint is_leaf,
-
static __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__add_node(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_parent, int __pyx_v_is_left, int __pyx_v_is_leaf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_feature, double __pyx_v_threshold, double __pyx_v_impurity, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_node_samples, double __pyx_v_weighted_n_node_samples) {
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_node_id;
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 0718:                           SIZE_t feature, double threshold, double impurity,
-
 0719:                           SIZE_t n_node_samples,
-
 0720:                           double weighted_n_node_samples) nogil except -1:
-
 0721:         """Add a node to the tree.
-
 0722:
-
 0723:         The new node registers itself as the child of its parent.
-
 0724:
-
 0725:         Returns (size_t)(-1) on error.
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-
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-
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-
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-
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-
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-
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-
+0735:         node.n_node_samples = n_node_samples
-
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-
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-
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 1426:         SIZE_t pruned_branch_node_idx
-
 1427:         DOUBLE_t subtree_alpha
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 1428:         DOUBLE_t effective_alpha
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 1429:         SIZE_t child_l_idx
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 1430:         SIZE_t child_r_idx
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 1431:         SIZE_t n_pruned_leaves
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 1432:         DOUBLE_t r_diff
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 1434:
-
 1435:     # find parent node ids and leaves
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-
  {
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-      PyThreadState *_save;
-      Py_UNBLOCK_THREADS
-      __Pyx_FastGIL_Remember();
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 1437:
-
+1438:         for i in range(r_node.shape[0]):
-
        __pyx_t_11 = (__pyx_v_r_node.shape[0]);
-        __pyx_t_12 = __pyx_t_11;
-        for (__pyx_t_1 = 0; __pyx_t_1 < __pyx_t_12; __pyx_t_1+=1) {
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-
+1439:             r_node[i] = (
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          __pyx_t_14 = __pyx_v_i;
-          *((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_14 * __pyx_v_r_node.strides[0]) )) = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_weighted_n_node_samples.data + __pyx_t_4 * __pyx_v_weighted_n_node_samples.strides[0]) ))) * (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_impurity.data + __pyx_t_13 * __pyx_v_impurity.strides[0]) )))) / __pyx_v_total_sum_weights);
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+1440:                 weighted_n_node_samples[i] * impurity[i] / total_sum_weights)
-
          __pyx_t_4 = __pyx_v_i;
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-
 1441:
-
 1442:         # Push root node, using StackRecord.start as node id
-
+1443:         rc = stack.push(0, 0, 0, -1, 0, 0, 0)
-
        __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, 0, 0, 0, -1, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1443, __pyx_L4_error)
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-
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+1445:             with gil:
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          {
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+1446:                 raise MemoryError("pruning tree")
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                __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_MemoryError, __pyx_tuple__16, NULL); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1446, __pyx_L10_error)
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-/* … */
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 1447:
-
+1448:         while not stack.is_empty():
-
        while (1) {
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+1449:             stack.pop(&stack_record)
-
          (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record)));
-
+1450:             node_idx = stack_record.start
-
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-
+1451:             parent[node_idx] = stack_record.parent
-
          __pyx_t_17 = __pyx_v_stack_record.parent;
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-
+1452:             if child_l[node_idx] == _TREE_LEAF:
-
          __pyx_t_13 = __pyx_v_node_idx;
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-/* … */
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-
 1453:                 # ... and child_r[node_idx] == _TREE_LEAF:
-
+1454:                 leaves_in_subtree[node_idx] = 1
-
            __pyx_t_13 = __pyx_v_node_idx;
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-
 1455:             else:
-
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-
          /*else*/ {
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-
+1457:                 if rc == -1:
-
            __pyx_t_16 = ((__pyx_v_rc == -1L) != 0);
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-/* … */
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+1458:                     with gil:
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              {
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+1459:                         raise MemoryError("pruning tree")
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                    __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_MemoryError, __pyx_tuple__16, NULL); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1459, __pyx_L19_error)
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-
 1460:
-
+1461:                 rc = stack.push(child_r[node_idx], 0, 0, node_idx, 0, 0, 0)
-
            __pyx_t_13 = __pyx_v_node_idx;
-            __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_r.data + __pyx_t_13 * __pyx_v_child_r.strides[0]) ))), 0, 0, __pyx_v_node_idx, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1461, __pyx_L4_error)
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-
+1462:                 if rc == -1:
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+1463:                     with gil:
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              {
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+1464:                         raise MemoryError("pruning tree")
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 1465:
-
 1466:         # computes number of leaves in all branches and the overall impurity of
-
 1467:         # the branch. The overall impurity is the sum of r_node in its leaves.
-
+1468:         for leaf_idx in range(leaves_in_subtree.shape[0]):
-
        __pyx_t_11 = (__pyx_v_leaves_in_subtree.shape[0]);
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-
+1469:             if not leaves_in_subtree[leaf_idx]:
-
          __pyx_t_13 = __pyx_v_leaf_idx;
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-/* … */
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+1470:                 continue
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+1471:             r_branch[leaf_idx] = r_node[leaf_idx]
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          __pyx_t_13 = __pyx_v_leaf_idx;
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-
 1472:
-
 1473:             # bubble up values to ancestor nodes
-
+1474:             current_r = r_node[leaf_idx]
-
          __pyx_t_13 = __pyx_v_leaf_idx;
-          __pyx_v_current_r = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) )));
-
+1475:             while leaf_idx != 0:
-
          while (1) {
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-
+1476:                 parent_idx = parent[leaf_idx]
-
            __pyx_t_13 = __pyx_v_leaf_idx;
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-
+1477:                 r_branch[parent_idx] += current_r
-
            __pyx_t_13 = __pyx_v_parent_idx;
-            *((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_13 * __pyx_v_r_branch.strides[0]) )) += __pyx_v_current_r;
-
+1478:                 n_leaves[parent_idx] += 1
-
            __pyx_t_13 = __pyx_v_parent_idx;
-            *((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_13 * __pyx_v_n_leaves.strides[0]) )) += 1;
-
+1479:                 leaf_idx = parent_idx
-
            __pyx_v_leaf_idx = __pyx_v_parent_idx;
-          }
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-
 1480:
-
+1481:         for i in range(leaves_in_subtree.shape[0]):
-
        __pyx_t_11 = (__pyx_v_leaves_in_subtree.shape[0]);
-        __pyx_t_12 = __pyx_t_11;
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-
+1482:             candidate_nodes[i] = not leaves_in_subtree[i]
-
          __pyx_t_13 = __pyx_v_i;
-          __pyx_t_4 = __pyx_v_i;
-          *((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_4 * __pyx_v_candidate_nodes.strides[0]) )) = (!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_13 * __pyx_v_leaves_in_subtree.strides[0]) ))) != 0));
-        }
-
 1483:
-
 1484:         # save metrics before pruning
-
+1485:         controller.save_metrics(0.0, r_branch[0])
-
        __pyx_t_13 = 0;
-        ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->save_metrics(__pyx_v_controller, 0.0, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_13 * __pyx_v_r_branch.strides[0]) ))));
-
 1486:
-
 1487:         # while root node is not a leaf
-
+1488:         while candidate_nodes[0]:
-
        while (1) {
-          __pyx_t_13 = 0;
-          __pyx_t_16 = ((*((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_13 * __pyx_v_candidate_nodes.strides[0]) ))) != 0);
-          if (!__pyx_t_16) break;
-
 1489:
-
 1490:             # computes ccp_alpha for subtrees and finds the minimal alpha
-
+1491:             effective_alpha = max_float64
-
          __pyx_v_effective_alpha = __pyx_v_max_float64;
-
+1492:             for i in range(n_nodes):
-
          __pyx_t_1 = __pyx_v_n_nodes;
-          __pyx_t_18 = __pyx_t_1;
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-            __pyx_v_i = __pyx_t_19;
-
+1493:                 if not candidate_nodes[i]:
-
            __pyx_t_13 = __pyx_v_i;
-            __pyx_t_16 = ((!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_13 * __pyx_v_candidate_nodes.strides[0]) ))) != 0)) != 0);
-            if (__pyx_t_16) {
-/* … */
-            }
-
+1494:                     continue
-
              goto __pyx_L36_continue;
-
+1495:                 subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1)
-
            __pyx_t_13 = __pyx_v_i;
-            __pyx_t_4 = __pyx_v_i;
-            __pyx_t_14 = __pyx_v_i;
-            __pyx_v_subtree_alpha = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))) - (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )))) / ((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) ))) - 1));
-
+1496:                 if subtree_alpha < effective_alpha:
-
            __pyx_t_16 = ((__pyx_v_subtree_alpha < __pyx_v_effective_alpha) != 0);
-            if (__pyx_t_16) {
-/* … */
-            }
-            __pyx_L36_continue:;
-          }
-
+1497:                     effective_alpha = subtree_alpha
-
              __pyx_v_effective_alpha = __pyx_v_subtree_alpha;
-
+1498:                     pruned_branch_node_idx = i
-
              __pyx_v_pruned_branch_node_idx = __pyx_v_i;
-
 1499:
-
+1500:             if controller.stop_pruning(effective_alpha):
-
          __pyx_t_16 = (((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->stop_pruning(__pyx_v_controller, __pyx_v_effective_alpha) != 0);
-          if (__pyx_t_16) {
-/* … */
-          }
-
+1501:                 break
-
            goto __pyx_L35_break;
-
 1502:
-
 1503:             # stack uses only the start variable
-
+1504:             rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0)
-
          __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_pruned_branch_node_idx, 0, 0, 0, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1504, __pyx_L4_error)
-          __pyx_v_rc = __pyx_t_15;
-
+1505:             if rc == -1:
-
          __pyx_t_16 = ((__pyx_v_rc == -1L) != 0);
-          if (__pyx_t_16) {
-/* … */
-          }
-
+1506:                 with gil:
-
            {
-                #ifdef WITH_THREAD
-                PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
-                #endif
-                /*try:*/ {
-/* … */
-                /*finally:*/ {
-                  __pyx_L45_error: {
-                    #ifdef WITH_THREAD
-                    __Pyx_PyGILState_Release(__pyx_gilstate_save);
-                    #endif
-                    goto __pyx_L4_error;
-                  }
-                }
-            }
-
+1507:                     raise MemoryError("pruning tree")
-
                  __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_MemoryError, __pyx_tuple__16, NULL); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1507, __pyx_L45_error)
-                  __Pyx_GOTREF(__pyx_t_6);
-                  __Pyx_Raise(__pyx_t_6, 0, 0, 0);
-                  __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
-                  __PYX_ERR(0, 1507, __pyx_L45_error)
-                }
-
 1508:
-
 1509:             # descendants of branch are not in subtree
-
+1510:             while not stack.is_empty():
-
          while (1) {
-            __pyx_t_16 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0);
-            if (!__pyx_t_16) break;
-
+1511:                 stack.pop(&stack_record)
-
            (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record)));
-
+1512:                 node_idx = stack_record.start
-
            __pyx_t_17 = __pyx_v_stack_record.start;
-            __pyx_v_node_idx = __pyx_t_17;
-
 1513:
-
+1514:                 if not in_subtree[node_idx]:
-
            __pyx_t_14 = __pyx_v_node_idx;
-            __pyx_t_16 = ((!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_in_subtree.data + __pyx_t_14 * __pyx_v_in_subtree.strides[0]) ))) != 0)) != 0);
-            if (__pyx_t_16) {
-/* … */
-            }
-
+1515:                     continue # branch has already been marked for pruning
-
              goto __pyx_L47_continue;
-
+1516:                 candidate_nodes[node_idx] = 0
-
            __pyx_t_14 = __pyx_v_node_idx;
-            *((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_14 * __pyx_v_candidate_nodes.strides[0]) )) = 0;
-
+1517:                 leaves_in_subtree[node_idx] = 0
-
            __pyx_t_14 = __pyx_v_node_idx;
-            *((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_14 * __pyx_v_leaves_in_subtree.strides[0]) )) = 0;
-
+1518:                 in_subtree[node_idx] = 0
-
            __pyx_t_14 = __pyx_v_node_idx;
-            *((unsigned char *) ( /* dim=0 */ (__pyx_v_in_subtree.data + __pyx_t_14 * __pyx_v_in_subtree.strides[0]) )) = 0;
-
 1519:
-
+1520:                 if child_l[node_idx] != _TREE_LEAF:
-
            __pyx_t_14 = __pyx_v_node_idx;
-            __pyx_t_16 = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_14 * __pyx_v_child_l.strides[0]) ))) != __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF) != 0);
-            if (__pyx_t_16) {
-/* … */
-            }
-            __pyx_L47_continue:;
-          }
-
 1521:                     # ... and child_r[node_idx] != _TREE_LEAF:
-
+1522:                     rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0)
-
              __pyx_t_14 = __pyx_v_node_idx;
-              __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_14 * __pyx_v_child_l.strides[0]) ))), 0, 0, 0, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1522, __pyx_L4_error)
-              __pyx_v_rc = __pyx_t_15;
-
+1523:                     if rc == -1:
-
              __pyx_t_16 = ((__pyx_v_rc == -1L) != 0);
-              if (__pyx_t_16) {
-/* … */
-              }
-
+1524:                         with gil:
-
                {
-                    #ifdef WITH_THREAD
-                    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
-                    #endif
-                    /*try:*/ {
-/* … */
-                    /*finally:*/ {
-                      __pyx_L55_error: {
-                        #ifdef WITH_THREAD
-                        __Pyx_PyGILState_Release(__pyx_gilstate_save);
-                        #endif
-                        goto __pyx_L4_error;
-                      }
-                    }
-                }
-
+1525:                             raise MemoryError("pruning tree")
-
                      __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_MemoryError, __pyx_tuple__16, NULL); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1525, __pyx_L55_error)
-                      __Pyx_GOTREF(__pyx_t_6);
-                      __Pyx_Raise(__pyx_t_6, 0, 0, 0);
-                      __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
-                      __PYX_ERR(0, 1525, __pyx_L55_error)
-                    }
-
+1526:                     rc = stack.push(child_r[node_idx], 0, 0, 0, 0, 0, 0)
-
              __pyx_t_14 = __pyx_v_node_idx;
-              __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_r.data + __pyx_t_14 * __pyx_v_child_r.strides[0]) ))), 0, 0, 0, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1526, __pyx_L4_error)
-              __pyx_v_rc = __pyx_t_15;
-
+1527:                     if rc == -1:
-
              __pyx_t_16 = ((__pyx_v_rc == -1L) != 0);
-              if (__pyx_t_16) {
-/* … */
-              }
-
+1528:                         with gil:
-
                {
-                    #ifdef WITH_THREAD
-                    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
-                    #endif
-                    /*try:*/ {
-/* … */
-                    /*finally:*/ {
-                      __pyx_L61_error: {
-                        #ifdef WITH_THREAD
-                        __Pyx_PyGILState_Release(__pyx_gilstate_save);
-                        #endif
-                        goto __pyx_L4_error;
-                      }
-                    }
-                }
-
+1529:                             raise MemoryError("pruning tree")
-
                      __pyx_t_6 = __Pyx_PyObject_Call(__pyx_builtin_MemoryError, __pyx_tuple__16, NULL); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1529, __pyx_L61_error)
-                      __Pyx_GOTREF(__pyx_t_6);
-                      __Pyx_Raise(__pyx_t_6, 0, 0, 0);
-                      __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
-                      __PYX_ERR(0, 1529, __pyx_L61_error)
-                    }
-
+1530:             leaves_in_subtree[pruned_branch_node_idx] = 1
-
          __pyx_t_14 = __pyx_v_pruned_branch_node_idx;
-          *((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_14 * __pyx_v_leaves_in_subtree.strides[0]) )) = 1;
-
+1531:             in_subtree[pruned_branch_node_idx] = 1
-
          __pyx_t_14 = __pyx_v_pruned_branch_node_idx;
-          *((unsigned char *) ( /* dim=0 */ (__pyx_v_in_subtree.data + __pyx_t_14 * __pyx_v_in_subtree.strides[0]) )) = 1;
-
 1532:
-
 1533:             # updates number of leaves
-
+1534:             n_pruned_leaves = n_leaves[pruned_branch_node_idx] - 1
-
          __pyx_t_14 = __pyx_v_pruned_branch_node_idx;
-          __pyx_v_n_pruned_leaves = ((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) ))) - 1);
-
+1535:             n_leaves[pruned_branch_node_idx] = 0
-
          __pyx_t_14 = __pyx_v_pruned_branch_node_idx;
-          *((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) )) = 0;
-
 1536:
-
 1537:             # computes the increase in r_branch to bubble up
-
+1538:             r_diff = r_node[pruned_branch_node_idx] - r_branch[pruned_branch_node_idx]
-
          __pyx_t_14 = __pyx_v_pruned_branch_node_idx;
-          __pyx_t_4 = __pyx_v_pruned_branch_node_idx;
-          __pyx_v_r_diff = ((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_14 * __pyx_v_r_node.strides[0]) ))) - (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) ))));
-
+1539:             r_branch[pruned_branch_node_idx] = r_node[pruned_branch_node_idx]
-
          __pyx_t_4 = __pyx_v_pruned_branch_node_idx;
-          __pyx_t_14 = __pyx_v_pruned_branch_node_idx;
-          *((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_14 * __pyx_v_r_branch.strides[0]) )) = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_4 * __pyx_v_r_node.strides[0]) )));
-
 1540:
-
 1541:             # bubble up values to ancestors
-
+1542:             node_idx = parent[pruned_branch_node_idx]
-
          __pyx_t_4 = __pyx_v_pruned_branch_node_idx;
-          __pyx_v_node_idx = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_4 * __pyx_v_parent.strides[0]) )));
-
+1543:             while node_idx != -1:
-
          while (1) {
-            __pyx_t_16 = ((__pyx_v_node_idx != -1L) != 0);
-            if (!__pyx_t_16) break;
-
+1544:                 n_leaves[node_idx] -= n_pruned_leaves
-
            __pyx_t_4 = __pyx_v_node_idx;
-            *((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_4 * __pyx_v_n_leaves.strides[0]) )) -= __pyx_v_n_pruned_leaves;
-
+1545:                 r_branch[node_idx] += r_diff
-
            __pyx_t_4 = __pyx_v_node_idx;
-            *((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )) += __pyx_v_r_diff;
-
+1546:                 node_idx = parent[node_idx]
-
            __pyx_t_4 = __pyx_v_node_idx;
-            __pyx_v_node_idx = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_4 * __pyx_v_parent.strides[0]) )));
-          }
-
 1547:
-
+1548:             controller.save_metrics(effective_alpha, r_branch[0])
-
          __pyx_t_4 = 0;
-          ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->save_metrics(__pyx_v_controller, __pyx_v_effective_alpha, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) ))));
-        }
-        __pyx_L35_break:;
-
 1549:
-
+1550:         controller.after_pruning(in_subtree)
-
        ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->after_pruning(__pyx_v_controller, __pyx_v_in_subtree);
-      }
-
 1551:
-
 1552:
-
+1553: def _build_pruned_tree_ccp(
-
/* Python wrapper */
-static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_1_build_pruned_tree_ccp(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
-static char __pyx_doc_13stpredictions_6models_3OK3_5_tree__build_pruned_tree_ccp[] = "Build a pruned tree from the original tree using cost complexity\n    pruning.\n\n    The values and nodes from the original tree are copied into the pruned\n    tree.\n\n    Parameters\n    ----------\n    tree : Tree\n        Location to place the pruned tree\n    orig_tree : Tree\n        Original tree\n    ccp_alpha : positive double\n        Complexity parameter. The subtree with the largest cost complexity\n        that is smaller than ``ccp_alpha`` will be chosen. By default,\n        no pruning is performed.\n    ";
-static PyMethodDef __pyx_mdef_13stpredictions_6models_3OK3_5_tree_1_build_pruned_tree_ccp = {"_build_pruned_tree_ccp", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_13stpredictions_6models_3OK3_5_tree_1_build_pruned_tree_ccp, METH_VARARGS|METH_KEYWORDS, __pyx_doc_13stpredictions_6models_3OK3_5_tree__build_pruned_tree_ccp};
-static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_1_build_pruned_tree_ccp(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
-  struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree = 0;
-  struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_orig_tree = 0;
-  __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_ccp_alpha;
-  PyObject *__pyx_r = 0;
-  __Pyx_RefNannyDeclarations
-  __Pyx_RefNannySetupContext("_build_pruned_tree_ccp (wrapper)", 0);
-  {
-    static PyObject **__pyx_pyargnames[] = {&__pyx_n_s_tree,&__pyx_n_s_orig_tree,&__pyx_n_s_ccp_alpha,0};
-    PyObject* values[3] = {0,0,0};
-    if (unlikely(__pyx_kwds)) {
-      Py_ssize_t kw_args;
-      const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
-      switch (pos_args) {
-        case  3: values[2] = PyTuple_GET_ITEM(__pyx_args, 2);
-        CYTHON_FALLTHROUGH;
-        case  2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
-        CYTHON_FALLTHROUGH;
-        case  1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
-        CYTHON_FALLTHROUGH;
-        case  0: break;
-        default: goto __pyx_L5_argtuple_error;
-      }
-      kw_args = PyDict_Size(__pyx_kwds);
-      switch (pos_args) {
-        case  0:
-        if (likely((values[0] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_tree)) != 0)) kw_args--;
-        else goto __pyx_L5_argtuple_error;
-        CYTHON_FALLTHROUGH;
-        case  1:
-        if (likely((values[1] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_orig_tree)) != 0)) kw_args--;
-        else {
-          __Pyx_RaiseArgtupleInvalid("_build_pruned_tree_ccp", 1, 3, 3, 1); __PYX_ERR(0, 1553, __pyx_L3_error)
-        }
-        CYTHON_FALLTHROUGH;
-        case  2:
-        if (likely((values[2] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_ccp_alpha)) != 0)) kw_args--;
-        else {
-          __Pyx_RaiseArgtupleInvalid("_build_pruned_tree_ccp", 1, 3, 3, 2); __PYX_ERR(0, 1553, __pyx_L3_error)
-        }
-      }
-      if (unlikely(kw_args > 0)) {
-        if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "_build_pruned_tree_ccp") < 0)) __PYX_ERR(0, 1553, __pyx_L3_error)
-      }
-    } else if (PyTuple_GET_SIZE(__pyx_args) != 3) {
-      goto __pyx_L5_argtuple_error;
-    } else {
-      values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
-      values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
-      values[2] = PyTuple_GET_ITEM(__pyx_args, 2);
-    }
-    __pyx_v_tree = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)values[0]);
-    __pyx_v_orig_tree = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)values[1]);
-    __pyx_v_ccp_alpha = __pyx_PyFloat_AsDouble(values[2]); if (unlikely((__pyx_v_ccp_alpha == ((npy_float64)-1)) && PyErr_Occurred())) __PYX_ERR(0, 1556, __pyx_L3_error)
-  }
-  goto __pyx_L4_argument_unpacking_done;
-  __pyx_L5_argtuple_error:;
-  __Pyx_RaiseArgtupleInvalid("_build_pruned_tree_ccp", 1, 3, 3, PyTuple_GET_SIZE(__pyx_args)); __PYX_ERR(0, 1553, __pyx_L3_error)
-  __pyx_L3_error:;
-  __Pyx_AddTraceback("stpredictions.models.OK3._tree._build_pruned_tree_ccp", __pyx_clineno, __pyx_lineno, __pyx_filename);
-  __Pyx_RefNannyFinishContext();
-  return NULL;
-  __pyx_L4_argument_unpacking_done:;
-  if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_tree), __pyx_ptype_13stpredictions_6models_3OK3_5_tree_Tree, 1, "tree", 0))) __PYX_ERR(0, 1554, __pyx_L1_error)
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-
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 1630:
-
 1631:
-
+1632: cdef _build_pruned_tree(
-
static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree__build_pruned_tree(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_orig_tree, __Pyx_memviewslice __pyx_v_leaves_in_subtree, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_capacity) {
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 1633:     Tree tree, # OUT
-
 1634:     Tree orig_tree,
-
 1635:     const unsigned char[:] leaves_in_subtree,
-
 1636:     SIZE_t capacity):
-
 1637:     """Build a pruned tree.
-
 1638:
-
 1639:     Build a pruned tree from the original tree by transforming the nodes in
-
 1640:     ``leaves_in_subtree`` into leaves.
-
 1641:
-
 1642:     Parameters
-
 1643:     ----------
-
 1644:     tree : Tree
-
 1645:         Location to place the pruned tree
-
 1646:     orig_tree : Tree
-
 1647:         Original tree
-
 1648:     leaves_in_subtree : unsigned char memoryview, shape=(node_count, )
-
 1649:         Boolean mask for leaves to include in subtree
-
 1650:     capacity : SIZE_t
-
 1651:         Number of nodes to initially allocate in pruned tree
-
 1652:     """
-
+1653:     tree._resize(capacity)
-
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-
 1655:     cdef:
-
 1656:         SIZE_t orig_node_id
-
 1657:         SIZE_t new_node_id
-
 1658:         SIZE_t depth
-
 1659:         SIZE_t parent
-
 1660:         bint is_left
-
 1661:         bint is_leaf
-
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-
+1663:         SIZE_t max_depth_seen = -1
-
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-
+1664:         int rc = 0
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  __pyx_v_rc = 0;
-
 1665:         Node* node
-
 1666:         double* orig_value_ptr
-
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-
 1669:         # Only uses the start, depth, parent, and is_left variables
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-  __pyx_t_3 = 0;
-
 1671:         StackRecord stack_record
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-
+1673:     with nogil:
-
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-
 1674:         # push root node onto stack
-
+1675:         rc = stack.push(0, 0, 0, _TREE_UNDEFINED, 0, 0.0, 0)
-
        __pyx_t_1 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, 0, 0, 0, __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED, 0, 0.0, 0); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 1675, __pyx_L4_error)
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-
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+1677:             with gil:
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-
+1678:                 raise MemoryError("pruning tree")
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-
+1680:         while not stack.is_empty():
-
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-
+1681:             stack.pop(&stack_record)
-
          (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record)));
-
 1682:
-
+1683:             orig_node_id = stack_record.start
-
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-          __pyx_v_orig_node_id = __pyx_t_5;
-
+1684:             depth = stack_record.depth
-
          __pyx_t_5 = __pyx_v_stack_record.depth;
-          __pyx_v_depth = __pyx_t_5;
-
+1685:             parent = stack_record.parent
-
          __pyx_t_5 = __pyx_v_stack_record.parent;
-          __pyx_v_parent = __pyx_t_5;
-
+1686:             is_left = stack_record.is_left
-
          __pyx_t_4 = __pyx_v_stack_record.is_left;
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-
+1688:             is_leaf = leaves_in_subtree[orig_node_id]
-
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-
+1689:             node = &orig_tree.nodes[orig_node_id]
-
          __pyx_v_node = (&(__pyx_v_orig_tree->nodes[__pyx_v_orig_node_id]));
-
 1690:
-
+1691:             new_node_id = tree._add_node(
-
          __pyx_t_7 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_add_node(__pyx_v_tree, __pyx_v_parent, __pyx_v_is_left, __pyx_v_is_leaf, __pyx_v_node->feature, __pyx_v_node->threshold, __pyx_v_node->impurity, __pyx_v_node->n_node_samples, __pyx_v_node->weighted_n_node_samples); if (unlikely(__pyx_t_7 == ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)-1))) __PYX_ERR(0, 1691, __pyx_L4_error)
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-
 1692:                 parent, is_left, is_leaf, node.feature, node.threshold,
-
 1693:                 node.impurity, node.n_node_samples,
-
 1694:                 node.weighted_n_node_samples)
-
 1695:
-
+1696:             if new_node_id == SIZE_MAX:
-
          __pyx_t_4 = ((__pyx_v_new_node_id == SIZE_MAX) != 0);
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-/* … */
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-
+1697:                 rc = -1
-
            __pyx_v_rc = -1;
-
+1698:                 break
-
            goto __pyx_L11_break;
-
 1699:
-
 1700:             # copy value from original tree to new tree
-
+1701:             orig_value_ptr = orig_tree.value + tree.K_y.shape[0] * orig_node_id
-
          __pyx_v_orig_value_ptr = (__pyx_v_orig_tree->value + ((__pyx_v_tree->K_y->dimensions[0]) * __pyx_v_orig_node_id));
-
+1702:             new_value_ptr = tree.value + tree.K_y.shape[0] * new_node_id
-
          __pyx_v_new_value_ptr = (__pyx_v_tree->value + ((__pyx_v_tree->K_y->dimensions[0]) * __pyx_v_new_node_id));
-
+1703:             memcpy(new_value_ptr, orig_value_ptr, sizeof(double) * tree.K_y.shape[0])
-
          (void)(memcpy(__pyx_v_new_value_ptr, __pyx_v_orig_value_ptr, ((sizeof(double)) * (__pyx_v_tree->K_y->dimensions[0]))));
-
 1704:
-
+1705:             if not is_leaf:
-
          __pyx_t_4 = ((!(__pyx_v_is_leaf != 0)) != 0);
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-/* … */
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-
 1706:                 # Push right child on stack
-
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diff --git a/stpredictions/models/OK3/extra/_utils.pxd b/stpredictions/models/OK3/extra/_utils.pxd deleted file mode 100644 index b8f2b7151..000000000 --- a/stpredictions/models/OK3/extra/_utils.pxd +++ /dev/null @@ -1,110 +0,0 @@ -# Authors: Gilles Louppe -# Peter Prettenhofer -# Arnaud Joly -# Jacob Schreiber -# Nelson Liu -# -# License: BSD 3 clause - -# See _utils.pyx for details. - -cimport numpy as cnp -from ._tree cimport Node -from ..neighbors._quad_tree cimport Cell - -ctypedef cnp.npy_float32 DTYPE_t # Type of X -ctypedef cnp.npy_float64 DOUBLE_t # Type of y, sample_weight -ctypedef cnp.npy_intp SIZE_t # Type for indices and counters -ctypedef cnp.npy_int32 INT32_t # Signed 32 bit integer -ctypedef cnp.npy_uint32 UINT32_t # Unsigned 32 bit integer - - -cdef enum: - # Max value for our rand_r replacement (near the bottom). - # We don't use RAND_MAX because it's different across platforms and - # particularly tiny on Windows/MSVC. - RAND_R_MAX = 0x7FFFFFFF - - -# safe_realloc(&p, n) resizes the allocation of p to n * sizeof(*p) bytes or -# raises a MemoryError. It never calls free, since that's __dealloc__'s job. -# cdef DTYPE_t *p = NULL -# safe_realloc(&p, n) -# is equivalent to p = malloc(n * sizeof(*p)) with error checking. -ctypedef fused realloc_ptr: - # Add pointer types here as needed. - (DTYPE_t*) - (SIZE_t*) - (unsigned char*) - (WeightedPQueueRecord*) - (DOUBLE_t*) - (DOUBLE_t**) - (Node*) - (Cell*) - (Node**) - -cdef realloc_ptr safe_realloc(realloc_ptr* p, size_t nelems) except * nogil - - -cdef cnp.ndarray sizet_ptr_to_ndarray(SIZE_t* data, SIZE_t size) - - -cdef SIZE_t rand_int(SIZE_t low, SIZE_t high, - UINT32_t* random_state) noexcept nogil - - -cdef double rand_uniform(double low, double high, - UINT32_t* random_state) noexcept nogil - - -cdef double log(double x) noexcept nogil - -# ============================================================================= -# WeightedPQueue data structure -# ============================================================================= - -# A record stored in the WeightedPQueue -cdef struct WeightedPQueueRecord: - DOUBLE_t data - DOUBLE_t weight - -cdef class WeightedPQueue: - cdef SIZE_t capacity - cdef SIZE_t array_ptr - cdef WeightedPQueueRecord* array_ - - cdef bint is_empty(self) noexcept nogil - cdef int reset(self) except -1 nogil - cdef SIZE_t size(self) noexcept nogil - cdef int push(self, DOUBLE_t data, DOUBLE_t weight) except -1 nogil - cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) noexcept nogil - cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) noexcept nogil - cdef int peek(self, DOUBLE_t* data, DOUBLE_t* weight) noexcept nogil - cdef DOUBLE_t get_weight_from_index(self, SIZE_t index) noexcept nogil - cdef DOUBLE_t get_value_from_index(self, SIZE_t index) noexcept nogil - - -# ============================================================================= -# WeightedMedianCalculator data structure -# ============================================================================= - -cdef class WeightedMedianCalculator: - cdef SIZE_t initial_capacity - cdef WeightedPQueue samples - cdef DOUBLE_t total_weight - cdef SIZE_t k - cdef DOUBLE_t sum_w_0_k # represents sum(weights[0:k]) - # = w[0] + w[1] + ... + w[k-1] - - cdef SIZE_t size(self) noexcept nogil - cdef int push(self, DOUBLE_t data, DOUBLE_t weight) except -1 nogil - cdef int reset(self) except -1 nogil - cdef int update_median_parameters_post_push( - self, DOUBLE_t data, DOUBLE_t weight, - DOUBLE_t original_median) noexcept nogil - cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) noexcept nogil - cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) noexcept nogil - cdef int update_median_parameters_post_remove( - self, DOUBLE_t data, DOUBLE_t weight, - DOUBLE_t original_median) noexcept nogil - cdef DOUBLE_t get_median(self) noexcept nogil diff --git a/stpredictions/models/OK3/kernel.py b/stpredictions/models/OK3/kernel.py index ad8f14303..370e0537a 100644 --- a/stpredictions/models/OK3/kernel.py +++ b/stpredictions/models/OK3/kernel.py @@ -3,49 +3,58 @@ from sklearn.metrics.pairwise import pairwise_distances from abc import abstractmethod -__all__ = ["Kernel", - "Mean_Dirac_Kernel", - "Linear_Kernel", - "Gaussian_Kernel", - "Laplacian_Kernel", - "Gini_Kernel", +__all__ = ["Kernel", + "Mean_Dirac_Kernel", + "Linear_Kernel", + "Gaussian_Kernel", + "Laplacian_Kernel", + "Gini_Kernel", "MSE_Kernel"] - class Kernel: - + @abstractmethod def __init__(self, name): + self.name = name - + def evaluate(self, obj1, obj2): + pass def get_Gram_matrix(self, objects_1, objects_2=None): + pass - + def get_sq_norms(self, objects): + pass - + def get_name(self): + return self.name + ##### Kernel classes class Mean_Dirac_Kernel(Kernel): - + def __init__(self): + super().__init__(name="mean_dirac") - + def evaluate(self, y1, y2): - return np.sum(y1 == y2) / len(y1) - + + return np.sum(y1==y2) / len(y1) + def get_Gram_matrix(self, list_y_1, list_y_2=None): + return 1 - pairwise_distances(list_y_1, list_y_2, metric="hamming") - + def get_sq_norms(self, list_y): - return np.ones(len(list_y)) # = (y==y).mean() + + return np.ones(len(list_y)) # = (y==y).mean() class Gini_Kernel(Mean_Dirac_Kernel): @@ -53,25 +62,31 @@ class Gini_Kernel(Mean_Dirac_Kernel): Identique au 'Mean_Dirac_Kernel', mais permet de signaler que le décodage ne se fait pas parmi un candidates set mais est une recherche exhaustive. """ - + def __init__(self): + super().__init__() self.name = "gini_clf" + class Linear_Kernel(Kernel): - + def __init__(self): + super().__init__(name="linear") - + def evaluate(self, y1, y2): + return np.atleast_1d(y1) @ np.atleast_1d(y2) - + def get_Gram_matrix(self, list_y_1, list_y_2=None): + return pairwise_kernels(list_y_1, list_y_2, metric="linear") def get_sq_norms(self, list_y): - return np.sum(list_y ** 2, axis=1) + + return np.sum(list_y**2, axis=1) class MSE_Kernel(Linear_Kernel): @@ -79,82 +94,99 @@ class MSE_Kernel(Linear_Kernel): Identique au 'Linear_Kernel', mais permet de signaler que le décodage ne se fait pas parmi un candidates set mais est une solution exacte. """ - + def __init__(self): + super().__init__() self.name = "mse_reg" + class Laplacian_Kernel(Kernel): def __init__(self, gamma=1): + name = "laplacian" if gamma != 1: name += "_" + str(gamma) super().__init__(name=name) self.gamma = gamma - + def evaluate(self, y1, y2): + return np.exp(-self.gamma * np.sum(np.abs(y1 - y2))) - + def get_Gram_matrix(self, list_y_1, list_y_2=None): + return pairwise_kernels(list_y_1, list_y_2, metric="laplacian", gamma=self.gamma) def get_sq_norms(self, list_y): - return np.ones(len(list_y)) # = exp(-gamma*0) + + return np.ones(len(list_y)) # = exp(-gamma*0) + class Gaussian_Kernel(Kernel): def __init__(self, gamma=1): + name = "gaussian" if gamma != 1: name += "_" + str(gamma) super().__init__(name=name) self.gamma = gamma - + def evaluate(self, y1, y2): - return np.exp(- self.gamma * np.sum((y1 - y2) ** 2)) - + + return np.exp(- self.gamma * np.sum((y1 - y2)**2)) + def get_Gram_matrix(self, list_y_1, list_y_2=None): + return pairwise_kernels(list_y_1, list_y_2, metric="rbf", gamma=self.gamma) def get_sq_norms(self, list_y): - return np.ones(len(list_y)) # = exp(-gamma*0) + + return np.ones(len(list_y)) # = exp(-gamma*0) + # Attention, noyau calculé naïvement : pas optimisé. - + # kernel for permutations # les permutations sigma de Sn sont représentées par des vecteurs y de # même taille n où y[i] = p <=> sigma(i) = p class Mallows_Kernel(Kernel): def __init__(self, gamma=1): - + name = "mallows" if gamma != 1: name += "_" + str(gamma) super().__init__(name=name) self.gamma = gamma - + def evaluate(self, y1, y2): - + kendall_tau_dist = 0 - for i in range(len(y1) - 1): - for j in range(i + 1, len(y1)): + for i in range(len(y1)-1): + for j in range(i+1, len(y1)): + kendall_tau_dist += ((y1[i] < y1[j]) and (y2[i] > y2[j])) + ((y1[i] > y1[j]) and (y2[i] < y2[j])) - + return np.exp(-self.gamma * kendall_tau_dist) - + def get_Gram_matrix(self, list_y_1, list_y_2=None): - + K = np.zeros((len(list_y_1), len(list_y_2)), dtype=np.double) for i in range(len(list_y_1)): for j in range(i, len(list_y_2)): - K[i, j] = self.evaluate(list_y_1[i], list_y_2[j]) + K[i,j] = self.evaluate(list_y_1[i], list_y_2[j]) return K def get_sq_norms(self, list_y): + + return np.ones(len(list_y)) # = exp(-gamma*0) + + + - return np.ones(len(list_y)) # = exp(-gamma*0) diff --git a/stpredictions/models/OK3/setup.py b/stpredictions/models/OK3/setup.py new file mode 100644 index 000000000..0fdb98c1f --- /dev/null +++ b/stpredictions/models/OK3/setup.py @@ -0,0 +1,42 @@ +import setuptools +from distutils.core import Extension, setup +from Cython.Build import cythonize + +setup(ext_modules=cythonize(["_tree.pyx", "_splitter.pyx", "_criterion.pyx"], language_level = "3")) + +""" +import os + +import numpy +from numpy.distutils.misc_util import Configuration + + +def configuration(parent_package="", top_path=None): + config = Configuration("tree", parent_package, top_path) + libraries = [] + if os.name == 'posix': + libraries.append('m') + config.add_extension("_tree", + sources=["_tree.pyx"], + include_dirs=[numpy.get_include()], + libraries=libraries, + extra_compile_args=["-O3"]) + config.add_extension("_splitter", + sources=["_splitter.pyx"], + include_dirs=[numpy.get_include()], + libraries=libraries, + extra_compile_args=["-O3"]) + config.add_extension("_criterion", + sources=["_criterion.pyx"], + include_dirs=[numpy.get_include()], + libraries=libraries, + extra_compile_args=["-O3"]) + + #config.add_subpackage("tests") + + return config + +if __name__ == "__main__": + from numpy.distutils.core import setup + setup(**configuration().todict()) +""" diff --git a/stpredictions/models/OK3/structured_object.py b/stpredictions/models/OK3/structured_object.py index 6a70bf9e5..ddf0d43c2 100644 --- a/stpredictions/models/OK3/structured_object.py +++ b/stpredictions/models/OK3/structured_object.py @@ -1,21 +1,25 @@ -import numpy as np +import numpy as np class StructuredObject: - + def __init__(self): + self.index = 0 self.vectorial_representation = np.zeros(0) self.name = '' - + def is_equal_to(self, other): + if self.index == other.index or self.vectorial_representation == other.vectorial_representation: return True - + def similarity_with(self, other, kernel): + return kernel.evaluate(self, other) - + def get_name(self): + return self.name From dc27c401f7d8e9a86bddc18c16ec78e7df4f9e30 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 15:39:07 +0100 Subject: [PATCH 14/33] First commmit that makes code compitable with all version of python > 3.6 --- setup.py | 6 +- stpredictions/models/OK3/MANIFEST | 5 - stpredictions/models/OK3/README.md | 36 - stpredictions/models/OK3/__init__.py | 20 + stpredictions/models/OK3/_classes.py | 51 +- stpredictions/models/OK3/_criterion.c | 1916 +- stpredictions/models/OK3/_criterion.pxd | 10 +- stpredictions/models/OK3/_criterion.pyx | 8 +- stpredictions/models/OK3/_forest.py | 63 +- stpredictions/models/OK3/_quad_tree.c | 33532 +++++++++++++++++++ stpredictions/models/OK3/_quad_tree.pxd | 101 + stpredictions/models/OK3/_quad_tree.pyx | 610 + stpredictions/models/OK3/_random.c | 5002 +++ stpredictions/models/OK3/_random.pxd | 44 + stpredictions/models/OK3/_random.pyx | 316 + stpredictions/models/OK3/_splitter.c | 4550 ++- stpredictions/models/OK3/_splitter.pxd | 10 +- stpredictions/models/OK3/_splitter.pyx | 10 +- stpredictions/models/OK3/_tree.c | 6100 ++-- stpredictions/models/OK3/_tree.pyx | 12 +- stpredictions/models/OK3/_utils.c | 31010 +++++++++++++++++ stpredictions/models/OK3/_utils.pxd | 170 + stpredictions/models/OK3/_utils.pyx | 660 + stpredictions/models/OK3/setup.py | 42 - tests/tests_OK3/test_classification.py | 6 +- tests/tests_OK3/test_forest_clf_and_reg.py | 14 +- tests/tests_OK3/test_tree_clf_and_reg.py | 18 +- 27 files changed, 77509 insertions(+), 6813 deletions(-) delete mode 100644 stpredictions/models/OK3/MANIFEST delete mode 100644 stpredictions/models/OK3/README.md create mode 100644 stpredictions/models/OK3/__init__.py create mode 100644 stpredictions/models/OK3/_quad_tree.c create mode 100644 stpredictions/models/OK3/_quad_tree.pxd create mode 100644 stpredictions/models/OK3/_quad_tree.pyx create mode 100644 stpredictions/models/OK3/_random.c create mode 100644 stpredictions/models/OK3/_random.pxd create mode 100644 stpredictions/models/OK3/_random.pyx create mode 100644 stpredictions/models/OK3/_utils.c create mode 100644 stpredictions/models/OK3/_utils.pxd create mode 100644 stpredictions/models/OK3/_utils.pyx delete mode 100644 stpredictions/models/OK3/setup.py diff --git a/setup.py b/setup.py index 76f11fffd..766db33fb 100644 --- a/setup.py +++ b/setup.py @@ -87,10 +87,10 @@ scripts=[], data_files=[], setup_requires=["oldest-supported-numpy", "cython>=0.23"], - # install_requires=["numpy>=1.16", "scipy>=1.0", "scikit-learn", "torch", - # "liac-arff", "requests"], - install_requires=["numpy", "scipy", "scikit-learn==0.24.2", "torch", + install_requires=["numpy>=1.16", "scipy>=1.0", "scikit-learn", "torch", "liac-arff", "requests"], + # install_requires=["numpy", "scipy", "scikit-learn==0.24.2", "torch", + # "liac-arff", "requests"], python_requires=">=3.6", classifiers=[ 'Development Status :: 5 - Production/Stable', diff --git a/stpredictions/models/OK3/MANIFEST b/stpredictions/models/OK3/MANIFEST deleted file mode 100644 index 1d7f493e8..000000000 --- a/stpredictions/models/OK3/MANIFEST +++ /dev/null @@ -1,5 +0,0 @@ -# file GENERATED by distutils, do NOT edit -_criterion.c -_splitter.c -_tree.c -setup.py diff --git a/stpredictions/models/OK3/README.md b/stpredictions/models/OK3/README.md deleted file mode 100644 index 43d41d84d..000000000 --- a/stpredictions/models/OK3/README.md +++ /dev/null @@ -1,36 +0,0 @@ -# pythonOK3 -classes and methods to implement the OK3 method : decision trees with a kernelized output for structured prediction. - - -Afin de tester facilement OK3, j'ai fais en sorte qu'il puisse prendre en argument des matrices de vecteurs de sortie plutôt que uniquement des matrices de Gram, il construira ensuite en interne la matrice de Gram des sorties et la donnera au "vraies" méthodes fit et predict notamment. - - -Pour tester les arbres OK3 pour de la classification multilabel ou de la régression sur des données vectorielles (avec respectivement un critère d'impurté Gini et variance), une série de tests est rédigée dans le fichier tests/test_tree_clf_and_reg.py. - - - -Protocole : - - -1 - Cloner le projet 'pythonOK3' - - -2 - Dans son dossier cloné, exécuter dans un terminal : python setup.py build_ext --inplace - - Cela va compiler les différents fichiers Cython, et certainment lever plusieurs warnings (à ignorer) - - -3 - Eventuellement restart le kernel de la console iPython si l'on souhaite y travailler pour prendre en compte les chanements dans les fichiers compilés - - -4 - Pour lancer la batterie de tests, entrer dans un terminal : pytest tests/test_treeclf_and_reg.py - - Cela va lancer la totalité des tests de ce fichier, certains étant assez longs. (Durée totale inférieure à 11min) - Ces tests sont appliqués à des tâches de régression et de classification uniquement, il reste à tester sur des vrais problèmes structurés. - - -5 - Une autre manière de tester très rapidement ces fonctions de classification et régression et de comparer aux résultats obtenus avec les arbres de classification et régression classique est d'exécuter les fichiers test_classification et test_regression qui vont imprimer certaines lignes démontrant la quasi identité des arbres construits par OK3 et ceux classiques. - - -6 - Pour tester la prédiction structurée (différent de la régression et classification simple), voir le fichier tests.exemple_utilisation.py qui décrit comment utiliser les arbres ok3 (sur un problème de classification multilabel pouvant s'apparenter à un pb de prédiction structurée). - diff --git a/stpredictions/models/OK3/__init__.py b/stpredictions/models/OK3/__init__.py new file mode 100644 index 000000000..5d116c4c0 --- /dev/null +++ b/stpredictions/models/OK3/__init__.py @@ -0,0 +1,20 @@ +""" +The :mod:`sklearn.tree` module includes decision tree-based models for +classification and regression. +""" + +from ._classes import BaseKernelizedOutputTree +from ._classes import OK3Regressor +from ._classes import ExtraOK3Regressor +from ._forest import BaseOKForest +from ._forest import OKForestRegressor +from ._forest import RandomOKForestRegressor + +__all__ = [ + "BaseKernelizedOutputTree", + "OK3Regressor", + "ExtraOK3Regressor", + "BaseOKForest", + "OKForestRegressor", + "RandomOKForestRegressor", +] diff --git a/stpredictions/models/OK3/_classes.py b/stpredictions/models/OK3/_classes.py index 3b2a19037..5671ca394 100644 --- a/stpredictions/models/OK3/_classes.py +++ b/stpredictions/models/OK3/_classes.py @@ -22,7 +22,7 @@ from sklearn.base import BaseEstimator from sklearn.base import clone -from base import StructuredOutputMixin +from .base import StructuredOutputMixin from sklearn.utils import Bunch from sklearn.utils import check_array @@ -32,15 +32,19 @@ from sklearn.utils.validation import check_is_fitted from sklearn.utils.validation import _deprecate_positional_args -from _criterion import Criterion -from _splitter import Splitter -from kernel import Kernel -from _tree import DepthFirstTreeBuilder -from _tree import BestFirstTreeBuilder -from _tree import Tree -from _tree import _build_pruned_tree_ccp -from _tree import ccp_pruning_path -import _tree, _splitter, _criterion, kernel +from ._criterion import Criterion +from ._splitter import Splitter +from .kernel import Kernel +from ._tree import DepthFirstTreeBuilder +from ._tree import BestFirstTreeBuilder +from ._tree import Tree +from ._tree import _build_pruned_tree_ccp +from ._tree import ccp_pruning_path + +from ._tree import DTYPE, DOUBLE +from .kernel import Gini_Kernel, MSE_Kernel, Mean_Dirac_Kernel, Linear_Kernel, Laplacian_Kernel, Gaussian_Kernel +from ._criterion import KernelizedMSE +from ._splitter import BestSplitter, RandomSplitter, BestSparseSplitter, RandomSparseSplitter __all__ = ["OK3Regressor", "ExtraOK3Regressor"] @@ -49,12 +53,13 @@ # Types and constants # ============================================================================= -DTYPE = _tree.DTYPE -DOUBLE = _tree.DOUBLE +#DTYPE = _tree.DTYPE +#DOUBLE = _tree.DOUBLE # The criteria is the loss function (in the embedding Hilbert space) the tree # wants to minimise. Here we've implemented the classic variance reduction, called here "mse". -CRITERIA = {"mse": _criterion.KernelizedMSE} +#CRITERIA = {"mse": _criterion.KernelizedMSE} +CRITERIA = {"mse": KernelizedMSE} # This is the different types of kernels which can be used to compute similarities between vectorial representations of the outputs. # Each one of them corresponds to a different embedding in an Hilbert space. @@ -62,19 +67,19 @@ # to the "mean-dirac" kernel and the linear kernel but by specifying that we want # (for a classification or a regression task) to perform an exact search of the output # instead of an approximate minimisation of the criterion among alist of candidates. -KERNELS = {"gini_clf": kernel.Gini_Kernel, - "mse_reg": kernel.MSE_Kernel, - "mean_dirac": kernel.Mean_Dirac_Kernel, - "linear": kernel.Linear_Kernel, - "laplacian": kernel.Laplacian_Kernel, - "gaussian": kernel.Gaussian_Kernel} +KERNELS = {"gini_clf": Gini_Kernel, + "mse_reg": MSE_Kernel, + "mean_dirac": Mean_Dirac_Kernel, + "linear": Linear_Kernel, + "laplacian": Laplacian_Kernel, + "gaussian": Gaussian_Kernel} # Les splitters sont des classes définissant les stratégies de recherche des splits (feature+threshold) -DENSE_SPLITTERS = {"best": _splitter.BestSplitter, - "random": _splitter.RandomSplitter} +DENSE_SPLITTERS = {"best": BestSplitter, + "random": RandomSplitter} -SPARSE_SPLITTERS = {"best": _splitter.BestSparseSplitter, - "random": _splitter.RandomSparseSplitter} +SPARSE_SPLITTERS = {"best": BestSparseSplitter, + "random": RandomSparseSplitter} # ============================================================================= # Base decision tree diff --git a/stpredictions/models/OK3/_criterion.c b/stpredictions/models/OK3/_criterion.c index 2590e3fb6..7b5d6c7fe 100644 --- a/stpredictions/models/OK3/_criterion.c +++ b/stpredictions/models/OK3/_criterion.c @@ -4,8 +4,8 @@ { "distutils": { "depends": [ - "/home/asani/anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/core/include/numpy/arrayobject.h", - "/home/asani/anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/core/include/numpy/ufuncobject.h" + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include/numpy/arrayobject.h", + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include/numpy/ufuncobject.h" ], "extra_compile_args": [ "-O3", @@ -16,15 +16,15 @@ "-fopenmp" ], "include_dirs": [ - "/home/asani/anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/core/include", + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include", "/home/asani/Documents/Hi_Paris_Code_Projects/Florence/structured-predictions/stpredictions/models/OK3/test" ], - "name": "_criterion", + "name": "stpredictions.models.OK3._criterion", "sources": [ "stpredictions/models/OK3/_criterion.pyx" ] }, - "module_name": "_criterion" + "module_name": "stpredictions.models.OK3._criterion" } END: Cython Metadata */ @@ -632,8 +632,8 @@ static CYTHON_INLINE float __PYX_NAN() { #endif #endif -#define __PYX_HAVE___criterion -#define __PYX_HAVE_API___criterion +#define __PYX_HAVE__stpredictions__models__OK3___criterion +#define __PYX_HAVE_API__stpredictions__models__OK3___criterion /* Early includes */ #include #include @@ -880,11 +880,10 @@ static const char *__pyx_f[] = { "stpredictions/models/OK3/_criterion.pyx", "__init__.pxd", "type.pxd", - "_criterion.pxd", - "_splitter.pxd", - "_tree.pxd", - "_quad_tree.pxd", - "_utils.pxd", + "stpredictions/models/OK3/_splitter.pxd", + "stpredictions/models/OK3/_tree.pxd", + "stpredictions/models/OK3/_quad_tree.pxd", + "stpredictions/models/OK3/_utils.pxd", }; /* MemviewSliceStruct.proto */ struct __pyx_memoryview_obj; @@ -995,7 +994,7 @@ typedef struct { } __Pyx_BufFmt_Context; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":689 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":689 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -1004,7 +1003,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":690 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":690 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -1013,7 +1012,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":691 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":691 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -1022,7 +1021,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":692 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":692 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -1031,7 +1030,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":696 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":696 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -1040,7 +1039,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":697 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":697 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -1049,7 +1048,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":698 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":698 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -1058,7 +1057,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":699 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":699 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -1067,7 +1066,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":703 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":703 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -1076,7 +1075,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":704 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":704 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -1085,7 +1084,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":713 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":713 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -1094,7 +1093,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":714 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":714 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -1103,7 +1102,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":715 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":715 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -1112,7 +1111,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":717 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":717 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -1121,7 +1120,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":718 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":718 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -1130,7 +1129,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":719 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":719 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -1139,7 +1138,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":721 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":721 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -1148,7 +1147,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":722 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":722 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -1157,7 +1156,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":724 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":724 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -1166,7 +1165,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":725 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":725 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -1175,7 +1174,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":726 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":726 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -1184,131 +1183,131 @@ typedef npy_double __pyx_t_5numpy_double_t; */ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; -/* "sklearn/tree/_tree.pxd":16 +/* "_tree.pxd":7 * cimport numpy as np * * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters */ -typedef npy_float32 __pyx_t_7sklearn_4tree_5_tree_DTYPE_t; +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t; -/* "sklearn/tree/_tree.pxd":17 +/* "_tree.pxd":8 * * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer */ -typedef npy_float64 __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t; +typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t; -/* "sklearn/tree/_tree.pxd":18 +/* "_tree.pxd":9 * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer */ -typedef npy_intp __pyx_t_7sklearn_4tree_5_tree_SIZE_t; +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t; -/* "sklearn/tree/_tree.pxd":19 +/* "_tree.pxd":10 * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer * */ -typedef npy_int32 __pyx_t_7sklearn_4tree_5_tree_INT32_t; +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t; -/* "sklearn/tree/_tree.pxd":20 +/* "_tree.pxd":11 * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< * - * from ._splitter cimport Splitter + * from _splitter cimport Splitter */ -typedef npy_uint32 __pyx_t_7sklearn_4tree_5_tree_UINT32_t; +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t; -/* "neighbors/_quad_tree.pxd":13 +/* "_quad_tree.pxd":13 * cimport numpy as np * * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer */ -typedef npy_float32 __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t; +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t; -/* "neighbors/_quad_tree.pxd":14 +/* "_quad_tree.pxd":14 * * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer */ -typedef npy_intp __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t; +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t; -/* "neighbors/_quad_tree.pxd":15 +/* "_quad_tree.pxd":15 * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer * */ -typedef npy_int32 __pyx_t_7sklearn_9neighbors_10_quad_tree_INT32_t; +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_INT32_t; -/* "neighbors/_quad_tree.pxd":16 +/* "_quad_tree.pxd":16 * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< * * # This is effectively an ifdef statement in Cython */ -typedef npy_uint32 __pyx_t_7sklearn_9neighbors_10_quad_tree_UINT32_t; +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_UINT32_t; -/* "sklearn/tree/_utils.pxd":16 - * from ..neighbors._quad_tree cimport Cell +/* "_utils.pxd":16 + * from ._quad_tree cimport Cell * * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters */ -typedef npy_float32 __pyx_t_7sklearn_4tree_6_utils_DTYPE_t; +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t; -/* "sklearn/tree/_utils.pxd":17 +/* "_utils.pxd":17 * * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer */ -typedef npy_float64 __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t; +typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t; -/* "sklearn/tree/_utils.pxd":18 +/* "_utils.pxd":18 * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer */ -typedef npy_intp __pyx_t_7sklearn_4tree_6_utils_SIZE_t; +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t; -/* "sklearn/tree/_utils.pxd":19 +/* "_utils.pxd":19 * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer * */ -typedef npy_int32 __pyx_t_7sklearn_4tree_6_utils_INT32_t; +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_6_utils_INT32_t; -/* "sklearn/tree/_utils.pxd":20 +/* "_utils.pxd":20 * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< * * */ -typedef npy_uint32 __pyx_t_7sklearn_4tree_6_utils_UINT32_t; +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_6_utils_UINT32_t; /* Declarations.proto */ #if CYTHON_CCOMPLEX #ifdef __cplusplus @@ -1335,26 +1334,23 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do /*--- Type declarations ---*/ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion; -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter; -struct __pyx_obj_7sklearn_4tree_5_tree_Tree; -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder; -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree; -struct __pyx_obj_7sklearn_4tree_6_utils_Stack; -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator; -struct __pyx_obj_10_criterion_Criterion; -struct __pyx_obj_10_criterion_KernelizedRegressionCriterion; -struct __pyx_obj_10_criterion_KernelizedMSE; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder; +struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE; struct __pyx_array_obj; struct __pyx_MemviewEnum_obj; struct __pyx_memoryview_obj; struct __pyx_memoryviewslice_obj; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":728 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":728 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -1363,7 +1359,7 @@ struct __pyx_memoryviewslice_obj; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":729 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":729 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -1372,7 +1368,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":730 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":730 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -1381,7 +1377,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":732 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":732 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -1389,88 +1385,88 @@ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; * cdef inline object PyArray_MultiIterNew1(a): */ typedef npy_cdouble __pyx_t_5numpy_complex_t; -struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord; +struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord; -/* "_splitter.pxd":23 +/* "_splitter.pxd":14 * from ._tree cimport UINT32_t # Unsigned 32 bit integer * * cdef struct SplitRecord: # <<<<<<<<<<<<<< * # Data to track sample split * SIZE_t feature # Which feature to split on. */ -struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; +struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t pos; double threshold; double improvement; double impurity_left; double impurity_right; }; -struct __pyx_t_7sklearn_4tree_5_tree_Node; -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c; -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances; -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build; +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build; -/* "sklearn/tree/_tree.pxd":25 - * from ._splitter cimport SplitRecord +/* "_tree.pxd":16 + * from _splitter cimport SplitRecord * * cdef struct Node: # <<<<<<<<<<<<<< * # Base storage structure for the nodes in a Tree object * */ -struct __pyx_t_7sklearn_4tree_5_tree_Node { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t left_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t right_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t threshold; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t impurity; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t weighted_n_node_samples; +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t left_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t right_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t threshold; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t impurity; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t weighted_n_node_samples; }; -/* "sklearn/tree/_tree.pxd":63 +/* "_tree.pxd":52 * double weighted_n_samples) nogil except -1 * cdef int _resize(self, SIZE_t capacity) nogil except -1 * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< * * cdef np.ndarray _get_value_ndarray(self) */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c { int __pyx_n; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; }; -/* "sklearn/tree/_tree.pxd":78 +/* "_tree.pxd":68 * cdef object _decision_path_sparse_csr(self, object X) * * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< * * */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances { int __pyx_n; PyObject *normalize; }; -/* "sklearn/tree/_tree.pxd":102 +/* "_tree.pxd":92 * cdef double min_impurity_decrease # Impurity threshold for early stopping * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< * np.ndarray sample_weight=*) * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build { int __pyx_n; PyArrayObject *sample_weight; }; -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; - -/* "neighbors/_quad_tree.pxd":21 +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell; + +/* "_quad_tree.pxd":21 * # It allows us to write printf debugging lines * # and remove them at compile time * cdef enum: # <<<<<<<<<<<<<< @@ -1478,96 +1474,96 @@ struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; * */ enum { - __pyx_e_7sklearn_9neighbors_10_quad_tree_DEBUGFLAG = 0 + __pyx_e_13stpredictions_6models_3OK3_10_quad_tree_DEBUGFLAG = 0 }; -/* "neighbors/_quad_tree.pxd":29 +/* "_quad_tree.pxd":29 * # have is_leaf and max_width consecutive as it permits to avoid padding by * # the compiler and keep the size coherent for both C and numpy data structures. * cdef struct Cell: # <<<<<<<<<<<<<< * # Base storage structure for cells in a QuadTree object * */ -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell { - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t parent; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t children[8]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t point_index; +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell { + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t parent; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t children[8]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t point_index; int is_leaf; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t squared_max_width; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cumulative_size; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t center[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t barycenter[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t min_bounds[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t max_bounds[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t squared_max_width; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t depth; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cumulative_size; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t center[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t barycenter[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t min_bounds[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t max_bounds[3]; }; -/* "neighbors/_quad_tree.pxd":75 +/* "_quad_tree.pxd":75 * * # Point insertion methods * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< * SIZE_t cell_id=*) nogil except -1 * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; }; -/* "neighbors/_quad_tree.pxd":77 +/* "_quad_tree.pxd":77 * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, * SIZE_t cell_id=*) nogil except -1 * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< * SIZE_t point_index, SIZE_t size=* * ) nogil */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t size; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t size; }; -/* "neighbors/_quad_tree.pxd":84 +/* "_quad_tree.pxd":84 * * # Create a summary of the Tree compare to a query point * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< * float squared_theta=*, SIZE_t cell_id=*, long idx=* * ) nogil */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize { int __pyx_n; float squared_theta; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; long idx; }; -/* "neighbors/_quad_tree.pxd":99 +/* "_quad_tree.pxd":99 * # Private array manipulation to manage the ``cells`` array * cdef int _resize(self, SIZE_t capacity) nogil except -1 * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 * cdef np.ndarray _get_cell_ndarray(self) */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t capacity; }; -/* "neighbors/_quad_tree.pxd":100 +/* "_quad_tree.pxd":100 * cdef int _resize(self, SIZE_t capacity) nogil except -1 * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< * cdef np.ndarray _get_cell_ndarray(self) */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; }; -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord; -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord; -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord; -/* "sklearn/tree/_utils.pxd":23 +/* "_utils.pxd":23 * * * cdef enum: # <<<<<<<<<<<<<< @@ -1575,39 +1571,39 @@ struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; * # We don't use RAND_MAX because it's different across platforms and */ enum { - __pyx_e_7sklearn_4tree_6_utils_RAND_R_MAX = 0x7FFFFFFF + __pyx_e_13stpredictions_6models_3OK3_6_utils_RAND_R_MAX = 0x7FFFFFFF }; -/* "sklearn/tree/_utils.pxd":70 +/* "_utils.pxd":70 * * # A record on the stack for depth-first tree growing * cdef struct StackRecord: # <<<<<<<<<<<<<< * SIZE_t start * SIZE_t end */ -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t parent; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t depth; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t parent; int is_left; double impurity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t n_constant_features; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t n_constant_features; }; -/* "sklearn/tree/_utils.pxd":96 +/* "_utils.pxd":96 * * # A record on the frontier for best-first tree growing * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< * SIZE_t node_id * SIZE_t start */ -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t node_id; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t pos; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t node_id; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t pos; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t depth; int is_leaf; double impurity; double impurity_left; @@ -1615,252 +1611,194 @@ struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { double improvement; }; -/* "sklearn/tree/_utils.pxd":127 +/* "_utils.pxd":127 * * # A record stored in the WeightedPQueue * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< * DOUBLE_t data * DOUBLE_t weight */ -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord { - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t data; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t weight; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t data; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t weight; }; -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtab; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - double weighted_n_samples; - double weighted_n_node_samples; - double weighted_n_left; - double weighted_n_right; - double *sum_total; - double *sum_left; - double *sum_right; -}; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t sum_stride; -}; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - double sq_sum_total; -}; - - -/* "_splitter.pxd":34 +/* "_splitter.pxd":25 * double impurity_right # Impurity of the right split. * * cdef class Splitter: # <<<<<<<<<<<<<< * # The splitter searches in the input space for a feature and a threshold * # to split the samples samples[start:end]. */ -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter { +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *criterion; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtab; + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *criterion; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; double min_weight_leaf; PyObject *random_state; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t rand_r_state; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_samples; double weighted_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *constant_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *feature_values; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t end; __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *sample_weight; }; -/* "sklearn/tree/_tree.pxd":37 +/* "_tree.pxd":28 * * * cdef class Tree: # <<<<<<<<<<<<<< * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and + * # TreeBuilder. */ -struct __pyx_obj_7sklearn_4tree_5_tree_Tree { +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtab; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t node_count; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; - struct __pyx_t_7sklearn_4tree_5_tree_Node *nodes; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t node_count; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; + PyArrayObject *K_y; + PyArrayObject *y; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *nodes; double *value; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t value_stride; }; -/* "sklearn/tree/_tree.pxd":85 +/* "_tree.pxd":75 * # ============================================================================= * * cdef class TreeBuilder: # <<<<<<<<<<<<<< * # The TreeBuilder recursively builds a Tree object from training samples, * # using a Splitter object for splitting internal nodes and assigning */ -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder { +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *splitter; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_split; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtab; + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *splitter; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_split; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; double min_weight_leaf; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; double min_impurity_split; double min_impurity_decrease; }; -/* "neighbors/_quad_tree.pxd":55 +/* "_quad_tree.pxd":55 * * * cdef class _QuadTree: # <<<<<<<<<<<<<< * # The QuadTree object is a quad tree structure constructed by inserting * # recursively points in the tree and splitting cells in 4 so that each */ -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree { +struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtab; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_vtab; int n_dimensions; int verbose; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_cells_per_cell; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t max_depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_count; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_points; - struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *cells; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t n_cells_per_cell; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_count; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t n_points; + struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *cells; }; -/* "sklearn/tree/_utils.pxd":79 +/* "_utils.pxd":79 * SIZE_t n_constant_features * * cdef class Stack: # <<<<<<<<<<<<<< * cdef SIZE_t capacity * cdef SIZE_t top */ -struct __pyx_obj_7sklearn_4tree_6_utils_Stack { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t top; - struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *stack_; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t top; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *stack_; }; -/* "sklearn/tree/_utils.pxd":108 +/* "_utils.pxd":108 * double improvement * * cdef class PriorityHeap: # <<<<<<<<<<<<<< * cdef SIZE_t capacity * cdef SIZE_t heap_ptr */ -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t heap_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *heap_; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t heap_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *heap_; }; -/* "sklearn/tree/_utils.pxd":131 +/* "_utils.pxd":131 * DOUBLE_t weight * * cdef class WeightedPQueue: # <<<<<<<<<<<<<< * cdef SIZE_t capacity * cdef SIZE_t array_ptr */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t array_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *array_; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t array_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *array_; }; -/* "sklearn/tree/_utils.pxd":151 +/* "_utils.pxd":151 * # ============================================================================= * * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< * cdef SIZE_t initial_capacity * cdef WeightedPQueue samples */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t initial_capacity; - struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *samples; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t total_weight; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t k; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t sum_w_0_k; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t initial_capacity; + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *samples; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t total_weight; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t k; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t sum_w_0_k; }; -/* "_criterion.pxd":12 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer +/* "stpredictions/models/OK3/_criterion.pxd":12 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer * * cdef class Criterion: # <<<<<<<<<<<<<< * # The criterion computes the impurity of a node and the reduction of * # impurity of a split on that node. */ -struct __pyx_obj_10_criterion_Criterion { +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion { PyObject_HEAD - struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtab; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtab; __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *sample_weight; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t pos; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; double weighted_n_samples; double weighted_n_node_samples; double weighted_n_left; @@ -1868,15 +1806,15 @@ struct __pyx_obj_10_criterion_Criterion { }; -/* "_criterion.pxd":50 +/* "stpredictions/models/OK3/_criterion.pxd":50 * * * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< * """Abstract kernelized output regression criterion.""" * */ -struct __pyx_obj_10_criterion_KernelizedRegressionCriterion { - struct __pyx_obj_10_criterion_Criterion __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; double sum_diag_Gramm; double sum_total_Gramm; double sum_diag_Gramm_left; @@ -1886,15 +1824,15 @@ struct __pyx_obj_10_criterion_KernelizedRegressionCriterion { }; -/* "_criterion.pyx":445 +/* "stpredictions/models/OK3/_criterion.pyx":445 * * * cdef class KernelizedMSE(KernelizedRegressionCriterion): # <<<<<<<<<<<<<< * """Mean squared error impurity criterion. * */ -struct __pyx_obj_10_criterion_KernelizedMSE { - struct __pyx_obj_10_criterion_KernelizedRegressionCriterion __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion __pyx_base; }; @@ -1976,57 +1914,7 @@ struct __pyx_memoryviewslice_obj { -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion { - int (*init)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double, double, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_Criterion; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_ClassificationCriterion; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_RegressionCriterion; - - -/* "_splitter.pxd":34 +/* "_splitter.pxd":25 * double impurity_right # Impurity of the right split. * * cdef class Splitter: # <<<<<<<<<<<<<< @@ -2034,43 +1922,44 @@ static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion * * # to split the samples samples[start:end]. */ -struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter { - int (*init)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); - int (*node_reset)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); - int (*node_split)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double, struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double *); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter { + int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *); + int (*node_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double *); + int (*node_split)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *); + void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double *); + double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtabptr_7sklearn_4tree_9_splitter_Splitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_Splitter; -/* "sklearn/tree/_tree.pxd":37 +/* "_tree.pxd":28 * * * cdef class Tree: # <<<<<<<<<<<<<< * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and - */ - -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double); - int (*_resize)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args); - PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*predict)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*apply)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*_apply_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*decision_path)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyObject *(*_decision_path_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*compute_feature_importances)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); + * # TreeBuilder. + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int, int, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double); + int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c *__pyx_optional_args); + PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); + PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); + PyArrayObject *(*decode_tree)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyArrayObject *, PyArrayObject *, PyObject *, PyObject *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int __pyx_skip_dispatch); + PyArrayObject *(*predict)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*apply)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*_apply_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*decision_path)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyObject *(*_decision_path_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*compute_feature_importances)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); }; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklearn_4tree_5_tree_Tree; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_Tree; -/* "sklearn/tree/_tree.pxd":85 +/* "_tree.pxd":75 * # ============================================================================= * * cdef class TreeBuilder: # <<<<<<<<<<<<<< @@ -2078,14 +1967,14 @@ static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklear * # using a Splitter object for splitting internal nodes and assigning */ -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder { - PyObject *(*build)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args); - PyObject *(*_check_input)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder { + PyObject *(*build)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build *__pyx_optional_args); + PyObject *(*_check_input)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_TreeBuilder; -/* "neighbors/_quad_tree.pxd":55 +/* "_quad_tree.pxd":55 * * * cdef class _QuadTree: # <<<<<<<<<<<<<< @@ -2093,24 +1982,24 @@ static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_ * # recursively points in the tree and splitting cells in 4 so that each */ -struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree { - int (*insert_point)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_is_duplicate)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - long (*summarize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); - void (*_init_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - void (*_init_root)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - int (*_check_point_in_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_resize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); - int (*_get_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); - PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree { + int (*insert_point)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *); + int (*_is_duplicate)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *); + long (*summarize)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); + void (*_init_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t); + void (*_init_root)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *); + int (*_check_point_in_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *); + int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); + int (*_get_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); + PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *); }; -static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtabptr_7sklearn_9neighbors_10_quad_tree__QuadTree; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_vtabptr_13stpredictions_6models_3OK3_10_quad_tree__QuadTree; -/* "sklearn/tree/_utils.pxd":79 +/* "_utils.pxd":79 * SIZE_t n_constant_features * * cdef class Stack: # <<<<<<<<<<<<<< @@ -2118,15 +2007,15 @@ static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx * cdef SIZE_t top */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, int, double, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7sklearn_4tree_6_utils_Stack; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_Stack; -/* "sklearn/tree/_utils.pxd":108 +/* "_utils.pxd":108 * double improvement * * cdef class PriorityHeap: # <<<<<<<<<<<<<< @@ -2134,17 +2023,17 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7skle * cdef SIZE_t heap_ptr */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); - void (*heapify_up)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - void (*heapify_down)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, double, double, double); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *); + void (*heapify_up)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + void (*heapify_down)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, int, double, double, double, double); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabptr_7sklearn_4tree_6_utils_PriorityHeap; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_PriorityHeap; -/* "sklearn/tree/_utils.pxd":131 +/* "_utils.pxd":131 * DOUBLE_t weight * * cdef class WeightedPQueue: # <<<<<<<<<<<<<< @@ -2152,21 +2041,21 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabpt * cdef SIZE_t array_ptr */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*peek)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*size)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + int (*peek)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedPQueue; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; -/* "sklearn/tree/_utils.pxd":151 +/* "_utils.pxd":151 * # ============================================================================= * * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< @@ -2174,20 +2063,20 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab * cdef WeightedPQueue samples */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*update_median_parameters_post_push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*update_median_parameters_post_remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*size)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); + int (*update_median_parameters_post_push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + int (*update_median_parameters_post_remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedMedianCalculator; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; -/* "_criterion.pyx":22 +/* "stpredictions/models/OK3/_criterion.pyx":22 * # from kernel import Kernel * * cdef class Criterion: # <<<<<<<<<<<<<< @@ -2195,21 +2084,21 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator * * */ -struct __pyx_vtabstruct_10_criterion_Criterion { - int (*init)(struct __pyx_obj_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion { + int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); }; -static struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtabptr_10_criterion_Criterion; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion; -/* "_criterion.pyx":209 +/* "stpredictions/models/OK3/_criterion.pyx":209 * * * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< @@ -2217,13 +2106,13 @@ static struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtabptr_10_criterio * */ -struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion { - struct __pyx_vtabstruct_10_criterion_Criterion __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; }; -static struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_10_criterion_KernelizedRegressionCriterion; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; -/* "_criterion.pyx":445 +/* "stpredictions/models/OK3/_criterion.pyx":445 * * * cdef class KernelizedMSE(KernelizedRegressionCriterion): # <<<<<<<<<<<<<< @@ -2231,10 +2120,10 @@ static struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion *__pyx * */ -struct __pyx_vtabstruct_10_criterion_KernelizedMSE { - struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion __pyx_base; }; -static struct __pyx_vtabstruct_10_criterion_KernelizedMSE *__pyx_vtabptr_10_criterion_KernelizedMSE; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE; /* "View.MemoryView":105 @@ -2993,25 +2882,25 @@ static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (** /* InitStrings.proto */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); -static int __pyx_f_10_criterion_9Criterion_init(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_y, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, CYTHON_UNUSED double __pyx_v_weighted_n_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end); /* proto*/ -static int __pyx_f_10_criterion_9Criterion_reset(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto*/ -static int __pyx_f_10_criterion_9Criterion_reverse_reset(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto*/ -static int __pyx_f_10_criterion_9Criterion_update(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos); /* proto*/ -static double __pyx_f_10_criterion_9Criterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto*/ -static void __pyx_f_10_criterion_9Criterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right); /* proto*/ -static void __pyx_f_10_criterion_9Criterion_node_value(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_dest); /* proto*/ -static double __pyx_f_10_criterion_9Criterion_proxy_impurity_improvement(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto*/ -static double __pyx_f_10_criterion_9Criterion_impurity_improvement(struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, double __pyx_v_impurity); /* proto*/ -static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, double __pyx_v_weighted_n_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end); /* proto*/ -static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ -static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ -static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos); /* proto*/ -static double __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ -static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right); /* proto*/ -static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, double *__pyx_v_dest); /* proto*/ -static double __pyx_f_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self); /* proto*/ -static double __pyx_f_10_criterion_13KernelizedMSE_proxy_impurity_improvement(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self); /* proto*/ -static void __pyx_f_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_init(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_y, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_sample_weight, CYTHON_UNUSED double __pyx_v_weighted_n_samples, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_reset(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_reverse_reset(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_update(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_new_pos); /* proto*/ +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_node_value(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_dest); /* proto*/ +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_proxy_impurity_improvement(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto*/ +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_impurity_improvement(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, double __pyx_v_impurity); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_init(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __Pyx_memviewslice __pyx_v_y, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_sample_weight, double __pyx_v_weighted_n_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_reset(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_reverse_reset(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_update(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_new_pos); /* proto*/ +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_node_value(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, double *__pyx_v_dest); /* proto*/ +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self); /* proto*/ +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_proxy_impurity_improvement(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right); /* proto*/ static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ @@ -3052,50 +2941,45 @@ static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ -/* Module declarations from 'sklearn.tree._criterion' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_Criterion = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_ClassificationCriterion = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_RegressionCriterion = 0; +/* Module declarations from 'stpredictions.models.OK3._splitter' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_Splitter = 0; -/* Module declarations from 'sklearn.tree._splitter' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_9_splitter_Splitter = 0; - -/* Module declarations from 'sklearn.tree._tree' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_Tree = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_TreeBuilder = 0; +/* Module declarations from 'stpredictions.models.OK3._tree' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree_Tree = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree_TreeBuilder = 0; /* Module declarations from 'libc.stdlib' */ /* Module declarations from 'libc.math' */ -/* Module declarations from 'sklearn.neighbors._quad_tree' */ -static PyTypeObject *__pyx_ptype_7sklearn_9neighbors_10_quad_tree__QuadTree = 0; -static float *__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON = 0; -#define __pyx_v_7sklearn_9neighbors_10_quad_tree_EPSILON (*__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON) - -/* Module declarations from 'sklearn.tree._utils' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_Stack = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_PriorityHeap = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedPQueue = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedMedianCalculator = 0; -static PyArrayObject *(*__pyx_f_7sklearn_4tree_6_utils_sizet_ptr_to_ndarray)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); /*proto*/ -static double (*__pyx_f_7sklearn_4tree_6_utils_log)(double); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DTYPE_t **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t **, size_t); /*proto*/ -static unsigned char *(*__pyx_fuse_2__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t ***, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_5_tree_Node *(*__pyx_fuse_6__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_5_tree_Node **(*__pyx_fuse_8__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node ***, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_StackRecord **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord **, size_t); /*proto*/ - -/* Module declarations from '_criterion' */ -static PyTypeObject *__pyx_ptype_10_criterion_Criterion = 0; -static PyTypeObject *__pyx_ptype_10_criterion_KernelizedRegressionCriterion = 0; -static PyTypeObject *__pyx_ptype_10_criterion_KernelizedMSE = 0; +/* Module declarations from 'stpredictions.models.OK3._quad_tree' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_quad_tree__QuadTree = 0; +static float *__pyx_vp_13stpredictions_6models_3OK3_10_quad_tree_EPSILON = 0; +#define __pyx_v_13stpredictions_6models_3OK3_10_quad_tree_EPSILON (*__pyx_vp_13stpredictions_6models_3OK3_10_quad_tree_EPSILON) + +/* Module declarations from 'stpredictions.models.OK3._utils' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_Stack = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_PriorityHeap = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_WeightedPQueue = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator = 0; +static PyArrayObject *(*__pyx_f_13stpredictions_6models_3OK3_6_utils_sizet_ptr_to_ndarray)(__pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); /*proto*/ +static double (*__pyx_f_13stpredictions_6models_3OK3_6_utils_log)(double); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t **, size_t); /*proto*/ +static unsigned char *(*__pyx_fuse_2__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t ***, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *(*__pyx_fuse_6__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node **(*__pyx_fuse_8__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node ***, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord **, size_t); /*proto*/ + +/* Module declarations from 'stpredictions.models.OK3._criterion' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_Criterion = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE = 0; static PyTypeObject *__pyx_array_type = 0; static PyTypeObject *__pyx_MemviewEnum_type = 0; static PyTypeObject *__pyx_memoryview_type = 0; @@ -3140,11 +3024,11 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ -#define __Pyx_MODULE_NAME "_criterion" -extern int __pyx_module_is_main__criterion; -int __pyx_module_is_main__criterion = 0; +#define __Pyx_MODULE_NAME "stpredictions.models.OK3._criterion" +extern int __pyx_module_is_main_stpredictions__models__OK3___criterion; +int __pyx_module_is_main_stpredictions__models__OK3___criterion = 0; -/* Implementation of '_criterion' */ +/* Implementation of 'stpredictions.models.OK3._criterion' */ static PyObject *__pyx_builtin_TypeError; static PyObject *__pyx_builtin_range; static PyObject *__pyx_builtin_ImportError; @@ -3344,13 +3228,13 @@ static PyObject *__pyx_kp_s_unable_to_allocate_array_data; static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; static PyObject *__pyx_n_s_unpack; static PyObject *__pyx_n_s_update; -static void __pyx_pf_10_criterion_9Criterion___dealloc__(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_10_criterion_9Criterion_2__getstate__(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_10_criterion_9Criterion_4__setstate__(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d); /* proto */ -static PyObject *__pyx_pf_10_criterion_9Criterion_6__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_10_criterion_9Criterion_8__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_pf_10_criterion_29KernelizedRegressionCriterion___cinit__(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_samples); /* proto */ -static PyObject *__pyx_pf_10_criterion_29KernelizedRegressionCriterion_2__reduce__(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto */ +static void __pyx_pf_13stpredictions_6models_3OK3_10_criterion_9Criterion___dealloc__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_9Criterion_2__getstate__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_9Criterion_4__setstate__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_9Criterion_6__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_9Criterion_8__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_samples); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_2__reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct 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*__pyx_pf_10_criterion_9Criterion_2__getstate__(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_9Criterion_2__getstate__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -3492,7 +3376,7 @@ static PyObject *__pyx_pf_10_criterion_9Criterion_2__getstate__(CYTHON_UNUSED st int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__getstate__", 0); - /* "_criterion.pyx":35 + /* "stpredictions/models/OK3/_criterion.pyx":35 * * def __getstate__(self): * return {} # <<<<<<<<<<<<<< @@ -3506,7 +3390,7 @@ static PyObject *__pyx_pf_10_criterion_9Criterion_2__getstate__(CYTHON_UNUSED st __pyx_t_1 = 0; goto __pyx_L0; - /* "_criterion.pyx":34 + /* "stpredictions/models/OK3/_criterion.pyx":34 * pass * * def __getstate__(self): # <<<<<<<<<<<<<< @@ -3517,7 +3401,7 @@ static PyObject *__pyx_pf_10_criterion_9Criterion_2__getstate__(CYTHON_UNUSED st /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_1); - __Pyx_AddTraceback("_criterion.Criterion.__getstate__", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._criterion.Criterion.__getstate__", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __Pyx_XGIVEREF(__pyx_r); @@ -3525,7 +3409,7 @@ static PyObject *__pyx_pf_10_criterion_9Criterion_2__getstate__(CYTHON_UNUSED st return __pyx_r; } -/* "_criterion.pyx":37 +/* "stpredictions/models/OK3/_criterion.pyx":37 * return {} * * def __setstate__(self, d): # <<<<<<<<<<<<<< @@ -3534,19 +3418,19 @@ static PyObject *__pyx_pf_10_criterion_9Criterion_2__getstate__(CYTHON_UNUSED st */ /* Python wrapper */ -static PyObject *__pyx_pw_10_criterion_9Criterion_5__setstate__(PyObject *__pyx_v_self, PyObject *__pyx_v_d); /*proto*/ -static PyObject *__pyx_pw_10_criterion_9Criterion_5__setstate__(PyObject *__pyx_v_self, PyObject *__pyx_v_d) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_10_criterion_9Criterion_5__setstate__(PyObject *__pyx_v_self, PyObject *__pyx_v_d); /*proto*/ +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_10_criterion_9Criterion_5__setstate__(PyObject *__pyx_v_self, PyObject *__pyx_v_d) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__setstate__ (wrapper)", 0); - __pyx_r = __pyx_pf_10_criterion_9Criterion_4__setstate__(((struct __pyx_obj_10_criterion_Criterion *)__pyx_v_self), ((PyObject *)__pyx_v_d)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_10_criterion_9Criterion_4__setstate__(((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self), ((PyObject *)__pyx_v_d)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_10_criterion_9Criterion_4__setstate__(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_9Criterion_4__setstate__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__setstate__", 0); @@ -3558,7 +3442,7 @@ static PyObject *__pyx_pf_10_criterion_9Criterion_4__setstate__(CYTHON_UNUSED st return __pyx_r; } -/* "_criterion.pyx":40 +/* "stpredictions/models/OK3/_criterion.pyx":40 * pass * * cdef int init(self, const DOUBLE_t[:, ::1] y, DOUBLE_t* sample_weight, # <<<<<<<<<<<<<< @@ -3566,7 +3450,7 @@ static PyObject *__pyx_pf_10_criterion_9Criterion_4__setstate__(CYTHON_UNUSED st * SIZE_t end) nogil except -1: */ -static int __pyx_f_10_criterion_9Criterion_init(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_y, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, CYTHON_UNUSED double __pyx_v_weighted_n_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end) { +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_init(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_y, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_sample_weight, CYTHON_UNUSED double __pyx_v_weighted_n_samples, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end) { int __pyx_r; /* function exit code */ @@ -3574,7 +3458,7 @@ static int __pyx_f_10_criterion_9Criterion_init(CYTHON_UNUSED struct __pyx_obj_1 return __pyx_r; } -/* "_criterion.pyx":68 +/* "stpredictions/models/OK3/_criterion.pyx":68 * pass * * cdef int reset(self) nogil except -1: # <<<<<<<<<<<<<< @@ -3582,7 +3466,7 @@ static int __pyx_f_10_criterion_9Criterion_init(CYTHON_UNUSED struct __pyx_obj_1 * */ -static int __pyx_f_10_criterion_9Criterion_reset(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self) { +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_reset(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self) { int __pyx_r; /* function exit code */ @@ -3590,7 +3474,7 @@ static int __pyx_f_10_criterion_9Criterion_reset(CYTHON_UNUSED struct __pyx_obj_ return __pyx_r; } -/* "_criterion.pyx":76 +/* "stpredictions/models/OK3/_criterion.pyx":76 * pass * * cdef int reverse_reset(self) nogil except -1: # <<<<<<<<<<<<<< @@ -3598,7 +3482,7 @@ static int __pyx_f_10_criterion_9Criterion_reset(CYTHON_UNUSED struct __pyx_obj_ * */ -static int __pyx_f_10_criterion_9Criterion_reverse_reset(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self) { +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_reverse_reset(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self) { int __pyx_r; /* function exit code */ @@ -3606,7 +3490,7 @@ static int __pyx_f_10_criterion_9Criterion_reverse_reset(CYTHON_UNUSED struct __ return __pyx_r; } -/* "_criterion.pyx":83 +/* "stpredictions/models/OK3/_criterion.pyx":83 * pass * * cdef int update(self, SIZE_t new_pos) nogil except -1: # <<<<<<<<<<<<<< @@ -3614,7 +3498,7 @@ static int __pyx_f_10_criterion_9Criterion_reverse_reset(CYTHON_UNUSED struct __ * */ -static int __pyx_f_10_criterion_9Criterion_update(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos) { +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_update(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_new_pos) { int __pyx_r; /* function exit code */ @@ -3622,7 +3506,7 @@ static int __pyx_f_10_criterion_9Criterion_update(CYTHON_UNUSED struct __pyx_obj return __pyx_r; } -/* "_criterion.pyx":98 +/* "stpredictions/models/OK3/_criterion.pyx":98 * pass * * cdef double node_impurity(self) nogil: # <<<<<<<<<<<<<< @@ -3630,7 +3514,7 @@ static int __pyx_f_10_criterion_9Criterion_update(CYTHON_UNUSED struct __pyx_obj * */ -static double __pyx_f_10_criterion_9Criterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self) { +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self) { double __pyx_r; /* function exit code */ @@ -3638,7 +3522,7 @@ static double __pyx_f_10_criterion_9Criterion_node_impurity(CYTHON_UNUSED struct return __pyx_r; } -/* "_criterion.pyx":108 +/* "stpredictions/models/OK3/_criterion.pyx":108 * pass * * cdef void children_impurity(self, double* impurity_left, # <<<<<<<<<<<<<< @@ -3646,12 +3530,12 @@ static double __pyx_f_10_criterion_9Criterion_node_impurity(CYTHON_UNUSED struct * """Placeholder for calculating the impurity of children. */ -static void __pyx_f_10_criterion_9Criterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) { +static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) { /* function exit code */ } -/* "_criterion.pyx":128 +/* "stpredictions/models/OK3/_criterion.pyx":128 * pass * * cdef void node_value(self, double* dest) nogil: # <<<<<<<<<<<<<< @@ -3659,12 +3543,12 @@ static void __pyx_f_10_criterion_9Criterion_children_impurity(CYTHON_UNUSED stru * */ -static void __pyx_f_10_criterion_9Criterion_node_value(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_dest) { +static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_node_value(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_dest) { /* function exit code */ } -/* "_criterion.pyx":142 +/* "stpredictions/models/OK3/_criterion.pyx":142 * pass * * cdef double proxy_impurity_improvement(self) nogil: # <<<<<<<<<<<<<< @@ -3672,7 +3556,7 @@ static void __pyx_f_10_criterion_9Criterion_node_value(CYTHON_UNUSED struct __py * */ -static double __pyx_f_10_criterion_9Criterion_proxy_impurity_improvement(CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_self) { +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_proxy_impurity_improvement(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_self) { double __pyx_r; /* function exit code */ @@ -3680,7 +3564,7 @@ static double __pyx_f_10_criterion_9Criterion_proxy_impurity_improvement(CYTHON_ return __pyx_r; } -/* "_criterion.pyx":162 +/* "stpredictions/models/OK3/_criterion.pyx":162 * pass * * cdef double impurity_improvement(self, double impurity) nogil: # <<<<<<<<<<<<<< @@ -3688,21 +3572,21 @@ static double __pyx_f_10_criterion_9Criterion_proxy_impurity_improvement(CYTHON_ * */ -static double __pyx_f_10_criterion_9Criterion_impurity_improvement(struct __pyx_obj_10_criterion_Criterion *__pyx_v_self, double __pyx_v_impurity) { +static double 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__pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_2__reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -4095,7 +3979,7 @@ static PyObject *__pyx_pf_10_criterion_29KernelizedRegressionCriterion_2__reduce int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__reduce__", 0); - /* "_criterion.pyx":252 + /* "stpredictions/models/OK3/_criterion.pyx":252 * * def __reduce__(self): * return (type(self), (self.n_samples,), self.__getstate__()) # <<<<<<<<<<<<<< @@ -4142,7 +4026,7 @@ static PyObject *__pyx_pf_10_criterion_29KernelizedRegressionCriterion_2__reduce __pyx_t_3 = 0; goto __pyx_L0; - /* "_criterion.pyx":251 + /* "stpredictions/models/OK3/_criterion.pyx":251 * * * def __reduce__(self): # <<<<<<<<<<<<<< @@ -4156,7 +4040,7 @@ 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__pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, double __pyx_v_weighted_n_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_q; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_i; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_j; +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_init(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __Pyx_memviewslice __pyx_v_y, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_sample_weight, double __pyx_v_weighted_n_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_i; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_j; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_q; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_w_i; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_w_j; int __pyx_r; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_3; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_3; int __pyx_t_4; Py_ssize_t __pyx_t_5; Py_ssize_t __pyx_t_6; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_8; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_9; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_7; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_8; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_9; int __pyx_t_10; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "_criterion.pyx":260 + /* "stpredictions/models/OK3/_criterion.pyx":260 * children samples[start:start] and samples[start:end].""" * # Initialize fields * self.y = y # <<<<<<<<<<<<<< @@ -4205,7 +4089,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py __PYX_INC_MEMVIEW(&__pyx_v_y, 1); __pyx_v_self->__pyx_base.y = __pyx_v_y; - /* "_criterion.pyx":261 + /* "stpredictions/models/OK3/_criterion.pyx":261 * # Initialize fields * self.y = y * self.sample_weight = sample_weight # <<<<<<<<<<<<<< @@ -4214,7 +4098,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->__pyx_base.sample_weight = __pyx_v_sample_weight; - /* "_criterion.pyx":262 + /* "stpredictions/models/OK3/_criterion.pyx":262 * self.y = y * self.sample_weight = sample_weight * self.samples = samples # <<<<<<<<<<<<<< @@ -4223,7 +4107,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->__pyx_base.samples = __pyx_v_samples; - /* "_criterion.pyx":263 + /* "stpredictions/models/OK3/_criterion.pyx":263 * self.sample_weight = sample_weight * self.samples = samples * self.start = start # <<<<<<<<<<<<<< @@ -4232,7 +4116,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->__pyx_base.start = __pyx_v_start; - /* "_criterion.pyx":264 + /* "stpredictions/models/OK3/_criterion.pyx":264 * self.samples = samples * self.start = start * self.end = end # <<<<<<<<<<<<<< @@ -4241,7 +4125,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->__pyx_base.end = __pyx_v_end; - /* "_criterion.pyx":265 + /* "stpredictions/models/OK3/_criterion.pyx":265 * self.start = start * self.end = end * self.n_node_samples = end - start # <<<<<<<<<<<<<< @@ -4250,7 +4134,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->__pyx_base.n_node_samples = (__pyx_v_end - __pyx_v_start); - /* "_criterion.pyx":266 + /* "stpredictions/models/OK3/_criterion.pyx":266 * self.end = end * self.n_node_samples = end - start * self.weighted_n_samples = weighted_n_samples # <<<<<<<<<<<<<< @@ -4259,7 +4143,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->__pyx_base.weighted_n_samples = __pyx_v_weighted_n_samples; - /* "_criterion.pyx":267 + /* "stpredictions/models/OK3/_criterion.pyx":267 * self.n_node_samples = end - start * self.weighted_n_samples = weighted_n_samples * self.weighted_n_node_samples = 0. # <<<<<<<<<<<<<< @@ -4268,7 +4152,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->__pyx_base.weighted_n_node_samples = 0.; - /* "_criterion.pyx":273 + /* "stpredictions/models/OK3/_criterion.pyx":273 * cdef SIZE_t p * cdef SIZE_t q * cdef DOUBLE_t w_i = 1.0 # <<<<<<<<<<<<<< @@ -4277,7 +4161,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_w_i = 1.0; - /* "_criterion.pyx":274 + /* "stpredictions/models/OK3/_criterion.pyx":274 * cdef SIZE_t q * cdef DOUBLE_t w_i = 1.0 * cdef DOUBLE_t w_j = 1.0 # <<<<<<<<<<<<<< @@ -4286,7 +4170,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_w_j = 1.0; - /* "_criterion.pyx":276 + /* "stpredictions/models/OK3/_criterion.pyx":276 * cdef DOUBLE_t w_j = 1.0 * * self.sum_diag_Gramm = 0.0 # <<<<<<<<<<<<<< @@ -4295,7 +4179,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->sum_diag_Gramm = 0.0; - /* "_criterion.pyx":277 + /* "stpredictions/models/OK3/_criterion.pyx":277 * * self.sum_diag_Gramm = 0.0 * self.sum_total_Gramm = 0.0 # <<<<<<<<<<<<<< @@ -4304,7 +4188,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->sum_total_Gramm = 0.0; - /* "_criterion.pyx":279 + /* "stpredictions/models/OK3/_criterion.pyx":279 * self.sum_total_Gramm = 0.0 * * self.sum_diag_Gramm_left = 0.0 # <<<<<<<<<<<<<< @@ -4313,7 +4197,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->sum_diag_Gramm_left = 0.0; - /* "_criterion.pyx":280 + /* "stpredictions/models/OK3/_criterion.pyx":280 * * self.sum_diag_Gramm_left = 0.0 * self.sum_diag_Gramm_right = 0.0 # <<<<<<<<<<<<<< @@ -4322,7 +4206,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->sum_diag_Gramm_right = 0.0; - /* "_criterion.pyx":282 + /* "stpredictions/models/OK3/_criterion.pyx":282 * self.sum_diag_Gramm_right = 0.0 * * self.sum_total_Gramm_left = 0.0 # <<<<<<<<<<<<<< @@ -4331,7 +4215,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->sum_total_Gramm_left = 0.0; - /* "_criterion.pyx":283 + /* "stpredictions/models/OK3/_criterion.pyx":283 * * self.sum_total_Gramm_left = 0.0 * self.sum_total_Gramm_right = 0.0 # <<<<<<<<<<<<<< @@ -4340,7 +4224,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->sum_total_Gramm_right = 0.0; - /* "_criterion.pyx":285 + /* "stpredictions/models/OK3/_criterion.pyx":285 * self.sum_total_Gramm_right = 0.0 * * for p in range(start, end): # <<<<<<<<<<<<<< @@ -4352,7 +4236,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py for (__pyx_t_3 = __pyx_v_start; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_p = __pyx_t_3; - /* "_criterion.pyx":286 + /* "stpredictions/models/OK3/_criterion.pyx":286 * * for p in range(start, end): * i = samples[p] # <<<<<<<<<<<<<< @@ -4361,7 +4245,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_i = (__pyx_v_samples[__pyx_v_p]); - /* "_criterion.pyx":290 + /* "stpredictions/models/OK3/_criterion.pyx":290 * # print("print samples :",i) * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -4371,7 +4255,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py __pyx_t_4 = ((__pyx_v_sample_weight != NULL) != 0); if (__pyx_t_4) { - /* "_criterion.pyx":291 + /* "stpredictions/models/OK3/_criterion.pyx":291 * * if sample_weight != NULL: * w_i = sample_weight[i] # <<<<<<<<<<<<<< @@ -4380,7 +4264,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_w_i = (__pyx_v_sample_weight[__pyx_v_i]); - /* "_criterion.pyx":290 + /* "stpredictions/models/OK3/_criterion.pyx":290 * # print("print samples :",i) * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -4389,7 +4273,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ } - /* "_criterion.pyx":293 + /* "stpredictions/models/OK3/_criterion.pyx":293 * w_i = sample_weight[i] * * self.weighted_n_node_samples += w_i # <<<<<<<<<<<<<< @@ -4398,7 +4282,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_self->__pyx_base.weighted_n_node_samples = (__pyx_v_self->__pyx_base.weighted_n_node_samples + __pyx_v_w_i); - /* "_criterion.pyx":295 + /* "stpredictions/models/OK3/_criterion.pyx":295 * self.weighted_n_node_samples += w_i * * self.sum_diag_Gramm += w_i * self.y[i,i] # <<<<<<<<<<<<<< @@ -4408,9 +4292,9 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 295, __pyx_L1_error)} __pyx_t_5 = __pyx_v_i; __pyx_t_6 = __pyx_v_i; - __pyx_v_self->sum_diag_Gramm = (__pyx_v_self->sum_diag_Gramm + (__pyx_v_w_i * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_5 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_6)) ))))); + __pyx_v_self->sum_diag_Gramm = (__pyx_v_self->sum_diag_Gramm + (__pyx_v_w_i * (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_5 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_6)) ))))); - /* "_criterion.pyx":297 + /* "stpredictions/models/OK3/_criterion.pyx":297 * self.sum_diag_Gramm += w_i * self.y[i,i] * * for q in range(start, end): # <<<<<<<<<<<<<< @@ -4422,7 +4306,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py for (__pyx_t_9 = __pyx_v_start; __pyx_t_9 < __pyx_t_8; __pyx_t_9+=1) { __pyx_v_q = __pyx_t_9; - /* "_criterion.pyx":298 + /* "stpredictions/models/OK3/_criterion.pyx":298 * * for q in range(start, end): * j = samples[q] # <<<<<<<<<<<<<< @@ -4431,7 +4315,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_j = (__pyx_v_samples[__pyx_v_q]); - /* "_criterion.pyx":300 + /* "stpredictions/models/OK3/_criterion.pyx":300 * j = samples[q] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -4441,7 +4325,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py __pyx_t_4 = ((__pyx_v_sample_weight != NULL) != 0); if (__pyx_t_4) { - /* "_criterion.pyx":301 + /* "stpredictions/models/OK3/_criterion.pyx":301 * * if sample_weight != NULL: * w_j = sample_weight[j] # <<<<<<<<<<<<<< @@ -4450,7 +4334,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]); - /* "_criterion.pyx":300 + /* "stpredictions/models/OK3/_criterion.pyx":300 * j = samples[q] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -4459,7 +4343,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py */ } - /* "_criterion.pyx":303 + /* "stpredictions/models/OK3/_criterion.pyx":303 * w_j = sample_weight[j] * * self.sum_total_Gramm += w_i * w_j * self.y[i,j] # <<<<<<<<<<<<<< @@ -4469,20 +4353,20 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 303, __pyx_L1_error)} __pyx_t_6 = __pyx_v_i; __pyx_t_5 = __pyx_v_j; - __pyx_v_self->sum_total_Gramm = (__pyx_v_self->sum_total_Gramm + ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_6 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_5)) ))))); + __pyx_v_self->sum_total_Gramm = (__pyx_v_self->sum_total_Gramm + ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_6 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_5)) ))))); } } - /* "_criterion.pyx":306 + /* "stpredictions/models/OK3/_criterion.pyx":306 * * # Reset to pos=start * self.reset() # <<<<<<<<<<<<<< * # with gil: * # print("print sum diag :",self.sum_diag_Gramm) */ - __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.reset(((struct __pyx_obj_10_criterion_Criterion *)__pyx_v_self)); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(1, 306, __pyx_L1_error) + __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.reset(((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self)); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(1, 306, __pyx_L1_error) - /* "_criterion.pyx":311 + /* "stpredictions/models/OK3/_criterion.pyx":311 * # print("print sum total :",self.sum_total_Gramm) * # print("print weighted_n_node_samples :",self.weighted_n_node_samples) * return 0 # <<<<<<<<<<<<<< @@ -4492,7 +4376,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py __pyx_r = 0; goto __pyx_L0; - /* "_criterion.pyx":254 + /* "stpredictions/models/OK3/_criterion.pyx":254 * return (type(self), (self.n_samples,), self.__getstate__()) * * cdef int init(self, const DOUBLE_t[:, ::1] y, DOUBLE_t* sample_weight, # <<<<<<<<<<<<<< @@ -4506,7 +4390,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif - __Pyx_AddTraceback("_criterion.KernelizedRegressionCriterion.init", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._criterion.KernelizedRegressionCriterion.init", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif @@ -4516,7 +4400,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py return __pyx_r; } -/* "_criterion.pyx":313 +/* "stpredictions/models/OK3/_criterion.pyx":313 * return 0 * * cdef int reset(self) nogil except -1: # <<<<<<<<<<<<<< @@ -4524,12 +4408,12 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_init(struct __py * */ -static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_reset(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { int __pyx_r; double __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_2; - /* "_criterion.pyx":316 + /* "stpredictions/models/OK3/_criterion.pyx":316 * """Reset the criterion at pos=start.""" * * self.sum_diag_Gramm_left = 0.0 # <<<<<<<<<<<<<< @@ -4538,7 +4422,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __p */ __pyx_v_self->sum_diag_Gramm_left = 0.0; - /* "_criterion.pyx":317 + /* "stpredictions/models/OK3/_criterion.pyx":317 * * self.sum_diag_Gramm_left = 0.0 * self.sum_diag_Gramm_right = self.sum_diag_Gramm # <<<<<<<<<<<<<< @@ -4548,7 +4432,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __p __pyx_t_1 = __pyx_v_self->sum_diag_Gramm; __pyx_v_self->sum_diag_Gramm_right = __pyx_t_1; - /* "_criterion.pyx":319 + /* "stpredictions/models/OK3/_criterion.pyx":319 * self.sum_diag_Gramm_right = self.sum_diag_Gramm * * self.sum_total_Gramm_left = 0.0 # <<<<<<<<<<<<<< @@ -4557,7 +4441,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __p */ __pyx_v_self->sum_total_Gramm_left = 0.0; - /* "_criterion.pyx":320 + /* "stpredictions/models/OK3/_criterion.pyx":320 * * self.sum_total_Gramm_left = 0.0 * self.sum_total_Gramm_right = self.sum_total_Gramm # <<<<<<<<<<<<<< @@ -4567,7 +4451,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __p __pyx_t_1 = __pyx_v_self->sum_total_Gramm; __pyx_v_self->sum_total_Gramm_right = __pyx_t_1; - /* "_criterion.pyx":322 + /* "stpredictions/models/OK3/_criterion.pyx":322 * self.sum_total_Gramm_right = self.sum_total_Gramm * * self.weighted_n_left = 0.0 # <<<<<<<<<<<<<< @@ -4576,7 +4460,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __p */ __pyx_v_self->__pyx_base.weighted_n_left = 0.0; - /* "_criterion.pyx":323 + /* "stpredictions/models/OK3/_criterion.pyx":323 * * self.weighted_n_left = 0.0 * self.weighted_n_right = self.weighted_n_node_samples # <<<<<<<<<<<<<< @@ -4586,7 +4470,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __p __pyx_t_1 = __pyx_v_self->__pyx_base.weighted_n_node_samples; __pyx_v_self->__pyx_base.weighted_n_right = __pyx_t_1; - /* "_criterion.pyx":324 + /* "stpredictions/models/OK3/_criterion.pyx":324 * self.weighted_n_left = 0.0 * self.weighted_n_right = self.weighted_n_node_samples * self.pos = self.start # <<<<<<<<<<<<<< @@ -4596,7 +4480,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __p __pyx_t_2 = __pyx_v_self->__pyx_base.start; __pyx_v_self->__pyx_base.pos = __pyx_t_2; - /* "_criterion.pyx":325 + /* "stpredictions/models/OK3/_criterion.pyx":325 * self.weighted_n_right = self.weighted_n_node_samples * self.pos = self.start * return 0 # <<<<<<<<<<<<<< @@ -4606,7 +4490,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __p __pyx_r = 0; goto __pyx_L0; - /* "_criterion.pyx":313 + /* "stpredictions/models/OK3/_criterion.pyx":313 * return 0 * * cdef int reset(self) nogil except -1: # <<<<<<<<<<<<<< @@ -4619,7 +4503,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __p return __pyx_r; } -/* "_criterion.pyx":327 +/* "stpredictions/models/OK3/_criterion.pyx":327 * return 0 * * cdef int reverse_reset(self) nogil except -1: # <<<<<<<<<<<<<< @@ -4627,12 +4511,12 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reset(struct __p * */ -static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_reverse_reset(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { int __pyx_r; double __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_2; - /* "_criterion.pyx":330 + /* "stpredictions/models/OK3/_criterion.pyx":330 * """Reset the criterion at pos=end.""" * * self.sum_diag_Gramm_right = 0.0 # <<<<<<<<<<<<<< @@ -4641,7 +4525,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(st */ __pyx_v_self->sum_diag_Gramm_right = 0.0; - /* "_criterion.pyx":331 + /* "stpredictions/models/OK3/_criterion.pyx":331 * * self.sum_diag_Gramm_right = 0.0 * self.sum_diag_Gramm_left = self.sum_diag_Gramm # <<<<<<<<<<<<<< @@ -4651,7 +4535,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(st __pyx_t_1 = __pyx_v_self->sum_diag_Gramm; __pyx_v_self->sum_diag_Gramm_left = __pyx_t_1; - /* "_criterion.pyx":333 + /* "stpredictions/models/OK3/_criterion.pyx":333 * self.sum_diag_Gramm_left = self.sum_diag_Gramm * * self.sum_total_Gramm_right = 0.0 # <<<<<<<<<<<<<< @@ -4660,7 +4544,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(st */ __pyx_v_self->sum_total_Gramm_right = 0.0; - /* "_criterion.pyx":334 + /* "stpredictions/models/OK3/_criterion.pyx":334 * * self.sum_total_Gramm_right = 0.0 * self.sum_total_Gramm_left = self.sum_total_Gramm # <<<<<<<<<<<<<< @@ -4670,7 +4554,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(st __pyx_t_1 = __pyx_v_self->sum_total_Gramm; __pyx_v_self->sum_total_Gramm_left = __pyx_t_1; - /* "_criterion.pyx":336 + /* "stpredictions/models/OK3/_criterion.pyx":336 * self.sum_total_Gramm_left = self.sum_total_Gramm * * self.weighted_n_right = 0.0 # <<<<<<<<<<<<<< @@ -4679,7 +4563,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(st */ __pyx_v_self->__pyx_base.weighted_n_right = 0.0; - /* "_criterion.pyx":337 + /* "stpredictions/models/OK3/_criterion.pyx":337 * * self.weighted_n_right = 0.0 * self.weighted_n_left = self.weighted_n_node_samples # <<<<<<<<<<<<<< @@ -4689,7 +4573,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(st __pyx_t_1 = __pyx_v_self->__pyx_base.weighted_n_node_samples; __pyx_v_self->__pyx_base.weighted_n_left = __pyx_t_1; - /* "_criterion.pyx":338 + /* "stpredictions/models/OK3/_criterion.pyx":338 * self.weighted_n_right = 0.0 * self.weighted_n_left = self.weighted_n_node_samples * self.pos = self.end # <<<<<<<<<<<<<< @@ -4699,7 +4583,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(st __pyx_t_2 = __pyx_v_self->__pyx_base.end; __pyx_v_self->__pyx_base.pos = __pyx_t_2; - /* "_criterion.pyx":339 + /* "stpredictions/models/OK3/_criterion.pyx":339 * self.weighted_n_left = self.weighted_n_node_samples * self.pos = self.end * return 0 # <<<<<<<<<<<<<< @@ -4709,7 +4593,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(st __pyx_r = 0; goto __pyx_L0; - /* "_criterion.pyx":327 + /* "stpredictions/models/OK3/_criterion.pyx":327 * return 0 * * cdef int reverse_reset(self) nogil except -1: # <<<<<<<<<<<<<< @@ -4722,7 +4606,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(st return __pyx_r; } -/* "_criterion.pyx":341 +/* "stpredictions/models/OK3/_criterion.pyx":341 * return 0 * * cdef int update(self, SIZE_t new_pos) nogil except -1: # <<<<<<<<<<<<<< @@ -4730,35 +4614,35 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_reverse_reset(st * */ -static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos) { +static int __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_update(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_new_pos) { double *__pyx_v_sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_q; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_i; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_j; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_pos; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_i; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_j; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_q; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_w_i; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_w_j; int __pyx_r; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_3; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_5; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_3; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_4; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_5; int __pyx_t_6; Py_ssize_t __pyx_t_7; Py_ssize_t __pyx_t_8; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_9; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_10; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_11; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_9; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_10; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_11; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "_criterion.pyx":344 + /* "stpredictions/models/OK3/_criterion.pyx":344 * """Updated statistics by moving samples[pos:new_pos] to the left.""" * * cdef double* sample_weight = self.sample_weight # <<<<<<<<<<<<<< @@ -4768,7 +4652,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_t_1 = __pyx_v_self->__pyx_base.sample_weight; __pyx_v_sample_weight = __pyx_t_1; - /* "_criterion.pyx":345 + /* "stpredictions/models/OK3/_criterion.pyx":345 * * cdef double* sample_weight = self.sample_weight * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< @@ -4778,7 +4662,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_t_2 = __pyx_v_self->__pyx_base.samples; __pyx_v_samples = __pyx_t_2; - /* "_criterion.pyx":347 + /* "stpredictions/models/OK3/_criterion.pyx":347 * cdef SIZE_t* samples = self.samples * * cdef SIZE_t start = self.start # <<<<<<<<<<<<<< @@ -4788,7 +4672,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_t_3 = __pyx_v_self->__pyx_base.start; __pyx_v_start = __pyx_t_3; - /* "_criterion.pyx":348 + /* "stpredictions/models/OK3/_criterion.pyx":348 * * cdef SIZE_t start = self.start * cdef SIZE_t pos = self.pos # <<<<<<<<<<<<<< @@ -4798,7 +4682,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_t_3 = __pyx_v_self->__pyx_base.pos; __pyx_v_pos = __pyx_t_3; - /* "_criterion.pyx":349 + /* "stpredictions/models/OK3/_criterion.pyx":349 * cdef SIZE_t start = self.start * cdef SIZE_t pos = self.pos * cdef SIZE_t end = self.end # <<<<<<<<<<<<<< @@ -4808,7 +4692,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_t_3 = __pyx_v_self->__pyx_base.end; __pyx_v_end = __pyx_t_3; - /* "_criterion.pyx":355 + /* "stpredictions/models/OK3/_criterion.pyx":355 * cdef SIZE_t p * cdef SIZE_t q * cdef DOUBLE_t w_i = 1.0 # <<<<<<<<<<<<<< @@ -4817,7 +4701,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_w_i = 1.0; - /* "_criterion.pyx":356 + /* "stpredictions/models/OK3/_criterion.pyx":356 * cdef SIZE_t q * cdef DOUBLE_t w_i = 1.0 * cdef DOUBLE_t w_j = 1.0 # <<<<<<<<<<<<<< @@ -4826,7 +4710,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_w_j = 1.0; - /* "_criterion.pyx":360 + /* "stpredictions/models/OK3/_criterion.pyx":360 * # Update statistics up to new_pos * * for p in range(pos, new_pos): # <<<<<<<<<<<<<< @@ -4838,7 +4722,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ for (__pyx_t_5 = __pyx_v_pos; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_p = __pyx_t_5; - /* "_criterion.pyx":361 + /* "stpredictions/models/OK3/_criterion.pyx":361 * * for p in range(pos, new_pos): * i = samples[p] # <<<<<<<<<<<<<< @@ -4847,7 +4731,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_i = (__pyx_v_samples[__pyx_v_p]); - /* "_criterion.pyx":363 + /* "stpredictions/models/OK3/_criterion.pyx":363 * i = samples[p] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -4857,7 +4741,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); if (__pyx_t_6) { - /* "_criterion.pyx":364 + /* "stpredictions/models/OK3/_criterion.pyx":364 * * if sample_weight != NULL: * w_i = sample_weight[i] # <<<<<<<<<<<<<< @@ -4866,7 +4750,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_w_i = (__pyx_v_sample_weight[__pyx_v_i]); - /* "_criterion.pyx":363 + /* "stpredictions/models/OK3/_criterion.pyx":363 * i = samples[p] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -4875,7 +4759,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ } - /* "_criterion.pyx":366 + /* "stpredictions/models/OK3/_criterion.pyx":366 * w_i = sample_weight[i] * * self.sum_diag_Gramm_left += w_i * self.y[i,i] # <<<<<<<<<<<<<< @@ -4885,9 +4769,9 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 366, __pyx_L1_error)} __pyx_t_7 = __pyx_v_i; __pyx_t_8 = __pyx_v_i; - __pyx_v_self->sum_diag_Gramm_left = (__pyx_v_self->sum_diag_Gramm_left + (__pyx_v_w_i * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) ))))); + __pyx_v_self->sum_diag_Gramm_left = (__pyx_v_self->sum_diag_Gramm_left + (__pyx_v_w_i * (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) ))))); - /* "_criterion.pyx":368 + /* "stpredictions/models/OK3/_criterion.pyx":368 * self.sum_diag_Gramm_left += w_i * self.y[i,i] * * self.sum_diag_Gramm_right -= w_i * self.y[i,i] # <<<<<<<<<<<<<< @@ -4897,9 +4781,9 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 368, __pyx_L1_error)} __pyx_t_8 = __pyx_v_i; __pyx_t_7 = __pyx_v_i; - __pyx_v_self->sum_diag_Gramm_right = (__pyx_v_self->sum_diag_Gramm_right - (__pyx_v_w_i * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) ))))); + __pyx_v_self->sum_diag_Gramm_right = (__pyx_v_self->sum_diag_Gramm_right - (__pyx_v_w_i * (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) ))))); - /* "_criterion.pyx":370 + /* "stpredictions/models/OK3/_criterion.pyx":370 * self.sum_diag_Gramm_right -= w_i * self.y[i,i] * * self.weighted_n_left += w_i # <<<<<<<<<<<<<< @@ -4908,7 +4792,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_self->__pyx_base.weighted_n_left = (__pyx_v_self->__pyx_base.weighted_n_left + __pyx_v_w_i); - /* "_criterion.pyx":372 + /* "stpredictions/models/OK3/_criterion.pyx":372 * self.weighted_n_left += w_i * * self.weighted_n_right -= w_i # <<<<<<<<<<<<<< @@ -4917,7 +4801,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_self->__pyx_base.weighted_n_right = (__pyx_v_self->__pyx_base.weighted_n_right - __pyx_v_w_i); - /* "_criterion.pyx":374 + /* "stpredictions/models/OK3/_criterion.pyx":374 * self.weighted_n_right -= w_i * * for q in range(start, pos): # <<<<<<<<<<<<<< @@ -4929,7 +4813,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ for (__pyx_t_11 = __pyx_v_start; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) { __pyx_v_q = __pyx_t_11; - /* "_criterion.pyx":375 + /* "stpredictions/models/OK3/_criterion.pyx":375 * * for q in range(start, pos): * j = samples[q] # <<<<<<<<<<<<<< @@ -4938,7 +4822,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_j = (__pyx_v_samples[__pyx_v_q]); - /* "_criterion.pyx":377 + /* "stpredictions/models/OK3/_criterion.pyx":377 * j = samples[q] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -4948,7 +4832,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); if (__pyx_t_6) { - /* "_criterion.pyx":378 + /* "stpredictions/models/OK3/_criterion.pyx":378 * * if sample_weight != NULL: * w_j = sample_weight[j] # <<<<<<<<<<<<<< @@ -4957,7 +4841,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]); - /* "_criterion.pyx":377 + /* "stpredictions/models/OK3/_criterion.pyx":377 * j = samples[q] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -4966,7 +4850,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ } - /* "_criterion.pyx":380 + /* "stpredictions/models/OK3/_criterion.pyx":380 * w_j = sample_weight[j] * * self.sum_total_Gramm_left += 2 * w_i * w_j * self.y[i,j] # <<<<<<<<<<<<<< @@ -4976,10 +4860,10 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 380, __pyx_L1_error)} __pyx_t_7 = __pyx_v_i; __pyx_t_8 = __pyx_v_j; - __pyx_v_self->sum_total_Gramm_left = (__pyx_v_self->sum_total_Gramm_left + (((2.0 * __pyx_v_w_i) * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) ))))); + __pyx_v_self->sum_total_Gramm_left = (__pyx_v_self->sum_total_Gramm_left + (((2.0 * __pyx_v_w_i) * __pyx_v_w_j) * (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) ))))); } - /* "_criterion.pyx":382 + /* "stpredictions/models/OK3/_criterion.pyx":382 * self.sum_total_Gramm_left += 2 * w_i * w_j * self.y[i,j] * * for q in range(pos, new_pos): # <<<<<<<<<<<<<< @@ -4991,7 +4875,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ for (__pyx_t_11 = __pyx_v_pos; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) { __pyx_v_q = __pyx_t_11; - /* "_criterion.pyx":383 + /* "stpredictions/models/OK3/_criterion.pyx":383 * * for q in range(pos, new_pos): * j = samples[q] # <<<<<<<<<<<<<< @@ -5000,7 +4884,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_j = (__pyx_v_samples[__pyx_v_q]); - /* "_criterion.pyx":385 + /* "stpredictions/models/OK3/_criterion.pyx":385 * j = samples[q] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -5010,7 +4894,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); if (__pyx_t_6) { - /* "_criterion.pyx":386 + /* "stpredictions/models/OK3/_criterion.pyx":386 * * if sample_weight != NULL: * w_j = sample_weight[j] # <<<<<<<<<<<<<< @@ -5019,7 +4903,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]); - /* "_criterion.pyx":385 + /* "stpredictions/models/OK3/_criterion.pyx":385 * j = samples[q] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -5028,7 +4912,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ } - /* "_criterion.pyx":388 + /* "stpredictions/models/OK3/_criterion.pyx":388 * w_j = sample_weight[j] * * self.sum_total_Gramm_left += w_i * w_j * self.y[i,j] # <<<<<<<<<<<<<< @@ -5038,9 +4922,9 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 388, __pyx_L1_error)} __pyx_t_8 = __pyx_v_i; __pyx_t_7 = __pyx_v_j; - __pyx_v_self->sum_total_Gramm_left = (__pyx_v_self->sum_total_Gramm_left + ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) ))))); + __pyx_v_self->sum_total_Gramm_left = (__pyx_v_self->sum_total_Gramm_left + ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) ))))); - /* "_criterion.pyx":390 + /* "stpredictions/models/OK3/_criterion.pyx":390 * self.sum_total_Gramm_left += w_i * w_j * self.y[i,j] * * self.sum_total_Gramm_right -= w_i * w_j * self.y[i,j] # <<<<<<<<<<<<<< @@ -5050,11 +4934,11 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 390, __pyx_L1_error)} __pyx_t_7 = __pyx_v_i; __pyx_t_8 = __pyx_v_j; - __pyx_v_self->sum_total_Gramm_right = (__pyx_v_self->sum_total_Gramm_right - ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) ))))); + __pyx_v_self->sum_total_Gramm_right = (__pyx_v_self->sum_total_Gramm_right - ((__pyx_v_w_i * __pyx_v_w_j) * (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_7 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_8)) ))))); } } - /* "_criterion.pyx":392 + /* "stpredictions/models/OK3/_criterion.pyx":392 * self.sum_total_Gramm_right -= w_i * w_j * self.y[i,j] * * for p in range(new_pos, end): # <<<<<<<<<<<<<< @@ -5066,7 +4950,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ for (__pyx_t_5 = __pyx_v_new_pos; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_p = __pyx_t_5; - /* "_criterion.pyx":393 + /* "stpredictions/models/OK3/_criterion.pyx":393 * * for p in range(new_pos, end): * i = samples[p] # <<<<<<<<<<<<<< @@ -5075,7 +4959,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_i = (__pyx_v_samples[__pyx_v_p]); - /* "_criterion.pyx":395 + /* "stpredictions/models/OK3/_criterion.pyx":395 * i = samples[p] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -5085,7 +4969,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); if (__pyx_t_6) { - /* "_criterion.pyx":396 + /* "stpredictions/models/OK3/_criterion.pyx":396 * * if sample_weight != NULL: * w_i = sample_weight[i] # <<<<<<<<<<<<<< @@ -5094,7 +4978,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_w_i = (__pyx_v_sample_weight[__pyx_v_i]); - /* "_criterion.pyx":395 + /* "stpredictions/models/OK3/_criterion.pyx":395 * i = samples[p] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -5103,7 +4987,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ } - /* "_criterion.pyx":398 + /* "stpredictions/models/OK3/_criterion.pyx":398 * w_i = sample_weight[i] * * for q in range(pos, new_pos): # <<<<<<<<<<<<<< @@ -5115,7 +4999,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ for (__pyx_t_11 = __pyx_v_pos; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) { __pyx_v_q = __pyx_t_11; - /* "_criterion.pyx":399 + /* "stpredictions/models/OK3/_criterion.pyx":399 * * for q in range(pos, new_pos): * j = samples[q] # <<<<<<<<<<<<<< @@ -5124,7 +5008,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_j = (__pyx_v_samples[__pyx_v_q]); - /* "_criterion.pyx":401 + /* "stpredictions/models/OK3/_criterion.pyx":401 * j = samples[q] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -5134,7 +5018,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0); if (__pyx_t_6) { - /* "_criterion.pyx":402 + /* "stpredictions/models/OK3/_criterion.pyx":402 * * if sample_weight != NULL: * w_j = sample_weight[j] # <<<<<<<<<<<<<< @@ -5143,7 +5027,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_w_j = (__pyx_v_sample_weight[__pyx_v_j]); - /* "_criterion.pyx":401 + /* "stpredictions/models/OK3/_criterion.pyx":401 * j = samples[q] * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -5152,7 +5036,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ } - /* "_criterion.pyx":404 + /* "stpredictions/models/OK3/_criterion.pyx":404 * w_j = sample_weight[j] * * self.sum_total_Gramm_right -= 2 * w_i * w_j * self.y[i,j] # <<<<<<<<<<<<<< @@ -5162,11 +5046,11 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ if (unlikely(!__pyx_v_self->__pyx_base.y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(1, 404, __pyx_L1_error)} __pyx_t_8 = __pyx_v_i; __pyx_t_7 = __pyx_v_j; - __pyx_v_self->sum_total_Gramm_right = (__pyx_v_self->sum_total_Gramm_right - (((2.0 * __pyx_v_w_i) * __pyx_v_w_j) * (*((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) ))))); + __pyx_v_self->sum_total_Gramm_right = (__pyx_v_self->sum_total_Gramm_right - (((2.0 * __pyx_v_w_i) * __pyx_v_w_j) * (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=1 */ ((char *) (((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const *) ( /* dim=0 */ (__pyx_v_self->__pyx_base.y.data + __pyx_t_8 * __pyx_v_self->__pyx_base.y.strides[0]) )) + __pyx_t_7)) ))))); } } - /* "_criterion.pyx":406 + /* "stpredictions/models/OK3/_criterion.pyx":406 * self.sum_total_Gramm_right -= 2 * w_i * w_j * self.y[i,j] * * self.pos = new_pos # <<<<<<<<<<<<<< @@ -5175,7 +5059,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ */ __pyx_v_self->__pyx_base.pos = __pyx_v_new_pos; - /* "_criterion.pyx":407 + /* "stpredictions/models/OK3/_criterion.pyx":407 * * self.pos = new_pos * return 0 # <<<<<<<<<<<<<< @@ -5185,7 +5069,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ __pyx_r = 0; goto __pyx_L0; - /* "_criterion.pyx":341 + /* "stpredictions/models/OK3/_criterion.pyx":341 * return 0 * * cdef int update(self, SIZE_t new_pos) nogil except -1: # <<<<<<<<<<<<<< @@ -5199,7 +5083,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif - __Pyx_AddTraceback("_criterion.KernelizedRegressionCriterion.update", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._criterion.KernelizedRegressionCriterion.update", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif @@ -5209,7 +5093,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ return __pyx_r; } -/* "_criterion.pyx":409 +/* "stpredictions/models/OK3/_criterion.pyx":409 * return 0 * * cdef double node_impurity(self) nogil: # <<<<<<<<<<<<<< @@ -5217,7 +5101,7 @@ static int __pyx_f_10_criterion_29KernelizedRegressionCriterion_update(struct __ * */ -static double __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self) { double __pyx_r; /* function exit code */ @@ -5225,7 +5109,7 @@ static double __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_impurity return __pyx_r; } -/* "_criterion.pyx":412 +/* "stpredictions/models/OK3/_criterion.pyx":412 * pass * * cdef void children_impurity(self, double* impurity_left, double* impurity_right) nogil: # <<<<<<<<<<<<<< @@ -5233,12 +5117,12 @@ static double __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_impurity * */ -static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) { +static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) { /* function exit code */ } -/* "_criterion.pyx":415 +/* "stpredictions/models/OK3/_criterion.pyx":415 * pass * * cdef void node_value(self, double* dest) nogil: # <<<<<<<<<<<<<< @@ -5246,16 +5130,16 @@ static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_children_impuri * */ -static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, double *__pyx_v_dest) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_3; +static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_node_value(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_v_self, double *__pyx_v_dest) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_k; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_w; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_3; int __pyx_t_4; - /* "_criterion.pyx":420 + /* "stpredictions/models/OK3/_criterion.pyx":420 * cdef SIZE_t p * cdef SIZE_t k * cdef DOUBLE_t w = 1.0 # <<<<<<<<<<<<<< @@ -5264,7 +5148,7 @@ static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(stru */ __pyx_v_w = 1.0; - /* "_criterion.pyx":422 + /* "stpredictions/models/OK3/_criterion.pyx":422 * cdef DOUBLE_t w = 1.0 * * for p in range(self.start, self.end): # <<<<<<<<<<<<<< @@ -5276,7 +5160,7 @@ static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(stru for (__pyx_t_3 = __pyx_v_self->__pyx_base.start; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_p = __pyx_t_3; - /* "_criterion.pyx":424 + /* "stpredictions/models/OK3/_criterion.pyx":424 * for p in range(self.start, self.end): * * k = self.samples[p] # <<<<<<<<<<<<<< @@ -5285,7 +5169,7 @@ static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(stru */ __pyx_v_k = (__pyx_v_self->__pyx_base.samples[__pyx_v_p]); - /* "_criterion.pyx":426 + /* "stpredictions/models/OK3/_criterion.pyx":426 * k = self.samples[p] * * if self.sample_weight != NULL: # <<<<<<<<<<<<<< @@ -5295,7 +5179,7 @@ static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(stru __pyx_t_4 = ((__pyx_v_self->__pyx_base.sample_weight != NULL) != 0); if (__pyx_t_4) { - /* "_criterion.pyx":427 + /* "stpredictions/models/OK3/_criterion.pyx":427 * * if self.sample_weight != NULL: * w = self.sample_weight[k] # <<<<<<<<<<<<<< @@ -5304,7 +5188,7 @@ static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(stru */ __pyx_v_w = (__pyx_v_self->__pyx_base.sample_weight[__pyx_v_k]); - /* "_criterion.pyx":426 + /* "stpredictions/models/OK3/_criterion.pyx":426 * k = self.samples[p] * * if self.sample_weight != NULL: # <<<<<<<<<<<<<< @@ -5313,7 +5197,7 @@ static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(stru */ } - /* "_criterion.pyx":429 + /* "stpredictions/models/OK3/_criterion.pyx":429 * w = self.sample_weight[k] * * dest[k] = w / self.weighted_n_node_samples # <<<<<<<<<<<<<< @@ -5323,7 +5207,7 @@ static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(stru (__pyx_v_dest[__pyx_v_k]) = (__pyx_v_w / __pyx_v_self->__pyx_base.weighted_n_node_samples); } - /* "_criterion.pyx":415 + /* "stpredictions/models/OK3/_criterion.pyx":415 * pass * * cdef void node_value(self, double* dest) nogil: # <<<<<<<<<<<<<< @@ -5334,7 +5218,7 @@ static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(stru /* function exit code */ } -/* "_criterion.pyx":454 +/* "stpredictions/models/OK3/_criterion.pyx":454 * """ * * cdef double node_impurity(self) nogil: # <<<<<<<<<<<<<< @@ -5342,11 +5226,11 @@ static void __pyx_f_10_criterion_29KernelizedRegressionCriterion_node_value(stru * samples[start:end].""" */ -static double __pyx_f_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self) { +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self) { double __pyx_v_impurity; double __pyx_r; - /* "_criterion.pyx":460 + /* "stpredictions/models/OK3/_criterion.pyx":460 * cdef double impurity * * impurity = self.sum_diag_Gramm / self.weighted_n_node_samples - self.sum_total_Gramm / (self.weighted_n_node_samples)**2 # <<<<<<<<<<<<<< @@ -5355,7 +5239,7 @@ static double __pyx_f_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_ob */ __pyx_v_impurity = ((__pyx_v_self->__pyx_base.sum_diag_Gramm / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples) - (__pyx_v_self->__pyx_base.sum_total_Gramm / pow(__pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples, 2.0))); - /* "_criterion.pyx":462 + /* "stpredictions/models/OK3/_criterion.pyx":462 * impurity = self.sum_diag_Gramm / self.weighted_n_node_samples - self.sum_total_Gramm / (self.weighted_n_node_samples)**2 * * return impurity # <<<<<<<<<<<<<< @@ -5365,7 +5249,7 @@ static double __pyx_f_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_ob __pyx_r = __pyx_v_impurity; goto __pyx_L0; - /* "_criterion.pyx":454 + /* "stpredictions/models/OK3/_criterion.pyx":454 * """ * * cdef double node_impurity(self) nogil: # <<<<<<<<<<<<<< @@ -5378,7 +5262,7 @@ static double __pyx_f_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_ob return __pyx_r; } -/* "_criterion.pyx":464 +/* "stpredictions/models/OK3/_criterion.pyx":464 * return impurity * * cdef double proxy_impurity_improvement(self) nogil: # <<<<<<<<<<<<<< @@ -5386,12 +5270,12 @@ static double __pyx_f_10_criterion_13KernelizedMSE_node_impurity(struct __pyx_ob * */ -static double __pyx_f_10_criterion_13KernelizedMSE_proxy_impurity_improvement(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self) { +static double __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_proxy_impurity_improvement(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self) { double __pyx_v_proxy_impurity_left; double __pyx_v_proxy_impurity_right; double __pyx_r; - /* "_criterion.pyx":476 + /* "stpredictions/models/OK3/_criterion.pyx":476 * """ * * cdef double proxy_impurity_left = self.sum_diag_Gramm_left - self.sum_total_Gramm_left / self.weighted_n_left # <<<<<<<<<<<<<< @@ -5400,7 +5284,7 @@ static double __pyx_f_10_criterion_13KernelizedMSE_proxy_impurity_improvement(st */ __pyx_v_proxy_impurity_left = (__pyx_v_self->__pyx_base.sum_diag_Gramm_left - (__pyx_v_self->__pyx_base.sum_total_Gramm_left / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_left)); - /* "_criterion.pyx":477 + /* "stpredictions/models/OK3/_criterion.pyx":477 * * cdef double proxy_impurity_left = self.sum_diag_Gramm_left - self.sum_total_Gramm_left / self.weighted_n_left * cdef double proxy_impurity_right = self.sum_diag_Gramm_right - self.sum_total_Gramm_right / self.weighted_n_right # <<<<<<<<<<<<<< @@ -5409,7 +5293,7 @@ static double __pyx_f_10_criterion_13KernelizedMSE_proxy_impurity_improvement(st */ __pyx_v_proxy_impurity_right = (__pyx_v_self->__pyx_base.sum_diag_Gramm_right - (__pyx_v_self->__pyx_base.sum_total_Gramm_right / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_right)); - /* "_criterion.pyx":479 + /* "stpredictions/models/OK3/_criterion.pyx":479 * cdef double proxy_impurity_right = self.sum_diag_Gramm_right - self.sum_total_Gramm_right / self.weighted_n_right * * return (- proxy_impurity_left - proxy_impurity_right) # <<<<<<<<<<<<<< @@ -5419,7 +5303,7 @@ static double __pyx_f_10_criterion_13KernelizedMSE_proxy_impurity_improvement(st __pyx_r = ((-__pyx_v_proxy_impurity_left) - __pyx_v_proxy_impurity_right); goto __pyx_L0; - /* "_criterion.pyx":464 + /* "stpredictions/models/OK3/_criterion.pyx":464 * return impurity * * cdef double proxy_impurity_improvement(self) nogil: # <<<<<<<<<<<<<< @@ -5432,7 +5316,7 @@ static double __pyx_f_10_criterion_13KernelizedMSE_proxy_impurity_improvement(st return __pyx_r; } -/* "_criterion.pyx":481 +/* "stpredictions/models/OK3/_criterion.pyx":481 * return (- proxy_impurity_left - proxy_impurity_right) * * cdef void children_impurity(self, double* impurity_left, double* impurity_right) nogil: # <<<<<<<<<<<<<< @@ -5440,14 +5324,14 @@ static double __pyx_f_10_criterion_13KernelizedMSE_proxy_impurity_improvement(st * left child (samples[start:pos]) and the impurity the right child */ -static void __pyx_f_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_obj_10_criterion_KernelizedMSE *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right) { +static void __pyx_f_13stpredictions_6models_3OK3_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right) { double __pyx_v_sum_diag_Gramm_left; double __pyx_v_sum_diag_Gramm_right; double __pyx_v_sum_total_Gramm_left; double __pyx_v_sum_total_Gramm_right; double __pyx_t_1; - /* "_criterion.pyx":486 + /* "stpredictions/models/OK3/_criterion.pyx":486 * (samples[pos:end]).""" * * cdef double sum_diag_Gramm_left = self.sum_diag_Gramm_left # <<<<<<<<<<<<<< @@ -5457,7 +5341,7 @@ static void __pyx_f_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_ __pyx_t_1 = __pyx_v_self->__pyx_base.sum_diag_Gramm_left; __pyx_v_sum_diag_Gramm_left = __pyx_t_1; - /* "_criterion.pyx":487 + /* "stpredictions/models/OK3/_criterion.pyx":487 * * cdef double sum_diag_Gramm_left = self.sum_diag_Gramm_left * cdef double sum_diag_Gramm_right = self.sum_diag_Gramm_right # <<<<<<<<<<<<<< @@ -5467,7 +5351,7 @@ static void __pyx_f_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_ __pyx_t_1 = __pyx_v_self->__pyx_base.sum_diag_Gramm_right; __pyx_v_sum_diag_Gramm_right = __pyx_t_1; - /* "_criterion.pyx":489 + /* "stpredictions/models/OK3/_criterion.pyx":489 * cdef double sum_diag_Gramm_right = self.sum_diag_Gramm_right * * cdef double sum_total_Gramm_left = self.sum_total_Gramm_left # <<<<<<<<<<<<<< @@ -5477,7 +5361,7 @@ static void __pyx_f_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_ __pyx_t_1 = __pyx_v_self->__pyx_base.sum_total_Gramm_left; __pyx_v_sum_total_Gramm_left = __pyx_t_1; - /* "_criterion.pyx":490 + /* "stpredictions/models/OK3/_criterion.pyx":490 * * cdef double sum_total_Gramm_left = self.sum_total_Gramm_left * cdef double sum_total_Gramm_right = self.sum_total_Gramm_right # <<<<<<<<<<<<<< @@ -5487,7 +5371,7 @@ static void __pyx_f_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_ __pyx_t_1 = __pyx_v_self->__pyx_base.sum_total_Gramm_right; __pyx_v_sum_total_Gramm_right = __pyx_t_1; - /* "_criterion.pyx":492 + /* "stpredictions/models/OK3/_criterion.pyx":492 * cdef double sum_total_Gramm_right = self.sum_total_Gramm_right * * impurity_left[0] = sum_diag_Gramm_left / self.weighted_n_left - sum_total_Gramm_left / (self.weighted_n_left)**2 # <<<<<<<<<<<<<< @@ -5496,7 +5380,7 @@ static void __pyx_f_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_ */ (__pyx_v_impurity_left[0]) = ((__pyx_v_sum_diag_Gramm_left / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_left) - (__pyx_v_sum_total_Gramm_left / pow(__pyx_v_self->__pyx_base.__pyx_base.weighted_n_left, 2.0))); - /* "_criterion.pyx":493 + /* "stpredictions/models/OK3/_criterion.pyx":493 * * impurity_left[0] = sum_diag_Gramm_left / self.weighted_n_left - sum_total_Gramm_left / (self.weighted_n_left)**2 * impurity_right[0] = sum_diag_Gramm_right / self.weighted_n_right - sum_total_Gramm_right / (self.weighted_n_right)**2 # <<<<<<<<<<<<<< @@ -5505,7 +5389,7 @@ static void __pyx_f_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_ */ (__pyx_v_impurity_right[0]) = ((__pyx_v_sum_diag_Gramm_right / __pyx_v_self->__pyx_base.__pyx_base.weighted_n_right) - (__pyx_v_sum_total_Gramm_right / pow(__pyx_v_self->__pyx_base.__pyx_base.weighted_n_right, 2.0))); - /* "_criterion.pyx":481 + /* "stpredictions/models/OK3/_criterion.pyx":481 * return (- proxy_impurity_left - proxy_impurity_right) * * cdef void children_impurity(self, double* impurity_left, double* impurity_right) nogil: # <<<<<<<<<<<<<< @@ -5516,7 +5400,7 @@ static void __pyx_f_10_criterion_13KernelizedMSE_children_impurity(struct __pyx_ /* function exit code */ } -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":734 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":734 * ctypedef npy_cdouble complex_t * * cdef inline object PyArray_MultiIterNew1(a): # <<<<<<<<<<<<<< @@ -5533,7 +5417,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("PyArray_MultiIterNew1", 0); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":735 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":735 * * cdef inline object PyArray_MultiIterNew1(a): * return PyArray_MultiIterNew(1, a) # <<<<<<<<<<<<<< @@ -5547,7 +5431,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__ __pyx_t_1 = 0; goto __pyx_L0; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":734 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":734 * ctypedef npy_cdouble complex_t * * cdef inline object PyArray_MultiIterNew1(a): # <<<<<<<<<<<<<< @@ -5566,7 +5450,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__ return __pyx_r; } -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":737 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":737 * return PyArray_MultiIterNew(1, a) * * cdef inline object PyArray_MultiIterNew2(a, b): # <<<<<<<<<<<<<< @@ -5583,7 +5467,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew2(PyObject *__ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("PyArray_MultiIterNew2", 0); - /* 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"../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":740 * return PyArray_MultiIterNew(2, a, b) * * cdef inline object PyArray_MultiIterNew3(a, b, c): # <<<<<<<<<<<<<< @@ -5633,7 +5517,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew3(PyObject *__ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("PyArray_MultiIterNew3", 0); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":741 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":741 * * cdef inline object PyArray_MultiIterNew3(a, b, c): * return PyArray_MultiIterNew(3, a, b, c) # <<<<<<<<<<<<<< @@ -5647,7 +5531,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew3(PyObject *__ __pyx_t_1 = 0; goto __pyx_L0; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":740 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":740 * return PyArray_MultiIterNew(2, a, b) * * cdef inline object PyArray_MultiIterNew3(a, b, c): # <<<<<<<<<<<<<< @@ -5666,7 +5550,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew3(PyObject *__ return __pyx_r; } -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":743 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":743 * return PyArray_MultiIterNew(3, a, b, c) * * cdef inline object PyArray_MultiIterNew4(a, b, c, d): # <<<<<<<<<<<<<< @@ -5683,7 +5567,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew4(PyObject *__ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("PyArray_MultiIterNew4", 0); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":744 + /* 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"../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":750 * * cdef inline tuple PyDataType_SHAPE(dtype d): * if PyDataType_HASSUBARRAY(d): # <<<<<<<<<<<<<< @@ -5811,7 +5695,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyDataType_SHAPE(PyArray_Descr *__ */ } - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":753 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":753 * return d.subarray.shape * else: * return () # <<<<<<<<<<<<<< @@ -5825,7 +5709,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyDataType_SHAPE(PyArray_Descr *__ goto __pyx_L0; } - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":749 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":749 * return PyArray_MultiIterNew(5, a, b, c, d, e) * * cdef inline tuple PyDataType_SHAPE(dtype 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/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":872 * PyArray_SetBaseObject(arr, base) * * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< @@ -5963,7 +5847,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py return __pyx_r; } -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":880 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":880 * # Versions of the import_* functions which are more suitable for * # Cython code. * cdef inline int import_array() except -1: # <<<<<<<<<<<<<< @@ -5987,7 +5871,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { int __pyx_clineno = 0; __Pyx_RefNannySetupContext("import_array", 0); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":881 + /* 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# <<<<<<<<<<<<<< @@ -6321,7 +6205,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_ufunc(void) { goto __pyx_L5_except_error; __pyx_L5_except_error:; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":893 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":893 * * cdef inline int import_ufunc() except -1: * try: # <<<<<<<<<<<<<< @@ -6336,7 +6220,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_ufunc(void) { __pyx_L8_try_end:; } - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":892 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":892 * raise ImportError("numpy.core.umath failed to import") * * cdef inline int import_ufunc() except -1: # <<<<<<<<<<<<<< @@ -19376,10 +19260,10 @@ static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *__ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static struct __pyx_vtabstruct_10_criterion_Criterion __pyx_vtable_10_criterion_Criterion; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_vtable_13stpredictions_6models_3OK3_10_criterion_Criterion; -static PyObject *__pyx_tp_new_10_criterion_Criterion(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { - struct __pyx_obj_10_criterion_Criterion *p; +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_10_criterion_Criterion(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); @@ -19387,15 +19271,15 @@ static PyObject *__pyx_tp_new_10_criterion_Criterion(PyTypeObject *t, CYTHON_UNU o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_10_criterion_Criterion *)o); - p->__pyx_vtab = __pyx_vtabptr_10_criterion_Criterion; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *)o); + p->__pyx_vtab = __pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion; p->y.data = NULL; p->y.memview = NULL; return o; } -static void __pyx_tp_dealloc_10_criterion_Criterion(PyObject *o) { - struct __pyx_obj_10_criterion_Criterion *p = (struct __pyx_obj_10_criterion_Criterion *)o; +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_10_criterion_Criterion(PyObject *o) { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *p = (struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *)o; #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { if (PyObject_CallFinalizerFromDealloc(o)) return; @@ -19405,7 +19289,7 @@ static void __pyx_tp_dealloc_10_criterion_Criterion(PyObject *o) { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); - __pyx_pw_10_criterion_9Criterion_1__dealloc__(o); + __pyx_pw_13stpredictions_6models_3OK3_10_criterion_9Criterion_1__dealloc__(o); __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } @@ -19413,20 +19297,20 @@ static void __pyx_tp_dealloc_10_criterion_Criterion(PyObject *o) { (*Py_TYPE(o)->tp_free)(o); } -static PyMethodDef __pyx_methods_10_criterion_Criterion[] = { - {"__getstate__", (PyCFunction)__pyx_pw_10_criterion_9Criterion_3__getstate__, METH_NOARGS, 0}, - {"__setstate__", (PyCFunction)__pyx_pw_10_criterion_9Criterion_5__setstate__, METH_O, 0}, - {"__reduce_cython__", (PyCFunction)__pyx_pw_10_criterion_9Criterion_7__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_10_criterion_9Criterion_9__setstate_cython__, METH_O, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_10_criterion_Criterion[] = { + {"__getstate__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_10_criterion_9Criterion_3__getstate__, METH_NOARGS, 0}, + {"__setstate__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_10_criterion_9Criterion_5__setstate__, METH_O, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_10_criterion_9Criterion_7__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_10_criterion_9Criterion_9__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_10_criterion_Criterion = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_10_criterion_Criterion = { PyVarObject_HEAD_INIT(0, 0) - "_criterion.Criterion", /*tp_name*/ - sizeof(struct __pyx_obj_10_criterion_Criterion), /*tp_basicsize*/ + "stpredictions.models.OK3._criterion.Criterion", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_10_criterion_Criterion, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_10_criterion_Criterion, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -19459,7 +19343,7 @@ static PyTypeObject __pyx_type_10_criterion_Criterion = { 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_10_criterion_Criterion, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_10_criterion_Criterion, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -19469,7 +19353,7 @@ static PyTypeObject __pyx_type_10_criterion_Criterion = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_10_criterion_Criterion, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_10_criterion_Criterion, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -19489,32 +19373,32 @@ static PyTypeObject __pyx_type_10_criterion_Criterion = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion __pyx_vtable_10_criterion_KernelizedRegressionCriterion; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion __pyx_vtable_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; -static PyObject *__pyx_tp_new_10_criterion_KernelizedRegressionCriterion(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *p; - PyObject *o = __pyx_tp_new_10_criterion_Criterion(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_10_criterion_Criterion(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_10_criterion_KernelizedRegressionCriterion *)o); - p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_10_criterion_Criterion*)__pyx_vtabptr_10_criterion_KernelizedRegressionCriterion; - if (unlikely(__pyx_pw_10_criterion_29KernelizedRegressionCriterion_1__cinit__(o, a, k) < 0)) goto bad; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion*)__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_1__cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } -static PyMethodDef __pyx_methods_10_criterion_KernelizedRegressionCriterion[] = { - {"__reduce__", (PyCFunction)__pyx_pw_10_criterion_29KernelizedRegressionCriterion_3__reduce__, METH_NOARGS, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion[] = { + {"__reduce__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_10_criterion_29KernelizedRegressionCriterion_3__reduce__, METH_NOARGS, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_10_criterion_KernelizedRegressionCriterion = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion = { PyVarObject_HEAD_INIT(0, 0) - "_criterion.KernelizedRegressionCriterion", /*tp_name*/ - sizeof(struct __pyx_obj_10_criterion_KernelizedRegressionCriterion), /*tp_basicsize*/ + "stpredictions.models.OK3._criterion.KernelizedRegressionCriterion", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_10_criterion_Criterion, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_10_criterion_Criterion, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -19547,7 +19431,7 @@ static PyTypeObject __pyx_type_10_criterion_KernelizedRegressionCriterion = { 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_10_criterion_KernelizedRegressionCriterion, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -19557,7 +19441,7 @@ static PyTypeObject __pyx_type_10_criterion_KernelizedRegressionCriterion = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_10_criterion_KernelizedRegressionCriterion, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -19577,23 +19461,23 @@ static PyTypeObject __pyx_type_10_criterion_KernelizedRegressionCriterion = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_10_criterion_KernelizedMSE __pyx_vtable_10_criterion_KernelizedMSE; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE __pyx_vtable_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE; -static PyObject *__pyx_tp_new_10_criterion_KernelizedMSE(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_10_criterion_KernelizedMSE *p; - PyObject *o = __pyx_tp_new_10_criterion_KernelizedRegressionCriterion(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_10_criterion_KernelizedMSE *)o); - p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_10_criterion_Criterion*)__pyx_vtabptr_10_criterion_KernelizedMSE; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE *)o); + p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion*)__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE; return o; } -static PyTypeObject __pyx_type_10_criterion_KernelizedMSE = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE = { PyVarObject_HEAD_INIT(0, 0) - "_criterion.KernelizedMSE", /*tp_name*/ - sizeof(struct __pyx_obj_10_criterion_KernelizedMSE), /*tp_basicsize*/ + "stpredictions.models.OK3._criterion.KernelizedMSE", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_10_criterion_Criterion, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_10_criterion_Criterion, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -19636,7 +19520,7 @@ static PyTypeObject __pyx_type_10_criterion_KernelizedMSE = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_10_criterion_KernelizedMSE, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_10_criterion_KernelizedMSE, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -19779,7 +19663,7 @@ static PyBufferProcs __pyx_tp_as_buffer_array = { static PyTypeObject __pyx_type___pyx_array = { PyVarObject_HEAD_INIT(0, 0) - "_criterion.array", /*tp_name*/ + "stpredictions.models.OK3._criterion.array", /*tp_name*/ sizeof(struct __pyx_array_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_array, /*tp_dealloc*/ @@ -19898,7 +19782,7 @@ static PyMethodDef __pyx_methods_Enum[] = { static PyTypeObject __pyx_type___pyx_MemviewEnum = { PyVarObject_HEAD_INIT(0, 0) - "_criterion.Enum", /*tp_name*/ + "stpredictions.models.OK3._criterion.Enum", /*tp_name*/ sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_Enum, /*tp_dealloc*/ @@ -20159,7 +20043,7 @@ static PyBufferProcs __pyx_tp_as_buffer_memoryview = { static PyTypeObject __pyx_type___pyx_memoryview = { PyVarObject_HEAD_INIT(0, 0) - "_criterion.memoryview", /*tp_name*/ + "stpredictions.models.OK3._criterion.memoryview", /*tp_name*/ sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_memoryview, /*tp_dealloc*/ @@ -20297,7 +20181,7 @@ static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = { static PyTypeObject __pyx_type___pyx_memoryviewslice = { PyVarObject_HEAD_INIT(0, 0) - "_criterion._memoryviewslice", /*tp_name*/ + "stpredictions.models.OK3._criterion._memoryviewslice", /*tp_name*/ sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/ @@ -20554,7 +20438,7 @@ static CYTHON_SMALL_CODE int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__2); __Pyx_GIVEREF(__pyx_tuple__2); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":884 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":884 * __pyx_import_array() * except Exception: * raise ImportError("numpy.core.multiarray failed to import") # <<<<<<<<<<<<<< @@ -20565,7 +20449,7 @@ static CYTHON_SMALL_CODE int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__3); __Pyx_GIVEREF(__pyx_tuple__3); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":890 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":890 * _import_umath() * except Exception: * raise ImportError("numpy.core.umath failed to import") # <<<<<<<<<<<<<< @@ -20894,63 +20778,63 @@ static int __Pyx_modinit_type_init_code(void) { int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__Pyx_modinit_type_init_code", 0); /*--- Type init code ---*/ - __pyx_vtabptr_10_criterion_Criterion = &__pyx_vtable_10_criterion_Criterion; - __pyx_vtable_10_criterion_Criterion.init = (int (*)(struct __pyx_obj_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t))__pyx_f_10_criterion_9Criterion_init; - __pyx_vtable_10_criterion_Criterion.reset = (int (*)(struct __pyx_obj_10_criterion_Criterion *))__pyx_f_10_criterion_9Criterion_reset; - __pyx_vtable_10_criterion_Criterion.reverse_reset = (int (*)(struct __pyx_obj_10_criterion_Criterion *))__pyx_f_10_criterion_9Criterion_reverse_reset; - __pyx_vtable_10_criterion_Criterion.update = (int (*)(struct __pyx_obj_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t))__pyx_f_10_criterion_9Criterion_update; - __pyx_vtable_10_criterion_Criterion.node_impurity = (double (*)(struct __pyx_obj_10_criterion_Criterion *))__pyx_f_10_criterion_9Criterion_node_impurity; - __pyx_vtable_10_criterion_Criterion.children_impurity = (void (*)(struct __pyx_obj_10_criterion_Criterion *, double *, double *))__pyx_f_10_criterion_9Criterion_children_impurity; - __pyx_vtable_10_criterion_Criterion.node_value = (void (*)(struct __pyx_obj_10_criterion_Criterion *, double *))__pyx_f_10_criterion_9Criterion_node_value; - __pyx_vtable_10_criterion_Criterion.impurity_improvement = (double (*)(struct __pyx_obj_10_criterion_Criterion *, double))__pyx_f_10_criterion_9Criterion_impurity_improvement; - __pyx_vtable_10_criterion_Criterion.proxy_impurity_improvement = (double (*)(struct __pyx_obj_10_criterion_Criterion *))__pyx_f_10_criterion_9Criterion_proxy_impurity_improvement; - if (PyType_Ready(&__pyx_type_10_criterion_Criterion) < 0) __PYX_ERR(1, 22, __pyx_L1_error) + __pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion = &__pyx_vtable_13stpredictions_6models_3OK3_10_criterion_Criterion; + __pyx_vtable_13stpredictions_6models_3OK3_10_criterion_Criterion.init = (int (*)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t))__pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_init; + __pyx_vtable_13stpredictions_6models_3OK3_10_criterion_Criterion.reset = (int (*)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *))__pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_reset; + __pyx_vtable_13stpredictions_6models_3OK3_10_criterion_Criterion.reverse_reset = (int (*)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *))__pyx_f_13stpredictions_6models_3OK3_10_criterion_9Criterion_reverse_reset; + __pyx_vtable_13stpredictions_6models_3OK3_10_criterion_Criterion.update 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b/stpredictions/models/OK3/_criterion.pxd index c9a78a6f1..94dde1b80 100644 --- a/stpredictions/models/OK3/_criterion.pxd +++ b/stpredictions/models/OK3/_criterion.pxd @@ -3,11 +3,11 @@ import numpy as np cimport numpy as np -from sklearn.tree._tree cimport DTYPE_t # Type of X -from sklearn.tree._tree cimport DOUBLE_t # Type of y, sample_weight -from sklearn.tree._tree cimport SIZE_t # Type for indices and counters -from sklearn.tree._tree cimport INT32_t # Signed 32 bit integer -from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer +from ._tree cimport DTYPE_t # Type of X +from ._tree cimport DOUBLE_t # Type of y, sample_weight +from ._tree cimport SIZE_t # Type for indices and counters +from ._tree cimport INT32_t # Signed 32 bit integer +from ._tree cimport UINT32_t # Unsigned 32 bit integer cdef class Criterion: # The criterion computes the impurity of a node and the reduction of diff --git a/stpredictions/models/OK3/_criterion.pyx b/stpredictions/models/OK3/_criterion.pyx index 6767b1e14..8e2445006 100644 --- a/stpredictions/models/OK3/_criterion.pyx +++ b/stpredictions/models/OK3/_criterion.pyx @@ -12,10 +12,10 @@ import numpy as np cimport numpy as np np.import_array() -from sklearn.tree._utils cimport log -from sklearn.tree._utils cimport safe_realloc -from sklearn.tree._utils cimport sizet_ptr_to_ndarray -from sklearn.tree._utils cimport WeightedMedianCalculator +from ._utils cimport log +from ._utils cimport safe_realloc +from ._utils cimport sizet_ptr_to_ndarray +from ._utils cimport WeightedMedianCalculator # from kernel import Kernel diff --git a/stpredictions/models/OK3/_forest.py b/stpredictions/models/OK3/_forest.py index 2aae5d9e2..8ac901f9b 100755 --- a/stpredictions/models/OK3/_forest.py +++ b/stpredictions/models/OK3/_forest.py @@ -41,34 +41,35 @@ class calls the ``fit`` method of each sub-estimator on random samples from scipy.sparse import issparse from scipy.sparse import hstack as sparse_hstack from joblib import Parallel, delayed +from pkg_resources import parse_version import itertools -from base import StructuredOutputMixin +from .base import StructuredOutputMixin from sklearn.metrics import accuracy_score from sklearn.metrics import hamming_loss from sklearn.metrics import r2_score from sklearn.preprocessing import OneHotEncoder -from _classes import OK3Regressor, ExtraOK3Regressor -from _tree import DTYPE, DOUBLE +from ._classes import OK3Regressor, ExtraOK3Regressor +from ._tree import DTYPE, DOUBLE from sklearn.utils import check_random_state, check_array from sklearn.exceptions import DataConversionWarning from sklearn.ensemble._base import BaseEnsemble, _partition_estimators -from sklearn.utils.fixes import _joblib_parallel_args +# from sklearn.utils.fixes import _joblib_parallel_args from sklearn.utils.multiclass import check_classification_targets from sklearn.utils.validation import check_is_fitted, _check_sample_weight from sklearn.utils.validation import _deprecate_positional_args -from kernel import Kernel -from _classes import KERNELS, CRITERIA +from .kernel import Kernel +from ._classes import KERNELS, CRITERIA -from _criterion import Criterion, KernelizedMSE +from ._criterion import Criterion, KernelizedMSE -import line_profiler +# import line_profiler __all__ = ["RandomOKForestRegressor", "ExtraOKTreesRegressor", @@ -76,6 +77,52 @@ class calls the ``fit`` method of each sub-estimator on random samples MAX_INT = np.iinfo(np.int32).max +def _joblib_parallel_args(**kwargs): + """Set joblib.Parallel arguments in a compatible way for 0.11 and 0.12+ + + For joblib 0.11 this maps both ``prefer`` and ``require`` parameters to + a specific ``backend``. + + Parameters + ---------- + + prefer : str in {'processes', 'threads'} or None + Soft hint to choose the default backend if no specific backend + was selected with the parallel_backend context manager. + + require : 'sharedmem' or None + Hard condstraint to select the backend. If set to 'sharedmem', + the selected backend will be single-host and thread-based even + if the user asked for a non-thread based backend with + parallel_backend. + + See joblib.Parallel documentation for more details + """ + import joblib + + if parse_version(joblib.__version__) >= parse_version('0.12'): + return kwargs + + extra_args = set(kwargs.keys()).difference({'prefer', 'require'}) + if extra_args: + raise NotImplementedError('unhandled arguments %s with joblib %s' + % (list(extra_args), joblib.__version__)) + args = {} + if 'prefer' in kwargs: + prefer = kwargs['prefer'] + if prefer not in ['threads', 'processes', None]: + raise ValueError('prefer=%s is not supported' % prefer) + args['backend'] = {'threads': 'threading', + 'processes': 'multiprocessing', + None: None}[prefer] + + if 'require' in kwargs: + require = kwargs['require'] + if require not in [None, 'sharedmem']: + raise ValueError('require=%s is not supported' % require) + if require == 'sharedmem': + args['backend'] = 'threading' + return args def _get_n_samples_bootstrap(n_samples, max_samples): """ diff --git a/stpredictions/models/OK3/_quad_tree.c b/stpredictions/models/OK3/_quad_tree.c new file mode 100644 index 000000000..e66afae9c --- /dev/null +++ b/stpredictions/models/OK3/_quad_tree.c @@ -0,0 +1,33532 @@ +/* Generated by Cython 0.29.23 */ + +/* BEGIN: Cython Metadata +{ + "distutils": { + "depends": [ + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include/numpy/arrayobject.h", + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include/numpy/ufuncobject.h" + ], + "extra_compile_args": [ + "-O3", + "-fopenmp", + "-DOMP" + ], + "extra_link_args": [ + "-fopenmp" + ], + "include_dirs": [ + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include", + 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CYTHON_PEP489_MULTI_PHASE_INIT 0 + #undef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE 0 + #undef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS 0 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 +#else + #define CYTHON_COMPILING_IN_PYPY 0 + #define CYTHON_COMPILING_IN_PYSTON 0 + #define CYTHON_COMPILING_IN_CPYTHON 1 + #ifndef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 1 + #endif + #if PY_VERSION_HEX < 0x02070000 + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #elif !defined(CYTHON_USE_PYTYPE_LOOKUP) + #define CYTHON_USE_PYTYPE_LOOKUP 1 + #endif + #if PY_MAJOR_VERSION < 3 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #elif !defined(CYTHON_USE_ASYNC_SLOTS) + #define CYTHON_USE_ASYNC_SLOTS 1 + #endif + #if PY_VERSION_HEX < 0x02070000 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #elif !defined(CYTHON_USE_PYLONG_INTERNALS) + #define CYTHON_USE_PYLONG_INTERNALS 1 + #endif + #ifndef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 1 + #endif + #ifndef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 1 + #endif + #if PY_VERSION_HEX < 0x030300F0 + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #elif !defined(CYTHON_USE_UNICODE_WRITER) + #define CYTHON_USE_UNICODE_WRITER 1 + #endif + #ifndef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 0 + #endif + #ifndef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 1 + #endif + #ifndef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 1 + #endif + #ifndef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 1 + #endif + #ifndef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 1 + #endif + #ifndef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT (PY_VERSION_HEX >= 0x03050000) + #endif + #ifndef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE (PY_VERSION_HEX >= 0x030400a1) + #endif + #ifndef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS (PY_VERSION_HEX >= 0x030600B1) + #endif + #ifndef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK (PY_VERSION_HEX >= 0x030700A3) + #endif +#endif +#if !defined(CYTHON_FAST_PYCCALL) +#define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) +#endif +#if CYTHON_USE_PYLONG_INTERNALS + #include "longintrepr.h" + #undef SHIFT + #undef BASE + #undef MASK + #ifdef SIZEOF_VOID_P + enum { __pyx_check_sizeof_voidp = 1 / (int)(SIZEOF_VOID_P == sizeof(void*)) }; + #endif +#endif +#ifndef __has_attribute + #define __has_attribute(x) 0 +#endif +#ifndef __has_cpp_attribute + #define __has_cpp_attribute(x) 0 +#endif +#ifndef CYTHON_RESTRICT + #if defined(__GNUC__) + #define CYTHON_RESTRICT __restrict__ + #elif defined(_MSC_VER) && _MSC_VER >= 1400 + #define CYTHON_RESTRICT __restrict + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_RESTRICT restrict + #else + #define CYTHON_RESTRICT + #endif +#endif +#ifndef CYTHON_UNUSED +# if defined(__GNUC__) +# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +#endif +#ifndef CYTHON_MAYBE_UNUSED_VAR +# if defined(__cplusplus) + template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } +# else +# define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) +# endif +#endif +#ifndef CYTHON_NCP_UNUSED +# if CYTHON_COMPILING_IN_CPYTHON +# define CYTHON_NCP_UNUSED +# else +# define CYTHON_NCP_UNUSED CYTHON_UNUSED +# endif +#endif +#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) +#ifdef _MSC_VER + #ifndef _MSC_STDINT_H_ + #if _MSC_VER < 1300 + typedef unsigned char uint8_t; + typedef unsigned int uint32_t; + #else + typedef unsigned __int8 uint8_t; + typedef unsigned __int32 uint32_t; + #endif + #endif +#else + #include +#endif +#ifndef CYTHON_FALLTHROUGH + #if defined(__cplusplus) && __cplusplus >= 201103L + #if __has_cpp_attribute(fallthrough) + #define CYTHON_FALLTHROUGH [[fallthrough]] + #elif __has_cpp_attribute(clang::fallthrough) + #define CYTHON_FALLTHROUGH [[clang::fallthrough]] + #elif __has_cpp_attribute(gnu::fallthrough) + #define CYTHON_FALLTHROUGH [[gnu::fallthrough]] + #endif + #endif + #ifndef CYTHON_FALLTHROUGH + #if __has_attribute(fallthrough) + #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) + #else + #define CYTHON_FALLTHROUGH + #endif + #endif + #if defined(__clang__ ) && defined(__apple_build_version__) + #if __apple_build_version__ < 7000000 + #undef CYTHON_FALLTHROUGH + #define CYTHON_FALLTHROUGH + #endif + #endif +#endif + +#ifndef CYTHON_INLINE + #if defined(__clang__) + #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) + #elif defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_INLINE inline + #else + #define CYTHON_INLINE + #endif +#endif + +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) + #define Py_OptimizeFlag 0 +#endif +#define __PYX_BUILD_PY_SSIZE_T "n" +#define CYTHON_FORMAT_SSIZE_T "z" +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) + #define __Pyx_DefaultClassType PyClass_Type +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#endif + #define __Pyx_DefaultClassType PyType_Type +#endif +#ifndef Py_TPFLAGS_CHECKTYPES + #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif +#ifndef Py_TPFLAGS_HAVE_FINALIZE + #define Py_TPFLAGS_HAVE_FINALIZE 0 +#endif +#ifndef METH_STACKLESS + #define METH_STACKLESS 0 +#endif +#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) + #ifndef METH_FASTCALL + #define METH_FASTCALL 0x80 + #endif + typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); + typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, + Py_ssize_t nargs, PyObject *kwnames); +#else + #define __Pyx_PyCFunctionFast _PyCFunctionFast + #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords +#endif +#if CYTHON_FAST_PYCCALL +#define __Pyx_PyFastCFunction_Check(func)\ + ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) +#else +#define __Pyx_PyFastCFunction_Check(func) 0 +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) + #define PyObject_Malloc(s) PyMem_Malloc(s) + #define PyObject_Free(p) PyMem_Free(p) + #define PyObject_Realloc(p) PyMem_Realloc(p) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 + #define PyMem_RawMalloc(n) PyMem_Malloc(n) + #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) + #define PyMem_RawFree(p) PyMem_Free(p) +#endif +#if CYTHON_COMPILING_IN_PYSTON + #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) +#else + #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) +#endif +#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#elif PY_VERSION_HEX >= 0x03060000 + #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() +#elif PY_VERSION_HEX >= 0x03000000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#else + #define __Pyx_PyThreadState_Current _PyThreadState_Current +#endif +#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) +#include "pythread.h" +#define Py_tss_NEEDS_INIT 0 +typedef int Py_tss_t; +static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { + *key = PyThread_create_key(); + return 0; +} +static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { + Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); + *key = Py_tss_NEEDS_INIT; + return key; +} +static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { + PyObject_Free(key); +} +static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { + return *key != Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { + PyThread_delete_key(*key); + *key = Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { + return PyThread_set_key_value(*key, value); +} +static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { + return PyThread_get_key_value(*key); +} +#endif +#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) +#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) +#else +#define __Pyx_PyDict_NewPresized(n) PyDict_New() +#endif +#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS +#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) +#else +#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) +#endif +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) + #define CYTHON_PEP393_ENABLED 1 + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ + 0 : _PyUnicode_Ready((PyObject *)(op))) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) + #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) + #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) + #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif +#else + #define CYTHON_PEP393_ENABLED 0 + #define PyUnicode_1BYTE_KIND 1 + #define PyUnicode_2BYTE_KIND 2 + #define PyUnicode_4BYTE_KIND 4 + #define __Pyx_PyUnicode_READY(op) (0) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) + #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) + #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) + #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) +#endif +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) +#else + #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ + PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) + #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) + #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) +#endif +#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) +#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) +#else + #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) +#endif +#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) + #define PyObject_ASCII(o) PyObject_Repr(o) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode + #define PyObject_Unicode PyObject_Str +#endif +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) + #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) +#else + #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) + #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif +#if CYTHON_ASSUME_SAFE_MACROS + #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) +#else + #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define PyNumber_Int PyNumber_Long +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif +#if PY_VERSION_HEX < 0x030200A4 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t PyInt_AsLong +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) +#endif +#if CYTHON_USE_ASYNC_SLOTS + #if PY_VERSION_HEX >= 0x030500B1 + #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods + #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) + #else + #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) + #endif +#else + #define __Pyx_PyType_AsAsync(obj) NULL +#endif +#ifndef __Pyx_PyAsyncMethodsStruct + typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; + } __Pyx_PyAsyncMethodsStruct; +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include +#ifdef NAN +#define __PYX_NAN() ((float) NAN) +#else +static CYTHON_INLINE float __PYX_NAN() { + float value; + memset(&value, 0xFF, sizeof(value)); + return value; +} +#endif +#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) +#define __Pyx_truncl trunc +#else +#define __Pyx_truncl truncl +#endif + +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } +#define __PYX_ERR(f_index, lineno, Ln_error) \ + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#define __PYX_HAVE__stpredictions__models__OK3___quad_tree +#define __PYX_HAVE_API__stpredictions__models__OK3___quad_tree +/* Early includes */ +#include +#include +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + +#include "pythread.h" +#include +#include +#include "math.h" +#include "pystate.h" +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) +#define CYTHON_WITHOUT_ASSERTIONS +#endif + +typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; + const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; + +#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) +#define __PYX_DEFAULT_STRING_ENCODING "" +#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString +#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX))) ) +static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { + return (size_t) i < (size_t) limit; +} +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (_MSC_VER) + #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); +#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) +#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); +#if PY_MAJOR_VERSION < 3 + #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#else + #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize +#endif +#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { + const Py_UNICODE *u_end = u; + while (*u_end++) ; + return (size_t)(u_end - u - 1); +} +#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) +#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode +#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); +#define __Pyx_PySequence_Tuple(obj)\ + (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +#if CYTHON_ASSUME_SAFE_MACROS +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#else +#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) +#endif +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) +#else +#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) +#endif +#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII +static int __Pyx_sys_getdefaultencoding_not_ascii; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + PyObject* ascii_chars_u = NULL; + PyObject* ascii_chars_b = NULL; + const char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + if (strcmp(default_encoding_c, "ascii") == 0) { + __Pyx_sys_getdefaultencoding_not_ascii = 0; + } else { + char ascii_chars[128]; + int c; + for (c = 0; c < 128; c++) { + ascii_chars[c] = c; + } + __Pyx_sys_getdefaultencoding_not_ascii = 1; + ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); + if (!ascii_chars_u) goto bad; + ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); + if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { + PyErr_Format( + PyExc_ValueError, + "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", + default_encoding_c); + goto bad; + } + Py_DECREF(ascii_chars_u); + Py_DECREF(ascii_chars_b); + } + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + Py_XDECREF(ascii_chars_u); + Py_XDECREF(ascii_chars_b); + return -1; +} +#endif +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) +#else +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +static char* __PYX_DEFAULT_STRING_ENCODING; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); + if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; + strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + return -1; +} +#endif +#endif + + +/* Test for GCC > 2.95 */ +#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) +#else /* !__GNUC__ or GCC < 2.95 */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ +static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } + +static PyObject *__pyx_m = NULL; +static PyObject *__pyx_d; +static PyObject *__pyx_b; +static PyObject *__pyx_cython_runtime = NULL; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static PyObject *__pyx_empty_unicode; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +/* Header.proto */ +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + + +static const char *__pyx_f[] = { + "stpredictions/models/OK3/_quad_tree.pyx", + "stpredictions/models/OK3/_quad_tree.pxd", + "__init__.pxd", + "stringsource", + "type.pxd", + "bool.pxd", + "complex.pxd", + "stpredictions/models/OK3/_criterion.pxd", + "stpredictions/models/OK3/_splitter.pxd", + "stpredictions/models/OK3/_tree.pxd", + "stpredictions/models/OK3/_utils.pxd", +}; +/* ForceInitThreads.proto */ +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + +/* NoFastGil.proto */ +#define __Pyx_PyGILState_Ensure PyGILState_Ensure +#define __Pyx_PyGILState_Release PyGILState_Release +#define __Pyx_FastGIL_Remember() +#define __Pyx_FastGIL_Forget() +#define __Pyx_FastGilFuncInit() + +/* MemviewSliceStruct.proto */ +struct __pyx_memoryview_obj; +typedef struct { + struct __pyx_memoryview_obj *memview; + char *data; + Py_ssize_t shape[8]; + Py_ssize_t strides[8]; + Py_ssize_t suboffsets[8]; +} __Pyx_memviewslice; +#define __Pyx_MemoryView_Len(m) (m.shape[0]) + +/* Atomics.proto */ +#include +#ifndef CYTHON_ATOMICS + #define CYTHON_ATOMICS 1 +#endif +#define __pyx_atomic_int_type int +#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\ + (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\ + !defined(__i386__) + #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) + #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using GNU atomics" + #endif +#elif CYTHON_ATOMICS && defined(_MSC_VER) && 0 + #include + #undef __pyx_atomic_int_type + #define __pyx_atomic_int_type LONG + #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #pragma message ("Using MSVC atomics") + #endif +#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 + #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using Intel atomics" + #endif +#else + #undef CYTHON_ATOMICS + #define CYTHON_ATOMICS 0 + #ifdef __PYX_DEBUG_ATOMICS + #warning "Not using atomics" + #endif +#endif +typedef volatile __pyx_atomic_int_type __pyx_atomic_int; +#if CYTHON_ATOMICS + #define __pyx_add_acquisition_count(memview)\ + __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview)\ + __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) +#else + #define __pyx_add_acquisition_count(memview)\ + __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview)\ + __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) +#endif + +/* BufferFormatStructs.proto */ +#define IS_UNSIGNED(type) (((type) -1) > 0) +struct __Pyx_StructField_; +#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) +typedef struct { + const char* name; + struct __Pyx_StructField_* fields; + size_t size; + size_t arraysize[8]; + int ndim; + char typegroup; + char is_unsigned; + int flags; +} __Pyx_TypeInfo; +typedef struct __Pyx_StructField_ { + __Pyx_TypeInfo* type; + const char* name; + size_t offset; +} __Pyx_StructField; +typedef struct { + __Pyx_StructField* field; + size_t parent_offset; +} __Pyx_BufFmt_StackElem; +typedef struct { + __Pyx_StructField root; + __Pyx_BufFmt_StackElem* head; + size_t fmt_offset; + size_t new_count, enc_count; + size_t struct_alignment; + int is_complex; + char enc_type; + char new_packmode; + char enc_packmode; + char is_valid_array; +} __Pyx_BufFmt_Context; + + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":689 + * # in Cython to enable them only on the right systems. + * + * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + */ +typedef npy_int8 __pyx_t_5numpy_int8_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":690 + * + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t + */ +typedef npy_int16 __pyx_t_5numpy_int16_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":691 + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< + * ctypedef npy_int64 int64_t + * #ctypedef npy_int96 int96_t + */ +typedef npy_int32 __pyx_t_5numpy_int32_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":692 + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< + * #ctypedef npy_int96 int96_t + * #ctypedef npy_int128 int128_t + */ +typedef npy_int64 __pyx_t_5numpy_int64_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":696 + * #ctypedef npy_int128 int128_t + * + * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + */ +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":697 + * + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t + */ +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":698 + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< + * ctypedef npy_uint64 uint64_t + * #ctypedef npy_uint96 uint96_t + */ +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":699 + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< + * #ctypedef npy_uint96 uint96_t + * #ctypedef npy_uint128 uint128_t + */ +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":703 + * #ctypedef npy_uint128 uint128_t + * + * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< + * ctypedef npy_float64 float64_t + * #ctypedef npy_float80 float80_t + */ +typedef npy_float32 __pyx_t_5numpy_float32_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":704 + * + * ctypedef npy_float32 float32_t + * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< + * #ctypedef npy_float80 float80_t + * #ctypedef npy_float128 float128_t + */ +typedef npy_float64 __pyx_t_5numpy_float64_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":713 + * # The int types are mapped a bit surprising -- + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t + */ +typedef npy_long __pyx_t_5numpy_int_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":714 + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong longlong_t + * + */ +typedef npy_longlong __pyx_t_5numpy_long_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":715 + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_ulong uint_t + */ +typedef npy_longlong __pyx_t_5numpy_longlong_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":717 + * ctypedef npy_longlong longlong_t + * + * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t + */ +typedef npy_ulong __pyx_t_5numpy_uint_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":718 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":719 + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_intp intp_t + */ +typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":721 + * ctypedef npy_ulonglong ulonglong_t + * + * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< + * ctypedef npy_uintp uintp_t + * + */ +typedef npy_intp __pyx_t_5numpy_intp_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":722 + * + * ctypedef npy_intp intp_t + * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< + * + * ctypedef npy_double float_t + */ +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":724 + * ctypedef npy_uintp uintp_t + * + * ctypedef npy_double float_t # <<<<<<<<<<<<<< + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t + */ +typedef npy_double __pyx_t_5numpy_float_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":725 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":726 + * ctypedef npy_double float_t + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cfloat cfloat_t + */ +typedef npy_longdouble __pyx_t_5numpy_longdouble_t; + +/* "_tree.pxd":7 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t; + +/* "_tree.pxd":8 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t; + +/* "_tree.pxd":9 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t; + +/* "_tree.pxd":10 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t; + +/* "_tree.pxd":11 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * from _splitter cimport Splitter + */ +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t; + +/* "_utils.pxd":16 + * from ._quad_tree cimport Cell + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t; + +/* "_utils.pxd":17 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t; + +/* "_utils.pxd":18 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t; + +/* "_utils.pxd":19 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_6_utils_INT32_t; + +/* "_utils.pxd":20 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * + */ +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_6_utils_UINT32_t; + +/* "stpredictions/models/OK3/_quad_tree.pxd":13 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t; + +/* "stpredictions/models/OK3/_quad_tree.pxd":14 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t; + +/* "stpredictions/models/OK3/_quad_tree.pxd":15 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_INT32_t; + +/* "stpredictions/models/OK3/_quad_tree.pxd":16 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * # This is effectively an ifdef statement in Cython + */ +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_UINT32_t; +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< float > __pyx_t_float_complex; + #else + typedef float _Complex __pyx_t_float_complex; + #endif +#else + typedef struct { float real, imag; } __pyx_t_float_complex; +#endif +static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); + +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< double > __pyx_t_double_complex; + #else + typedef double _Complex __pyx_t_double_complex; + #endif +#else + typedef struct { double real, imag; } __pyx_t_double_complex; +#endif +static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); + + +/*--- Type declarations ---*/ +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; +struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree; +struct __pyx_array_obj; +struct __pyx_MemviewEnum_obj; +struct __pyx_memoryview_obj; +struct __pyx_memoryviewslice_obj; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":728 + * ctypedef npy_longdouble longdouble_t + * + * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t + */ +typedef npy_cfloat __pyx_t_5numpy_cfloat_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":729 + * + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< + * ctypedef npy_clongdouble clongdouble_t + * + */ +typedef npy_cdouble __pyx_t_5numpy_cdouble_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":730 + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cdouble complex_t + */ +typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":732 + * ctypedef npy_clongdouble clongdouble_t + * + * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< + * + * cdef inline object PyArray_MultiIterNew1(a): + */ +typedef npy_cdouble __pyx_t_5numpy_complex_t; +struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord; + +/* "_splitter.pxd":14 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef struct SplitRecord: # <<<<<<<<<<<<<< + * # Data to track sample split + * SIZE_t feature # Which feature to split on. + */ +struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t pos; + double threshold; + double improvement; + double impurity_left; + double impurity_right; +}; +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build; + +/* "_tree.pxd":16 + * from _splitter cimport SplitRecord + * + * cdef struct Node: # <<<<<<<<<<<<<< + * # Base storage structure for the nodes in a Tree object + * + */ +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t left_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t right_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t threshold; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t impurity; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t weighted_n_node_samples; +}; + +/* "_tree.pxd":52 + * double weighted_n_samples) nogil except -1 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * + * cdef np.ndarray _get_value_ndarray(self) + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c { + int __pyx_n; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; +}; + +/* "_tree.pxd":68 + * cdef object _decision_path_sparse_csr(self, object X) + * + * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< + * + * + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances { + int __pyx_n; + PyObject *normalize; +}; + +/* "_tree.pxd":92 + * cdef double min_impurity_decrease # Impurity threshold for early stopping + * + * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< + * np.ndarray sample_weight=*) + * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build { + int __pyx_n; + PyArrayObject *sample_weight; +}; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord; + +/* "_utils.pxd":23 + * + * + * cdef enum: # <<<<<<<<<<<<<< + * # Max value for our rand_r replacement (near the bottom). + * # We don't use RAND_MAX because it's different across platforms and + */ +enum { + __pyx_e_13stpredictions_6models_3OK3_6_utils_RAND_R_MAX = 0x7FFFFFFF +}; + +/* "_utils.pxd":70 + * + * # A record on the stack for depth-first tree growing + * cdef struct StackRecord: # <<<<<<<<<<<<<< + * SIZE_t start + * SIZE_t end + */ +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t depth; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t parent; + int is_left; + double impurity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t n_constant_features; +}; + +/* "_utils.pxd":96 + * + * # A record on the frontier for best-first tree growing + * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< + * SIZE_t node_id + * SIZE_t start + */ +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t node_id; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t pos; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t depth; + int is_leaf; + double impurity; + double impurity_left; + double impurity_right; + double improvement; +}; + +/* "_utils.pxd":127 + * + * # A record stored in the WeightedPQueue + * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< + * DOUBLE_t data + * DOUBLE_t weight + */ +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t data; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t weight; +}; +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell; + +/* "stpredictions/models/OK3/_quad_tree.pxd":21 + * # It allows us to write printf debugging lines + * # and remove them at compile time + * cdef enum: # <<<<<<<<<<<<<< + * DEBUGFLAG = 0 + * + */ +enum { + __pyx_e_13stpredictions_6models_3OK3_10_quad_tree_DEBUGFLAG = 0 +}; + +/* "stpredictions/models/OK3/_quad_tree.pxd":29 + * # have is_leaf and max_width consecutive as it permits to avoid padding by + * # the compiler and keep the size coherent for both C and numpy data structures. + * cdef struct Cell: # <<<<<<<<<<<<<< + * # Base storage structure for cells in a QuadTree object + * + */ +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell { + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t parent; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t children[8]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t point_index; + int is_leaf; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t squared_max_width; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t depth; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cumulative_size; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t center[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t barycenter[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t min_bounds[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t max_bounds[3]; +}; + +/* "stpredictions/models/OK3/_quad_tree.pxd":75 + * + * # Point insertion methods + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< + * SIZE_t cell_id=*) nogil except -1 + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point { + int __pyx_n; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; +}; + +/* "stpredictions/models/OK3/_quad_tree.pxd":77 + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, + * SIZE_t cell_id=*) nogil except -1 + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< + * SIZE_t point_index, SIZE_t size=* + * ) nogil + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child { + int __pyx_n; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t size; +}; + +/* "stpredictions/models/OK3/_quad_tree.pxd":84 + * + * # Create a summary of the Tree compare to a query point + * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< + * float squared_theta=*, SIZE_t cell_id=*, long idx=* + * ) nogil + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize { + int __pyx_n; + float squared_theta; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; + long idx; +}; + +/* "stpredictions/models/OK3/_quad_tree.pxd":99 + * # Private array manipulation to manage the ``cells`` array + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 + * cdef np.ndarray _get_cell_ndarray(self) + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c { + int __pyx_n; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t capacity; +}; + +/* "stpredictions/models/OK3/_quad_tree.pxd":100 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 + * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< + * cdef np.ndarray _get_cell_ndarray(self) + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell { + int __pyx_n; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; +}; + +/* "_criterion.pxd":12 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. + */ +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtab; + __Pyx_memviewslice y; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *sample_weight; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t pos; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; + double weighted_n_samples; + double weighted_n_node_samples; + double weighted_n_left; + double weighted_n_right; +}; + + +/* "_criterion.pxd":50 + * + * + * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract kernelized output regression criterion.""" + * + */ +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; + double sum_diag_Gramm; + double sum_total_Gramm; + double sum_diag_Gramm_left; + double sum_diag_Gramm_right; + double sum_total_Gramm_left; + double sum_total_Gramm_right; +}; + + +/* "_splitter.pxd":25 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtab; + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *criterion; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + PyObject *random_state; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t rand_r_state; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_samples; + double weighted_n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *constant_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *feature_values; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t end; + __Pyx_memviewslice y; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *sample_weight; +}; + + +/* "_tree.pxd":28 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. + */ +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t node_count; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; + PyArrayObject *K_y; + PyArrayObject *y; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *nodes; + double *value; +}; + + +/* "_tree.pxd":75 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtab; + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *splitter; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_split; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; + double min_impurity_split; + double min_impurity_decrease; +}; + + +/* "_utils.pxd":79 + * SIZE_t n_constant_features + * + * cdef class Stack: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t top + */ +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t top; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *stack_; +}; + + +/* "_utils.pxd":108 + * double improvement + * + * cdef class PriorityHeap: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t heap_ptr + */ +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t heap_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *heap_; +}; + + +/* "_utils.pxd":131 + * DOUBLE_t weight + * + * cdef class WeightedPQueue: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t array_ptr + */ +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t array_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *array_; +}; + + +/* "_utils.pxd":151 + * # ============================================================================= + * + * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< + * cdef SIZE_t initial_capacity + * cdef WeightedPQueue samples + */ +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t initial_capacity; + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *samples; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t total_weight; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t k; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t sum_w_0_k; +}; + + +/* "stpredictions/models/OK3/_quad_tree.pxd":55 + * + * + * cdef class _QuadTree: # <<<<<<<<<<<<<< + * # The QuadTree object is a quad tree structure constructed by inserting + * # recursively points in the tree and splitting cells in 4 so that each + */ +struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_vtab; + int n_dimensions; + int verbose; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t n_cells_per_cell; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_count; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t n_points; + struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *cells; +}; + + +/* "View.MemoryView":105 + * + * @cname("__pyx_array") + * cdef class array: # <<<<<<<<<<<<<< + * + * cdef: + */ +struct __pyx_array_obj { + PyObject_HEAD + struct __pyx_vtabstruct_array *__pyx_vtab; + char *data; + Py_ssize_t len; + char *format; + int ndim; + Py_ssize_t *_shape; + Py_ssize_t *_strides; + Py_ssize_t itemsize; + PyObject *mode; + PyObject *_format; + void (*callback_free_data)(void *); + int free_data; + int dtype_is_object; +}; + + +/* "View.MemoryView":279 + * + * @cname('__pyx_MemviewEnum') + * cdef class Enum(object): # <<<<<<<<<<<<<< + * cdef object name + * def __init__(self, name): + */ +struct __pyx_MemviewEnum_obj { + PyObject_HEAD + PyObject *name; +}; + + +/* "View.MemoryView":330 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ +struct __pyx_memoryview_obj { + PyObject_HEAD + struct __pyx_vtabstruct_memoryview *__pyx_vtab; + PyObject *obj; + PyObject *_size; + PyObject *_array_interface; + PyThread_type_lock lock; + __pyx_atomic_int acquisition_count[2]; + __pyx_atomic_int *acquisition_count_aligned_p; + Py_buffer view; + int flags; + int dtype_is_object; + __Pyx_TypeInfo *typeinfo; +}; + + +/* "View.MemoryView":965 + * + * @cname('__pyx_memoryviewslice') + * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< + * "Internal class for passing memoryview slices to Python" + * + */ +struct __pyx_memoryviewslice_obj { + struct __pyx_memoryview_obj __pyx_base; + __Pyx_memviewslice from_slice; + PyObject *from_object; + PyObject *(*to_object_func)(char *); + int (*to_dtype_func)(char *, PyObject *); +}; + + + +/* "_criterion.pxd":12 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion { + int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion; + + +/* "_criterion.pxd":50 + * + * + * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract kernelized output regression criterion.""" + * + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; + + +/* "_splitter.pxd":25 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter { + int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *); + int (*node_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double *); + int (*node_split)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *); + void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double *); + double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_Splitter; + + +/* "_tree.pxd":28 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int, int, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double); + int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c *__pyx_optional_args); + PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); + PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); + PyArrayObject *(*decode_tree)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyArrayObject *, PyArrayObject *, PyObject *, PyObject *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int __pyx_skip_dispatch); + PyArrayObject *(*predict)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*apply)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*_apply_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*decision_path)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyObject *(*_decision_path_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*compute_feature_importances)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_Tree; + + +/* "_tree.pxd":75 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder { + PyObject *(*build)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build *__pyx_optional_args); + PyObject *(*_check_input)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_TreeBuilder; + + +/* "_utils.pxd":79 + * SIZE_t n_constant_features + * + * cdef class Stack: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t top + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, int, double, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_Stack; + + +/* "_utils.pxd":108 + * double improvement + * + * cdef class PriorityHeap: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t heap_ptr + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *); + void (*heapify_up)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + void (*heapify_down)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, int, double, double, double, double); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_PriorityHeap; + + +/* "_utils.pxd":131 + * DOUBLE_t weight + * + * cdef class WeightedPQueue: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t array_ptr + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*size)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + int (*peek)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; + + +/* "_utils.pxd":151 + * # ============================================================================= + * + * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< + * cdef SIZE_t initial_capacity + * cdef WeightedPQueue samples + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*size)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); + int (*update_median_parameters_post_push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + int (*update_median_parameters_post_remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; + + +/* "stpredictions/models/OK3/_quad_tree.pyx":43 + * + * + * cdef class _QuadTree: # <<<<<<<<<<<<<< + * """Array-based representation of a QuadTree. + * + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree { + int (*insert_point)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *); + int (*_is_duplicate)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *); + long (*summarize)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); + void (*_init_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t); + void (*_init_root)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *); + int (*_check_point_in_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *); + int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); + int (*_get_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); + PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_vtabptr_13stpredictions_6models_3OK3_10_quad_tree__QuadTree; + + +/* "View.MemoryView":105 + * + * @cname("__pyx_array") + * cdef class array: # <<<<<<<<<<<<<< + * + * cdef: + */ + +struct __pyx_vtabstruct_array { + PyObject *(*get_memview)(struct __pyx_array_obj *); +}; +static struct __pyx_vtabstruct_array *__pyx_vtabptr_array; + + +/* "View.MemoryView":330 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ + +struct __pyx_vtabstruct_memoryview { + char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); + PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *); 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}} while(0) + #define __Pyx_XDECREF(r) do { if((r) != NULL) {__Pyx_DECREF(r); }} while(0) + #define __Pyx_XGOTREF(r) do { if((r) != NULL) {__Pyx_GOTREF(r); }} while(0) + #define __Pyx_XGIVEREF(r) do { if((r) != NULL) {__Pyx_GIVEREF(r);}} while(0) +#else + #define __Pyx_RefNannyDeclarations + #define __Pyx_RefNannySetupContext(name, acquire_gil) + #define __Pyx_RefNannyFinishContext() + #define __Pyx_INCREF(r) Py_INCREF(r) + #define __Pyx_DECREF(r) Py_DECREF(r) + #define __Pyx_GOTREF(r) + #define __Pyx_GIVEREF(r) + #define __Pyx_XINCREF(r) Py_XINCREF(r) + #define __Pyx_XDECREF(r) Py_XDECREF(r) + #define __Pyx_XGOTREF(r) + #define __Pyx_XGIVEREF(r) +#endif +#define __Pyx_XDECREF_SET(r, v) do {\ + PyObject *tmp = (PyObject *) r;\ + r = v; __Pyx_XDECREF(tmp);\ + } while (0) +#define __Pyx_DECREF_SET(r, v) do {\ + PyObject *tmp = (PyObject *) r;\ + r = v; __Pyx_DECREF(tmp);\ + } while (0) +#define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0) +#define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0) + +/* PyObjectGetAttrStr.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n) +#endif + +/* GetBuiltinName.proto */ +static PyObject *__Pyx_GetBuiltinName(PyObject *name); + +/* RaiseArgTupleInvalid.proto */ +static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, + Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found); + +/* RaiseDoubleKeywords.proto */ +static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); + +/* ParseKeywords.proto */ +static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ + PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ + const char* function_name); + +/* GetItemInt.proto */ +#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ + __Pyx_GetItemInt_Generic(o, to_py_func(i)))) +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck); + +/* ObjectGetItem.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key); +#else +#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) +#endif + +/* SliceObject.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice( + PyObject* obj, Py_ssize_t cstart, Py_ssize_t cstop, + PyObject** py_start, PyObject** py_stop, PyObject** py_slice, + int has_cstart, int has_cstop, int wraparound); + +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + +/* GetModuleGlobalName.proto */ +#if CYTHON_USE_DICT_VERSIONS +#define __Pyx_GetModuleGlobalName(var, name) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + (var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\ + (likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\ + __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +#define __Pyx_GetModuleGlobalNameUncached(var, name) {\ + PY_UINT64_T __pyx_dict_version;\ + PyObject *__pyx_dict_cached_value;\ + (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value); +#else +#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) +#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); +#endif + +/* PyObjectCall.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); +#else +#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) +#endif + +/* PyFloatBinop.proto */ +#if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyFloat_AddCObj(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check); +#else +#define __Pyx_PyFloat_AddCObj(op1, op2, floatval, inplace, zerodivision_check)\ + (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) +#endif + +/* PyCFunctionFastCall.proto */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); +#else +#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) +#endif + +/* PyFunctionFastCall.proto */ +#if CYTHON_FAST_PYCALL +#define __Pyx_PyFunction_FastCall(func, args, nargs)\ + __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); +#else +#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) +#endif +#define __Pyx_BUILD_ASSERT_EXPR(cond)\ + (sizeof(char [1 - 2*!(cond)]) - 1) +#ifndef Py_MEMBER_SIZE +#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) +#endif + static size_t __pyx_pyframe_localsplus_offset = 0; + #include "frameobject.h" + #define __Pxy_PyFrame_Initialize_Offsets()\ + ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ + (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) + #define __Pyx_PyFrame_GetLocalsplus(frame)\ + (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) +#endif + +/* PyObjectCall2Args.proto */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); + +/* PyObjectCallMethO.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); +#endif + +/* PyObjectCallOneArg.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); + +/* PyFloatBinop.proto */ +#if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyFloat_AddObjC(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check); +#else +#define __Pyx_PyFloat_AddObjC(op1, op2, floatval, inplace, zerodivision_check)\ + (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) +#endif + +/* PyThreadStateGet.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate; +#define __Pyx_PyThreadState_assign __pyx_tstate = __Pyx_PyThreadState_Current; +#define __Pyx_PyErr_Occurred() __pyx_tstate->curexc_type +#else +#define __Pyx_PyThreadState_declare +#define __Pyx_PyThreadState_assign +#define __Pyx_PyErr_Occurred() PyErr_Occurred() +#endif + +/* PyErrFetchRestore.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL) +#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) +#else +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#endif +#else +#define __Pyx_PyErr_Clear() PyErr_Clear() +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) +#endif + +/* WriteUnraisableException.proto */ +static void __Pyx_WriteUnraisable(const char *name, int clineno, + int lineno, const char *filename, + int full_traceback, int nogil); + +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + +/* PyObjectCallNoArg.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); +#else +#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) +#endif + +/* DictGetItem.proto */ +#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key); +#define __Pyx_PyObject_Dict_GetItem(obj, name)\ + (likely(PyDict_CheckExact(obj)) ?\ + __Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name)) +#else +#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) +#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name) +#endif + +/* PySequenceContains.proto */ +static CYTHON_INLINE int __Pyx_PySequence_ContainsTF(PyObject* item, PyObject* seq, int eq) { + int result = PySequence_Contains(seq, item); + return unlikely(result < 0) ? result : (result == (eq == Py_EQ)); +} + +/* PyIntCompare.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_NeObjC(PyObject *op1, PyObject *op2, long intval, long inplace); + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + +/* MemviewSliceInit.proto */ +#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d +#define __Pyx_MEMVIEW_DIRECT 1 +#define __Pyx_MEMVIEW_PTR 2 +#define __Pyx_MEMVIEW_FULL 4 +#define __Pyx_MEMVIEW_CONTIG 8 +#define __Pyx_MEMVIEW_STRIDED 16 +#define __Pyx_MEMVIEW_FOLLOW 32 +#define __Pyx_IS_C_CONTIG 1 +#define __Pyx_IS_F_CONTIG 2 +static int __Pyx_init_memviewslice( + struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference); +static CYTHON_INLINE int __pyx_add_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p) +#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview)) +#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__) +#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__) +static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); + +/* GetTopmostException.proto */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); +#endif + +/* SaveResetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +#else +#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) +#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) +#endif + +/* PyErrExceptionMatches.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) +static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); +#else +#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) +#endif + +/* GetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* IncludeStringH.proto */ +#include + +/* ArgTypeTest.proto */ +#define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\ + ((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\ + __Pyx__ArgTypeTest(obj, type, name, exact)) +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact); + +/* BytesEquals.proto */ +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); + +/* UnicodeEquals.proto */ +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals); + +/* StrEquals.proto */ +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals +#else +#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals +#endif + +/* UnaryNegOverflows.proto */ +#define UNARY_NEG_WOULD_OVERFLOW(x)\ + (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) + +static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/ +/* GetAttr.proto */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); + +/* decode_c_string_utf16.proto */ +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 0; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = -1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} + +/* decode_c_string.proto */ +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); + +/* GetAttr3.proto */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *); + +/* RaiseTooManyValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); + +/* RaiseNeedMoreValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); + +/* RaiseNoneIterError.proto */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); + +/* SwapException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* Import.proto */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + +/* FastTypeChecks.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); +#else +#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) +#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) +#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) +#endif +#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) + +static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +/* ListCompAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len)) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) +#endif + +/* PyIntBinop.proto */ +#if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); +#else +#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ + (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) +#endif + +/* ListExtend.proto */ +static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject* none = _PyList_Extend((PyListObject*)L, v); + if (unlikely(!none)) + return -1; + Py_DECREF(none); + return 0; +#else + return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v); +#endif +} + +/* ListAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_PyList_Append(L,x) PyList_Append(L,x) +#endif + +/* None.proto */ +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); + +/* ImportFrom.proto */ +static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); + +/* HasAttr.proto */ +static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *); + +/* StringJoin.proto */ +#if PY_MAJOR_VERSION < 3 +#define __Pyx_PyString_Join __Pyx_PyBytes_Join +#define __Pyx_PyBaseString_Join(s, v) (PyUnicode_CheckExact(s) ? PyUnicode_Join(s, v) : __Pyx_PyBytes_Join(s, v)) +#else +#define __Pyx_PyString_Join PyUnicode_Join +#define __Pyx_PyBaseString_Join PyUnicode_Join +#endif +#if CYTHON_COMPILING_IN_CPYTHON + #if PY_MAJOR_VERSION < 3 + #define __Pyx_PyBytes_Join _PyString_Join + #else + #define __Pyx_PyBytes_Join _PyBytes_Join + #endif +#else +static CYTHON_INLINE PyObject* __Pyx_PyBytes_Join(PyObject* sep, PyObject* values); +#endif + +/* PyObject_Unicode.proto */ +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyObject_Unicode(obj)\ + (likely(PyUnicode_CheckExact(obj)) ? __Pyx_NewRef(obj) : PyObject_Str(obj)) +#else +#define __Pyx_PyObject_Unicode(obj)\ + (likely(PyUnicode_CheckExact(obj)) ? __Pyx_NewRef(obj) : PyObject_Unicode(obj)) +#endif + +/* PyObject_GenericGetAttrNoDict.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr +#endif + +/* PyObject_GenericGetAttr.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr +#endif + +/* SetVTable.proto */ +static int __Pyx_SetVtable(PyObject *dict, void *vtable); + +/* PyObjectGetAttrStrNoError.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); + +/* SetupReduce.proto */ +static int __Pyx_setup_reduce(PyObject* type_obj); + +/* TypeImport.proto */ +#ifndef __PYX_HAVE_RT_ImportType_proto +#define __PYX_HAVE_RT_ImportType_proto +enum __Pyx_ImportType_CheckSize { + __Pyx_ImportType_CheckSize_Error = 0, + __Pyx_ImportType_CheckSize_Warn = 1, + __Pyx_ImportType_CheckSize_Ignore = 2 +}; +static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); +#endif + +/* GetVTable.proto */ +static void* __Pyx_GetVtable(PyObject *dict); + +/* CLineInTraceback.proto */ +#ifdef CYTHON_CLINE_IN_TRACEBACK +#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) +#else +static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); +#endif + +/* CodeObjectCache.proto */ +typedef struct { + PyCodeObject* code_object; + int code_line; +} __Pyx_CodeObjectCacheEntry; +struct __Pyx_CodeObjectCache { + int count; + int max_count; + __Pyx_CodeObjectCacheEntry* entries; +}; +static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); +static PyCodeObject *__pyx_find_code_object(int code_line); +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); + +/* AddTraceback.proto */ +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename); + +#if PY_MAJOR_VERSION < 3 + static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); + static void __Pyx_ReleaseBuffer(Py_buffer *view); +#else + #define __Pyx_GetBuffer PyObject_GetBuffer + #define __Pyx_ReleaseBuffer PyBuffer_Release +#endif + + +/* BufferStructDeclare.proto */ +typedef struct { + Py_ssize_t shape, strides, suboffsets; +} __Pyx_Buf_DimInfo; +typedef struct { + size_t refcount; + Py_buffer pybuffer; +} __Pyx_Buffer; +typedef struct { + __Pyx_Buffer *rcbuffer; + char *data; + __Pyx_Buf_DimInfo diminfo[8]; +} __Pyx_LocalBuf_ND; + +/* MemviewSliceIsContig.proto */ +static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); + +/* OverlappingSlices.proto */ +static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize); + +/* Capsule.proto */ +static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); + +/* GCCDiagnostics.proto */ +#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) +#define __Pyx_HAS_GCC_DIAGNOSTIC +#endif + +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell; +static PyObject* __pyx_convert__to_py_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell s); +/* MemviewDtypeToObject.proto */ +static CYTHON_INLINE PyObject *__pyx_memview_get_nn_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell(const char *itemp); +static CYTHON_INLINE int __pyx_memview_set_nn_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell(const char *itemp, PyObject *obj); + +/* IsLittleEndian.proto */ +static CYTHON_INLINE int __Pyx_Is_Little_Endian(void); + +/* BufferFormatCheck.proto */ +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts); +static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type); + +/* TypeInfoCompare.proto */ +static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); + +/* MemviewSliceValidateAndInit.proto */ +static int __Pyx_ValidateAndInit_memviewslice( + int *axes_specs, + int c_or_f_flag, + int buf_flags, + int ndim, + __Pyx_TypeInfo *dtype, + __Pyx_BufFmt_StackElem stack[], + __Pyx_memviewslice *memviewslice, + PyObject *original_obj); + +/* ObjectToMemviewSlice.proto */ +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(PyObject *, int writable_flag); + +/* ObjectToMemviewSlice.proto */ +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(PyObject *, int writable_flag); + +/* None.proto */ +static CYTHON_INLINE long __Pyx_pow_long(long, long); + +/* None.proto */ +static CYTHON_INLINE int __Pyx_ErrOccurredWithGIL(void); /* proto */ + +/* MemviewDtypeToObject.proto */ +static CYTHON_INLINE PyObject *__pyx_memview_get_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(const char *itemp); +static CYTHON_INLINE int __pyx_memview_set_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(const char *itemp, PyObject *obj); + +/* RealImag.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #define __Pyx_CREAL(z) ((z).real()) + #define __Pyx_CIMAG(z) ((z).imag()) + #else + #define __Pyx_CREAL(z) (__real__(z)) + #define __Pyx_CIMAG(z) (__imag__(z)) + #endif +#else + #define __Pyx_CREAL(z) ((z).real) + #define __Pyx_CIMAG(z) ((z).imag) +#endif +#if defined(__cplusplus) && CYTHON_CCOMPLEX\ + && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) + #define __Pyx_SET_CREAL(z,x) ((z).real(x)) + #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) +#else + #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) + #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_float(a, b) ((a)==(b)) + #define __Pyx_c_sum_float(a, b) ((a)+(b)) + #define __Pyx_c_diff_float(a, b) ((a)-(b)) + #define __Pyx_c_prod_float(a, b) ((a)*(b)) + #define __Pyx_c_quot_float(a, b) ((a)/(b)) + #define __Pyx_c_neg_float(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_float(z) ((z)==(float)0) + #define __Pyx_c_conj_float(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_float(z) (::std::abs(z)) + #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_float(z) ((z)==0) + #define __Pyx_c_conj_float(z) (conjf(z)) + #if 1 + #define __Pyx_c_abs_float(z) (cabsf(z)) + #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); + #endif +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_double(a, b) ((a)==(b)) + #define __Pyx_c_sum_double(a, b) ((a)+(b)) + #define __Pyx_c_diff_double(a, b) ((a)-(b)) + #define __Pyx_c_prod_double(a, b) ((a)*(b)) + #define __Pyx_c_quot_double(a, b) ((a)/(b)) + #define __Pyx_c_neg_double(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_double(z) ((z)==(double)0) + #define __Pyx_c_conj_double(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (::std::abs(z)) + #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_double(z) ((z)==0) + #define __Pyx_c_conj_double(z) (conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (cabs(z)) + #define __Pyx_c_pow_double(a, b) (cpow(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); + #endif +#endif + +/* MemviewSliceCopyTemplate.proto */ +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object); + +/* TypeInfoToFormat.proto */ +struct __pyx_typeinfo_string { + char string[3]; +}; +static struct __pyx_typeinfo_string __Pyx_TypeInfoToFormat(__Pyx_TypeInfo *type); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE size_t __Pyx_PyInt_As_size_t(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); + +/* CheckBinaryVersion.proto */ +static int __Pyx_check_binary_version(void); + +/* PyObjectSetAttrStr.proto */ +#if CYTHON_USE_TYPE_SLOTS +#define __Pyx_PyObject_DelAttrStr(o,n) __Pyx_PyObject_SetAttrStr(o, n, NULL) +static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value); +#else +#define __Pyx_PyObject_DelAttrStr(o,n) PyObject_DelAttr(o,n) +#define __Pyx_PyObject_SetAttrStr(o,n,v) PyObject_SetAttr(o,n,v) +#endif + +/* VoidPtrExport.proto */ +static int __Pyx_ExportVoidPtr(PyObject *name, void *p, const char *sig); + +/* FunctionImport.proto */ +static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig); + +/* InitStrings.proto */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); + +static int __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_point_index, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); /* proto*/ +static __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_v_cell, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_point_index, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__is_duplicate(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point1, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point2); /* proto*/ +static __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__select_child(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_v_cell); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__init_cell(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_v_cell, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_parent, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_depth); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__init_root(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_min_bounds, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_max_bounds); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__check_point_in_cell(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_v_cell); /* proto*/ +static long __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_results, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); /* proto*/ +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell_ndarray(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_capacity); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); /* proto*/ +static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ +static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ +static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ + +/* Module declarations from 'cpython.buffer' */ + +/* Module declarations from 'libc.string' */ + +/* Module declarations from 'libc.stdio' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.type' */ +static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; + +/* Module declarations from 'cpython.version' */ + +/* Module declarations from 'cpython.exc' */ + +/* Module declarations from 'cpython.module' */ + +/* Module declarations from 'cpython.mem' */ + +/* Module declarations from 'cpython.tuple' */ + +/* Module declarations from 'cpython.list' */ + +/* Module declarations from 'cpython.sequence' */ + +/* Module declarations from 'cpython.mapping' */ + +/* Module declarations from 'cpython.iterator' */ + +/* Module declarations from 'cpython.number' */ + +/* Module declarations from 'cpython.int' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.bool' */ +static PyTypeObject *__pyx_ptype_7cpython_4bool_bool = 0; + +/* Module declarations from 'cpython.long' */ + +/* Module declarations from 'cpython.float' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.complex' */ +static PyTypeObject *__pyx_ptype_7cpython_7complex_complex = 0; + +/* Module declarations from 'cpython.string' */ + +/* Module declarations from 'cpython.unicode' */ + +/* Module declarations from 'cpython.dict' */ + +/* Module declarations from 'cpython.instance' */ + +/* Module declarations from 'cpython.function' */ + +/* Module declarations from 'cpython.method' */ + +/* Module declarations from 'cpython.weakref' */ + +/* Module declarations from 'cpython.getargs' */ + +/* Module declarations from 'cpython.pythread' */ + +/* Module declarations from 'cpython.pystate' */ + +/* Module declarations from 'cpython.cobject' */ + +/* Module declarations from 'cpython.oldbuffer' */ + +/* Module declarations from 'cpython.set' */ + +/* Module declarations from 'cpython.bytes' */ + +/* Module declarations from 'cpython.pycapsule' */ + +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + +/* Module declarations from 'numpy' */ + +/* Module declarations from 'numpy' */ +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; 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/*proto*/ +static unsigned char *(*__pyx_fuse_2__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t ***, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *(*__pyx_fuse_6__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node **(*__pyx_fuse_8__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node ***, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord **, size_t); /*proto*/ + +/* Module declarations from 'stpredictions.models.OK3._quad_tree' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_quad_tree__QuadTree = 0; +static PyTypeObject *__pyx_array_type = 0; +static PyTypeObject *__pyx_MemviewEnum_type = 0; +static PyTypeObject *__pyx_memoryview_type = 0; +static PyTypeObject *__pyx_memoryviewslice_type = 0; +static float __pyx_v_13stpredictions_6models_3OK3_10_quad_tree_EPSILON; +static struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell __pyx_v_13stpredictions_6models_3OK3_10_quad_tree_dummy; +static PyObject *generic = 0; +static PyObject *strided = 0; +static PyObject *indirect = 0; +static PyObject *contiguous = 0; +static PyObject *indirect_contiguous = 0; +static int __pyx_memoryview_thread_locks_used; +static PyThread_type_lock __pyx_memoryview_thread_locks[8]; +static CYTHON_INLINE PyObject *__Pyx_carray_to_py___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t *, Py_ssize_t); /*proto*/ +static CYTHON_INLINE PyObject *__Pyx_carray_to_tuple___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t *, Py_ssize_t); /*proto*/ +static CYTHON_INLINE PyObject *__Pyx_carray_to_py___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, Py_ssize_t); /*proto*/ +static CYTHON_INLINE PyObject *__Pyx_carray_to_tuple___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, Py_ssize_t); /*proto*/ +static int __Pyx_carray_from_py___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t(PyObject *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t *, Py_ssize_t); /*proto*/ +static int __Pyx_carray_from_py___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(PyObject *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, Py_ssize_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell __pyx_convert__from_py_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell(PyObject *); /*proto*/ +static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ +static void *__pyx_align_pointer(void *, size_t); /*proto*/ +static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ +static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ +static PyObject *_unellipsify(PyObject *, int); /*proto*/ +static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ +static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ +static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ +static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); 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/*proto*/ +static PyObject *__pyx_format_from_typeinfo(__Pyx_TypeInfo *); /*proto*/ +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t = { "SIZE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t), 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t___5b_8_5d_ = { "SIZE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t), { 8 }, 1, IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t), 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_int = { "bint", NULL, sizeof(int), { 0 }, 0, IS_UNSIGNED(int) ? 'U' : 'I', IS_UNSIGNED(int), 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t = { "DTYPE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t___5b_3_5d_ = { "DTYPE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t), { 3 }, 1, 'R', 0, 0 }; +static __Pyx_StructField __Pyx_StructFields_nn_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell[] = { + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, "parent", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, parent)}, + {&__Pyx_TypeInfo___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t___5b_8_5d_, "children", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, children)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, "cell_id", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, cell_id)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, "point_index", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, point_index)}, + {&__Pyx_TypeInfo_int, "is_leaf", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, is_leaf)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t, "squared_max_width", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, squared_max_width)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, "depth", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, depth)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, "cumulative_size", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, cumulative_size)}, + {&__Pyx_TypeInfo___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t___5b_3_5d_, "center", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, center)}, + {&__Pyx_TypeInfo___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t___5b_3_5d_, "barycenter", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, barycenter)}, + {&__Pyx_TypeInfo___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t___5b_3_5d_, "min_bounds", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, min_bounds)}, + {&__Pyx_TypeInfo___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t___5b_3_5d_, "max_bounds", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, max_bounds)}, + {NULL, NULL, 0} +}; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell = { "Cell", __Pyx_StructFields_nn_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell, sizeof(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell), { 0 }, 0, 'S', 0, 0 }; +#define __Pyx_MODULE_NAME "stpredictions.models.OK3._quad_tree" +extern int __pyx_module_is_main_stpredictions__models__OK3___quad_tree; +int __pyx_module_is_main_stpredictions__models__OK3___quad_tree = 0; + +/* Implementation of 'stpredictions.models.OK3._quad_tree' */ +static PyObject *__pyx_builtin_range; +static PyObject *__pyx_builtin_ValueError; +static PyObject *__pyx_builtin_MemoryError; +static PyObject *__pyx_builtin_ImportError; +static PyObject *__pyx_builtin_TypeError; +static PyObject *__pyx_builtin_OverflowError; +static PyObject *__pyx_builtin_enumerate; +static PyObject *__pyx_builtin_IndexError; +static PyObject *__pyx_builtin_KeyError; +static PyObject *__pyx_builtin_Ellipsis; +static PyObject *__pyx_builtin_id; +static const char __pyx_k_O[] = "O"; +static const char __pyx_k_T[] = "T{"; + static const char __pyx_k_X[] = "X"; + static const char __pyx_k_c[] = "c"; + static const char __pyx_k_s[] = "(%s)"; + static const char __pyx_k_id[] = "id"; + static const char __pyx_k_np[] = "np"; + static const char __pyx_k__38[] = "^"; + static const char __pyx_k__39[] = ""; + static const char __pyx_k__40[] = ":"; +static const char __pyx_k__41[] = "}"; +static const char __pyx_k__42[] = ","; +static const char __pyx_k_max[] = "max"; +static const char __pyx_k_min[] = "min"; +static const char __pyx_k_new[] = "__new__"; +static const char __pyx_k_obj[] = "obj"; +static const char __pyx_k_axis[] = "axis"; +static const char __pyx_k_base[] = "base"; +static const char __pyx_k_dict[] = "__dict__"; +static const char __pyx_k_join[] = "join"; +static const char __pyx_k_main[] = "__main__"; +static const char __pyx_k_mode[] = "mode"; +static const char __pyx_k_name[] = "name"; +static const char __pyx_k_ndim[] = "ndim"; +static const char __pyx_k_pack[] = "pack"; +static const char __pyx_k_sign[] = "sign"; +static const char __pyx_k_size[] = "size"; +static const char __pyx_k_step[] = "step"; +static const char __pyx_k_stop[] = "stop"; +static const char __pyx_k_test[] = "__test__"; +static const char __pyx_k_ASCII[] = "ASCII"; +static const char __pyx_k_angle[] = "angle"; +static const char __pyx_k_cells[] = "cells"; +static const char __pyx_k_class[] = "__class__"; +static const char __pyx_k_depth[] = "depth"; +static const char __pyx_k_dtype[] = "dtype"; +static const char __pyx_k_empty[] = "empty"; +static const char __pyx_k_error[] = "error"; +static const char __pyx_k_flags[] = "flags"; +static const char __pyx_k_numpy[] = "numpy"; +static const char __pyx_k_range[] = "range"; +static const char __pyx_k_shape[] = "shape"; +static const char __pyx_k_start[] = "start"; +static const char __pyx_k_center[] = "center"; +static const char __pyx_k_encode[] = "encode"; +static const char __pyx_k_format[] = "format"; +static const char __pyx_k_import[] = "__import__"; +static const char __pyx_k_name_2[] = "__name__"; +static const char __pyx_k_parent[] = "parent"; +static const char __pyx_k_pickle[] = "pickle"; +static const char __pyx_k_reduce[] = "__reduce__"; +static const char __pyx_k_struct[] = "struct"; +static const char __pyx_k_unpack[] = "unpack"; +static const char __pyx_k_update[] = "update"; +static const char __pyx_k_EPSILON[] = "EPSILON"; +static const char __pyx_k_asarray[] = "asarray"; +static const char __pyx_k_cell_id[] = "cell_id"; +static const char __pyx_k_float32[] = "float32"; +static const char __pyx_k_fortran[] = "fortran"; +static const char __pyx_k_is_leaf[] = "is_leaf"; +static const char __pyx_k_maximum[] = "maximum"; +static const char __pyx_k_memview[] = "memview"; +static const char __pyx_k_verbose[] = "verbose"; +static const char __pyx_k_Ellipsis[] = "Ellipsis"; +static const char __pyx_k_KeyError[] = "KeyError"; +static const char __pyx_k_QuadTree[] = "_QuadTree"; +static const char __pyx_k_capacity[] = "capacity"; +static const char __pyx_k_children[] = "children"; +static const char __pyx_k_getstate[] = "__getstate__"; +static const char __pyx_k_itemsize[] = "itemsize"; +static const char __pyx_k_n_points[] = "n_points"; +static const char __pyx_k_pyx_capi[] = "__pyx_capi__"; +static const char __pyx_k_pyx_type[] = "__pyx_type"; +static const char __pyx_k_query_pt[] = "query_pt"; +static const char __pyx_k_setstate[] = "__setstate__"; +static const char __pyx_k_TypeError[] = "TypeError"; +static const char __pyx_k_enumerate[] = "enumerate"; +static const char __pyx_k_max_depth[] = "max_depth"; +static const char __pyx_k_pyx_state[] = "__pyx_state"; +static const char __pyx_k_reduce_ex[] = "__reduce_ex__"; +static const char __pyx_k_CELL_DTYPE[] = "CELL_DTYPE"; +static const char __pyx_k_IndexError[] = "IndexError"; +static const char __pyx_k_ValueError[] = "ValueError"; +static const char __pyx_k_barycenter[] = "barycenter"; +static const char __pyx_k_cell_count[] = "cell_count"; +static const char __pyx_k_max_bounds[] = "max_bounds"; +static const char __pyx_k_min_bounds[] = "min_bounds"; +static const char __pyx_k_pyx_result[] = "__pyx_result"; +static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; +static const char __pyx_k_ImportError[] = "ImportError"; +static const char __pyx_k_MemoryError[] = "MemoryError"; +static const char __pyx_k_PickleError[] = "PickleError"; +static const char __pyx_k_point_index[] = "point_index"; +static const char __pyx_k_c_contiguous[] = "c_contiguous"; +static const char __pyx_k_n_dimensions[] = "n_dimensions"; +static const char __pyx_k_pyx_checksum[] = "__pyx_checksum"; +static const char __pyx_k_stringsource[] = "stringsource"; +static const char __pyx_k_OverflowError[] = "OverflowError"; +static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; +static const char __pyx_k_reduce_cython[] = "__reduce_cython__"; +static const char __pyx_k_View_MemoryView[] = "View.MemoryView"; +static const char __pyx_k_allocate_buffer[] = "allocate_buffer"; +static const char __pyx_k_cumulative_size[] = "cumulative_size"; +static const char __pyx_k_dtype_is_object[] = "dtype_is_object"; +static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError"; +static const char __pyx_k_setstate_cython[] = "__setstate_cython__"; +static const char __pyx_k_pyx_unpickle_Enum[] = "__pyx_unpickle_Enum"; +static const char __pyx_k_squared_max_width[] = "squared_max_width"; +static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; +static const char __pyx_k_resizing_tree_to_d[] = "resizing tree to %d"; +static const char __pyx_k_strided_and_direct[] = ""; +static const char __pyx_k_strided_and_indirect[] = ""; +static const char __pyx_k_Can_t_intialize_array[] = "Can't intialize array!"; +static const char __pyx_k_contiguous_and_direct[] = ""; +static const char __pyx_k_MemoryView_of_r_object[] = ""; +static const char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; +static const char __pyx_k_contiguous_and_indirect[] = ""; +static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; +static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; +static const char __pyx_k_Query_point_not_in_the_Tree[] = "Query point not in the Tree."; +static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; +static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; +static const char __pyx_k_strided_and_direct_or_indirect[] = ""; +static const char __pyx_k_QuadTree_InsertionError_point_o[] = "[QuadTree] InsertionError: point out of cell "; +static const char __pyx_k_QuadTree_is_incoherent_Size_but[] = "QuadTree is incoherent. Size={} but found {} points in children."; +static const char __pyx_k_boundary_Axis_li_cell_f_f_point[] = "boundary.\nAxis %li: cell [%f, %f]; point %f\n"; +static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; +static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; +static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; +static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview"; +static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview"; +static const char __pyx_k_Cell_id_not_correctly_initiliaze[] = "Cell id not correctly initiliazed."; +static const char __pyx_k_Cell_is_incoherent_Size_but_foun[] = "Cell {} is incoherent. Size={} but found {} points in children. ({})"; +static const char __pyx_k_Did_not_recognise_loaded_array_l[] = "Did not recognise loaded array layout"; +static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; +static const char __pyx_k_Incompatible_checksums_s_vs_0xb0[] = "Incompatible checksums (%s vs 0xb068931 = (name))"; +static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; +static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; +static const char __pyx_k_No_value_specified_for_struct_at[] = "No value specified for struct attribute 'parent'"; +static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; +static const char __pyx_k_Query_point_should_be_a_point_in[] = "Query point should be a point in dimension {}."; +static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; +static const char __pyx_k_You_have_loaded_Tree_version_whi[] = "You have loaded Tree version which cannot be imported"; +static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; +static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; +static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; +static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; +static const char __pyx_k_No_value_specified_for_struct_at_2[] = "No value specified for struct attribute 'children'"; +static const char __pyx_k_No_value_specified_for_struct_at_3[] = "No value specified for struct attribute 'cell_id'"; +static const char __pyx_k_No_value_specified_for_struct_at_4[] = "No value specified for struct attribute 'point_index'"; +static const char __pyx_k_No_value_specified_for_struct_at_5[] = "No value specified for struct attribute 'is_leaf'"; +static const char __pyx_k_No_value_specified_for_struct_at_6[] = "No value specified for struct attribute 'squared_max_width'"; +static const char __pyx_k_No_value_specified_for_struct_at_7[] = "No value specified for struct attribute 'depth'"; +static const char __pyx_k_No_value_specified_for_struct_at_8[] = "No value specified for struct attribute 'cumulative_size'"; +static const char __pyx_k_No_value_specified_for_struct_at_9[] = "No value specified for struct attribute 'center'"; +static const char __pyx_k_No_value_specified_for_struct_at_10[] = "No value specified for struct attribute 'barycenter'"; +static const char __pyx_k_No_value_specified_for_struct_at_11[] = "No value specified for struct attribute 'min_bounds'"; +static const char __pyx_k_No_value_specified_for_struct_at_12[] = "No value specified for struct attribute 'max_bounds'"; +static PyObject *__pyx_n_s_ASCII; +static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; +static PyObject *__pyx_n_s_CELL_DTYPE; +static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; +static PyObject *__pyx_kp_s_Can_t_intialize_array; +static PyObject *__pyx_kp_s_Cannot_assign_to_read_only_memor; +static PyObject *__pyx_kp_s_Cannot_create_writable_memory_vi; +static PyObject *__pyx_kp_s_Cannot_index_with_type_s; +static PyObject *__pyx_kp_s_Cell_id_not_correctly_initiliaze; +static PyObject *__pyx_kp_s_Cell_is_incoherent_Size_but_foun; +static PyObject *__pyx_kp_s_Did_not_recognise_loaded_array_l; +static PyObject *__pyx_n_s_EPSILON; +static PyObject *__pyx_n_s_Ellipsis; +static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; +static PyObject *__pyx_n_s_ImportError; +static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xb0; +static PyObject *__pyx_n_s_IndexError; +static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; +static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; +static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; +static PyObject *__pyx_n_s_KeyError; +static PyObject *__pyx_n_s_MemoryError; +static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; +static PyObject *__pyx_kp_s_MemoryView_of_r_object; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_10; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_11; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_12; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_2; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_3; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_4; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_5; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_6; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_7; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_8; +static PyObject *__pyx_kp_s_No_value_specified_for_struct_at_9; +static PyObject *__pyx_n_b_O; +static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; +static PyObject *__pyx_n_s_OverflowError; +static PyObject *__pyx_n_s_PickleError; +static PyObject *__pyx_n_s_QuadTree; +static PyObject *__pyx_kp_s_QuadTree_InsertionError_point_o; +static PyObject *__pyx_kp_s_QuadTree_is_incoherent_Size_but; +static PyObject *__pyx_kp_s_Query_point_not_in_the_Tree; +static PyObject *__pyx_kp_s_Query_point_should_be_a_point_in; +static PyObject *__pyx_kp_b_T; +static PyObject *__pyx_n_s_TypeError; +static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; +static PyObject *__pyx_n_s_ValueError; +static PyObject *__pyx_n_s_View_MemoryView; +static PyObject *__pyx_n_s_X; +static PyObject *__pyx_kp_s_You_have_loaded_Tree_version_whi; +static PyObject *__pyx_kp_b__38; +static PyObject *__pyx_kp_b__39; +static PyObject *__pyx_kp_b__40; +static PyObject *__pyx_kp_b__41; +static PyObject *__pyx_kp_u__42; +static PyObject *__pyx_n_s_allocate_buffer; +static PyObject *__pyx_n_s_angle; +static PyObject *__pyx_n_s_asarray; +static PyObject *__pyx_n_s_axis; +static PyObject *__pyx_n_s_barycenter; +static PyObject *__pyx_n_s_base; +static PyObject *__pyx_kp_s_boundary_Axis_li_cell_f_f_point; +static PyObject *__pyx_n_s_c; +static PyObject *__pyx_n_u_c; +static PyObject *__pyx_n_s_c_contiguous; +static PyObject *__pyx_n_s_capacity; +static PyObject *__pyx_n_s_cell_count; +static PyObject *__pyx_n_s_cell_id; +static PyObject *__pyx_n_s_cells; +static PyObject *__pyx_n_s_center; +static PyObject *__pyx_n_s_children; +static PyObject *__pyx_n_s_class; +static PyObject *__pyx_n_s_cline_in_traceback; +static PyObject *__pyx_kp_s_contiguous_and_direct; +static PyObject *__pyx_kp_s_contiguous_and_indirect; +static PyObject *__pyx_n_s_cumulative_size; +static PyObject *__pyx_n_s_depth; +static PyObject *__pyx_n_s_dict; +static PyObject *__pyx_n_s_dtype; +static PyObject *__pyx_n_s_dtype_is_object; +static PyObject *__pyx_n_s_empty; +static PyObject *__pyx_n_s_encode; +static PyObject *__pyx_n_s_enumerate; +static PyObject *__pyx_n_s_error; +static PyObject *__pyx_n_s_flags; +static PyObject *__pyx_n_s_float32; +static PyObject *__pyx_n_s_format; +static PyObject *__pyx_n_s_fortran; +static PyObject *__pyx_n_u_fortran; +static PyObject *__pyx_n_s_getstate; +static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; +static PyObject *__pyx_n_s_id; +static PyObject *__pyx_n_s_import; +static PyObject *__pyx_n_s_is_leaf; +static PyObject *__pyx_n_s_itemsize; +static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; +static PyObject *__pyx_n_s_join; +static PyObject *__pyx_n_s_main; +static PyObject *__pyx_n_s_max; +static PyObject *__pyx_n_s_max_bounds; +static PyObject *__pyx_n_s_max_depth; +static PyObject *__pyx_n_s_maximum; +static PyObject *__pyx_n_s_memview; +static PyObject *__pyx_n_s_min; +static PyObject *__pyx_n_s_min_bounds; +static PyObject *__pyx_n_s_mode; +static PyObject *__pyx_n_s_n_dimensions; +static PyObject *__pyx_n_s_n_points; +static PyObject *__pyx_n_s_name; +static PyObject *__pyx_n_s_name_2; +static PyObject *__pyx_n_s_ndim; +static PyObject *__pyx_n_s_new; +static PyObject *__pyx_kp_s_no_default___reduce___due_to_non; +static PyObject *__pyx_n_s_np; +static PyObject *__pyx_n_s_numpy; +static PyObject *__pyx_kp_s_numpy_core_multiarray_failed_to; +static PyObject *__pyx_kp_s_numpy_core_umath_failed_to_impor; +static PyObject *__pyx_n_s_obj; +static PyObject *__pyx_n_s_pack; +static PyObject *__pyx_n_s_parent; +static PyObject *__pyx_n_s_pickle; +static PyObject *__pyx_n_s_point_index; +static PyObject *__pyx_n_s_pyx_PickleError; +static PyObject *__pyx_n_s_pyx_capi; +static PyObject *__pyx_n_s_pyx_checksum; +static PyObject *__pyx_n_s_pyx_getbuffer; +static PyObject *__pyx_n_s_pyx_result; +static PyObject *__pyx_n_s_pyx_state; +static PyObject *__pyx_n_s_pyx_type; +static PyObject *__pyx_n_s_pyx_unpickle_Enum; +static PyObject *__pyx_n_s_pyx_vtable; +static PyObject *__pyx_n_s_query_pt; +static PyObject *__pyx_n_s_range; +static PyObject *__pyx_n_s_reduce; +static PyObject *__pyx_n_s_reduce_cython; +static PyObject *__pyx_n_s_reduce_ex; +static PyObject *__pyx_kp_s_resizing_tree_to_d; +static PyObject *__pyx_kp_u_s; +static PyObject *__pyx_n_s_setstate; +static PyObject *__pyx_n_s_setstate_cython; +static PyObject *__pyx_n_s_shape; +static PyObject *__pyx_n_s_sign; +static PyObject *__pyx_n_s_size; +static PyObject *__pyx_n_s_squared_max_width; +static PyObject *__pyx_n_s_start; +static PyObject *__pyx_n_s_step; +static PyObject *__pyx_n_s_stop; +static PyObject *__pyx_kp_s_strided_and_direct; +static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; +static PyObject *__pyx_kp_s_strided_and_indirect; +static PyObject *__pyx_kp_s_stringsource; +static PyObject *__pyx_n_s_struct; +static PyObject *__pyx_n_s_test; +static PyObject *__pyx_kp_s_unable_to_allocate_array_data; +static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; +static PyObject *__pyx_n_s_unpack; +static PyObject *__pyx_n_s_update; +static PyObject *__pyx_n_s_verbose; +static int __pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, int __pyx_v_n_dimensions, int __pyx_v_verbose); /* proto */ +static void __pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_15cumulative_size___get__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_5leafs___get__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_4build_tree(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_6_check_coherence(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_8get_cell(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, PyObject *__pyx_v_point); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_10__reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_12__getstate__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_14__setstate__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, PyObject *__pyx_v_d); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_16_py_summarize(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __Pyx_memviewslice __pyx_v_query_pt, __Pyx_memviewslice __pyx_v_X, float __pyx_v_angle); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_12n_dimensions___get__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_12n_dimensions_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_7verbose___get__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_7verbose_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_9max_depth___get__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_9max_depth_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_10cell_count___get__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_10cell_count_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_8capacity___get__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_8capacity_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_8n_points___get__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_8n_points_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_12__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf___pyx_array___reduce_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_array_2__setstate_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ +static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_MemviewEnum___reduce_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_MemviewEnum_2__setstate_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ +static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryview___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryview_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryviewslice___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView___pyx_unpickle_Enum(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_10_quad_tree__QuadTree(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_float_1_; +static PyObject *__pyx_float_1eneg_3; +static PyObject *__pyx_int_0; +static PyObject *__pyx_int_1; +static PyObject *__pyx_int_184977713; +static PyObject *__pyx_int_neg_1; +static __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_k__5; +static PyObject *__pyx_tuple_; +static PyObject *__pyx_tuple__2; +static PyObject *__pyx_tuple__3; +static PyObject *__pyx_tuple__4; +static PyObject *__pyx_tuple__6; +static PyObject *__pyx_tuple__7; +static PyObject *__pyx_tuple__8; +static PyObject *__pyx_tuple__9; +static PyObject *__pyx_slice__34; +static PyObject *__pyx_tuple__10; +static PyObject *__pyx_tuple__11; +static PyObject *__pyx_tuple__12; +static PyObject *__pyx_tuple__13; +static PyObject *__pyx_tuple__14; +static PyObject *__pyx_tuple__15; +static PyObject *__pyx_tuple__16; +static PyObject *__pyx_tuple__17; +static PyObject *__pyx_tuple__18; +static PyObject *__pyx_tuple__19; +static PyObject *__pyx_tuple__20; +static PyObject *__pyx_tuple__21; +static PyObject *__pyx_tuple__22; +static PyObject *__pyx_tuple__23; +static PyObject *__pyx_tuple__24; +static PyObject *__pyx_tuple__25; +static PyObject *__pyx_tuple__26; +static PyObject *__pyx_tuple__27; +static PyObject *__pyx_tuple__28; +static PyObject *__pyx_tuple__29; 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+ + /* "stpredictions/models/OK3/_quad_tree.pyx":126 + * cdef SIZE_t selected_child + * cdef Cell* cell = &self.cells[cell_id] + * cdef SIZE_t n_point = cell.cumulative_size # <<<<<<<<<<<<<< + * + * if self.verbose > 10: + */ + __pyx_t_1 = __pyx_v_cell->cumulative_size; + __pyx_v_n_point = __pyx_t_1; + + /* "stpredictions/models/OK3/_quad_tree.pyx":128 + * cdef SIZE_t n_point = cell.cumulative_size + * + * if self.verbose > 10: # <<<<<<<<<<<<<< + * printf("[QuadTree] Inserting depth %li\n", cell.depth) + * + */ + __pyx_t_2 = ((__pyx_v_self->verbose > 10) != 0); + if (__pyx_t_2) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":129 + * + * if self.verbose > 10: + * printf("[QuadTree] Inserting depth %li\n", cell.depth) # <<<<<<<<<<<<<< + * + * # Assert that the point is in the right range + */ + (void)(printf(((char const *)"[QuadTree] Inserting depth %li\n"), __pyx_v_cell->depth)); + + /* "stpredictions/models/OK3/_quad_tree.pyx":128 + * cdef SIZE_t n_point = cell.cumulative_size + * + * if self.verbose > 10: # <<<<<<<<<<<<<< + * printf("[QuadTree] Inserting depth %li\n", cell.depth) + * + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":132 + * + * # Assert that the point is in the right range + * if DEBUGFLAG: # <<<<<<<<<<<<<< + * self._check_point_in_cell(point, cell) + * + */ + if (__pyx_e_13stpredictions_6models_3OK3_10_quad_tree_DEBUGFLAG) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":133 + * # Assert that the point is in the right range + * if DEBUGFLAG: + * self._check_point_in_cell(point, cell) # <<<<<<<<<<<<<< + * + * # If the cell is an empty leaf, insert the point in it + */ + __pyx_t_3 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->_check_point_in_cell(__pyx_v_self, __pyx_v_point, __pyx_v_cell); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(0, 133, __pyx_L1_error) + + /* "stpredictions/models/OK3/_quad_tree.pyx":132 + * + * # Assert that the point is in the right range + * if DEBUGFLAG: # <<<<<<<<<<<<<< + * self._check_point_in_cell(point, cell) + * + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":136 + * + * # If the cell is an empty leaf, insert the point in it + * if cell.cumulative_size == 0: # <<<<<<<<<<<<<< + * cell.cumulative_size = 1 + * self.n_points += 1 + */ + __pyx_t_2 = ((__pyx_v_cell->cumulative_size == 0) != 0); + if (__pyx_t_2) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":137 + * # If the cell is an empty leaf, insert the point in it + * if cell.cumulative_size == 0: + * cell.cumulative_size = 1 # <<<<<<<<<<<<<< + * self.n_points += 1 + * for i in range(self.n_dimensions): + */ + __pyx_v_cell->cumulative_size = 1; + + /* "stpredictions/models/OK3/_quad_tree.pyx":138 + * if cell.cumulative_size == 0: + * cell.cumulative_size = 1 + * self.n_points += 1 # <<<<<<<<<<<<<< + * for i in range(self.n_dimensions): + * cell.barycenter[i] = point[i] + */ + __pyx_v_self->n_points = (__pyx_v_self->n_points + 1); + + /* "stpredictions/models/OK3/_quad_tree.pyx":139 + * cell.cumulative_size = 1 + * self.n_points += 1 + * for i in range(self.n_dimensions): # <<<<<<<<<<<<<< + * cell.barycenter[i] = point[i] + * cell.point_index = point_index + */ + __pyx_t_3 = __pyx_v_self->n_dimensions; + __pyx_t_4 = __pyx_t_3; + for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_i = __pyx_t_5; + + /* "stpredictions/models/OK3/_quad_tree.pyx":140 + * self.n_points += 1 + * for i in range(self.n_dimensions): + * cell.barycenter[i] = point[i] # <<<<<<<<<<<<<< + * cell.point_index = point_index + * if self.verbose > 10: + */ + (__pyx_v_cell->barycenter[__pyx_v_i]) = (__pyx_v_point[__pyx_v_i]); + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":141 + * for i in range(self.n_dimensions): + * cell.barycenter[i] = point[i] + * cell.point_index = point_index # <<<<<<<<<<<<<< + * if self.verbose > 10: + * printf("[QuadTree] inserted point %li in cell %li\n", + */ + __pyx_v_cell->point_index = __pyx_v_point_index; + + /* "stpredictions/models/OK3/_quad_tree.pyx":142 + * cell.barycenter[i] = point[i] + * cell.point_index = point_index + * if self.verbose > 10: # <<<<<<<<<<<<<< + * printf("[QuadTree] inserted point %li in cell %li\n", + * point_index, cell_id) + */ + __pyx_t_2 = ((__pyx_v_self->verbose > 10) != 0); + if (__pyx_t_2) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":143 + * cell.point_index = point_index + * if self.verbose > 10: + * printf("[QuadTree] inserted point %li in cell %li\n", # <<<<<<<<<<<<<< + * point_index, cell_id) + * return cell_id + */ + (void)(printf(((char const *)"[QuadTree] inserted point %li in cell %li\n"), __pyx_v_point_index, __pyx_v_cell_id)); + + /* "stpredictions/models/OK3/_quad_tree.pyx":142 + * cell.barycenter[i] = point[i] + * cell.point_index = point_index + * if self.verbose > 10: # <<<<<<<<<<<<<< + * printf("[QuadTree] inserted point %li in cell %li\n", + * point_index, cell_id) + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":145 + * printf("[QuadTree] inserted point %li in cell %li\n", + * point_index, cell_id) + * return cell_id # <<<<<<<<<<<<<< + * + * # If the cell is not a leaf, update cell internals and + */ + __pyx_r = __pyx_v_cell_id; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":136 + * + * # If the cell is an empty leaf, insert the point in it + * if cell.cumulative_size == 0: # <<<<<<<<<<<<<< + * cell.cumulative_size = 1 + * self.n_points += 1 + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":149 + * # If the cell is not a leaf, update cell internals and + * # recurse in selected child + * if not cell.is_leaf: # <<<<<<<<<<<<<< + * for ax in range(self.n_dimensions): + * # barycenter update using a weighted mean + */ + __pyx_t_2 = ((!(__pyx_v_cell->is_leaf != 0)) != 0); + if (__pyx_t_2) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":150 + * # recurse in selected child + * if not cell.is_leaf: + * for ax in range(self.n_dimensions): # <<<<<<<<<<<<<< + * # barycenter update using a weighted mean + * cell.barycenter[ax] = ( + */ + __pyx_t_3 = __pyx_v_self->n_dimensions; + __pyx_t_4 = __pyx_t_3; + for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_ax = __pyx_t_5; + + /* "stpredictions/models/OK3/_quad_tree.pyx":152 + * for ax in range(self.n_dimensions): + * # barycenter update using a weighted mean + * cell.barycenter[ax] = ( # <<<<<<<<<<<<<< + * n_point * cell.barycenter[ax] + point[ax]) / (n_point + 1) + * + */ + (__pyx_v_cell->barycenter[__pyx_v_ax]) = (((__pyx_v_n_point * (__pyx_v_cell->barycenter[__pyx_v_ax])) + (__pyx_v_point[__pyx_v_ax])) / (__pyx_v_n_point + 1)); + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":156 + * + * # Increase the size of the subtree starting from this cell + * cell.cumulative_size += 1 # <<<<<<<<<<<<<< + * + * # Insert child in the correct subtree + */ + __pyx_v_cell->cumulative_size = (__pyx_v_cell->cumulative_size + 1); + + /* "stpredictions/models/OK3/_quad_tree.pyx":159 + * + * # Insert child in the correct subtree + * selected_child = self._select_child(point, cell) # <<<<<<<<<<<<<< + * if self.verbose > 49: + * printf("[QuadTree] selected child %li\n", selected_child) + */ + __pyx_v_selected_child = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->_select_child(__pyx_v_self, __pyx_v_point, __pyx_v_cell); + + /* "stpredictions/models/OK3/_quad_tree.pyx":160 + * # Insert child in the correct subtree + * selected_child = self._select_child(point, cell) + * if self.verbose > 49: # <<<<<<<<<<<<<< + * printf("[QuadTree] selected child %li\n", selected_child) + * if selected_child == -1: + */ + __pyx_t_2 = ((__pyx_v_self->verbose > 49) != 0); + if (__pyx_t_2) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":161 + * selected_child = self._select_child(point, cell) + * if self.verbose > 49: + * printf("[QuadTree] selected child %li\n", selected_child) # <<<<<<<<<<<<<< + * if selected_child == -1: + * self.n_points += 1 + */ + (void)(printf(((char const *)"[QuadTree] selected child %li\n"), __pyx_v_selected_child)); + + /* "stpredictions/models/OK3/_quad_tree.pyx":160 + * # Insert child in the correct subtree + * selected_child = self._select_child(point, cell) + * if self.verbose > 49: # <<<<<<<<<<<<<< + * printf("[QuadTree] selected child %li\n", selected_child) + * if selected_child == -1: + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":162 + * if self.verbose > 49: + * printf("[QuadTree] selected child %li\n", selected_child) + * if selected_child == -1: # <<<<<<<<<<<<<< + * self.n_points += 1 + * return self._insert_point_in_new_child(point, cell, point_index) + */ + __pyx_t_2 = ((__pyx_v_selected_child == -1L) != 0); + if (__pyx_t_2) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":163 + * printf("[QuadTree] selected child %li\n", selected_child) + * if selected_child == -1: + * self.n_points += 1 # <<<<<<<<<<<<<< + * return self._insert_point_in_new_child(point, cell, point_index) + * return self.insert_point(point, point_index, selected_child) + */ + __pyx_v_self->n_points = (__pyx_v_self->n_points + 1); + + /* "stpredictions/models/OK3/_quad_tree.pyx":164 + * if selected_child == -1: + * self.n_points += 1 + * return self._insert_point_in_new_child(point, cell, point_index) # <<<<<<<<<<<<<< + * return self.insert_point(point, point_index, selected_child) + * + */ + __pyx_r = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->_insert_point_in_new_child(__pyx_v_self, __pyx_v_point, __pyx_v_cell, __pyx_v_point_index, NULL); + goto __pyx_L0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":162 + * if self.verbose > 49: + * printf("[QuadTree] selected child %li\n", selected_child) + * if selected_child == -1: # <<<<<<<<<<<<<< + * self.n_points += 1 + * return self._insert_point_in_new_child(point, cell, point_index) + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":165 + * self.n_points += 1 + * return self._insert_point_in_new_child(point, cell, point_index) + * return self.insert_point(point, point_index, selected_child) # <<<<<<<<<<<<<< + * + * # Finally, if the cell is a leaf with a point already inserted, + */ + __pyx_t_6.__pyx_n = 1; + __pyx_t_6.cell_id = __pyx_v_selected_child; + __pyx_t_3 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->insert_point(__pyx_v_self, __pyx_v_point, __pyx_v_point_index, &__pyx_t_6); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(0, 165, __pyx_L1_error) + __pyx_r = __pyx_t_3; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":149 + * # If the cell is not a leaf, update cell internals and + * # recurse in selected child + * if not cell.is_leaf: # <<<<<<<<<<<<<< + * for ax in range(self.n_dimensions): + * # barycenter update using a weighted mean + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":170 + * # split the cell in n_cells_per_cell if the point is not a duplicate. + * # If it is a duplicate, increase the size of the leaf and return. + * if self._is_duplicate(point, cell.barycenter): # <<<<<<<<<<<<<< + * if self.verbose > 10: + * printf("[QuadTree] found a duplicate!\n") + */ + __pyx_t_2 = (((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->_is_duplicate(__pyx_v_self, __pyx_v_point, __pyx_v_cell->barycenter) != 0); + if (__pyx_t_2) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":171 + * # If it is a duplicate, increase the size of the leaf and return. + * if self._is_duplicate(point, cell.barycenter): + * if self.verbose > 10: # <<<<<<<<<<<<<< + * printf("[QuadTree] found a duplicate!\n") + * cell.cumulative_size += 1 + */ + __pyx_t_2 = ((__pyx_v_self->verbose > 10) != 0); + if (__pyx_t_2) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":172 + * if self._is_duplicate(point, cell.barycenter): + * if self.verbose > 10: + * printf("[QuadTree] found a duplicate!\n") # <<<<<<<<<<<<<< + * cell.cumulative_size += 1 + * self.n_points += 1 + */ + (void)(printf(((char const *)"[QuadTree] found a duplicate!\n"))); + + /* "stpredictions/models/OK3/_quad_tree.pyx":171 + * # If it is a duplicate, increase the size of the leaf and return. + * if self._is_duplicate(point, cell.barycenter): + * if self.verbose > 10: # <<<<<<<<<<<<<< + * printf("[QuadTree] found a duplicate!\n") + * cell.cumulative_size += 1 + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":173 + * if self.verbose > 10: + * printf("[QuadTree] found a duplicate!\n") + * cell.cumulative_size += 1 # <<<<<<<<<<<<<< + * self.n_points += 1 + * return cell_id + */ + __pyx_v_cell->cumulative_size = (__pyx_v_cell->cumulative_size + 1); + + /* "stpredictions/models/OK3/_quad_tree.pyx":174 + * printf("[QuadTree] found a duplicate!\n") + * cell.cumulative_size += 1 + * self.n_points += 1 # <<<<<<<<<<<<<< + * return cell_id + * + */ + __pyx_v_self->n_points = (__pyx_v_self->n_points + 1); + + /* "stpredictions/models/OK3/_quad_tree.pyx":175 + * cell.cumulative_size += 1 + * self.n_points += 1 + * return cell_id # <<<<<<<<<<<<<< + * + * # In a leaf, the barycenter correspond to the only point included + */ + __pyx_r = __pyx_v_cell_id; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":170 + * # split the cell in n_cells_per_cell if the point is not a duplicate. + * # If it is a duplicate, increase the size of the leaf and return. + * if self._is_duplicate(point, cell.barycenter): # <<<<<<<<<<<<<< + * if self.verbose > 10: + * printf("[QuadTree] found a duplicate!\n") + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":179 + * # In a leaf, the barycenter correspond to the only point included + * # in it. + * self._insert_point_in_new_child(cell.barycenter, cell, cell.point_index, # <<<<<<<<<<<<<< + * cell.cumulative_size) + * return self.insert_point(point, point_index, cell_id) + */ + __pyx_t_7.__pyx_n = 1; + __pyx_t_7.size = __pyx_v_cell->cumulative_size; + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->_insert_point_in_new_child(__pyx_v_self, __pyx_v_cell->barycenter, __pyx_v_cell, __pyx_v_cell->point_index, &__pyx_t_7); + + /* "stpredictions/models/OK3/_quad_tree.pyx":181 + * self._insert_point_in_new_child(cell.barycenter, cell, cell.point_index, + * cell.cumulative_size) + * return self.insert_point(point, point_index, cell_id) # <<<<<<<<<<<<<< + * + * # XXX: This operation is not Thread safe + */ + __pyx_t_6.__pyx_n = 1; + __pyx_t_6.cell_id = __pyx_v_cell_id; + __pyx_t_3 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->insert_point(__pyx_v_self, __pyx_v_point, __pyx_v_point_index, &__pyx_t_6); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(0, 181, __pyx_L1_error) + __pyx_r = __pyx_t_3; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":119 + * self._resize(capacity=self.cell_count) + * + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< + * SIZE_t cell_id=0) nogil except -1: + * """Insert a point in the QuadTree.""" + */ + + /* function exit code */ + __pyx_L1_error:; + { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); + #endif + __Pyx_AddTraceback("stpredictions.models.OK3._quad_tree._QuadTree.insert_point", __pyx_clineno, __pyx_lineno, __pyx_filename); + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + } + __pyx_r = -1; + __pyx_L0:; + return __pyx_r; +} + +/* "stpredictions/models/OK3/_quad_tree.pyx":184 + * + * # XXX: This operation is not Thread safe + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< + * SIZE_t point_index, SIZE_t size=1 + * ) nogil: + */ + +static __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_v_cell, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_point_index, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args) { + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_size = ((__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t)1); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_cell_child_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_parent_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t __pyx_v_save_point[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t __pyx_v_width; + struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_v_child; + int __pyx_v_i; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_r; + int __pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_t_2; + int __pyx_t_3; + int __pyx_t_4; + int __pyx_t_5; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t __pyx_t_6; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t __pyx_t_7; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t __pyx_t_8; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + if (__pyx_optional_args) { + if (__pyx_optional_args->__pyx_n > 0) { + __pyx_v_size = __pyx_optional_args->size; + } + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":200 + * # We need to save the current cell id and the current point to retrieve them + * # in case the reallocation + * if self.cell_count + 1 > self.capacity: # <<<<<<<<<<<<<< + * parent_id = cell.cell_id + * for i in range(self.n_dimensions): + */ + __pyx_t_1 = (((__pyx_v_self->cell_count + 1) > __pyx_v_self->capacity) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":201 + * # in case the reallocation + * if self.cell_count + 1 > self.capacity: + * parent_id = cell.cell_id # <<<<<<<<<<<<<< + * for i in range(self.n_dimensions): + * save_point[i] = point[i] + */ + __pyx_t_2 = __pyx_v_cell->cell_id; + __pyx_v_parent_id = __pyx_t_2; + + /* "stpredictions/models/OK3/_quad_tree.pyx":202 + * if self.cell_count + 1 > self.capacity: + * parent_id = cell.cell_id + * for i in range(self.n_dimensions): # <<<<<<<<<<<<<< + * save_point[i] = point[i] + * self._resize(SIZE_MAX) + */ + __pyx_t_3 = __pyx_v_self->n_dimensions; + __pyx_t_4 = __pyx_t_3; + for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_i = __pyx_t_5; + + /* "stpredictions/models/OK3/_quad_tree.pyx":203 + * parent_id = cell.cell_id + * for i in range(self.n_dimensions): + * save_point[i] = point[i] # <<<<<<<<<<<<<< + * self._resize(SIZE_MAX) + * cell = &self.cells[parent_id] + */ + (__pyx_v_save_point[__pyx_v_i]) = (__pyx_v_point[__pyx_v_i]); + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":204 + * for i in range(self.n_dimensions): + * save_point[i] = point[i] + * self._resize(SIZE_MAX) # <<<<<<<<<<<<<< + * cell = &self.cells[parent_id] + * point = save_point + */ + __pyx_t_3 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->_resize(__pyx_v_self, SIZE_MAX); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(0, 204, __pyx_L1_error) + + /* "stpredictions/models/OK3/_quad_tree.pyx":205 + * save_point[i] = point[i] + * self._resize(SIZE_MAX) + * cell = &self.cells[parent_id] # <<<<<<<<<<<<<< + * point = save_point + * + */ + __pyx_v_cell = (&(__pyx_v_self->cells[__pyx_v_parent_id])); + + /* "stpredictions/models/OK3/_quad_tree.pyx":206 + * self._resize(SIZE_MAX) + * cell = &self.cells[parent_id] + * point = save_point # <<<<<<<<<<<<<< + * + * # Get an empty cell and initialize it + */ + __pyx_v_point = __pyx_v_save_point; + + /* "stpredictions/models/OK3/_quad_tree.pyx":200 + * # We need to save the current cell id and the current point to retrieve them + * # in case the reallocation + * if self.cell_count + 1 > self.capacity: # <<<<<<<<<<<<<< + * parent_id = cell.cell_id + * for i in range(self.n_dimensions): + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":209 + * + * # Get an empty cell and initialize it + * cell_id = self.cell_count # <<<<<<<<<<<<<< + * self.cell_count += 1 + * child = &self.cells[cell_id] + */ + __pyx_t_2 = __pyx_v_self->cell_count; + __pyx_v_cell_id = __pyx_t_2; + + /* "stpredictions/models/OK3/_quad_tree.pyx":210 + * # Get an empty cell and initialize it + * cell_id = self.cell_count + * self.cell_count += 1 # <<<<<<<<<<<<<< + * child = &self.cells[cell_id] + * + */ + __pyx_v_self->cell_count = (__pyx_v_self->cell_count + 1); + + /* "stpredictions/models/OK3/_quad_tree.pyx":211 + * cell_id = self.cell_count + * self.cell_count += 1 + * child = &self.cells[cell_id] # <<<<<<<<<<<<<< + * + * self._init_cell(child, cell.cell_id, cell.depth + 1) + */ + __pyx_v_child = (&(__pyx_v_self->cells[__pyx_v_cell_id])); + + /* "stpredictions/models/OK3/_quad_tree.pyx":213 + * child = &self.cells[cell_id] + * + * self._init_cell(child, cell.cell_id, cell.depth + 1) # <<<<<<<<<<<<<< + * child.cell_id = cell_id + * + */ + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->_init_cell(__pyx_v_self, __pyx_v_child, __pyx_v_cell->cell_id, (__pyx_v_cell->depth + 1)); + + /* "stpredictions/models/OK3/_quad_tree.pyx":214 + * + * self._init_cell(child, cell.cell_id, cell.depth + 1) + * child.cell_id = cell_id # <<<<<<<<<<<<<< + * + * # Set the cell as an inner cell of the Tree + */ + __pyx_v_child->cell_id = __pyx_v_cell_id; + + /* "stpredictions/models/OK3/_quad_tree.pyx":217 + * + * # Set the cell as an inner cell of the Tree + * cell.is_leaf = False # <<<<<<<<<<<<<< + * cell.point_index = -1 + * + */ + __pyx_v_cell->is_leaf = 0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":218 + * # Set the cell as an inner cell of the Tree + * cell.is_leaf = False + * cell.point_index = -1 # <<<<<<<<<<<<<< + * + * # Set the correct boundary for the cell, store the point in the cell + */ + __pyx_v_cell->point_index = -1; + + /* "stpredictions/models/OK3/_quad_tree.pyx":222 + * # Set the correct boundary for the cell, store the point in the cell + * # and compute its index in the children array. + * cell_child_id = 0 # <<<<<<<<<<<<<< + * for i in range(self.n_dimensions): + * cell_child_id *= 2 + */ + __pyx_v_cell_child_id = 0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":223 + * # and compute its index in the children array. + * cell_child_id = 0 + * for i in range(self.n_dimensions): # <<<<<<<<<<<<<< + * cell_child_id *= 2 + * if point[i] >= cell.center[i]: + */ + __pyx_t_3 = __pyx_v_self->n_dimensions; + __pyx_t_4 = __pyx_t_3; + for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_i = __pyx_t_5; + + /* "stpredictions/models/OK3/_quad_tree.pyx":224 + * cell_child_id = 0 + * for i in range(self.n_dimensions): + * cell_child_id *= 2 # <<<<<<<<<<<<<< + * if point[i] >= cell.center[i]: + * cell_child_id += 1 + */ + __pyx_v_cell_child_id = (__pyx_v_cell_child_id * 2); + + /* "stpredictions/models/OK3/_quad_tree.pyx":225 + * for i in range(self.n_dimensions): + * cell_child_id *= 2 + * if point[i] >= cell.center[i]: # <<<<<<<<<<<<<< + * cell_child_id += 1 + * child.min_bounds[i] = cell.center[i] + */ + __pyx_t_1 = (((__pyx_v_point[__pyx_v_i]) >= (__pyx_v_cell->center[__pyx_v_i])) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":226 + * cell_child_id *= 2 + * if point[i] >= cell.center[i]: + * cell_child_id += 1 # <<<<<<<<<<<<<< + * child.min_bounds[i] = cell.center[i] + * child.max_bounds[i] = cell.max_bounds[i] + */ + __pyx_v_cell_child_id = (__pyx_v_cell_child_id + 1); + + /* "stpredictions/models/OK3/_quad_tree.pyx":227 + * if point[i] >= cell.center[i]: + * cell_child_id += 1 + * child.min_bounds[i] = cell.center[i] # <<<<<<<<<<<<<< + * child.max_bounds[i] = cell.max_bounds[i] + * else: + */ + (__pyx_v_child->min_bounds[__pyx_v_i]) = (__pyx_v_cell->center[__pyx_v_i]); + + /* "stpredictions/models/OK3/_quad_tree.pyx":228 + * cell_child_id += 1 + * child.min_bounds[i] = cell.center[i] + * child.max_bounds[i] = cell.max_bounds[i] # <<<<<<<<<<<<<< + * else: + * child.min_bounds[i] = cell.min_bounds[i] + */ + (__pyx_v_child->max_bounds[__pyx_v_i]) = (__pyx_v_cell->max_bounds[__pyx_v_i]); + + /* "stpredictions/models/OK3/_quad_tree.pyx":225 + * for i in range(self.n_dimensions): + * cell_child_id *= 2 + * if point[i] >= cell.center[i]: # <<<<<<<<<<<<<< + * cell_child_id += 1 + * child.min_bounds[i] = cell.center[i] + */ + goto __pyx_L8; + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":230 + * child.max_bounds[i] = cell.max_bounds[i] + * else: + * child.min_bounds[i] = cell.min_bounds[i] # <<<<<<<<<<<<<< + * child.max_bounds[i] = cell.center[i] + * child.center[i] = (child.min_bounds[i] + child.max_bounds[i]) / 2. + */ + /*else*/ { + (__pyx_v_child->min_bounds[__pyx_v_i]) = (__pyx_v_cell->min_bounds[__pyx_v_i]); + + /* "stpredictions/models/OK3/_quad_tree.pyx":231 + * else: + * child.min_bounds[i] = cell.min_bounds[i] + * child.max_bounds[i] = cell.center[i] # <<<<<<<<<<<<<< + * child.center[i] = (child.min_bounds[i] + child.max_bounds[i]) / 2. + * width = child.max_bounds[i] - child.min_bounds[i] + */ + (__pyx_v_child->max_bounds[__pyx_v_i]) = (__pyx_v_cell->center[__pyx_v_i]); + } + __pyx_L8:; + + /* "stpredictions/models/OK3/_quad_tree.pyx":232 + * child.min_bounds[i] = cell.min_bounds[i] + * child.max_bounds[i] = cell.center[i] + * child.center[i] = (child.min_bounds[i] + child.max_bounds[i]) / 2. # <<<<<<<<<<<<<< + * width = child.max_bounds[i] - child.min_bounds[i] + * + */ + (__pyx_v_child->center[__pyx_v_i]) = (((__pyx_v_child->min_bounds[__pyx_v_i]) + (__pyx_v_child->max_bounds[__pyx_v_i])) / 2.); + + /* "stpredictions/models/OK3/_quad_tree.pyx":233 + * child.max_bounds[i] = cell.center[i] + * child.center[i] = (child.min_bounds[i] + child.max_bounds[i]) / 2. + * width = child.max_bounds[i] - child.min_bounds[i] # <<<<<<<<<<<<<< + * + * child.barycenter[i] = point[i] + */ + __pyx_v_width = ((__pyx_v_child->max_bounds[__pyx_v_i]) - (__pyx_v_child->min_bounds[__pyx_v_i])); + + /* "stpredictions/models/OK3/_quad_tree.pyx":235 + * width = child.max_bounds[i] - child.min_bounds[i] + * + * child.barycenter[i] = point[i] # <<<<<<<<<<<<<< + * child.squared_max_width = max(child.squared_max_width, width*width) + * + */ + (__pyx_v_child->barycenter[__pyx_v_i]) = (__pyx_v_point[__pyx_v_i]); + + /* "stpredictions/models/OK3/_quad_tree.pyx":236 + * + * child.barycenter[i] = point[i] + * child.squared_max_width = max(child.squared_max_width, width*width) # <<<<<<<<<<<<<< + * + * # Store the point info and the size to account for duplicated points + */ + __pyx_t_6 = (__pyx_v_width * __pyx_v_width); + __pyx_t_7 = __pyx_v_child->squared_max_width; + if (((__pyx_t_6 > __pyx_t_7) != 0)) { + __pyx_t_8 = __pyx_t_6; + } else { + __pyx_t_8 = __pyx_t_7; + } + __pyx_v_child->squared_max_width = __pyx_t_8; + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":239 + * + * # Store the point info and the size to account for duplicated points + * child.point_index = point_index # <<<<<<<<<<<<<< + * child.cumulative_size = size + * + */ + __pyx_v_child->point_index = __pyx_v_point_index; + + /* "stpredictions/models/OK3/_quad_tree.pyx":240 + * # Store the point info and the size to account for duplicated points + * child.point_index = point_index + * child.cumulative_size = size # <<<<<<<<<<<<<< + * + * # Store the child cell in the correct place in children + */ + __pyx_v_child->cumulative_size = __pyx_v_size; + + /* "stpredictions/models/OK3/_quad_tree.pyx":243 + * + * # Store the child cell in the correct place in children + * cell.children[cell_child_id] = child.cell_id # <<<<<<<<<<<<<< + * + * if DEBUGFLAG: + */ + __pyx_t_2 = __pyx_v_child->cell_id; + (__pyx_v_cell->children[__pyx_v_cell_child_id]) = __pyx_t_2; + + /* "stpredictions/models/OK3/_quad_tree.pyx":245 + * cell.children[cell_child_id] = child.cell_id + * + * if DEBUGFLAG: # <<<<<<<<<<<<<< + * # Assert that the point is in the right range + * self._check_point_in_cell(point, child) + */ + if (__pyx_e_13stpredictions_6models_3OK3_10_quad_tree_DEBUGFLAG) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":247 + * if DEBUGFLAG: + * # Assert that the point is in the right range + * self._check_point_in_cell(point, child) # <<<<<<<<<<<<<< + * if self.verbose > 10: + * printf("[QuadTree] inserted point %li in new child %li\n", + */ + __pyx_t_3 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->_check_point_in_cell(__pyx_v_self, __pyx_v_point, __pyx_v_child); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(0, 247, __pyx_L1_error) + + /* "stpredictions/models/OK3/_quad_tree.pyx":245 + * cell.children[cell_child_id] = child.cell_id + * + * if DEBUGFLAG: # <<<<<<<<<<<<<< + * # Assert that the point is in the right range + * self._check_point_in_cell(point, child) + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":248 + * # Assert that the point is in the right range + * self._check_point_in_cell(point, child) + * if self.verbose > 10: # <<<<<<<<<<<<<< + * printf("[QuadTree] inserted point %li in new child %li\n", + * point_index, cell_id) + */ + __pyx_t_1 = ((__pyx_v_self->verbose > 10) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":249 + * self._check_point_in_cell(point, child) + * if self.verbose > 10: + * printf("[QuadTree] inserted point %li in new child %li\n", # <<<<<<<<<<<<<< + * point_index, cell_id) + * + */ + (void)(printf(((char const *)"[QuadTree] inserted point %li in new child %li\n"), __pyx_v_point_index, __pyx_v_cell_id)); + + /* "stpredictions/models/OK3/_quad_tree.pyx":248 + * # Assert that the point is in the right range + * self._check_point_in_cell(point, child) + * if self.verbose > 10: # <<<<<<<<<<<<<< + * printf("[QuadTree] inserted point %li in new child %li\n", + * point_index, cell_id) + */ + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":252 + * point_index, cell_id) + * + * return cell_id # <<<<<<<<<<<<<< + * + * + */ + __pyx_r = __pyx_v_cell_id; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":184 + * + * # XXX: This operation is not Thread safe + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< + * SIZE_t point_index, SIZE_t size=1 + * ) nogil: + */ + + /* function exit code */ + __pyx_L1_error:; + __Pyx_WriteUnraisable("stpredictions.models.OK3._quad_tree._QuadTree._insert_point_in_new_child", __pyx_clineno, __pyx_lineno, __pyx_filename, 1, 1); + __pyx_r = 0; + __pyx_L0:; + return __pyx_r; +} + +/* "stpredictions/models/OK3/_quad_tree.pyx":255 + * + * + * cdef bint _is_duplicate(self, DTYPE_t[3] point1, DTYPE_t[3] point2) nogil: # <<<<<<<<<<<<<< + * """Check if the two given points are equals.""" + * cdef int i + */ + +static int __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__is_duplicate(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point1, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point2) { + int __pyx_v_i; + int __pyx_v_res; + int __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + + /* "stpredictions/models/OK3/_quad_tree.pyx":258 + * """Check if the two given points are equals.""" + * cdef int i + * cdef bint res = True # <<<<<<<<<<<<<< + * for i in range(self.n_dimensions): + * # Use EPSILON to avoid numerical error that would overgrow the tree + */ + __pyx_v_res = 1; + + /* "stpredictions/models/OK3/_quad_tree.pyx":259 + * cdef int i + * cdef bint res = True + * for i in range(self.n_dimensions): # <<<<<<<<<<<<<< + * # Use EPSILON to avoid numerical error that would overgrow the tree + * res &= fabsf(point1[i] - point2[i]) <= EPSILON + */ + __pyx_t_1 = __pyx_v_self->n_dimensions; + __pyx_t_2 = __pyx_t_1; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "stpredictions/models/OK3/_quad_tree.pyx":261 + * for i in range(self.n_dimensions): + * # Use EPSILON to avoid numerical error that would overgrow the tree + * res &= fabsf(point1[i] - point2[i]) <= EPSILON # <<<<<<<<<<<<<< + * return res + * + */ + __pyx_v_res = (__pyx_v_res & (fabsf(((__pyx_v_point1[__pyx_v_i]) - (__pyx_v_point2[__pyx_v_i]))) <= __pyx_v_13stpredictions_6models_3OK3_10_quad_tree_EPSILON)); + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":262 + * # Use EPSILON to avoid numerical error that would overgrow the tree + * res &= fabsf(point1[i] - point2[i]) <= EPSILON + * return res # <<<<<<<<<<<<<< + * + * + */ + __pyx_r = __pyx_v_res; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":255 + * + * + * cdef bint _is_duplicate(self, DTYPE_t[3] point1, DTYPE_t[3] point2) nogil: # <<<<<<<<<<<<<< + * """Check if the two given points are equals.""" + * cdef int i + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "stpredictions/models/OK3/_quad_tree.pyx":265 + * + * + * cdef SIZE_t _select_child(self, DTYPE_t[3] point, Cell* cell) nogil: # <<<<<<<<<<<<<< + * """Select the child of cell which contains the given query point.""" + * cdef: + */ + +static __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__select_child(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_v_cell) { + int __pyx_v_i; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_selected_child; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_t_4; + + /* "stpredictions/models/OK3/_quad_tree.pyx":269 + * cdef: + * int i + * SIZE_t selected_child = 0 # <<<<<<<<<<<<<< + * + * for i in range(self.n_dimensions): + */ + __pyx_v_selected_child = 0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":271 + * SIZE_t selected_child = 0 + * + * for i in range(self.n_dimensions): # <<<<<<<<<<<<<< + * # Select the correct child cell to insert the point by comparing + * # it to the borders of the cells using precomputed center. + */ + __pyx_t_1 = __pyx_v_self->n_dimensions; + __pyx_t_2 = __pyx_t_1; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "stpredictions/models/OK3/_quad_tree.pyx":274 + * # Select the correct child cell to insert the point by comparing + * # it to the borders of the cells using precomputed center. + * selected_child *= 2 # <<<<<<<<<<<<<< + * if point[i] >= cell.center[i]: + * selected_child += 1 + */ + __pyx_v_selected_child = (__pyx_v_selected_child * 2); + + /* "stpredictions/models/OK3/_quad_tree.pyx":275 + * # it to the borders of the cells using precomputed center. + * selected_child *= 2 + * if point[i] >= cell.center[i]: # <<<<<<<<<<<<<< + * selected_child += 1 + * return cell.children[selected_child] + */ + __pyx_t_4 = (((__pyx_v_point[__pyx_v_i]) >= (__pyx_v_cell->center[__pyx_v_i])) != 0); + if (__pyx_t_4) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":276 + * selected_child *= 2 + * if point[i] >= cell.center[i]: + * selected_child += 1 # <<<<<<<<<<<<<< + * return cell.children[selected_child] + * + */ + __pyx_v_selected_child = (__pyx_v_selected_child + 1); + + /* "stpredictions/models/OK3/_quad_tree.pyx":275 + * # it to the borders of the cells using precomputed center. + * selected_child *= 2 + * if point[i] >= cell.center[i]: # <<<<<<<<<<<<<< + * selected_child += 1 + * return cell.children[selected_child] + */ + } + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":277 + * if point[i] >= cell.center[i]: + * selected_child += 1 + * return cell.children[selected_child] # <<<<<<<<<<<<<< + * + * cdef void _init_cell(self, Cell* cell, SIZE_t parent, SIZE_t depth) nogil: + */ + __pyx_r = (__pyx_v_cell->children[__pyx_v_selected_child]); + goto __pyx_L0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":265 + * + * + * cdef SIZE_t _select_child(self, DTYPE_t[3] point, Cell* cell) nogil: # <<<<<<<<<<<<<< + * """Select the child of cell which contains the given query point.""" + * cdef: + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "stpredictions/models/OK3/_quad_tree.pyx":279 + * return cell.children[selected_child] + * + * cdef void _init_cell(self, Cell* cell, SIZE_t parent, SIZE_t depth) nogil: # <<<<<<<<<<<<<< + * """Initialize a cell structure with some constants.""" + * cell.parent = parent + */ + +static void __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__init_cell(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_v_cell, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_parent, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_depth) { + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_v_i; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t __pyx_t_3; + + /* "stpredictions/models/OK3/_quad_tree.pyx":281 + * cdef void _init_cell(self, Cell* cell, SIZE_t parent, SIZE_t depth) nogil: + * """Initialize a cell structure with some constants.""" + * cell.parent = parent # <<<<<<<<<<<<<< + * cell.is_leaf = True + * cell.depth = depth + */ + __pyx_v_cell->parent = __pyx_v_parent; + + /* "stpredictions/models/OK3/_quad_tree.pyx":282 + * """Initialize a cell structure with some constants.""" + * cell.parent = parent + * cell.is_leaf = True # <<<<<<<<<<<<<< + * cell.depth = depth + * cell.squared_max_width = 0 + */ + __pyx_v_cell->is_leaf = 1; + + /* "stpredictions/models/OK3/_quad_tree.pyx":283 + * cell.parent = parent + * cell.is_leaf = True + * cell.depth = depth # <<<<<<<<<<<<<< + * cell.squared_max_width = 0 + * cell.cumulative_size = 0 + */ + __pyx_v_cell->depth = __pyx_v_depth; + + /* "stpredictions/models/OK3/_quad_tree.pyx":284 + * cell.is_leaf = True + * cell.depth = depth + * cell.squared_max_width = 0 # <<<<<<<<<<<<<< + * cell.cumulative_size = 0 + * for i in range(self.n_cells_per_cell): + */ + __pyx_v_cell->squared_max_width = 0.0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":285 + * cell.depth = depth + * cell.squared_max_width = 0 + * cell.cumulative_size = 0 # <<<<<<<<<<<<<< + * for i in range(self.n_cells_per_cell): + * cell.children[i] = SIZE_MAX + */ + __pyx_v_cell->cumulative_size = 0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":286 + * cell.squared_max_width = 0 + * cell.cumulative_size = 0 + * for i in range(self.n_cells_per_cell): # <<<<<<<<<<<<<< + * cell.children[i] = SIZE_MAX + * + */ + __pyx_t_1 = __pyx_v_self->n_cells_per_cell; + __pyx_t_2 = __pyx_t_1; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "stpredictions/models/OK3/_quad_tree.pyx":287 + * cell.cumulative_size = 0 + * for i in range(self.n_cells_per_cell): + * cell.children[i] = SIZE_MAX # <<<<<<<<<<<<<< + * + * cdef void _init_root(self, DTYPE_t[3] min_bounds, DTYPE_t[3] max_bounds + */ + (__pyx_v_cell->children[__pyx_v_i]) = SIZE_MAX; + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":279 + * return cell.children[selected_child] + * + * cdef void _init_cell(self, Cell* cell, SIZE_t parent, SIZE_t depth) nogil: # <<<<<<<<<<<<<< + * """Initialize a cell structure with some constants.""" + * cell.parent = parent + */ + + /* function exit code */ +} + +/* "stpredictions/models/OK3/_quad_tree.pyx":289 + * cell.children[i] = SIZE_MAX + * + * cdef void _init_root(self, DTYPE_t[3] min_bounds, DTYPE_t[3] max_bounds # <<<<<<<<<<<<<< + * ) nogil: + * """Initialize the root node with the given space boundaries""" + */ + +static void __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__init_root(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_min_bounds, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_max_bounds) { + int __pyx_v_i; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t __pyx_v_width; + struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_v_root; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t __pyx_t_4; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t __pyx_t_5; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t __pyx_t_6; + + /* "stpredictions/models/OK3/_quad_tree.pyx":295 + * int i + * DTYPE_t width + * Cell* root = &self.cells[0] # <<<<<<<<<<<<<< + * + * self._init_cell(root, -1, 0) + */ + __pyx_v_root = (&(__pyx_v_self->cells[0])); + + /* "stpredictions/models/OK3/_quad_tree.pyx":297 + * Cell* root = &self.cells[0] + * + * self._init_cell(root, -1, 0) # <<<<<<<<<<<<<< + * for i in range(self.n_dimensions): + * root.min_bounds[i] = min_bounds[i] + */ + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *)__pyx_v_self->__pyx_vtab)->_init_cell(__pyx_v_self, __pyx_v_root, -1, 0); + + /* "stpredictions/models/OK3/_quad_tree.pyx":298 + * + * self._init_cell(root, -1, 0) + * for i in range(self.n_dimensions): # <<<<<<<<<<<<<< + * root.min_bounds[i] = min_bounds[i] + * root.max_bounds[i] = max_bounds[i] + */ + __pyx_t_1 = __pyx_v_self->n_dimensions; + __pyx_t_2 = __pyx_t_1; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "stpredictions/models/OK3/_quad_tree.pyx":299 + * self._init_cell(root, -1, 0) + * for i in range(self.n_dimensions): + * root.min_bounds[i] = min_bounds[i] # <<<<<<<<<<<<<< + * root.max_bounds[i] = max_bounds[i] + * root.center[i] = (max_bounds[i] + min_bounds[i]) / 2. + */ + (__pyx_v_root->min_bounds[__pyx_v_i]) = (__pyx_v_min_bounds[__pyx_v_i]); + + /* "stpredictions/models/OK3/_quad_tree.pyx":300 + * for i in range(self.n_dimensions): + * root.min_bounds[i] = min_bounds[i] + * root.max_bounds[i] = max_bounds[i] # <<<<<<<<<<<<<< + * root.center[i] = (max_bounds[i] + min_bounds[i]) / 2. + * width = max_bounds[i] - min_bounds[i] + */ + (__pyx_v_root->max_bounds[__pyx_v_i]) = (__pyx_v_max_bounds[__pyx_v_i]); + + /* "stpredictions/models/OK3/_quad_tree.pyx":301 + * root.min_bounds[i] = min_bounds[i] + * root.max_bounds[i] = max_bounds[i] + * root.center[i] = (max_bounds[i] + min_bounds[i]) / 2. # <<<<<<<<<<<<<< + * width = max_bounds[i] - min_bounds[i] + * root.squared_max_width = max(root.squared_max_width, width*width) + */ + (__pyx_v_root->center[__pyx_v_i]) = (((__pyx_v_max_bounds[__pyx_v_i]) + (__pyx_v_min_bounds[__pyx_v_i])) / 2.); + + /* "stpredictions/models/OK3/_quad_tree.pyx":302 + * root.max_bounds[i] = max_bounds[i] + * root.center[i] = (max_bounds[i] + min_bounds[i]) / 2. + * width = max_bounds[i] - min_bounds[i] # <<<<<<<<<<<<<< + * root.squared_max_width = max(root.squared_max_width, width*width) + * root.cell_id = 0 + */ + __pyx_v_width = ((__pyx_v_max_bounds[__pyx_v_i]) - (__pyx_v_min_bounds[__pyx_v_i])); + + /* "stpredictions/models/OK3/_quad_tree.pyx":303 + * root.center[i] = (max_bounds[i] + min_bounds[i]) / 2. + * width = max_bounds[i] - min_bounds[i] + * root.squared_max_width = max(root.squared_max_width, width*width) # <<<<<<<<<<<<<< + * root.cell_id = 0 + * + */ + __pyx_t_4 = (__pyx_v_width * __pyx_v_width); + __pyx_t_5 = __pyx_v_root->squared_max_width; + if (((__pyx_t_4 > __pyx_t_5) != 0)) { + __pyx_t_6 = __pyx_t_4; + } else { + __pyx_t_6 = __pyx_t_5; + } + __pyx_v_root->squared_max_width = __pyx_t_6; + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":304 + * width = max_bounds[i] - min_bounds[i] + * root.squared_max_width = max(root.squared_max_width, width*width) + * root.cell_id = 0 # <<<<<<<<<<<<<< + * + * self.cell_count += 1 + */ + __pyx_v_root->cell_id = 0; + + /* "stpredictions/models/OK3/_quad_tree.pyx":306 + * root.cell_id = 0 + * + * self.cell_count += 1 # <<<<<<<<<<<<<< + * + * cdef int _check_point_in_cell(self, DTYPE_t[3] point, Cell* cell + */ + __pyx_v_self->cell_count = (__pyx_v_self->cell_count + 1); + + /* "stpredictions/models/OK3/_quad_tree.pyx":289 + * cell.children[i] = SIZE_MAX + * + * cdef void _init_root(self, DTYPE_t[3] min_bounds, DTYPE_t[3] max_bounds # <<<<<<<<<<<<<< + * ) nogil: + * """Initialize the root node with the given space boundaries""" + */ + + /* function exit code */ +} + +/* "stpredictions/models/OK3/_quad_tree.pyx":308 + * self.cell_count += 1 + * + * cdef int _check_point_in_cell(self, DTYPE_t[3] point, Cell* cell # <<<<<<<<<<<<<< + * ) nogil except -1: + * """Check that the given point is in the cell boundaries.""" + */ + +static int __pyx_f_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__check_point_in_cell(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *__pyx_v_point, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_v_cell) { + int __pyx_v_i; + PyObject *__pyx_v_msg = NULL; + int __pyx_r; + __Pyx_RefNannyDeclarations + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_t_4; + int __pyx_t_5; + PyObject *__pyx_t_6 = NULL; + PyObject *__pyx_t_7 = NULL; + PyObject *__pyx_t_8 = NULL; + PyObject *__pyx_t_9 = NULL; + PyObject *__pyx_t_10 = NULL; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); + #endif + __Pyx_RefNannySetupContext("_check_point_in_cell", 0); + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + + /* "stpredictions/models/OK3/_quad_tree.pyx":310 + * cdef int _check_point_in_cell(self, DTYPE_t[3] point, Cell* cell + * ) nogil except -1: + * """Check that the given point is in the cell boundaries.""" # <<<<<<<<<<<<<< + * + * if self.verbose >= 50: + */ + /*try:*/ { + + /* "stpredictions/models/OK3/_quad_tree.pyx":312 + * """Check that the given point is in the cell boundaries.""" + * + * if self.verbose >= 50: # <<<<<<<<<<<<<< + * if self.n_dimensions == 3: + * printf("[QuadTree] Checking point (%f, %f, %f) in cell %li " + */ + __pyx_t_1 = ((__pyx_v_self->verbose >= 50) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":313 + * + * if self.verbose >= 50: + * if self.n_dimensions == 3: # <<<<<<<<<<<<<< + * printf("[QuadTree] Checking point (%f, %f, %f) in cell %li " + * "([%f/%f, %f/%f, %f/%f], size %li)\n", + */ + __pyx_t_1 = ((__pyx_v_self->n_dimensions == 3) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_quad_tree.pyx":314 + * if self.verbose >= 50: + * if self.n_dimensions == 3: + * printf("[QuadTree] Checking point (%f, %f, %f) in cell %li " # <<<<<<<<<<<<<< + * "([%f/%f, %f/%f, %f/%f], size %li)\n", + * point[0], point[1], point[2], cell.cell_id, + */ + (void)(printf(((char const *)"[QuadTree] Checking point (%f, %f, %f) in cell %li ([%f/%f, %f/%f, %f/%f], size %li)\n"), (__pyx_v_point[0]), (__pyx_v_point[1]), (__pyx_v_point[2]), __pyx_v_cell->cell_id, (__pyx_v_cell->min_bounds[0]), (__pyx_v_cell->max_bounds[0]), (__pyx_v_cell->min_bounds[1]), (__pyx_v_cell->max_bounds[1]), (__pyx_v_cell->min_bounds[2]), (__pyx_v_cell->max_bounds[2]), __pyx_v_cell->cumulative_size)); + + /* "stpredictions/models/OK3/_quad_tree.pyx":313 + * + * if self.verbose >= 50: + * if self.n_dimensions == 3: # <<<<<<<<<<<<<< + * printf("[QuadTree] Checking point (%f, %f, %f) in cell %li " + * "([%f/%f, %f/%f, %f/%f], size %li)\n", + */ + goto __pyx_L7; + } + + /* "stpredictions/models/OK3/_quad_tree.pyx":321 + * cell.cumulative_size) + * else: + * printf("[QuadTree] Checking point (%f, %f) in cell %li " # <<<<<<<<<<<<<< + * "([%f/%f, %f/%f], size %li)\n", + * point[0], point[1],cell.cell_id, cell.min_bounds[0], + */ + /*else*/ { + + /* "stpredictions/models/OK3/_quad_tree.pyx":325 + * point[0], point[1],cell.cell_id, cell.min_bounds[0], + * cell.max_bounds[0], cell.min_bounds[1], + * cell.max_bounds[1], cell.cumulative_size) # <<<<<<<<<<<<<< + * + * for i in range(self.n_dimensions): + */ + (void)(printf(((char const *)"[QuadTree] Checking point (%f, %f) in cell %li ([%f/%f, %f/%f], size %li)\n"), (__pyx_v_point[0]), (__pyx_v_point[1]), __pyx_v_cell->cell_id, (__pyx_v_cell->min_bounds[0]), (__pyx_v_cell->max_bounds[0]), (__pyx_v_cell->min_bounds[1]), (__pyx_v_cell->max_bounds[1]), __pyx_v_cell->cumulative_size)); 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+ CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; + Py_ssize_t __pyx_v_dst_extent; + Py_ssize_t __pyx_v_src_stride; + Py_ssize_t __pyx_v_dst_stride; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + Py_ssize_t __pyx_t_4; + Py_ssize_t __pyx_t_5; + Py_ssize_t __pyx_t_6; + + /* "View.MemoryView":1147 + * + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + */ + __pyx_v_src_extent = (__pyx_v_src_shape[0]); + + /* "View.MemoryView":1148 + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] + */ + __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); + + /* "View.MemoryView":1149 + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + */ + __pyx_v_src_stride = (__pyx_v_src_strides[0]); + + /* "View.MemoryView":1150 + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< + * + * if ndim == 1: + */ + __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); + + /* "View.MemoryView":1152 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + + /* "View.MemoryView":1154 + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + */ + __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); + if (__pyx_t_2) { + __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); + } + __pyx_t_3 = (__pyx_t_2 != 0); + __pyx_t_1 = __pyx_t_3; + __pyx_L5_bool_binop_done:; + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + if (__pyx_t_1) { + + /* "View.MemoryView":1155 + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + goto __pyx_L4; + } + + /* "View.MemoryView":1157 + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + */ + /*else*/ { + __pyx_t_4 = __pyx_v_dst_extent; + __pyx_t_5 = __pyx_t_4; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1158 + * else: + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< + * src_data += src_stride + * dst_data += dst_stride + */ + (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize)); + + /* "View.MemoryView":1159 + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * else: + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1160 + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L4:; + + /* "View.MemoryView":1152 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1162 + * dst_data += dst_stride + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * _copy_strided_to_strided(src_data, src_strides + 1, + * dst_data, dst_strides + 1, + */ + /*else*/ { + __pyx_t_4 = __pyx_v_dst_extent; + __pyx_t_5 = __pyx_t_4; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1163 + * else: + * for i in range(dst_extent): + * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< + * dst_data, dst_strides + 1, + * src_shape + 1, dst_shape + 1, + */ + _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); + + /* "View.MemoryView":1167 + * src_shape + 1, dst_shape + 1, + * ndim - 1, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1168 + * ndim - 1, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L3:; + + /* "View.MemoryView":1140 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + + /* function exit code */ +} + +/* "View.MemoryView":1170 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + +static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + + /* "View.MemoryView":1173 + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< + * src.shape, dst.shape, ndim, itemsize) + * + */ + _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1170 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + + /* function exit code */ +} + +/* "View.MemoryView":1177 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + */ + +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { + Py_ssize_t __pyx_v_shape; + Py_ssize_t __pyx_v_size; + Py_ssize_t __pyx_r; + Py_ssize_t __pyx_t_1; + Py_ssize_t *__pyx_t_2; + Py_ssize_t *__pyx_t_3; + Py_ssize_t *__pyx_t_4; + + /* "View.MemoryView":1179 + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize # <<<<<<<<<<<<<< + * + * for shape in src.shape[:ndim]: + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; + __pyx_v_size = __pyx_t_1; + + /* "View.MemoryView":1181 + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + * + * for shape in src.shape[:ndim]: # <<<<<<<<<<<<<< + * size *= shape + * + */ + __pyx_t_3 = (__pyx_v_src->shape + __pyx_v_ndim); + for (__pyx_t_4 = __pyx_v_src->shape; __pyx_t_4 < __pyx_t_3; __pyx_t_4++) { + __pyx_t_2 = __pyx_t_4; + __pyx_v_shape = (__pyx_t_2[0]); + + /* "View.MemoryView":1182 + * + * for shape in src.shape[:ndim]: + * size *= shape # <<<<<<<<<<<<<< + * + * return size + */ + __pyx_v_size = (__pyx_v_size * __pyx_v_shape); + } + + /* "View.MemoryView":1184 + * size *= shape + * + * return size # <<<<<<<<<<<<<< + * + * @cname('__pyx_fill_contig_strides_array') + */ + __pyx_r = __pyx_v_size; + goto __pyx_L0; + + /* "View.MemoryView":1177 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1187 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { + int __pyx_v_idx; + Py_ssize_t __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_t_4; + + /* "View.MemoryView":1196 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + __pyx_t_1 = ((__pyx_v_order == 'F') != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1197 + * + * if order == 'F': + * for idx in range(ndim): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride *= shape[idx] + */ + __pyx_t_2 = __pyx_v_ndim; + __pyx_t_3 = __pyx_t_2; + for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { + __pyx_v_idx = __pyx_t_4; + + /* "View.MemoryView":1198 + * if order == 'F': + * for idx in range(ndim): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride *= shape[idx] + * else: + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1199 + * for idx in range(ndim): + * strides[idx] = stride + * stride *= shape[idx] # <<<<<<<<<<<<<< + * else: + * for idx in range(ndim - 1, -1, -1): + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + } + + /* "View.MemoryView":1196 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1201 + * stride *= shape[idx] + * else: + * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride *= shape[idx] + */ + /*else*/ { + for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) { + __pyx_v_idx = __pyx_t_2; + + /* "View.MemoryView":1202 + * else: + * for idx in range(ndim - 1, -1, -1): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride *= shape[idx] + * + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1203 + * for idx in range(ndim - 1, -1, -1): + * strides[idx] = stride + * stride *= shape[idx] # <<<<<<<<<<<<<< + * + * return stride + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + } + } + __pyx_L3:; + + /* "View.MemoryView":1205 + * stride *= shape[idx] + * + * return stride # <<<<<<<<<<<<<< + * + * @cname('__pyx_memoryview_copy_data_to_temp') + */ + __pyx_r = __pyx_v_stride; + goto __pyx_L0; + + /* "View.MemoryView":1187 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1208 + * + * @cname('__pyx_memoryview_copy_data_to_temp') + * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *tmpslice, + * char order, + */ + +static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_tmpslice, char __pyx_v_order, int __pyx_v_ndim) { + int __pyx_v_i; + void *__pyx_v_result; + size_t __pyx_v_itemsize; + size_t __pyx_v_size; + void *__pyx_r; + Py_ssize_t __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + struct __pyx_memoryview_obj *__pyx_t_4; + int __pyx_t_5; + int __pyx_t_6; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "View.MemoryView":1219 + * cdef void *result + * + * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< + * cdef size_t size = slice_get_size(src, ndim) + * + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; + __pyx_v_itemsize = __pyx_t_1; + + /* "View.MemoryView":1220 + * + * cdef size_t itemsize = src.memview.view.itemsize + * cdef size_t size = slice_get_size(src, ndim) # <<<<<<<<<<<<<< + * + * result = malloc(size) + */ + __pyx_v_size = __pyx_memoryview_slice_get_size(__pyx_v_src, __pyx_v_ndim); + + /* "View.MemoryView":1222 + * cdef size_t size = slice_get_size(src, ndim) + * + * result = malloc(size) # <<<<<<<<<<<<<< + * if not result: + * _err(MemoryError, NULL) + */ + __pyx_v_result = malloc(__pyx_v_size); + + /* "View.MemoryView":1223 + * + * result = malloc(size) + * if not result: # <<<<<<<<<<<<<< + * _err(MemoryError, NULL) + * + */ + __pyx_t_2 = ((!(__pyx_v_result != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1224 + * result = malloc(size) + * if not result: + * _err(MemoryError, NULL) # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(3, 1224, __pyx_L1_error) + + /* "View.MemoryView":1223 + * + * result = malloc(size) + * if not result: # <<<<<<<<<<<<<< + * _err(MemoryError, NULL) + * + */ + } + + /* "View.MemoryView":1227 + * + * + * tmpslice.data = result # <<<<<<<<<<<<<< + * tmpslice.memview = src.memview + * for i in range(ndim): + */ + __pyx_v_tmpslice->data = ((char *)__pyx_v_result); + + /* "View.MemoryView":1228 + * + * tmpslice.data = result + * tmpslice.memview = src.memview # <<<<<<<<<<<<<< + * for i in range(ndim): + * tmpslice.shape[i] = src.shape[i] + */ + __pyx_t_4 = __pyx_v_src->memview; + __pyx_v_tmpslice->memview = __pyx_t_4; + + /* "View.MemoryView":1229 + * tmpslice.data = result + * tmpslice.memview = src.memview + * for i in range(ndim): # <<<<<<<<<<<<<< + * tmpslice.shape[i] = src.shape[i] + * tmpslice.suboffsets[i] = -1 + */ + __pyx_t_3 = __pyx_v_ndim; + __pyx_t_5 = __pyx_t_3; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1230 + * tmpslice.memview = src.memview + * for i in range(ndim): + * tmpslice.shape[i] = src.shape[i] # <<<<<<<<<<<<<< + * tmpslice.suboffsets[i] = -1 + * + */ + (__pyx_v_tmpslice->shape[__pyx_v_i]) = (__pyx_v_src->shape[__pyx_v_i]); + + /* "View.MemoryView":1231 + * for i in range(ndim): + * tmpslice.shape[i] = src.shape[i] + * tmpslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< + * + * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, + */ + (__pyx_v_tmpslice->suboffsets[__pyx_v_i]) = -1L; + } + + /* "View.MemoryView":1233 + * tmpslice.suboffsets[i] = -1 + * + * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, # <<<<<<<<<<<<<< + * ndim, order) + * + */ + (void)(__pyx_fill_contig_strides_array((&(__pyx_v_tmpslice->shape[0])), (&(__pyx_v_tmpslice->strides[0])), __pyx_v_itemsize, __pyx_v_ndim, __pyx_v_order)); + + /* "View.MemoryView":1237 + * + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * if tmpslice.shape[i] == 1: + * tmpslice.strides[i] = 0 + */ + __pyx_t_3 = __pyx_v_ndim; + __pyx_t_5 = __pyx_t_3; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1238 + * + * for i in range(ndim): + * if tmpslice.shape[i] == 1: # <<<<<<<<<<<<<< + * tmpslice.strides[i] = 0 + * + */ + __pyx_t_2 = (((__pyx_v_tmpslice->shape[__pyx_v_i]) == 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1239 + * for i in range(ndim): + * if tmpslice.shape[i] == 1: + * tmpslice.strides[i] = 0 # <<<<<<<<<<<<<< + * + * if slice_is_contig(src[0], order, ndim): + */ + (__pyx_v_tmpslice->strides[__pyx_v_i]) = 0; + + /* "View.MemoryView":1238 + * + * for i in range(ndim): + * if tmpslice.shape[i] == 1: # <<<<<<<<<<<<<< + * tmpslice.strides[i] = 0 + * + */ + } + } + + /* "View.MemoryView":1241 + * tmpslice.strides[i] = 0 + * + * if slice_is_contig(src[0], order, ndim): # <<<<<<<<<<<<<< + * memcpy(result, src.data, size) + * else: + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig((__pyx_v_src[0]), __pyx_v_order, __pyx_v_ndim) != 0); 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+ + /* "View.MemoryView":1289 + * broadcast_leading(&dst, dst_ndim, src_ndim) + * + * cdef int ndim = max(src_ndim, dst_ndim) # <<<<<<<<<<<<<< + * + * for i in range(ndim): + */ + __pyx_t_3 = __pyx_v_dst_ndim; + __pyx_t_4 = __pyx_v_src_ndim; + if (((__pyx_t_3 > __pyx_t_4) != 0)) { + __pyx_t_5 = __pyx_t_3; + } else { + __pyx_t_5 = __pyx_t_4; + } + __pyx_v_ndim = __pyx_t_5; + + /* "View.MemoryView":1291 + * cdef int ndim = max(src_ndim, dst_ndim) + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: + */ + __pyx_t_5 = __pyx_v_ndim; + __pyx_t_3 = __pyx_t_5; + for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { + __pyx_v_i = __pyx_t_4; + + /* "View.MemoryView":1292 + * + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< + * if src.shape[i] == 1: + * broadcasting = True + */ + __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) != (__pyx_v_dst.shape[__pyx_v_i])) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1293 + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: # <<<<<<<<<<<<<< + * broadcasting = True + * src.strides[i] = 0 + */ + __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) == 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1294 + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: + * broadcasting = True # <<<<<<<<<<<<<< + * src.strides[i] = 0 + * else: + */ + __pyx_v_broadcasting = 1; + + /* "View.MemoryView":1295 + * if src.shape[i] == 1: + * broadcasting = True + * src.strides[i] = 0 # <<<<<<<<<<<<<< + * else: + * _err_extents(i, dst.shape[i], src.shape[i]) + */ + (__pyx_v_src.strides[__pyx_v_i]) = 0; + + /* "View.MemoryView":1293 + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: # <<<<<<<<<<<<<< + * broadcasting = True + * src.strides[i] = 0 + */ + goto __pyx_L7; + } + + /* "View.MemoryView":1297 + * src.strides[i] = 0 + * else: + * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<< + * + * if src.suboffsets[i] >= 0: + */ + /*else*/ { + __pyx_t_6 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(3, 1297, __pyx_L1_error) + } + __pyx_L7:; + + /* "View.MemoryView":1292 + * + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< + * if src.shape[i] == 1: + * broadcasting = True + */ + } + + /* "View.MemoryView":1299 + * _err_extents(i, dst.shape[i], src.shape[i]) + * + * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + */ + __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1300 + * + * if src.suboffsets[i] >= 0: + * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<< + * + * if slices_overlap(&src, &dst, ndim, itemsize): + */ + __pyx_t_6 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Dimension %d is not direct"), __pyx_v_i); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(3, 1300, __pyx_L1_error) + + /* "View.MemoryView":1299 + * _err_extents(i, dst.shape[i], src.shape[i]) + * + * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + */ + } + } + + /* "View.MemoryView":1302 + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< + * + * if not slice_is_contig(src, order, ndim): + */ + __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1304 + * if slices_overlap(&src, &dst, ndim, itemsize): + * + * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< + * order = get_best_order(&dst, ndim) + * + */ + __pyx_t_2 = ((!(__pyx_memviewslice_is_contig(__pyx_v_src, __pyx_v_order, __pyx_v_ndim) != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1305 + * + * if not slice_is_contig(src, order, ndim): + * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) + */ + __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim); + + /* "View.MemoryView":1304 + * if slices_overlap(&src, &dst, ndim, itemsize): + * + * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< + * order = get_best_order(&dst, ndim) + * + */ + } + + /* "View.MemoryView":1307 + * order = get_best_order(&dst, ndim) + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< + * src = tmp + * + */ + __pyx_t_7 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_7 == ((void *)NULL))) __PYX_ERR(3, 1307, __pyx_L1_error) + __pyx_v_tmpdata = __pyx_t_7; + + /* "View.MemoryView":1308 + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) + * src = tmp # <<<<<<<<<<<<<< + * + * if not broadcasting: + */ + __pyx_v_src = __pyx_v_tmp; + + /* "View.MemoryView":1302 + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< + * + * if not slice_is_contig(src, order, ndim): + */ + } + + /* "View.MemoryView":1310 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1313 + * + * + * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'C', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1314 + * + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) # <<<<<<<<<<<<<< + * elif slice_is_contig(src, 'F', ndim): + * direct_copy = slice_is_contig(dst, 'F', ndim) + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim); + + /* "View.MemoryView":1313 + * + * + * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + */ + goto __pyx_L12; + } + + /* "View.MemoryView":1315 + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'F', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1316 + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + * direct_copy = slice_is_contig(dst, 'F', ndim) # <<<<<<<<<<<<<< + * + * if direct_copy: + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim); + + /* "View.MemoryView":1315 + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + */ + } + __pyx_L12:; + + /* "View.MemoryView":1318 + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_2 = (__pyx_v_direct_copy != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1320 + * if direct_copy: + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1321 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + */ + (void)(memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim))); + + /* "View.MemoryView":1322 + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * free(tmpdata) + * return 0 + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1323 + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) # <<<<<<<<<<<<<< + * return 0 + * + */ + free(__pyx_v_tmpdata); + + /* "View.MemoryView":1324 + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + * return 0 # <<<<<<<<<<<<<< + * + * if order == 'F' == get_best_order(&dst, ndim): + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "View.MemoryView":1318 + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + } + + /* "View.MemoryView":1310 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + } + + /* "View.MemoryView":1326 + * return 0 + * + * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = (__pyx_v_order == 'F'); + if (__pyx_t_2) { + __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim)); + } + __pyx_t_8 = (__pyx_t_2 != 0); + if (__pyx_t_8) { + + /* "View.MemoryView":1329 + * + * + * transpose_memslice(&src) # <<<<<<<<<<<<<< + * transpose_memslice(&dst) + * + */ + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(3, 1329, __pyx_L1_error) + + /* "View.MemoryView":1330 + * + * transpose_memslice(&src) + * transpose_memslice(&dst) # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(3, 1330, __pyx_L1_error) + + /* "View.MemoryView":1326 + * return 0 + * + * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< + * + * + */ + } + + /* "View.MemoryView":1332 + * transpose_memslice(&dst) + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * copy_strided_to_strided(&src, &dst, ndim, itemsize) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1333 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * + */ + copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1334 + * refcount_copying(&dst, dtype_is_object, ndim, False) + * copy_strided_to_strided(&src, &dst, ndim, itemsize) + * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * + * free(tmpdata) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1336 + * refcount_copying(&dst, dtype_is_object, ndim, True) + * + * free(tmpdata) # <<<<<<<<<<<<<< + * return 0 + * + */ + free(__pyx_v_tmpdata); + + /* "View.MemoryView":1337 + * + * free(tmpdata) + * return 0 # <<<<<<<<<<<<<< + * + * @cname('__pyx_memoryview_broadcast_leading') + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "View.MemoryView":1268 + * + * @cname('__pyx_memoryview_copy_contents') + * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice dst, + * int src_ndim, int dst_ndim, + */ + + /* function exit code */ + __pyx_L1_error:; + { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); + #endif + __Pyx_AddTraceback("View.MemoryView.memoryview_copy_contents", __pyx_clineno, __pyx_lineno, __pyx_filename); + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + } + __pyx_r = -1; + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1340 + * + * @cname('__pyx_memoryview_broadcast_leading') + * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< + * int ndim, + * int ndim_other) nogil: + */ + +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) { + int __pyx_v_i; + int __pyx_v_offset; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + + /* "View.MemoryView":1344 + * int ndim_other) nogil: + * cdef int i + * cdef int offset = ndim_other - ndim # <<<<<<<<<<<<<< + * + * for i in range(ndim - 1, -1, -1): + */ + __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim); + + /* "View.MemoryView":1346 + * cdef int offset = ndim_other - ndim + * + * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] + */ + for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { + __pyx_v_i = __pyx_t_1; + + /* "View.MemoryView":1347 + * + * for i in range(ndim - 1, -1, -1): + * mslice.shape[i + offset] = mslice.shape[i] # <<<<<<<<<<<<<< + * mslice.strides[i + offset] = mslice.strides[i] + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] + */ + (__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]); + + /* "View.MemoryView":1348 + * for i in range(ndim - 1, -1, -1): + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] # <<<<<<<<<<<<<< + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] + * + */ + (__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1349 + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] # <<<<<<<<<<<<<< + * + * for i in range(offset): + */ + (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]); + } + + /* "View.MemoryView":1351 + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] + * + * for i in range(offset): # <<<<<<<<<<<<<< + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] + */ + __pyx_t_1 = __pyx_v_offset; + __pyx_t_2 = __pyx_t_1; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "View.MemoryView":1352 + * + * for i in range(offset): + * mslice.shape[i] = 1 # <<<<<<<<<<<<<< + * mslice.strides[i] = mslice.strides[0] + * mslice.suboffsets[i] = -1 + */ + (__pyx_v_mslice->shape[__pyx_v_i]) = 1; + + /* "View.MemoryView":1353 + * for i in range(offset): + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] # <<<<<<<<<<<<<< + * mslice.suboffsets[i] = -1 + * + */ + (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]); + + /* "View.MemoryView":1354 + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] + * mslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< + * + * + */ + (__pyx_v_mslice->suboffsets[__pyx_v_i]) = -1L; + } + + /* "View.MemoryView":1340 + * + * @cname('__pyx_memoryview_broadcast_leading') + * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< + * int ndim, + * int ndim_other) nogil: + */ + + /* function exit code */ +} + +/* "View.MemoryView":1362 + * + * @cname('__pyx_memoryview_refcount_copying') + * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< + * int ndim, bint inc) nogil: + * + */ + +static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_dtype_is_object, int __pyx_v_ndim, int __pyx_v_inc) { + int __pyx_t_1; + + /* "View.MemoryView":1366 + * + * + * if dtype_is_object: # <<<<<<<<<<<<<< + * refcount_objects_in_slice_with_gil(dst.data, dst.shape, + * dst.strides, ndim, inc) + */ + __pyx_t_1 = (__pyx_v_dtype_is_object != 0); 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+ +static struct PyGetSetDef __pyx_getsets_13stpredictions_6models_3OK3_10_quad_tree__QuadTree[] = { + {(char *)"cumulative_size", __pyx_getprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_cumulative_size, 0, (char *)0, 0}, + {(char *)"leafs", __pyx_getprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_leafs, 0, (char *)0, 0}, + {(char *)"n_dimensions", __pyx_getprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_n_dimensions, __pyx_setprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_n_dimensions, (char *)0, 0}, + {(char *)"verbose", __pyx_getprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_verbose, __pyx_setprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_verbose, (char *)0, 0}, + {(char *)"max_depth", __pyx_getprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_max_depth, __pyx_setprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_max_depth, (char *)0, 0}, + {(char *)"cell_count", __pyx_getprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_cell_count, __pyx_setprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_cell_count, (char *)0, 0}, + {(char *)"capacity", __pyx_getprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_capacity, __pyx_setprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_capacity, (char *)0, 0}, + {(char *)"n_points", __pyx_getprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_n_points, __pyx_setprop_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_n_points, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; 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It is planned to split the 2 implementations\n using `Cython.Tempita` to save some memory for QuadTree.\n\n Note that this code is currently internally used only by the Barnes-Hut\n method in `sklearn.manifold.TSNE`. It is planned to be refactored and\n generalized in the future to be compatible with nearest neighbors API of\n `sklearn.neighbors` with 2D and 3D data.\n ", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_13stpredictions_6models_3OK3_10_quad_tree__QuadTree, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_13stpredictions_6models_3OK3_10_quad_tree__QuadTree, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_13stpredictions_6models_3OK3_10_quad_tree__QuadTree, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_array __pyx_vtable_array; + +static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_array_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_array_obj *)o); + p->__pyx_vtab = __pyx_vtabptr_array; + p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None); + p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None); + if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_array(PyObject *o) { + struct __pyx_array_obj *p = (struct __pyx_array_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_array___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->mode); + Py_CLEAR(p->_format); + (*Py_TYPE(o)->tp_free)(o); +} +static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_array___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) { + PyObject *v = __Pyx_PyObject_GenericGetAttr(o, n); + if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Clear(); + v = __pyx_array___getattr__(o, n); + } + return v; +} + +static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_5array_7memview_1__get__(o); +} + +static PyMethodDef __pyx_methods_array[] = { + {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_array_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_array_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_array[] = { + {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_array = { + __pyx_array___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_array, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_array = { + __pyx_array___len__, /*mp_length*/ + __pyx_array___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_array = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_array_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_array = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._quad_tree.array", /*tp_name*/ + sizeof(struct __pyx_array_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_array, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_array, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_array, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + __pyx_tp_getattro_array, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_array, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + 0, /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_array, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_array, /*tp_getset*/ + 0, 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Py_INCREF(Py_None); + return o; +} + +static void __pyx_tp_dealloc_Enum(PyObject *o) { + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + Py_CLEAR(p->name); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + if (p->name) { + e = (*v)(p->name, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_Enum(PyObject *o) { + PyObject* tmp; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + tmp = ((PyObject*)p->name); + p->name = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + return 0; +} + +static PyMethodDef __pyx_methods_Enum[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_MemviewEnum = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._quad_tree.Enum", /*tp_name*/ + sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_Enum, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + __pyx_MemviewEnum___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_Enum, /*tp_traverse*/ + __pyx_tp_clear_Enum, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_Enum, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + __pyx_MemviewEnum___init__, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_Enum, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; 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Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_memoryview___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->obj); + Py_CLEAR(p->_size); + Py_CLEAR(p->_array_interface); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + if (p->obj) { + e = (*v)(p->obj, a); if (e) return e; + } + if (p->_size) { + e = (*v)(p->_size, a); if (e) return e; + } + if (p->_array_interface) { + e = (*v)(p->_array_interface, a); if (e) return e; + } + if (p->view.obj) { + e = (*v)(p->view.obj, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_memoryview(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + tmp = ((PyObject*)p->obj); + p->obj = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_size); + p->_size = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_array_interface); + p->_array_interface = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + Py_CLEAR(p->view.obj); + return 0; +} +static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_memoryview___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_1T_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4base_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_5shape_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_7strides_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_10suboffsets_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4ndim_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_8itemsize_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_6nbytes_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4size_1__get__(o); +} + +static PyMethodDef __pyx_methods_memoryview[] = { + {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0}, + {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0}, + {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0}, + {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_memoryview[] = { + {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, (char *)0, 0}, + {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, (char *)0, 0}, + {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, (char *)0, 0}, + {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, (char *)0, 0}, + {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, (char *)0, 0}, + {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, (char *)0, 0}, + {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, (char *)0, 0}, + {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, (char *)0, 0}, + {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_memoryview = { + __pyx_memoryview___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_memoryview, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_memoryview = { + __pyx_memoryview___len__, /*mp_length*/ + __pyx_memoryview___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_memoryview = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_memoryview_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_memoryview = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._quad_tree.memoryview", /*tp_name*/ + sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_memoryview, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + __pyx_memoryview___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + __pyx_memoryview___str__, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_memoryview, /*tp_traverse*/ + __pyx_tp_clear_memoryview, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_memoryview, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_memoryview, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_memoryview, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice; + +static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryviewslice_obj *p; + PyObject *o = __pyx_tp_new_memoryview(t, a, k); + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryviewslice_obj *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice; + p->from_object = Py_None; Py_INCREF(Py_None); + p->from_slice.memview = NULL; + return o; +} + +static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) { + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_memoryviewslice___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->from_object); + PyObject_GC_Track(o); + __pyx_tp_dealloc_memoryview(o); +} + +static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e; + if (p->from_object) { + e = (*v)(p->from_object, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear__memoryviewslice(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o; + __pyx_tp_clear_memoryview(o); + tmp = ((PyObject*)p->from_object); + p->from_object = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + __PYX_XDEC_MEMVIEW(&p->from_slice, 1); + return 0; +} + +static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_16_memoryviewslice_4base_1__get__(o); +} + +static PyMethodDef __pyx_methods__memoryviewslice[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = { + {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_memoryviewslice = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._quad_tree._memoryviewslice", /*tp_name*/ + sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___repr__, /*tp_repr*/ + #else + 0, /*tp_repr*/ + #endif + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + #if CYTHON_COMPILING_IN_PYPY + __pyx_memoryview___str__, /*tp_str*/ + #else + 0, /*tp_str*/ + #endif + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Internal class for passing memoryview slices to Python", /*tp_doc*/ + __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/ + __pyx_tp_clear__memoryviewslice, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods__memoryviewslice, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets__memoryviewslice, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, 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"" : "s", num_found); +} + +/* RaiseDoubleKeywords */ +static void __Pyx_RaiseDoubleKeywordsError( + const char* func_name, + PyObject* kw_name) +{ + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION >= 3 + "%s() got multiple values for keyword argument '%U'", func_name, kw_name); + #else + "%s() got multiple values for keyword argument '%s'", func_name, + PyString_AsString(kw_name)); + #endif +} + +/* ParseKeywords */ +static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + continue; + } + name = first_kw_arg; + #if PY_MAJOR_VERSION < 3 + if (likely(PyString_Check(key))) { + while (*name) { + if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) + && _PyString_Eq(**name, key)) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + if ((**argname == key) || ( + (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) + && _PyString_Eq(**argname, key))) { + goto arg_passed_twice; + } + argname++; + } + } + } else + #endif + if (likely(PyUnicode_Check(key))) { + while (*name) { + int cmp = (**name == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**name, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + int cmp = (**argname == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**argname, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) goto arg_passed_twice; + argname++; + } + } + } else + goto invalid_keyword_type; + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, key); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%.200s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%.200s() got an unexpected keyword argument '%.200s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +/* GetItemInt */ +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { + PyObject *r; + if (!j) return NULL; + r = PyObject_GetItem(o, j); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyList_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { + PyObject *r = PyList_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyTuple_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); + if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { + PyObject *r = PyList_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } + else if (PyTuple_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + return NULL; + PyErr_Clear(); + } + } + return m->sq_item(o, i); + } + } +#else + if (is_list || PySequence_Check(o)) { + return PySequence_GetItem(o, i); + } +#endif + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +} + +/* ObjectGetItem */ +#if CYTHON_USE_TYPE_SLOTS +static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { + PyObject *runerr; + Py_ssize_t key_value; + PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; + if (unlikely(!(m && m->sq_item))) { + PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); + return NULL; + } + key_value = __Pyx_PyIndex_AsSsize_t(index); + if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { + return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); + } + if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { + PyErr_Clear(); + PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); + } + return NULL; +} +static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { + PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; + if (likely(m && m->mp_subscript)) { + return m->mp_subscript(obj, key); + } + return __Pyx_PyObject_GetIndex(obj, key); +} +#endif + +/* SliceObject */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice(PyObject* obj, + Py_ssize_t cstart, Py_ssize_t cstop, + PyObject** _py_start, PyObject** _py_stop, PyObject** _py_slice, + int has_cstart, int has_cstop, CYTHON_UNUSED int wraparound) { +#if CYTHON_USE_TYPE_SLOTS + PyMappingMethods* mp; +#if PY_MAJOR_VERSION < 3 + PySequenceMethods* ms = Py_TYPE(obj)->tp_as_sequence; + if (likely(ms && ms->sq_slice)) { + if (!has_cstart) { + if (_py_start && (*_py_start != Py_None)) { + cstart = __Pyx_PyIndex_AsSsize_t(*_py_start); + if ((cstart == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad; + } else + cstart = 0; + } + if (!has_cstop) { + if (_py_stop && (*_py_stop != Py_None)) { + cstop = __Pyx_PyIndex_AsSsize_t(*_py_stop); + if ((cstop == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad; + } else + cstop = PY_SSIZE_T_MAX; + } + if (wraparound && unlikely((cstart < 0) | (cstop < 0)) && likely(ms->sq_length)) { + Py_ssize_t l = ms->sq_length(obj); + if (likely(l >= 0)) { + if (cstop < 0) { + cstop += l; + if (cstop < 0) cstop = 0; + } + if (cstart < 0) { + cstart += l; + if (cstart < 0) cstart = 0; + } + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + goto bad; + PyErr_Clear(); + } + } + return ms->sq_slice(obj, cstart, cstop); + } +#endif + mp = Py_TYPE(obj)->tp_as_mapping; + if (likely(mp && mp->mp_subscript)) +#endif + { + PyObject* result; + PyObject *py_slice, *py_start, *py_stop; + if (_py_slice) { + py_slice = *_py_slice; + } else { + PyObject* owned_start = NULL; + PyObject* owned_stop = NULL; + if (_py_start) { + py_start = *_py_start; + } else { + if (has_cstart) { + owned_start = py_start = PyInt_FromSsize_t(cstart); + if (unlikely(!py_start)) goto bad; + } else + py_start = Py_None; + } + if (_py_stop) { + py_stop = *_py_stop; + } else { + if (has_cstop) { + owned_stop = py_stop = PyInt_FromSsize_t(cstop); + if (unlikely(!py_stop)) { + Py_XDECREF(owned_start); + goto bad; + } + } else + py_stop = Py_None; + } + py_slice = PySlice_New(py_start, py_stop, Py_None); + Py_XDECREF(owned_start); + Py_XDECREF(owned_stop); + if (unlikely(!py_slice)) goto bad; + } +#if CYTHON_USE_TYPE_SLOTS + result = mp->mp_subscript(obj, py_slice); +#else + result = PyObject_GetItem(obj, py_slice); +#endif + if (!_py_slice) { + Py_DECREF(py_slice); + } + return result; + } + PyErr_Format(PyExc_TypeError, + "'%.200s' object is unsliceable", Py_TYPE(obj)->tp_name); +bad: + return NULL; +} + +/* PyDictVersioning */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + +/* GetModuleGlobalName */ +#if CYTHON_USE_DICT_VERSIONS +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) +#else +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) +#endif +{ + PyObject *result; +#if !CYTHON_AVOID_BORROWED_REFS +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 + result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } else if (unlikely(PyErr_Occurred())) { + return NULL; + } +#else + result = PyDict_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } +#endif +#else + result = PyObject_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } + PyErr_Clear(); +#endif + return __Pyx_GetBuiltinName(name); +} + +/* PyObjectCall */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { + PyObject *result; + ternaryfunc call = func->ob_type->tp_call; + if (unlikely(!call)) + return PyObject_Call(func, arg, kw); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = (*call)(func, arg, kw); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyFloatBinop */ +#if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyFloat_AddCObj(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check) { + const double a = floatval; + double b, result; + (void)inplace; + (void)zerodivision_check; + if (likely(PyFloat_CheckExact(op2))) { + b = PyFloat_AS_DOUBLE(op2); + + } else + #if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(op2))) { + b = (double) PyInt_AS_LONG(op2); + + } else + #endif + if (likely(PyLong_CheckExact(op2))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)op2)->ob_digit; + const Py_ssize_t size = Py_SIZE(op2); + switch (size) { + case 0: b = 0.0; break; + case -1: b = -(double) digits[0]; break; + case 1: b = (double) digits[0]; break; + case -2: + case 2: + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (1 * PyLong_SHIFT < 53))) { + b = (double) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + if ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53) || (b < (double) ((PY_LONG_LONG)1 << 53))) { + if (size == -2) + b = -b; + break; + } + } + CYTHON_FALLTHROUGH; + case -3: + case 3: + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53))) { + b = (double) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + if ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53) || (b < (double) ((PY_LONG_LONG)1 << 53))) { + if (size == -3) + b = -b; + break; + } + } + CYTHON_FALLTHROUGH; + case -4: + case 4: + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53))) { + b = (double) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + if ((8 * sizeof(unsigned long) < 53) || (4 * PyLong_SHIFT < 53) || (b < (double) ((PY_LONG_LONG)1 << 53))) { + if (size == -4) + b = -b; + break; + } + } + CYTHON_FALLTHROUGH; + default: + #else + { + #endif + b = PyLong_AsDouble(op2); + if (unlikely(b == -1.0 && PyErr_Occurred())) return NULL; + + } + } else { + return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); + } + + PyFPE_START_PROTECT("add", return NULL) + result = a + b; + PyFPE_END_PROTECT(result) + return PyFloat_FromDouble(result); +} +#endif + +/* PyCFunctionFastCall */ + #if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { + PyCFunctionObject *func = (PyCFunctionObject*)func_obj; + PyCFunction meth = PyCFunction_GET_FUNCTION(func); + PyObject *self = PyCFunction_GET_SELF(func); + int flags = PyCFunction_GET_FLAGS(func); + assert(PyCFunction_Check(func)); + assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); + assert(nargs >= 0); + assert(nargs == 0 || args != NULL); + /* _PyCFunction_FastCallDict() must not be called with an exception set, + because it may clear it (directly or indirectly) and so the + caller loses its exception */ + assert(!PyErr_Occurred()); + if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { + return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); + } else { + return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); + } +} +#endif + +/* PyFunctionFastCall */ + #if CYTHON_FAST_PYCALL +static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, + PyObject *globals) { + PyFrameObject *f; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject **fastlocals; + Py_ssize_t i; + PyObject *result; + assert(globals != NULL); + /* XXX Perhaps we should create a specialized + PyFrame_New() that doesn't take locals, but does + take builtins without sanity checking them. + */ + assert(tstate != NULL); + f = PyFrame_New(tstate, co, globals, NULL); + if (f == NULL) { + return NULL; + } + fastlocals = __Pyx_PyFrame_GetLocalsplus(f); + for (i = 0; i < na; i++) { + Py_INCREF(*args); + fastlocals[i] = *args++; + } + result = PyEval_EvalFrameEx(f,0); + ++tstate->recursion_depth; + Py_DECREF(f); + --tstate->recursion_depth; + return result; +} +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { + PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); + PyObject *globals = PyFunction_GET_GLOBALS(func); + PyObject *argdefs = PyFunction_GET_DEFAULTS(func); + PyObject *closure; +#if PY_MAJOR_VERSION >= 3 + PyObject *kwdefs; +#endif + PyObject *kwtuple, **k; + PyObject **d; + Py_ssize_t nd; + Py_ssize_t nk; + PyObject *result; + assert(kwargs == NULL || PyDict_Check(kwargs)); + nk = kwargs ? PyDict_Size(kwargs) : 0; + if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { + return NULL; + } + if ( +#if PY_MAJOR_VERSION >= 3 + co->co_kwonlyargcount == 0 && +#endif + likely(kwargs == NULL || nk == 0) && + co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { + if (argdefs == NULL && co->co_argcount == nargs) { + result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); + goto done; + } + else if (nargs == 0 && argdefs != NULL + && co->co_argcount == Py_SIZE(argdefs)) { + /* function called with no arguments, but all parameters have + a default value: use default values as arguments .*/ + args = &PyTuple_GET_ITEM(argdefs, 0); + result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); + goto done; + } + } + if (kwargs != NULL) { + Py_ssize_t pos, i; + kwtuple = PyTuple_New(2 * nk); + if (kwtuple == NULL) { + result = NULL; + goto done; + } + k = &PyTuple_GET_ITEM(kwtuple, 0); + pos = i = 0; + while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { + Py_INCREF(k[i]); + Py_INCREF(k[i+1]); + i += 2; + } + nk = i / 2; + } + else { + kwtuple = NULL; + k = NULL; + } + closure = PyFunction_GET_CLOSURE(func); +#if PY_MAJOR_VERSION >= 3 + kwdefs = PyFunction_GET_KW_DEFAULTS(func); +#endif + if (argdefs != NULL) { + d = &PyTuple_GET_ITEM(argdefs, 0); + nd = Py_SIZE(argdefs); + } + else { + d = NULL; + nd = 0; + } +#if PY_MAJOR_VERSION >= 3 + result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, kwdefs, closure); +#else + result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, closure); +#endif + Py_XDECREF(kwtuple); +done: + Py_LeaveRecursiveCall(); + return result; +} +#endif +#endif + +/* PyObjectCall2Args */ + static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { + PyObject *args, *result = NULL; + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyFunction_FastCall(function, args, 2); + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyCFunction_FastCall(function, args, 2); + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(arg1); + PyTuple_SET_ITEM(args, 0, arg1); + Py_INCREF(arg2); + PyTuple_SET_ITEM(args, 1, arg2); + Py_INCREF(function); + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); +done: + return result; +} + +/* PyObjectCallMethO */ + #if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallOneArg */ + #if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, &arg, 1); + } +#endif + if (likely(PyCFunction_Check(func))) { + if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { + return __Pyx_PyObject_CallMethO(func, arg); +#if CYTHON_FAST_PYCCALL + } else if (__Pyx_PyFastCFunction_Check(func)) { + return __Pyx_PyCFunction_FastCall(func, &arg, 1); +#endif + } + } + return __Pyx__PyObject_CallOneArg(func, arg); +} +#else +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_Pack(1, arg); + if (unlikely(!args)) return NULL; + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +#endif + +/* PyFloatBinop */ + #if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyFloat_AddObjC(PyObject *op1, PyObject *op2, double floatval, int inplace, int zerodivision_check) { + const double b = floatval; + double a, result; + (void)inplace; + (void)zerodivision_check; + if (likely(PyFloat_CheckExact(op1))) { + a = PyFloat_AS_DOUBLE(op1); + + } else + #if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(op1))) { + a = (double) PyInt_AS_LONG(op1); + + } else + #endif + if (likely(PyLong_CheckExact(op1))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)op1)->ob_digit; + const Py_ssize_t size = Py_SIZE(op1); + switch (size) { + case 0: a = 0.0; break; + case -1: a = -(double) digits[0]; break; + case 1: a = (double) digits[0]; break; + case -2: + case 2: + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (1 * PyLong_SHIFT < 53))) { + a = (double) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + if ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) { + if (size == -2) + a = -a; + break; + } + } + CYTHON_FALLTHROUGH; + case -3: + case 3: + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53))) { + a = (double) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + if ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) { + if (size == -3) + a = -a; + break; + } + } + CYTHON_FALLTHROUGH; + case -4: + case 4: + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53))) { + a = (double) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + if ((8 * sizeof(unsigned long) < 53) || (4 * PyLong_SHIFT < 53) || (a < (double) ((PY_LONG_LONG)1 << 53))) { + if (size == -4) + a = -a; + break; + } + } + CYTHON_FALLTHROUGH; + default: + #else + { + #endif + a = PyLong_AsDouble(op1); + if (unlikely(a == -1.0 && PyErr_Occurred())) return NULL; + + } + } else { + return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); + } + + PyFPE_START_PROTECT("add", return NULL) + result = a + b; + PyFPE_END_PROTECT(result) + return PyFloat_FromDouble(result); +} +#endif + +/* PyErrFetchRestore */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} +#endif + +/* WriteUnraisableException */ + static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, + CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, + int full_traceback, CYTHON_UNUSED int nogil) { + PyObject *old_exc, *old_val, *old_tb; + PyObject *ctx; + __Pyx_PyThreadState_declare +#ifdef WITH_THREAD + PyGILState_STATE state; + if (nogil) + state = PyGILState_Ensure(); +#ifdef _MSC_VER + else state = (PyGILState_STATE)-1; +#endif +#endif + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); + if (full_traceback) { + Py_XINCREF(old_exc); + Py_XINCREF(old_val); + Py_XINCREF(old_tb); + __Pyx_ErrRestore(old_exc, old_val, old_tb); + PyErr_PrintEx(1); + } + #if PY_MAJOR_VERSION < 3 + ctx = PyString_FromString(name); + #else + ctx = PyUnicode_FromString(name); + #endif + __Pyx_ErrRestore(old_exc, old_val, old_tb); + if (!ctx) { + PyErr_WriteUnraisable(Py_None); + } else { + PyErr_WriteUnraisable(ctx); + Py_DECREF(ctx); + } +#ifdef WITH_THREAD + if (nogil) + PyGILState_Release(state); +#endif +} + +/* RaiseException */ + #if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + __Pyx_PyThreadState_declare + Py_XINCREF(type); + if (!value || value == Py_None) + value = NULL; + else + Py_INCREF(value); + if (!tb || tb == Py_None) + tb = NULL; + else { + Py_INCREF(tb); + if (!PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + } + if (PyType_Check(type)) { +#if CYTHON_COMPILING_IN_PYPY + if (!value) { + Py_INCREF(Py_None); + value = Py_None; + } +#endif + PyErr_NormalizeException(&type, &value, &tb); + } else { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + value = type; + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + } + __Pyx_PyThreadState_assign + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + PyObject* owned_instance = NULL; + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (PyExceptionClass_Check(type)) { + PyObject *instance_class = NULL; + if (value && PyExceptionInstance_Check(value)) { + instance_class = (PyObject*) Py_TYPE(value); + if (instance_class != type) { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { + instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; + } + } + } + if (!instance_class) { + PyObject *args; + if (!value) + args = PyTuple_New(0); + else if (PyTuple_Check(value)) { + Py_INCREF(value); + args = value; + } else + args = PyTuple_Pack(1, value); + if (!args) + goto bad; + owned_instance = PyObject_Call(type, args, NULL); + Py_DECREF(args); + if (!owned_instance) + goto bad; + value = owned_instance; + if (!PyExceptionInstance_Check(value)) { + PyErr_Format(PyExc_TypeError, + "calling %R should have returned an instance of " + "BaseException, not %R", + type, Py_TYPE(value)); + goto bad; + } + } + } else { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + if (cause == Py_None) { + fixed_cause = NULL; + } else if (PyExceptionClass_Check(cause)) { + fixed_cause = PyObject_CallObject(cause, NULL); + if (fixed_cause == NULL) + goto bad; + } else if (PyExceptionInstance_Check(cause)) { + fixed_cause = cause; + Py_INCREF(fixed_cause); + } else { + PyErr_SetString(PyExc_TypeError, + "exception causes must derive from " + "BaseException"); + goto bad; + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } +#endif + } +bad: + Py_XDECREF(owned_instance); + return; +} +#endif + +/* PyObjectCallNoArg */ + #if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, NULL, 0); + } +#endif +#ifdef __Pyx_CyFunction_USED + if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) +#else + if (likely(PyCFunction_Check(func))) +#endif + { + if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { + return __Pyx_PyObject_CallMethO(func, NULL); + } + } + return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); +} +#endif + +/* DictGetItem */ + #if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { + PyObject *value; + value = PyDict_GetItemWithError(d, key); + if (unlikely(!value)) { + if (!PyErr_Occurred()) { + if (unlikely(PyTuple_Check(key))) { + PyObject* args = PyTuple_Pack(1, key); + if (likely(args)) { + PyErr_SetObject(PyExc_KeyError, args); + Py_DECREF(args); + } + } else { + PyErr_SetObject(PyExc_KeyError, key); + } + } + return NULL; + } + Py_INCREF(value); + return value; +} +#endif + +/* PyIntCompare */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_NeObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED long inplace) { + if (op1 == op2) { + Py_RETURN_FALSE; + } + #if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(op1))) { + const long b = intval; + long a = PyInt_AS_LONG(op1); + if (a != b) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } + #endif + #if CYTHON_USE_PYLONG_INTERNALS + if (likely(PyLong_CheckExact(op1))) { + int unequal; + unsigned long uintval; + Py_ssize_t size = Py_SIZE(op1); + const digit* digits = ((PyLongObject*)op1)->ob_digit; + if (intval == 0) { + if (size != 0) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } else if (intval < 0) { + if (size >= 0) + Py_RETURN_TRUE; + intval = -intval; + size = -size; + } else { + if (size <= 0) + Py_RETURN_TRUE; + } + uintval = (unsigned long) intval; +#if PyLong_SHIFT * 4 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 4)) { + unequal = (size != 5) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[4] != ((uintval >> (4 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif +#if PyLong_SHIFT * 3 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 3)) { + unequal = (size != 4) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[3] != ((uintval >> (3 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif +#if PyLong_SHIFT * 2 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 2)) { + unequal = (size != 3) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)) | (digits[2] != ((uintval >> (2 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif +#if PyLong_SHIFT * 1 < SIZEOF_LONG*8 + if (uintval >> (PyLong_SHIFT * 1)) { + unequal = (size != 2) || (digits[0] != (uintval & (unsigned long) PyLong_MASK)) + | (digits[1] != ((uintval >> (1 * PyLong_SHIFT)) & (unsigned long) PyLong_MASK)); + } else +#endif + unequal = (size != 1) || (((unsigned long) digits[0]) != (uintval & (unsigned long) PyLong_MASK)); + if (unequal != 0) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } + #endif + if (PyFloat_CheckExact(op1)) { + const long b = intval; + double a = PyFloat_AS_DOUBLE(op1); + if ((double)a != (double)b) Py_RETURN_TRUE; else Py_RETURN_FALSE; + } + return ( + PyObject_RichCompare(op1, op2, Py_NE)); +} + +/* ExtTypeTest */ + static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +/* MemviewSliceInit */ + static int +__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference) +{ + __Pyx_RefNannyDeclarations + int i, retval=-1; + Py_buffer *buf = &memview->view; + __Pyx_RefNannySetupContext("init_memviewslice", 0); + if (unlikely(memviewslice->memview || memviewslice->data)) { + PyErr_SetString(PyExc_ValueError, + "memviewslice is already initialized!"); + goto fail; + } + if (buf->strides) { + for (i = 0; i < ndim; i++) { + memviewslice->strides[i] = buf->strides[i]; + } + } else { + Py_ssize_t stride = buf->itemsize; + for (i = ndim - 1; i >= 0; i--) { + memviewslice->strides[i] = stride; + stride *= buf->shape[i]; + } + } + for (i = 0; i < ndim; i++) { + memviewslice->shape[i] = buf->shape[i]; + if (buf->suboffsets) { + memviewslice->suboffsets[i] = buf->suboffsets[i]; + } else { + memviewslice->suboffsets[i] = -1; + } + } + memviewslice->memview = memview; + memviewslice->data = (char *)buf->buf; + if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { + Py_INCREF(memview); + } + retval = 0; + goto no_fail; +fail: + memviewslice->memview = 0; + memviewslice->data = 0; + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} +#ifndef Py_NO_RETURN +#define Py_NO_RETURN +#endif +static void __pyx_fatalerror(const char *fmt, ...) Py_NO_RETURN { + va_list vargs; + char msg[200]; +#ifdef HAVE_STDARG_PROTOTYPES + va_start(vargs, fmt); +#else + va_start(vargs); +#endif + vsnprintf(msg, 200, fmt, vargs); + va_end(vargs); + Py_FatalError(msg); +} +static CYTHON_INLINE int +__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)++; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE int +__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)--; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE void +__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) +{ + int first_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (unlikely(!memview || (PyObject *) memview == Py_None)) + return; + if (unlikely(__pyx_get_slice_count(memview) < 0)) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + first_time = __pyx_add_acquisition_count(memview) == 0; + if (unlikely(first_time)) { + if (have_gil) { + Py_INCREF((PyObject *) memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_INCREF((PyObject *) memview); + PyGILState_Release(_gilstate); + } + } +} +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, + int have_gil, int lineno) { + int last_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (unlikely(!memview || (PyObject *) memview == Py_None)) { + memslice->memview = NULL; + return; + } + if (unlikely(__pyx_get_slice_count(memview) <= 0)) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + last_time = __pyx_sub_acquisition_count(memview) == 1; + memslice->data = NULL; + if (unlikely(last_time)) { + if (have_gil) { + Py_CLEAR(memslice->memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_CLEAR(memslice->memview); + PyGILState_Release(_gilstate); + } + } else { + memslice->memview = NULL; + } +} + +/* GetTopmostException */ + #if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +/* ArgTypeTest */ + static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) +{ + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + else if (exact) { + #if PY_MAJOR_VERSION == 2 + if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; + #endif + } + else { + if (likely(__Pyx_TypeCheck(obj, type))) return 1; + } + PyErr_Format(PyExc_TypeError, + "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); + return 0; +} + +/* BytesEquals */ + static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else + if (s1 == s2) { + return (equals == Py_EQ); + } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { + const char *ps1, *ps2; + Py_ssize_t length = PyBytes_GET_SIZE(s1); + if (length != PyBytes_GET_SIZE(s2)) + return (equals == Py_NE); + ps1 = PyBytes_AS_STRING(s1); + ps2 = PyBytes_AS_STRING(s2); + if (ps1[0] != ps2[0]) { + return (equals == Py_NE); + } else if (length == 1) { + return (equals == Py_EQ); + } else { + int result; +#if CYTHON_USE_UNICODE_INTERNALS + Py_hash_t hash1, hash2; + hash1 = ((PyBytesObject*)s1)->ob_shash; + hash2 = ((PyBytesObject*)s2)->ob_shash; + if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { + return (equals == Py_NE); + } +#endif + result = memcmp(ps1, ps2, (size_t)length); + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { + return (equals == Py_NE); + } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { + return (equals == Py_NE); + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +#endif +} + +/* UnicodeEquals */ + static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else +#if PY_MAJOR_VERSION < 3 + PyObject* owned_ref = NULL; +#endif + int s1_is_unicode, s2_is_unicode; + if (s1 == s2) { + goto return_eq; + } + s1_is_unicode = PyUnicode_CheckExact(s1); + s2_is_unicode = PyUnicode_CheckExact(s2); +#if PY_MAJOR_VERSION < 3 + if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { + owned_ref = PyUnicode_FromObject(s2); + if (unlikely(!owned_ref)) + return -1; + s2 = owned_ref; + s2_is_unicode = 1; + } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { + owned_ref = PyUnicode_FromObject(s1); + if (unlikely(!owned_ref)) + return -1; + s1 = owned_ref; + s1_is_unicode = 1; + } else if (((!s2_is_unicode) & (!s1_is_unicode))) { + return __Pyx_PyBytes_Equals(s1, s2, equals); + } +#endif + if (s1_is_unicode & s2_is_unicode) { + Py_ssize_t length; + int kind; + void *data1, *data2; + if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) + return -1; + length = __Pyx_PyUnicode_GET_LENGTH(s1); + if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { + goto return_ne; + } +#if CYTHON_USE_UNICODE_INTERNALS + { + Py_hash_t hash1, hash2; + #if CYTHON_PEP393_ENABLED + hash1 = ((PyASCIIObject*)s1)->hash; + hash2 = ((PyASCIIObject*)s2)->hash; + #else + hash1 = ((PyUnicodeObject*)s1)->hash; + hash2 = ((PyUnicodeObject*)s2)->hash; + #endif + if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { + goto return_ne; + } + } +#endif + kind = __Pyx_PyUnicode_KIND(s1); + if (kind != __Pyx_PyUnicode_KIND(s2)) { + goto return_ne; + } + data1 = __Pyx_PyUnicode_DATA(s1); + data2 = __Pyx_PyUnicode_DATA(s2); + if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { + goto return_ne; + } else if (length == 1) { + goto return_eq; + } else { + int result = memcmp(data1, data2, (size_t)(length * kind)); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & s2_is_unicode) { + goto return_ne; + } else if ((s2 == Py_None) & s1_is_unicode) { + goto return_ne; + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +return_eq: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ); +return_ne: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_NE); +#endif +} + +/* GetAttr */ + static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { +#if CYTHON_USE_TYPE_SLOTS +#if PY_MAJOR_VERSION >= 3 + if (likely(PyUnicode_Check(n))) +#else + if (likely(PyString_Check(n))) +#endif + return __Pyx_PyObject_GetAttrStr(o, n); +#endif + return PyObject_GetAttr(o, n); +} + +/* decode_c_string */ + static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { + Py_ssize_t length; + if (unlikely((start < 0) | (stop < 0))) { + size_t slen = strlen(cstring); + if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { + PyErr_SetString(PyExc_OverflowError, + "c-string too long to convert to Python"); + return NULL; + } + length = (Py_ssize_t) slen; + if (start < 0) { + start += length; + if (start < 0) + start = 0; + } + if (stop < 0) + stop += length; + } + if (unlikely(stop <= start)) + return __Pyx_NewRef(__pyx_empty_unicode); + length = stop - start; + cstring += start; + if (decode_func) { + return decode_func(cstring, length, errors); + } else { + return PyUnicode_Decode(cstring, length, encoding, errors); + } +} + +/* GetAttr3 */ + static PyObject *__Pyx_GetAttr3Default(PyObject *d) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + return NULL; + __Pyx_PyErr_Clear(); + Py_INCREF(d); + return d; +} +static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) { + PyObject *r = __Pyx_GetAttr(o, n); + return (likely(r)) ? r : __Pyx_GetAttr3Default(d); +} + +/* RaiseTooManyValuesToUnpack */ + static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { + PyErr_Format(PyExc_ValueError, + "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); +} + +/* RaiseNeedMoreValuesToUnpack */ + static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { + PyErr_Format(PyExc_ValueError, + "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", + index, (index == 1) ? "" : "s"); +} + +/* RaiseNoneIterError */ + static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); +} + +/* SwapException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = *type; + exc_info->exc_value = *value; + exc_info->exc_traceback = *tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = *type; + tstate->exc_value = *value; + tstate->exc_traceback = *tb; + #endif + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} +#else +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); + PyErr_SetExcInfo(*type, *value, *tb); + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} +#endif + +/* Import */ + static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_MAJOR_VERSION < 3 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_MAJOR_VERSION < 3 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + +/* FastTypeChecks */ + #if CYTHON_COMPILING_IN_CPYTHON +static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { + while (a) { + a = a->tp_base; + if (a == b) + return 1; + } + return b == &PyBaseObject_Type; +} +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { + PyObject *mro; + if (a == b) return 1; + mro = a->tp_mro; + if (likely(mro)) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(mro); + for (i = 0; i < n; i++) { + if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) + return 1; + } + return 0; + } + return __Pyx_InBases(a, b); +} +#if PY_MAJOR_VERSION == 2 +static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { + PyObject *exception, *value, *tb; + int res; + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&exception, &value, &tb); + res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + if (!res) { + res = PyObject_IsSubclass(err, exc_type2); + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + } + __Pyx_ErrRestore(exception, value, tb); + return res; +} +#else +static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { + int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; + if (!res) { + res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); + } + return res; +} +#endif +static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + assert(PyExceptionClass_Check(exc_type)); + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; i= 0 || (x^b) >= 0)) + return PyInt_FromLong(x); + return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + #endif + #if CYTHON_USE_PYLONG_INTERNALS + if (likely(PyLong_CheckExact(op1))) { + const long b = intval; + long a, x; +#ifdef HAVE_LONG_LONG + const PY_LONG_LONG llb = intval; + PY_LONG_LONG lla, llx; +#endif + const digit* digits = ((PyLongObject*)op1)->ob_digit; + const Py_ssize_t size = Py_SIZE(op1); + if (likely(__Pyx_sst_abs(size) <= 1)) { + a = likely(size) ? digits[0] : 0; + if (size == -1) a = -a; + } else { + switch (size) { + case -2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + default: return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + } + x = a + b; + return PyLong_FromLong(x); +#ifdef HAVE_LONG_LONG + long_long: + llx = lla + llb; + return PyLong_FromLongLong(llx); +#endif + + + } + #endif + if (PyFloat_CheckExact(op1)) { + const long b = intval; + double a = PyFloat_AS_DOUBLE(op1); + double result; + PyFPE_START_PROTECT("add", return NULL) + result = ((double)a) + (double)b; + PyFPE_END_PROTECT(result) + return PyFloat_FromDouble(result); + } + return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); +} +#endif + +/* None */ + static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { + PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); +} + +/* ImportFrom */ + static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { + PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); + if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Format(PyExc_ImportError, + #if PY_MAJOR_VERSION < 3 + "cannot import name %.230s", PyString_AS_STRING(name)); + #else + "cannot import name %S", name); + #endif + } + return value; +} + +/* HasAttr */ + static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) { + PyObject *r; + if (unlikely(!__Pyx_PyBaseString_Check(n))) { + PyErr_SetString(PyExc_TypeError, + "hasattr(): attribute name must be string"); + return -1; + } + r = __Pyx_GetAttr(o, n); + if (unlikely(!r)) { + PyErr_Clear(); + return 0; + } else { + Py_DECREF(r); + return 1; + } +} + +/* StringJoin */ + #if !CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyBytes_Join(PyObject* sep, PyObject* values) { + return PyObject_CallMethodObjArgs(sep, __pyx_n_s_join, values, NULL); +} +#endif + +/* PyObject_GenericGetAttrNoDict */ + #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) { + PyErr_Format(PyExc_AttributeError, +#if PY_MAJOR_VERSION >= 3 + "'%.50s' object has no attribute '%U'", + tp->tp_name, attr_name); +#else + "'%.50s' object has no attribute '%.400s'", + tp->tp_name, PyString_AS_STRING(attr_name)); +#endif + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) { + PyObject *descr; + PyTypeObject *tp = Py_TYPE(obj); + if (unlikely(!PyString_Check(attr_name))) { + return PyObject_GenericGetAttr(obj, attr_name); + } + assert(!tp->tp_dictoffset); + descr = _PyType_Lookup(tp, attr_name); + if (unlikely(!descr)) { + return __Pyx_RaiseGenericGetAttributeError(tp, attr_name); + } + Py_INCREF(descr); + #if PY_MAJOR_VERSION < 3 + if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS))) + #endif + { + descrgetfunc f = Py_TYPE(descr)->tp_descr_get; + if (unlikely(f)) { + PyObject *res = f(descr, obj, (PyObject *)tp); + Py_DECREF(descr); + return res; + } + } + return descr; +} +#endif + +/* PyObject_GenericGetAttr */ + #if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) { + if (unlikely(Py_TYPE(obj)->tp_dictoffset)) { + return PyObject_GenericGetAttr(obj, attr_name); + } + return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name); +} +#endif + +/* SetVTable */ + static int __Pyx_SetVtable(PyObject *dict, void *vtable) { +#if PY_VERSION_HEX >= 0x02070000 + PyObject *ob = PyCapsule_New(vtable, 0, 0); +#else + PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); +#endif + if (!ob) + goto bad; + if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) + goto bad; + Py_DECREF(ob); + return 0; +bad: + Py_XDECREF(ob); + return -1; +} + +/* PyObjectGetAttrStrNoError */ + static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + __Pyx_PyErr_Clear(); +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { + PyObject *result; +#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { + return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); + } +#endif + result = __Pyx_PyObject_GetAttrStr(obj, attr_name); + if (unlikely(!result)) { + __Pyx_PyObject_GetAttrStr_ClearAttributeError(); + } + return result; +} + +/* SetupReduce */ + static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { + int ret; + PyObject *name_attr; + name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2); + if (likely(name_attr)) { + ret = PyObject_RichCompareBool(name_attr, name, Py_EQ); + } else { + ret = -1; + } + if (unlikely(ret < 0)) { + PyErr_Clear(); + ret = 0; + } + Py_XDECREF(name_attr); + return ret; +} +static int __Pyx_setup_reduce(PyObject* type_obj) { + int ret = 0; + PyObject *object_reduce = NULL; + PyObject *object_reduce_ex = NULL; + PyObject *reduce = NULL; + PyObject *reduce_ex = NULL; + PyObject *reduce_cython = NULL; + PyObject *setstate = NULL; + PyObject *setstate_cython = NULL; +#if CYTHON_USE_PYTYPE_LOOKUP + if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#else + if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#endif +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#else + object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#endif + reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; + if (reduce_ex == object_reduce_ex) { +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#else + object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#endif + reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; + if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { + reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); + if (likely(reduce_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (reduce == object_reduce || PyErr_Occurred()) { + goto __PYX_BAD; + } + setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); + if (!setstate) PyErr_Clear(); + if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { + setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); + if (likely(setstate_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (!setstate || PyErr_Occurred()) { + goto __PYX_BAD; + } + } + PyType_Modified((PyTypeObject*)type_obj); + } + } + goto __PYX_GOOD; +__PYX_BAD: + if (!PyErr_Occurred()) + PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); + ret = -1; +__PYX_GOOD: +#if !CYTHON_USE_PYTYPE_LOOKUP + Py_XDECREF(object_reduce); + Py_XDECREF(object_reduce_ex); +#endif + Py_XDECREF(reduce); + Py_XDECREF(reduce_ex); + Py_XDECREF(reduce_cython); + Py_XDECREF(setstate); + Py_XDECREF(setstate_cython); + return ret; +} + +/* TypeImport */ + #ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, + size_t size, enum __Pyx_ImportType_CheckSize check_size) +{ + PyObject *result = 0; + char warning[200]; + Py_ssize_t basicsize; +#ifdef Py_LIMITED_API + PyObject *py_basicsize; +#endif + result = PyObject_GetAttrString(module, class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%.200s.%.200s is not a type object", + module_name, class_name); + goto bad; + } +#ifndef Py_LIMITED_API + basicsize = ((PyTypeObject *)result)->tp_basicsize; +#else + py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); + if (!py_basicsize) + goto bad; + basicsize = PyLong_AsSsize_t(py_basicsize); + Py_DECREF(py_basicsize); + py_basicsize = 0; + if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) + goto bad; +#endif + if ((size_t)basicsize < size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(result); + return NULL; +} +#endif + +/* GetVTable */ + static void* __Pyx_GetVtable(PyObject *dict) { + void* ptr; + PyObject *ob = PyObject_GetItem(dict, __pyx_n_s_pyx_vtable); + if (!ob) + goto bad; +#if PY_VERSION_HEX >= 0x02070000 + ptr = PyCapsule_GetPointer(ob, 0); +#else + ptr = PyCObject_AsVoidPtr(ob); +#endif + if (!ptr && !PyErr_Occurred()) + PyErr_SetString(PyExc_RuntimeError, "invalid vtable found for imported type"); + Py_DECREF(ob); + return ptr; +bad: + Py_XDECREF(ob); + return NULL; +} + +/* CLineInTraceback */ + #ifndef CYTHON_CLINE_IN_TRACEBACK +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { + PyObject *use_cline; + PyObject *ptype, *pvalue, *ptraceback; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject **cython_runtime_dict; +#endif + if (unlikely(!__pyx_cython_runtime)) { + return c_line; + } + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); +#if CYTHON_COMPILING_IN_CPYTHON + cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); + if (likely(cython_runtime_dict)) { + __PYX_PY_DICT_LOOKUP_IF_MODIFIED( + use_cline, *cython_runtime_dict, + __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) + } else +#endif + { + PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); + if (use_cline_obj) { + use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; + Py_DECREF(use_cline_obj); + } else { + PyErr_Clear(); + use_cline = NULL; + } + } + if (!use_cline) { + c_line = 0; + PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); + } + else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { + c_line = 0; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + return c_line; +} +#endif + +/* CodeObjectCache */ + static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = start + (end - start) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +/* AddTraceback */ + #include "compile.h" +#include "frameobject.h" +#include "traceback.h" +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyObject *py_srcfile = 0; + PyObject *py_funcname = 0; + #if PY_MAJOR_VERSION < 3 + py_srcfile = PyString_FromString(filename); + #else + py_srcfile = PyUnicode_FromString(filename); + #endif + if (!py_srcfile) goto bad; + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + #else + py_funcname = PyUnicode_FromString(funcname); + #endif + } + if (!py_funcname) goto bad; + py_code = __Pyx_PyCode_New( + 0, + 0, + 0, + 0, + 0, + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + Py_DECREF(py_funcname); + return py_code; +bad: + Py_XDECREF(py_srcfile); + Py_XDECREF(py_funcname); + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + if (c_line) { + c_line = __Pyx_CLineForTraceback(tstate, c_line); + } + py_code = __pyx_find_code_object(c_line ? -c_line : py_line); + if (!py_code) { + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) goto bad; + __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); + } + py_frame = PyFrame_New( + tstate, /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + __pyx_d, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + __Pyx_PyFrame_SetLineNumber(py_frame, py_line); + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { + if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); + if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); + if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); + PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); + return -1; +} +static void __Pyx_ReleaseBuffer(Py_buffer *view) { + PyObject *obj = view->obj; + if (!obj) return; + if (PyObject_CheckBuffer(obj)) { + PyBuffer_Release(view); + return; + } + if ((0)) {} + view->obj = NULL; + Py_DECREF(obj); +} +#endif + + + /* MemviewSliceIsContig */ + static int +__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) +{ + int i, index, step, start; + Py_ssize_t itemsize = mvs.memview->view.itemsize; + if (order == 'F') { + step = 1; + start = 0; + } else { + step = -1; + start = ndim - 1; + } + for (i = 0; i < ndim; i++) { + index = start + step * i; + if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) + return 0; + itemsize *= mvs.shape[index]; + } + return 1; +} + +/* OverlappingSlices */ + static void +__pyx_get_array_memory_extents(__Pyx_memviewslice *slice, + void **out_start, void **out_end, + int ndim, size_t itemsize) +{ + char *start, *end; + int i; + start = end = slice->data; + for (i = 0; i < ndim; i++) { + Py_ssize_t stride = slice->strides[i]; + Py_ssize_t extent = slice->shape[i]; + if (extent == 0) { + *out_start = *out_end = start; + return; + } else { + if (stride > 0) + end += stride * (extent - 1); + else + start += stride * (extent - 1); + } + } + *out_start = start; + *out_end = end + itemsize; +} +static int +__pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize) +{ + void *start1, *end1, *start2, *end2; + __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); + __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); + return (start1 < end2) && (start2 < end1); +} + +/* Capsule */ + static CYTHON_INLINE PyObject * +__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) +{ + PyObject *cobj; +#if PY_VERSION_HEX >= 0x02070000 + cobj = PyCapsule_New(p, sig, NULL); +#else + cobj = PyCObject_FromVoidPtr(p, NULL); +#endif + return cobj; +} + +static PyObject* __pyx_convert__to_py_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell s) { + PyObject* res; + PyObject* member; + res = __Pyx_PyDict_NewPresized(12); if (unlikely(!res)) return NULL; + member = __Pyx_PyInt_From_Py_intptr_t(s.parent); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_parent, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_carray_to_py___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t(s.children, 8); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_children, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_PyInt_From_Py_intptr_t(s.cell_id); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_cell_id, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_PyInt_From_Py_intptr_t(s.point_index); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_point_index, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_PyBool_FromLong(s.is_leaf); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_is_leaf, member) < 0)) goto bad; + Py_DECREF(member); + member = PyFloat_FromDouble(s.squared_max_width); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_squared_max_width, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_PyInt_From_Py_intptr_t(s.depth); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_depth, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_PyInt_From_Py_intptr_t(s.cumulative_size); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_cumulative_size, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_carray_to_py___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(s.center, 3); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_center, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_carray_to_py___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(s.barycenter, 3); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_barycenter, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_carray_to_py___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(s.min_bounds, 3); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_min_bounds, member) < 0)) goto bad; + Py_DECREF(member); + member = __Pyx_carray_to_py___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(s.max_bounds, 3); if (unlikely(!member)) goto bad; + if (unlikely(PyDict_SetItem(res, __pyx_n_s_max_bounds, member) < 0)) goto bad; + Py_DECREF(member); + return res; + bad: + Py_XDECREF(member); + Py_DECREF(res); + return NULL; + } + /* CIntFromPyVerify */ + #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ + } + +/* MemviewDtypeToObject */ + static CYTHON_INLINE PyObject *__pyx_memview_get_nn_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell(const char *itemp) { + return (PyObject *) __pyx_convert__to_py_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell(*(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *) itemp); +} +static CYTHON_INLINE int __pyx_memview_set_nn_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell(const char *itemp, PyObject *obj) { + struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell value = __pyx_convert__from_py_struct____pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell(obj); + if (PyErr_Occurred()) + return 0; + *(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *) itemp = value; + return 1; +} + +/* IsLittleEndian */ + static CYTHON_INLINE int __Pyx_Is_Little_Endian(void) +{ + union { + uint32_t u32; + uint8_t u8[4]; + } S; + S.u32 = 0x01020304; + return S.u8[0] == 4; +} + +/* BufferFormatCheck */ + static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type) { + stack[0].field = &ctx->root; + stack[0].parent_offset = 0; + ctx->root.type = type; + ctx->root.name = "buffer dtype"; + ctx->root.offset = 0; + ctx->head = stack; + ctx->head->field = &ctx->root; + ctx->fmt_offset = 0; + ctx->head->parent_offset = 0; + ctx->new_packmode = '@'; + ctx->enc_packmode = '@'; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->is_complex = 0; + ctx->is_valid_array = 0; + ctx->struct_alignment = 0; + while (type->typegroup == 'S') { + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = 0; + type = type->fields->type; + } +} +static int __Pyx_BufFmt_ParseNumber(const char** ts) { + int count; + const char* t = *ts; + if (*t < '0' || *t > '9') { + return -1; + } else { + count = *t++ - '0'; + while (*t >= '0' && *t <= '9') { + count *= 10; + count += *t++ - '0'; + } + } + *ts = t; + return count; +} +static int __Pyx_BufFmt_ExpectNumber(const char **ts) { + int number = __Pyx_BufFmt_ParseNumber(ts); + if (number == -1) + PyErr_Format(PyExc_ValueError,\ + "Does not understand character buffer dtype format string ('%c')", **ts); + return number; +} +static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { + PyErr_Format(PyExc_ValueError, + "Unexpected format string character: '%c'", ch); +} +static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { + switch (ch) { + case '?': return "'bool'"; + case 'c': return "'char'"; + case 'b': return "'signed char'"; + case 'B': return "'unsigned char'"; + case 'h': return "'short'"; + case 'H': return "'unsigned short'"; + case 'i': return "'int'"; + case 'I': return "'unsigned int'"; + case 'l': return "'long'"; + case 'L': return "'unsigned long'"; + case 'q': return "'long long'"; + case 'Q': return "'unsigned long long'"; + case 'f': return (is_complex ? "'complex float'" : "'float'"); + case 'd': return (is_complex ? "'complex double'" : "'double'"); + case 'g': return (is_complex ? "'complex long double'" : "'long double'"); + case 'T': return "a struct"; + case 'O': return "Python object"; + case 'P': return "a pointer"; + case 's': case 'p': return "a string"; + case 0: return "end"; + default: return "unparseable format string"; + } +} +static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return 2; + case 'i': case 'I': case 'l': case 'L': return 4; + case 'q': case 'Q': return 8; + case 'f': return (is_complex ? 8 : 4); + case 'd': return (is_complex ? 16 : 8); + case 'g': { + PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); + return 0; + } + case 'O': case 'P': return sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(short); + case 'i': case 'I': return sizeof(int); + case 'l': case 'L': return sizeof(long); + #ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(PY_LONG_LONG); + #endif + case 'f': return sizeof(float) * (is_complex ? 2 : 1); + case 'd': return sizeof(double) * (is_complex ? 2 : 1); + case 'g': return sizeof(long double) * (is_complex ? 2 : 1); + case 'O': case 'P': return sizeof(void*); + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +typedef struct { char c; short x; } __Pyx_st_short; +typedef struct { char c; int x; } __Pyx_st_int; +typedef struct { char c; long x; } __Pyx_st_long; +typedef struct { char c; float x; } __Pyx_st_float; +typedef struct { char c; double x; } __Pyx_st_double; +typedef struct { char c; long double x; } __Pyx_st_longdouble; +typedef struct { char c; void *x; } __Pyx_st_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_st_float) - sizeof(float); + case 'd': return sizeof(__Pyx_st_double) - sizeof(double); + case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +/* These are for computing the padding at the end of the struct to align + on the first member of the struct. This will probably the same as above, + but we don't have any guarantees. + */ +typedef struct { short x; char c; } __Pyx_pad_short; +typedef struct { int x; char c; } __Pyx_pad_int; +typedef struct { long x; char c; } __Pyx_pad_long; +typedef struct { float x; char c; } __Pyx_pad_float; +typedef struct { double x; char c; } __Pyx_pad_double; +typedef struct { long double x; char c; } __Pyx_pad_longdouble; +typedef struct { void *x; char c; } __Pyx_pad_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); + case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); + case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { + switch (ch) { + case 'c': + return 'H'; + case 'b': case 'h': case 'i': + case 'l': case 'q': case 's': case 'p': + return 'I'; + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': + return 'U'; + case 'f': case 'd': case 'g': + return (is_complex ? 'C' : 'R'); + case 'O': + return 'O'; + case 'P': + return 'P'; + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { + if (ctx->head == NULL || ctx->head->field == &ctx->root) { + const char* expected; + const char* quote; + if (ctx->head == NULL) { + expected = "end"; + quote = ""; + } else { + expected = ctx->head->field->type->name; + quote = "'"; + } + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected %s%s%s but got %s", + quote, expected, quote, + __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); + } else { + __Pyx_StructField* field = ctx->head->field; + __Pyx_StructField* parent = (ctx->head - 1)->field; + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", + field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), + parent->type->name, field->name); + } +} +static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { + char group; + size_t size, offset, arraysize = 1; + if (ctx->enc_type == 0) return 0; + if (ctx->head->field->type->arraysize[0]) { + int i, ndim = 0; + if (ctx->enc_type == 's' || ctx->enc_type == 'p') { + ctx->is_valid_array = ctx->head->field->type->ndim == 1; + ndim = 1; + if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { + PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %zu", + ctx->head->field->type->arraysize[0], ctx->enc_count); + return -1; + } + } + if (!ctx->is_valid_array) { + PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", + ctx->head->field->type->ndim, ndim); + return -1; + } + for (i = 0; i < ctx->head->field->type->ndim; i++) { + arraysize *= ctx->head->field->type->arraysize[i]; + } + ctx->is_valid_array = 0; + ctx->enc_count = 1; + } + group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); + do { + __Pyx_StructField* field = ctx->head->field; + __Pyx_TypeInfo* type = field->type; + if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { + size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); + } else { + size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); + } + if (ctx->enc_packmode == '@') { + size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); + size_t align_mod_offset; + if (align_at == 0) return -1; + align_mod_offset = ctx->fmt_offset % align_at; + if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; + if (ctx->struct_alignment == 0) + ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, + ctx->is_complex); + } + if (type->size != size || type->typegroup != group) { + if (type->typegroup == 'C' && type->fields != NULL) { + size_t parent_offset = ctx->head->parent_offset + field->offset; + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = parent_offset; + continue; + } + if ((type->typegroup == 'H' || group == 'H') && type->size == size) { + } else { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + } + offset = ctx->head->parent_offset + field->offset; + if (ctx->fmt_offset != offset) { + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", + (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); + return -1; + } + ctx->fmt_offset += size; + if (arraysize) + ctx->fmt_offset += (arraysize - 1) * size; + --ctx->enc_count; + while (1) { + if (field == &ctx->root) { + ctx->head = NULL; + if (ctx->enc_count != 0) { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + break; + } + ctx->head->field = ++field; + if (field->type == NULL) { + --ctx->head; + field = ctx->head->field; + continue; + } else if (field->type->typegroup == 'S') { + size_t parent_offset = ctx->head->parent_offset + field->offset; + if (field->type->fields->type == NULL) continue; + field = field->type->fields; + ++ctx->head; + ctx->head->field = field; + ctx->head->parent_offset = parent_offset; + break; + } else { + break; + } + } + } while (ctx->enc_count); + ctx->enc_type = 0; + ctx->is_complex = 0; + return 0; +} +static PyObject * +__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) +{ + const char *ts = *tsp; + int i = 0, number, ndim; + ++ts; + if (ctx->new_count != 1) { + PyErr_SetString(PyExc_ValueError, + "Cannot handle repeated arrays in format string"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; + while (*ts && *ts != ')') { + switch (*ts) { + case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; + default: break; + } + number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) + return PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %d", + ctx->head->field->type->arraysize[i], number); + if (*ts != ',' && *ts != ')') + return PyErr_Format(PyExc_ValueError, + "Expected a comma in format string, got '%c'", *ts); + if (*ts == ',') ts++; + i++; + } + if (i != ndim) + return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", + ctx->head->field->type->ndim, i); + if (!*ts) { + PyErr_SetString(PyExc_ValueError, + "Unexpected end of format string, expected ')'"); + return NULL; + } + ctx->is_valid_array = 1; + ctx->new_count = 1; + *tsp = ++ts; + return Py_None; +} +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { + int got_Z = 0; + while (1) { + switch(*ts) { + case 0: + if (ctx->enc_type != 0 && ctx->head == NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + if (ctx->head != NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + return ts; + case ' ': + case '\r': + case '\n': + ++ts; + break; + case '<': + if (!__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '>': + case '!': + if (__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '=': + case '@': + case '^': + ctx->new_packmode = *ts++; + break; + case 'T': + { + const char* ts_after_sub; + size_t i, struct_count = ctx->new_count; + size_t struct_alignment = ctx->struct_alignment; + ctx->new_count = 1; + ++ts; + if (*ts != '{') { + PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + ctx->enc_count = 0; + ctx->struct_alignment = 0; + ++ts; + ts_after_sub = ts; + for (i = 0; i != struct_count; ++i) { + ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); + if (!ts_after_sub) return NULL; + } + ts = ts_after_sub; + if (struct_alignment) ctx->struct_alignment = struct_alignment; + } + break; + case '}': + { + size_t alignment = ctx->struct_alignment; + ++ts; + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + if (alignment && ctx->fmt_offset % alignment) { + ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); + } + } + return ts; + case 'x': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->fmt_offset += ctx->new_count; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->enc_packmode = ctx->new_packmode; + ++ts; + break; + case 'Z': + got_Z = 1; + ++ts; + if (*ts != 'f' && *ts != 'd' && *ts != 'g') { + __Pyx_BufFmt_RaiseUnexpectedChar('Z'); + return NULL; + } + CYTHON_FALLTHROUGH; + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case 'l': case 'L': case 'q': case 'Q': + case 'f': case 'd': case 'g': + case 'O': case 'p': + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { + ctx->enc_count += ctx->new_count; + ctx->new_count = 1; + got_Z = 0; + ++ts; + break; + } + CYTHON_FALLTHROUGH; + case 's': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_count = ctx->new_count; + ctx->enc_packmode = ctx->new_packmode; + ctx->enc_type = *ts; + ctx->is_complex = got_Z; + ++ts; + ctx->new_count = 1; + got_Z = 0; + break; + case ':': + ++ts; + while(*ts != ':') ++ts; + ++ts; + break; + case '(': + if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; + break; + default: + { + int number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + ctx->new_count = (size_t)number; + } + } + } +} + +/* TypeInfoCompare */ + static int +__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) +{ + int i; + if (!a || !b) + return 0; + if (a == b) + return 1; + if (a->size != b->size || a->typegroup != b->typegroup || + a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { + if (a->typegroup == 'H' || b->typegroup == 'H') { + return a->size == b->size; + } else { + return 0; + } + } + if (a->ndim) { + for (i = 0; i < a->ndim; i++) + if (a->arraysize[i] != b->arraysize[i]) + return 0; + } + if (a->typegroup == 'S') { + if (a->flags != b->flags) + return 0; + if (a->fields || b->fields) { + if (!(a->fields && b->fields)) + return 0; + for (i = 0; a->fields[i].type && b->fields[i].type; i++) { + __Pyx_StructField *field_a = a->fields + i; + __Pyx_StructField *field_b = b->fields + i; + if (field_a->offset != field_b->offset || + !__pyx_typeinfo_cmp(field_a->type, field_b->type)) + return 0; + } + return !a->fields[i].type && !b->fields[i].type; + } + } + return 1; +} + +/* MemviewSliceValidateAndInit */ + static int +__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) +{ + if (buf->shape[dim] <= 1) + return 1; + if (buf->strides) { + if (spec & __Pyx_MEMVIEW_CONTIG) { + if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { + if (unlikely(buf->strides[dim] != sizeof(void *))) { + PyErr_Format(PyExc_ValueError, + "Buffer is not indirectly contiguous " + "in dimension %d.", dim); + goto fail; + } + } else if (unlikely(buf->strides[dim] != buf->itemsize)) { + PyErr_SetString(PyExc_ValueError, + "Buffer and memoryview are not contiguous " + "in the same dimension."); + goto fail; + } + } + if (spec & __Pyx_MEMVIEW_FOLLOW) { + Py_ssize_t stride = buf->strides[dim]; + if (stride < 0) + stride = -stride; + if (unlikely(stride < buf->itemsize)) { + PyErr_SetString(PyExc_ValueError, + "Buffer and memoryview are not contiguous " + "in the same dimension."); + goto fail; + } + } + } else { + if (unlikely(spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1)) { + PyErr_Format(PyExc_ValueError, + "C-contiguous buffer is not contiguous in " + "dimension %d", dim); + goto fail; + } else if (unlikely(spec & (__Pyx_MEMVIEW_PTR))) { + PyErr_Format(PyExc_ValueError, + "C-contiguous buffer is not indirect in " + "dimension %d", dim); + goto fail; + } else if (unlikely(buf->suboffsets)) { + PyErr_SetString(PyExc_ValueError, + "Buffer exposes suboffsets but no strides"); + goto fail; + } + } + return 1; +fail: + return 0; +} +static int +__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) +{ + if (spec & __Pyx_MEMVIEW_DIRECT) { + if (unlikely(buf->suboffsets && buf->suboffsets[dim] >= 0)) { + PyErr_Format(PyExc_ValueError, + "Buffer not compatible with direct access " + "in dimension %d.", dim); + goto fail; + } + } + if (spec & __Pyx_MEMVIEW_PTR) { + if (unlikely(!buf->suboffsets || (buf->suboffsets[dim] < 0))) { + PyErr_Format(PyExc_ValueError, + "Buffer is not indirectly accessible " + "in dimension %d.", dim); + goto fail; + } + } + return 1; +fail: + return 0; +} +static int +__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) +{ + int i; + if (c_or_f_flag & __Pyx_IS_F_CONTIG) { + Py_ssize_t stride = 1; + for (i = 0; i < ndim; i++) { + if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { + PyErr_SetString(PyExc_ValueError, + "Buffer not fortran contiguous."); + goto fail; + } + stride = stride * buf->shape[i]; + } + } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { + Py_ssize_t stride = 1; + for (i = ndim - 1; i >- 1; i--) { + if (unlikely(stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1)) { + PyErr_SetString(PyExc_ValueError, + "Buffer not C contiguous."); + goto fail; + } + stride = stride * buf->shape[i]; + } + } + return 1; +fail: + return 0; +} +static int __Pyx_ValidateAndInit_memviewslice( + int *axes_specs, + int c_or_f_flag, + int buf_flags, + int ndim, + __Pyx_TypeInfo *dtype, + __Pyx_BufFmt_StackElem stack[], + __Pyx_memviewslice *memviewslice, + PyObject *original_obj) +{ + struct __pyx_memoryview_obj *memview, *new_memview; + __Pyx_RefNannyDeclarations + Py_buffer *buf; + int i, spec = 0, retval = -1; + __Pyx_BufFmt_Context ctx; + int from_memoryview = __pyx_memoryview_check(original_obj); + __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0); + if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) + original_obj)->typeinfo)) { + memview = (struct __pyx_memoryview_obj *) original_obj; + new_memview = NULL; + } else { + memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + original_obj, buf_flags, 0, dtype); + new_memview = memview; + if (unlikely(!memview)) + goto fail; + } + buf = &memview->view; + if (unlikely(buf->ndim != ndim)) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + ndim, buf->ndim); + goto fail; + } + if (new_memview) { + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (unlikely(!__Pyx_BufFmt_CheckString(&ctx, buf->format))) goto fail; + } + if (unlikely((unsigned) buf->itemsize != dtype->size)) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " + "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", + buf->itemsize, + (buf->itemsize > 1) ? "s" : "", + dtype->name, + dtype->size, + (dtype->size > 1) ? "s" : ""); + goto fail; + } + if (buf->len > 0) { + for (i = 0; i < ndim; i++) { + spec = axes_specs[i]; + if (unlikely(!__pyx_check_strides(buf, i, ndim, spec))) + goto fail; + if (unlikely(!__pyx_check_suboffsets(buf, i, ndim, spec))) + goto fail; + } + if (unlikely(buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))) + goto fail; + } + if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, + new_memview != NULL) == -1)) { + goto fail; + } + retval = 0; + goto no_fail; +fail: + Py_XDECREF(new_memview); + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} + +/* ObjectToMemviewSlice */ + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(PyObject *obj, int writable_flag) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS_RO | writable_flag, 1, + &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +/* ObjectToMemviewSlice */ + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(PyObject *obj, int writable_flag) { + __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; + __Pyx_BufFmt_StackElem stack[1]; + int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; + int retcode; + if (obj == Py_None) { + result.memview = (struct __pyx_memoryview_obj *) Py_None; + return result; + } + retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, + PyBUF_RECORDS_RO | writable_flag, 2, + &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t, stack, + &result, obj); + if (unlikely(retcode == -1)) + goto __pyx_fail; + return result; +__pyx_fail: + result.memview = NULL; + result.data = NULL; + return result; +} + +/* None */ + static CYTHON_INLINE long __Pyx_pow_long(long b, long e) { + long t = b; + switch (e) { + case 3: + t *= b; + CYTHON_FALLTHROUGH; + case 2: + t *= b; + CYTHON_FALLTHROUGH; + case 1: + return t; + case 0: + return 1; + } + #if 1 + if (unlikely(e<0)) return 0; + #endif + t = 1; + while (likely(e)) { + t *= (b * (e&1)) | ((~e)&1); + b *= b; + e >>= 1; + } + return t; +} + +/* None */ + static CYTHON_INLINE int __Pyx_ErrOccurredWithGIL(void) { + int err; + #ifdef WITH_THREAD + PyGILState_STATE _save = PyGILState_Ensure(); + #endif + err = !!PyErr_Occurred(); + #ifdef WITH_THREAD + PyGILState_Release(_save); + #endif + return err; +} + +/* MemviewDtypeToObject */ + static CYTHON_INLINE PyObject *__pyx_memview_get_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(const char *itemp) { + return (PyObject *) PyFloat_FromDouble(*(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *) itemp); +} +static CYTHON_INLINE int __pyx_memview_set_nn___pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t(const char *itemp, PyObject *obj) { + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t value = __pyx_PyFloat_AsFloat(obj); + if ((value == ((npy_float32)-1)) && PyErr_Occurred()) + return 0; + *(__pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *) itemp = value; + return 1; +} + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabsf(b.real) >= fabsf(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + float r = b.imag / b.real; + float s = (float)(1.0) / (b.real + b.imag * r); + return __pyx_t_float_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + float r = b.real / b.imag; + float s = (float)(1.0) / (b.imag + b.real * r); + return __pyx_t_float_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + float denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_float_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_float(a, a); + case 3: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, a); + case 4: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = powf(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2f(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_float(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabs(b.real) >= fabs(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + double r = b.imag / b.real; + double s = (double)(1.0) / (b.real + b.imag * r); + return __pyx_t_double_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + double r = b.real / b.imag; + double s = (double)(1.0) / (b.imag + b.real * r); + return __pyx_t_double_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + double denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_double_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_double(a, a); + case 3: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, a); + case 4: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = pow(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_double(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +/* MemviewSliceCopyTemplate */ + static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object) +{ + __Pyx_RefNannyDeclarations + int i; + __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; + struct __pyx_memoryview_obj *from_memview = from_mvs->memview; + Py_buffer *buf = &from_memview->view; + PyObject *shape_tuple = NULL; + PyObject *temp_int = NULL; + struct __pyx_array_obj *array_obj = NULL; + struct __pyx_memoryview_obj *memview_obj = NULL; + __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); + for (i = 0; i < ndim; i++) { + if (unlikely(from_mvs->suboffsets[i] >= 0)) { + PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " + "indirect dimensions (axis %d)", i); + goto fail; + } + } + shape_tuple = PyTuple_New(ndim); + if (unlikely(!shape_tuple)) { + goto fail; + } + __Pyx_GOTREF(shape_tuple); + for(i = 0; i < ndim; i++) { + temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); + if(unlikely(!temp_int)) { + goto fail; + } else { + PyTuple_SET_ITEM(shape_tuple, i, temp_int); + temp_int = NULL; + } + } + array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); + if (unlikely(!array_obj)) { + goto fail; + } + __Pyx_GOTREF(array_obj); + memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + (PyObject *) array_obj, contig_flag, + dtype_is_object, + from_mvs->memview->typeinfo); + if (unlikely(!memview_obj)) + goto fail; + if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) + goto fail; + if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, + dtype_is_object) < 0)) + goto fail; + goto no_fail; +fail: + __Pyx_XDECREF(new_mvs.memview); + new_mvs.memview = NULL; + new_mvs.data = NULL; +no_fail: + __Pyx_XDECREF(shape_tuple); + __Pyx_XDECREF(temp_int); + __Pyx_XDECREF(array_obj); + __Pyx_RefNannyFinishContext(); + return new_mvs; +} + +/* TypeInfoToFormat */ + static struct __pyx_typeinfo_string __Pyx_TypeInfoToFormat(__Pyx_TypeInfo *type) { + struct __pyx_typeinfo_string result = { {0} }; + char *buf = (char *) result.string; + size_t size = type->size; + switch (type->typegroup) { + case 'H': + *buf = 'c'; + break; + case 'I': + case 'U': + if (size == 1) + *buf = (type->is_unsigned) ? 'B' : 'b'; + else if (size == 2) + *buf = (type->is_unsigned) ? 'H' : 'h'; + else if (size == 4) + *buf = (type->is_unsigned) ? 'I' : 'i'; + else if (size == 8) + *buf = (type->is_unsigned) ? 'Q' : 'q'; + break; + case 'P': + *buf = 'P'; + break; + case 'C': + { + __Pyx_TypeInfo complex_type = *type; + complex_type.typegroup = 'R'; + complex_type.size /= 2; + *buf++ = 'Z'; + *buf = __Pyx_TypeInfoToFormat(&complex_type).string[0]; + break; + } + case 'R': + if (size == 4) + *buf = 'f'; + else if (size == 8) + *buf = 'd'; + else + *buf = 'g'; + break; + } + return result; +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(Py_intptr_t) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(Py_intptr_t) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(Py_intptr_t), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(Py_intptr_t) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (Py_intptr_t) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (Py_intptr_t) 0; + case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, digits[0]) + case 2: + if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 2 * PyLong_SHIFT) { + return (Py_intptr_t) (((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 3 * PyLong_SHIFT) { + return (Py_intptr_t) (((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 4 * PyLong_SHIFT) { + return (Py_intptr_t) (((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (Py_intptr_t) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (Py_intptr_t) 0; + case -1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, +digits[0]) + case -2: + if (8 * sizeof(Py_intptr_t) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + } +#endif + if (sizeof(Py_intptr_t) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + Py_intptr_t val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (Py_intptr_t) -1; + } + } else { + Py_intptr_t val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (Py_intptr_t) -1; + val = __Pyx_PyInt_As_Py_intptr_t(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to Py_intptr_t"); + return (Py_intptr_t) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to Py_intptr_t"); + return (Py_intptr_t) -1; +} + +/* CIntFromPy */ + static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + } +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(long) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(long) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(long) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(long), + little, !is_unsigned); + } +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(int) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(int) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(int) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(int), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(long) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (long) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(long) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + } +#endif + if (sizeof(long) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + long val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (long) -1; + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (long) -1; + val = __Pyx_PyInt_As_long(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to long"); + return (long) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long) -1; +} + +/* CIntFromPy */ + static CYTHON_INLINE size_t __Pyx_PyInt_As_size_t(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const size_t neg_one = (size_t) -1, const_zero = (size_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(size_t) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(size_t, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (size_t) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (size_t) 0; + case 1: __PYX_VERIFY_RETURN_INT(size_t, digit, digits[0]) + case 2: + if (8 * sizeof(size_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) >= 2 * PyLong_SHIFT) { + return (size_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(size_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) >= 3 * PyLong_SHIFT) { + return (size_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(size_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) >= 4 * PyLong_SHIFT) { + return (size_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (size_t) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(size_t) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(size_t, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(size_t) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(size_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (size_t) 0; + case -1: __PYX_VERIFY_RETURN_INT(size_t, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(size_t, digit, +digits[0]) + case -2: + if (8 * sizeof(size_t) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) { + return (size_t) (((size_t)-1)*(((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(size_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) { + return (size_t) ((((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) { + return (size_t) (((size_t)-1)*(((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(size_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) { + return (size_t) ((((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 4 * PyLong_SHIFT) { + return (size_t) (((size_t)-1)*(((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(size_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 4 * PyLong_SHIFT) { + return (size_t) ((((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + } +#endif + if (sizeof(size_t) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(size_t, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(size_t) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(size_t, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + size_t val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (size_t) -1; + } + } else { + size_t val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (size_t) -1; + val = __Pyx_PyInt_As_size_t(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to size_t"); + return (size_t) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to size_t"); + return (size_t) -1; +} + +/* CIntFromPy */ + static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const char neg_one = (char) -1, const_zero = (char) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(char) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (char) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (char) 0; + case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { + return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { + return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { + return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (char) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(char) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (char) 0; + case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) + case -2: + if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + } +#endif + if (sizeof(char) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + char val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (char) -1; + } + } else { + char val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (char) -1; + val = __Pyx_PyInt_As_char(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to char"); + return (char) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to char"); + return (char) -1; +} + +/* CheckBinaryVersion */ + static int __Pyx_check_binary_version(void) { + char ctversion[4], rtversion[4]; + PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); + PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); + if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { + char message[200]; + PyOS_snprintf(message, sizeof(message), + "compiletime version %s of module '%.100s' " + "does not match runtime version %s", + ctversion, __Pyx_MODULE_NAME, rtversion); + return PyErr_WarnEx(NULL, message, 1); + } + return 0; +} + +/* PyObjectSetAttrStr */ + #if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value) { + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_setattro)) + return tp->tp_setattro(obj, attr_name, value); +#if PY_MAJOR_VERSION < 3 + if (likely(tp->tp_setattr)) + return tp->tp_setattr(obj, PyString_AS_STRING(attr_name), value); +#endif + return PyObject_SetAttr(obj, attr_name, value); +} +#endif + +/* VoidPtrExport */ + static int __Pyx_ExportVoidPtr(PyObject *name, void *p, const char *sig) { + PyObject *d; + PyObject *cobj = 0; + d = PyDict_GetItem(__pyx_d, __pyx_n_s_pyx_capi); + Py_XINCREF(d); + if (!d) { + d = PyDict_New(); + if (!d) + goto bad; + if (__Pyx_PyObject_SetAttrStr(__pyx_m, __pyx_n_s_pyx_capi, d) < 0) + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + cobj = PyCapsule_New(p, sig, 0); +#else + cobj = PyCObject_FromVoidPtrAndDesc(p, (void *)sig, 0); +#endif + if (!cobj) + goto bad; + if (PyDict_SetItem(d, name, cobj) < 0) + goto bad; + Py_DECREF(cobj); + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(cobj); + Py_XDECREF(d); + return -1; +} + +/* FunctionImport */ + #ifndef __PYX_HAVE_RT_ImportFunction +#define __PYX_HAVE_RT_ImportFunction +static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (**f)(void), const char *sig) { + PyObject *d = 0; + PyObject *cobj = 0; + union { + void (*fp)(void); + void *p; + } tmp; + d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); + if (!d) + goto bad; + cobj = PyDict_GetItemString(d, funcname); + if (!cobj) { + PyErr_Format(PyExc_ImportError, + "%.200s does not export expected C function %.200s", + PyModule_GetName(module), funcname); + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + if (!PyCapsule_IsValid(cobj, sig)) { + PyErr_Format(PyExc_TypeError, + "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), funcname, sig, PyCapsule_GetName(cobj)); + goto bad; + } + tmp.p = PyCapsule_GetPointer(cobj, sig); +#else + {const char *desc, *s1, *s2; + desc = (const char *)PyCObject_GetDesc(cobj); + if (!desc) + goto bad; + s1 = desc; s2 = sig; + while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } + if (*s1 != *s2) { + PyErr_Format(PyExc_TypeError, + "C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), funcname, sig, desc); + goto bad; + } + tmp.p = PyCObject_AsVoidPtr(cobj);} +#endif + *f = tmp.fp; + if (!(*f)) + goto bad; + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(d); + return -1; +} +#endif + +/* InitStrings */ + static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + if (PyObject_Hash(*t->p) == -1) + return -1; + ++t; + } + return 0; +} + +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { + return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); +} +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { + Py_ssize_t ignore; + return __Pyx_PyObject_AsStringAndSize(o, &ignore); +} +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if !CYTHON_PEP393_ENABLED +static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + char* defenc_c; + PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); + if (!defenc) return NULL; + defenc_c = PyBytes_AS_STRING(defenc); +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + { + char* end = defenc_c + PyBytes_GET_SIZE(defenc); + char* c; + for (c = defenc_c; c < end; c++) { + if ((unsigned char) (*c) >= 128) { + PyUnicode_AsASCIIString(o); + return NULL; + } + } + } +#endif + *length = PyBytes_GET_SIZE(defenc); + return defenc_c; +} +#else +static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + if (likely(PyUnicode_IS_ASCII(o))) { + *length = PyUnicode_GET_LENGTH(o); + return PyUnicode_AsUTF8(o); + } else { + PyUnicode_AsASCIIString(o); + return NULL; + } +#else + return PyUnicode_AsUTF8AndSize(o, length); +#endif +} +#endif +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT + if ( +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + __Pyx_sys_getdefaultencoding_not_ascii && +#endif + PyUnicode_Check(o)) { + return __Pyx_PyUnicode_AsStringAndSize(o, length); + } else +#endif +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) + if (PyByteArray_Check(o)) { + *length = PyByteArray_GET_SIZE(o); + return PyByteArray_AS_STRING(o); + } else +#endif + { + char* result; + int r = PyBytes_AsStringAndSize(o, &result, length); + if (unlikely(r < 0)) { + return NULL; + } else { + return result; + } + } +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { + int retval; + if (unlikely(!x)) return -1; + retval = __Pyx_PyObject_IsTrue(x); + Py_DECREF(x); + return retval; +} +static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { +#if PY_MAJOR_VERSION >= 3 + if (PyLong_Check(result)) { + if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, + "__int__ returned non-int (type %.200s). " + "The ability to return an instance of a strict subclass of int " + "is deprecated, and may be removed in a future version of Python.", + Py_TYPE(result)->tp_name)) { + Py_DECREF(result); + return NULL; + } + return result; + } +#endif + PyErr_Format(PyExc_TypeError, + "__%.4s__ returned non-%.4s (type %.200s)", + type_name, type_name, Py_TYPE(result)->tp_name); + Py_DECREF(result); + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { +#if CYTHON_USE_TYPE_SLOTS + PyNumberMethods *m; +#endif + const char *name = NULL; + PyObject *res = NULL; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x) || PyLong_Check(x))) +#else + if (likely(PyLong_Check(x))) +#endif + return __Pyx_NewRef(x); +#if CYTHON_USE_TYPE_SLOTS + m = Py_TYPE(x)->tp_as_number; + #if PY_MAJOR_VERSION < 3 + if (m && m->nb_int) { + name = "int"; + res = m->nb_int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = m->nb_long(x); + } + #else + if (likely(m && m->nb_int)) { + name = "int"; + res = m->nb_int(x); + } + #endif +#else + if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { + res = PyNumber_Int(x); + } +#endif + if (likely(res)) { +#if PY_MAJOR_VERSION < 3 + if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { +#else + if (unlikely(!PyLong_CheckExact(res))) { +#endif + return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject *x; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(b); + } +#endif + if (likely(PyLong_CheckExact(b))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + } + } + #endif + return PyLong_AsSsize_t(b); + } + x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { + return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); +} +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { + return PyInt_FromSize_t(ival); +} + + +#endif /* Py_PYTHON_H */ diff --git a/stpredictions/models/OK3/_quad_tree.pxd b/stpredictions/models/OK3/_quad_tree.pxd new file mode 100644 index 000000000..ec04447fa --- /dev/null +++ b/stpredictions/models/OK3/_quad_tree.pxd @@ -0,0 +1,101 @@ +# cython: boundscheck=False +# cython: wraparound=False +# cython: cdivision=True +# +# Author: Thomas Moreau +# Author: Olivier Grisel + +# See quad_tree.pyx for details. + +import numpy as np +cimport numpy as np + +ctypedef np.npy_float32 DTYPE_t # Type of X +ctypedef np.npy_intp SIZE_t # Type for indices and counters +ctypedef np.npy_int32 INT32_t # Signed 32 bit integer +ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + +# This is effectively an ifdef statement in Cython +# It allows us to write printf debugging lines +# and remove them at compile time +cdef enum: + DEBUGFLAG = 0 + +cdef float EPSILON = 1e-6 + +# XXX: Careful to not change the order of the arguments. It is important to +# have is_leaf and max_width consecutive as it permits to avoid padding by +# the compiler and keep the size coherent for both C and numpy data structures. +cdef struct Cell: + # Base storage structure for cells in a QuadTree object + + # Tree structure + SIZE_t parent # Parent cell of this cell + SIZE_t[8] children # Array pointing to childrens of this cell + + # Cell description + SIZE_t cell_id # Id of the cell in the cells array in the Tree + SIZE_t point_index # Index of the point at this cell (only defined + # in non empty leaf) + bint is_leaf # Does this cell have children? + DTYPE_t squared_max_width # Squared value of the maximum width w + SIZE_t depth # Depth of the cell in the tree + SIZE_t cumulative_size # Number of points included in the subtree with + # this cell as a root. + + # Internal constants + DTYPE_t[3] center # Store the center for quick split of cells + DTYPE_t[3] barycenter # Keep track of the center of mass of the cell + + # Cell boundaries + DTYPE_t[3] min_bounds # Inferior boundaries of this cell (inclusive) + DTYPE_t[3] max_bounds # Superior boundaries of this cell (exclusive) + + +cdef class _QuadTree: + # The QuadTree object is a quad tree structure constructed by inserting + # recursively points in the tree and splitting cells in 4 so that each + # leaf cell contains at most one point. + # This structure also handle 3D data, inserted in trees with 8 children + # for each node. + + # Parameters of the tree + cdef public int n_dimensions # Number of dimensions in X + cdef public int verbose # Verbosity of the output + cdef SIZE_t n_cells_per_cell # Number of children per node. (2 ** n_dimension) + + # Tree inner structure + cdef public SIZE_t max_depth # Max depth of the tree + cdef public SIZE_t cell_count # Counter for node IDs + cdef public SIZE_t capacity # Capacity of tree, in terms of nodes + cdef public SIZE_t n_points # Total number of points + cdef Cell* cells # Array of nodes + + # Point insertion methods + cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, + SIZE_t cell_id=*) nogil except -1 + cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, + SIZE_t point_index, SIZE_t size=* + ) nogil + cdef SIZE_t _select_child(self, DTYPE_t[3] point, Cell* cell) nogil + cdef bint _is_duplicate(self, DTYPE_t[3] point1, DTYPE_t[3] point2) nogil + + # Create a summary of the Tree compare to a query point + cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, + float squared_theta=*, SIZE_t cell_id=*, long idx=* + ) nogil + + # Internal cell initialization methods + cdef void _init_cell(self, Cell* cell, SIZE_t parent, SIZE_t depth) nogil + cdef void _init_root(self, DTYPE_t[3] min_bounds, DTYPE_t[3] max_bounds + ) nogil + + # Private methods + cdef int _check_point_in_cell(self, DTYPE_t[3] point, Cell* cell + ) nogil except -1 + + # Private array manipulation to manage the ``cells`` array + cdef int _resize(self, SIZE_t capacity) nogil except -1 + cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 + cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 + cdef np.ndarray _get_cell_ndarray(self) \ No newline at end of file diff --git a/stpredictions/models/OK3/_quad_tree.pyx b/stpredictions/models/OK3/_quad_tree.pyx new file mode 100644 index 000000000..81e6c98b5 --- /dev/null +++ b/stpredictions/models/OK3/_quad_tree.pyx @@ -0,0 +1,610 @@ +# cython: boundscheck=False +# cython: wraparound=False +# cython: cdivision=True +# +# Author: Thomas Moreau +# Author: Olivier Grisel + + +from cpython cimport Py_INCREF, PyObject, PyTypeObject + +from libc.stdlib cimport malloc, free +from libc.string cimport memcpy +from libc.stdio cimport printf +from libc.stdint cimport SIZE_MAX + +from ._utils cimport safe_realloc, sizet_ptr_to_ndarray +# from .utils import check_array + +import numpy as np +cimport numpy as np +np.import_array() + +cdef extern from "math.h": + float fabsf(float x) nogil + +cdef extern from "numpy/arrayobject.h": + object PyArray_NewFromDescr(PyTypeObject* subtype, np.dtype descr, + int nd, np.npy_intp* dims, + np.npy_intp* strides, + void* data, int flags, object obj) + int PyArray_SetBaseObject(np.ndarray arr, PyObject* obj) + +# Build the corresponding numpy dtype for Cell. +# This works by casting `dummy` to an array of Cell of length 1, which numpy +# can construct a `dtype`-object for. See https://stackoverflow.com/q/62448946 +# for a more detailed explanation. +cdef Cell dummy; +CELL_DTYPE = np.asarray((&dummy)).dtype + +assert CELL_DTYPE.itemsize == sizeof(Cell) + + +cdef class _QuadTree: + """Array-based representation of a QuadTree. + + This class is currently working for indexing 2D data (regular QuadTree) and + for indexing 3D data (OcTree). It is planned to split the 2 implementations + using `Cython.Tempita` to save some memory for QuadTree. + + Note that this code is currently internally used only by the Barnes-Hut + method in `sklearn.manifold.TSNE`. It is planned to be refactored and + generalized in the future to be compatible with nearest neighbors API of + `sklearn.neighbors` with 2D and 3D data. + """ + def __cinit__(self, int n_dimensions, int verbose): + """Constructor.""" + # Parameters of the tree + self.n_dimensions = n_dimensions + self.verbose = verbose + self.n_cells_per_cell = 2 ** self.n_dimensions + + # Inner structures + self.max_depth = 0 + self.cell_count = 0 + self.capacity = 0 + self.n_points = 0 + self.cells = NULL + + def __dealloc__(self): + """Destructor.""" + # Free all inner structures + free(self.cells) + + property cumulative_size: + def __get__(self): + return self._get_cell_ndarray()['cumulative_size'][:self.cell_count] + + property leafs: + def __get__(self): + return self._get_cell_ndarray()['is_leaf'][:self.cell_count] + + def build_tree(self, X): + """Build a tree from an array of points X.""" + cdef: + int i + DTYPE_t[3] pt + DTYPE_t[3] min_bounds, max_bounds + + # validate X and prepare for query + # X = check_array(X, dtype=DTYPE_t, order='C') + n_samples = X.shape[0] + + capacity = 100 + self._resize(capacity) + m = np.min(X, axis=0) + M = np.max(X, axis=0) + # Scale the maximum to get all points strictly in the tree bounding box + # The 3 bounds are for positive, negative and small values + M = np.maximum(M * (1. + 1e-3 * np.sign(M)), M + 1e-3) + for i in range(self.n_dimensions): + min_bounds[i] = m[i] + max_bounds[i] = M[i] + + if self.verbose > 10: + printf("[QuadTree] bounding box axis %i : [%f, %f]\n", + i, min_bounds[i], max_bounds[i]) + + # Create the initial node with boundaries from the dataset + self._init_root(min_bounds, max_bounds) + + for i in range(n_samples): + for j in range(self.n_dimensions): + pt[j] = X[i, j] + self.insert_point(pt, i) + + # Shrink the cells array to reduce memory usage + self._resize(capacity=self.cell_count) + + cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, + SIZE_t cell_id=0) nogil except -1: + """Insert a point in the QuadTree.""" + cdef int ax + cdef DTYPE_t n_frac + cdef SIZE_t selected_child + cdef Cell* cell = &self.cells[cell_id] + cdef SIZE_t n_point = cell.cumulative_size + + if self.verbose > 10: + printf("[QuadTree] Inserting depth %li\n", cell.depth) + + # Assert that the point is in the right range + if DEBUGFLAG: + self._check_point_in_cell(point, cell) + + # If the cell is an empty leaf, insert the point in it + if cell.cumulative_size == 0: + cell.cumulative_size = 1 + self.n_points += 1 + for i in range(self.n_dimensions): + cell.barycenter[i] = point[i] + cell.point_index = point_index + if self.verbose > 10: + printf("[QuadTree] inserted point %li in cell %li\n", + point_index, cell_id) + return cell_id + + # If the cell is not a leaf, update cell internals and + # recurse in selected child + if not cell.is_leaf: + for ax in range(self.n_dimensions): + # barycenter update using a weighted mean + cell.barycenter[ax] = ( + n_point * cell.barycenter[ax] + point[ax]) / (n_point + 1) + + # Increase the size of the subtree starting from this cell + cell.cumulative_size += 1 + + # Insert child in the correct subtree + selected_child = self._select_child(point, cell) + if self.verbose > 49: + printf("[QuadTree] selected child %li\n", selected_child) + if selected_child == -1: + self.n_points += 1 + return self._insert_point_in_new_child(point, cell, point_index) + return self.insert_point(point, point_index, selected_child) + + # Finally, if the cell is a leaf with a point already inserted, + # split the cell in n_cells_per_cell if the point is not a duplicate. + # If it is a duplicate, increase the size of the leaf and return. + if self._is_duplicate(point, cell.barycenter): + if self.verbose > 10: + printf("[QuadTree] found a duplicate!\n") + cell.cumulative_size += 1 + self.n_points += 1 + return cell_id + + # In a leaf, the barycenter correspond to the only point included + # in it. + self._insert_point_in_new_child(cell.barycenter, cell, cell.point_index, + cell.cumulative_size) + return self.insert_point(point, point_index, cell_id) + + # XXX: This operation is not Thread safe + cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, + SIZE_t point_index, SIZE_t size=1 + ) nogil: + """Create a child of cell which will contain point.""" + + # Local variable definition + cdef: + SIZE_t cell_id, cell_child_id, parent_id + DTYPE_t[3] save_point + DTYPE_t width + Cell* child + int i + + # If the maximal capacity of the Tree have been reached, double the capacity + # We need to save the current cell id and the current point to retrieve them + # in case the reallocation + if self.cell_count + 1 > self.capacity: + parent_id = cell.cell_id + for i in range(self.n_dimensions): + save_point[i] = point[i] + self._resize(SIZE_MAX) + cell = &self.cells[parent_id] + point = save_point + + # Get an empty cell and initialize it + cell_id = self.cell_count + self.cell_count += 1 + child = &self.cells[cell_id] + + self._init_cell(child, cell.cell_id, cell.depth + 1) + child.cell_id = cell_id + + # Set the cell as an inner cell of the Tree + cell.is_leaf = False + cell.point_index = -1 + + # Set the correct boundary for the cell, store the point in the cell + # and compute its index in the children array. + cell_child_id = 0 + for i in range(self.n_dimensions): + cell_child_id *= 2 + if point[i] >= cell.center[i]: + cell_child_id += 1 + child.min_bounds[i] = cell.center[i] + child.max_bounds[i] = cell.max_bounds[i] + else: + child.min_bounds[i] = cell.min_bounds[i] + child.max_bounds[i] = cell.center[i] + child.center[i] = (child.min_bounds[i] + child.max_bounds[i]) / 2. + width = child.max_bounds[i] - child.min_bounds[i] + + child.barycenter[i] = point[i] + child.squared_max_width = max(child.squared_max_width, width*width) + + # Store the point info and the size to account for duplicated points + child.point_index = point_index + child.cumulative_size = size + + # Store the child cell in the correct place in children + cell.children[cell_child_id] = child.cell_id + + if DEBUGFLAG: + # Assert that the point is in the right range + self._check_point_in_cell(point, child) + if self.verbose > 10: + printf("[QuadTree] inserted point %li in new child %li\n", + point_index, cell_id) + + return cell_id + + + cdef bint _is_duplicate(self, DTYPE_t[3] point1, DTYPE_t[3] point2) nogil: + """Check if the two given points are equals.""" + cdef int i + cdef bint res = True + for i in range(self.n_dimensions): + # Use EPSILON to avoid numerical error that would overgrow the tree + res &= fabsf(point1[i] - point2[i]) <= EPSILON + return res + + + cdef SIZE_t _select_child(self, DTYPE_t[3] point, Cell* cell) nogil: + """Select the child of cell which contains the given query point.""" + cdef: + int i + SIZE_t selected_child = 0 + + for i in range(self.n_dimensions): + # Select the correct child cell to insert the point by comparing + # it to the borders of the cells using precomputed center. + selected_child *= 2 + if point[i] >= cell.center[i]: + selected_child += 1 + return cell.children[selected_child] + + cdef void _init_cell(self, Cell* cell, SIZE_t parent, SIZE_t depth) nogil: + """Initialize a cell structure with some constants.""" + cell.parent = parent + cell.is_leaf = True + cell.depth = depth + cell.squared_max_width = 0 + cell.cumulative_size = 0 + for i in range(self.n_cells_per_cell): + cell.children[i] = SIZE_MAX + + cdef void _init_root(self, DTYPE_t[3] min_bounds, DTYPE_t[3] max_bounds + ) nogil: + """Initialize the root node with the given space boundaries""" + cdef: + int i + DTYPE_t width + Cell* root = &self.cells[0] + + self._init_cell(root, -1, 0) + for i in range(self.n_dimensions): + root.min_bounds[i] = min_bounds[i] + root.max_bounds[i] = max_bounds[i] + root.center[i] = (max_bounds[i] + min_bounds[i]) / 2. + width = max_bounds[i] - min_bounds[i] + root.squared_max_width = max(root.squared_max_width, width*width) + root.cell_id = 0 + + self.cell_count += 1 + + cdef int _check_point_in_cell(self, DTYPE_t[3] point, Cell* cell + ) nogil except -1: + """Check that the given point is in the cell boundaries.""" + + if self.verbose >= 50: + if self.n_dimensions == 3: + printf("[QuadTree] Checking point (%f, %f, %f) in cell %li " + "([%f/%f, %f/%f, %f/%f], size %li)\n", + point[0], point[1], point[2], cell.cell_id, + cell.min_bounds[0], cell.max_bounds[0], cell.min_bounds[1], + cell.max_bounds[1], cell.min_bounds[2], cell.max_bounds[2], + cell.cumulative_size) + else: + printf("[QuadTree] Checking point (%f, %f) in cell %li " + "([%f/%f, %f/%f], size %li)\n", + point[0], point[1],cell.cell_id, cell.min_bounds[0], + cell.max_bounds[0], cell.min_bounds[1], + cell.max_bounds[1], cell.cumulative_size) + + for i in range(self.n_dimensions): + if (cell.min_bounds[i] > point[i] or + cell.max_bounds[i] <= point[i]): + with gil: + msg = "[QuadTree] InsertionError: point out of cell " + msg += "boundary.\nAxis %li: cell [%f, %f]; point %f\n" + + msg %= i, cell.min_bounds[i], cell.max_bounds[i], point[i] + raise ValueError(msg) + + def _check_coherence(self): + """Check the coherence of the cells of the tree. + + Check that the info stored in each cell is compatible with the info + stored in descendent and sibling cells. Raise a ValueError if this + fails. + """ + for cell in self.cells[:self.cell_count]: + # Check that the barycenter of inserted point is within the cell + # boundaries + self._check_point_in_cell(cell.barycenter, &cell) + + if not cell.is_leaf: + # Compute the number of point in children and compare with + # its cummulative_size. + n_points = 0 + for idx in range(self.n_cells_per_cell): + child_id = cell.children[idx] + if child_id != -1: + child = self.cells[child_id] + n_points += child.cumulative_size + assert child.cell_id == child_id, ( + "Cell id not correctly initiliazed.") + if n_points != cell.cumulative_size: + raise ValueError( + "Cell {} is incoherent. Size={} but found {} points " + "in children. ({})" + .format(cell.cell_id, cell.cumulative_size, + n_points, cell.children)) + + # Make sure that the number of point in the tree correspond to the + # cummulative size in root cell. + if self.n_points != self.cells[0].cumulative_size: + raise ValueError( + "QuadTree is incoherent. Size={} but found {} points " + "in children." + .format(self.n_points, self.cells[0].cumulative_size)) + + cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, + float squared_theta=.5, SIZE_t cell_id=0, long idx=0 + ) nogil: + """Summarize the tree compared to a query point. + + Input arguments + --------------- + point : array (n_dimensions) + query point to construct the summary. + cell_id : integer, optional (default: 0) + current cell of the tree summarized. This should be set to 0 for + external calls. + idx : integer, optional (default: 0) + current index in the result array. This should be set to 0 for + external calls + squared_theta: float, optional (default: .5) + threshold to decide whether the node is sufficiently far + from the query point to be a good summary. The formula is such that + the node is a summary if + node_width^2 / dist_node_point^2 < squared_theta. + Note that the argument should be passed as theta^2 to avoid + computing square roots of the distances. + + Output arguments + ---------------- + results : array (n_samples * (n_dimensions+2)) + result will contain a summary of the tree information compared to + the query point: + - results[idx:idx+n_dimensions] contains the coordinate-wise + difference between the query point and the summary cell idx. + This is useful in t-SNE to compute the negative forces. + - result[idx+n_dimensions+1] contains the squared euclidean + distance to the summary cell idx. + - result[idx+n_dimensions+2] contains the number of point of the + tree contained in the summary cell idx. + + Return + ------ + idx : integer + number of elements in the results array. + """ + cdef: + int i, idx_d = idx + self.n_dimensions + bint duplicate = True + Cell* cell = &self.cells[cell_id] + + results[idx_d] = 0. + for i in range(self.n_dimensions): + results[idx + i] = point[i] - cell.barycenter[i] + results[idx_d] += results[idx + i] * results[idx + i] + duplicate &= fabsf(results[idx + i]) <= EPSILON + + # Do not compute self interactions + if duplicate and cell.is_leaf: + return idx + + # Check whether we can use this node as a summary + # It's a summary node if the angular size as measured from the point + # is relatively small (w.r.t. to theta) or if it is a leaf node. + # If it can be summarized, we use the cell center of mass + # Otherwise, we go a higher level of resolution and into the leaves. + if cell.is_leaf or ( + (cell.squared_max_width / results[idx_d]) < squared_theta): + results[idx_d + 1] = cell.cumulative_size + return idx + self.n_dimensions + 2 + + else: + # Recursively compute the summary in nodes + for c in range(self.n_cells_per_cell): + child_id = cell.children[c] + if child_id != -1: + idx = self.summarize(point, results, squared_theta, + child_id, idx) + + return idx + + def get_cell(self, point): + """return the id of the cell containing the query point or raise + ValueError if the point is not in the tree + """ + cdef DTYPE_t[3] query_pt + cdef int i + + assert len(point) == self.n_dimensions, ( + "Query point should be a point in dimension {}." + .format(self.n_dimensions)) + + for i in range(self.n_dimensions): + query_pt[i] = point[i] + + return self._get_cell(query_pt, 0) + + cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=0 + ) nogil except -1: + """guts of get_cell. + + Return the id of the cell containing the query point or raise ValueError + if the point is not in the tree""" + cdef: + SIZE_t selected_child + Cell* cell = &self.cells[cell_id] + + if cell.is_leaf: + if self._is_duplicate(cell.barycenter, point): + if self.verbose > 99: + printf("[QuadTree] Found point in cell: %li\n", + cell.cell_id) + return cell_id + with gil: + raise ValueError("Query point not in the Tree.") + + selected_child = self._select_child(point, cell) + if selected_child > 0: + if self.verbose > 99: + printf("[QuadTree] Selected_child: %li\n", selected_child) + return self._get_cell(point, selected_child) + with gil: + raise ValueError("Query point not in the Tree.") + + # Pickling primitives + + def __reduce__(self): + """Reduce re-implementation, for pickling.""" + return (_QuadTree, (self.n_dimensions, self.verbose), + self.__getstate__()) + + def __getstate__(self): + """Getstate re-implementation, for pickling.""" + d = {} + # capacity is inferred during the __setstate__ using nodes + d["max_depth"] = self.max_depth + d["cell_count"] = self.cell_count + d["capacity"] = self.capacity + d["n_points"] = self.n_points + d["cells"] = self._get_cell_ndarray() + return d + + def __setstate__(self, d): + """Setstate re-implementation, for unpickling.""" + self.max_depth = d["max_depth"] + self.cell_count = d["cell_count"] + self.capacity = d["capacity"] + self.n_points = d["n_points"] + + if 'cells' not in d: + raise ValueError('You have loaded Tree version which ' + 'cannot be imported') + + cell_ndarray = d['cells'] + + if (cell_ndarray.ndim != 1 or + cell_ndarray.dtype != CELL_DTYPE or + not cell_ndarray.flags.c_contiguous): + raise ValueError('Did not recognise loaded array layout') + + self.capacity = cell_ndarray.shape[0] + if self._resize_c(self.capacity) != 0: + raise MemoryError("resizing tree to %d" % self.capacity) + + cells = memcpy(self.cells, ( cell_ndarray).data, + self.capacity * sizeof(Cell)) + + + # Array manipulation methods, to convert it to numpy or to resize + # self.cells array + + cdef np.ndarray _get_cell_ndarray(self): + """Wraps nodes as a NumPy struct array. + + The array keeps a reference to this Tree, which manages the underlying + memory. Individual fields are publicly accessible as properties of the + Tree. + """ + cdef np.npy_intp shape[1] + shape[0] = self.cell_count + cdef np.npy_intp strides[1] + strides[0] = sizeof(Cell) + cdef np.ndarray arr + Py_INCREF(CELL_DTYPE) + arr = PyArray_NewFromDescr( np.ndarray, + CELL_DTYPE, 1, shape, + strides, self.cells, + np.NPY_DEFAULT, None) + Py_INCREF(self) + if PyArray_SetBaseObject(arr, self) < 0: + raise ValueError("Can't intialize array!") + return arr + + cdef int _resize(self, SIZE_t capacity) nogil except -1: + """Resize all inner arrays to `capacity`, if `capacity` == -1, then + double the size of the inner arrays. + + Returns -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + if self._resize_c(capacity) != 0: + # Acquire gil only if we need to raise + with gil: + raise MemoryError() + + cdef int _resize_c(self, SIZE_t capacity=SIZE_MAX) nogil except -1: + """Guts of _resize + + Returns -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + if capacity == self.capacity and self.cells != NULL: + return 0 + + if capacity == SIZE_MAX: + if self.capacity == 0: + capacity = 9 # default initial value to min + else: + capacity = 2 * self.capacity + + safe_realloc(&self.cells, capacity) + + # if capacity smaller than cell_count, adjust the counter + if capacity < self.cell_count: + self.cell_count = capacity + + self.capacity = capacity + return 0 + + def _py_summarize(self, DTYPE_t[:] query_pt, DTYPE_t[:, :] X, float angle): + # Used for testing summarize + cdef: + DTYPE_t[:] summary + int n_samples, n_dimensions + + n_samples = X.shape[0] + n_dimensions = X.shape[1] + summary = np.empty(4 * n_samples, dtype=np.float32) + + idx = self.summarize(&query_pt[0], &summary[0], angle * angle) + return idx, summary \ No newline at end of file diff --git a/stpredictions/models/OK3/_random.c b/stpredictions/models/OK3/_random.c new file mode 100644 index 000000000..5c9b70c38 --- /dev/null +++ b/stpredictions/models/OK3/_random.c @@ -0,0 +1,5002 @@ +/* Generated by Cython 0.29.23 */ + +/* BEGIN: Cython Metadata +{ + "distutils": { + "depends": [ + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include/numpy/arrayobject.h", + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include/numpy/ufuncobject.h" + ], + "extra_compile_args": [ + "-O3", + "-fopenmp", + "-DOMP" + ], + "extra_link_args": [ + "-fopenmp" + ], + "include_dirs": [ + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include", + "/home/asani/Documents/Hi_Paris_Code_Projects/Florence/structured-predictions/stpredictions/models/OK3/test" + ], + "name": "stpredictions.models.OK3._random", + "sources": [ + "stpredictions/models/OK3/_random.pyx" + ] + }, + "module_name": "stpredictions.models.OK3._random" +} +END: Cython Metadata */ + +#ifndef PY_SSIZE_T_CLEAN +#define PY_SSIZE_T_CLEAN +#endif /* PY_SSIZE_T_CLEAN */ +#include "Python.h" +#ifndef Py_PYTHON_H + #error Python headers needed to compile C extensions, please install development version of Python. +#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) + #error Cython requires Python 2.6+ or Python 3.3+. +#else +#define CYTHON_ABI "0_29_23" +#define CYTHON_HEX_VERSION 0x001D17F0 +#define CYTHON_FUTURE_DIVISION 0 +#include +#ifndef offsetof + #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) +#endif +#if !defined(WIN32) && !defined(MS_WINDOWS) + #ifndef __stdcall + #define __stdcall + #endif + #ifndef __cdecl + #define __cdecl + #endif + #ifndef __fastcall + #define __fastcall + #endif +#endif +#ifndef DL_IMPORT + #define DL_IMPORT(t) t +#endif +#ifndef DL_EXPORT + #define DL_EXPORT(t) t +#endif +#define __PYX_COMMA , +#ifndef HAVE_LONG_LONG + #if PY_VERSION_HEX >= 0x02070000 + #define HAVE_LONG_LONG + #endif +#endif +#ifndef PY_LONG_LONG + #define PY_LONG_LONG LONG_LONG +#endif +#ifndef Py_HUGE_VAL + #define Py_HUGE_VAL HUGE_VAL +#endif +#ifdef PYPY_VERSION + #define CYTHON_COMPILING_IN_PYPY 1 + #define CYTHON_COMPILING_IN_PYSTON 0 + #define CYTHON_COMPILING_IN_CPYTHON 0 + #undef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 0 + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #if PY_VERSION_HEX < 0x03050000 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #elif !defined(CYTHON_USE_ASYNC_SLOTS) + #define CYTHON_USE_ASYNC_SLOTS 1 + #endif + #undef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 0 + #undef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 0 + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #undef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 1 + #undef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 0 + #undef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 0 + #undef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 0 + #undef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 0 + #undef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT 0 + #undef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE 0 + #undef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS 0 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 +#elif defined(PYSTON_VERSION) + #define CYTHON_COMPILING_IN_PYPY 0 + #define CYTHON_COMPILING_IN_PYSTON 1 + #define CYTHON_COMPILING_IN_CPYTHON 0 + #ifndef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 1 + #endif + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #undef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 0 + #ifndef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 1 + #endif + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #ifndef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 0 + #endif + #ifndef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 1 + #endif + #ifndef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 1 + #endif + #undef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 0 + #undef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 0 + #undef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT 0 + #undef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE 0 + #undef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS 0 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 +#else + #define CYTHON_COMPILING_IN_PYPY 0 + #define CYTHON_COMPILING_IN_PYSTON 0 + #define CYTHON_COMPILING_IN_CPYTHON 1 + #ifndef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 1 + #endif + #if PY_VERSION_HEX < 0x02070000 + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #elif !defined(CYTHON_USE_PYTYPE_LOOKUP) + #define CYTHON_USE_PYTYPE_LOOKUP 1 + #endif + #if PY_MAJOR_VERSION < 3 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #elif !defined(CYTHON_USE_ASYNC_SLOTS) + #define CYTHON_USE_ASYNC_SLOTS 1 + #endif + #if PY_VERSION_HEX < 0x02070000 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #elif !defined(CYTHON_USE_PYLONG_INTERNALS) + #define CYTHON_USE_PYLONG_INTERNALS 1 + #endif + #ifndef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 1 + #endif + #ifndef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 1 + #endif + #if PY_VERSION_HEX < 0x030300F0 + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #elif !defined(CYTHON_USE_UNICODE_WRITER) + #define CYTHON_USE_UNICODE_WRITER 1 + #endif + #ifndef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 0 + #endif + #ifndef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 1 + #endif + #ifndef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 1 + #endif + #ifndef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 1 + #endif + #ifndef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 1 + #endif + #ifndef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT (PY_VERSION_HEX >= 0x03050000) + #endif + #ifndef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE (PY_VERSION_HEX >= 0x030400a1) + #endif + #ifndef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS (PY_VERSION_HEX >= 0x030600B1) + #endif + #ifndef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK (PY_VERSION_HEX >= 0x030700A3) + #endif +#endif +#if !defined(CYTHON_FAST_PYCCALL) +#define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) +#endif +#if CYTHON_USE_PYLONG_INTERNALS + #include "longintrepr.h" + #undef SHIFT + #undef BASE + #undef MASK + #ifdef SIZEOF_VOID_P + enum { __pyx_check_sizeof_voidp = 1 / (int)(SIZEOF_VOID_P == sizeof(void*)) }; + #endif +#endif +#ifndef __has_attribute + #define __has_attribute(x) 0 +#endif +#ifndef __has_cpp_attribute + #define __has_cpp_attribute(x) 0 +#endif +#ifndef CYTHON_RESTRICT + #if defined(__GNUC__) + #define CYTHON_RESTRICT __restrict__ + #elif defined(_MSC_VER) && _MSC_VER >= 1400 + #define CYTHON_RESTRICT __restrict + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_RESTRICT restrict + #else + #define CYTHON_RESTRICT + #endif +#endif +#ifndef CYTHON_UNUSED +# if defined(__GNUC__) +# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +#endif +#ifndef CYTHON_MAYBE_UNUSED_VAR +# if defined(__cplusplus) + template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } +# else +# define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) +# endif +#endif +#ifndef CYTHON_NCP_UNUSED +# if CYTHON_COMPILING_IN_CPYTHON +# define CYTHON_NCP_UNUSED +# else +# define CYTHON_NCP_UNUSED CYTHON_UNUSED +# endif +#endif +#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) +#ifdef _MSC_VER + #ifndef _MSC_STDINT_H_ + #if _MSC_VER < 1300 + typedef unsigned char uint8_t; + typedef unsigned int uint32_t; + #else + typedef unsigned __int8 uint8_t; + typedef unsigned __int32 uint32_t; + #endif + #endif +#else + #include +#endif +#ifndef CYTHON_FALLTHROUGH + #if defined(__cplusplus) && __cplusplus >= 201103L + #if __has_cpp_attribute(fallthrough) + #define CYTHON_FALLTHROUGH [[fallthrough]] + #elif __has_cpp_attribute(clang::fallthrough) + #define CYTHON_FALLTHROUGH [[clang::fallthrough]] + #elif __has_cpp_attribute(gnu::fallthrough) + #define CYTHON_FALLTHROUGH [[gnu::fallthrough]] + #endif + #endif + #ifndef CYTHON_FALLTHROUGH + #if __has_attribute(fallthrough) + #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) + #else + #define CYTHON_FALLTHROUGH + #endif + #endif + #if defined(__clang__ ) && defined(__apple_build_version__) + #if __apple_build_version__ < 7000000 + #undef CYTHON_FALLTHROUGH + #define CYTHON_FALLTHROUGH + #endif + #endif +#endif + +#ifndef CYTHON_INLINE + #if defined(__clang__) + #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) + #elif defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_INLINE inline + #else + #define CYTHON_INLINE + #endif +#endif + +#if 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(PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) +#else +#define __Pyx_PyFastCFunction_Check(func) 0 +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) + #define PyObject_Malloc(s) PyMem_Malloc(s) + #define PyObject_Free(p) PyMem_Free(p) + #define PyObject_Realloc(p) PyMem_Realloc(p) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 + #define PyMem_RawMalloc(n) PyMem_Malloc(n) + #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) + #define PyMem_RawFree(p) PyMem_Free(p) +#endif +#if CYTHON_COMPILING_IN_PYSTON + #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) +#else + #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) +#endif +#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#elif PY_VERSION_HEX >= 0x03060000 + #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() +#elif PY_VERSION_HEX >= 0x03000000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#else + #define __Pyx_PyThreadState_Current _PyThreadState_Current +#endif +#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) +#include "pythread.h" +#define Py_tss_NEEDS_INIT 0 +typedef int Py_tss_t; +static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { + *key = PyThread_create_key(); + return 0; +} +static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { + Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); + *key = Py_tss_NEEDS_INIT; + return key; +} +static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { + PyObject_Free(key); +} +static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { + return *key != Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { + PyThread_delete_key(*key); + *key = Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { + return PyThread_set_key_value(*key, value); +} +static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { + return PyThread_get_key_value(*key); +} +#endif +#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) +#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) +#else +#define __Pyx_PyDict_NewPresized(n) PyDict_New() +#endif +#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS +#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) +#else +#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) +#endif +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) + #define CYTHON_PEP393_ENABLED 1 + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ + 0 : _PyUnicode_Ready((PyObject *)(op))) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) + #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) + #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) + #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif +#else + #define CYTHON_PEP393_ENABLED 0 + #define PyUnicode_1BYTE_KIND 1 + #define PyUnicode_2BYTE_KIND 2 + #define PyUnicode_4BYTE_KIND 4 + #define __Pyx_PyUnicode_READY(op) (0) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) + #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) + #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) + #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) +#endif +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) +#else + #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ + PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) + #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) + #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) +#endif +#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) +#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) +#else + #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) +#endif +#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) + #define PyObject_ASCII(o) PyObject_Repr(o) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode + #define PyObject_Unicode PyObject_Str +#endif +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) + #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) +#else + #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) + #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif +#if CYTHON_ASSUME_SAFE_MACROS + #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) +#else + #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define PyNumber_Int PyNumber_Long +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif +#if PY_VERSION_HEX < 0x030200A4 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t PyInt_AsLong +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) +#endif +#if CYTHON_USE_ASYNC_SLOTS + #if PY_VERSION_HEX >= 0x030500B1 + #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods + #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) + #else + #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) + #endif +#else + #define __Pyx_PyType_AsAsync(obj) NULL +#endif +#ifndef __Pyx_PyAsyncMethodsStruct + typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; + } __Pyx_PyAsyncMethodsStruct; +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include +#ifdef NAN +#define __PYX_NAN() ((float) NAN) +#else +static CYTHON_INLINE float __PYX_NAN() { + float value; + memset(&value, 0xFF, sizeof(value)); + return value; +} +#endif +#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) +#define __Pyx_truncl trunc +#else +#define __Pyx_truncl truncl +#endif + +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } +#define __PYX_ERR(f_index, lineno, Ln_error) \ + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#define __PYX_HAVE__stpredictions__models__OK3___random +#define __PYX_HAVE_API__stpredictions__models__OK3___random +/* Early includes */ +#include +#include +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) +#define CYTHON_WITHOUT_ASSERTIONS +#endif + +typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; + const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; + +#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) +#define __PYX_DEFAULT_STRING_ENCODING "" +#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString +#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX))) ) +static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { + return (size_t) i < (size_t) limit; +} +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (_MSC_VER) + #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); +#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) +#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); +#if PY_MAJOR_VERSION < 3 + #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#else + #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize +#endif +#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { + const Py_UNICODE *u_end = u; + while (*u_end++) ; + return (size_t)(u_end - u - 1); +} +#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) +#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode +#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); +#define __Pyx_PySequence_Tuple(obj)\ + (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +#if CYTHON_ASSUME_SAFE_MACROS +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#else +#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) +#endif +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) +#else +#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) +#endif +#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII +static int __Pyx_sys_getdefaultencoding_not_ascii; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + PyObject* ascii_chars_u = NULL; + PyObject* ascii_chars_b = NULL; + const char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + if (strcmp(default_encoding_c, "ascii") == 0) { + __Pyx_sys_getdefaultencoding_not_ascii = 0; + } else { + char ascii_chars[128]; + int c; + for (c = 0; c < 128; c++) { + ascii_chars[c] = c; + } + __Pyx_sys_getdefaultencoding_not_ascii = 1; + ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); + if (!ascii_chars_u) goto bad; + ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); + if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { + PyErr_Format( + PyExc_ValueError, + "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", + default_encoding_c); + goto bad; + } + Py_DECREF(ascii_chars_u); + Py_DECREF(ascii_chars_b); + } + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + Py_XDECREF(ascii_chars_u); + Py_XDECREF(ascii_chars_b); + return -1; +} +#endif +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) +#else +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +static char* __PYX_DEFAULT_STRING_ENCODING; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); + if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; + strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + return -1; +} +#endif +#endif + + +/* Test for GCC > 2.95 */ +#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) +#else /* !__GNUC__ or GCC < 2.95 */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ +static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } + +static PyObject *__pyx_m = NULL; +static PyObject *__pyx_d; +static PyObject *__pyx_b; +static PyObject *__pyx_cython_runtime = NULL; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static PyObject *__pyx_empty_unicode; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +/* Header.proto */ +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + + +static const char *__pyx_f[] = { + "__init__.pxd", + "stpredictions/models/OK3/_random.pxd", + "stpredictions/models/OK3/_random.pyx", + "type.pxd", +}; +/* ForceInitThreads.proto */ +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + +/* NoFastGil.proto */ +#define __Pyx_PyGILState_Ensure PyGILState_Ensure +#define __Pyx_PyGILState_Release PyGILState_Release +#define __Pyx_FastGIL_Remember() +#define __Pyx_FastGIL_Forget() +#define __Pyx_FastGilFuncInit() + + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":689 + * # in Cython to enable them only on the right systems. + * + * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + */ +typedef npy_int8 __pyx_t_5numpy_int8_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":690 + * + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t + */ +typedef npy_int16 __pyx_t_5numpy_int16_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":691 + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< + * ctypedef npy_int64 int64_t + * #ctypedef npy_int96 int96_t + */ +typedef npy_int32 __pyx_t_5numpy_int32_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":692 + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< + * #ctypedef npy_int96 int96_t + * #ctypedef npy_int128 int128_t + */ +typedef npy_int64 __pyx_t_5numpy_int64_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":696 + * #ctypedef npy_int128 int128_t + * + * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + */ +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":697 + * + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t + */ +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":698 + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< + * ctypedef npy_uint64 uint64_t + * #ctypedef npy_uint96 uint96_t + */ +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":699 + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< + * #ctypedef npy_uint96 uint96_t + * #ctypedef npy_uint128 uint128_t + */ +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":703 + * #ctypedef npy_uint128 uint128_t + * + * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< + * ctypedef npy_float64 float64_t + * #ctypedef npy_float80 float80_t + */ +typedef npy_float32 __pyx_t_5numpy_float32_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":704 + * + * ctypedef npy_float32 float32_t + * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< + * #ctypedef npy_float80 float80_t + * #ctypedef npy_float128 float128_t + */ +typedef npy_float64 __pyx_t_5numpy_float64_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":713 + * # The int types are mapped a bit surprising -- + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t + */ +typedef npy_long __pyx_t_5numpy_int_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":714 + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong longlong_t + * + */ +typedef npy_longlong __pyx_t_5numpy_long_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":715 + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_ulong uint_t + */ +typedef npy_longlong __pyx_t_5numpy_longlong_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":717 + * ctypedef npy_longlong longlong_t + * + * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t + */ +typedef npy_ulong __pyx_t_5numpy_uint_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":718 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; 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+ +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":725 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":726 + * ctypedef npy_double float_t + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cfloat cfloat_t + */ +typedef npy_longdouble __pyx_t_5numpy_longdouble_t; + +/* "stpredictions/models/OK3/_random.pxd":8 + * import numpy as np + * cimport numpy as np + * ctypedef np.npy_uint32 UINT32_t # <<<<<<<<<<<<<< + * + * cdef inline UINT32_t DEFAULT_SEED = 1 + */ +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_7_random_UINT32_t; +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< float > __pyx_t_float_complex; 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+#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +/* PyObjectCall */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { + PyObject *result; + ternaryfunc call = func->ob_type->tp_call; + if (unlikely(!call)) + return PyObject_Call(func, arg, kw); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = (*call)(func, arg, kw); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyErrFetchRestore */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} +#endif + +/* RaiseException */ +#if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + __Pyx_PyThreadState_declare + Py_XINCREF(type); + if (!value || value == Py_None) + value = NULL; + else + Py_INCREF(value); + if (!tb || tb == Py_None) + tb = NULL; + else { + Py_INCREF(tb); + if (!PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + } + if (PyType_Check(type)) { +#if CYTHON_COMPILING_IN_PYPY + if (!value) { + Py_INCREF(Py_None); + value = Py_None; + } +#endif + PyErr_NormalizeException(&type, &value, &tb); + } else { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + value = type; + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + } + __Pyx_PyThreadState_assign + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + PyObject* owned_instance = NULL; + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (PyExceptionClass_Check(type)) { + PyObject *instance_class = NULL; + if (value && PyExceptionInstance_Check(value)) { + instance_class = (PyObject*) Py_TYPE(value); + if (instance_class != type) { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { + instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; + } + } + } + if (!instance_class) { + PyObject *args; + if (!value) + args = PyTuple_New(0); + else if (PyTuple_Check(value)) { + Py_INCREF(value); + args = value; + } else + args = PyTuple_Pack(1, value); + if (!args) + goto bad; + owned_instance = PyObject_Call(type, args, NULL); + Py_DECREF(args); + if (!owned_instance) + goto bad; + value = owned_instance; + if (!PyExceptionInstance_Check(value)) { + PyErr_Format(PyExc_TypeError, + "calling %R should have returned an instance of " + "BaseException, not %R", + type, Py_TYPE(value)); + goto bad; + } + } + } else { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + if (cause == Py_None) { + fixed_cause = NULL; + } else if (PyExceptionClass_Check(cause)) { + fixed_cause = PyObject_CallObject(cause, NULL); + if (fixed_cause == NULL) + goto bad; + } else if (PyExceptionInstance_Check(cause)) { + fixed_cause = cause; + Py_INCREF(fixed_cause); + } else { + PyErr_SetString(PyExc_TypeError, + "exception causes must derive from " + "BaseException"); + goto bad; + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } +#endif + } +bad: + Py_XDECREF(owned_instance); + return; +} +#endif + +/* WriteUnraisableException */ +static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, + CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, + int full_traceback, CYTHON_UNUSED int nogil) { + PyObject *old_exc, *old_val, *old_tb; + PyObject *ctx; + __Pyx_PyThreadState_declare +#ifdef WITH_THREAD + PyGILState_STATE state; + if (nogil) + state = PyGILState_Ensure(); +#ifdef _MSC_VER + else state = (PyGILState_STATE)-1; +#endif +#endif + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); + if (full_traceback) { + Py_XINCREF(old_exc); + Py_XINCREF(old_val); + Py_XINCREF(old_tb); + __Pyx_ErrRestore(old_exc, old_val, old_tb); + PyErr_PrintEx(1); + } + #if PY_MAJOR_VERSION < 3 + ctx = PyString_FromString(name); + #else + ctx = PyUnicode_FromString(name); + #endif + __Pyx_ErrRestore(old_exc, old_val, old_tb); + if (!ctx) { + PyErr_WriteUnraisable(Py_None); + } else { + PyErr_WriteUnraisable(ctx); + Py_DECREF(ctx); + } +#ifdef WITH_THREAD + if (nogil) + PyGILState_Release(state); +#endif +} + +/* TypeImport */ +#ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, + size_t size, enum __Pyx_ImportType_CheckSize check_size) +{ + PyObject *result = 0; + char warning[200]; + Py_ssize_t basicsize; +#ifdef Py_LIMITED_API + PyObject *py_basicsize; +#endif + result = PyObject_GetAttrString(module, class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%.200s.%.200s is not a type object", + module_name, class_name); + goto bad; + } +#ifndef Py_LIMITED_API + basicsize = ((PyTypeObject *)result)->tp_basicsize; +#else + py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); + if (!py_basicsize) + goto bad; + basicsize = PyLong_AsSsize_t(py_basicsize); + Py_DECREF(py_basicsize); + py_basicsize = 0; + if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) + goto bad; +#endif + if ((size_t)basicsize < size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(result); + return NULL; +} +#endif + +/* Import */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_MAJOR_VERSION < 3 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_MAJOR_VERSION < 3 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + +/* PyDictVersioning */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + +/* CLineInTraceback */ +#ifndef CYTHON_CLINE_IN_TRACEBACK +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { + PyObject *use_cline; + PyObject *ptype, *pvalue, *ptraceback; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject **cython_runtime_dict; +#endif + if (unlikely(!__pyx_cython_runtime)) { + return c_line; + } + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); +#if CYTHON_COMPILING_IN_CPYTHON + cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); + if (likely(cython_runtime_dict)) { + __PYX_PY_DICT_LOOKUP_IF_MODIFIED( + use_cline, *cython_runtime_dict, + __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) + } else +#endif + { + PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); + if (use_cline_obj) { + use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; + Py_DECREF(use_cline_obj); + } else { + PyErr_Clear(); + use_cline = NULL; + } + } + if (!use_cline) { + c_line = 0; + PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); + } + else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { + c_line = 0; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + return c_line; +} +#endif + +/* CodeObjectCache */ +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = start + (end - start) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +/* AddTraceback */ +#include "compile.h" +#include "frameobject.h" +#include "traceback.h" +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyObject *py_srcfile = 0; + PyObject *py_funcname = 0; + #if PY_MAJOR_VERSION < 3 + py_srcfile = PyString_FromString(filename); + #else + py_srcfile = PyUnicode_FromString(filename); + #endif + if (!py_srcfile) goto bad; + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + #else + py_funcname = PyUnicode_FromString(funcname); + #endif + } + if (!py_funcname) goto bad; + py_code = __Pyx_PyCode_New( + 0, + 0, + 0, + 0, + 0, + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + Py_DECREF(py_funcname); + return py_code; +bad: + Py_XDECREF(py_srcfile); + Py_XDECREF(py_funcname); + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + if (c_line) { + c_line = __Pyx_CLineForTraceback(tstate, c_line); + } + py_code = __pyx_find_code_object(c_line ? -c_line : py_line); + if (!py_code) { + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) goto bad; + __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); + } + py_frame = PyFrame_New( + tstate, /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + __pyx_d, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + __Pyx_PyFrame_SetLineNumber(py_frame, py_line); + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +/* Declarations */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabsf(b.real) >= fabsf(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + float r = b.imag / b.real; + float s = (float)(1.0) / (b.real + b.imag * r); + return __pyx_t_float_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + float r = b.real / b.imag; + float s = (float)(1.0) / (b.imag + b.real * r); + return __pyx_t_float_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + float denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_float_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_float(a, a); + case 3: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, a); + case 4: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = powf(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2f(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_float(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +/* Declarations */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabs(b.real) >= fabs(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + double r = b.imag / b.real; + double s = (double)(1.0) / (b.real + b.imag * r); + return __pyx_t_double_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + double r = b.real / b.imag; + double s = (double)(1.0) / (b.imag + b.real * r); + return __pyx_t_double_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + double denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_double_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_double(a, a); + case 3: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, a); + case 4: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = pow(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_double(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(long) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(long) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(long) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(long), + little, !is_unsigned); + } +} + +/* CIntFromPyVerify */ +#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ + } + +/* CIntFromPy */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(long) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (long) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(long) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + } +#endif + if (sizeof(long) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + long val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (long) -1; + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (long) -1; + val = __Pyx_PyInt_As_long(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to long"); + return (long) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long) -1; +} + +/* CIntFromPy */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + } +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +/* FastTypeChecks */ +#if CYTHON_COMPILING_IN_CPYTHON +static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { + while (a) { + a = a->tp_base; + if (a == b) + return 1; + } + return b == &PyBaseObject_Type; +} +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { + PyObject *mro; + if (a == b) return 1; + mro = a->tp_mro; + if (likely(mro)) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(mro); + for (i = 0; i < n; i++) { + if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) + return 1; + } + return 0; + } + return __Pyx_InBases(a, b); +} +#if PY_MAJOR_VERSION == 2 +static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { + PyObject *exception, *value, *tb; + int res; + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&exception, &value, &tb); + res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + if (!res) { + res = PyObject_IsSubclass(err, exc_type2); + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + } + __Pyx_ErrRestore(exception, value, tb); + return res; +} +#else +static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { + int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; + if (!res) { + res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); + } + return res; +} +#endif +static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + assert(PyExceptionClass_Check(exc_type)); + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; itp_setattro)) + return tp->tp_setattro(obj, attr_name, value); +#if PY_MAJOR_VERSION < 3 + if (likely(tp->tp_setattr)) + return tp->tp_setattr(obj, PyString_AS_STRING(attr_name), value); +#endif + return PyObject_SetAttr(obj, attr_name, value); +} +#endif + +/* VoidPtrExport */ +static int __Pyx_ExportVoidPtr(PyObject *name, void *p, const char *sig) { + PyObject *d; + PyObject *cobj = 0; + d = PyDict_GetItem(__pyx_d, __pyx_n_s_pyx_capi); + Py_XINCREF(d); + if (!d) { + d = PyDict_New(); + if (!d) + goto bad; + if (__Pyx_PyObject_SetAttrStr(__pyx_m, __pyx_n_s_pyx_capi, d) < 0) + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + cobj = PyCapsule_New(p, sig, 0); +#else + cobj = PyCObject_FromVoidPtrAndDesc(p, (void *)sig, 0); +#endif + if (!cobj) + goto bad; + if (PyDict_SetItem(d, name, cobj) < 0) + goto bad; + Py_DECREF(cobj); + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(cobj); + Py_XDECREF(d); + return -1; +} + +/* InitStrings */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + if (PyObject_Hash(*t->p) == -1) + return -1; + ++t; + } + return 0; +} + +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { + return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); +} +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { + Py_ssize_t ignore; + return __Pyx_PyObject_AsStringAndSize(o, &ignore); +} +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if !CYTHON_PEP393_ENABLED +static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + char* defenc_c; + PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); + if (!defenc) return NULL; + defenc_c = PyBytes_AS_STRING(defenc); +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + { + char* end = defenc_c + PyBytes_GET_SIZE(defenc); + char* c; + for (c = defenc_c; c < end; c++) { + if ((unsigned char) (*c) >= 128) { + PyUnicode_AsASCIIString(o); + return NULL; + } + } + } +#endif + *length = PyBytes_GET_SIZE(defenc); + return defenc_c; +} +#else +static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + if (likely(PyUnicode_IS_ASCII(o))) { + *length = PyUnicode_GET_LENGTH(o); + return PyUnicode_AsUTF8(o); + } else { + PyUnicode_AsASCIIString(o); + return NULL; + } +#else + return PyUnicode_AsUTF8AndSize(o, length); +#endif +} +#endif +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT + if ( +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + __Pyx_sys_getdefaultencoding_not_ascii && +#endif + PyUnicode_Check(o)) { + return __Pyx_PyUnicode_AsStringAndSize(o, length); + } else +#endif +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) + if (PyByteArray_Check(o)) { + *length = PyByteArray_GET_SIZE(o); + return PyByteArray_AS_STRING(o); + } else +#endif + { + char* result; + int r = PyBytes_AsStringAndSize(o, &result, length); + if (unlikely(r < 0)) { + return NULL; + } else { + return result; + } + } +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { + int retval; + if (unlikely(!x)) return -1; + retval = __Pyx_PyObject_IsTrue(x); + Py_DECREF(x); + return retval; +} +static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { +#if PY_MAJOR_VERSION >= 3 + if (PyLong_Check(result)) { + if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, + "__int__ returned non-int (type %.200s). " + "The ability to return an instance of a strict subclass of int " + "is deprecated, and may be removed in a future version of Python.", + Py_TYPE(result)->tp_name)) { + Py_DECREF(result); + return NULL; + } + return result; + } +#endif + PyErr_Format(PyExc_TypeError, + "__%.4s__ returned non-%.4s (type %.200s)", + type_name, type_name, Py_TYPE(result)->tp_name); + Py_DECREF(result); + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { +#if CYTHON_USE_TYPE_SLOTS + PyNumberMethods *m; +#endif + const char *name = NULL; + PyObject *res = NULL; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x) || PyLong_Check(x))) +#else + if (likely(PyLong_Check(x))) +#endif + return __Pyx_NewRef(x); +#if CYTHON_USE_TYPE_SLOTS + m = Py_TYPE(x)->tp_as_number; + #if PY_MAJOR_VERSION < 3 + if (m && m->nb_int) { + name = "int"; + res = m->nb_int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = m->nb_long(x); + } + #else + if (likely(m && m->nb_int)) { + name = "int"; + res = m->nb_int(x); + } + #endif +#else + if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { + res = PyNumber_Int(x); + } +#endif + if (likely(res)) { +#if PY_MAJOR_VERSION < 3 + if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { +#else + if (unlikely(!PyLong_CheckExact(res))) { +#endif + return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject *x; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(b); + } +#endif + if (likely(PyLong_CheckExact(b))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + } + } + #endif + return PyLong_AsSsize_t(b); + } + x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { + return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); +} +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { + return PyInt_FromSize_t(ival); +} + + +#endif /* Py_PYTHON_H */ diff --git a/stpredictions/models/OK3/_random.pxd b/stpredictions/models/OK3/_random.pxd new file mode 100644 index 000000000..60266c6d3 --- /dev/null +++ b/stpredictions/models/OK3/_random.pxd @@ -0,0 +1,44 @@ +# Authors: Arnaud Joly +# +# License: BSD 3 clause + + +import numpy as np +cimport numpy as np +ctypedef np.npy_uint32 UINT32_t + +cdef inline UINT32_t DEFAULT_SEED = 1 + +cdef enum: + # Max value for our rand_r replacement (near the bottom). + # We don't use RAND_MAX because it's different across platforms and + # particularly tiny on Windows/MSVC. + RAND_R_MAX = 0x7FFFFFFF + +# cpdef sample_without_replacement(np.int_t n_population, +# np.int_t n_samples, +# method=*, +# random_state=*) + +# rand_r replacement using a 32bit XorShift generator +# See http://www.jstatsoft.org/v08/i14/paper for details +cdef inline UINT32_t our_rand_r(UINT32_t* seed) nogil: + """Generate a pseudo-random np.uint32 from a np.uint32 seed""" + # seed shouldn't ever be 0. + if (seed[0] == 0): seed[0] = DEFAULT_SEED + + seed[0] ^= (seed[0] << 13) + seed[0] ^= (seed[0] >> 17) + seed[0] ^= (seed[0] << 5) + + # Note: we must be careful with the final line cast to np.uint32 so that + # the function behaves consistently across platforms. + # + # The following cast might yield different results on different platforms: + # wrong_cast = RAND_R_MAX + 1 + # + # We can use: + # good_cast = (RAND_R_MAX + 1) + # or: + # cdef np.uint32_t another_good_cast = RAND_R_MAX + 1 + return seed[0] % (RAND_R_MAX + 1) \ No newline at end of file diff --git a/stpredictions/models/OK3/_random.pyx b/stpredictions/models/OK3/_random.pyx new file mode 100644 index 000000000..7cedf711d --- /dev/null +++ b/stpredictions/models/OK3/_random.pyx @@ -0,0 +1,316 @@ +# cython: boundscheck=False +# cython: wraparound=False +# +# Author: Arnaud Joly +# +# License: BSD 3 clause +""" +Random utility function +======================= +This module complements missing features of ``numpy.random``. + +The module contains: + * Several algorithms to sample integers without replacement. + * Fast rand_r alternative based on xor shifts +""" +cimport cython + +import numpy as np +cimport numpy as np +np.import_array() + +# from . import check_random_state + +cdef UINT32_t DEFAULT_SEED = 1 + + +# cpdef _sample_without_replacement_check_input(np.int_t n_population, +# np.int_t n_samples): +# """ Check that input are consistent for sample_without_replacement""" +# if n_population < 0: +# raise ValueError('n_population should be greater than 0, got %s.' +# % n_population) + +# if n_samples > n_population: +# raise ValueError('n_population should be greater or equal than ' +# 'n_samples, got n_samples > n_population (%s > %s)' +# % (n_samples, n_population)) + + +# cpdef _sample_without_replacement_with_tracking_selection( +# np.int_t n_population, +# np.int_t n_samples, +# random_state=None): +# r"""Sample integers without replacement. + +# Select n_samples integers from the set [0, n_population) without +# replacement. + +# Time complexity: +# - Worst-case: unbounded +# - Average-case: +# O(O(np.random.randint) * \sum_{i=1}^n_samples 1 / +# (1 - i / n_population))) +# <= O(O(np.random.randint) * +# n_population * ln((n_population - 2) +# /(n_population - 1 - n_samples))) +# <= O(O(np.random.randint) * +# n_population * 1 / (1 - n_samples / n_population)) + +# Space complexity of O(n_samples) in a python set. + + +# Parameters +# ---------- +# n_population : int +# The size of the set to sample from. + +# n_samples : int +# The number of integer to sample. + +# random_state : int, RandomState instance or None, default=None +# If int, random_state is the seed used by the random number generator; +# If RandomState instance, random_state is the random number generator; +# If None, the random number generator is the RandomState instance used +# by `np.random`. + +# Returns +# ------- +# out : ndarray of shape (n_samples,) +# The sampled subsets of integer. +# """ +# _sample_without_replacement_check_input(n_population, n_samples) + +# cdef np.int_t i +# cdef np.int_t j +# cdef np.ndarray[np.int_t, ndim=1] out = np.empty((n_samples, ), dtype=int) + +# rng = check_random_state(random_state) +# rng_randint = rng.randint + +# # The following line of code are heavily inspired from python core, +# # more precisely of random.sample. +# cdef set selected = set() + +# for i in range(n_samples): +# j = rng_randint(n_population) +# while j in selected: +# j = rng_randint(n_population) +# selected.add(j) +# out[i] = j + +# return out + + +# cpdef _sample_without_replacement_with_pool(np.int_t n_population, +# np.int_t n_samples, +# random_state=None): +# """Sample integers without replacement. + +# Select n_samples integers from the set [0, n_population) without +# replacement. + +# Time complexity: O(n_population + O(np.random.randint) * n_samples) + +# Space complexity of O(n_population + n_samples). + + +# Parameters +# ---------- +# n_population : int +# The size of the set to sample from. + +# n_samples : int +# The number of integer to sample. + +# random_state : int, RandomState instance or None, default=None +# If int, random_state is the seed used by the random number generator; +# If RandomState instance, random_state is the random number generator; +# If None, the random number generator is the RandomState instance used +# by `np.random`. + +# Returns +# ------- +# out : ndarray of shape (n_samples,) +# The sampled subsets of integer. +# """ +# _sample_without_replacement_check_input(n_population, n_samples) + +# cdef np.int_t i +# cdef np.int_t j +# cdef np.ndarray[np.int_t, ndim=1] out = np.empty((n_samples, ), dtype=int) + +# cdef np.ndarray[np.int_t, ndim=1] pool = np.empty((n_population, ), +# dtype=int) + +# rng = check_random_state(random_state) +# rng_randint = rng.randint + +# # Initialize the pool +# for i in range(n_population): +# pool[i] = i + +# # The following line of code are heavily inspired from python core, +# # more precisely of random.sample. +# for i in range(n_samples): +# j = rng_randint(n_population - i) # invariant: non-selected at [0,n-i) +# out[i] = pool[j] +# pool[j] = pool[n_population - i - 1] # move non-selected item into +# # vacancy + +# return out + + +# cpdef _sample_without_replacement_with_reservoir_sampling( +# np.int_t n_population, +# np.int_t n_samples, +# random_state=None): +# """Sample integers without replacement. + +# Select n_samples integers from the set [0, n_population) without +# replacement. + +# Time complexity of +# O((n_population - n_samples) * O(np.random.randint) + n_samples) +# Space complexity of O(n_samples) + + +# Parameters +# ---------- +# n_population : int +# The size of the set to sample from. + +# n_samples : int +# The number of integer to sample. + +# random_state : int, RandomState instance or None, default=None +# If int, random_state is the seed used by the random number generator; +# If RandomState instance, random_state is the random number generator; +# If None, the random number generator is the RandomState instance used +# by `np.random`. + +# Returns +# ------- +# out : ndarray of shape (n_samples,) +# The sampled subsets of integer. The order of the items is not +# necessarily random. Use a random permutation of the array if the order +# of the items has to be randomized. +# """ +# _sample_without_replacement_check_input(n_population, n_samples) + +# cdef np.int_t i +# cdef np.int_t j +# cdef np.ndarray[np.int_t, ndim=1] out = np.empty((n_samples, ), dtype=int) + +# rng = check_random_state(random_state) +# rng_randint = rng.randint + +# # This cython implementation is based on the one of Robert Kern: +# # http://mail.scipy.org/pipermail/numpy-discussion/2010-December/ +# # 054289.html +# # +# for i in range(n_samples): +# out[i] = i + +# for i from n_samples <= i < n_population: +# j = rng_randint(0, i + 1) +# if j < n_samples: +# out[j] = i + +# return out + + +# cpdef sample_without_replacement(np.int_t n_population, +# np.int_t n_samples, +# method="auto", +# random_state=None): +# """Sample integers without replacement. + +# Select n_samples integers from the set [0, n_population) without +# replacement. + + +# Parameters +# ---------- +# n_population : int +# The size of the set to sample from. + +# n_samples : int +# The number of integer to sample. + +# random_state : int, RandomState instance or None, default=None +# If int, random_state is the seed used by the random number generator; +# If RandomState instance, random_state is the random number generator; +# If None, the random number generator is the RandomState instance used +# by `np.random`. + +# method : {"auto", "tracking_selection", "reservoir_sampling", "pool"}, \ +# default='auto' +# If method == "auto", the ratio of n_samples / n_population is used +# to determine which algorithm to use: +# If ratio is between 0 and 0.01, tracking selection is used. +# If ratio is between 0.01 and 0.99, numpy.random.permutation is used. +# If ratio is greater than 0.99, reservoir sampling is used. +# The order of the selected integers is undefined. If a random order is +# desired, the selected subset should be shuffled. + +# If method =="tracking_selection", a set based implementation is used +# which is suitable for `n_samples` <<< `n_population`. + +# If method == "reservoir_sampling", a reservoir sampling algorithm is +# used which is suitable for high memory constraint or when +# O(`n_samples`) ~ O(`n_population`). +# The order of the selected integers is undefined. If a random order is +# desired, the selected subset should be shuffled. + +# If method == "pool", a pool based algorithm is particularly fast, even +# faster than the tracking selection method. However, a vector containing +# the entire population has to be initialized. +# If n_samples ~ n_population, the reservoir sampling method is faster. + +# Returns +# ------- +# out : ndarray of shape (n_samples,) +# The sampled subsets of integer. The subset of selected integer might +# not be randomized, see the method argument. +# """ +# _sample_without_replacement_check_input(n_population, n_samples) + +# all_methods = ("auto", "tracking_selection", "reservoir_sampling", "pool") + +# ratio = n_samples / n_population if n_population != 0.0 else 1.0 + +# # Check ratio and use permutation unless ratio < 0.01 or ratio > 0.99 +# if method == "auto" and ratio > 0.01 and ratio < 0.99: +# rng = check_random_state(random_state) +# return rng.permutation(n_population)[:n_samples] + +# if method == "auto" or method == "tracking_selection": +# # TODO the pool based method can also be used. +# # however, it requires special benchmark to take into account +# # the memory requirement of the array vs the set. + +# # The value 0.2 has been determined through benchmarking. +# if ratio < 0.2: +# return _sample_without_replacement_with_tracking_selection( +# n_population, n_samples, random_state) +# else: +# return _sample_without_replacement_with_reservoir_sampling( +# n_population, n_samples, random_state) + +# elif method == "reservoir_sampling": +# return _sample_without_replacement_with_reservoir_sampling( +# n_population, n_samples, random_state) + +# elif method == "pool": +# return _sample_without_replacement_with_pool(n_population, n_samples, +# random_state) +# else: +# raise ValueError('Expected a method name in %s, got %s. ' +# % (all_methods, method)) + + +# def _our_rand_r_py(seed): +# """Python utils to test the our_rand_r function""" +# cdef UINT32_t my_seed = seed +# return our_rand_r(&my_seed) \ No newline at end of file diff --git a/stpredictions/models/OK3/_splitter.c b/stpredictions/models/OK3/_splitter.c index 3e8c4dfd9..a4e0c5c97 100644 --- a/stpredictions/models/OK3/_splitter.c +++ b/stpredictions/models/OK3/_splitter.c @@ -4,8 +4,8 @@ { "distutils": { "depends": [ - "/home/asani/anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/core/include/numpy/arrayobject.h", - "/home/asani/anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/core/include/numpy/ufuncobject.h" + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include/numpy/arrayobject.h", + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include/numpy/ufuncobject.h" ], "extra_compile_args": [ "-O3", @@ -16,15 +16,15 @@ "-fopenmp" ], "include_dirs": [ - "/home/asani/anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/core/include", + "/home/asani/Documents/Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/core/include", "/home/asani/Documents/Hi_Paris_Code_Projects/Florence/structured-predictions/stpredictions/models/OK3/test" ], - "name": "_splitter", + "name": "stpredictions.models.OK3._splitter", "sources": [ "stpredictions/models/OK3/_splitter.pyx" ] }, - "module_name": "_splitter" + "module_name": "stpredictions.models.OK3._splitter" } END: Cython Metadata */ @@ -632,8 +632,8 @@ static CYTHON_INLINE float __PYX_NAN() { #endif #endif -#define __PYX_HAVE___splitter -#define __PYX_HAVE_API___splitter +#define __PYX_HAVE__stpredictions__models__OK3___splitter +#define __PYX_HAVE_API__stpredictions__models__OK3___splitter /* Early includes */ #include #include @@ -880,12 +880,10 @@ static const char *__pyx_f[] = { "stpredictions/models/OK3/_splitter.pxd", "__init__.pxd", "type.pxd", - "_criterion.pxd", - "_splitter.pxd", - "_tree.pxd", + "stpredictions/models/OK3/_tree.pxd", "stpredictions/models/OK3/_criterion.pxd", - "_quad_tree.pxd", - "_utils.pxd", + "stpredictions/models/OK3/_quad_tree.pxd", + "stpredictions/models/OK3/_utils.pxd", }; /* MemviewSliceStruct.proto */ struct __pyx_memoryview_obj; @@ -996,7 +994,7 @@ typedef struct { } __Pyx_BufFmt_Context; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":689 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":689 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -1005,7 +1003,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":690 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":690 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -1014,7 +1012,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":691 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":691 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -1023,7 +1021,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":692 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":692 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -1032,7 +1030,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":696 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":696 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -1041,7 +1039,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":697 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":697 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -1050,7 +1048,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":698 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":698 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -1059,7 +1057,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":699 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":699 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -1068,7 +1066,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":703 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":703 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -1077,7 +1075,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":704 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":704 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -1086,7 +1084,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":713 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":713 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -1095,7 +1093,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":714 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":714 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -1104,7 +1102,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":715 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":715 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -1113,7 +1111,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":717 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":717 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -1122,7 +1120,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":718 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":718 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -1131,7 +1129,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":719 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":719 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -1140,7 +1138,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":721 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":721 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -1149,7 +1147,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":722 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":722 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -1158,7 +1156,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":724 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":724 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -1167,7 +1165,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":725 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":725 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -1176,7 +1174,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":726 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":726 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -1185,131 +1183,131 @@ typedef npy_double __pyx_t_5numpy_double_t; */ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; -/* "sklearn/tree/_tree.pxd":16 +/* "_tree.pxd":7 * cimport numpy as np * * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters */ -typedef npy_float32 __pyx_t_7sklearn_4tree_5_tree_DTYPE_t; +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t; -/* "sklearn/tree/_tree.pxd":17 +/* "_tree.pxd":8 * * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer */ -typedef npy_float64 __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t; +typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t; -/* "sklearn/tree/_tree.pxd":18 +/* "_tree.pxd":9 * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer */ -typedef npy_intp __pyx_t_7sklearn_4tree_5_tree_SIZE_t; +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t; -/* "sklearn/tree/_tree.pxd":19 +/* "_tree.pxd":10 * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer * */ -typedef npy_int32 __pyx_t_7sklearn_4tree_5_tree_INT32_t; +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t; -/* "sklearn/tree/_tree.pxd":20 +/* "_tree.pxd":11 * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< * - * from ._splitter cimport Splitter + * from _splitter cimport Splitter */ -typedef npy_uint32 __pyx_t_7sklearn_4tree_5_tree_UINT32_t; +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t; -/* "neighbors/_quad_tree.pxd":13 +/* "_quad_tree.pxd":13 * cimport numpy as np * * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer */ -typedef npy_float32 __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t; +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t; -/* "neighbors/_quad_tree.pxd":14 +/* "_quad_tree.pxd":14 * * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer */ -typedef npy_intp __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t; +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t; -/* "neighbors/_quad_tree.pxd":15 +/* "_quad_tree.pxd":15 * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer * */ -typedef npy_int32 __pyx_t_7sklearn_9neighbors_10_quad_tree_INT32_t; +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_INT32_t; -/* "neighbors/_quad_tree.pxd":16 +/* "_quad_tree.pxd":16 * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< * * # This is effectively an ifdef statement in Cython */ -typedef npy_uint32 __pyx_t_7sklearn_9neighbors_10_quad_tree_UINT32_t; +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_UINT32_t; -/* "sklearn/tree/_utils.pxd":16 - * from ..neighbors._quad_tree cimport Cell +/* "_utils.pxd":16 + * from ._quad_tree cimport Cell * * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters */ -typedef npy_float32 __pyx_t_7sklearn_4tree_6_utils_DTYPE_t; +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t; -/* "sklearn/tree/_utils.pxd":17 +/* "_utils.pxd":17 * * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer */ -typedef npy_float64 __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t; +typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t; -/* "sklearn/tree/_utils.pxd":18 +/* "_utils.pxd":18 * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer */ -typedef npy_intp __pyx_t_7sklearn_4tree_6_utils_SIZE_t; +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t; -/* "sklearn/tree/_utils.pxd":19 +/* "_utils.pxd":19 * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer * */ -typedef npy_int32 __pyx_t_7sklearn_4tree_6_utils_INT32_t; +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_6_utils_INT32_t; -/* "sklearn/tree/_utils.pxd":20 +/* "_utils.pxd":20 * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< * * */ -typedef npy_uint32 __pyx_t_7sklearn_4tree_6_utils_UINT32_t; +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_6_utils_UINT32_t; /* Declarations.proto */ #if CYTHON_CCOMPLEX #ifdef __cplusplus @@ -1336,32 +1334,28 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do /*--- Type declarations ---*/ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion; -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter; -struct __pyx_obj_7sklearn_4tree_5_tree_Tree; -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder; -struct __pyx_obj_10_criterion_Criterion; -struct __pyx_obj_10_criterion_KernelizedRegressionCriterion; -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree; -struct __pyx_obj_7sklearn_4tree_6_utils_Stack; -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator; -struct __pyx_obj_9_splitter_Splitter; -struct __pyx_obj_9_splitter_BaseDenseSplitter; -struct __pyx_obj_9_splitter_BestSplitter; -struct __pyx_obj_9_splitter_RandomSplitter; -struct __pyx_obj_9_splitter_BaseSparseSplitter; -struct __pyx_obj_9_splitter_BestSparseSplitter; -struct __pyx_obj_9_splitter_RandomSparseSplitter; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; +struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter; struct __pyx_array_obj; struct __pyx_MemviewEnum_obj; struct __pyx_memoryview_obj; struct __pyx_memoryviewslice_obj; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":728 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":728 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -1370,7 +1364,7 @@ struct __pyx_memoryviewslice_obj; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":729 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":729 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -1379,7 +1373,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":730 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":730 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -1388,7 +1382,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":732 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":732 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -1396,88 +1390,71 @@ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; * cdef inline object PyArray_MultiIterNew1(a): */ typedef npy_cdouble __pyx_t_5numpy_complex_t; -struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord; +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build; -/* "_splitter.pxd":23 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef struct SplitRecord: # <<<<<<<<<<<<<< - * # Data to track sample split - * SIZE_t feature # Which feature to split on. - */ -struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - double threshold; - double improvement; - double impurity_left; - double impurity_right; -}; -struct __pyx_t_7sklearn_4tree_5_tree_Node; -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c; -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances; -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build; - -/* "sklearn/tree/_tree.pxd":25 - * from ._splitter cimport SplitRecord +/* "_tree.pxd":16 + * from _splitter cimport SplitRecord * * cdef struct Node: # <<<<<<<<<<<<<< * # Base storage structure for the nodes in a Tree object * */ -struct __pyx_t_7sklearn_4tree_5_tree_Node { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t left_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t right_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t threshold; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t impurity; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t weighted_n_node_samples; +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t left_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t right_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t threshold; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t impurity; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t weighted_n_node_samples; }; -/* "sklearn/tree/_tree.pxd":63 +/* "_tree.pxd":52 * double weighted_n_samples) nogil except -1 * cdef int _resize(self, SIZE_t capacity) nogil except -1 * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< * * cdef np.ndarray _get_value_ndarray(self) */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c { int __pyx_n; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; }; -/* "sklearn/tree/_tree.pxd":78 +/* "_tree.pxd":68 * cdef object _decision_path_sparse_csr(self, object X) * * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< * * */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances { int __pyx_n; PyObject *normalize; }; -/* "sklearn/tree/_tree.pxd":102 +/* "_tree.pxd":92 * cdef double min_impurity_decrease # Impurity threshold for early stopping * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< * np.ndarray sample_weight=*) * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build { int __pyx_n; PyArrayObject *sample_weight; }; -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; - -/* "neighbors/_quad_tree.pxd":21 +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell; + +/* "_quad_tree.pxd":21 * # It allows us to write printf debugging lines * # and remove them at compile time * cdef enum: # <<<<<<<<<<<<<< @@ -1485,96 +1462,96 @@ struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; * */ enum { - __pyx_e_7sklearn_9neighbors_10_quad_tree_DEBUGFLAG = 0 + __pyx_e_13stpredictions_6models_3OK3_10_quad_tree_DEBUGFLAG = 0 }; -/* "neighbors/_quad_tree.pxd":29 +/* "_quad_tree.pxd":29 * # have is_leaf and max_width consecutive as it permits to avoid padding by * # the compiler and keep the size coherent for both C and numpy data structures. * cdef struct Cell: # <<<<<<<<<<<<<< * # Base storage structure for cells in a QuadTree object * */ -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell { - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t parent; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t children[8]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t point_index; +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell { + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t parent; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t children[8]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t point_index; int is_leaf; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t squared_max_width; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cumulative_size; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t center[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t barycenter[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t min_bounds[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t max_bounds[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t squared_max_width; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t depth; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cumulative_size; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t center[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t barycenter[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t min_bounds[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t max_bounds[3]; }; -/* "neighbors/_quad_tree.pxd":75 +/* "_quad_tree.pxd":75 * * # Point insertion methods * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< * SIZE_t cell_id=*) nogil except -1 * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; }; -/* "neighbors/_quad_tree.pxd":77 +/* "_quad_tree.pxd":77 * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, * SIZE_t cell_id=*) nogil except -1 * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< * SIZE_t point_index, SIZE_t size=* * ) nogil */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t size; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t size; }; -/* "neighbors/_quad_tree.pxd":84 +/* "_quad_tree.pxd":84 * * # Create a summary of the Tree compare to a query point * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< * float squared_theta=*, SIZE_t cell_id=*, long idx=* * ) nogil */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize { int __pyx_n; float squared_theta; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; long idx; }; -/* "neighbors/_quad_tree.pxd":99 +/* "_quad_tree.pxd":99 * # Private array manipulation to manage the ``cells`` array * cdef int _resize(self, SIZE_t capacity) nogil except -1 * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 * cdef np.ndarray _get_cell_ndarray(self) */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t capacity; }; -/* "neighbors/_quad_tree.pxd":100 +/* "_quad_tree.pxd":100 * cdef int _resize(self, SIZE_t capacity) nogil except -1 * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< * cdef np.ndarray _get_cell_ndarray(self) */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; }; -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord; -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord; -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord; -/* "sklearn/tree/_utils.pxd":23 +/* "_utils.pxd":23 * * * cdef enum: # <<<<<<<<<<<<<< @@ -1582,39 +1559,39 @@ struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; * # We don't use RAND_MAX because it's different across platforms and */ enum { - __pyx_e_7sklearn_4tree_6_utils_RAND_R_MAX = 0x7FFFFFFF + __pyx_e_13stpredictions_6models_3OK3_6_utils_RAND_R_MAX = 0x7FFFFFFF }; -/* "sklearn/tree/_utils.pxd":70 +/* "_utils.pxd":70 * * # A record on the stack for depth-first tree growing * cdef struct StackRecord: # <<<<<<<<<<<<<< * SIZE_t start * SIZE_t end */ -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t parent; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t depth; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t parent; int is_left; double impurity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t n_constant_features; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t n_constant_features; }; -/* "sklearn/tree/_utils.pxd":96 +/* "_utils.pxd":96 * * # A record on the frontier for best-first tree growing * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< * SIZE_t node_id * SIZE_t start */ -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t node_id; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t pos; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t node_id; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t pos; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t depth; int is_leaf; double impurity; double impurity_left; @@ -1622,182 +1599,94 @@ struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { double improvement; }; -/* "sklearn/tree/_utils.pxd":127 +/* "_utils.pxd":127 * * # A record stored in the WeightedPQueue * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< * DOUBLE_t data * DOUBLE_t weight */ -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord { - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t data; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t weight; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t data; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t weight; }; -struct __pyx_t_9_splitter_SplitRecord; +struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord; -/* "_splitter.pxd":14 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer +/* "stpredictions/models/OK3/_splitter.pxd":14 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer * * cdef struct SplitRecord: # <<<<<<<<<<<<<< * # Data to track sample split * SIZE_t feature # Which feature to split on. */ -struct __pyx_t_9_splitter_SplitRecord { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; +struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t pos; double threshold; double improvement; double impurity_left; double impurity_right; }; -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtab; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - double weighted_n_samples; - double weighted_n_node_samples; - double weighted_n_left; - double weighted_n_right; - double *sum_total; - double *sum_left; - double *sum_right; -}; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t sum_stride; -}; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - double sq_sum_total; -}; - - -/* "_splitter.pxd":34 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *criterion; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - PyObject *random_state; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - double weighted_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; -}; - - -/* "sklearn/tree/_tree.pxd":37 +/* "_tree.pxd":28 * * * cdef class Tree: # <<<<<<<<<<<<<< * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and + * # TreeBuilder. */ -struct __pyx_obj_7sklearn_4tree_5_tree_Tree { +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtab; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t node_count; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; - struct __pyx_t_7sklearn_4tree_5_tree_Node *nodes; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t node_count; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; + PyArrayObject *K_y; + PyArrayObject *y; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *nodes; double *value; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t value_stride; }; -/* "sklearn/tree/_tree.pxd":85 +/* "_tree.pxd":75 * # ============================================================================= * * cdef class TreeBuilder: # <<<<<<<<<<<<<< * # The TreeBuilder recursively builds a Tree object from training samples, * # using a Splitter object for splitting internal nodes and assigning */ -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder { +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *splitter; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_split; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtab; + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *splitter; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_split; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; double min_weight_leaf; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; double min_impurity_split; double min_impurity_decrease; }; /* "_criterion.pxd":12 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * from ._tree cimport UINT32_t # Unsigned 32 bit integer * * cdef class Criterion: # <<<<<<<<<<<<<< * # The criterion computes the impurity of a node and the reduction of * # impurity of a split on that node. */ -struct __pyx_obj_10_criterion_Criterion { +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion { PyObject_HEAD - struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtab; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtab; __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *sample_weight; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t pos; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; double weighted_n_samples; double weighted_n_node_samples; double weighted_n_left; @@ -1812,8 +1701,8 @@ struct __pyx_obj_10_criterion_Criterion { * """Abstract kernelized output regression criterion.""" * */ -struct __pyx_obj_10_criterion_KernelizedRegressionCriterion { - struct __pyx_obj_10_criterion_Criterion __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; double sum_diag_Gramm; double sum_total_Gramm; double sum_diag_Gramm_left; @@ -1823,200 +1712,200 @@ struct __pyx_obj_10_criterion_KernelizedRegressionCriterion { }; -/* "neighbors/_quad_tree.pxd":55 +/* "_quad_tree.pxd":55 * * * cdef class _QuadTree: # <<<<<<<<<<<<<< * # The QuadTree object is a quad tree structure constructed by inserting * # recursively points in the tree and splitting cells in 4 so that each */ -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree { +struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtab; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_vtab; int n_dimensions; int verbose; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_cells_per_cell; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t max_depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_count; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_points; - struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *cells; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t n_cells_per_cell; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_count; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t n_points; + struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *cells; }; -/* "sklearn/tree/_utils.pxd":79 +/* "_utils.pxd":79 * SIZE_t n_constant_features * * cdef class Stack: # <<<<<<<<<<<<<< * cdef SIZE_t capacity * cdef SIZE_t top */ -struct __pyx_obj_7sklearn_4tree_6_utils_Stack { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t top; - struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *stack_; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t top; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *stack_; }; -/* "sklearn/tree/_utils.pxd":108 +/* "_utils.pxd":108 * double improvement * * cdef class PriorityHeap: # <<<<<<<<<<<<<< * cdef SIZE_t capacity * cdef SIZE_t heap_ptr */ -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t heap_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *heap_; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t heap_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *heap_; }; -/* "sklearn/tree/_utils.pxd":131 +/* "_utils.pxd":131 * DOUBLE_t weight * * cdef class WeightedPQueue: # <<<<<<<<<<<<<< * cdef SIZE_t capacity * cdef SIZE_t array_ptr */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t array_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *array_; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t array_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *array_; }; -/* "sklearn/tree/_utils.pxd":151 +/* "_utils.pxd":151 * # ============================================================================= * * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< * cdef SIZE_t initial_capacity * cdef WeightedPQueue samples */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t initial_capacity; - struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *samples; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t total_weight; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t k; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t sum_w_0_k; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t initial_capacity; + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *samples; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t total_weight; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t k; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t sum_w_0_k; }; -/* "_splitter.pxd":25 +/* "stpredictions/models/OK3/_splitter.pxd":25 * double impurity_right # Impurity of the right split. * * cdef class Splitter: # <<<<<<<<<<<<<< * # The splitter searches in the input space for a feature and a threshold * # to split the samples samples[start:end]. */ -struct __pyx_obj_9_splitter_Splitter { +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter { PyObject_HEAD - struct __pyx_vtabstruct_9_splitter_Splitter *__pyx_vtab; - struct __pyx_obj_10_criterion_Criterion *criterion; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtab; + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *criterion; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; double min_weight_leaf; PyObject *random_state; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t rand_r_state; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_samples; double weighted_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *constant_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *feature_values; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t end; __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *sample_weight; }; -/* "_splitter.pyx":223 +/* "stpredictions/models/OK3/_splitter.pyx":223 * * * cdef class BaseDenseSplitter(Splitter): # <<<<<<<<<<<<<< * cdef const DTYPE_t[:, :] X * */ -struct __pyx_obj_9_splitter_BaseDenseSplitter { - struct __pyx_obj_9_splitter_Splitter __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter __pyx_base; __Pyx_memviewslice X; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_total_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_total_samples; }; -/* "_splitter.pyx":245 +/* "stpredictions/models/OK3/_splitter.pyx":245 * * * cdef class BestSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< * """Splitter for finding the best split.""" * def __reduce__(self): */ -struct __pyx_obj_9_splitter_BestSplitter { - struct __pyx_obj_9_splitter_BaseDenseSplitter __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter __pyx_base; }; -/* "_splitter.pyx":564 +/* "stpredictions/models/OK3/_splitter.pyx":564 * * * cdef class RandomSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< * """Splitter for finding the best random split.""" * def __reduce__(self): */ -struct __pyx_obj_9_splitter_RandomSplitter { - struct __pyx_obj_9_splitter_BaseDenseSplitter __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter __pyx_base; }; -/* "_splitter.pyx":761 +/* "stpredictions/models/OK3/_splitter.pyx":761 * * * cdef class BaseSparseSplitter(Splitter): # <<<<<<<<<<<<<< * # The sparse splitter works only with csc sparse matrix format * cdef DTYPE_t* X_data */ -struct __pyx_obj_9_splitter_BaseSparseSplitter { - struct __pyx_obj_9_splitter_Splitter __pyx_base; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *X_data; - __pyx_t_7sklearn_4tree_5_tree_INT32_t *X_indices; - __pyx_t_7sklearn_4tree_5_tree_INT32_t *X_indptr; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_total_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *index_to_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *sorted_samples; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter __pyx_base; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *X_data; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *X_indices; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *X_indptr; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_total_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *index_to_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *sorted_samples; }; -/* "_splitter.pyx":1080 +/* "stpredictions/models/OK3/_splitter.pyx":1080 * * * cdef class BestSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< * """Splitter for finding the best split, using the sparse data.""" * */ -struct __pyx_obj_9_splitter_BestSparseSplitter { - struct __pyx_obj_9_splitter_BaseSparseSplitter __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_base; }; -/* "_splitter.pyx":1309 +/* "stpredictions/models/OK3/_splitter.pyx":1309 * * * cdef class RandomSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< * """Splitter for finding a random split, using the sparse data.""" * */ -struct __pyx_obj_9_splitter_RandomSparseSplitter { - struct __pyx_obj_9_splitter_BaseSparseSplitter __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_base; }; @@ -2098,101 +1987,34 @@ struct __pyx_memoryviewslice_obj { -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion { - int (*init)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double, double, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_Criterion; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_ClassificationCriterion; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_RegressionCriterion; - - -/* "_splitter.pxd":34 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ - -struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter { - int (*init)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); - int (*node_reset)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); - int (*node_split)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double, struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double *); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtabptr_7sklearn_4tree_9_splitter_Splitter; - - -/* "sklearn/tree/_tree.pxd":37 +/* "_tree.pxd":28 * * * cdef class Tree: # <<<<<<<<<<<<<< * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and - */ - -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double); - int (*_resize)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args); - PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*predict)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*apply)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*_apply_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*decision_path)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyObject *(*_decision_path_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*compute_feature_importances)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); + * # TreeBuilder. + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int, int, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double); + int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c *__pyx_optional_args); + PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); + PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); + PyArrayObject *(*decode_tree)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyArrayObject *, PyArrayObject *, PyObject *, PyObject *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int __pyx_skip_dispatch); + PyArrayObject *(*predict)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*apply)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*_apply_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*decision_path)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyObject *(*_decision_path_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*compute_feature_importances)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); }; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklearn_4tree_5_tree_Tree; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_Tree; -/* "sklearn/tree/_tree.pxd":85 +/* "_tree.pxd":75 * # ============================================================================= * * cdef class TreeBuilder: # <<<<<<<<<<<<<< @@ -2200,33 +2022,33 @@ static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklear * # using a Splitter object for splitting internal nodes and assigning */ -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder { - PyObject *(*build)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args); - PyObject *(*_check_input)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder { + PyObject *(*build)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build *__pyx_optional_args); + PyObject *(*_check_input)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_TreeBuilder; /* "_criterion.pxd":12 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * from ._tree cimport UINT32_t # Unsigned 32 bit integer * * cdef class Criterion: # <<<<<<<<<<<<<< * # The criterion computes the impurity of a node and the reduction of * # impurity of a split on that node. */ -struct __pyx_vtabstruct_10_criterion_Criterion { - int (*init)(struct __pyx_obj_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion { + int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); }; -static struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtabptr_10_criterion_Criterion; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion; /* "_criterion.pxd":50 @@ -2237,13 +2059,13 @@ static struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtabptr_10_criterio * */ -struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion { - struct __pyx_vtabstruct_10_criterion_Criterion __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; }; -static struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_10_criterion_KernelizedRegressionCriterion; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; -/* "neighbors/_quad_tree.pxd":55 +/* "_quad_tree.pxd":55 * * * cdef class _QuadTree: # <<<<<<<<<<<<<< @@ -2251,24 +2073,24 @@ static struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion *__pyx * # recursively points in the tree and splitting cells in 4 so that each */ -struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree { - int (*insert_point)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_is_duplicate)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - long (*summarize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); - void (*_init_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - void (*_init_root)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - int (*_check_point_in_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_resize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); - int (*_get_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); - PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree { + int (*insert_point)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *); + int (*_is_duplicate)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *); + long (*summarize)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); + void (*_init_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t); + void (*_init_root)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *); + int (*_check_point_in_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *); + int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); + int (*_get_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); + PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *); }; -static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtabptr_7sklearn_9neighbors_10_quad_tree__QuadTree; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_vtabptr_13stpredictions_6models_3OK3_10_quad_tree__QuadTree; -/* "sklearn/tree/_utils.pxd":79 +/* "_utils.pxd":79 * SIZE_t n_constant_features * * cdef class Stack: # <<<<<<<<<<<<<< @@ -2276,15 +2098,15 @@ static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx * cdef SIZE_t top */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, int, double, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7sklearn_4tree_6_utils_Stack; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_Stack; -/* "sklearn/tree/_utils.pxd":108 +/* "_utils.pxd":108 * double improvement * * cdef class PriorityHeap: # <<<<<<<<<<<<<< @@ -2292,17 +2114,17 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7skle * cdef SIZE_t heap_ptr */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); - void (*heapify_up)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - void (*heapify_down)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, double, double, double); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *); + void (*heapify_up)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + void (*heapify_down)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, int, double, double, double, double); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabptr_7sklearn_4tree_6_utils_PriorityHeap; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_PriorityHeap; -/* "sklearn/tree/_utils.pxd":131 +/* "_utils.pxd":131 * DOUBLE_t weight * * cdef class WeightedPQueue: # <<<<<<<<<<<<<< @@ -2310,21 +2132,21 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabpt * cdef SIZE_t array_ptr */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*peek)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*size)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + int (*peek)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedPQueue; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; -/* "sklearn/tree/_utils.pxd":151 +/* "_utils.pxd":151 * # ============================================================================= * * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< @@ -2332,20 +2154,20 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab * cdef WeightedPQueue samples */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*update_median_parameters_post_push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*update_median_parameters_post_remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*size)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); + int (*update_median_parameters_post_push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + int (*update_median_parameters_post_remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedMedianCalculator; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; -/* "_splitter.pyx":41 +/* "stpredictions/models/OK3/_splitter.pyx":41 * self.improvement = -INFINITY * * cdef class Splitter: # <<<<<<<<<<<<<< @@ -2353,17 +2175,17 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator * * */ -struct __pyx_vtabstruct_9_splitter_Splitter { - int (*init)(struct __pyx_obj_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); - int (*node_reset)(struct __pyx_obj_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); - int (*node_split)(struct __pyx_obj_9_splitter_Splitter *, double, struct __pyx_t_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); - void (*node_value)(struct __pyx_obj_9_splitter_Splitter *, double *); - double (*node_impurity)(struct __pyx_obj_9_splitter_Splitter *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter { + int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *); + int (*node_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double *); + int (*node_split)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *); + void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double *); + double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *); }; -static struct __pyx_vtabstruct_9_splitter_Splitter *__pyx_vtabptr_9_splitter_Splitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_Splitter; -/* "_splitter.pyx":223 +/* "stpredictions/models/OK3/_splitter.pyx":223 * * * cdef class BaseDenseSplitter(Splitter): # <<<<<<<<<<<<<< @@ -2371,13 +2193,13 @@ static struct __pyx_vtabstruct_9_splitter_Splitter *__pyx_vtabptr_9_splitter_Spl * */ -struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter { - struct __pyx_vtabstruct_9_splitter_Splitter __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter __pyx_base; }; -static struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter *__pyx_vtabptr_9_splitter_BaseDenseSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter; -/* "_splitter.pyx":245 +/* "stpredictions/models/OK3/_splitter.pyx":245 * * * cdef class BestSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< @@ -2385,13 +2207,13 @@ static struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter *__pyx_vtabptr_9_spl * def __reduce__(self): */ -struct __pyx_vtabstruct_9_splitter_BestSplitter { - struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSplitter { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter __pyx_base; }; -static struct __pyx_vtabstruct_9_splitter_BestSplitter *__pyx_vtabptr_9_splitter_BestSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BestSplitter; -/* "_splitter.pyx":564 +/* "stpredictions/models/OK3/_splitter.pyx":564 * * * cdef class RandomSplitter(BaseDenseSplitter): # <<<<<<<<<<<<<< @@ -2399,13 +2221,13 @@ static struct __pyx_vtabstruct_9_splitter_BestSplitter *__pyx_vtabptr_9_splitter * def __reduce__(self): */ -struct __pyx_vtabstruct_9_splitter_RandomSplitter { - struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSplitter { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter __pyx_base; }; -static struct __pyx_vtabstruct_9_splitter_RandomSplitter *__pyx_vtabptr_9_splitter_RandomSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_RandomSplitter; -/* "_splitter.pyx":761 +/* "stpredictions/models/OK3/_splitter.pyx":761 * * * cdef class BaseSparseSplitter(Splitter): # <<<<<<<<<<<<<< @@ -2413,17 +2235,17 @@ static struct __pyx_vtabstruct_9_splitter_RandomSplitter *__pyx_vtabptr_9_splitt * cdef DTYPE_t* X_data */ -struct __pyx_vtabstruct_9_splitter_BaseSparseSplitter { - struct __pyx_vtabstruct_9_splitter_Splitter __pyx_base; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_partition)(struct __pyx_obj_9_splitter_BaseSparseSplitter *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - void (*extract_nnz)(struct __pyx_obj_9_splitter_BaseSparseSplitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, int *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter __pyx_base; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t (*_partition)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + void (*extract_nnz)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, int *); }; -static struct __pyx_vtabstruct_9_splitter_BaseSparseSplitter *__pyx_vtabptr_9_splitter_BaseSparseSplitter; -static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_9_splitter_BaseSparseSplitter *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); -static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_9_splitter_BaseSparseSplitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, int *); +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter; +static CYTHON_INLINE __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, int *); -/* "_splitter.pyx":1080 +/* "stpredictions/models/OK3/_splitter.pyx":1080 * * * cdef class BestSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< @@ -2431,13 +2253,13 @@ static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(st * */ -struct __pyx_vtabstruct_9_splitter_BestSparseSplitter { - struct __pyx_vtabstruct_9_splitter_BaseSparseSplitter __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_base; }; -static struct __pyx_vtabstruct_9_splitter_BestSparseSplitter *__pyx_vtabptr_9_splitter_BestSparseSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter; -/* "_splitter.pyx":1309 +/* "stpredictions/models/OK3/_splitter.pyx":1309 * * * cdef class RandomSparseSplitter(BaseSparseSplitter): # <<<<<<<<<<<<<< @@ -2445,10 +2267,10 @@ static struct __pyx_vtabstruct_9_splitter_BestSparseSplitter *__pyx_vtabptr_9_sp * */ -struct __pyx_vtabstruct_9_splitter_RandomSparseSplitter { - struct __pyx_vtabstruct_9_splitter_BaseSparseSplitter __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_base; }; -static struct __pyx_vtabstruct_9_splitter_RandomSparseSplitter *__pyx_vtabptr_9_splitter_RandomSparseSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter; /* "View.MemoryView":105 @@ -3240,7 +3062,7 @@ static int __Pyx_ValidateAndInit_memviewslice( PyObject *original_obj); /* ObjectToMemviewSlice.proto */ -static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t__const__(PyObject *, int writable_flag); +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t__const__(PyObject *, int writable_flag); /* CheckBinaryVersion.proto */ static int __Pyx_check_binary_version(void); @@ -3254,19 +3076,19 @@ static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (** /* InitStrings.proto */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); -static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ -static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, double *__pyx_v_weighted_n_node_samples); /* proto*/ -static int __pyx_f_9_splitter_8Splitter_node_split(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED double __pyx_v_impurity, CYTHON_UNUSED struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ -static void __pyx_f_9_splitter_8Splitter_node_value(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, double *__pyx_v_dest); /* proto*/ -static double __pyx_f_9_splitter_8Splitter_node_impurity(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto*/ -static int __pyx_f_9_splitter_17BaseDenseSplitter_init(struct __pyx_obj_9_splitter_BaseDenseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ -static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_splitter_BestSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ -static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_splitter_RandomSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ -static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ -static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, double __pyx_v_threshold, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_zero_pos); /* proto*/ -static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_feature, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive, int *__pyx_v_is_samples_sorted); /* proto*/ -static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9_splitter_BestSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ -static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj_9_splitter_RandomSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_init(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_reset(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end, double *__pyx_v_weighted_n_node_samples); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_split(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED double __pyx_v_impurity, CYTHON_UNUSED struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_value(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, double *__pyx_v_dest); /* proto*/ +static double __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter_init(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_12BestSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_sample_weight); /* proto*/ +static CYTHON_INLINE __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, double __pyx_v_threshold, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end_negative, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start_positive, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_zero_pos); /* proto*/ +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_feature, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_start_positive, int *__pyx_v_is_samples_sorted); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_n_constant_features); /* proto*/ static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ @@ -3307,64 +3129,56 @@ static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ -/* Module declarations from 'sklearn.tree._criterion' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_Criterion = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_ClassificationCriterion = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_RegressionCriterion = 0; - -/* Module declarations from 'sklearn.tree._splitter' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_9_splitter_Splitter = 0; +/* Module declarations from 'stpredictions.models.OK3._tree' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree_Tree = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree_TreeBuilder = 0; -/* Module declarations from 'sklearn.tree._tree' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_Tree = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_TreeBuilder = 0; - -/* Module declarations from '_criterion' */ -static PyTypeObject *__pyx_ptype_10_criterion_Criterion = 0; -static PyTypeObject *__pyx_ptype_10_criterion_KernelizedRegressionCriterion = 0; +/* Module declarations from 'stpredictions.models.OK3._criterion' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_Criterion = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion = 0; /* Module declarations from 'libc.stdlib' */ -/* Module declarations from 'sklearn.neighbors._quad_tree' */ -static PyTypeObject *__pyx_ptype_7sklearn_9neighbors_10_quad_tree__QuadTree = 0; -static float *__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON = 0; -#define __pyx_v_7sklearn_9neighbors_10_quad_tree_EPSILON (*__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON) - -/* Module declarations from 'sklearn.tree._utils' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_Stack = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_PriorityHeap = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedPQueue = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedMedianCalculator = 0; -static __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*__pyx_f_7sklearn_4tree_6_utils_rand_int)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_UINT32_t *); /*proto*/ -static double (*__pyx_f_7sklearn_4tree_6_utils_rand_uniform)(double, double, __pyx_t_7sklearn_4tree_6_utils_UINT32_t *); /*proto*/ -static double (*__pyx_f_7sklearn_4tree_6_utils_log)(double); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DTYPE_t **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t **, size_t); /*proto*/ -static unsigned char *(*__pyx_fuse_2__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t ***, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_5_tree_Node *(*__pyx_fuse_6__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_5_tree_Node **(*__pyx_fuse_8__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node ***, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_StackRecord **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord **, size_t); /*proto*/ - -/* Module declarations from '_splitter' */ -static PyTypeObject *__pyx_ptype_9_splitter_Splitter = 0; -static PyTypeObject *__pyx_ptype_9_splitter_BaseDenseSplitter = 0; -static PyTypeObject *__pyx_ptype_9_splitter_BestSplitter = 0; -static PyTypeObject *__pyx_ptype_9_splitter_RandomSplitter = 0; -static PyTypeObject *__pyx_ptype_9_splitter_BaseSparseSplitter = 0; -static PyTypeObject *__pyx_ptype_9_splitter_BestSparseSplitter = 0; -static PyTypeObject *__pyx_ptype_9_splitter_RandomSparseSplitter = 0; +/* Module declarations from 'stpredictions.models.OK3._quad_tree' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_quad_tree__QuadTree = 0; +static float *__pyx_vp_13stpredictions_6models_3OK3_10_quad_tree_EPSILON = 0; +#define __pyx_v_13stpredictions_6models_3OK3_10_quad_tree_EPSILON (*__pyx_vp_13stpredictions_6models_3OK3_10_quad_tree_EPSILON) + +/* Module declarations from 'stpredictions.models.OK3._utils' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_Stack = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_PriorityHeap = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_WeightedPQueue = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator = 0; +static __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*__pyx_f_13stpredictions_6models_3OK3_6_utils_rand_int)(__pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_UINT32_t *); /*proto*/ +static double (*__pyx_f_13stpredictions_6models_3OK3_6_utils_rand_uniform)(double, double, __pyx_t_13stpredictions_6models_3OK3_6_utils_UINT32_t *); /*proto*/ +static double (*__pyx_f_13stpredictions_6models_3OK3_6_utils_log)(double); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t **, size_t); /*proto*/ +static unsigned char *(*__pyx_fuse_2__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t ***, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *(*__pyx_fuse_6__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node **(*__pyx_fuse_8__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node ***, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord **, size_t); /*proto*/ + +/* Module declarations from 'stpredictions.models.OK3._splitter' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_Splitter = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_BestSplitter = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_RandomSplitter = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter = 0; static PyTypeObject *__pyx_array_type = 0; static PyTypeObject *__pyx_MemviewEnum_type = 0; static PyTypeObject *__pyx_memoryview_type = 0; static PyTypeObject *__pyx_memoryviewslice_type = 0; -static double __pyx_v_9_splitter_INFINITY; -static __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_9_splitter_FEATURE_THRESHOLD; -static __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_9_splitter_EXTRACT_NNZ_SWITCH; +static double __pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY; +static __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD; +static __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_13stpredictions_6models_3OK3_9_splitter_EXTRACT_NNZ_SWITCH; static PyObject *generic = 0; static PyObject *strided = 0; static PyObject *indirect = 0; @@ -3372,18 +3186,18 @@ static PyObject *contiguous = 0; static PyObject *indirect_contiguous = 0; static int __pyx_memoryview_thread_locks_used; static PyThread_type_lock __pyx_memoryview_thread_locks[8]; -static CYTHON_INLINE void __pyx_f_9_splitter__init_split(struct __pyx_t_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static CYTHON_INLINE void __pyx_f_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static CYTHON_INLINE void __pyx_f_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_median3(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int); /*proto*/ -static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ -static int __pyx_f_9_splitter_compare_SIZE_t(void const *, void const *); /*proto*/ -static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t *); /*proto*/ -static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_t_7sklearn_4tree_5_tree_INT32_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); /*proto*/ -static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_INT32_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, int *); /*proto*/ -static CYTHON_INLINE void __pyx_f_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/ +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split(struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); /*proto*/ +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); /*proto*/ +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); /*proto*/ +static CYTHON_INLINE __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_median3(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); /*proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int); /*proto*/ +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sift_down(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); /*proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_heapsort(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); /*proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_compare_SIZE_t(void const *, void const *); /*proto*/ +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_binary_search(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *); /*proto*/ +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_index_to_samples(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *); /*proto*/ +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_binary_search(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, int *); /*proto*/ +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); /*proto*/ static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ static void *__pyx_align_pointer(void *, size_t); /*proto*/ static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ @@ -3417,14 +3231,14 @@ static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t = { "DTYPE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t), { 0 }, 0, 'R', 0, 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_INT32_t = { "INT32_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_INT32_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_7sklearn_4tree_5_tree_INT32_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_7sklearn_4tree_5_tree_INT32_t), 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t__const__ = { "const DTYPE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const ), { 0 }, 0, 'R', 0, 0 }; -#define __Pyx_MODULE_NAME "_splitter" -extern int __pyx_module_is_main__splitter; -int __pyx_module_is_main__splitter = 0; - -/* Implementation of '_splitter' */ +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t = { "DTYPE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t = { "INT32_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t), 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t__const__ = { "const DTYPE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t const ), { 0 }, 0, 'R', 0, 0 }; +#define __Pyx_MODULE_NAME "stpredictions.models.OK3._splitter" +extern int __pyx_module_is_main_stpredictions__models__OK3___splitter; +int __pyx_module_is_main_stpredictions__models__OK3___splitter = 0; + +/* Implementation of 'stpredictions.models.OK3._splitter' */ static PyObject *__pyx_builtin_range; static PyObject *__pyx_builtin_TypeError; static PyObject *__pyx_builtin_ValueError; @@ -3654,31 +3468,31 @@ static PyObject *__pyx_kp_s_unable_to_allocate_array_data; static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; static PyObject *__pyx_n_s_unpack; static PyObject *__pyx_n_s_update; -static int __pyx_pf_9_splitter_8Splitter___cinit__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, struct __pyx_obj_10_criterion_Criterion *__pyx_v_criterion, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, PyObject *__pyx_v_random_state); /* proto */ -static void __pyx_pf_9_splitter_8Splitter_2__dealloc__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_9_splitter_8Splitter_4__getstate__(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_9_splitter_8Splitter_6__setstate__(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d); /* proto */ -static PyObject *__pyx_pf_9_splitter_8Splitter_9criterion___get__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ -static int __pyx_pf_9_splitter_8Splitter_9criterion_2__set__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static int __pyx_pf_9_splitter_8Splitter_9criterion_4__del__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_9_splitter_8Splitter_12max_features___get__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ -static int __pyx_pf_9_splitter_8Splitter_12max_features_2__set__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_9_splitter_8Splitter_16min_samples_leaf___get__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ -static int __pyx_pf_9_splitter_8Splitter_16min_samples_leaf_2__set__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_9_splitter_8Splitter_15min_weight_leaf___get__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ -static int __pyx_pf_9_splitter_8Splitter_15min_weight_leaf_2__set__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_9_splitter_8Splitter_8__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_9_splitter_8Splitter_10__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_9_splitter_17BaseDenseSplitter___reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_BaseDenseSplitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_9_splitter_17BaseDenseSplitter_2__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_BaseDenseSplitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_9_splitter_12BestSplitter___reduce__(struct __pyx_obj_9_splitter_BestSplitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_obj_9_splitter_RandomSplitter *__pyx_v_self); /* proto */ -static int __pyx_pf_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_criterion, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, CYTHON_UNUSED double __pyx_v_min_weight_leaf, CYTHON_UNUSED PyObject *__pyx_v_random_state); /* proto */ -static void __pyx_pf_9_splitter_18BaseSparseSplitter_2__dealloc__(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_9_splitter_18BaseSparseSplitter_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_9_splitter_18BaseSparseSplitter_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __pyx_obj_9_splitter_BestSparseSplitter *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_9_splitter_20RandomSparseSplitter___reduce__(struct __pyx_obj_9_splitter_RandomSparseSplitter *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_criterion, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_features, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, PyObject *__pyx_v_random_state); /* proto */ +static void __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_4__getstate__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_6__setstate__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion___get__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_4__del__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features___get__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_16min_samples_leaf___get__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_16min_samples_leaf_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_15min_weight_leaf___get__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_15min_weight_leaf_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_8__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_10__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter___reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter_2__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_12BestSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_criterion, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_features, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf, CYTHON_UNUSED double __pyx_v_min_weight_leaf, CYTHON_UNUSED PyObject *__pyx_v_random_state); /* proto */ +static void __pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_v_self); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ @@ -3721,13 +3535,13 @@ static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__ static PyObject *__pyx_pf___pyx_memoryviewslice___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView___pyx_unpickle_Enum(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_tp_new_9_splitter_Splitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_9_splitter_BaseDenseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_9_splitter_BestSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_9_splitter_RandomSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_9_splitter_BaseSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_9_splitter_BestSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_9_splitter_RandomSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_Splitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BestSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_RandomSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ @@ -3772,7 +3586,7 @@ static PyObject *__pyx_tuple__33; static PyObject *__pyx_codeobj__34; /* Late includes */ -/* "_splitter.pyx":33 +/* "stpredictions/models/OK3/_splitter.pyx":33 * cdef DTYPE_t EXTRACT_NNZ_SWITCH = 0.1 * * cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) nogil: # <<<<<<<<<<<<<< @@ -3780,27 +3594,27 @@ static PyObject *__pyx_codeobj__34; * self.impurity_right = INFINITY */ -static CYTHON_INLINE void __pyx_f_9_splitter__init_split(struct __pyx_t_9_splitter_SplitRecord *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_pos) { +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split(struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start_pos) { - /* "_splitter.pyx":34 + /* "stpredictions/models/OK3/_splitter.pyx":34 * * cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) nogil: * self.impurity_left = INFINITY # <<<<<<<<<<<<<< * self.impurity_right = INFINITY * self.pos = start_pos */ - __pyx_v_self->impurity_left = __pyx_v_9_splitter_INFINITY; + __pyx_v_self->impurity_left = __pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY; - /* "_splitter.pyx":35 + /* "stpredictions/models/OK3/_splitter.pyx":35 * cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) nogil: * self.impurity_left = INFINITY * self.impurity_right = INFINITY # <<<<<<<<<<<<<< * self.pos = start_pos * self.feature = 0 */ - __pyx_v_self->impurity_right = __pyx_v_9_splitter_INFINITY; + __pyx_v_self->impurity_right = __pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY; - /* "_splitter.pyx":36 + /* "stpredictions/models/OK3/_splitter.pyx":36 * self.impurity_left = INFINITY * self.impurity_right = INFINITY * self.pos = start_pos # <<<<<<<<<<<<<< @@ -3809,7 +3623,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter__init_split(struct __pyx_t_9_splitt */ __pyx_v_self->pos = __pyx_v_start_pos; - /* "_splitter.pyx":37 + /* "stpredictions/models/OK3/_splitter.pyx":37 * self.impurity_right = INFINITY * self.pos = start_pos * self.feature = 0 # <<<<<<<<<<<<<< @@ -3818,7 +3632,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter__init_split(struct __pyx_t_9_splitt */ __pyx_v_self->feature = 0; - /* "_splitter.pyx":38 + /* "stpredictions/models/OK3/_splitter.pyx":38 * self.pos = start_pos * self.feature = 0 * self.threshold = 0. # <<<<<<<<<<<<<< @@ -3827,16 +3641,16 @@ static CYTHON_INLINE void __pyx_f_9_splitter__init_split(struct __pyx_t_9_splitt */ __pyx_v_self->threshold = 0.; - /* "_splitter.pyx":39 + /* "stpredictions/models/OK3/_splitter.pyx":39 * self.feature = 0 * self.threshold = 0. * self.improvement = -INFINITY # <<<<<<<<<<<<<< * * cdef class Splitter: */ - __pyx_v_self->improvement = (-__pyx_v_9_splitter_INFINITY); + __pyx_v_self->improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - /* "_splitter.pyx":33 + /* "stpredictions/models/OK3/_splitter.pyx":33 * cdef DTYPE_t EXTRACT_NNZ_SWITCH = 0.1 * * cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) nogil: # <<<<<<<<<<<<<< @@ -3847,7 +3661,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter__init_split(struct __pyx_t_9_splitt /* function exit code */ } -/* "_splitter.pyx":48 +/* "stpredictions/models/OK3/_splitter.pyx":48 * """ * * def __cinit__(self, Criterion criterion, SIZE_t max_features, # <<<<<<<<<<<<<< @@ -3856,11 +3670,11 @@ static CYTHON_INLINE void __pyx_f_9_splitter__init_split(struct __pyx_t_9_splitt */ /* Python wrapper */ -static int __pyx_pw_9_splitter_8Splitter_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static int __pyx_pw_9_splitter_8Splitter_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { - struct __pyx_obj_10_criterion_Criterion *__pyx_v_criterion = 0; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf; +static int __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static int __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_criterion = 0; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf; double __pyx_v_min_weight_leaf; PyObject *__pyx_v_random_state = 0; int __pyx_lineno = 0; @@ -3931,7 +3745,7 @@ static int __pyx_pw_9_splitter_8Splitter_1__cinit__(PyObject *__pyx_v_self, PyOb values[3] = PyTuple_GET_ITEM(__pyx_args, 3); values[4] = PyTuple_GET_ITEM(__pyx_args, 4); } - __pyx_v_criterion = ((struct __pyx_obj_10_criterion_Criterion *)values[0]); + __pyx_v_criterion = ((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *)values[0]); __pyx_v_max_features = __Pyx_PyInt_As_Py_intptr_t(values[1]); if (unlikely((__pyx_v_max_features == ((npy_intp)-1)) && PyErr_Occurred())) __PYX_ERR(0, 48, __pyx_L3_error) __pyx_v_min_samples_leaf = __Pyx_PyInt_As_Py_intptr_t(values[2]); if (unlikely((__pyx_v_min_samples_leaf == ((npy_intp)-1)) && PyErr_Occurred())) __PYX_ERR(0, 49, __pyx_L3_error) __pyx_v_min_weight_leaf = __pyx_PyFloat_AsDouble(values[3]); if (unlikely((__pyx_v_min_weight_leaf == (double)-1) && PyErr_Occurred())) __PYX_ERR(0, 49, __pyx_L3_error) @@ -3941,12 +3755,12 @@ static int __pyx_pw_9_splitter_8Splitter_1__cinit__(PyObject *__pyx_v_self, PyOb __pyx_L5_argtuple_error:; __Pyx_RaiseArgtupleInvalid("__cinit__", 1, 5, 5, PyTuple_GET_SIZE(__pyx_args)); __PYX_ERR(0, 48, __pyx_L3_error) __pyx_L3_error:; - __Pyx_AddTraceback("_splitter.Splitter.__cinit__", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.Splitter.__cinit__", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return -1; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_criterion), __pyx_ptype_10_criterion_Criterion, 1, "criterion", 0))) __PYX_ERR(0, 48, __pyx_L1_error) - __pyx_r = __pyx_pf_9_splitter_8Splitter___cinit__(((struct __pyx_obj_9_splitter_Splitter *)__pyx_v_self), __pyx_v_criterion, __pyx_v_max_features, __pyx_v_min_samples_leaf, __pyx_v_min_weight_leaf, __pyx_v_random_state); + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_criterion), __pyx_ptype_13stpredictions_6models_3OK3_10_criterion_Criterion, 1, "criterion", 0))) __PYX_ERR(0, 48, __pyx_L1_error) + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter___cinit__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_self), __pyx_v_criterion, __pyx_v_max_features, __pyx_v_min_samples_leaf, __pyx_v_min_weight_leaf, __pyx_v_random_state); /* function exit code */ goto __pyx_L0; @@ -3957,12 +3771,12 @@ static int __pyx_pw_9_splitter_8Splitter_1__cinit__(PyObject *__pyx_v_self, PyOb return __pyx_r; } -static int __pyx_pf_9_splitter_8Splitter___cinit__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, struct __pyx_obj_10_criterion_Criterion *__pyx_v_criterion, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, PyObject *__pyx_v_random_state) { +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_criterion, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_features, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, PyObject *__pyx_v_random_state) { int __pyx_r; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__cinit__", 0); - /* "_splitter.pyx":74 + /* "stpredictions/models/OK3/_splitter.pyx":74 * """ * * self.criterion = criterion # <<<<<<<<<<<<<< @@ -3975,7 +3789,7 @@ static int __pyx_pf_9_splitter_8Splitter___cinit__(struct __pyx_obj_9_splitter_S __Pyx_DECREF(((PyObject *)__pyx_v_self->criterion)); __pyx_v_self->criterion = __pyx_v_criterion; - /* "_splitter.pyx":76 + /* "stpredictions/models/OK3/_splitter.pyx":76 * self.criterion = criterion * * self.samples = NULL # <<<<<<<<<<<<<< @@ -3984,7 +3798,7 @@ static int __pyx_pf_9_splitter_8Splitter___cinit__(struct __pyx_obj_9_splitter_S */ __pyx_v_self->samples = NULL; - /* "_splitter.pyx":77 + /* "stpredictions/models/OK3/_splitter.pyx":77 * * self.samples = NULL * self.n_samples = 0 # <<<<<<<<<<<<<< @@ -3993,7 +3807,7 @@ static int __pyx_pf_9_splitter_8Splitter___cinit__(struct __pyx_obj_9_splitter_S */ __pyx_v_self->n_samples = 0; - /* "_splitter.pyx":78 + /* "stpredictions/models/OK3/_splitter.pyx":78 * self.samples = NULL * self.n_samples = 0 * self.features = NULL # <<<<<<<<<<<<<< @@ -4002,7 +3816,7 @@ static int __pyx_pf_9_splitter_8Splitter___cinit__(struct __pyx_obj_9_splitter_S */ __pyx_v_self->features = NULL; 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/*proto*/ -static PyObject *__pyx_pw_9_splitter_8Splitter_5__getstate__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_5__getstate__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/ +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_5__getstate__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__getstate__ (wrapper)", 0); - __pyx_r = __pyx_pf_9_splitter_8Splitter_4__getstate__(((struct __pyx_obj_9_splitter_Splitter *)__pyx_v_self)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_4__getstate__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_9_splitter_8Splitter_4__getstate__(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_4__getstate__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self) { PyObject *__pyx_r = NULL; 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+ __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_8; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t *__pyx_t_9; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_10; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_11; int __pyx_t_12; int __pyx_t_13; int __pyx_lineno = 0; @@ -4286,7 +4100,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte int __pyx_clineno = 0; __Pyx_RefNannySetupContext("init", 0); - /* "_splitter.pyx":128 + /* "stpredictions/models/OK3/_splitter.pyx":128 * """ * * self.rand_r_state = self.random_state.randint(0, RAND_R_MAX) # <<<<<<<<<<<<<< @@ -4295,7 +4109,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ __pyx_t_2 = __Pyx_PyObject_GetAttrStr(__pyx_v_self->random_state, __pyx_n_s_randint); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 128, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); - __pyx_t_3 = __Pyx_PyInt_From_int(__pyx_e_7sklearn_4tree_6_utils_RAND_R_MAX); if (unlikely(!__pyx_t_3)) __PYX_ERR(0, 128, __pyx_L1_error) + __pyx_t_3 = __Pyx_PyInt_From_int(__pyx_e_13stpredictions_6models_3OK3_6_utils_RAND_R_MAX); if (unlikely(!__pyx_t_3)) __PYX_ERR(0, 128, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); __pyx_t_4 = NULL; __pyx_t_5 = 0; @@ -4348,7 +4162,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_self->rand_r_state = __pyx_t_7; - /* "_splitter.pyx":129 + /* "stpredictions/models/OK3/_splitter.pyx":129 * * self.rand_r_state = self.random_state.randint(0, RAND_R_MAX) * cdef SIZE_t n_samples = X.shape[0] # <<<<<<<<<<<<<< @@ -4364,17 +4178,17 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __pyx_v_n_samples = __pyx_t_8; - /* "_splitter.pyx":133 + /* "stpredictions/models/OK3/_splitter.pyx":133 * # Create a new array which will be used to store nonzero * # samples from the feature of interest * cdef SIZE_t* samples = safe_realloc(&self.samples, n_samples) # <<<<<<<<<<<<<< * * cdef SIZE_t i, j */ - __pyx_t_9 = __pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->samples), __pyx_v_n_samples); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 133, __pyx_L1_error) + __pyx_t_9 = __pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_self->samples), __pyx_v_n_samples); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 133, __pyx_L1_error) __pyx_v_samples = __pyx_t_9; - /* "_splitter.pyx":136 + /* "stpredictions/models/OK3/_splitter.pyx":136 * * cdef SIZE_t i, j * cdef double weighted_n_samples = 0.0 # <<<<<<<<<<<<<< @@ -4383,7 +4197,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ __pyx_v_weighted_n_samples = 0.0; - /* "_splitter.pyx":137 + /* "stpredictions/models/OK3/_splitter.pyx":137 * cdef SIZE_t i, j * cdef double weighted_n_samples = 0.0 * j = 0 # <<<<<<<<<<<<<< @@ -4392,7 +4206,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ __pyx_v_j = 0; - /* "_splitter.pyx":139 + /* "stpredictions/models/OK3/_splitter.pyx":139 * j = 0 * * for i in range(n_samples): # <<<<<<<<<<<<<< @@ -4404,7 +4218,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte for (__pyx_t_11 = 0; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) { __pyx_v_i = __pyx_t_11; - /* "_splitter.pyx":141 + /* "stpredictions/models/OK3/_splitter.pyx":141 * for i in range(n_samples): * # Only work with positively weighted samples * if sample_weight == NULL or sample_weight[i] != 0.0: # <<<<<<<<<<<<<< @@ -4422,7 +4236,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte __pyx_L6_bool_binop_done:; if (__pyx_t_12) { - /* "_splitter.pyx":142 + /* "stpredictions/models/OK3/_splitter.pyx":142 * # Only work with positively weighted samples * if sample_weight == NULL or sample_weight[i] != 0.0: * samples[j] = i # <<<<<<<<<<<<<< @@ -4431,7 +4245,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ (__pyx_v_samples[__pyx_v_j]) = __pyx_v_i; - /* "_splitter.pyx":143 + /* "stpredictions/models/OK3/_splitter.pyx":143 * if sample_weight == NULL or sample_weight[i] != 0.0: * samples[j] = i * j += 1 # <<<<<<<<<<<<<< @@ -4440,7 +4254,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ __pyx_v_j = (__pyx_v_j + 1); - /* "_splitter.pyx":141 + /* "stpredictions/models/OK3/_splitter.pyx":141 * for i in range(n_samples): * # Only work with positively weighted samples * if sample_weight == NULL or sample_weight[i] != 0.0: # <<<<<<<<<<<<<< @@ -4449,7 +4263,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ } - /* "_splitter.pyx":145 + /* "stpredictions/models/OK3/_splitter.pyx":145 * j += 1 * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -4459,7 +4273,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte __pyx_t_12 = ((__pyx_v_sample_weight != NULL) != 0); if (__pyx_t_12) { - /* "_splitter.pyx":146 + /* "stpredictions/models/OK3/_splitter.pyx":146 * * if sample_weight != NULL: * weighted_n_samples += sample_weight[i] # <<<<<<<<<<<<<< @@ -4468,7 +4282,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ __pyx_v_weighted_n_samples = (__pyx_v_weighted_n_samples + (__pyx_v_sample_weight[__pyx_v_i])); - /* "_splitter.pyx":145 + /* "stpredictions/models/OK3/_splitter.pyx":145 * j += 1 * * if sample_weight != NULL: # <<<<<<<<<<<<<< @@ -4478,7 +4292,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte goto __pyx_L8; } - /* "_splitter.pyx":148 + /* "stpredictions/models/OK3/_splitter.pyx":148 * weighted_n_samples += sample_weight[i] * else: * weighted_n_samples += 1.0 # <<<<<<<<<<<<<< @@ -4491,7 +4305,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte __pyx_L8:; } - /* "_splitter.pyx":151 + /* "stpredictions/models/OK3/_splitter.pyx":151 * * # Number of samples is number of positively weighted samples * self.n_samples = j # <<<<<<<<<<<<<< @@ -4500,7 +4314,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ __pyx_v_self->n_samples = __pyx_v_j; - /* "_splitter.pyx":152 + /* "stpredictions/models/OK3/_splitter.pyx":152 * # Number of samples is number of positively weighted samples * self.n_samples = j * self.weighted_n_samples = weighted_n_samples # <<<<<<<<<<<<<< @@ -4509,7 +4323,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ __pyx_v_self->weighted_n_samples = __pyx_v_weighted_n_samples; - /* "_splitter.pyx":154 + /* "stpredictions/models/OK3/_splitter.pyx":154 * self.weighted_n_samples = weighted_n_samples * * cdef SIZE_t n_features = X.shape[1] # <<<<<<<<<<<<<< @@ -4525,17 +4339,17 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_n_features = __pyx_t_8; - /* "_splitter.pyx":155 + /* "stpredictions/models/OK3/_splitter.pyx":155 * * cdef SIZE_t n_features = X.shape[1] * cdef SIZE_t* features = safe_realloc(&self.features, n_features) # <<<<<<<<<<<<<< * * for i in range(n_features): */ - __pyx_t_9 = __pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->features), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 155, __pyx_L1_error) + __pyx_t_9 = __pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_self->features), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 155, __pyx_L1_error) __pyx_v_features = __pyx_t_9; - /* "_splitter.pyx":157 + /* "stpredictions/models/OK3/_splitter.pyx":157 * cdef SIZE_t* features = safe_realloc(&self.features, n_features) * * for i in range(n_features): # <<<<<<<<<<<<<< @@ -4547,7 +4361,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte for (__pyx_t_11 = 0; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) { __pyx_v_i = __pyx_t_11; - /* "_splitter.pyx":158 + /* "stpredictions/models/OK3/_splitter.pyx":158 * * for i in range(n_features): * features[i] = i # <<<<<<<<<<<<<< @@ -4557,7 +4371,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte (__pyx_v_features[__pyx_v_i]) = __pyx_v_i; } - /* "_splitter.pyx":160 + /* "stpredictions/models/OK3/_splitter.pyx":160 * features[i] = i * * self.n_features = n_features # <<<<<<<<<<<<<< @@ -4566,25 +4380,25 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ __pyx_v_self->n_features = __pyx_v_n_features; - /* "_splitter.pyx":162 + /* "stpredictions/models/OK3/_splitter.pyx":162 * self.n_features = n_features * * safe_realloc(&self.feature_values, n_samples) # <<<<<<<<<<<<<< * safe_realloc(&self.constant_features, n_features) * */ - __pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->feature_values), __pyx_v_n_samples); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 162, __pyx_L1_error) + __pyx_fuse_0__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_self->feature_values), __pyx_v_n_samples); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 162, __pyx_L1_error) - /* "_splitter.pyx":163 + /* "stpredictions/models/OK3/_splitter.pyx":163 * * safe_realloc(&self.feature_values, n_samples) * safe_realloc(&self.constant_features, n_features) # <<<<<<<<<<<<<< * * self.y = y */ - __pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->constant_features), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 163, __pyx_L1_error) + __pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_self->constant_features), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 163, __pyx_L1_error) - /* "_splitter.pyx":165 + /* "stpredictions/models/OK3/_splitter.pyx":165 * safe_realloc(&self.constant_features, n_features) * * self.y = y # <<<<<<<<<<<<<< @@ -4595,7 +4409,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte __PYX_INC_MEMVIEW(&__pyx_v_y, 0); __pyx_v_self->y = __pyx_v_y; - /* "_splitter.pyx":167 + /* "stpredictions/models/OK3/_splitter.pyx":167 * self.y = y * * self.sample_weight = sample_weight # <<<<<<<<<<<<<< @@ -4604,7 +4418,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte */ __pyx_v_self->sample_weight = __pyx_v_sample_weight; - /* "_splitter.pyx":168 + /* "stpredictions/models/OK3/_splitter.pyx":168 * * self.sample_weight = sample_weight * return 0 # <<<<<<<<<<<<<< @@ -4614,7 +4428,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte __pyx_r = 0; goto __pyx_L0; - /* "_splitter.pyx":103 + /* "stpredictions/models/OK3/_splitter.pyx":103 * pass * * cdef int init(self, # <<<<<<<<<<<<<< @@ -4629,14 +4443,14 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte __Pyx_XDECREF(__pyx_t_3); __Pyx_XDECREF(__pyx_t_4); __Pyx_XDECREF(__pyx_t_6); - __Pyx_AddTraceback("_splitter.Splitter.init", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.Splitter.init", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = -1; __pyx_L0:; __Pyx_RefNannyFinishContext(); return __pyx_r; } -/* "_splitter.pyx":170 +/* "stpredictions/models/OK3/_splitter.pyx":170 * return 0 * * cdef int node_reset(self, SIZE_t start, SIZE_t end, # <<<<<<<<<<<<<< @@ -4644,7 +4458,7 @@ static int __pyx_f_9_splitter_8Splitter_init(struct __pyx_obj_9_splitter_Splitte * """Reset splitter on node samples[start:end]. */ -static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, double *__pyx_v_weighted_n_node_samples) { +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_reset(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end, double *__pyx_v_weighted_n_node_samples) { int __pyx_r; int __pyx_t_1; double __pyx_t_2; @@ -4652,7 +4466,7 @@ static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_S const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "_splitter.pyx":187 + /* "stpredictions/models/OK3/_splitter.pyx":187 * """ * * self.start = start # <<<<<<<<<<<<<< @@ -4661,7 +4475,7 @@ static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_S */ __pyx_v_self->start = __pyx_v_start; - /* "_splitter.pyx":188 + /* "stpredictions/models/OK3/_splitter.pyx":188 * * self.start = start * self.end = end # <<<<<<<<<<<<<< @@ -4670,7 +4484,7 @@ static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_S */ __pyx_v_self->end = __pyx_v_end; - /* "_splitter.pyx":190 + /* "stpredictions/models/OK3/_splitter.pyx":190 * self.end = end * * self.criterion.init(self.y, # <<<<<<<<<<<<<< @@ -4679,16 +4493,16 @@ static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_S */ if (unlikely(!__pyx_v_self->y.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 190, __pyx_L1_error)} - /* "_splitter.pyx":195 + /* "stpredictions/models/OK3/_splitter.pyx":195 * self.samples, * start, * end) # <<<<<<<<<<<<<< * * weighted_n_node_samples[0] = self.criterion.weighted_n_node_samples */ - __pyx_t_1 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->criterion->__pyx_vtab)->init(__pyx_v_self->criterion, __pyx_v_self->y, __pyx_v_self->sample_weight, __pyx_v_self->weighted_n_samples, __pyx_v_self->samples, __pyx_v_start, __pyx_v_end); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 190, __pyx_L1_error) + __pyx_t_1 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->criterion->__pyx_vtab)->init(__pyx_v_self->criterion, __pyx_v_self->y, __pyx_v_self->sample_weight, __pyx_v_self->weighted_n_samples, __pyx_v_self->samples, __pyx_v_start, __pyx_v_end); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 190, __pyx_L1_error) - /* "_splitter.pyx":197 + /* "stpredictions/models/OK3/_splitter.pyx":197 * end) * * weighted_n_node_samples[0] = self.criterion.weighted_n_node_samples # <<<<<<<<<<<<<< @@ -4698,7 +4512,7 @@ static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_S __pyx_t_2 = __pyx_v_self->criterion->weighted_n_node_samples; (__pyx_v_weighted_n_node_samples[0]) = __pyx_t_2; - /* "_splitter.pyx":198 + /* "stpredictions/models/OK3/_splitter.pyx":198 * * weighted_n_node_samples[0] = self.criterion.weighted_n_node_samples * return 0 # <<<<<<<<<<<<<< @@ -4708,7 +4522,7 @@ static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_S __pyx_r = 0; goto __pyx_L0; - /* "_splitter.pyx":170 + /* "stpredictions/models/OK3/_splitter.pyx":170 * return 0 * * cdef int node_reset(self, SIZE_t start, SIZE_t end, # <<<<<<<<<<<<<< @@ -4722,7 +4536,7 @@ static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_S #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif - __Pyx_AddTraceback("_splitter.Splitter.node_reset", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.Splitter.node_reset", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif @@ -4732,7 +4546,7 @@ static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_S return __pyx_r; } -/* "_splitter.pyx":200 +/* "stpredictions/models/OK3/_splitter.pyx":200 * return 0 * * cdef int node_split(self, double impurity, SplitRecord* split, # <<<<<<<<<<<<<< @@ -4740,7 +4554,7 @@ static int __pyx_f_9_splitter_8Splitter_node_reset(struct __pyx_obj_9_splitter_S * """Find the best split on node samples[start:end]. */ -static int __pyx_f_9_splitter_8Splitter_node_split(CYTHON_UNUSED struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED double __pyx_v_impurity, CYTHON_UNUSED struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features) { +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_split(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, CYTHON_UNUSED double __pyx_v_impurity, CYTHON_UNUSED struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_n_constant_features) { int __pyx_r; /* function exit code */ @@ -4748,7 +4562,7 @@ static int __pyx_f_9_splitter_8Splitter_node_split(CYTHON_UNUSED struct __pyx_ob return __pyx_r; } -/* "_splitter.pyx":212 +/* "stpredictions/models/OK3/_splitter.pyx":212 * pass * * cdef void node_value(self, double* dest) nogil: # <<<<<<<<<<<<<< @@ -4756,18 +4570,18 @@ static int __pyx_f_9_splitter_8Splitter_node_split(CYTHON_UNUSED struct __pyx_ob * */ -static void __pyx_f_9_splitter_8Splitter_node_value(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, double *__pyx_v_dest) { +static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_value(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, double *__pyx_v_dest) { - /* "_splitter.pyx":215 + /* "stpredictions/models/OK3/_splitter.pyx":215 * """Copy the value of node samples[start:end] into dest.""" * * self.criterion.node_value(dest) # <<<<<<<<<<<<<< * * cdef double node_impurity(self) nogil: */ - ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->criterion->__pyx_vtab)->node_value(__pyx_v_self->criterion, __pyx_v_dest); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->criterion->__pyx_vtab)->node_value(__pyx_v_self->criterion, __pyx_v_dest); - /* "_splitter.pyx":212 + /* "stpredictions/models/OK3/_splitter.pyx":212 * pass * * cdef void node_value(self, double* dest) nogil: # <<<<<<<<<<<<<< @@ -4778,7 +4592,7 @@ static void __pyx_f_9_splitter_8Splitter_node_value(struct __pyx_obj_9_splitter_ /* function exit code */ } -/* "_splitter.pyx":217 +/* "stpredictions/models/OK3/_splitter.pyx":217 * self.criterion.node_value(dest) * * cdef double node_impurity(self) nogil: # <<<<<<<<<<<<<< @@ -4786,20 +4600,20 @@ static void __pyx_f_9_splitter_8Splitter_node_value(struct __pyx_obj_9_splitter_ * */ -static double __pyx_f_9_splitter_8Splitter_node_impurity(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self) { +static double __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_node_impurity(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self) { double __pyx_r; 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/*proto*/ -static int __pyx_pw_9_splitter_8Splitter_9criterion_5__del__(PyObject *__pyx_v_self) { +static int __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_5__del__(PyObject *__pyx_v_self); /*proto*/ +static int __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_5__del__(PyObject *__pyx_v_self) { int __pyx_r; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__del__ (wrapper)", 0); - __pyx_r = __pyx_pf_9_splitter_8Splitter_9criterion_4__del__(((struct __pyx_obj_9_splitter_Splitter *)__pyx_v_self)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_4__del__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static int __pyx_pf_9_splitter_8Splitter_9criterion_4__del__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self) { +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_4__del__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self) { int __pyx_r; 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/*proto*/ -static PyObject *__pyx_pw_9_splitter_8Splitter_12max_features_1__get__(PyObject *__pyx_v_self) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features_1__get__(PyObject *__pyx_v_self); /*proto*/ +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features_1__get__(PyObject *__pyx_v_self) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__get__ (wrapper)", 0); - __pyx_r = __pyx_pf_9_splitter_8Splitter_12max_features___get__(((struct __pyx_obj_9_splitter_Splitter *)__pyx_v_self)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features___get__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_9_splitter_8Splitter_12max_features___get__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features___get__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self) { PyObject *__pyx_r = NULL; 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/*proto*/ +static int __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features_3__set__(PyObject *__pyx_v_self, PyObject *__pyx_v_value) { int __pyx_r; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__set__ (wrapper)", 0); - __pyx_r = __pyx_pf_9_splitter_8Splitter_12max_features_2__set__(((struct __pyx_obj_9_splitter_Splitter *)__pyx_v_self), ((PyObject *)__pyx_v_value)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features_2__set__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_self), ((PyObject *)__pyx_v_value)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static int __pyx_pf_9_splitter_8Splitter_12max_features_2__set__(struct __pyx_obj_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value) { +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_self, PyObject *__pyx_v_value) { int __pyx_r; 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+ __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_total_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_partition_end; int __pyx_r; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_t_3; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_t_3; double __pyx_t_4; int __pyx_t_5; int __pyx_t_6; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_8; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_7; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_8; Py_ssize_t __pyx_t_9; Py_ssize_t __pyx_t_10; int __pyx_t_11; @@ -5676,7 +5490,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "_splitter.pyx":262 + /* "stpredictions/models/OK3/_splitter.pyx":262 * """ * # Find the best split * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< @@ -5686,7 +5500,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.samples; __pyx_v_samples = __pyx_t_1; - /* "_splitter.pyx":263 + /* "stpredictions/models/OK3/_splitter.pyx":263 * # Find the best split * cdef SIZE_t* samples = self.samples * cdef SIZE_t start = self.start # <<<<<<<<<<<<<< @@ -5696,7 +5510,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.start; __pyx_v_start = __pyx_t_2; - /* "_splitter.pyx":264 + /* "stpredictions/models/OK3/_splitter.pyx":264 * cdef SIZE_t* samples = self.samples * cdef SIZE_t start = self.start * cdef SIZE_t end = self.end # <<<<<<<<<<<<<< @@ -5706,7 +5520,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end; __pyx_v_end = __pyx_t_2; - /* "_splitter.pyx":266 + /* "stpredictions/models/OK3/_splitter.pyx":266 * cdef SIZE_t end = self.end * * cdef SIZE_t* features = self.features # <<<<<<<<<<<<<< @@ -5716,7 +5530,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.features; __pyx_v_features = __pyx_t_1; - /* "_splitter.pyx":267 + /* "stpredictions/models/OK3/_splitter.pyx":267 * * cdef SIZE_t* features = self.features * cdef SIZE_t* constant_features = self.constant_features # <<<<<<<<<<<<<< @@ -5726,7 +5540,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.constant_features; __pyx_v_constant_features = __pyx_t_1; - /* "_splitter.pyx":268 + /* "stpredictions/models/OK3/_splitter.pyx":268 * cdef SIZE_t* features = self.features * cdef SIZE_t* constant_features = self.constant_features * cdef SIZE_t n_features = self.n_features # <<<<<<<<<<<<<< @@ -5736,7 +5550,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_features; __pyx_v_n_features = __pyx_t_2; - /* "_splitter.pyx":270 + /* "stpredictions/models/OK3/_splitter.pyx":270 * cdef SIZE_t n_features = self.n_features * * cdef DTYPE_t* Xf = self.feature_values # <<<<<<<<<<<<<< @@ -5746,7 +5560,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.feature_values; __pyx_v_Xf = __pyx_t_3; - /* "_splitter.pyx":271 + /* "stpredictions/models/OK3/_splitter.pyx":271 * * cdef DTYPE_t* Xf = self.feature_values * cdef SIZE_t max_features = self.max_features # <<<<<<<<<<<<<< @@ -5756,7 +5570,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features; __pyx_v_max_features = __pyx_t_2; - /* "_splitter.pyx":272 + /* "stpredictions/models/OK3/_splitter.pyx":272 * cdef DTYPE_t* Xf = self.feature_values * cdef SIZE_t max_features = self.max_features * cdef SIZE_t min_samples_leaf = self.min_samples_leaf # <<<<<<<<<<<<<< @@ -5766,7 +5580,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf; __pyx_v_min_samples_leaf = __pyx_t_2; - /* "_splitter.pyx":273 + /* "stpredictions/models/OK3/_splitter.pyx":273 * cdef SIZE_t max_features = self.max_features * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< @@ -5776,7 +5590,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf; __pyx_v_min_weight_leaf = __pyx_t_4; - /* "_splitter.pyx":274 + /* "stpredictions/models/OK3/_splitter.pyx":274 * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf * cdef UINT32_t* random_state = &self.rand_r_state # <<<<<<<<<<<<<< @@ -5785,25 +5599,25 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state); - /* "_splitter.pyx":277 + /* "stpredictions/models/OK3/_splitter.pyx":277 * * cdef SplitRecord best, current * cdef double current_proxy_improvement = -INFINITY # <<<<<<<<<<<<<< * cdef double best_proxy_improvement = -INFINITY * */ - __pyx_v_current_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + __pyx_v_current_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - /* "_splitter.pyx":278 + /* "stpredictions/models/OK3/_splitter.pyx":278 * cdef SplitRecord best, current * cdef double current_proxy_improvement = -INFINITY * cdef double best_proxy_improvement = -INFINITY # <<<<<<<<<<<<<< * * cdef SIZE_t f_i = n_features */ - __pyx_v_best_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + __pyx_v_best_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - /* "_splitter.pyx":280 + /* "stpredictions/models/OK3/_splitter.pyx":280 * cdef double best_proxy_improvement = -INFINITY * * cdef SIZE_t f_i = n_features # <<<<<<<<<<<<<< @@ -5812,7 +5626,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_f_i = __pyx_v_n_features; - /* "_splitter.pyx":288 + /* "stpredictions/models/OK3/_splitter.pyx":288 * cdef SIZE_t j * * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< @@ -5821,7 +5635,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_n_visited_features = 0; - /* "_splitter.pyx":290 + /* "stpredictions/models/OK3/_splitter.pyx":290 * cdef SIZE_t n_visited_features = 0 * # Number of features discovered to be constant during the split search * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< @@ -5830,7 +5644,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_n_found_constants = 0; - /* "_splitter.pyx":292 + /* "stpredictions/models/OK3/_splitter.pyx":292 * cdef SIZE_t n_found_constants = 0 * # Number of features known to be constant and drawn without replacement * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< @@ -5839,7 +5653,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_n_drawn_constants = 0; - /* "_splitter.pyx":293 + /* "stpredictions/models/OK3/_splitter.pyx":293 * # Number of features known to be constant and drawn without replacement * cdef SIZE_t n_drawn_constants = 0 * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< @@ -5848,7 +5662,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); - /* "_splitter.pyx":295 + /* "stpredictions/models/OK3/_splitter.pyx":295 * cdef SIZE_t n_known_constants = n_constant_features[0] * # n_total_constants = n_known_constants + n_found_constants * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< @@ -5857,16 +5671,16 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_n_total_constants = __pyx_v_n_known_constants; - /* "_splitter.pyx":299 + /* "stpredictions/models/OK3/_splitter.pyx":299 * cdef SIZE_t partition_end * * _init_split(&best, end) # <<<<<<<<<<<<<< * * # Sample up to max_features without replacement using a */ - __pyx_f_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); + __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); - /* "_splitter.pyx":310 + /* "stpredictions/models/OK3/_splitter.pyx":310 * # newly discovered constant features to spare computation on descendant * # nodes. * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< @@ -5881,7 +5695,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split goto __pyx_L5_bool_binop_done; } - /* "_splitter.pyx":312 + /* "stpredictions/models/OK3/_splitter.pyx":312 * while (f_i > n_total_constants and # Stop early if remaining features * # are constant * (n_visited_features < max_features or # <<<<<<<<<<<<<< @@ -5895,7 +5709,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split goto __pyx_L5_bool_binop_done; } - /* "_splitter.pyx":314 + /* "stpredictions/models/OK3/_splitter.pyx":314 * (n_visited_features < max_features or * # At least one drawn features must be non constant * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< @@ -5907,7 +5721,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_L5_bool_binop_done:; if (!__pyx_t_5) break; - /* "_splitter.pyx":316 + /* "stpredictions/models/OK3/_splitter.pyx":316 * n_visited_features <= n_found_constants + n_drawn_constants)): * * n_visited_features += 1 # <<<<<<<<<<<<<< @@ -5916,16 +5730,16 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); - /* "_splitter.pyx":330 + /* "stpredictions/models/OK3/_splitter.pyx":330 * * # Draw a feature at random * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< * random_state) * */ - __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); + __pyx_v_f_j = __pyx_f_13stpredictions_6models_3OK3_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); - /* "_splitter.pyx":333 + /* "stpredictions/models/OK3/_splitter.pyx":333 * random_state) * * if f_j < n_known_constants: # <<<<<<<<<<<<<< @@ -5935,7 +5749,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_5 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":335 + /* "stpredictions/models/OK3/_splitter.pyx":335 * if f_j < n_known_constants: * # f_j in the interval [n_drawn_constants, n_known_constants[ * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] # <<<<<<<<<<<<<< @@ -5947,7 +5761,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_2; (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; - /* "_splitter.pyx":337 + /* "stpredictions/models/OK3/_splitter.pyx":337 * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] * * n_drawn_constants += 1 # <<<<<<<<<<<<<< @@ -5956,7 +5770,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); - /* "_splitter.pyx":333 + /* "stpredictions/models/OK3/_splitter.pyx":333 * random_state) * * if f_j < n_known_constants: # <<<<<<<<<<<<<< @@ -5966,7 +5780,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split goto __pyx_L8; } - /* "_splitter.pyx":341 + /* "stpredictions/models/OK3/_splitter.pyx":341 * else: * # f_j in the interval [n_known_constants, f_i - n_found_constants[ * f_j += n_found_constants # <<<<<<<<<<<<<< @@ -5976,7 +5790,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split /*else*/ { __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); - /* "_splitter.pyx":343 + /* "stpredictions/models/OK3/_splitter.pyx":343 * f_j += n_found_constants * # f_j in the interval [n_total_constants, f_i[ * current.feature = features[f_j] # <<<<<<<<<<<<<< @@ -5985,7 +5799,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); - /* "_splitter.pyx":349 + /* "stpredictions/models/OK3/_splitter.pyx":349 * # sorting the array in a manner which utilizes the cache more * # effectively. * for i in range(start, end): # <<<<<<<<<<<<<< @@ -5997,7 +5811,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split for (__pyx_t_8 = __pyx_v_start; __pyx_t_8 < __pyx_t_2; __pyx_t_8+=1) { __pyx_v_i = __pyx_t_8; - /* "_splitter.pyx":350 + /* "stpredictions/models/OK3/_splitter.pyx":350 * # effectively. * for i in range(start, end): * Xf[i] = self.X[samples[i], current.feature] # <<<<<<<<<<<<<< @@ -6007,29 +5821,29 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 350, __pyx_L1_error)} __pyx_t_9 = (__pyx_v_samples[__pyx_v_i]); __pyx_t_10 = __pyx_v_current.feature; - (__pyx_v_Xf[__pyx_v_i]) = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_10 * __pyx_v_self->__pyx_base.X.strides[1]) ))); + (__pyx_v_Xf[__pyx_v_i]) = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_10 * __pyx_v_self->__pyx_base.X.strides[1]) ))); } - /* "_splitter.pyx":352 + /* "stpredictions/models/OK3/_splitter.pyx":352 * Xf[i] = self.X[samples[i], current.feature] * * sort(Xf + start, samples + start, end - start) # <<<<<<<<<<<<<< * * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: */ - __pyx_f_9_splitter_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end - __pyx_v_start)); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end - __pyx_v_start)); - /* "_splitter.pyx":354 + /* "stpredictions/models/OK3/_splitter.pyx":354 * sort(Xf + start, samples + start, end - start) * * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] * */ - __pyx_t_5 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + __pyx_t_5 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":355 + /* "stpredictions/models/OK3/_splitter.pyx":355 * * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] # <<<<<<<<<<<<<< @@ -6041,7 +5855,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2; - /* "_splitter.pyx":357 + /* "stpredictions/models/OK3/_splitter.pyx":357 * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] * * n_found_constants += 1 # <<<<<<<<<<<<<< @@ -6050,7 +5864,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); - /* "_splitter.pyx":358 + /* "stpredictions/models/OK3/_splitter.pyx":358 * * n_found_constants += 1 * n_total_constants += 1 # <<<<<<<<<<<<<< @@ -6059,7 +5873,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); - /* "_splitter.pyx":354 + /* "stpredictions/models/OK3/_splitter.pyx":354 * sort(Xf + start, samples + start, end - start) * * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< @@ -6069,7 +5883,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split goto __pyx_L11; } - /* "_splitter.pyx":361 + /* "stpredictions/models/OK3/_splitter.pyx":361 * * else: * f_i -= 1 # <<<<<<<<<<<<<< @@ -6079,7 +5893,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split /*else*/ { __pyx_v_f_i = (__pyx_v_f_i - 1); - /* "_splitter.pyx":362 + /* "stpredictions/models/OK3/_splitter.pyx":362 * else: * f_i -= 1 * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< @@ -6091,16 +5905,16 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2; (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; - /* "_splitter.pyx":365 + /* "stpredictions/models/OK3/_splitter.pyx":365 * * # Evaluate all splits * self.criterion.reset() # <<<<<<<<<<<<<< * p = start * */ - __pyx_t_11 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 365, __pyx_L1_error) + __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 365, __pyx_L1_error) - /* "_splitter.pyx":366 + /* "stpredictions/models/OK3/_splitter.pyx":366 * # Evaluate all splits * self.criterion.reset() * p = start # <<<<<<<<<<<<<< @@ -6109,7 +5923,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_p = __pyx_v_start; - /* "_splitter.pyx":368 + /* "stpredictions/models/OK3/_splitter.pyx":368 * p = start * * while p < end: # <<<<<<<<<<<<<< @@ -6120,7 +5934,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_5 = ((__pyx_v_p < __pyx_v_end) != 0); if (!__pyx_t_5) break; - /* "_splitter.pyx":369 + /* "stpredictions/models/OK3/_splitter.pyx":369 * * while p < end: * while (p + 1 < end and # <<<<<<<<<<<<<< @@ -6135,19 +5949,19 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split goto __pyx_L16_bool_binop_done; } - /* "_splitter.pyx":370 + /* "stpredictions/models/OK3/_splitter.pyx":370 * while p < end: * while (p + 1 < end and * Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): # <<<<<<<<<<<<<< * p += 1 * */ - __pyx_t_6 = (((__pyx_v_Xf[(__pyx_v_p + 1)]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + __pyx_t_6 = (((__pyx_v_Xf[(__pyx_v_p + 1)]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); __pyx_t_5 = __pyx_t_6; __pyx_L16_bool_binop_done:; if (!__pyx_t_5) break; - /* "_splitter.pyx":371 + /* "stpredictions/models/OK3/_splitter.pyx":371 * while (p + 1 < end and * Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD): * p += 1 # <<<<<<<<<<<<<< @@ -6157,7 +5971,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_v_p = (__pyx_v_p + 1); } - /* "_splitter.pyx":375 + /* "stpredictions/models/OK3/_splitter.pyx":375 * # (p + 1 >= end) or (X[samples[p + 1], current.feature] > * # X[samples[p], current.feature]) * p += 1 # <<<<<<<<<<<<<< @@ -6166,7 +5980,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_p = (__pyx_v_p + 1); - /* "_splitter.pyx":379 + /* "stpredictions/models/OK3/_splitter.pyx":379 * # X[samples[p - 1], current.feature]) * * if p < end: # <<<<<<<<<<<<<< @@ -6176,7 +5990,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_5 = ((__pyx_v_p < __pyx_v_end) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":380 + /* "stpredictions/models/OK3/_splitter.pyx":380 * * if p < end: * current.pos = p # <<<<<<<<<<<<<< @@ -6185,7 +5999,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_current.pos = __pyx_v_p; - /* "_splitter.pyx":383 + /* "stpredictions/models/OK3/_splitter.pyx":383 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -6199,7 +6013,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split goto __pyx_L20_bool_binop_done; } - /* "_splitter.pyx":384 + /* "stpredictions/models/OK3/_splitter.pyx":384 * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or * ((end - current.pos) < min_samples_leaf)): # <<<<<<<<<<<<<< @@ -6210,7 +6024,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_5 = __pyx_t_6; __pyx_L20_bool_binop_done:; - /* "_splitter.pyx":383 + /* "stpredictions/models/OK3/_splitter.pyx":383 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -6219,7 +6033,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ if (__pyx_t_5) { - /* "_splitter.pyx":385 + /* "stpredictions/models/OK3/_splitter.pyx":385 * if (((current.pos - start) < min_samples_leaf) or * ((end - current.pos) < min_samples_leaf)): * continue # <<<<<<<<<<<<<< @@ -6228,7 +6042,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ goto __pyx_L12_continue; - /* "_splitter.pyx":383 + /* "stpredictions/models/OK3/_splitter.pyx":383 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -6237,16 +6051,16 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ } - /* "_splitter.pyx":387 + /* "stpredictions/models/OK3/_splitter.pyx":387 * continue * * self.criterion.update(current.pos) # <<<<<<<<<<<<<< * * # Reject if min_weight_leaf is not satisfied */ - __pyx_t_11 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 387, __pyx_L1_error) + __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 387, __pyx_L1_error) - /* "_splitter.pyx":390 + /* "stpredictions/models/OK3/_splitter.pyx":390 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -6260,7 +6074,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split goto __pyx_L23_bool_binop_done; } - /* "_splitter.pyx":391 + /* "stpredictions/models/OK3/_splitter.pyx":391 * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or * (self.criterion.weighted_n_right < min_weight_leaf)): # <<<<<<<<<<<<<< @@ -6271,7 +6085,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_5 = __pyx_t_6; __pyx_L23_bool_binop_done:; - /* "_splitter.pyx":390 + /* "stpredictions/models/OK3/_splitter.pyx":390 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -6280,7 +6094,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ if (__pyx_t_5) { - /* "_splitter.pyx":392 + /* "stpredictions/models/OK3/_splitter.pyx":392 * if ((self.criterion.weighted_n_left < min_weight_leaf) or * (self.criterion.weighted_n_right < min_weight_leaf)): * continue # <<<<<<<<<<<<<< @@ -6289,7 +6103,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ goto __pyx_L12_continue; - /* "_splitter.pyx":390 + /* "stpredictions/models/OK3/_splitter.pyx":390 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -6298,16 +6112,16 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ } - /* "_splitter.pyx":394 + /* "stpredictions/models/OK3/_splitter.pyx":394 * continue * * current_proxy_improvement = self.criterion.proxy_impurity_improvement() # <<<<<<<<<<<<<< * * # with gil: */ - __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); + __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); - /* "_splitter.pyx":402 + /* "stpredictions/models/OK3/_splitter.pyx":402 * # print() * * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< @@ -6317,7 +6131,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_5 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":403 + /* "stpredictions/models/OK3/_splitter.pyx":403 * * if current_proxy_improvement > best_proxy_improvement: * best_proxy_improvement = current_proxy_improvement # <<<<<<<<<<<<<< @@ -6326,7 +6140,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement; - /* "_splitter.pyx":405 + /* "stpredictions/models/OK3/_splitter.pyx":405 * best_proxy_improvement = current_proxy_improvement * # sum of halves is used to avoid infinite value * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 # <<<<<<<<<<<<<< @@ -6335,7 +6149,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_current.threshold = (((__pyx_v_Xf[(__pyx_v_p - 1)]) / 2.0) + ((__pyx_v_Xf[__pyx_v_p]) / 2.0)); - /* "_splitter.pyx":407 + /* "stpredictions/models/OK3/_splitter.pyx":407 * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 * * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< @@ -6349,32 +6163,32 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split goto __pyx_L27_bool_binop_done; } - /* "_splitter.pyx":408 + /* "stpredictions/models/OK3/_splitter.pyx":408 * * if ((current.threshold == Xf[p]) or * (current.threshold == INFINITY) or # <<<<<<<<<<<<<< * (current.threshold == -INFINITY)): * current.threshold = Xf[p - 1] */ - __pyx_t_6 = ((__pyx_v_current.threshold == __pyx_v_9_splitter_INFINITY) != 0); + __pyx_t_6 = ((__pyx_v_current.threshold == __pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY) != 0); if (!__pyx_t_6) { } else { __pyx_t_5 = __pyx_t_6; goto __pyx_L27_bool_binop_done; } - /* "_splitter.pyx":409 + /* "stpredictions/models/OK3/_splitter.pyx":409 * if ((current.threshold == Xf[p]) or * (current.threshold == INFINITY) or * (current.threshold == -INFINITY)): # <<<<<<<<<<<<<< * current.threshold = Xf[p - 1] * */ - __pyx_t_6 = ((__pyx_v_current.threshold == (-__pyx_v_9_splitter_INFINITY)) != 0); + __pyx_t_6 = ((__pyx_v_current.threshold == (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY)) != 0); __pyx_t_5 = __pyx_t_6; __pyx_L27_bool_binop_done:; - /* "_splitter.pyx":407 + /* "stpredictions/models/OK3/_splitter.pyx":407 * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 * * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< @@ -6383,7 +6197,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ if (__pyx_t_5) { - /* "_splitter.pyx":410 + /* "stpredictions/models/OK3/_splitter.pyx":410 * (current.threshold == INFINITY) or * (current.threshold == -INFINITY)): * current.threshold = Xf[p - 1] # <<<<<<<<<<<<<< @@ -6392,7 +6206,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_current.threshold = (__pyx_v_Xf[(__pyx_v_p - 1)]); - /* "_splitter.pyx":407 + /* "stpredictions/models/OK3/_splitter.pyx":407 * current.threshold = Xf[p - 1] / 2.0 + Xf[p] / 2.0 * * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< @@ -6401,7 +6215,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ } - /* "_splitter.pyx":412 + /* "stpredictions/models/OK3/_splitter.pyx":412 * current.threshold = Xf[p - 1] * * best = current # copy # <<<<<<<<<<<<<< @@ -6410,7 +6224,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_best = __pyx_v_current; - /* "_splitter.pyx":402 + /* "stpredictions/models/OK3/_splitter.pyx":402 * # print() * * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< @@ -6419,7 +6233,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ } - /* "_splitter.pyx":379 + /* "stpredictions/models/OK3/_splitter.pyx":379 * # X[samples[p - 1], current.feature]) * * if p < end: # <<<<<<<<<<<<<< @@ -6435,7 +6249,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_L8:; } - /* "_splitter.pyx":415 + /* "stpredictions/models/OK3/_splitter.pyx":415 * * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: # <<<<<<<<<<<<<< @@ -6445,7 +6259,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_5 = ((__pyx_v_best.pos < __pyx_v_end) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":416 + /* "stpredictions/models/OK3/_splitter.pyx":416 * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: * partition_end = end # <<<<<<<<<<<<<< @@ -6454,7 +6268,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_partition_end = __pyx_v_end; - /* "_splitter.pyx":417 + /* "stpredictions/models/OK3/_splitter.pyx":417 * if best.pos < end: * partition_end = end * p = start # <<<<<<<<<<<<<< @@ -6463,7 +6277,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_p = __pyx_v_start; - /* "_splitter.pyx":419 + /* "stpredictions/models/OK3/_splitter.pyx":419 * p = start * * while p < partition_end: # <<<<<<<<<<<<<< @@ -6474,7 +6288,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0); if (!__pyx_t_5) break; - /* "_splitter.pyx":420 + /* "stpredictions/models/OK3/_splitter.pyx":420 * * while p < partition_end: * if self.X[samples[p], best.feature] <= best.threshold: # <<<<<<<<<<<<<< @@ -6484,10 +6298,10 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 420, __pyx_L1_error)} __pyx_t_10 = (__pyx_v_samples[__pyx_v_p]); __pyx_t_9 = __pyx_v_best.feature; - __pyx_t_5 = (((*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_10 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))) <= __pyx_v_best.threshold) != 0); + __pyx_t_5 = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_10 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))) <= __pyx_v_best.threshold) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":421 + /* "stpredictions/models/OK3/_splitter.pyx":421 * while p < partition_end: * if self.X[samples[p], best.feature] <= best.threshold: * p += 1 # <<<<<<<<<<<<<< @@ -6496,7 +6310,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ __pyx_v_p = (__pyx_v_p + 1); - /* "_splitter.pyx":420 + /* "stpredictions/models/OK3/_splitter.pyx":420 * * while p < partition_end: * if self.X[samples[p], best.feature] <= best.threshold: # <<<<<<<<<<<<<< @@ -6506,7 +6320,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split goto __pyx_L33; } - /* "_splitter.pyx":424 + /* "stpredictions/models/OK3/_splitter.pyx":424 * * else: * partition_end -= 1 # <<<<<<<<<<<<<< @@ -6516,7 +6330,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split /*else*/ { __pyx_v_partition_end = (__pyx_v_partition_end - 1); - /* "_splitter.pyx":426 + /* "stpredictions/models/OK3/_splitter.pyx":426 * partition_end -= 1 * * samples[p], samples[partition_end] = samples[partition_end], samples[p] # <<<<<<<<<<<<<< @@ -6531,43 +6345,43 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_L33:; } - /* "_splitter.pyx":428 + /* "stpredictions/models/OK3/_splitter.pyx":428 * samples[p], samples[partition_end] = samples[partition_end], samples[p] * * self.criterion.reset() # <<<<<<<<<<<<<< * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) */ - __pyx_t_11 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 428, __pyx_L1_error) + __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 428, __pyx_L1_error) - /* "_splitter.pyx":429 + /* "stpredictions/models/OK3/_splitter.pyx":429 * * self.criterion.reset() * self.criterion.update(best.pos) # <<<<<<<<<<<<<< * best.improvement = self.criterion.impurity_improvement(impurity) * self.criterion.children_impurity(&best.impurity_left, */ - __pyx_t_11 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 429, __pyx_L1_error) + __pyx_t_11 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_11 == ((int)-1))) __PYX_ERR(0, 429, __pyx_L1_error) - /* "_splitter.pyx":430 + /* "stpredictions/models/OK3/_splitter.pyx":430 * self.criterion.reset() * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) # <<<<<<<<<<<<<< * self.criterion.children_impurity(&best.impurity_left, * &best.impurity_right) */ - __pyx_v_best.improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); + __pyx_v_best.improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); - /* "_splitter.pyx":431 + /* "stpredictions/models/OK3/_splitter.pyx":431 * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) * self.criterion.children_impurity(&best.impurity_left, # <<<<<<<<<<<<<< * &best.impurity_right) * */ - ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); - /* "_splitter.pyx":415 + /* "stpredictions/models/OK3/_splitter.pyx":415 * * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: # <<<<<<<<<<<<<< @@ -6576,25 +6390,25 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ } - /* "_splitter.pyx":437 + /* "stpredictions/models/OK3/_splitter.pyx":437 * # element in features[:n_known_constants] must be preserved for sibling * # and child nodes * memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) # <<<<<<<<<<<<<< * * # Copy newly found constant features */ - (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants))); + (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)) * __pyx_v_n_known_constants))); - /* "_splitter.pyx":440 + /* "stpredictions/models/OK3/_splitter.pyx":440 * * # Copy newly found constant features * memcpy(constant_features + n_known_constants, # <<<<<<<<<<<<<< * features + n_known_constants, * sizeof(SIZE_t) * n_found_constants) */ - (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants))); + (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)) * __pyx_v_n_found_constants))); - /* "_splitter.pyx":445 + /* "stpredictions/models/OK3/_splitter.pyx":445 * * # Return values * split[0] = best # <<<<<<<<<<<<<< @@ -6603,7 +6417,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ (__pyx_v_split[0]) = __pyx_v_best; - /* "_splitter.pyx":446 + /* "stpredictions/models/OK3/_splitter.pyx":446 * # Return values * split[0] = best * n_constant_features[0] = n_total_constants # <<<<<<<<<<<<<< @@ -6612,7 +6426,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split */ (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants; - /* "_splitter.pyx":447 + /* "stpredictions/models/OK3/_splitter.pyx":447 * split[0] = best * n_constant_features[0] = n_total_constants * return 0 # <<<<<<<<<<<<<< @@ -6622,7 +6436,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split __pyx_r = 0; goto __pyx_L0; - /* "_splitter.pyx":254 + /* "stpredictions/models/OK3/_splitter.pyx":254 * self.random_state), self.__getstate__()) * * cdef int node_split(self, double impurity, SplitRecord* split, # <<<<<<<<<<<<<< @@ -6636,7 +6450,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif - __Pyx_AddTraceback("_splitter.BestSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.BestSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif @@ -6646,7 +6460,7 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split return __pyx_r; } -/* "_splitter.pyx":452 +/* "stpredictions/models/OK3/_splitter.pyx":452 * # Sort n-element arrays pointed to by Xf and samples, simultaneously, * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: # <<<<<<<<<<<<<< @@ -6654,11 +6468,11 @@ static int __pyx_f_9_splitter_12BestSplitter_node_split(struct __pyx_obj_9_split * return */ -static CYTHON_INLINE void __pyx_f_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) { +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n) { int __pyx_v_maxd; int __pyx_t_1; - /* "_splitter.pyx":453 + /* "stpredictions/models/OK3/_splitter.pyx":453 * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: * if n == 0: # <<<<<<<<<<<<<< @@ -6668,7 +6482,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_ __pyx_t_1 = ((__pyx_v_n == 0) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":454 + /* "stpredictions/models/OK3/_splitter.pyx":454 * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: * if n == 0: * return # <<<<<<<<<<<<<< @@ -6677,7 +6491,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_ */ goto __pyx_L0; - /* "_splitter.pyx":453 + /* "stpredictions/models/OK3/_splitter.pyx":453 * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: * if n == 0: # <<<<<<<<<<<<<< @@ -6686,25 +6500,25 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_ */ } - /* "_splitter.pyx":455 + /* "stpredictions/models/OK3/_splitter.pyx":455 * if n == 0: * return * cdef int maxd = 2 * log(n) # <<<<<<<<<<<<<< * introsort(Xf, samples, n, maxd) * */ - __pyx_v_maxd = (2 * ((int)__pyx_f_7sklearn_4tree_6_utils_log(__pyx_v_n))); + __pyx_v_maxd = (2 * ((int)__pyx_f_13stpredictions_6models_3OK3_6_utils_log(__pyx_v_n))); - /* "_splitter.pyx":456 + /* "stpredictions/models/OK3/_splitter.pyx":456 * return * cdef int maxd = 2 * log(n) * introsort(Xf, samples, n, maxd) # <<<<<<<<<<<<<< * * */ - __pyx_f_9_splitter_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n, __pyx_v_maxd); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n, __pyx_v_maxd); - /* "_splitter.pyx":452 + /* "stpredictions/models/OK3/_splitter.pyx":452 * # Sort n-element arrays pointed to by Xf and samples, simultaneously, * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997). * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: # <<<<<<<<<<<<<< @@ -6716,7 +6530,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_ __pyx_L0:; } -/* "_splitter.pyx":459 +/* "stpredictions/models/OK3/_splitter.pyx":459 * * * cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< @@ -6724,13 +6538,13 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sort(__pyx_t_7sklearn_4tree_5_tree_ * # Helper for sort */ -static CYTHON_INLINE void __pyx_f_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j) { - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_3; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4; +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_i, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_j) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_3; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_4; - /* "_splitter.pyx":462 + /* "stpredictions/models/OK3/_splitter.pyx":462 * SIZE_t i, SIZE_t j) nogil: * # Helper for sort * Xf[i], Xf[j] = Xf[j], Xf[i] # <<<<<<<<<<<<<< @@ -6742,7 +6556,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_ (__pyx_v_Xf[__pyx_v_i]) = __pyx_t_1; (__pyx_v_Xf[__pyx_v_j]) = __pyx_t_2; - /* "_splitter.pyx":463 + /* "stpredictions/models/OK3/_splitter.pyx":463 * # Helper for sort * Xf[i], Xf[j] = Xf[j], Xf[i] * samples[i], samples[j] = samples[j], samples[i] # <<<<<<<<<<<<<< @@ -6754,7 +6568,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_ (__pyx_v_samples[__pyx_v_i]) = __pyx_t_3; (__pyx_v_samples[__pyx_v_j]) = __pyx_t_4; - /* "_splitter.pyx":459 + /* "stpredictions/models/OK3/_splitter.pyx":459 * * * cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< @@ -6765,7 +6579,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_ /* function exit code */ } -/* "_splitter.pyx":466 +/* "stpredictions/models/OK3/_splitter.pyx":466 * * * cdef inline DTYPE_t median3(DTYPE_t* Xf, SIZE_t n) nogil: # <<<<<<<<<<<<<< @@ -6773,14 +6587,14 @@ static CYTHON_INLINE void __pyx_f_9_splitter_swap(__pyx_t_7sklearn_4tree_5_tree_ * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. */ -static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_median3(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) { - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_a; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_b; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_c; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_r; +static CYTHON_INLINE __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_median3(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_a; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_b; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_c; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_r; int __pyx_t_1; - /* "_splitter.pyx":469 + /* "stpredictions/models/OK3/_splitter.pyx":469 * # Median of three pivot selection, after Bentley and McIlroy (1993). * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] # <<<<<<<<<<<<<< @@ -6791,7 +6605,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me __pyx_v_b = (__pyx_v_Xf[(__pyx_v_n / 2)]); __pyx_v_c = (__pyx_v_Xf[(__pyx_v_n - 1)]); - /* "_splitter.pyx":470 + /* "stpredictions/models/OK3/_splitter.pyx":470 * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] * if a < b: # <<<<<<<<<<<<<< @@ -6801,7 +6615,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me __pyx_t_1 = ((__pyx_v_a < __pyx_v_b) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":471 + /* "stpredictions/models/OK3/_splitter.pyx":471 * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] * if a < b: * if b < c: # <<<<<<<<<<<<<< @@ -6811,7 +6625,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me __pyx_t_1 = ((__pyx_v_b < __pyx_v_c) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":472 + /* "stpredictions/models/OK3/_splitter.pyx":472 * if a < b: * if b < c: * return b # <<<<<<<<<<<<<< @@ -6821,7 +6635,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me __pyx_r = __pyx_v_b; goto __pyx_L0; - /* "_splitter.pyx":471 + /* "stpredictions/models/OK3/_splitter.pyx":471 * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] * if a < b: * if b < c: # <<<<<<<<<<<<<< @@ -6830,7 +6644,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me */ } - /* "_splitter.pyx":473 + /* "stpredictions/models/OK3/_splitter.pyx":473 * if b < c: * return b * elif a < c: # <<<<<<<<<<<<<< @@ -6840,7 +6654,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me __pyx_t_1 = ((__pyx_v_a < __pyx_v_c) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":474 + /* "stpredictions/models/OK3/_splitter.pyx":474 * return b * elif a < c: * return c # <<<<<<<<<<<<<< @@ -6850,7 +6664,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me __pyx_r = __pyx_v_c; goto __pyx_L0; - /* "_splitter.pyx":473 + /* "stpredictions/models/OK3/_splitter.pyx":473 * if b < c: * return b * elif a < c: # <<<<<<<<<<<<<< @@ -6859,7 +6673,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me */ } - /* "_splitter.pyx":476 + /* "stpredictions/models/OK3/_splitter.pyx":476 * return c * else: * return a # <<<<<<<<<<<<<< @@ -6871,7 +6685,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me goto __pyx_L0; } - /* "_splitter.pyx":470 + /* "stpredictions/models/OK3/_splitter.pyx":470 * # Engineering a sort function. SP&E. Requires 8/3 comparisons on average. * cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1] * if a < b: # <<<<<<<<<<<<<< @@ -6880,7 +6694,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me */ } - /* "_splitter.pyx":477 + /* "stpredictions/models/OK3/_splitter.pyx":477 * else: * return a * elif b < c: # <<<<<<<<<<<<<< @@ -6890,7 +6704,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me __pyx_t_1 = ((__pyx_v_b < __pyx_v_c) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":478 + /* "stpredictions/models/OK3/_splitter.pyx":478 * return a * elif b < c: * if a < c: # <<<<<<<<<<<<<< @@ -6900,7 +6714,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me __pyx_t_1 = ((__pyx_v_a < __pyx_v_c) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":479 + /* "stpredictions/models/OK3/_splitter.pyx":479 * elif b < c: * if a < c: * return a # <<<<<<<<<<<<<< @@ -6910,7 +6724,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me __pyx_r = __pyx_v_a; goto __pyx_L0; - /* "_splitter.pyx":478 + /* "stpredictions/models/OK3/_splitter.pyx":478 * return a * elif b < c: * if a < c: # <<<<<<<<<<<<<< @@ -6919,7 +6733,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me */ } - /* "_splitter.pyx":481 + /* "stpredictions/models/OK3/_splitter.pyx":481 * return a * else: * return c # <<<<<<<<<<<<<< @@ -6931,7 +6745,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me goto __pyx_L0; } - /* "_splitter.pyx":477 + /* "stpredictions/models/OK3/_splitter.pyx":477 * else: * return a * elif b < c: # <<<<<<<<<<<<<< @@ -6940,7 +6754,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me */ } - /* "_splitter.pyx":483 + /* "stpredictions/models/OK3/_splitter.pyx":483 * return c * else: * return b # <<<<<<<<<<<<<< @@ -6952,7 +6766,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me goto __pyx_L0; } - /* "_splitter.pyx":466 + /* "stpredictions/models/OK3/_splitter.pyx":466 * * * cdef inline DTYPE_t median3(DTYPE_t* Xf, SIZE_t n) nogil: # <<<<<<<<<<<<<< @@ -6965,7 +6779,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me return __pyx_r; } -/* "_splitter.pyx":488 +/* "stpredictions/models/OK3/_splitter.pyx":488 * # Introsort with median of 3 pivot selection and 3-way partition function * # (robust to repeated elements, e.g. lots of zero features). * cdef void introsort(DTYPE_t* Xf, SIZE_t *samples, # <<<<<<<<<<<<<< @@ -6973,14 +6787,14 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_9_splitter_me * cdef DTYPE_t pivot */ -static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n, int __pyx_v_maxd) { - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_pivot; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_l; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_r; +static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n, int __pyx_v_maxd) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_pivot; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_i; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_l; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_r; int __pyx_t_1; - /* "_splitter.pyx":493 + /* "stpredictions/models/OK3/_splitter.pyx":493 * cdef SIZE_t i, l, r * * while n > 1: # <<<<<<<<<<<<<< @@ -6991,7 +6805,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * __pyx_t_1 = ((__pyx_v_n > 1) != 0); if (!__pyx_t_1) break; - /* "_splitter.pyx":494 + /* "stpredictions/models/OK3/_splitter.pyx":494 * * while n > 1: * if maxd <= 0: # max depth limit exceeded ("gone quadratic") # <<<<<<<<<<<<<< @@ -7001,16 +6815,16 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * __pyx_t_1 = ((__pyx_v_maxd <= 0) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":495 + /* "stpredictions/models/OK3/_splitter.pyx":495 * while n > 1: * if maxd <= 0: # max depth limit exceeded ("gone quadratic") * heapsort(Xf, samples, n) # <<<<<<<<<<<<<< * return * maxd -= 1 */ - __pyx_f_9_splitter_heapsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_heapsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n); - /* "_splitter.pyx":496 + /* "stpredictions/models/OK3/_splitter.pyx":496 * if maxd <= 0: # max depth limit exceeded ("gone quadratic") * heapsort(Xf, samples, n) * return # <<<<<<<<<<<<<< @@ -7019,7 +6833,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * */ goto __pyx_L0; - /* "_splitter.pyx":494 + /* "stpredictions/models/OK3/_splitter.pyx":494 * * while n > 1: * if maxd <= 0: # max depth limit exceeded ("gone quadratic") # <<<<<<<<<<<<<< @@ -7028,7 +6842,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * */ } - /* "_splitter.pyx":497 + /* "stpredictions/models/OK3/_splitter.pyx":497 * heapsort(Xf, samples, n) * return * maxd -= 1 # <<<<<<<<<<<<<< @@ -7037,16 +6851,16 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * */ __pyx_v_maxd = (__pyx_v_maxd - 1); - /* "_splitter.pyx":499 + /* "stpredictions/models/OK3/_splitter.pyx":499 * maxd -= 1 * * pivot = median3(Xf, n) # <<<<<<<<<<<<<< * * # Three-way partition. */ - __pyx_v_pivot = __pyx_f_9_splitter_median3(__pyx_v_Xf, __pyx_v_n); + __pyx_v_pivot = __pyx_f_13stpredictions_6models_3OK3_9_splitter_median3(__pyx_v_Xf, __pyx_v_n); - /* "_splitter.pyx":502 + /* "stpredictions/models/OK3/_splitter.pyx":502 * * # Three-way partition. * i = l = 0 # <<<<<<<<<<<<<< @@ -7056,7 +6870,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * __pyx_v_i = 0; __pyx_v_l = 0; - /* "_splitter.pyx":503 + /* "stpredictions/models/OK3/_splitter.pyx":503 * # Three-way partition. * i = l = 0 * r = n # <<<<<<<<<<<<<< @@ -7065,7 +6879,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * */ __pyx_v_r = __pyx_v_n; - /* "_splitter.pyx":504 + /* "stpredictions/models/OK3/_splitter.pyx":504 * i = l = 0 * r = n * while i < r: # <<<<<<<<<<<<<< @@ -7076,7 +6890,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * __pyx_t_1 = ((__pyx_v_i < __pyx_v_r) != 0); if (!__pyx_t_1) break; - /* "_splitter.pyx":505 + /* "stpredictions/models/OK3/_splitter.pyx":505 * r = n * while i < r: * if Xf[i] < pivot: # <<<<<<<<<<<<<< @@ -7086,16 +6900,16 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_i]) < __pyx_v_pivot) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":506 + /* "stpredictions/models/OK3/_splitter.pyx":506 * while i < r: * if Xf[i] < pivot: * swap(Xf, samples, i, l) # <<<<<<<<<<<<<< * i += 1 * l += 1 */ - __pyx_f_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_l); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_l); - /* "_splitter.pyx":507 + /* "stpredictions/models/OK3/_splitter.pyx":507 * if Xf[i] < pivot: * swap(Xf, samples, i, l) * i += 1 # <<<<<<<<<<<<<< @@ -7104,7 +6918,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * */ __pyx_v_i = (__pyx_v_i + 1); - /* "_splitter.pyx":508 + /* "stpredictions/models/OK3/_splitter.pyx":508 * swap(Xf, samples, i, l) * i += 1 * l += 1 # <<<<<<<<<<<<<< @@ -7113,7 +6927,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * */ __pyx_v_l = (__pyx_v_l + 1); - /* "_splitter.pyx":505 + /* "stpredictions/models/OK3/_splitter.pyx":505 * r = n * while i < r: * if Xf[i] < pivot: # <<<<<<<<<<<<<< @@ -7123,7 +6937,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * goto __pyx_L8; } - /* "_splitter.pyx":509 + /* "stpredictions/models/OK3/_splitter.pyx":509 * i += 1 * l += 1 * elif Xf[i] > pivot: # <<<<<<<<<<<<<< @@ -7133,7 +6947,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_i]) > __pyx_v_pivot) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":510 + /* "stpredictions/models/OK3/_splitter.pyx":510 * l += 1 * elif Xf[i] > pivot: * r -= 1 # <<<<<<<<<<<<<< @@ -7142,16 +6956,16 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * */ __pyx_v_r = (__pyx_v_r - 1); - /* "_splitter.pyx":511 + /* "stpredictions/models/OK3/_splitter.pyx":511 * elif Xf[i] > pivot: * r -= 1 * swap(Xf, samples, i, r) # <<<<<<<<<<<<<< * else: * i += 1 */ - __pyx_f_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_r); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_r); - /* "_splitter.pyx":509 + /* "stpredictions/models/OK3/_splitter.pyx":509 * i += 1 * l += 1 * elif Xf[i] > pivot: # <<<<<<<<<<<<<< @@ -7161,7 +6975,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * goto __pyx_L8; } - /* "_splitter.pyx":513 + /* "stpredictions/models/OK3/_splitter.pyx":513 * swap(Xf, samples, i, r) * else: * i += 1 # <<<<<<<<<<<<<< @@ -7174,16 +6988,16 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * __pyx_L8:; } - /* "_splitter.pyx":515 + /* "stpredictions/models/OK3/_splitter.pyx":515 * i += 1 * * introsort(Xf, samples, l, maxd) # <<<<<<<<<<<<<< * Xf += r * samples += r */ - __pyx_f_9_splitter_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_l, __pyx_v_maxd); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_l, __pyx_v_maxd); - /* "_splitter.pyx":516 + /* "stpredictions/models/OK3/_splitter.pyx":516 * * introsort(Xf, samples, l, maxd) * Xf += r # <<<<<<<<<<<<<< @@ -7192,7 +7006,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * */ __pyx_v_Xf = (__pyx_v_Xf + __pyx_v_r); - /* "_splitter.pyx":517 + /* "stpredictions/models/OK3/_splitter.pyx":517 * introsort(Xf, samples, l, maxd) * Xf += r * samples += r # <<<<<<<<<<<<<< @@ -7201,7 +7015,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * */ __pyx_v_samples = (__pyx_v_samples + __pyx_v_r); - /* "_splitter.pyx":518 + /* "stpredictions/models/OK3/_splitter.pyx":518 * Xf += r * samples += r * n -= r # <<<<<<<<<<<<<< @@ -7211,7 +7025,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * __pyx_v_n = (__pyx_v_n - __pyx_v_r); } - /* "_splitter.pyx":488 + /* "stpredictions/models/OK3/_splitter.pyx":488 * # Introsort with median of 3 pivot selection and 3-way partition function * # (robust to repeated elements, e.g. lots of zero features). * cdef void introsort(DTYPE_t* Xf, SIZE_t *samples, # <<<<<<<<<<<<<< @@ -7223,7 +7037,7 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * __pyx_L0:; } -/* "_splitter.pyx":521 +/* "stpredictions/models/OK3/_splitter.pyx":521 * * * cdef inline void sift_down(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< @@ -7231,14 +7045,14 @@ static void __pyx_f_9_splitter_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t * * # Restore heap order in Xf[start:end] by moving the max element to start. */ -static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_maxind; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_root; +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sift_down(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_maxind; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_root; int __pyx_t_1; int __pyx_t_2; - /* "_splitter.pyx":526 + /* "stpredictions/models/OK3/_splitter.pyx":526 * cdef SIZE_t child, maxind, root * * root = start # <<<<<<<<<<<<<< @@ -7247,7 +7061,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ */ __pyx_v_root = __pyx_v_start; - /* "_splitter.pyx":527 + /* "stpredictions/models/OK3/_splitter.pyx":527 * * root = start * while True: # <<<<<<<<<<<<<< @@ -7256,7 +7070,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ */ while (1) { - /* "_splitter.pyx":528 + /* "stpredictions/models/OK3/_splitter.pyx":528 * root = start * while True: * child = root * 2 + 1 # <<<<<<<<<<<<<< @@ -7265,7 +7079,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ */ __pyx_v_child = ((__pyx_v_root * 2) + 1); - /* "_splitter.pyx":531 + /* "stpredictions/models/OK3/_splitter.pyx":531 * * # find max of root, left child, right child * maxind = root # <<<<<<<<<<<<<< @@ -7274,7 +7088,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ */ __pyx_v_maxind = __pyx_v_root; - /* "_splitter.pyx":532 + /* "stpredictions/models/OK3/_splitter.pyx":532 * # find max of root, left child, right child * maxind = root * if child < end and Xf[maxind] < Xf[child]: # <<<<<<<<<<<<<< @@ -7292,7 +7106,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ __pyx_L6_bool_binop_done:; if (__pyx_t_1) { - /* "_splitter.pyx":533 + /* "stpredictions/models/OK3/_splitter.pyx":533 * maxind = root * if child < end and Xf[maxind] < Xf[child]: * maxind = child # <<<<<<<<<<<<<< @@ -7301,7 +7115,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ */ __pyx_v_maxind = __pyx_v_child; - /* "_splitter.pyx":532 + /* "stpredictions/models/OK3/_splitter.pyx":532 * # find max of root, left child, right child * maxind = root * if child < end and Xf[maxind] < Xf[child]: # <<<<<<<<<<<<<< @@ -7310,7 +7124,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ */ } - /* "_splitter.pyx":534 + /* "stpredictions/models/OK3/_splitter.pyx":534 * if child < end and Xf[maxind] < Xf[child]: * maxind = child * if child + 1 < end and Xf[maxind] < Xf[child + 1]: # <<<<<<<<<<<<<< @@ -7328,7 +7142,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ __pyx_L9_bool_binop_done:; if (__pyx_t_1) { - /* "_splitter.pyx":535 + /* "stpredictions/models/OK3/_splitter.pyx":535 * maxind = child * if child + 1 < end and Xf[maxind] < Xf[child + 1]: * maxind = child + 1 # <<<<<<<<<<<<<< @@ -7337,7 +7151,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ */ __pyx_v_maxind = (__pyx_v_child + 1); - /* "_splitter.pyx":534 + /* "stpredictions/models/OK3/_splitter.pyx":534 * if child < end and Xf[maxind] < Xf[child]: * maxind = child * if child + 1 < end and Xf[maxind] < Xf[child + 1]: # <<<<<<<<<<<<<< @@ -7346,7 +7160,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ */ } - /* "_splitter.pyx":537 + /* "stpredictions/models/OK3/_splitter.pyx":537 * maxind = child + 1 * * if maxind == root: # <<<<<<<<<<<<<< @@ -7356,7 +7170,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ __pyx_t_1 = ((__pyx_v_maxind == __pyx_v_root) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":538 + /* "stpredictions/models/OK3/_splitter.pyx":538 * * if maxind == root: * break # <<<<<<<<<<<<<< @@ -7365,7 +7179,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ */ goto __pyx_L4_break; - /* "_splitter.pyx":537 + /* "stpredictions/models/OK3/_splitter.pyx":537 * maxind = child + 1 * * if maxind == root: # <<<<<<<<<<<<<< @@ -7374,7 +7188,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ */ } - /* "_splitter.pyx":540 + /* "stpredictions/models/OK3/_splitter.pyx":540 * break * else: * swap(Xf, samples, root, maxind) # <<<<<<<<<<<<<< @@ -7382,9 +7196,9 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ * */ /*else*/ { - __pyx_f_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_root, __pyx_v_maxind); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_root, __pyx_v_maxind); - /* "_splitter.pyx":541 + /* "stpredictions/models/OK3/_splitter.pyx":541 * else: * swap(Xf, samples, root, maxind) * root = maxind # <<<<<<<<<<<<<< @@ -7396,7 +7210,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ } __pyx_L4_break:; - /* "_splitter.pyx":521 + /* "stpredictions/models/OK3/_splitter.pyx":521 * * * cdef inline void sift_down(DTYPE_t* Xf, SIZE_t* samples, # <<<<<<<<<<<<<< @@ -7407,7 +7221,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ /* function exit code */ } -/* "_splitter.pyx":544 +/* "stpredictions/models/OK3/_splitter.pyx":544 * * * cdef void heapsort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: # <<<<<<<<<<<<<< @@ -7415,12 +7229,12 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sift_down(__pyx_t_7sklearn_4tree_5_ * */ -static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end; +static void __pyx_f_13stpredictions_6models_3OK3_9_splitter_heapsort(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end; int __pyx_t_1; - /* "_splitter.pyx":548 + /* "stpredictions/models/OK3/_splitter.pyx":548 * * # heapify * start = (n - 2) / 2 # <<<<<<<<<<<<<< @@ -7429,7 +7243,7 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ */ __pyx_v_start = ((__pyx_v_n - 2) / 2); - /* "_splitter.pyx":549 + /* "stpredictions/models/OK3/_splitter.pyx":549 * # heapify * start = (n - 2) / 2 * end = n # <<<<<<<<<<<<<< @@ -7438,7 +7252,7 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ */ __pyx_v_end = __pyx_v_n; - /* "_splitter.pyx":550 + /* "stpredictions/models/OK3/_splitter.pyx":550 * start = (n - 2) / 2 * end = n * while True: # <<<<<<<<<<<<<< @@ -7447,16 +7261,16 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ */ while (1) { - /* "_splitter.pyx":551 + /* "stpredictions/models/OK3/_splitter.pyx":551 * end = n * while True: * sift_down(Xf, samples, start, end) # <<<<<<<<<<<<<< * if start == 0: * break */ - __pyx_f_9_splitter_sift_down(__pyx_v_Xf, __pyx_v_samples, __pyx_v_start, __pyx_v_end); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_sift_down(__pyx_v_Xf, __pyx_v_samples, __pyx_v_start, __pyx_v_end); - /* "_splitter.pyx":552 + /* "stpredictions/models/OK3/_splitter.pyx":552 * while True: * sift_down(Xf, samples, start, end) * if start == 0: # <<<<<<<<<<<<<< @@ -7466,7 +7280,7 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ __pyx_t_1 = ((__pyx_v_start == 0) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":553 + /* "stpredictions/models/OK3/_splitter.pyx":553 * sift_down(Xf, samples, start, end) * if start == 0: * break # <<<<<<<<<<<<<< @@ -7475,7 +7289,7 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ */ goto __pyx_L4_break; - /* "_splitter.pyx":552 + /* "stpredictions/models/OK3/_splitter.pyx":552 * while True: * sift_down(Xf, samples, start, end) * if start == 0: # <<<<<<<<<<<<<< @@ -7484,7 +7298,7 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ */ } - /* "_splitter.pyx":554 + /* "stpredictions/models/OK3/_splitter.pyx":554 * if start == 0: * break * start -= 1 # <<<<<<<<<<<<<< @@ -7495,7 +7309,7 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ } __pyx_L4_break:; - /* "_splitter.pyx":557 + /* "stpredictions/models/OK3/_splitter.pyx":557 * * # sort by shrinking the heap, putting the max element immediately after it * end = n - 1 # <<<<<<<<<<<<<< @@ -7504,7 +7318,7 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ */ __pyx_v_end = (__pyx_v_n - 1); - /* "_splitter.pyx":558 + /* "stpredictions/models/OK3/_splitter.pyx":558 * # sort by shrinking the heap, putting the max element immediately after it * end = n - 1 * while end > 0: # <<<<<<<<<<<<<< @@ -7515,25 +7329,25 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ __pyx_t_1 = ((__pyx_v_end > 0) != 0); if (!__pyx_t_1) break; - /* "_splitter.pyx":559 + /* "stpredictions/models/OK3/_splitter.pyx":559 * end = n - 1 * while end > 0: * swap(Xf, samples, 0, end) # <<<<<<<<<<<<<< * sift_down(Xf, samples, 0, end) * end = end - 1 */ - __pyx_f_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, 0, __pyx_v_end); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_swap(__pyx_v_Xf, __pyx_v_samples, 0, __pyx_v_end); - /* "_splitter.pyx":560 + /* "stpredictions/models/OK3/_splitter.pyx":560 * while end > 0: * swap(Xf, samples, 0, end) * sift_down(Xf, samples, 0, end) # <<<<<<<<<<<<<< * end = end - 1 * */ - __pyx_f_9_splitter_sift_down(__pyx_v_Xf, __pyx_v_samples, 0, __pyx_v_end); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_sift_down(__pyx_v_Xf, __pyx_v_samples, 0, __pyx_v_end); - /* "_splitter.pyx":561 + /* "stpredictions/models/OK3/_splitter.pyx":561 * swap(Xf, samples, 0, end) * sift_down(Xf, samples, 0, end) * end = end - 1 # <<<<<<<<<<<<<< @@ -7543,7 +7357,7 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ __pyx_v_end = (__pyx_v_end - 1); } - /* "_splitter.pyx":544 + /* "stpredictions/models/OK3/_splitter.pyx":544 * * * cdef void heapsort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil: # <<<<<<<<<<<<<< @@ -7554,7 +7368,7 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ /* function exit code */ } -/* "_splitter.pyx":566 +/* "stpredictions/models/OK3/_splitter.pyx":566 * cdef class RandomSplitter(BaseDenseSplitter): * """Splitter for finding the best random split.""" * def __reduce__(self): # <<<<<<<<<<<<<< @@ -7563,19 +7377,19 @@ static void __pyx_f_9_splitter_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *_ */ /* Python wrapper */ -static PyObject *__pyx_pw_9_splitter_14RandomSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/ -static PyObject *__pyx_pw_9_splitter_14RandomSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/ +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0); - __pyx_r = __pyx_pf_9_splitter_14RandomSplitter___reduce__(((struct __pyx_obj_9_splitter_RandomSplitter *)__pyx_v_self)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter___reduce__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_obj_9_splitter_RandomSplitter *__pyx_v_self) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *__pyx_v_self) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject 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"_splitter.pyx":569 + /* "stpredictions/models/OK3/_splitter.pyx":569 * return (RandomSplitter, (self.criterion, * self.max_features, * self.min_samples_leaf, # <<<<<<<<<<<<<< @@ -7616,7 +7430,7 @@ static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_ob __pyx_t_2 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 569, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); - /* "_splitter.pyx":570 + /* "stpredictions/models/OK3/_splitter.pyx":570 * self.max_features, * self.min_samples_leaf, * self.min_weight_leaf, # <<<<<<<<<<<<<< @@ -7626,7 +7440,7 @@ static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_ob __pyx_t_3 = PyFloat_FromDouble(__pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf); if (unlikely(!__pyx_t_3)) __PYX_ERR(0, 570, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); - /* "_splitter.pyx":567 + /* "stpredictions/models/OK3/_splitter.pyx":567 * """Splitter for finding the best random split.""" * def __reduce__(self): * return (RandomSplitter, (self.criterion, # <<<<<<<<<<<<<< @@ -7651,7 +7465,7 @@ static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_ob __pyx_t_2 = 0; __pyx_t_3 = 0; - /* "_splitter.pyx":571 + /* "stpredictions/models/OK3/_splitter.pyx":571 * self.min_samples_leaf, * self.min_weight_leaf, * self.random_state), self.__getstate__()) # <<<<<<<<<<<<<< @@ -7676,7 +7490,7 @@ static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_ob __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - /* "_splitter.pyx":567 + /* "stpredictions/models/OK3/_splitter.pyx":567 * """Splitter for finding the best random split.""" * def __reduce__(self): * return (RandomSplitter, (self.criterion, # <<<<<<<<<<<<<< @@ -7685,9 +7499,9 @@ static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_ob */ __pyx_t_2 = PyTuple_New(3); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 567, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); - __Pyx_INCREF(((PyObject *)__pyx_ptype_9_splitter_RandomSplitter)); - __Pyx_GIVEREF(((PyObject *)__pyx_ptype_9_splitter_RandomSplitter)); - PyTuple_SET_ITEM(__pyx_t_2, 0, ((PyObject *)__pyx_ptype_9_splitter_RandomSplitter)); + __Pyx_INCREF(((PyObject *)__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_RandomSplitter)); + __Pyx_GIVEREF(((PyObject *)__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_RandomSplitter)); + PyTuple_SET_ITEM(__pyx_t_2, 0, ((PyObject *)__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_RandomSplitter)); __Pyx_GIVEREF(__pyx_t_4); PyTuple_SET_ITEM(__pyx_t_2, 1, __pyx_t_4); __Pyx_GIVEREF(__pyx_t_3); @@ -7698,7 +7512,7 @@ static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_ob __pyx_t_2 = 0; goto __pyx_L0; - /* "_splitter.pyx":566 + /* "stpredictions/models/OK3/_splitter.pyx":566 * cdef class RandomSplitter(BaseDenseSplitter): * """Splitter for finding the best random split.""" * def __reduce__(self): # <<<<<<<<<<<<<< @@ -7712,7 +7526,7 @@ static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_ob __Pyx_XDECREF(__pyx_t_2); __Pyx_XDECREF(__pyx_t_3); __Pyx_XDECREF(__pyx_t_4); - __Pyx_AddTraceback("_splitter.RandomSplitter.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.RandomSplitter.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __Pyx_XGIVEREF(__pyx_r); @@ -7720,7 +7534,7 @@ static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_ob return __pyx_r; } -/* "_splitter.pyx":573 +/* "stpredictions/models/OK3/_splitter.pyx":573 * self.random_state), self.__getstate__()) * * cdef int node_split(self, double impurity, SplitRecord* split, # <<<<<<<<<<<<<< @@ -7728,53 +7542,53 @@ static PyObject *__pyx_pf_9_splitter_14RandomSplitter___reduce__(struct __pyx_ob * """Find the best random split on node samples[start:end] */ -static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_splitter_RandomSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf; +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_n_constant_features) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_constant_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf; double __pyx_v_min_weight_leaf; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t *__pyx_v_random_state; - struct __pyx_t_9_splitter_SplitRecord __pyx_v_best; - struct __pyx_t_9_splitter_SplitRecord __pyx_v_current; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t *__pyx_v_random_state; + struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_best; + struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_current; double __pyx_v_current_proxy_improvement; double __pyx_v_best_proxy_improvement; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_i; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_j; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_partition_end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_found_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_drawn_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_known_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_total_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_visited_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_min_feature_value; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_max_feature_value; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_current_feature_value; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_f_i; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_f_j; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_partition_end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_found_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_drawn_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_known_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_total_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_visited_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_min_feature_value; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_max_feature_value; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_current_feature_value; int __pyx_r; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_t_3; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_t_3; double __pyx_t_4; int __pyx_t_5; int __pyx_t_6; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_7; Py_ssize_t __pyx_t_8; Py_ssize_t __pyx_t_9; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_10; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_11; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_12; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_10; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_t_11; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_t_12; int __pyx_t_13; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "_splitter.pyx":581 + /* "stpredictions/models/OK3/_splitter.pyx":581 * """ * # Draw random splits and pick the best * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< @@ -7784,7 +7598,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.samples; __pyx_v_samples = __pyx_t_1; - /* "_splitter.pyx":582 + /* "stpredictions/models/OK3/_splitter.pyx":582 * # Draw random splits and pick the best * cdef SIZE_t* samples = self.samples * cdef SIZE_t start = self.start # <<<<<<<<<<<<<< @@ -7794,7 +7608,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.start; __pyx_v_start = __pyx_t_2; - /* "_splitter.pyx":583 + /* "stpredictions/models/OK3/_splitter.pyx":583 * cdef SIZE_t* samples = self.samples * cdef SIZE_t start = self.start * cdef SIZE_t end = self.end # <<<<<<<<<<<<<< @@ -7804,7 +7618,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end; __pyx_v_end = __pyx_t_2; - /* "_splitter.pyx":585 + /* "stpredictions/models/OK3/_splitter.pyx":585 * cdef SIZE_t end = self.end * * cdef SIZE_t* features = self.features # <<<<<<<<<<<<<< @@ -7814,7 +7628,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.features; __pyx_v_features = __pyx_t_1; - /* "_splitter.pyx":586 + /* "stpredictions/models/OK3/_splitter.pyx":586 * * cdef SIZE_t* features = self.features * cdef SIZE_t* constant_features = self.constant_features # <<<<<<<<<<<<<< @@ -7824,7 +7638,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.constant_features; __pyx_v_constant_features = __pyx_t_1; - /* "_splitter.pyx":587 + /* "stpredictions/models/OK3/_splitter.pyx":587 * cdef SIZE_t* features = self.features * cdef SIZE_t* constant_features = self.constant_features * cdef SIZE_t n_features = self.n_features # <<<<<<<<<<<<<< @@ -7834,7 +7648,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_features; __pyx_v_n_features = __pyx_t_2; - /* "_splitter.pyx":589 + /* "stpredictions/models/OK3/_splitter.pyx":589 * cdef SIZE_t n_features = self.n_features * * cdef DTYPE_t* Xf = self.feature_values # <<<<<<<<<<<<<< @@ -7844,7 +7658,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.feature_values; __pyx_v_Xf = __pyx_t_3; - /* "_splitter.pyx":590 + /* "stpredictions/models/OK3/_splitter.pyx":590 * * cdef DTYPE_t* Xf = self.feature_values * cdef SIZE_t max_features = self.max_features # <<<<<<<<<<<<<< @@ -7854,7 +7668,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features; __pyx_v_max_features = __pyx_t_2; - /* "_splitter.pyx":591 + /* "stpredictions/models/OK3/_splitter.pyx":591 * cdef DTYPE_t* Xf = self.feature_values * cdef SIZE_t max_features = self.max_features * cdef SIZE_t min_samples_leaf = self.min_samples_leaf # <<<<<<<<<<<<<< @@ -7864,7 +7678,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf; __pyx_v_min_samples_leaf = __pyx_t_2; - /* "_splitter.pyx":592 + /* "stpredictions/models/OK3/_splitter.pyx":592 * cdef SIZE_t max_features = self.max_features * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< @@ -7874,7 +7688,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf; __pyx_v_min_weight_leaf = __pyx_t_4; - /* "_splitter.pyx":593 + /* "stpredictions/models/OK3/_splitter.pyx":593 * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf * cdef UINT32_t* random_state = &self.rand_r_state # <<<<<<<<<<<<<< @@ -7883,25 +7697,25 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state); - /* "_splitter.pyx":596 + /* "stpredictions/models/OK3/_splitter.pyx":596 * * cdef SplitRecord best, current * cdef double current_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< * cdef double best_proxy_improvement = - INFINITY * */ - __pyx_v_current_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + __pyx_v_current_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - /* "_splitter.pyx":597 + /* "stpredictions/models/OK3/_splitter.pyx":597 * cdef SplitRecord best, current * cdef double current_proxy_improvement = - INFINITY * cdef double best_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< * * cdef SIZE_t f_i = n_features */ - __pyx_v_best_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + __pyx_v_best_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - /* "_splitter.pyx":599 + /* "stpredictions/models/OK3/_splitter.pyx":599 * cdef double best_proxy_improvement = - INFINITY * * cdef SIZE_t f_i = n_features # <<<<<<<<<<<<<< @@ -7910,7 +7724,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_f_i = __pyx_v_n_features; - /* "_splitter.pyx":605 + /* "stpredictions/models/OK3/_splitter.pyx":605 * cdef SIZE_t feature_stride * # Number of features discovered to be constant during the split search * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< @@ -7919,7 +7733,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_n_found_constants = 0; - /* "_splitter.pyx":607 + /* "stpredictions/models/OK3/_splitter.pyx":607 * cdef SIZE_t n_found_constants = 0 * # Number of features known to be constant and drawn without replacement * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< @@ -7928,7 +7742,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_n_drawn_constants = 0; - /* "_splitter.pyx":608 + /* "stpredictions/models/OK3/_splitter.pyx":608 * # Number of features known to be constant and drawn without replacement * cdef SIZE_t n_drawn_constants = 0 * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< @@ -7937,7 +7751,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); - /* "_splitter.pyx":610 + /* "stpredictions/models/OK3/_splitter.pyx":610 * cdef SIZE_t n_known_constants = n_constant_features[0] * # n_total_constants = n_known_constants + n_found_constants * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< @@ -7946,7 +7760,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_n_total_constants = __pyx_v_n_known_constants; - /* "_splitter.pyx":611 + /* "stpredictions/models/OK3/_splitter.pyx":611 * # n_total_constants = n_known_constants + n_found_constants * cdef SIZE_t n_total_constants = n_known_constants * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< @@ -7955,16 +7769,16 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_n_visited_features = 0; - /* "_splitter.pyx":616 + /* "stpredictions/models/OK3/_splitter.pyx":616 * cdef DTYPE_t current_feature_value * * _init_split(&best, end) # <<<<<<<<<<<<<< * * # Sample up to max_features without replacement using a */ - __pyx_f_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); + __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); - /* "_splitter.pyx":627 + /* "stpredictions/models/OK3/_splitter.pyx":627 * # newly discovered constant features to spare computation on descendant * # nodes. * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< @@ -7979,7 +7793,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl goto __pyx_L5_bool_binop_done; } - /* "_splitter.pyx":629 + /* "stpredictions/models/OK3/_splitter.pyx":629 * while (f_i > n_total_constants and # Stop early if remaining features * # are constant * (n_visited_features < max_features or # <<<<<<<<<<<<<< @@ -7993,7 +7807,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl goto __pyx_L5_bool_binop_done; } - /* "_splitter.pyx":631 + /* "stpredictions/models/OK3/_splitter.pyx":631 * (n_visited_features < max_features or * # At least one drawn features must be non constant * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< @@ -8005,7 +7819,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_L5_bool_binop_done:; if (!__pyx_t_5) break; - /* "_splitter.pyx":632 + /* "stpredictions/models/OK3/_splitter.pyx":632 * # At least one drawn features must be non constant * n_visited_features <= n_found_constants + n_drawn_constants)): * n_visited_features += 1 # <<<<<<<<<<<<<< @@ -8014,16 +7828,16 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); - /* "_splitter.pyx":646 + /* "stpredictions/models/OK3/_splitter.pyx":646 * * # Draw a feature at random * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< * random_state) * */ - __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); + __pyx_v_f_j = __pyx_f_13stpredictions_6models_3OK3_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); - /* "_splitter.pyx":649 + /* "stpredictions/models/OK3/_splitter.pyx":649 * random_state) * * if f_j < n_known_constants: # <<<<<<<<<<<<<< @@ -8033,7 +7847,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":651 + /* "stpredictions/models/OK3/_splitter.pyx":651 * if f_j < n_known_constants: * # f_j in the interval [n_drawn_constants, n_known_constants[ * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] # <<<<<<<<<<<<<< @@ -8045,7 +7859,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_2; (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; - /* "_splitter.pyx":652 + /* "stpredictions/models/OK3/_splitter.pyx":652 * # f_j in the interval [n_drawn_constants, n_known_constants[ * features[n_drawn_constants], features[f_j] = features[f_j], features[n_drawn_constants] * n_drawn_constants += 1 # <<<<<<<<<<<<<< @@ -8054,7 +7868,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); - /* "_splitter.pyx":649 + /* "stpredictions/models/OK3/_splitter.pyx":649 * random_state) * * if f_j < n_known_constants: # <<<<<<<<<<<<<< @@ -8064,7 +7878,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl goto __pyx_L8; } - /* "_splitter.pyx":656 + /* "stpredictions/models/OK3/_splitter.pyx":656 * else: * # f_j in the interval [n_known_constants, f_i - n_found_constants[ * f_j += n_found_constants # <<<<<<<<<<<<<< @@ -8074,7 +7888,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl /*else*/ { __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); - /* "_splitter.pyx":659 + /* "stpredictions/models/OK3/_splitter.pyx":659 * # f_j in the interval [n_total_constants, f_i[ * * current.feature = features[f_j] # <<<<<<<<<<<<<< @@ -8083,7 +7897,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); - /* "_splitter.pyx":662 + /* "stpredictions/models/OK3/_splitter.pyx":662 * * # Find min, max * min_feature_value = self.X[samples[start], current.feature] # <<<<<<<<<<<<<< @@ -8093,9 +7907,9 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 662, __pyx_L1_error)} __pyx_t_8 = (__pyx_v_samples[__pyx_v_start]); __pyx_t_9 = __pyx_v_current.feature; - __pyx_v_min_feature_value = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))); + __pyx_v_min_feature_value = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))); - /* "_splitter.pyx":663 + /* "stpredictions/models/OK3/_splitter.pyx":663 * # Find min, max * min_feature_value = self.X[samples[start], current.feature] * max_feature_value = min_feature_value # <<<<<<<<<<<<<< @@ -8104,7 +7918,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_max_feature_value = __pyx_v_min_feature_value; - /* "_splitter.pyx":664 + /* "stpredictions/models/OK3/_splitter.pyx":664 * min_feature_value = self.X[samples[start], current.feature] * max_feature_value = min_feature_value * Xf[start] = min_feature_value # <<<<<<<<<<<<<< @@ -8113,7 +7927,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ (__pyx_v_Xf[__pyx_v_start]) = __pyx_v_min_feature_value; - /* "_splitter.pyx":666 + /* "stpredictions/models/OK3/_splitter.pyx":666 * Xf[start] = min_feature_value * * for p in range(start + 1, end): # <<<<<<<<<<<<<< @@ -8125,7 +7939,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl for (__pyx_t_10 = (__pyx_v_start + 1); __pyx_t_10 < __pyx_t_2; __pyx_t_10+=1) { __pyx_v_p = __pyx_t_10; - /* "_splitter.pyx":667 + /* "stpredictions/models/OK3/_splitter.pyx":667 * * for p in range(start + 1, end): * current_feature_value = self.X[samples[p], current.feature] # <<<<<<<<<<<<<< @@ -8135,9 +7949,9 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 667, __pyx_L1_error)} __pyx_t_9 = (__pyx_v_samples[__pyx_v_p]); __pyx_t_8 = __pyx_v_current.feature; - __pyx_v_current_feature_value = (*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[1]) ))); + __pyx_v_current_feature_value = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[1]) ))); - /* "_splitter.pyx":668 + /* "stpredictions/models/OK3/_splitter.pyx":668 * for p in range(start + 1, end): * current_feature_value = self.X[samples[p], current.feature] * Xf[p] = current_feature_value # <<<<<<<<<<<<<< @@ -8146,7 +7960,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ (__pyx_v_Xf[__pyx_v_p]) = __pyx_v_current_feature_value; - /* "_splitter.pyx":670 + /* "stpredictions/models/OK3/_splitter.pyx":670 * Xf[p] = current_feature_value * * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< @@ -8156,7 +7970,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":671 + /* "stpredictions/models/OK3/_splitter.pyx":671 * * if current_feature_value < min_feature_value: * min_feature_value = current_feature_value # <<<<<<<<<<<<<< @@ -8165,7 +7979,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_min_feature_value = __pyx_v_current_feature_value; - /* "_splitter.pyx":670 + /* "stpredictions/models/OK3/_splitter.pyx":670 * Xf[p] = current_feature_value * * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< @@ -8175,7 +7989,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl goto __pyx_L11; } - /* "_splitter.pyx":672 + /* "stpredictions/models/OK3/_splitter.pyx":672 * if current_feature_value < min_feature_value: * min_feature_value = current_feature_value * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< @@ -8185,7 +7999,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":673 + /* "stpredictions/models/OK3/_splitter.pyx":673 * min_feature_value = current_feature_value * elif current_feature_value > max_feature_value: * max_feature_value = current_feature_value # <<<<<<<<<<<<<< @@ -8194,7 +8008,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_max_feature_value = __pyx_v_current_feature_value; - /* "_splitter.pyx":672 + /* "stpredictions/models/OK3/_splitter.pyx":672 * if current_feature_value < min_feature_value: * min_feature_value = current_feature_value * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< @@ -8205,17 +8019,17 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_L11:; } - /* "_splitter.pyx":675 + /* "stpredictions/models/OK3/_splitter.pyx":675 * max_feature_value = current_feature_value * * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature * */ - __pyx_t_5 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + __pyx_t_5 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":676 + /* "stpredictions/models/OK3/_splitter.pyx":676 * * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature # <<<<<<<<<<<<<< @@ -8227,7 +8041,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2; - /* "_splitter.pyx":678 + /* "stpredictions/models/OK3/_splitter.pyx":678 * features[f_j], features[n_total_constants] = features[n_total_constants], current.feature * * n_found_constants += 1 # <<<<<<<<<<<<<< @@ -8236,7 +8050,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); - /* "_splitter.pyx":679 + /* "stpredictions/models/OK3/_splitter.pyx":679 * * n_found_constants += 1 * n_total_constants += 1 # <<<<<<<<<<<<<< @@ -8245,7 +8059,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); - /* "_splitter.pyx":675 + /* "stpredictions/models/OK3/_splitter.pyx":675 * max_feature_value = current_feature_value * * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< @@ -8255,7 +8069,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl goto __pyx_L12; } - /* "_splitter.pyx":682 + /* "stpredictions/models/OK3/_splitter.pyx":682 * * else: * f_i -= 1 # <<<<<<<<<<<<<< @@ -8265,7 +8079,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl /*else*/ { __pyx_v_f_i = (__pyx_v_f_i - 1); - /* "_splitter.pyx":683 + /* "stpredictions/models/OK3/_splitter.pyx":683 * else: * f_i -= 1 * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< @@ -8277,16 +8091,16 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2; (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_7; - /* "_splitter.pyx":686 + /* "stpredictions/models/OK3/_splitter.pyx":686 * * # Draw a random threshold * current.threshold = rand_uniform(min_feature_value, # <<<<<<<<<<<<<< * max_feature_value, * random_state) */ - __pyx_v_current.threshold = __pyx_f_7sklearn_4tree_6_utils_rand_uniform(__pyx_v_min_feature_value, __pyx_v_max_feature_value, __pyx_v_random_state); + __pyx_v_current.threshold = __pyx_f_13stpredictions_6models_3OK3_6_utils_rand_uniform(__pyx_v_min_feature_value, __pyx_v_max_feature_value, __pyx_v_random_state); - /* "_splitter.pyx":690 + /* "stpredictions/models/OK3/_splitter.pyx":690 * random_state) * * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< @@ -8296,7 +8110,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = ((__pyx_v_current.threshold == __pyx_v_max_feature_value) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":691 + /* "stpredictions/models/OK3/_splitter.pyx":691 * * if current.threshold == max_feature_value: * current.threshold = min_feature_value # <<<<<<<<<<<<<< @@ -8305,7 +8119,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_current.threshold = __pyx_v_min_feature_value; - /* "_splitter.pyx":690 + /* "stpredictions/models/OK3/_splitter.pyx":690 * random_state) * * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< @@ -8314,7 +8128,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ } - /* "_splitter.pyx":694 + /* "stpredictions/models/OK3/_splitter.pyx":694 * * # Partition * p, partition_end = start, end # <<<<<<<<<<<<<< @@ -8326,7 +8140,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_v_p = __pyx_t_7; __pyx_v_partition_end = __pyx_t_2; - /* "_splitter.pyx":695 + /* "stpredictions/models/OK3/_splitter.pyx":695 * # Partition * p, partition_end = start, end * while p < partition_end: # <<<<<<<<<<<<<< @@ -8337,7 +8151,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0); if (!__pyx_t_5) break; - /* "_splitter.pyx":696 + /* "stpredictions/models/OK3/_splitter.pyx":696 * p, partition_end = start, end * while p < partition_end: * if Xf[p] <= current.threshold: # <<<<<<<<<<<<<< @@ -8347,7 +8161,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = (((__pyx_v_Xf[__pyx_v_p]) <= __pyx_v_current.threshold) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":697 + /* "stpredictions/models/OK3/_splitter.pyx":697 * while p < partition_end: * if Xf[p] <= current.threshold: * p += 1 # <<<<<<<<<<<<<< @@ -8356,7 +8170,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_p = (__pyx_v_p + 1); - /* "_splitter.pyx":696 + /* "stpredictions/models/OK3/_splitter.pyx":696 * p, partition_end = start, end * while p < partition_end: * if Xf[p] <= current.threshold: # <<<<<<<<<<<<<< @@ -8366,7 +8180,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl goto __pyx_L16; } - /* "_splitter.pyx":699 + /* "stpredictions/models/OK3/_splitter.pyx":699 * p += 1 * else: * partition_end -= 1 # <<<<<<<<<<<<<< @@ -8376,7 +8190,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl /*else*/ { __pyx_v_partition_end = (__pyx_v_partition_end - 1); - /* "_splitter.pyx":701 + /* "stpredictions/models/OK3/_splitter.pyx":701 * partition_end -= 1 * * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] # <<<<<<<<<<<<<< @@ -8388,7 +8202,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl (__pyx_v_Xf[__pyx_v_p]) = __pyx_t_11; (__pyx_v_Xf[__pyx_v_partition_end]) = __pyx_t_12; - /* "_splitter.pyx":702 + /* "stpredictions/models/OK3/_splitter.pyx":702 * * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] * samples[p], samples[partition_end] = samples[partition_end], samples[p] # <<<<<<<<<<<<<< @@ -8403,7 +8217,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_L16:; } - /* "_splitter.pyx":704 + /* "stpredictions/models/OK3/_splitter.pyx":704 * samples[p], samples[partition_end] = samples[partition_end], samples[p] * * current.pos = partition_end # <<<<<<<<<<<<<< @@ -8412,7 +8226,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_current.pos = __pyx_v_partition_end; - /* "_splitter.pyx":707 + /* "stpredictions/models/OK3/_splitter.pyx":707 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -8426,7 +8240,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl goto __pyx_L18_bool_binop_done; } - /* "_splitter.pyx":708 + /* "stpredictions/models/OK3/_splitter.pyx":708 * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or * ((end - current.pos) < min_samples_leaf)): # <<<<<<<<<<<<<< @@ -8437,7 +8251,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = __pyx_t_6; __pyx_L18_bool_binop_done:; - /* "_splitter.pyx":707 + /* "stpredictions/models/OK3/_splitter.pyx":707 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -8446,7 +8260,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ if (__pyx_t_5) { - /* "_splitter.pyx":709 + /* "stpredictions/models/OK3/_splitter.pyx":709 * if (((current.pos - start) < min_samples_leaf) or * ((end - current.pos) < min_samples_leaf)): * continue # <<<<<<<<<<<<<< @@ -8455,7 +8269,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ goto __pyx_L3_continue; - /* "_splitter.pyx":707 + /* "stpredictions/models/OK3/_splitter.pyx":707 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -8464,25 +8278,25 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ } - /* "_splitter.pyx":712 + /* "stpredictions/models/OK3/_splitter.pyx":712 * * # Evaluate split * self.criterion.reset() # <<<<<<<<<<<<<< * self.criterion.update(current.pos) * */ - __pyx_t_13 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 712, __pyx_L1_error) + __pyx_t_13 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 712, __pyx_L1_error) - /* "_splitter.pyx":713 + /* "stpredictions/models/OK3/_splitter.pyx":713 * # Evaluate split * self.criterion.reset() * self.criterion.update(current.pos) # <<<<<<<<<<<<<< * * # Reject if min_weight_leaf is not satisfied */ - __pyx_t_13 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 713, __pyx_L1_error) + __pyx_t_13 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 713, __pyx_L1_error) - /* "_splitter.pyx":716 + /* "stpredictions/models/OK3/_splitter.pyx":716 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -8496,7 +8310,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl goto __pyx_L21_bool_binop_done; } - /* "_splitter.pyx":717 + /* "stpredictions/models/OK3/_splitter.pyx":717 * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or * (self.criterion.weighted_n_right < min_weight_leaf)): # <<<<<<<<<<<<<< @@ -8507,7 +8321,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = __pyx_t_6; __pyx_L21_bool_binop_done:; - /* "_splitter.pyx":716 + /* "stpredictions/models/OK3/_splitter.pyx":716 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -8516,7 +8330,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ if (__pyx_t_5) { - /* "_splitter.pyx":718 + /* "stpredictions/models/OK3/_splitter.pyx":718 * if ((self.criterion.weighted_n_left < min_weight_leaf) or * (self.criterion.weighted_n_right < min_weight_leaf)): * continue # <<<<<<<<<<<<<< @@ -8525,7 +8339,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ goto __pyx_L3_continue; - /* "_splitter.pyx":716 + /* "stpredictions/models/OK3/_splitter.pyx":716 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -8534,16 +8348,16 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ } - /* "_splitter.pyx":720 + /* "stpredictions/models/OK3/_splitter.pyx":720 * continue * * current_proxy_improvement = self.criterion.proxy_impurity_improvement() # <<<<<<<<<<<<<< * * if current_proxy_improvement > best_proxy_improvement: */ - __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); + __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); - /* "_splitter.pyx":722 + /* "stpredictions/models/OK3/_splitter.pyx":722 * current_proxy_improvement = self.criterion.proxy_impurity_improvement() * * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< @@ -8553,7 +8367,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":723 + /* "stpredictions/models/OK3/_splitter.pyx":723 * * if current_proxy_improvement > best_proxy_improvement: * best_proxy_improvement = current_proxy_improvement # <<<<<<<<<<<<<< @@ -8562,7 +8376,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement; - /* "_splitter.pyx":724 + /* "stpredictions/models/OK3/_splitter.pyx":724 * if current_proxy_improvement > best_proxy_improvement: * best_proxy_improvement = current_proxy_improvement * best = current # copy # <<<<<<<<<<<<<< @@ -8571,7 +8385,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_best = __pyx_v_current; - /* "_splitter.pyx":722 + /* "stpredictions/models/OK3/_splitter.pyx":722 * current_proxy_improvement = self.criterion.proxy_impurity_improvement() * * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< @@ -8586,7 +8400,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_L3_continue:; } - /* "_splitter.pyx":727 + /* "stpredictions/models/OK3/_splitter.pyx":727 * * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: # <<<<<<<<<<<<<< @@ -8596,7 +8410,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = ((__pyx_v_best.pos < __pyx_v_end) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":728 + /* "stpredictions/models/OK3/_splitter.pyx":728 * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: * if current.feature != best.feature: # <<<<<<<<<<<<<< @@ -8606,7 +8420,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = ((__pyx_v_current.feature != __pyx_v_best.feature) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":729 + /* "stpredictions/models/OK3/_splitter.pyx":729 * if best.pos < end: * if current.feature != best.feature: * p, partition_end = start, end # <<<<<<<<<<<<<< @@ -8618,7 +8432,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_v_p = __pyx_t_7; __pyx_v_partition_end = __pyx_t_2; - /* "_splitter.pyx":731 + /* "stpredictions/models/OK3/_splitter.pyx":731 * p, partition_end = start, end * * while p < partition_end: # <<<<<<<<<<<<<< @@ -8629,7 +8443,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0); if (!__pyx_t_5) break; - /* "_splitter.pyx":732 + /* "stpredictions/models/OK3/_splitter.pyx":732 * * while p < partition_end: * if self.X[samples[p], best.feature] <= best.threshold: # <<<<<<<<<<<<<< @@ -8639,10 +8453,10 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl if (unlikely(!__pyx_v_self->__pyx_base.X.memview)) {PyErr_SetString(PyExc_AttributeError,"Memoryview is not initialized");__PYX_ERR(0, 732, __pyx_L1_error)} __pyx_t_8 = (__pyx_v_samples[__pyx_v_p]); __pyx_t_9 = __pyx_v_best.feature; - __pyx_t_5 = (((*((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))) <= __pyx_v_best.threshold) != 0); + __pyx_t_5 = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_self->__pyx_base.X.data + __pyx_t_8 * __pyx_v_self->__pyx_base.X.strides[0]) ) + __pyx_t_9 * __pyx_v_self->__pyx_base.X.strides[1]) ))) <= __pyx_v_best.threshold) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":733 + /* "stpredictions/models/OK3/_splitter.pyx":733 * while p < partition_end: * if self.X[samples[p], best.feature] <= best.threshold: * p += 1 # <<<<<<<<<<<<<< @@ -8651,7 +8465,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ __pyx_v_p = (__pyx_v_p + 1); - /* "_splitter.pyx":732 + /* "stpredictions/models/OK3/_splitter.pyx":732 * * while p < partition_end: * if self.X[samples[p], best.feature] <= best.threshold: # <<<<<<<<<<<<<< @@ -8661,7 +8475,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl goto __pyx_L28; } - /* "_splitter.pyx":735 + /* "stpredictions/models/OK3/_splitter.pyx":735 * p += 1 * else: * partition_end -= 1 # <<<<<<<<<<<<<< @@ -8671,7 +8485,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl /*else*/ { __pyx_v_partition_end = (__pyx_v_partition_end - 1); - /* "_splitter.pyx":737 + /* "stpredictions/models/OK3/_splitter.pyx":737 * partition_end -= 1 * * samples[p], samples[partition_end] = samples[partition_end], samples[p] # <<<<<<<<<<<<<< @@ -8686,7 +8500,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_L28:; } - /* "_splitter.pyx":728 + /* "stpredictions/models/OK3/_splitter.pyx":728 * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: * if current.feature != best.feature: # <<<<<<<<<<<<<< @@ -8695,43 +8509,43 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ } - /* "_splitter.pyx":739 + /* "stpredictions/models/OK3/_splitter.pyx":739 * samples[p], samples[partition_end] = samples[partition_end], samples[p] * * self.criterion.reset() # <<<<<<<<<<<<<< * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) */ - __pyx_t_13 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 739, __pyx_L1_error) + __pyx_t_13 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 739, __pyx_L1_error) - /* "_splitter.pyx":740 + /* "stpredictions/models/OK3/_splitter.pyx":740 * * self.criterion.reset() * self.criterion.update(best.pos) # <<<<<<<<<<<<<< * best.improvement = self.criterion.impurity_improvement(impurity) * self.criterion.children_impurity(&best.impurity_left, */ - __pyx_t_13 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 740, __pyx_L1_error) + __pyx_t_13 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_13 == ((int)-1))) __PYX_ERR(0, 740, __pyx_L1_error) - /* "_splitter.pyx":741 + /* "stpredictions/models/OK3/_splitter.pyx":741 * self.criterion.reset() * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) # <<<<<<<<<<<<<< * self.criterion.children_impurity(&best.impurity_left, * &best.impurity_right) */ - __pyx_v_best.improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); + __pyx_v_best.improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); - /* "_splitter.pyx":742 + /* "stpredictions/models/OK3/_splitter.pyx":742 * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) * self.criterion.children_impurity(&best.impurity_left, # <<<<<<<<<<<<<< * &best.impurity_right) * */ - ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); - /* "_splitter.pyx":727 + /* "stpredictions/models/OK3/_splitter.pyx":727 * * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: # <<<<<<<<<<<<<< @@ -8740,25 +8554,25 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ } - /* "_splitter.pyx":748 + /* "stpredictions/models/OK3/_splitter.pyx":748 * # element in features[:n_known_constants] must be preserved for sibling * # and child nodes * memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) # <<<<<<<<<<<<<< * * # Copy newly found constant features */ - (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants))); + (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)) * __pyx_v_n_known_constants))); - /* "_splitter.pyx":751 + /* "stpredictions/models/OK3/_splitter.pyx":751 * * # Copy newly found constant features * memcpy(constant_features + n_known_constants, # <<<<<<<<<<<<<< * features + n_known_constants, * sizeof(SIZE_t) * n_found_constants) */ - (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants))); + (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)) * __pyx_v_n_found_constants))); - /* "_splitter.pyx":756 + /* "stpredictions/models/OK3/_splitter.pyx":756 * * # Return values * split[0] = best # <<<<<<<<<<<<<< @@ -8767,7 +8581,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ (__pyx_v_split[0]) = __pyx_v_best; - /* "_splitter.pyx":757 + /* "stpredictions/models/OK3/_splitter.pyx":757 * # Return values * split[0] = best * n_constant_features[0] = n_total_constants # <<<<<<<<<<<<<< @@ -8776,7 +8590,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants; - /* "_splitter.pyx":758 + /* "stpredictions/models/OK3/_splitter.pyx":758 * split[0] = best * n_constant_features[0] = n_total_constants * return 0 # <<<<<<<<<<<<<< @@ -8786,7 +8600,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl __pyx_r = 0; goto __pyx_L0; - /* "_splitter.pyx":573 + /* "stpredictions/models/OK3/_splitter.pyx":573 * self.random_state), self.__getstate__()) * * cdef int node_split(self, double impurity, SplitRecord* split, # <<<<<<<<<<<<<< @@ -8800,7 +8614,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif - __Pyx_AddTraceback("_splitter.RandomSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.RandomSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif @@ -8810,7 +8624,7 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl return __pyx_r; } -/* "_splitter.pyx":772 +/* "stpredictions/models/OK3/_splitter.pyx":772 * cdef SIZE_t* sorted_samples * * def __cinit__(self, Criterion criterion, SIZE_t max_features, # <<<<<<<<<<<<<< @@ -8819,11 +8633,11 @@ static int __pyx_f_9_splitter_14RandomSplitter_node_split(struct __pyx_obj_9_spl */ /* Python wrapper */ -static int __pyx_pw_9_splitter_18BaseSparseSplitter_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static int __pyx_pw_9_splitter_18BaseSparseSplitter_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { - CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_criterion = 0; - CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features; - CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf; +static int __pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static int __pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_1__cinit__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_criterion = 0; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_features; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf; CYTHON_UNUSED double __pyx_v_min_weight_leaf; CYTHON_UNUSED PyObject *__pyx_v_random_state = 0; int __pyx_lineno = 0; @@ -8894,7 +8708,7 @@ static int __pyx_pw_9_splitter_18BaseSparseSplitter_1__cinit__(PyObject *__pyx_v values[3] = PyTuple_GET_ITEM(__pyx_args, 3); values[4] = PyTuple_GET_ITEM(__pyx_args, 4); } - __pyx_v_criterion = ((struct __pyx_obj_10_criterion_Criterion *)values[0]); + __pyx_v_criterion = ((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *)values[0]); __pyx_v_max_features = __Pyx_PyInt_As_Py_intptr_t(values[1]); if (unlikely((__pyx_v_max_features == ((npy_intp)-1)) && PyErr_Occurred())) __PYX_ERR(0, 772, __pyx_L3_error) __pyx_v_min_samples_leaf = __Pyx_PyInt_As_Py_intptr_t(values[2]); if (unlikely((__pyx_v_min_samples_leaf == ((npy_intp)-1)) && PyErr_Occurred())) __PYX_ERR(0, 773, __pyx_L3_error) __pyx_v_min_weight_leaf = __pyx_PyFloat_AsDouble(values[3]); if 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__pyx_v_max_features, __pyx_v_min_samples_leaf, __pyx_v_min_weight_leaf, __pyx_v_random_state); + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_criterion), __pyx_ptype_13stpredictions_6models_3OK3_10_criterion_Criterion, 1, "criterion", 0))) __PYX_ERR(0, 772, __pyx_L1_error) + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter___cinit__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_criterion, __pyx_v_max_features, __pyx_v_min_samples_leaf, __pyx_v_min_weight_leaf, __pyx_v_random_state); /* function exit code */ goto __pyx_L0; @@ -8920,12 +8734,12 @@ static int __pyx_pw_9_splitter_18BaseSparseSplitter_1__cinit__(PyObject *__pyx_v return __pyx_r; } -static int __pyx_pf_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_10_criterion_Criterion *__pyx_v_criterion, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, CYTHON_UNUSED double __pyx_v_min_weight_leaf, CYTHON_UNUSED PyObject *__pyx_v_random_state) { +static int __pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_v_criterion, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_features, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf, CYTHON_UNUSED double __pyx_v_min_weight_leaf, CYTHON_UNUSED PyObject *__pyx_v_random_state) { int __pyx_r; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__cinit__", 0); - /* "_splitter.pyx":777 + /* "stpredictions/models/OK3/_splitter.pyx":777 * # Parent __cinit__ is automatically called * * self.X_data = NULL # <<<<<<<<<<<<<< @@ -8934,7 +8748,7 @@ static int __pyx_pf_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_9 */ __pyx_v_self->X_data = NULL; - /* "_splitter.pyx":778 + /* "stpredictions/models/OK3/_splitter.pyx":778 * * self.X_data = NULL * self.X_indices = NULL # <<<<<<<<<<<<<< @@ -8943,7 +8757,7 @@ static int __pyx_pf_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_9 */ __pyx_v_self->X_indices = NULL; - /* "_splitter.pyx":779 + /* "stpredictions/models/OK3/_splitter.pyx":779 * self.X_data = NULL * self.X_indices = NULL * self.X_indptr = NULL # <<<<<<<<<<<<<< @@ -8952,7 +8766,7 @@ static int __pyx_pf_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_9 */ __pyx_v_self->X_indptr = NULL; - /* "_splitter.pyx":781 + /* "stpredictions/models/OK3/_splitter.pyx":781 * self.X_indptr = NULL * * self.n_total_samples = 0 # <<<<<<<<<<<<<< @@ -8961,7 +8775,7 @@ static int __pyx_pf_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_9 */ __pyx_v_self->n_total_samples = 0; - /* "_splitter.pyx":783 + /* "stpredictions/models/OK3/_splitter.pyx":783 * self.n_total_samples = 0 * * self.index_to_samples = NULL # <<<<<<<<<<<<<< @@ -8970,7 +8784,7 @@ static int __pyx_pf_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_9 */ __pyx_v_self->index_to_samples = NULL; - /* "_splitter.pyx":784 + /* "stpredictions/models/OK3/_splitter.pyx":784 * * self.index_to_samples = NULL * self.sorted_samples = NULL # <<<<<<<<<<<<<< @@ -8979,7 +8793,7 @@ static int __pyx_pf_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_9 */ __pyx_v_self->sorted_samples = NULL; - /* "_splitter.pyx":772 + /* "stpredictions/models/OK3/_splitter.pyx":772 * cdef SIZE_t* sorted_samples * * def __cinit__(self, Criterion criterion, SIZE_t max_features, # <<<<<<<<<<<<<< @@ -8993,7 +8807,7 @@ static int __pyx_pf_9_splitter_18BaseSparseSplitter___cinit__(struct __pyx_obj_9 return __pyx_r; } -/* "_splitter.pyx":786 +/* "stpredictions/models/OK3/_splitter.pyx":786 * self.sorted_samples = NULL 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*)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); } -static void __pyx_pf_9_splitter_18BaseSparseSplitter_2__dealloc__(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self) { +static void __pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self) { __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__dealloc__", 0); - /* "_splitter.pyx":788 + /* "stpredictions/models/OK3/_splitter.pyx":788 * def __dealloc__(self): * """Deallocate memory.""" * free(self.index_to_samples) # <<<<<<<<<<<<<< @@ -9025,7 +8839,7 @@ static void __pyx_pf_9_splitter_18BaseSparseSplitter_2__dealloc__(struct __pyx_o */ free(__pyx_v_self->index_to_samples); - /* "_splitter.pyx":789 + /* "stpredictions/models/OK3/_splitter.pyx":789 * """Deallocate memory.""" * free(self.index_to_samples) * free(self.sorted_samples) # <<<<<<<<<<<<<< @@ -9034,7 +8848,7 @@ static void __pyx_pf_9_splitter_18BaseSparseSplitter_2__dealloc__(struct __pyx_o */ free(__pyx_v_self->sorted_samples); - /* "_splitter.pyx":786 + /* "stpredictions/models/OK3/_splitter.pyx":786 * self.sorted_samples = NULL * * def __dealloc__(self): # <<<<<<<<<<<<<< @@ -9046,7 +8860,7 @@ static void __pyx_pf_9_splitter_18BaseSparseSplitter_2__dealloc__(struct __pyx_o __Pyx_RefNannyFinishContext(); } -/* "_splitter.pyx":791 +/* "stpredictions/models/OK3/_splitter.pyx":791 * free(self.sorted_samples) * * cdef int init(self, # <<<<<<<<<<<<<< @@ -9054,15 +8868,15 @@ static void __pyx_pf_9_splitter_18BaseSparseSplitter_2__dealloc__(struct __pyx_o * const DOUBLE_t[:, ::1] y, */ -static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_samples; +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, PyObject *__pyx_v_X, __Pyx_memviewslice __pyx_v_y, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_sample_weight) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_samples; PyArrayObject *__pyx_v_data = 0; PyArrayObject *__pyx_v_indices = 0; PyArrayObject *__pyx_v_indptr = 0; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_total_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_total_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_index_to_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p; __Pyx_LocalBuf_ND __pyx_pybuffernd_data; __Pyx_Buffer __pyx_pybuffer_data; __Pyx_LocalBuf_ND __pyx_pybuffernd_indices; @@ -9075,14 +8889,14 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split PyObject *__pyx_t_2 = NULL; int __pyx_t_3; int __pyx_t_4; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_5; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_6; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_t_5; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_6; PyArrayObject *__pyx_t_7 = NULL; PyArrayObject *__pyx_t_8 = NULL; PyArrayObject *__pyx_t_9 = NULL; PyObject *__pyx_t_10 = NULL; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_11; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_12; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_11; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_12; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -9100,16 +8914,16 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_pybuffernd_indptr.data = NULL; __pyx_pybuffernd_indptr.rcbuffer = &__pyx_pybuffer_indptr; - /* "_splitter.pyx":801 + /* "stpredictions/models/OK3/_splitter.pyx":801 * """ * # Call parent init * Splitter.init(self, X, y, sample_weight) # <<<<<<<<<<<<<< * * if not isinstance(X, csc_matrix): */ - __pyx_t_1 = __pyx_f_9_splitter_8Splitter_init(((struct __pyx_obj_9_splitter_Splitter *)__pyx_v_self), __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 801, __pyx_L1_error) + __pyx_t_1 = __pyx_f_13stpredictions_6models_3OK3_9_splitter_8Splitter_init(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_self), __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 801, __pyx_L1_error) - /* "_splitter.pyx":803 + /* "stpredictions/models/OK3/_splitter.pyx":803 * Splitter.init(self, X, y, sample_weight) * * if not isinstance(X, csc_matrix): # <<<<<<<<<<<<<< @@ -9123,7 +8937,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_t_4 = ((!(__pyx_t_3 != 0)) != 0); if (unlikely(__pyx_t_4)) { - /* "_splitter.pyx":804 + /* "stpredictions/models/OK3/_splitter.pyx":804 * * if not isinstance(X, csc_matrix): * raise ValueError("X should be in csc format") # <<<<<<<<<<<<<< @@ -9136,7 +8950,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __PYX_ERR(0, 804, __pyx_L1_error) - /* "_splitter.pyx":803 + /* "stpredictions/models/OK3/_splitter.pyx":803 * Splitter.init(self, X, y, sample_weight) * * if not isinstance(X, csc_matrix): # <<<<<<<<<<<<<< @@ -9145,7 +8959,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split */ } - /* "_splitter.pyx":806 + /* "stpredictions/models/OK3/_splitter.pyx":806 * raise ValueError("X should be in csc format") * * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< @@ -9155,7 +8969,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_t_5 = __pyx_v_self->__pyx_base.samples; __pyx_v_samples = __pyx_t_5; - /* "_splitter.pyx":807 + /* "stpredictions/models/OK3/_splitter.pyx":807 * * cdef SIZE_t* samples = self.samples * cdef SIZE_t n_samples = self.n_samples # <<<<<<<<<<<<<< @@ -9165,7 +8979,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_t_6 = __pyx_v_self->__pyx_base.n_samples; __pyx_v_n_samples = __pyx_t_6; - /* "_splitter.pyx":810 + /* "stpredictions/models/OK3/_splitter.pyx":810 * * # Initialize X * cdef np.ndarray[dtype=DTYPE_t, ndim=1] data = X.data # <<<<<<<<<<<<<< @@ -9178,7 +8992,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_t_7 = ((PyArrayObject *)__pyx_t_2); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_data.rcbuffer->pybuffer, (PyObject*)__pyx_t_7, &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_data.rcbuffer->pybuffer, (PyObject*)__pyx_t_7, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_data = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_data.rcbuffer->pybuffer.buf = NULL; __PYX_ERR(0, 810, __pyx_L1_error) } else {__pyx_pybuffernd_data.diminfo[0].strides = __pyx_pybuffernd_data.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_data.diminfo[0].shape = __pyx_pybuffernd_data.rcbuffer->pybuffer.shape[0]; @@ -9188,7 +9002,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_v_data = ((PyArrayObject *)__pyx_t_2); __pyx_t_2 = 0; - /* "_splitter.pyx":811 + /* "stpredictions/models/OK3/_splitter.pyx":811 * # Initialize X * cdef np.ndarray[dtype=DTYPE_t, ndim=1] data = X.data * cdef np.ndarray[dtype=INT32_t, ndim=1] indices = X.indices # <<<<<<<<<<<<<< @@ -9201,7 +9015,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_t_8 = ((PyArrayObject *)__pyx_t_2); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_t_8, &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_INT32_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_t_8, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_indices = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_indices.rcbuffer->pybuffer.buf = NULL; __PYX_ERR(0, 811, __pyx_L1_error) } else {__pyx_pybuffernd_indices.diminfo[0].strides = __pyx_pybuffernd_indices.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_indices.diminfo[0].shape = __pyx_pybuffernd_indices.rcbuffer->pybuffer.shape[0]; @@ -9211,7 +9025,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_v_indices = ((PyArrayObject *)__pyx_t_2); __pyx_t_2 = 0; - /* "_splitter.pyx":812 + /* "stpredictions/models/OK3/_splitter.pyx":812 * cdef np.ndarray[dtype=DTYPE_t, ndim=1] data = X.data * cdef np.ndarray[dtype=INT32_t, ndim=1] indices = X.indices * cdef np.ndarray[dtype=INT32_t, ndim=1] indptr = X.indptr # <<<<<<<<<<<<<< @@ -9224,7 +9038,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_t_9 = ((PyArrayObject *)__pyx_t_2); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indptr.rcbuffer->pybuffer, (PyObject*)__pyx_t_9, &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_INT32_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indptr.rcbuffer->pybuffer, (PyObject*)__pyx_t_9, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_indptr = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_indptr.rcbuffer->pybuffer.buf = NULL; __PYX_ERR(0, 812, __pyx_L1_error) } else {__pyx_pybuffernd_indptr.diminfo[0].strides = __pyx_pybuffernd_indptr.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_indptr.diminfo[0].shape = __pyx_pybuffernd_indptr.rcbuffer->pybuffer.shape[0]; @@ -9234,7 +9048,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_v_indptr = ((PyArrayObject *)__pyx_t_2); __pyx_t_2 = 0; - /* "_splitter.pyx":813 + /* "stpredictions/models/OK3/_splitter.pyx":813 * cdef np.ndarray[dtype=INT32_t, ndim=1] indices = X.indices * cdef np.ndarray[dtype=INT32_t, ndim=1] indptr = X.indptr * cdef SIZE_t n_total_samples = X.shape[0] # <<<<<<<<<<<<<< @@ -9250,34 +9064,34 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; __pyx_v_n_total_samples = __pyx_t_6; - /* "_splitter.pyx":815 + /* "stpredictions/models/OK3/_splitter.pyx":815 * cdef SIZE_t n_total_samples = X.shape[0] * * self.X_data = data.data # <<<<<<<<<<<<<< * self.X_indices = indices.data * self.X_indptr = indptr.data */ - __pyx_v_self->X_data = ((__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *)__pyx_v_data->data); + __pyx_v_self->X_data = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *)__pyx_v_data->data); - /* "_splitter.pyx":816 + /* "stpredictions/models/OK3/_splitter.pyx":816 * * self.X_data = data.data * self.X_indices = indices.data # <<<<<<<<<<<<<< * self.X_indptr = indptr.data * self.n_total_samples = n_total_samples */ - __pyx_v_self->X_indices = ((__pyx_t_7sklearn_4tree_5_tree_INT32_t *)__pyx_v_indices->data); + __pyx_v_self->X_indices = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *)__pyx_v_indices->data); - /* "_splitter.pyx":817 + /* "stpredictions/models/OK3/_splitter.pyx":817 * self.X_data = data.data * self.X_indices = indices.data * self.X_indptr = indptr.data # <<<<<<<<<<<<<< * self.n_total_samples = n_total_samples * */ - __pyx_v_self->X_indptr = ((__pyx_t_7sklearn_4tree_5_tree_INT32_t *)__pyx_v_indptr->data); + __pyx_v_self->X_indptr = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *)__pyx_v_indptr->data); - /* "_splitter.pyx":818 + /* "stpredictions/models/OK3/_splitter.pyx":818 * self.X_indices = indices.data * self.X_indptr = indptr.data * self.n_total_samples = n_total_samples # <<<<<<<<<<<<<< @@ -9286,25 +9100,25 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split */ __pyx_v_self->n_total_samples = __pyx_v_n_total_samples; - /* "_splitter.pyx":821 + /* "stpredictions/models/OK3/_splitter.pyx":821 * * # Initialize auxiliary array used to perform split * safe_realloc(&self.index_to_samples, n_total_samples) # <<<<<<<<<<<<<< * safe_realloc(&self.sorted_samples, n_samples) * */ - __pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->index_to_samples), __pyx_v_n_total_samples); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 821, __pyx_L1_error) + __pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_self->index_to_samples), __pyx_v_n_total_samples); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 821, __pyx_L1_error) - /* "_splitter.pyx":822 + /* "stpredictions/models/OK3/_splitter.pyx":822 * # Initialize auxiliary array used to perform split * safe_realloc(&self.index_to_samples, n_total_samples) * safe_realloc(&self.sorted_samples, n_samples) # <<<<<<<<<<<<<< * * cdef SIZE_t* index_to_samples = self.index_to_samples */ - __pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->sorted_samples), __pyx_v_n_samples); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 822, __pyx_L1_error) + __pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_self->sorted_samples), __pyx_v_n_samples); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 822, __pyx_L1_error) - /* "_splitter.pyx":824 + /* "stpredictions/models/OK3/_splitter.pyx":824 * safe_realloc(&self.sorted_samples, n_samples) * * cdef SIZE_t* index_to_samples = self.index_to_samples # <<<<<<<<<<<<<< @@ -9314,7 +9128,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_t_5 = __pyx_v_self->index_to_samples; __pyx_v_index_to_samples = __pyx_t_5; - /* "_splitter.pyx":826 + /* "stpredictions/models/OK3/_splitter.pyx":826 * cdef SIZE_t* index_to_samples = self.index_to_samples * cdef SIZE_t p * for p in range(n_total_samples): # <<<<<<<<<<<<<< @@ -9326,7 +9140,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) { __pyx_v_p = __pyx_t_12; - /* "_splitter.pyx":827 + /* "stpredictions/models/OK3/_splitter.pyx":827 * cdef SIZE_t p * for p in range(n_total_samples): * index_to_samples[p] = -1 # <<<<<<<<<<<<<< @@ -9336,7 +9150,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split (__pyx_v_index_to_samples[__pyx_v_p]) = -1; } - /* "_splitter.pyx":829 + /* "stpredictions/models/OK3/_splitter.pyx":829 * index_to_samples[p] = -1 * * for p in range(n_samples): # <<<<<<<<<<<<<< @@ -9348,7 +9162,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) { __pyx_v_p = __pyx_t_12; - /* "_splitter.pyx":830 + /* "stpredictions/models/OK3/_splitter.pyx":830 * * for p in range(n_samples): * index_to_samples[samples[p]] = p # <<<<<<<<<<<<<< @@ -9358,7 +9172,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_p])]) = __pyx_v_p; } - /* "_splitter.pyx":831 + /* "stpredictions/models/OK3/_splitter.pyx":831 * for p in range(n_samples): * index_to_samples[samples[p]] = p * return 0 # <<<<<<<<<<<<<< @@ -9368,7 +9182,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __pyx_r = 0; goto __pyx_L0; - /* "_splitter.pyx":791 + /* "stpredictions/models/OK3/_splitter.pyx":791 * free(self.sorted_samples) * * cdef int init(self, # <<<<<<<<<<<<<< @@ -9388,7 +9202,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_indices.rcbuffer->pybuffer); __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_indptr.rcbuffer->pybuffer); __Pyx_ErrRestore(__pyx_type, __pyx_value, __pyx_tb);} - __Pyx_AddTraceback("_splitter.BaseSparseSplitter.init", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.BaseSparseSplitter.init", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = -1; goto __pyx_L2; __pyx_L0:; @@ -9403,7 +9217,7 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split return __pyx_r; } -/* "_splitter.pyx":833 +/* "stpredictions/models/OK3/_splitter.pyx":833 * return 0 * * cdef inline SIZE_t _partition(self, double threshold, # <<<<<<<<<<<<<< @@ -9411,21 +9225,21 @@ static int __pyx_f_9_splitter_18BaseSparseSplitter_init(struct __pyx_obj_9_split * SIZE_t zero_pos) nogil: */ -static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, double __pyx_v_threshold, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_zero_pos) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_partition_end; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_r; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_2; +static CYTHON_INLINE __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, double __pyx_v_threshold, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end_negative, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start_positive, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_zero_pos) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_partition_end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_index_to_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_r; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_t_2; int __pyx_t_3; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_5; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_6; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_4; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_t_5; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_t_6; - /* "_splitter.pyx":841 + /* "stpredictions/models/OK3/_splitter.pyx":841 * cdef SIZE_t partition_end * * cdef DTYPE_t* Xf = self.feature_values # <<<<<<<<<<<<<< @@ -9435,7 +9249,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B __pyx_t_1 = __pyx_v_self->__pyx_base.feature_values; __pyx_v_Xf = __pyx_t_1; - /* "_splitter.pyx":842 + /* "stpredictions/models/OK3/_splitter.pyx":842 * * cdef DTYPE_t* Xf = self.feature_values * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< @@ -9445,7 +9259,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B __pyx_t_2 = __pyx_v_self->__pyx_base.samples; __pyx_v_samples = __pyx_t_2; - /* "_splitter.pyx":843 + /* "stpredictions/models/OK3/_splitter.pyx":843 * cdef DTYPE_t* Xf = self.feature_values * cdef SIZE_t* samples = self.samples * cdef SIZE_t* index_to_samples = self.index_to_samples # <<<<<<<<<<<<<< @@ -9455,7 +9269,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B __pyx_t_2 = __pyx_v_self->index_to_samples; __pyx_v_index_to_samples = __pyx_t_2; - /* "_splitter.pyx":845 + /* "stpredictions/models/OK3/_splitter.pyx":845 * cdef SIZE_t* index_to_samples = self.index_to_samples * * if threshold < 0.: # <<<<<<<<<<<<<< @@ -9465,7 +9279,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B __pyx_t_3 = ((__pyx_v_threshold < 0.) != 0); if (__pyx_t_3) { - /* "_splitter.pyx":846 + /* "stpredictions/models/OK3/_splitter.pyx":846 * * if threshold < 0.: * p = self.start # <<<<<<<<<<<<<< @@ -9475,7 +9289,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B __pyx_t_4 = __pyx_v_self->__pyx_base.start; __pyx_v_p = __pyx_t_4; - /* "_splitter.pyx":847 + /* "stpredictions/models/OK3/_splitter.pyx":847 * if threshold < 0.: * p = self.start * partition_end = end_negative # <<<<<<<<<<<<<< @@ -9484,7 +9298,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B */ __pyx_v_partition_end = __pyx_v_end_negative; - /* "_splitter.pyx":845 + /* "stpredictions/models/OK3/_splitter.pyx":845 * cdef SIZE_t* index_to_samples = self.index_to_samples * * if threshold < 0.: # <<<<<<<<<<<<<< @@ -9494,7 +9308,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B goto __pyx_L3; } - /* "_splitter.pyx":848 + /* "stpredictions/models/OK3/_splitter.pyx":848 * p = self.start * partition_end = end_negative * elif threshold > 0.: # <<<<<<<<<<<<<< @@ -9504,7 +9318,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B __pyx_t_3 = ((__pyx_v_threshold > 0.) != 0); if (__pyx_t_3) { - /* "_splitter.pyx":849 + /* "stpredictions/models/OK3/_splitter.pyx":849 * partition_end = end_negative * elif threshold > 0.: * p = start_positive # <<<<<<<<<<<<<< @@ -9513,7 +9327,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B */ __pyx_v_p = __pyx_v_start_positive; - /* "_splitter.pyx":850 + /* "stpredictions/models/OK3/_splitter.pyx":850 * elif threshold > 0.: * p = start_positive * partition_end = self.end # <<<<<<<<<<<<<< @@ -9523,7 +9337,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B __pyx_t_4 = __pyx_v_self->__pyx_base.end; __pyx_v_partition_end = __pyx_t_4; - /* "_splitter.pyx":848 + /* "stpredictions/models/OK3/_splitter.pyx":848 * p = self.start * partition_end = end_negative * elif threshold > 0.: # <<<<<<<<<<<<<< @@ -9533,7 +9347,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B goto __pyx_L3; } - /* "_splitter.pyx":853 + /* "stpredictions/models/OK3/_splitter.pyx":853 * else: * # Data are already split * return zero_pos # <<<<<<<<<<<<<< @@ -9546,7 +9360,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B } __pyx_L3:; - /* "_splitter.pyx":855 + /* "stpredictions/models/OK3/_splitter.pyx":855 * return zero_pos * * while p < partition_end: # <<<<<<<<<<<<<< @@ -9557,7 +9371,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B __pyx_t_3 = ((__pyx_v_p < __pyx_v_partition_end) != 0); if (!__pyx_t_3) break; - /* "_splitter.pyx":856 + /* "stpredictions/models/OK3/_splitter.pyx":856 * * while p < partition_end: * if Xf[p] <= threshold: # <<<<<<<<<<<<<< @@ -9567,7 +9381,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B __pyx_t_3 = (((__pyx_v_Xf[__pyx_v_p]) <= __pyx_v_threshold) != 0); if (__pyx_t_3) { - /* "_splitter.pyx":857 + /* "stpredictions/models/OK3/_splitter.pyx":857 * while p < partition_end: * if Xf[p] <= threshold: * p += 1 # <<<<<<<<<<<<<< @@ -9576,7 +9390,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B */ __pyx_v_p = (__pyx_v_p + 1); - /* "_splitter.pyx":856 + /* "stpredictions/models/OK3/_splitter.pyx":856 * * while p < partition_end: * if Xf[p] <= threshold: # <<<<<<<<<<<<<< @@ -9586,7 +9400,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B goto __pyx_L6; } - /* "_splitter.pyx":860 + /* "stpredictions/models/OK3/_splitter.pyx":860 * * else: * partition_end -= 1 # <<<<<<<<<<<<<< @@ -9596,7 +9410,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B /*else*/ { __pyx_v_partition_end = (__pyx_v_partition_end - 1); - /* "_splitter.pyx":862 + /* "stpredictions/models/OK3/_splitter.pyx":862 * partition_end -= 1 * * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] # <<<<<<<<<<<<<< @@ -9608,19 +9422,19 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B (__pyx_v_Xf[__pyx_v_p]) = __pyx_t_5; (__pyx_v_Xf[__pyx_v_partition_end]) = __pyx_t_6; - /* "_splitter.pyx":863 + /* "stpredictions/models/OK3/_splitter.pyx":863 * * Xf[p], Xf[partition_end] = Xf[partition_end], Xf[p] * sparse_swap(index_to_samples, samples, p, partition_end) # <<<<<<<<<<<<<< * * return partition_end */ - __pyx_f_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_p, __pyx_v_partition_end); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_p, __pyx_v_partition_end); } __pyx_L6:; } - /* "_splitter.pyx":865 + /* "stpredictions/models/OK3/_splitter.pyx":865 * sparse_swap(index_to_samples, samples, p, partition_end) * * return partition_end # <<<<<<<<<<<<<< @@ -9630,7 +9444,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B __pyx_r = __pyx_v_partition_end; goto __pyx_L0; - /* "_splitter.pyx":833 + /* "stpredictions/models/OK3/_splitter.pyx":833 * return 0 * * cdef inline SIZE_t _partition(self, double threshold, # <<<<<<<<<<<<<< @@ -9643,7 +9457,7 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B return __pyx_r; } -/* "_splitter.pyx":867 +/* "stpredictions/models/OK3/_splitter.pyx":867 * return partition_end * * cdef inline void extract_nnz(self, SIZE_t feature, # <<<<<<<<<<<<<< @@ -9651,14 +9465,14 @@ static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_9_splitter_18B * bint* is_samples_sorted) nogil: */ -static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_feature, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive, int *__pyx_v_is_samples_sorted) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_indptr_start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_indptr_end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_indices; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_samples; +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_feature, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_start_positive, int *__pyx_v_is_samples_sorted) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_indptr_start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_indptr_end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_indices; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_samples; int __pyx_t_1; - /* "_splitter.pyx":899 + /* "stpredictions/models/OK3/_splitter.pyx":899 * * """ * cdef SIZE_t indptr_start = self.X_indptr[feature], # <<<<<<<<<<<<<< @@ -9667,7 +9481,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(st */ __pyx_v_indptr_start = (__pyx_v_self->X_indptr[__pyx_v_feature]); - /* "_splitter.pyx":900 + /* "stpredictions/models/OK3/_splitter.pyx":900 * """ * cdef SIZE_t indptr_start = self.X_indptr[feature], * cdef SIZE_t indptr_end = self.X_indptr[feature + 1] # <<<<<<<<<<<<<< @@ -9676,16 +9490,16 @@ static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(st */ __pyx_v_indptr_end = (__pyx_v_self->X_indptr[(__pyx_v_feature + 1)]); - /* "_splitter.pyx":901 + /* "stpredictions/models/OK3/_splitter.pyx":901 * cdef SIZE_t indptr_start = self.X_indptr[feature], * cdef SIZE_t indptr_end = self.X_indptr[feature + 1] * cdef SIZE_t n_indices = (indptr_end - indptr_start) # <<<<<<<<<<<<<< * cdef SIZE_t n_samples = self.end - self.start * */ - __pyx_v_n_indices = ((__pyx_t_7sklearn_4tree_5_tree_SIZE_t)(__pyx_v_indptr_end - __pyx_v_indptr_start)); + __pyx_v_n_indices = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)(__pyx_v_indptr_end - __pyx_v_indptr_start)); - /* "_splitter.pyx":902 + /* "stpredictions/models/OK3/_splitter.pyx":902 * cdef SIZE_t indptr_end = self.X_indptr[feature + 1] * cdef SIZE_t n_indices = (indptr_end - indptr_start) * cdef SIZE_t n_samples = self.end - self.start # <<<<<<<<<<<<<< @@ -9694,16 +9508,16 @@ static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(st */ __pyx_v_n_samples = (__pyx_v_self->__pyx_base.end - __pyx_v_self->__pyx_base.start); - /* "_splitter.pyx":910 + /* "stpredictions/models/OK3/_splitter.pyx":910 * # approach. * if ((1 - is_samples_sorted[0]) * n_samples * log(n_samples) + * n_samples * log(n_indices) < EXTRACT_NNZ_SWITCH * n_indices): # <<<<<<<<<<<<<< * extract_nnz_binary_search(self.X_indices, self.X_data, * indptr_start, indptr_end, */ - __pyx_t_1 = ((((((1 - (__pyx_v_is_samples_sorted[0])) * __pyx_v_n_samples) * __pyx_f_7sklearn_4tree_6_utils_log(__pyx_v_n_samples)) + (__pyx_v_n_samples * __pyx_f_7sklearn_4tree_6_utils_log(__pyx_v_n_indices))) < (__pyx_v_9_splitter_EXTRACT_NNZ_SWITCH * __pyx_v_n_indices)) != 0); + __pyx_t_1 = ((((((1 - (__pyx_v_is_samples_sorted[0])) * __pyx_v_n_samples) * __pyx_f_13stpredictions_6models_3OK3_6_utils_log(__pyx_v_n_samples)) + (__pyx_v_n_samples * __pyx_f_13stpredictions_6models_3OK3_6_utils_log(__pyx_v_n_indices))) < (__pyx_v_13stpredictions_6models_3OK3_9_splitter_EXTRACT_NNZ_SWITCH * __pyx_v_n_indices)) != 0); - /* "_splitter.pyx":909 + /* "stpredictions/models/OK3/_splitter.pyx":909 * # search and O(n_indices) is the running time of index_to_samples * # approach. * if ((1 - is_samples_sorted[0]) * n_samples * log(n_samples) + # <<<<<<<<<<<<<< @@ -9712,16 +9526,16 @@ static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(st */ if (__pyx_t_1) { - /* "_splitter.pyx":911 + /* "stpredictions/models/OK3/_splitter.pyx":911 * if ((1 - is_samples_sorted[0]) * n_samples * log(n_samples) + * n_samples * log(n_indices) < EXTRACT_NNZ_SWITCH * n_indices): * extract_nnz_binary_search(self.X_indices, self.X_data, # <<<<<<<<<<<<<< * indptr_start, indptr_end, * self.samples, self.start, self.end, */ - __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_v_self->X_indices, __pyx_v_self->X_data, __pyx_v_indptr_start, __pyx_v_indptr_end, __pyx_v_self->__pyx_base.samples, __pyx_v_self->__pyx_base.start, __pyx_v_self->__pyx_base.end, __pyx_v_self->index_to_samples, __pyx_v_self->__pyx_base.feature_values, __pyx_v_end_negative, __pyx_v_start_positive, __pyx_v_self->sorted_samples, __pyx_v_is_samples_sorted); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_binary_search(__pyx_v_self->X_indices, __pyx_v_self->X_data, __pyx_v_indptr_start, __pyx_v_indptr_end, __pyx_v_self->__pyx_base.samples, __pyx_v_self->__pyx_base.start, __pyx_v_self->__pyx_base.end, __pyx_v_self->index_to_samples, __pyx_v_self->__pyx_base.feature_values, __pyx_v_end_negative, __pyx_v_start_positive, __pyx_v_self->sorted_samples, __pyx_v_is_samples_sorted); - /* "_splitter.pyx":909 + /* "stpredictions/models/OK3/_splitter.pyx":909 * # search and O(n_indices) is the running time of index_to_samples * # approach. * if ((1 - is_samples_sorted[0]) * n_samples * log(n_samples) + # <<<<<<<<<<<<<< @@ -9731,7 +9545,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(st goto __pyx_L3; } - /* "_splitter.pyx":922 + /* "stpredictions/models/OK3/_splitter.pyx":922 * # index_to_samples is a mapping from X_indices to samples * else: * extract_nnz_index_to_samples(self.X_indices, self.X_data, # <<<<<<<<<<<<<< @@ -9740,18 +9554,18 @@ static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(st */ /*else*/ { - /* "_splitter.pyx":927 + /* "stpredictions/models/OK3/_splitter.pyx":927 * self.index_to_samples, * self.feature_values, * end_negative, start_positive) # <<<<<<<<<<<<<< * * */ - __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_v_self->X_indices, __pyx_v_self->X_data, __pyx_v_indptr_start, __pyx_v_indptr_end, __pyx_v_self->__pyx_base.samples, __pyx_v_self->__pyx_base.start, __pyx_v_self->__pyx_base.end, __pyx_v_self->index_to_samples, __pyx_v_self->__pyx_base.feature_values, __pyx_v_end_negative, __pyx_v_start_positive); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_index_to_samples(__pyx_v_self->X_indices, __pyx_v_self->X_data, __pyx_v_indptr_start, __pyx_v_indptr_end, __pyx_v_self->__pyx_base.samples, __pyx_v_self->__pyx_base.start, __pyx_v_self->__pyx_base.end, __pyx_v_self->index_to_samples, __pyx_v_self->__pyx_base.feature_values, __pyx_v_end_negative, __pyx_v_start_positive); } __pyx_L3:; - /* "_splitter.pyx":867 + /* "stpredictions/models/OK3/_splitter.pyx":867 * return partition_end * * cdef inline void extract_nnz(self, SIZE_t feature, # <<<<<<<<<<<<<< @@ -9769,19 +9583,19 @@ static CYTHON_INLINE void __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(st */ /* Python wrapper */ -static PyObject *__pyx_pw_9_splitter_18BaseSparseSplitter_5__reduce_cython__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/ -static PyObject *__pyx_pw_9_splitter_18BaseSparseSplitter_5__reduce_cython__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_5__reduce_cython__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/ +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_5__reduce_cython__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__reduce_cython__ (wrapper)", 0); - __pyx_r = __pyx_pf_9_splitter_18BaseSparseSplitter_4__reduce_cython__(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_4__reduce_cython__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_9_splitter_18BaseSparseSplitter_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -9811,7 +9625,7 @@ static PyObject *__pyx_pf_9_splitter_18BaseSparseSplitter_4__reduce_cython__(CYT /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_1); - __Pyx_AddTraceback("_splitter.BaseSparseSplitter.__reduce_cython__", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.BaseSparseSplitter.__reduce_cython__", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __Pyx_XGIVEREF(__pyx_r); __Pyx_RefNannyFinishContext(); @@ -9826,19 +9640,19 @@ static PyObject *__pyx_pf_9_splitter_18BaseSparseSplitter_4__reduce_cython__(CYT */ /* Python wrapper */ -static PyObject *__pyx_pw_9_splitter_18BaseSparseSplitter_7__setstate_cython__(PyObject *__pyx_v_self, PyObject *__pyx_v___pyx_state); /*proto*/ -static PyObject *__pyx_pw_9_splitter_18BaseSparseSplitter_7__setstate_cython__(PyObject *__pyx_v_self, PyObject *__pyx_v___pyx_state) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_7__setstate_cython__(PyObject *__pyx_v_self, PyObject *__pyx_v___pyx_state); /*proto*/ +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_7__setstate_cython__(PyObject *__pyx_v_self, PyObject *__pyx_v___pyx_state) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__setstate_cython__ (wrapper)", 0); - __pyx_r = __pyx_pf_9_splitter_18BaseSparseSplitter_6__setstate_cython__(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), ((PyObject *)__pyx_v___pyx_state)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_6__setstate_cython__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), ((PyObject *)__pyx_v___pyx_state)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_9_splitter_18BaseSparseSplitter_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -9868,14 +9682,14 @@ static PyObject *__pyx_pf_9_splitter_18BaseSparseSplitter_6__setstate_cython__(C /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_1); - __Pyx_AddTraceback("_splitter.BaseSparseSplitter.__setstate_cython__", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.BaseSparseSplitter.__setstate_cython__", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __Pyx_XGIVEREF(__pyx_r); __Pyx_RefNannyFinishContext(); return __pyx_r; } -/* "_splitter.pyx":930 +/* "stpredictions/models/OK3/_splitter.pyx":930 * * * cdef int compare_SIZE_t(const void* a, const void* b) nogil: # <<<<<<<<<<<<<< @@ -9883,20 +9697,20 @@ static PyObject *__pyx_pf_9_splitter_18BaseSparseSplitter_6__setstate_cython__(C * return ((a)[0] - (b)[0]) */ -static int __pyx_f_9_splitter_compare_SIZE_t(void const *__pyx_v_a, void const *__pyx_v_b) { +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_compare_SIZE_t(void const *__pyx_v_a, void const *__pyx_v_b) { int __pyx_r; - /* "_splitter.pyx":932 + /* "stpredictions/models/OK3/_splitter.pyx":932 * cdef int compare_SIZE_t(const void* a, const void* b) nogil: * """Comparison function for sort.""" * return ((a)[0] - (b)[0]) # <<<<<<<<<<<<<< * * */ - __pyx_r = ((int)((((__pyx_t_7sklearn_4tree_5_tree_SIZE_t *)__pyx_v_a)[0]) - (((__pyx_t_7sklearn_4tree_5_tree_SIZE_t *)__pyx_v_b)[0]))); + __pyx_r = ((int)((((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *)__pyx_v_a)[0]) - (((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *)__pyx_v_b)[0]))); goto __pyx_L0; - /* "_splitter.pyx":930 + /* "stpredictions/models/OK3/_splitter.pyx":930 * * * cdef int compare_SIZE_t(const void* a, const void* b) nogil: # <<<<<<<<<<<<<< @@ -9909,7 +9723,7 @@ static int __pyx_f_9_splitter_compare_SIZE_t(void const *__pyx_v_a, void const * return __pyx_r; } -/* "_splitter.pyx":935 +/* "stpredictions/models/OK3/_splitter.pyx":935 * * * cdef inline void binary_search(INT32_t* sorted_array, # <<<<<<<<<<<<<< @@ -9917,11 +9731,11 @@ static int __pyx_f_9_splitter_compare_SIZE_t(void const *__pyx_v_a, void const * * SIZE_t value, SIZE_t* index, */ -static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_sorted_array, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_value, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index, __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_new_start) { - __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_pivot; +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_binary_search(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_sorted_array, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_v_end, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_value, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_index, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_new_start) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_v_pivot; int __pyx_t_1; - /* "_splitter.pyx":944 + /* "stpredictions/models/OK3/_splitter.pyx":944 * """ * cdef INT32_t pivot * index[0] = -1 # <<<<<<<<<<<<<< @@ -9930,7 +9744,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre */ (__pyx_v_index[0]) = -1; - /* "_splitter.pyx":945 + /* "stpredictions/models/OK3/_splitter.pyx":945 * cdef INT32_t pivot * index[0] = -1 * while start < end: # <<<<<<<<<<<<<< @@ -9941,7 +9755,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre __pyx_t_1 = ((__pyx_v_start < __pyx_v_end) != 0); if (!__pyx_t_1) break; - /* "_splitter.pyx":946 + /* "stpredictions/models/OK3/_splitter.pyx":946 * index[0] = -1 * while start < end: * pivot = start + (end - start) / 2 # <<<<<<<<<<<<<< @@ -9950,7 +9764,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre */ __pyx_v_pivot = (__pyx_v_start + ((__pyx_v_end - __pyx_v_start) / 2)); - /* "_splitter.pyx":948 + /* "stpredictions/models/OK3/_splitter.pyx":948 * pivot = start + (end - start) / 2 * * if sorted_array[pivot] == value: # <<<<<<<<<<<<<< @@ -9960,7 +9774,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre __pyx_t_1 = (((__pyx_v_sorted_array[__pyx_v_pivot]) == __pyx_v_value) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":949 + /* "stpredictions/models/OK3/_splitter.pyx":949 * * if sorted_array[pivot] == value: * index[0] = pivot # <<<<<<<<<<<<<< @@ -9969,7 +9783,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre */ (__pyx_v_index[0]) = __pyx_v_pivot; - /* "_splitter.pyx":950 + /* "stpredictions/models/OK3/_splitter.pyx":950 * if sorted_array[pivot] == value: * index[0] = pivot * start = pivot + 1 # <<<<<<<<<<<<<< @@ -9978,7 +9792,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre */ __pyx_v_start = (__pyx_v_pivot + 1); - /* "_splitter.pyx":951 + /* "stpredictions/models/OK3/_splitter.pyx":951 * index[0] = pivot * start = pivot + 1 * break # <<<<<<<<<<<<<< @@ -9987,7 +9801,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre */ goto __pyx_L4_break; - /* "_splitter.pyx":948 + /* "stpredictions/models/OK3/_splitter.pyx":948 * pivot = start + (end - start) / 2 * * if sorted_array[pivot] == value: # <<<<<<<<<<<<<< @@ -9996,7 +9810,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre */ } - /* "_splitter.pyx":953 + /* "stpredictions/models/OK3/_splitter.pyx":953 * break * * if sorted_array[pivot] < value: # <<<<<<<<<<<<<< @@ -10006,7 +9820,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre __pyx_t_1 = (((__pyx_v_sorted_array[__pyx_v_pivot]) < __pyx_v_value) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":954 + /* "stpredictions/models/OK3/_splitter.pyx":954 * * if sorted_array[pivot] < value: * start = pivot + 1 # <<<<<<<<<<<<<< @@ -10015,7 +9829,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre */ __pyx_v_start = (__pyx_v_pivot + 1); - /* "_splitter.pyx":953 + /* "stpredictions/models/OK3/_splitter.pyx":953 * break * * if sorted_array[pivot] < value: # <<<<<<<<<<<<<< @@ -10025,7 +9839,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre goto __pyx_L6; } - /* "_splitter.pyx":956 + /* "stpredictions/models/OK3/_splitter.pyx":956 * start = pivot + 1 * else: * end = pivot # <<<<<<<<<<<<<< @@ -10039,7 +9853,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre } __pyx_L4_break:; - /* "_splitter.pyx":957 + /* "stpredictions/models/OK3/_splitter.pyx":957 * else: * end = pivot * new_start[0] = start # <<<<<<<<<<<<<< @@ -10048,7 +9862,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre */ (__pyx_v_new_start[0]) = __pyx_v_start; - /* "_splitter.pyx":935 + /* "stpredictions/models/OK3/_splitter.pyx":935 * * * cdef inline void binary_search(INT32_t* sorted_array, # <<<<<<<<<<<<<< @@ -10059,7 +9873,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre /* function exit code */ } -/* "_splitter.pyx":960 +/* "stpredictions/models/OK3/_splitter.pyx":960 * * * cdef inline void extract_nnz_index_to_samples(INT32_t* X_indices, # <<<<<<<<<<<<<< @@ -10067,18 +9881,18 @@ static CYTHON_INLINE void __pyx_f_9_splitter_binary_search(__pyx_t_7sklearn_4tre * INT32_t indptr_start, */ -static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indices, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X_data, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_start, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive) { - __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_k; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_index; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative_; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive_; - __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_t_3; +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_index_to_samples(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_X_indices, __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_X_data, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_v_indptr_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_v_indptr_end, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_start_positive) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_v_k; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_index; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end_negative_; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start_positive_; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_t_3; int __pyx_t_4; int __pyx_t_5; - /* "_splitter.pyx":977 + /* "stpredictions/models/OK3/_splitter.pyx":977 * cdef INT32_t k * cdef SIZE_t index * cdef SIZE_t end_negative_ = start # <<<<<<<<<<<<<< @@ -10087,7 +9901,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ */ __pyx_v_end_negative_ = __pyx_v_start; - /* "_splitter.pyx":978 + /* "stpredictions/models/OK3/_splitter.pyx":978 * cdef SIZE_t index * cdef SIZE_t end_negative_ = start * cdef SIZE_t start_positive_ = end # <<<<<<<<<<<<<< @@ -10096,7 +9910,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ */ __pyx_v_start_positive_ = __pyx_v_end; - /* "_splitter.pyx":980 + /* "stpredictions/models/OK3/_splitter.pyx":980 * cdef SIZE_t start_positive_ = end * * for k in range(indptr_start, indptr_end): # <<<<<<<<<<<<<< @@ -10108,7 +9922,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ for (__pyx_t_3 = __pyx_v_indptr_start; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_k = __pyx_t_3; - /* "_splitter.pyx":981 + /* "stpredictions/models/OK3/_splitter.pyx":981 * * for k in range(indptr_start, indptr_end): * if start <= index_to_samples[X_indices[k]] < end: # <<<<<<<<<<<<<< @@ -10122,7 +9936,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ __pyx_t_5 = (__pyx_t_4 != 0); if (__pyx_t_5) { - /* "_splitter.pyx":982 + /* "stpredictions/models/OK3/_splitter.pyx":982 * for k in range(indptr_start, indptr_end): * if start <= index_to_samples[X_indices[k]] < end: * if X_data[k] > 0: # <<<<<<<<<<<<<< @@ -10132,7 +9946,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ __pyx_t_5 = (((__pyx_v_X_data[__pyx_v_k]) > 0.0) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":983 + /* "stpredictions/models/OK3/_splitter.pyx":983 * if start <= index_to_samples[X_indices[k]] < end: * if X_data[k] > 0: * start_positive_ -= 1 # <<<<<<<<<<<<<< @@ -10141,7 +9955,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ */ __pyx_v_start_positive_ = (__pyx_v_start_positive_ - 1); - /* "_splitter.pyx":984 + /* "stpredictions/models/OK3/_splitter.pyx":984 * if X_data[k] > 0: * start_positive_ -= 1 * Xf[start_positive_] = X_data[k] # <<<<<<<<<<<<<< @@ -10150,7 +9964,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ */ (__pyx_v_Xf[__pyx_v_start_positive_]) = (__pyx_v_X_data[__pyx_v_k]); - /* "_splitter.pyx":985 + /* "stpredictions/models/OK3/_splitter.pyx":985 * start_positive_ -= 1 * Xf[start_positive_] = X_data[k] * index = index_to_samples[X_indices[k]] # <<<<<<<<<<<<<< @@ -10159,16 +9973,16 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ */ __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]); - /* "_splitter.pyx":986 + /* "stpredictions/models/OK3/_splitter.pyx":986 * Xf[start_positive_] = X_data[k] * index = index_to_samples[X_indices[k]] * sparse_swap(index_to_samples, samples, index, start_positive_) # <<<<<<<<<<<<<< * * */ - __pyx_f_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_start_positive_); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_start_positive_); - /* "_splitter.pyx":982 + /* "stpredictions/models/OK3/_splitter.pyx":982 * for k in range(indptr_start, indptr_end): * if start <= index_to_samples[X_indices[k]] < end: * if X_data[k] > 0: # <<<<<<<<<<<<<< @@ -10178,7 +9992,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ goto __pyx_L6; } - /* "_splitter.pyx":989 + /* "stpredictions/models/OK3/_splitter.pyx":989 * * * elif X_data[k] < 0: # <<<<<<<<<<<<<< @@ -10188,7 +10002,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ __pyx_t_5 = (((__pyx_v_X_data[__pyx_v_k]) < 0.0) != 0); if (__pyx_t_5) { - /* "_splitter.pyx":990 + /* "stpredictions/models/OK3/_splitter.pyx":990 * * elif X_data[k] < 0: * Xf[end_negative_] = X_data[k] # <<<<<<<<<<<<<< @@ -10197,7 +10011,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ */ (__pyx_v_Xf[__pyx_v_end_negative_]) = (__pyx_v_X_data[__pyx_v_k]); - /* "_splitter.pyx":991 + /* "stpredictions/models/OK3/_splitter.pyx":991 * elif X_data[k] < 0: * Xf[end_negative_] = X_data[k] * index = index_to_samples[X_indices[k]] # <<<<<<<<<<<<<< @@ -10206,16 +10020,16 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ */ __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]); - /* "_splitter.pyx":992 + /* "stpredictions/models/OK3/_splitter.pyx":992 * Xf[end_negative_] = X_data[k] * index = index_to_samples[X_indices[k]] * sparse_swap(index_to_samples, samples, index, end_negative_) # <<<<<<<<<<<<<< * end_negative_ += 1 * */ - __pyx_f_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_end_negative_); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_end_negative_); - /* "_splitter.pyx":993 + /* "stpredictions/models/OK3/_splitter.pyx":993 * index = index_to_samples[X_indices[k]] * sparse_swap(index_to_samples, samples, index, end_negative_) * end_negative_ += 1 # <<<<<<<<<<<<<< @@ -10224,7 +10038,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ */ __pyx_v_end_negative_ = (__pyx_v_end_negative_ + 1); - /* "_splitter.pyx":989 + /* "stpredictions/models/OK3/_splitter.pyx":989 * * * elif X_data[k] < 0: # <<<<<<<<<<<<<< @@ -10234,7 +10048,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ } __pyx_L6:; - /* "_splitter.pyx":981 + /* "stpredictions/models/OK3/_splitter.pyx":981 * * for k in range(indptr_start, indptr_end): * if start <= index_to_samples[X_indices[k]] < end: # <<<<<<<<<<<<<< @@ -10244,7 +10058,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ } } - /* "_splitter.pyx":996 + /* "stpredictions/models/OK3/_splitter.pyx":996 * * # Returned values * end_negative[0] = end_negative_ # <<<<<<<<<<<<<< @@ -10253,7 +10067,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ */ (__pyx_v_end_negative[0]) = __pyx_v_end_negative_; - /* "_splitter.pyx":997 + /* "stpredictions/models/OK3/_splitter.pyx":997 * # Returned values * end_negative[0] = end_negative_ * start_positive[0] = start_positive_ # <<<<<<<<<<<<<< @@ -10262,7 +10076,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ */ (__pyx_v_start_positive[0]) = __pyx_v_start_positive_; - /* "_splitter.pyx":960 + /* "stpredictions/models/OK3/_splitter.pyx":960 * * * cdef inline void extract_nnz_index_to_samples(INT32_t* X_indices, # <<<<<<<<<<<<<< @@ -10273,7 +10087,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ /* function exit code */ } -/* "_splitter.pyx":1000 +/* "stpredictions/models/OK3/_splitter.pyx":1000 * * * cdef inline void extract_nnz_binary_search(INT32_t* X_indices, # <<<<<<<<<<<<<< @@ -10281,17 +10095,17 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_index_to_samples(__pyx_ * INT32_t indptr_start, */ -static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indices, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X_data, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_start, __pyx_t_7sklearn_4tree_5_tree_INT32_t __pyx_v_indptr_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_start_positive, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_sorted_samples, int *__pyx_v_is_samples_sorted) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_index; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative_; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive_; +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_extract_nnz_binary_search(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_X_indices, __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_X_data, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_v_indptr_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_v_indptr_end, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_end_negative, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_start_positive, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_sorted_samples, int *__pyx_v_is_samples_sorted) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_index; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_k; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end_negative_; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start_positive_; int __pyx_t_1; int __pyx_t_2; - /* "_splitter.pyx":1023 + /* "stpredictions/models/OK3/_splitter.pyx":1023 * cdef SIZE_t n_samples * * if not is_samples_sorted[0]: # <<<<<<<<<<<<<< @@ -10301,7 +10115,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 __pyx_t_1 = ((!((__pyx_v_is_samples_sorted[0]) != 0)) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":1024 + /* "stpredictions/models/OK3/_splitter.pyx":1024 * * if not is_samples_sorted[0]: * n_samples = end - start # <<<<<<<<<<<<<< @@ -10310,25 +10124,25 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ __pyx_v_n_samples = (__pyx_v_end - __pyx_v_start); - /* "_splitter.pyx":1025 + /* "stpredictions/models/OK3/_splitter.pyx":1025 * if not is_samples_sorted[0]: * n_samples = end - start * memcpy(sorted_samples + start, samples + start, # <<<<<<<<<<<<<< * n_samples * sizeof(SIZE_t)) * qsort(sorted_samples + start, n_samples, sizeof(SIZE_t), */ - (void)(memcpy((__pyx_v_sorted_samples + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_n_samples * (sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t))))); + (void)(memcpy((__pyx_v_sorted_samples + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_n_samples * (sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t))))); - /* "_splitter.pyx":1027 + /* "stpredictions/models/OK3/_splitter.pyx":1027 * memcpy(sorted_samples + start, samples + start, * n_samples * sizeof(SIZE_t)) * qsort(sorted_samples + start, n_samples, sizeof(SIZE_t), # <<<<<<<<<<<<<< * compare_SIZE_t) * is_samples_sorted[0] = 1 */ - qsort((__pyx_v_sorted_samples + __pyx_v_start), __pyx_v_n_samples, (sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)), __pyx_f_9_splitter_compare_SIZE_t); + qsort((__pyx_v_sorted_samples + __pyx_v_start), __pyx_v_n_samples, (sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)), __pyx_f_13stpredictions_6models_3OK3_9_splitter_compare_SIZE_t); - /* "_splitter.pyx":1029 + /* "stpredictions/models/OK3/_splitter.pyx":1029 * qsort(sorted_samples + start, n_samples, sizeof(SIZE_t), * compare_SIZE_t) * is_samples_sorted[0] = 1 # <<<<<<<<<<<<<< @@ -10337,7 +10151,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ (__pyx_v_is_samples_sorted[0]) = 1; - /* "_splitter.pyx":1023 + /* "stpredictions/models/OK3/_splitter.pyx":1023 * cdef SIZE_t n_samples * * if not is_samples_sorted[0]: # <<<<<<<<<<<<<< @@ -10346,7 +10160,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ } - /* "_splitter.pyx":1031 + /* "stpredictions/models/OK3/_splitter.pyx":1031 * is_samples_sorted[0] = 1 * * while (indptr_start < indptr_end and # <<<<<<<<<<<<<< @@ -10361,7 +10175,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 goto __pyx_L6_bool_binop_done; } - /* "_splitter.pyx":1032 + /* "stpredictions/models/OK3/_splitter.pyx":1032 * * while (indptr_start < indptr_end and * sorted_samples[start] > X_indices[indptr_start]): # <<<<<<<<<<<<<< @@ -10373,7 +10187,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 __pyx_L6_bool_binop_done:; if (!__pyx_t_1) break; - /* "_splitter.pyx":1033 + /* "stpredictions/models/OK3/_splitter.pyx":1033 * while (indptr_start < indptr_end and * sorted_samples[start] > X_indices[indptr_start]): * indptr_start += 1 # <<<<<<<<<<<<<< @@ -10383,7 +10197,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 __pyx_v_indptr_start = (__pyx_v_indptr_start + 1); } - /* "_splitter.pyx":1035 + /* "stpredictions/models/OK3/_splitter.pyx":1035 * indptr_start += 1 * * while (indptr_start < indptr_end and # <<<<<<<<<<<<<< @@ -10398,7 +10212,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 goto __pyx_L10_bool_binop_done; } - /* "_splitter.pyx":1036 + /* "stpredictions/models/OK3/_splitter.pyx":1036 * * while (indptr_start < indptr_end and * sorted_samples[end - 1] < X_indices[indptr_end - 1]): # <<<<<<<<<<<<<< @@ -10410,7 +10224,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 __pyx_L10_bool_binop_done:; if (!__pyx_t_1) break; - /* "_splitter.pyx":1037 + /* "stpredictions/models/OK3/_splitter.pyx":1037 * while (indptr_start < indptr_end and * sorted_samples[end - 1] < X_indices[indptr_end - 1]): * indptr_end -= 1 # <<<<<<<<<<<<<< @@ -10420,7 +10234,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 __pyx_v_indptr_end = (__pyx_v_indptr_end - 1); } - /* "_splitter.pyx":1039 + /* "stpredictions/models/OK3/_splitter.pyx":1039 * indptr_end -= 1 * * cdef SIZE_t p = start # <<<<<<<<<<<<<< @@ -10429,7 +10243,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ __pyx_v_p = __pyx_v_start; - /* "_splitter.pyx":1042 + /* "stpredictions/models/OK3/_splitter.pyx":1042 * cdef SIZE_t index * cdef SIZE_t k * cdef SIZE_t end_negative_ = start # <<<<<<<<<<<<<< @@ -10438,7 +10252,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ __pyx_v_end_negative_ = __pyx_v_start; - /* "_splitter.pyx":1043 + /* "stpredictions/models/OK3/_splitter.pyx":1043 * cdef SIZE_t k * cdef SIZE_t end_negative_ = start * cdef SIZE_t start_positive_ = end # <<<<<<<<<<<<<< @@ -10447,7 +10261,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ __pyx_v_start_positive_ = __pyx_v_end; - /* "_splitter.pyx":1045 + /* "stpredictions/models/OK3/_splitter.pyx":1045 * cdef SIZE_t start_positive_ = end * * while (p < end and indptr_start < indptr_end): # <<<<<<<<<<<<<< @@ -10466,16 +10280,16 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 __pyx_L14_bool_binop_done:; if (!__pyx_t_1) break; - /* "_splitter.pyx":1047 + /* "stpredictions/models/OK3/_splitter.pyx":1047 * while (p < end and indptr_start < indptr_end): * # Find index of sorted_samples[p] in X_indices * binary_search(X_indices, indptr_start, indptr_end, # <<<<<<<<<<<<<< * sorted_samples[p], &k, &indptr_start) * */ - __pyx_f_9_splitter_binary_search(__pyx_v_X_indices, __pyx_v_indptr_start, __pyx_v_indptr_end, (__pyx_v_sorted_samples[__pyx_v_p]), (&__pyx_v_k), (&__pyx_v_indptr_start)); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_binary_search(__pyx_v_X_indices, __pyx_v_indptr_start, __pyx_v_indptr_end, (__pyx_v_sorted_samples[__pyx_v_p]), (&__pyx_v_k), (&__pyx_v_indptr_start)); - /* "_splitter.pyx":1050 + /* "stpredictions/models/OK3/_splitter.pyx":1050 * sorted_samples[p], &k, &indptr_start) * * if k != -1: # <<<<<<<<<<<<<< @@ -10485,7 +10299,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 __pyx_t_1 = ((__pyx_v_k != -1L) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":1053 + /* "stpredictions/models/OK3/_splitter.pyx":1053 * # If k != -1, we have found a non zero value * * if X_data[k] > 0: # <<<<<<<<<<<<<< @@ -10495,7 +10309,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 __pyx_t_1 = (((__pyx_v_X_data[__pyx_v_k]) > 0.0) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":1054 + /* "stpredictions/models/OK3/_splitter.pyx":1054 * * if X_data[k] > 0: * start_positive_ -= 1 # <<<<<<<<<<<<<< @@ -10504,7 +10318,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ __pyx_v_start_positive_ = (__pyx_v_start_positive_ - 1); - /* "_splitter.pyx":1055 + /* "stpredictions/models/OK3/_splitter.pyx":1055 * if X_data[k] > 0: * start_positive_ -= 1 * Xf[start_positive_] = X_data[k] # <<<<<<<<<<<<<< @@ -10513,7 +10327,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ (__pyx_v_Xf[__pyx_v_start_positive_]) = (__pyx_v_X_data[__pyx_v_k]); - /* "_splitter.pyx":1056 + /* "stpredictions/models/OK3/_splitter.pyx":1056 * start_positive_ -= 1 * Xf[start_positive_] = X_data[k] * index = index_to_samples[X_indices[k]] # <<<<<<<<<<<<<< @@ -10522,16 +10336,16 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]); - /* "_splitter.pyx":1057 + /* "stpredictions/models/OK3/_splitter.pyx":1057 * Xf[start_positive_] = X_data[k] * index = index_to_samples[X_indices[k]] * sparse_swap(index_to_samples, samples, index, start_positive_) # <<<<<<<<<<<<<< * * */ - __pyx_f_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_start_positive_); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_start_positive_); - /* "_splitter.pyx":1053 + /* "stpredictions/models/OK3/_splitter.pyx":1053 * # If k != -1, we have found a non zero value * * if X_data[k] > 0: # <<<<<<<<<<<<<< @@ -10541,7 +10355,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 goto __pyx_L17; } - /* "_splitter.pyx":1060 + /* "stpredictions/models/OK3/_splitter.pyx":1060 * * * elif X_data[k] < 0: # <<<<<<<<<<<<<< @@ -10551,7 +10365,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 __pyx_t_1 = (((__pyx_v_X_data[__pyx_v_k]) < 0.0) != 0); if (__pyx_t_1) { - /* "_splitter.pyx":1061 + /* "stpredictions/models/OK3/_splitter.pyx":1061 * * elif X_data[k] < 0: * Xf[end_negative_] = X_data[k] # <<<<<<<<<<<<<< @@ -10560,7 +10374,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ (__pyx_v_Xf[__pyx_v_end_negative_]) = (__pyx_v_X_data[__pyx_v_k]); - /* "_splitter.pyx":1062 + /* "stpredictions/models/OK3/_splitter.pyx":1062 * elif X_data[k] < 0: * Xf[end_negative_] = X_data[k] * index = index_to_samples[X_indices[k]] # <<<<<<<<<<<<<< @@ -10569,16 +10383,16 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ __pyx_v_index = (__pyx_v_index_to_samples[(__pyx_v_X_indices[__pyx_v_k])]); - /* "_splitter.pyx":1063 + /* "stpredictions/models/OK3/_splitter.pyx":1063 * Xf[end_negative_] = X_data[k] * index = index_to_samples[X_indices[k]] * sparse_swap(index_to_samples, samples, index, end_negative_) # <<<<<<<<<<<<<< * end_negative_ += 1 * p += 1 */ - __pyx_f_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_end_negative_); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_v_index_to_samples, __pyx_v_samples, __pyx_v_index, __pyx_v_end_negative_); - /* "_splitter.pyx":1064 + /* "stpredictions/models/OK3/_splitter.pyx":1064 * index = index_to_samples[X_indices[k]] * sparse_swap(index_to_samples, samples, index, end_negative_) * end_negative_ += 1 # <<<<<<<<<<<<<< @@ -10587,7 +10401,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ __pyx_v_end_negative_ = (__pyx_v_end_negative_ + 1); - /* "_splitter.pyx":1060 + /* "stpredictions/models/OK3/_splitter.pyx":1060 * * * elif X_data[k] < 0: # <<<<<<<<<<<<<< @@ -10597,7 +10411,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 } __pyx_L17:; - /* "_splitter.pyx":1050 + /* "stpredictions/models/OK3/_splitter.pyx":1050 * sorted_samples[p], &k, &indptr_start) * * if k != -1: # <<<<<<<<<<<<<< @@ -10606,7 +10420,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ } - /* "_splitter.pyx":1065 + /* "stpredictions/models/OK3/_splitter.pyx":1065 * sparse_swap(index_to_samples, samples, index, end_negative_) * end_negative_ += 1 * p += 1 # <<<<<<<<<<<<<< @@ -10616,7 +10430,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 __pyx_v_p = (__pyx_v_p + 1); } - /* "_splitter.pyx":1068 + /* "stpredictions/models/OK3/_splitter.pyx":1068 * * # Returned values * end_negative[0] = end_negative_ # <<<<<<<<<<<<<< @@ -10625,7 +10439,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ (__pyx_v_end_negative[0]) = __pyx_v_end_negative_; - /* "_splitter.pyx":1069 + /* "stpredictions/models/OK3/_splitter.pyx":1069 * # Returned values * end_negative[0] = end_negative_ * start_positive[0] = start_positive_ # <<<<<<<<<<<<<< @@ -10634,7 +10448,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 */ (__pyx_v_start_positive[0]) = __pyx_v_start_positive_; - /* "_splitter.pyx":1000 + /* "stpredictions/models/OK3/_splitter.pyx":1000 * * * cdef inline void extract_nnz_binary_search(INT32_t* X_indices, # <<<<<<<<<<<<<< @@ -10645,7 +10459,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 /* function exit code */ } -/* "_splitter.pyx":1072 +/* "stpredictions/models/OK3/_splitter.pyx":1072 * * * cdef inline void sparse_swap(SIZE_t* index_to_samples, SIZE_t* samples, # <<<<<<<<<<<<<< @@ -10653,11 +10467,11 @@ static CYTHON_INLINE void __pyx_f_9_splitter_extract_nnz_binary_search(__pyx_t_7 * """Swap sample pos_1 and pos_2 preserving sparse invariant.""" */ -static CYTHON_INLINE void __pyx_f_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos_1, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos_2) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; +static CYTHON_INLINE void __pyx_f_13stpredictions_6models_3OK3_9_splitter_sparse_swap(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_index_to_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_pos_1, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_pos_2) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_2; - /* "_splitter.pyx":1075 + /* "stpredictions/models/OK3/_splitter.pyx":1075 * SIZE_t pos_1, SIZE_t pos_2) nogil: * """Swap sample pos_1 and pos_2 preserving sparse invariant.""" * samples[pos_1], samples[pos_2] = samples[pos_2], samples[pos_1] # <<<<<<<<<<<<<< @@ -10669,7 +10483,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_ (__pyx_v_samples[__pyx_v_pos_1]) = __pyx_t_1; (__pyx_v_samples[__pyx_v_pos_2]) = __pyx_t_2; - /* "_splitter.pyx":1076 + /* "stpredictions/models/OK3/_splitter.pyx":1076 * """Swap sample pos_1 and pos_2 preserving sparse invariant.""" * samples[pos_1], samples[pos_2] = samples[pos_2], samples[pos_1] * index_to_samples[samples[pos_1]] = pos_1 # <<<<<<<<<<<<<< @@ -10678,7 +10492,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_ */ (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_pos_1])]) = __pyx_v_pos_1; - /* "_splitter.pyx":1077 + /* "stpredictions/models/OK3/_splitter.pyx":1077 * samples[pos_1], samples[pos_2] = samples[pos_2], samples[pos_1] * index_to_samples[samples[pos_1]] = pos_1 * index_to_samples[samples[pos_2]] = pos_2 # <<<<<<<<<<<<<< @@ -10687,7 +10501,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_ */ (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_pos_2])]) = __pyx_v_pos_2; - /* "_splitter.pyx":1072 + /* "stpredictions/models/OK3/_splitter.pyx":1072 * * * cdef inline void sparse_swap(SIZE_t* index_to_samples, SIZE_t* samples, # <<<<<<<<<<<<<< @@ -10698,7 +10512,7 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_ /* function exit code */ } -/* "_splitter.pyx":1083 +/* "stpredictions/models/OK3/_splitter.pyx":1083 * """Splitter for finding the best split, using the sparse data.""" * * def __reduce__(self): # <<<<<<<<<<<<<< @@ -10707,19 +10521,19 @@ static CYTHON_INLINE void __pyx_f_9_splitter_sparse_swap(__pyx_t_7sklearn_4tree_ */ /* Python wrapper */ -static PyObject *__pyx_pw_9_splitter_18BestSparseSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/ -static PyObject *__pyx_pw_9_splitter_18BestSparseSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/ +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0); - __pyx_r = __pyx_pf_9_splitter_18BestSparseSplitter___reduce__(((struct __pyx_obj_9_splitter_BestSparseSplitter *)__pyx_v_self)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter___reduce__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __pyx_obj_9_splitter_BestSparseSplitter *__pyx_v_self) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *__pyx_v_self) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -10731,7 +10545,7 @@ static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__reduce__", 0); - /* "_splitter.pyx":1084 + /* "stpredictions/models/OK3/_splitter.pyx":1084 * * def __reduce__(self): * return (BestSparseSplitter, (self.criterion, # <<<<<<<<<<<<<< @@ -10740,7 +10554,7 @@ static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py */ __Pyx_XDECREF(__pyx_r); - /* "_splitter.pyx":1085 + /* "stpredictions/models/OK3/_splitter.pyx":1085 * def __reduce__(self): * return (BestSparseSplitter, (self.criterion, * self.max_features, # <<<<<<<<<<<<<< @@ -10750,7 +10564,7 @@ static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py __pyx_t_1 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_self->__pyx_base.__pyx_base.max_features); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 1085, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - /* "_splitter.pyx":1086 + /* "stpredictions/models/OK3/_splitter.pyx":1086 * return (BestSparseSplitter, (self.criterion, * self.max_features, * self.min_samples_leaf, # <<<<<<<<<<<<<< @@ -10760,7 +10574,7 @@ static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py __pyx_t_2 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 1086, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); - /* "_splitter.pyx":1087 + /* "stpredictions/models/OK3/_splitter.pyx":1087 * self.max_features, * self.min_samples_leaf, * self.min_weight_leaf, # <<<<<<<<<<<<<< @@ -10770,7 +10584,7 @@ static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py __pyx_t_3 = PyFloat_FromDouble(__pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf); if (unlikely(!__pyx_t_3)) __PYX_ERR(0, 1087, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); - /* "_splitter.pyx":1084 + /* "stpredictions/models/OK3/_splitter.pyx":1084 * * def __reduce__(self): * return (BestSparseSplitter, (self.criterion, # <<<<<<<<<<<<<< @@ -10795,7 +10609,7 @@ static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py __pyx_t_2 = 0; __pyx_t_3 = 0; - /* "_splitter.pyx":1088 + /* "stpredictions/models/OK3/_splitter.pyx":1088 * self.min_samples_leaf, * self.min_weight_leaf, * self.random_state), self.__getstate__()) # <<<<<<<<<<<<<< @@ -10820,7 +10634,7 @@ static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - /* "_splitter.pyx":1084 + /* "stpredictions/models/OK3/_splitter.pyx":1084 * * def 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PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py __pyx_t_2 = 0; goto __pyx_L0; - /* "_splitter.pyx":1083 + /* "stpredictions/models/OK3/_splitter.pyx":1083 * """Splitter for finding the best split, using the sparse data.""" * * def __reduce__(self): # <<<<<<<<<<<<<< @@ -10856,7 +10670,7 @@ static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py __Pyx_XDECREF(__pyx_t_2); __Pyx_XDECREF(__pyx_t_3); __Pyx_XDECREF(__pyx_t_4); - __Pyx_AddTraceback("_splitter.BestSparseSplitter.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.BestSparseSplitter.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __Pyx_XGIVEREF(__pyx_r); @@ -10864,7 +10678,7 @@ static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py return __pyx_r; } -/* "_splitter.pyx":1090 +/* "stpredictions/models/OK3/_splitter.pyx":1090 * self.random_state), self.__getstate__()) * * cdef int node_split(self, double impurity, SplitRecord* split, # <<<<<<<<<<<<<< @@ -10872,56 +10686,56 @@ static PyObject *__pyx_pf_9_splitter_18BestSparseSplitter___reduce__(struct __py * """Find the best split on node samples[start:end], using sparse features */ -static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9_splitter_BestSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features) { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end; - CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indices; - CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_v_X_indptr; - CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X_data; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf; - CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_sorted_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_index_to_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf; +static int __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_n_constant_features) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_X_indices; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_X_indptr; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_X_data; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_constant_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_sorted_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_index_to_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf; double __pyx_v_min_weight_leaf; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t *__pyx_v_random_state; - struct __pyx_t_9_splitter_SplitRecord __pyx_v_best; - struct __pyx_t_9_splitter_SplitRecord __pyx_v_current; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t *__pyx_v_random_state; + struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_best; + struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_current; double __pyx_v_current_proxy_improvement; double __pyx_v_best_proxy_improvement; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_i; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_j; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_visited_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_found_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_drawn_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_known_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_total_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p_next; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p_prev; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_f_i; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_f_j; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_visited_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_found_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_drawn_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_known_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_total_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p_next; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p_prev; int __pyx_v_is_samples_sorted; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start_positive; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end_negative; int __pyx_r; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_t_3; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_t_4; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_t_3; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_t_4; double __pyx_t_5; int __pyx_t_6; int __pyx_t_7; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_8; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_9; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_8; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_9; int __pyx_t_10; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "_splitter.pyx":1098 + /* "stpredictions/models/OK3/_splitter.pyx":1098 * """ * # Find the best split * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< @@ -10931,7 +10745,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.samples; __pyx_v_samples = __pyx_t_1; - /* "_splitter.pyx":1099 + /* "stpredictions/models/OK3/_splitter.pyx":1099 * # Find the best split * cdef SIZE_t* samples = self.samples * cdef SIZE_t start = self.start # <<<<<<<<<<<<<< @@ -10941,7 +10755,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.start; __pyx_v_start = __pyx_t_2; - /* "_splitter.pyx":1100 + /* "stpredictions/models/OK3/_splitter.pyx":1100 * cdef SIZE_t* samples = self.samples * cdef SIZE_t start = self.start * cdef SIZE_t end = self.end # <<<<<<<<<<<<<< @@ -10951,7 +10765,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end; __pyx_v_end = __pyx_t_2; - /* "_splitter.pyx":1102 + /* "stpredictions/models/OK3/_splitter.pyx":1102 * cdef SIZE_t end = self.end * * cdef INT32_t* X_indices = self.X_indices # <<<<<<<<<<<<<< @@ -10961,7 +10775,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_3 = __pyx_v_self->__pyx_base.X_indices; __pyx_v_X_indices = __pyx_t_3; - /* "_splitter.pyx":1103 + /* "stpredictions/models/OK3/_splitter.pyx":1103 * * cdef INT32_t* X_indices = self.X_indices * cdef INT32_t* X_indptr = self.X_indptr # <<<<<<<<<<<<<< @@ -10971,7 +10785,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_3 = __pyx_v_self->__pyx_base.X_indptr; __pyx_v_X_indptr = __pyx_t_3; - /* "_splitter.pyx":1104 + /* "stpredictions/models/OK3/_splitter.pyx":1104 * cdef INT32_t* X_indices = self.X_indices * cdef INT32_t* X_indptr = self.X_indptr * cdef DTYPE_t* X_data = self.X_data # <<<<<<<<<<<<<< @@ -10981,7 +10795,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_4 = __pyx_v_self->__pyx_base.X_data; __pyx_v_X_data = __pyx_t_4; - /* "_splitter.pyx":1106 + /* "stpredictions/models/OK3/_splitter.pyx":1106 * cdef DTYPE_t* X_data = self.X_data * * cdef SIZE_t* features = self.features # <<<<<<<<<<<<<< @@ -10991,7 +10805,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.features; __pyx_v_features = __pyx_t_1; - /* "_splitter.pyx":1107 + /* "stpredictions/models/OK3/_splitter.pyx":1107 * * cdef SIZE_t* features = self.features * cdef SIZE_t* constant_features = self.constant_features # <<<<<<<<<<<<<< @@ -11001,7 +10815,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.constant_features; __pyx_v_constant_features = __pyx_t_1; - /* "_splitter.pyx":1108 + /* "stpredictions/models/OK3/_splitter.pyx":1108 * cdef SIZE_t* features = self.features * cdef SIZE_t* constant_features = self.constant_features * cdef SIZE_t n_features = self.n_features # <<<<<<<<<<<<<< @@ -11011,7 +10825,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_features; __pyx_v_n_features = __pyx_t_2; - /* "_splitter.pyx":1110 + /* "stpredictions/models/OK3/_splitter.pyx":1110 * cdef SIZE_t n_features = self.n_features * * cdef DTYPE_t* Xf = self.feature_values # <<<<<<<<<<<<<< @@ -11021,7 +10835,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.feature_values; __pyx_v_Xf = __pyx_t_4; - /* "_splitter.pyx":1111 + /* "stpredictions/models/OK3/_splitter.pyx":1111 * * cdef DTYPE_t* Xf = self.feature_values * cdef SIZE_t* sorted_samples = self.sorted_samples # <<<<<<<<<<<<<< @@ -11031,7 +10845,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_1 = __pyx_v_self->__pyx_base.sorted_samples; __pyx_v_sorted_samples = __pyx_t_1; - /* "_splitter.pyx":1112 + /* "stpredictions/models/OK3/_splitter.pyx":1112 * cdef DTYPE_t* Xf = self.feature_values * cdef SIZE_t* sorted_samples = self.sorted_samples * cdef SIZE_t* index_to_samples = self.index_to_samples # <<<<<<<<<<<<<< @@ -11041,7 +10855,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_1 = __pyx_v_self->__pyx_base.index_to_samples; __pyx_v_index_to_samples = __pyx_t_1; - /* "_splitter.pyx":1113 + /* "stpredictions/models/OK3/_splitter.pyx":1113 * cdef SIZE_t* sorted_samples = self.sorted_samples * cdef SIZE_t* index_to_samples = self.index_to_samples * cdef SIZE_t max_features = self.max_features # <<<<<<<<<<<<<< @@ -11051,7 +10865,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features; __pyx_v_max_features = __pyx_t_2; - /* "_splitter.pyx":1114 + /* "stpredictions/models/OK3/_splitter.pyx":1114 * cdef SIZE_t* index_to_samples = self.index_to_samples * cdef SIZE_t max_features = self.max_features * cdef SIZE_t min_samples_leaf = self.min_samples_leaf # <<<<<<<<<<<<<< @@ -11061,7 +10875,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf; __pyx_v_min_samples_leaf = __pyx_t_2; - /* "_splitter.pyx":1115 + /* "stpredictions/models/OK3/_splitter.pyx":1115 * cdef SIZE_t max_features = self.max_features * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< @@ -11071,7 +10885,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_5 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf; __pyx_v_min_weight_leaf = __pyx_t_5; - /* "_splitter.pyx":1116 + /* "stpredictions/models/OK3/_splitter.pyx":1116 * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf * cdef UINT32_t* random_state = &self.rand_r_state # <<<<<<<<<<<<<< @@ -11080,34 +10894,34 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state); - /* "_splitter.pyx":1119 + /* "stpredictions/models/OK3/_splitter.pyx":1119 * * cdef SplitRecord best, current * _init_split(&best, end) # <<<<<<<<<<<<<< * cdef double current_proxy_improvement = - INFINITY * cdef double best_proxy_improvement = - INFINITY */ - __pyx_f_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); + __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); - /* "_splitter.pyx":1120 + /* "stpredictions/models/OK3/_splitter.pyx":1120 * cdef SplitRecord best, current * _init_split(&best, end) * cdef double current_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< * cdef double best_proxy_improvement = - INFINITY * */ - __pyx_v_current_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + __pyx_v_current_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - /* "_splitter.pyx":1121 + /* "stpredictions/models/OK3/_splitter.pyx":1121 * _init_split(&best, end) * cdef double current_proxy_improvement = - INFINITY * cdef double best_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< * * cdef SIZE_t f_i = n_features */ - __pyx_v_best_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + __pyx_v_best_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - /* "_splitter.pyx":1123 + /* "stpredictions/models/OK3/_splitter.pyx":1123 * cdef double best_proxy_improvement = - INFINITY * * cdef SIZE_t f_i = n_features # <<<<<<<<<<<<<< @@ -11116,7 +10930,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_f_i = __pyx_v_n_features; - /* "_splitter.pyx":1125 + /* "stpredictions/models/OK3/_splitter.pyx":1125 * cdef SIZE_t f_i = n_features * cdef SIZE_t f_j, p * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< @@ -11125,7 +10939,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_n_visited_features = 0; - /* "_splitter.pyx":1127 + /* "stpredictions/models/OK3/_splitter.pyx":1127 * cdef SIZE_t n_visited_features = 0 * # Number of features discovered to be constant during the split search * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< @@ -11134,7 +10948,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_n_found_constants = 0; - /* "_splitter.pyx":1129 + /* "stpredictions/models/OK3/_splitter.pyx":1129 * cdef SIZE_t n_found_constants = 0 * # Number of features known to be constant and drawn without replacement * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< @@ -11143,7 +10957,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_n_drawn_constants = 0; - /* "_splitter.pyx":1130 + /* "stpredictions/models/OK3/_splitter.pyx":1130 * # Number of features known to be constant and drawn without replacement * cdef SIZE_t n_drawn_constants = 0 * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< @@ -11152,7 +10966,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); - /* "_splitter.pyx":1132 + /* "stpredictions/models/OK3/_splitter.pyx":1132 * cdef SIZE_t n_known_constants = n_constant_features[0] * # n_total_constants = n_known_constants + n_found_constants * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< @@ -11161,7 +10975,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_n_total_constants = __pyx_v_n_known_constants; - /* "_splitter.pyx":1137 + /* "stpredictions/models/OK3/_splitter.pyx":1137 * cdef SIZE_t p_next * cdef SIZE_t p_prev * cdef bint is_samples_sorted = 0 # indicate is sorted_samples is # <<<<<<<<<<<<<< @@ -11170,7 +10984,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_is_samples_sorted = 0; - /* "_splitter.pyx":1154 + /* "stpredictions/models/OK3/_splitter.pyx":1154 * # newly discovered constant features to spare computation on descendant * # nodes. * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< @@ -11185,7 +10999,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 goto __pyx_L5_bool_binop_done; } - /* "_splitter.pyx":1156 + /* "stpredictions/models/OK3/_splitter.pyx":1156 * while (f_i > n_total_constants and # Stop early if remaining features * # are constant * (n_visited_features < max_features or # <<<<<<<<<<<<<< @@ -11199,7 +11013,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 goto __pyx_L5_bool_binop_done; } - /* "_splitter.pyx":1158 + /* "stpredictions/models/OK3/_splitter.pyx":1158 * (n_visited_features < max_features or * # At least one drawn features must be non constant * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< @@ -11211,7 +11025,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_L5_bool_binop_done:; if (!__pyx_t_6) break; - /* "_splitter.pyx":1160 + /* "stpredictions/models/OK3/_splitter.pyx":1160 * n_visited_features <= n_found_constants + n_drawn_constants)): * * n_visited_features += 1 # <<<<<<<<<<<<<< @@ -11220,16 +11034,16 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); - /* "_splitter.pyx":1174 + /* "stpredictions/models/OK3/_splitter.pyx":1174 * * # Draw a feature at random * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< * random_state) * */ - __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); + __pyx_v_f_j = __pyx_f_13stpredictions_6models_3OK3_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); - /* "_splitter.pyx":1177 + /* "stpredictions/models/OK3/_splitter.pyx":1177 * random_state) * * if f_j < n_known_constants: # <<<<<<<<<<<<<< @@ -11239,7 +11053,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1179 + /* "stpredictions/models/OK3/_splitter.pyx":1179 * if f_j < n_known_constants: * # f_j in the interval [n_drawn_constants, n_known_constants[ * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] # <<<<<<<<<<<<<< @@ -11251,7 +11065,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2; (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_8; - /* "_splitter.pyx":1181 + /* "stpredictions/models/OK3/_splitter.pyx":1181 * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] * * n_drawn_constants += 1 # <<<<<<<<<<<<<< @@ -11260,7 +11074,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); - /* "_splitter.pyx":1177 + /* "stpredictions/models/OK3/_splitter.pyx":1177 * random_state) * * if f_j < n_known_constants: # <<<<<<<<<<<<<< @@ -11270,7 +11084,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 goto __pyx_L8; } - /* "_splitter.pyx":1185 + /* "stpredictions/models/OK3/_splitter.pyx":1185 * else: * # f_j in the interval [n_known_constants, f_i - n_found_constants[ * f_j += n_found_constants # <<<<<<<<<<<<<< @@ -11280,7 +11094,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 /*else*/ { __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); - /* "_splitter.pyx":1188 + /* "stpredictions/models/OK3/_splitter.pyx":1188 * # f_j in the interval [n_total_constants, f_i[ * * current.feature = features[f_j] # <<<<<<<<<<<<<< @@ -11289,34 +11103,34 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); - /* "_splitter.pyx":1189 + /* "stpredictions/models/OK3/_splitter.pyx":1189 * * current.feature = features[f_j] * self.extract_nnz(current.feature, # <<<<<<<<<<<<<< * &end_negative, &start_positive, * &is_samples_sorted) */ - __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); - /* "_splitter.pyx":1194 + /* "stpredictions/models/OK3/_splitter.pyx":1194 * * # Sort the positive and negative parts of `Xf` * sort(Xf + start, samples + start, end_negative - start) # <<<<<<<<<<<<<< * sort(Xf + start_positive, samples + start_positive, * end - start_positive) */ - __pyx_f_9_splitter_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end_negative - __pyx_v_start)); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end_negative - __pyx_v_start)); - /* "_splitter.pyx":1195 + /* "stpredictions/models/OK3/_splitter.pyx":1195 * # Sort the positive and negative parts of `Xf` * sort(Xf + start, samples + start, end_negative - start) * sort(Xf + start_positive, samples + start_positive, # <<<<<<<<<<<<<< * end - start_positive) * */ - __pyx_f_9_splitter_sort((__pyx_v_Xf + __pyx_v_start_positive), (__pyx_v_samples + __pyx_v_start_positive), (__pyx_v_end - __pyx_v_start_positive)); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_sort((__pyx_v_Xf + __pyx_v_start_positive), (__pyx_v_samples + __pyx_v_start_positive), (__pyx_v_end - __pyx_v_start_positive)); - /* "_splitter.pyx":1199 + /* "stpredictions/models/OK3/_splitter.pyx":1199 * * # Update index_to_samples to take into account the sort * for p in range(start, end_negative): # <<<<<<<<<<<<<< @@ -11328,7 +11142,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 for (__pyx_t_9 = __pyx_v_start; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { __pyx_v_p = __pyx_t_9; - /* "_splitter.pyx":1200 + /* "stpredictions/models/OK3/_splitter.pyx":1200 * # Update index_to_samples to take into account the sort * for p in range(start, end_negative): * index_to_samples[samples[p]] = p # <<<<<<<<<<<<<< @@ -11338,7 +11152,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_p])]) = __pyx_v_p; } - /* "_splitter.pyx":1201 + /* "stpredictions/models/OK3/_splitter.pyx":1201 * for p in range(start, end_negative): * index_to_samples[samples[p]] = p * for p in range(start_positive, end): # <<<<<<<<<<<<<< @@ -11350,7 +11164,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 for (__pyx_t_9 = __pyx_v_start_positive; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { __pyx_v_p = __pyx_t_9; - /* "_splitter.pyx":1202 + /* "stpredictions/models/OK3/_splitter.pyx":1202 * index_to_samples[samples[p]] = p * for p in range(start_positive, end): * index_to_samples[samples[p]] = p # <<<<<<<<<<<<<< @@ -11360,7 +11174,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 (__pyx_v_index_to_samples[(__pyx_v_samples[__pyx_v_p])]) = __pyx_v_p; } - /* "_splitter.pyx":1205 + /* "stpredictions/models/OK3/_splitter.pyx":1205 * * # Add one or two zeros in Xf, if there is any * if end_negative < start_positive: # <<<<<<<<<<<<<< @@ -11370,7 +11184,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = ((__pyx_v_end_negative < __pyx_v_start_positive) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1206 + /* "stpredictions/models/OK3/_splitter.pyx":1206 * # Add one or two zeros in Xf, if there is any * if end_negative < start_positive: * start_positive -= 1 # <<<<<<<<<<<<<< @@ -11379,7 +11193,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_start_positive = (__pyx_v_start_positive - 1); - /* "_splitter.pyx":1207 + /* "stpredictions/models/OK3/_splitter.pyx":1207 * if end_negative < start_positive: * start_positive -= 1 * Xf[start_positive] = 0. # <<<<<<<<<<<<<< @@ -11388,7 +11202,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ (__pyx_v_Xf[__pyx_v_start_positive]) = 0.; - /* "_splitter.pyx":1209 + /* "stpredictions/models/OK3/_splitter.pyx":1209 * Xf[start_positive] = 0. * * if end_negative != start_positive: # <<<<<<<<<<<<<< @@ -11398,7 +11212,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = ((__pyx_v_end_negative != __pyx_v_start_positive) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1210 + /* "stpredictions/models/OK3/_splitter.pyx":1210 * * if end_negative != start_positive: * Xf[end_negative] = 0. # <<<<<<<<<<<<<< @@ -11407,7 +11221,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ (__pyx_v_Xf[__pyx_v_end_negative]) = 0.; - /* "_splitter.pyx":1211 + /* "stpredictions/models/OK3/_splitter.pyx":1211 * if end_negative != start_positive: * Xf[end_negative] = 0. * end_negative += 1 # <<<<<<<<<<<<<< @@ -11416,7 +11230,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_end_negative = (__pyx_v_end_negative + 1); - /* "_splitter.pyx":1209 + /* "stpredictions/models/OK3/_splitter.pyx":1209 * Xf[start_positive] = 0. * * if end_negative != start_positive: # <<<<<<<<<<<<<< @@ -11425,7 +11239,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ } - /* "_splitter.pyx":1205 + /* "stpredictions/models/OK3/_splitter.pyx":1205 * * # Add one or two zeros in Xf, if there is any * if end_negative < start_positive: # <<<<<<<<<<<<<< @@ -11434,17 +11248,17 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ } - /* "_splitter.pyx":1213 + /* "stpredictions/models/OK3/_splitter.pyx":1213 * end_negative += 1 * * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] * */ - __pyx_t_6 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + __pyx_t_6 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1214 + /* "stpredictions/models/OK3/_splitter.pyx":1214 * * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] # <<<<<<<<<<<<<< @@ -11456,7 +11270,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_8; (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2; - /* "_splitter.pyx":1216 + /* "stpredictions/models/OK3/_splitter.pyx":1216 * features[f_j], features[n_total_constants] = features[n_total_constants], features[f_j] * * n_found_constants += 1 # <<<<<<<<<<<<<< @@ -11465,7 +11279,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); - /* "_splitter.pyx":1217 + /* "stpredictions/models/OK3/_splitter.pyx":1217 * * n_found_constants += 1 * n_total_constants += 1 # <<<<<<<<<<<<<< @@ -11474,7 +11288,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); - /* "_splitter.pyx":1213 + /* "stpredictions/models/OK3/_splitter.pyx":1213 * end_negative += 1 * * if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< @@ -11484,7 +11298,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 goto __pyx_L15; } - /* "_splitter.pyx":1220 + /* "stpredictions/models/OK3/_splitter.pyx":1220 * * else: * f_i -= 1 # <<<<<<<<<<<<<< @@ -11494,7 +11308,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 /*else*/ { __pyx_v_f_i = (__pyx_v_f_i - 1); - /* "_splitter.pyx":1221 + /* "stpredictions/models/OK3/_splitter.pyx":1221 * else: * f_i -= 1 * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< @@ -11506,16 +11320,16 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2; (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_8; - /* "_splitter.pyx":1224 + /* "stpredictions/models/OK3/_splitter.pyx":1224 * * # Evaluate all splits * self.criterion.reset() # <<<<<<<<<<<<<< * p = start * */ - __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1224, __pyx_L1_error) + __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1224, __pyx_L1_error) - /* "_splitter.pyx":1225 + /* "stpredictions/models/OK3/_splitter.pyx":1225 * # Evaluate all splits * self.criterion.reset() * p = start # <<<<<<<<<<<<<< @@ -11524,7 +11338,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_p = __pyx_v_start; - /* "_splitter.pyx":1227 + /* "stpredictions/models/OK3/_splitter.pyx":1227 * p = start * * while p < end: # <<<<<<<<<<<<<< @@ -11535,7 +11349,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = ((__pyx_v_p < __pyx_v_end) != 0); if (!__pyx_t_6) break; - /* "_splitter.pyx":1228 + /* "stpredictions/models/OK3/_splitter.pyx":1228 * * while p < end: * if p + 1 != end_negative: # <<<<<<<<<<<<<< @@ -11545,7 +11359,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = (((__pyx_v_p + 1) != __pyx_v_end_negative) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1229 + /* "stpredictions/models/OK3/_splitter.pyx":1229 * while p < end: * if p + 1 != end_negative: * p_next = p + 1 # <<<<<<<<<<<<<< @@ -11554,7 +11368,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_p_next = (__pyx_v_p + 1); - /* "_splitter.pyx":1228 + /* "stpredictions/models/OK3/_splitter.pyx":1228 * * while p < end: * if p + 1 != end_negative: # <<<<<<<<<<<<<< @@ -11564,7 +11378,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 goto __pyx_L18; } - /* "_splitter.pyx":1231 + /* "stpredictions/models/OK3/_splitter.pyx":1231 * p_next = p + 1 * else: * p_next = start_positive # <<<<<<<<<<<<<< @@ -11576,7 +11390,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 } __pyx_L18:; - /* "_splitter.pyx":1233 + /* "stpredictions/models/OK3/_splitter.pyx":1233 * p_next = start_positive * * while (p_next < end and # <<<<<<<<<<<<<< @@ -11591,19 +11405,19 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 goto __pyx_L21_bool_binop_done; } - /* "_splitter.pyx":1234 + /* "stpredictions/models/OK3/_splitter.pyx":1234 * * while (p_next < end and * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): # <<<<<<<<<<<<<< * p = p_next * if p + 1 != end_negative: */ - __pyx_t_7 = (((__pyx_v_Xf[__pyx_v_p_next]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + __pyx_t_7 = (((__pyx_v_Xf[__pyx_v_p_next]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); __pyx_t_6 = __pyx_t_7; __pyx_L21_bool_binop_done:; if (!__pyx_t_6) break; - /* "_splitter.pyx":1235 + /* "stpredictions/models/OK3/_splitter.pyx":1235 * while (p_next < end and * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): * p = p_next # <<<<<<<<<<<<<< @@ -11612,7 +11426,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_p = __pyx_v_p_next; - /* "_splitter.pyx":1236 + /* "stpredictions/models/OK3/_splitter.pyx":1236 * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): * p = p_next * if p + 1 != end_negative: # <<<<<<<<<<<<<< @@ -11622,7 +11436,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = (((__pyx_v_p + 1) != __pyx_v_end_negative) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1237 + /* "stpredictions/models/OK3/_splitter.pyx":1237 * p = p_next * if p + 1 != end_negative: * p_next = p + 1 # <<<<<<<<<<<<<< @@ -11631,7 +11445,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_p_next = (__pyx_v_p + 1); - /* "_splitter.pyx":1236 + /* "stpredictions/models/OK3/_splitter.pyx":1236 * Xf[p_next] <= Xf[p] + FEATURE_THRESHOLD): * p = p_next * if p + 1 != end_negative: # <<<<<<<<<<<<<< @@ -11641,7 +11455,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 goto __pyx_L23; } - /* "_splitter.pyx":1239 + /* "stpredictions/models/OK3/_splitter.pyx":1239 * p_next = p + 1 * else: * p_next = start_positive # <<<<<<<<<<<<<< @@ -11654,7 +11468,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_L23:; } - /* "_splitter.pyx":1244 + /* "stpredictions/models/OK3/_splitter.pyx":1244 * # (p_next >= end) or (X[samples[p_next], current.feature] > * # X[samples[p], current.feature]) * p_prev = p # <<<<<<<<<<<<<< @@ -11663,7 +11477,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_p_prev = __pyx_v_p; - /* "_splitter.pyx":1245 + /* "stpredictions/models/OK3/_splitter.pyx":1245 * # X[samples[p], current.feature]) * p_prev = p * p = p_next # <<<<<<<<<<<<<< @@ -11672,7 +11486,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_p = __pyx_v_p_next; - /* "_splitter.pyx":1250 + /* "stpredictions/models/OK3/_splitter.pyx":1250 * * * if p < end: # <<<<<<<<<<<<<< @@ -11682,7 +11496,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = ((__pyx_v_p < __pyx_v_end) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1251 + /* "stpredictions/models/OK3/_splitter.pyx":1251 * * if p < end: * current.pos = p # <<<<<<<<<<<<<< @@ -11691,7 +11505,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_current.pos = __pyx_v_p; - /* "_splitter.pyx":1254 + /* "stpredictions/models/OK3/_splitter.pyx":1254 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -11705,7 +11519,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 goto __pyx_L26_bool_binop_done; } - /* "_splitter.pyx":1255 + /* "stpredictions/models/OK3/_splitter.pyx":1255 * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or * ((end - current.pos) < min_samples_leaf)): # <<<<<<<<<<<<<< @@ -11716,7 +11530,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = __pyx_t_7; __pyx_L26_bool_binop_done:; - /* "_splitter.pyx":1254 + /* "stpredictions/models/OK3/_splitter.pyx":1254 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -11725,7 +11539,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ if (__pyx_t_6) { - /* "_splitter.pyx":1256 + /* "stpredictions/models/OK3/_splitter.pyx":1256 * if (((current.pos - start) < min_samples_leaf) or * ((end - current.pos) < min_samples_leaf)): * continue # <<<<<<<<<<<<<< @@ -11734,7 +11548,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ goto __pyx_L16_continue; - /* "_splitter.pyx":1254 + /* "stpredictions/models/OK3/_splitter.pyx":1254 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -11743,16 +11557,16 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ } - /* "_splitter.pyx":1258 + /* "stpredictions/models/OK3/_splitter.pyx":1258 * continue * * self.criterion.update(current.pos) # <<<<<<<<<<<<<< * * # Reject if min_weight_leaf is not satisfied */ - __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1258, __pyx_L1_error) + __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1258, __pyx_L1_error) - /* "_splitter.pyx":1261 + /* "stpredictions/models/OK3/_splitter.pyx":1261 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -11766,7 +11580,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 goto __pyx_L29_bool_binop_done; } - /* "_splitter.pyx":1262 + /* "stpredictions/models/OK3/_splitter.pyx":1262 * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or * (self.criterion.weighted_n_right < min_weight_leaf)): # <<<<<<<<<<<<<< @@ -11777,7 +11591,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = __pyx_t_7; __pyx_L29_bool_binop_done:; - /* "_splitter.pyx":1261 + /* "stpredictions/models/OK3/_splitter.pyx":1261 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -11786,7 +11600,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ if (__pyx_t_6) { - /* "_splitter.pyx":1263 + /* "stpredictions/models/OK3/_splitter.pyx":1263 * if ((self.criterion.weighted_n_left < min_weight_leaf) or * (self.criterion.weighted_n_right < min_weight_leaf)): * continue # <<<<<<<<<<<<<< @@ -11795,7 +11609,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ goto __pyx_L16_continue; - /* "_splitter.pyx":1261 + /* "stpredictions/models/OK3/_splitter.pyx":1261 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -11804,16 +11618,16 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ } - /* "_splitter.pyx":1265 + /* "stpredictions/models/OK3/_splitter.pyx":1265 * continue * * current_proxy_improvement = self.criterion.proxy_impurity_improvement() # <<<<<<<<<<<<<< * * if current_proxy_improvement > best_proxy_improvement: */ - __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); + __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); - /* "_splitter.pyx":1267 + /* "stpredictions/models/OK3/_splitter.pyx":1267 * current_proxy_improvement = self.criterion.proxy_impurity_improvement() * * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< @@ -11823,7 +11637,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1268 + /* "stpredictions/models/OK3/_splitter.pyx":1268 * * if current_proxy_improvement > best_proxy_improvement: * best_proxy_improvement = current_proxy_improvement # <<<<<<<<<<<<<< @@ -11832,7 +11646,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement; - /* "_splitter.pyx":1270 + /* "stpredictions/models/OK3/_splitter.pyx":1270 * best_proxy_improvement = current_proxy_improvement * # sum of halves used to avoid infinite values * current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0 # <<<<<<<<<<<<<< @@ -11841,7 +11655,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_current.threshold = (((__pyx_v_Xf[__pyx_v_p_prev]) / 2.0) + ((__pyx_v_Xf[__pyx_v_p]) / 2.0)); - /* "_splitter.pyx":1272 + /* "stpredictions/models/OK3/_splitter.pyx":1272 * current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0 * * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< @@ -11855,32 +11669,32 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 goto __pyx_L33_bool_binop_done; } - /* "_splitter.pyx":1273 + /* "stpredictions/models/OK3/_splitter.pyx":1273 * * if ((current.threshold == Xf[p]) or * (current.threshold == INFINITY) or # <<<<<<<<<<<<<< * (current.threshold == -INFINITY)): * current.threshold = Xf[p_prev] */ - __pyx_t_7 = ((__pyx_v_current.threshold == __pyx_v_9_splitter_INFINITY) != 0); + __pyx_t_7 = ((__pyx_v_current.threshold == __pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY) != 0); if (!__pyx_t_7) { } else { __pyx_t_6 = __pyx_t_7; goto __pyx_L33_bool_binop_done; } - /* "_splitter.pyx":1274 + /* "stpredictions/models/OK3/_splitter.pyx":1274 * if ((current.threshold == Xf[p]) or * (current.threshold == INFINITY) or * (current.threshold == -INFINITY)): # <<<<<<<<<<<<<< * current.threshold = Xf[p_prev] * */ - __pyx_t_7 = ((__pyx_v_current.threshold == (-__pyx_v_9_splitter_INFINITY)) != 0); + __pyx_t_7 = ((__pyx_v_current.threshold == (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY)) != 0); __pyx_t_6 = __pyx_t_7; __pyx_L33_bool_binop_done:; - /* "_splitter.pyx":1272 + /* "stpredictions/models/OK3/_splitter.pyx":1272 * current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0 * * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< @@ -11889,7 +11703,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ if (__pyx_t_6) { - /* "_splitter.pyx":1275 + /* "stpredictions/models/OK3/_splitter.pyx":1275 * (current.threshold == INFINITY) or * (current.threshold == -INFINITY)): * current.threshold = Xf[p_prev] # <<<<<<<<<<<<<< @@ -11898,7 +11712,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_current.threshold = (__pyx_v_Xf[__pyx_v_p_prev]); - /* "_splitter.pyx":1272 + /* "stpredictions/models/OK3/_splitter.pyx":1272 * current.threshold = Xf[p_prev] / 2.0 + Xf[p] / 2.0 * * if ((current.threshold == Xf[p]) or # <<<<<<<<<<<<<< @@ -11907,7 +11721,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ } - /* "_splitter.pyx":1277 + /* "stpredictions/models/OK3/_splitter.pyx":1277 * current.threshold = Xf[p_prev] * * best = current # <<<<<<<<<<<<<< @@ -11916,7 +11730,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ __pyx_v_best = __pyx_v_current; - /* "_splitter.pyx":1267 + /* "stpredictions/models/OK3/_splitter.pyx":1267 * current_proxy_improvement = self.criterion.proxy_impurity_improvement() * * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< @@ -11925,7 +11739,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ } - /* "_splitter.pyx":1250 + /* "stpredictions/models/OK3/_splitter.pyx":1250 * * * if p < end: # <<<<<<<<<<<<<< @@ -11941,7 +11755,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_L8:; } - /* "_splitter.pyx":1280 + /* "stpredictions/models/OK3/_splitter.pyx":1280 * * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: # <<<<<<<<<<<<<< @@ -11951,61 +11765,61 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_t_6 = ((__pyx_v_best.pos < __pyx_v_end) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1281 + /* "stpredictions/models/OK3/_splitter.pyx":1281 * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: * self.extract_nnz(best.feature, &end_negative, &start_positive, # <<<<<<<<<<<<<< * &is_samples_sorted) * */ - __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); - /* "_splitter.pyx":1284 + /* "stpredictions/models/OK3/_splitter.pyx":1284 * &is_samples_sorted) * * self._partition(best.threshold, end_negative, start_positive, # <<<<<<<<<<<<<< * best.pos) * */ - (void)(__pyx_f_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.threshold, __pyx_v_end_negative, __pyx_v_start_positive, __pyx_v_best.pos)); + (void)(__pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.threshold, __pyx_v_end_negative, __pyx_v_start_positive, __pyx_v_best.pos)); - /* "_splitter.pyx":1287 + /* "stpredictions/models/OK3/_splitter.pyx":1287 * best.pos) * * self.criterion.reset() # <<<<<<<<<<<<<< * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) */ - __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1287, __pyx_L1_error) + __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1287, __pyx_L1_error) - /* "_splitter.pyx":1288 + /* "stpredictions/models/OK3/_splitter.pyx":1288 * * self.criterion.reset() * self.criterion.update(best.pos) # <<<<<<<<<<<<<< * best.improvement = self.criterion.impurity_improvement(impurity) * self.criterion.children_impurity(&best.impurity_left, */ - __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1288, __pyx_L1_error) + __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1288, __pyx_L1_error) - /* "_splitter.pyx":1289 + /* "stpredictions/models/OK3/_splitter.pyx":1289 * self.criterion.reset() * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) # <<<<<<<<<<<<<< * self.criterion.children_impurity(&best.impurity_left, * &best.impurity_right) */ - __pyx_v_best.improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); + __pyx_v_best.improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); - /* "_splitter.pyx":1290 + /* "stpredictions/models/OK3/_splitter.pyx":1290 * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) * self.criterion.children_impurity(&best.impurity_left, # <<<<<<<<<<<<<< * &best.impurity_right) * */ - ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); - /* "_splitter.pyx":1280 + /* "stpredictions/models/OK3/_splitter.pyx":1280 * * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: # <<<<<<<<<<<<<< @@ -12014,25 +11828,25 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ } - /* "_splitter.pyx":1296 + /* "stpredictions/models/OK3/_splitter.pyx":1296 * # element in features[:n_known_constants] must be preserved for sibling * # and child nodes * memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) # <<<<<<<<<<<<<< * * # Copy newly found constant features */ - (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants))); + (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)) * __pyx_v_n_known_constants))); - /* "_splitter.pyx":1299 + /* "stpredictions/models/OK3/_splitter.pyx":1299 * * # Copy newly found constant features * memcpy(constant_features + n_known_constants, # <<<<<<<<<<<<<< * features + n_known_constants, * sizeof(SIZE_t) * n_found_constants) */ - (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants))); + (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)) * __pyx_v_n_found_constants))); - /* "_splitter.pyx":1304 + /* "stpredictions/models/OK3/_splitter.pyx":1304 * * # Return values * split[0] = best # <<<<<<<<<<<<<< @@ -12041,7 +11855,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ (__pyx_v_split[0]) = __pyx_v_best; - /* "_splitter.pyx":1305 + /* "stpredictions/models/OK3/_splitter.pyx":1305 * # Return values * split[0] = best * n_constant_features[0] = n_total_constants # <<<<<<<<<<<<<< @@ -12050,7 +11864,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants; - /* "_splitter.pyx":1306 + /* "stpredictions/models/OK3/_splitter.pyx":1306 * split[0] = best * n_constant_features[0] = n_total_constants * return 0 # <<<<<<<<<<<<<< @@ -12060,7 +11874,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 __pyx_r = 0; goto __pyx_L0; - /* "_splitter.pyx":1090 + /* "stpredictions/models/OK3/_splitter.pyx":1090 * self.random_state), self.__getstate__()) * * cdef int node_split(self, double impurity, SplitRecord* split, # <<<<<<<<<<<<<< @@ -12074,7 +11888,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif - __Pyx_AddTraceback("_splitter.BestSparseSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.BestSparseSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif @@ -12084,7 +11898,7 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 return __pyx_r; } -/* "_splitter.pyx":1312 +/* "stpredictions/models/OK3/_splitter.pyx":1312 * """Splitter for finding a random split, using the sparse data.""" * * def __reduce__(self): # <<<<<<<<<<<<<< @@ -12093,19 +11907,19 @@ static int __pyx_f_9_splitter_18BestSparseSplitter_node_split(struct __pyx_obj_9 */ /* Python wrapper */ -static PyObject *__pyx_pw_9_splitter_20RandomSparseSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/ -static PyObject *__pyx_pw_9_splitter_20RandomSparseSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/ +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0); - __pyx_r = __pyx_pf_9_splitter_20RandomSparseSplitter___reduce__(((struct __pyx_obj_9_splitter_RandomSparseSplitter *)__pyx_v_self)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter___reduce__(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_9_splitter_20RandomSparseSplitter___reduce__(struct __pyx_obj_9_splitter_RandomSparseSplitter *__pyx_v_self) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter___reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_v_self) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -12117,7 +11931,7 @@ static PyObject *__pyx_pf_9_splitter_20RandomSparseSplitter___reduce__(struct __ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__reduce__", 0); - /* "_splitter.pyx":1313 + /* "stpredictions/models/OK3/_splitter.pyx":1313 * * def __reduce__(self): * return 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__pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.RandomSparseSplitter.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __Pyx_XGIVEREF(__pyx_r); @@ -12250,7 +12064,7 @@ static PyObject *__pyx_pf_9_splitter_20RandomSparseSplitter___reduce__(struct __ return __pyx_r; } -/* "_splitter.pyx":1319 +/* "stpredictions/models/OK3/_splitter.pyx":1319 * self.random_state), self.__getstate__()) * * cdef int node_split(self, double impurity, SplitRecord* split, # <<<<<<<<<<<<<< @@ -12258,57 +12072,57 @@ static PyObject *__pyx_pf_9_splitter_20RandomSparseSplitter___reduce__(struct __ * """Find a random split on node samples[start:end], using sparse features */ -static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj_9_splitter_RandomSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features) { - 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__pyx_f_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *__pyx_v_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_n_constant_features) { + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_X_indices; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_X_indptr; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_X_data; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_constant_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_Xf; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_sorted_samples; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_index_to_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf; double __pyx_v_min_weight_leaf; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t *__pyx_v_random_state; - struct __pyx_t_9_splitter_SplitRecord __pyx_v_best; - struct __pyx_t_9_splitter_SplitRecord __pyx_v_current; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t *__pyx_v_random_state; + struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_best; + struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_current; double __pyx_v_current_proxy_improvement; double __pyx_v_best_proxy_improvement; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_current_feature_value; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_i; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_j; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_visited_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_found_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_drawn_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_known_constants; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_total_constants; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_min_feature_value; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_max_feature_value; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_current_feature_value; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_f_i; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_f_j; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_p; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_visited_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_found_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_drawn_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_known_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_total_constants; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_min_feature_value; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_max_feature_value; int __pyx_v_is_samples_sorted; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start_positive; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end_negative; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start_positive; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end_negative; int __pyx_r; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_1; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2; - __pyx_t_7sklearn_4tree_5_tree_INT32_t *__pyx_t_3; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_t_4; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_2; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_t_3; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_t_4; double __pyx_t_5; int __pyx_t_6; int __pyx_t_7; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_8; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_9; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_8; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_9; int __pyx_t_10; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "_splitter.pyx":1327 + /* "stpredictions/models/OK3/_splitter.pyx":1327 * """ * # Find the best split * cdef SIZE_t* samples = self.samples # <<<<<<<<<<<<<< @@ -12318,7 +12132,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.samples; __pyx_v_samples = __pyx_t_1; - /* "_splitter.pyx":1328 + /* "stpredictions/models/OK3/_splitter.pyx":1328 * # Find the best split * cdef SIZE_t* samples = self.samples * cdef SIZE_t start = self.start # <<<<<<<<<<<<<< @@ -12328,7 +12142,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.start; __pyx_v_start = __pyx_t_2; - /* "_splitter.pyx":1329 + /* "stpredictions/models/OK3/_splitter.pyx":1329 * cdef SIZE_t* samples = self.samples * cdef SIZE_t start = self.start * cdef SIZE_t end = self.end # <<<<<<<<<<<<<< @@ -12338,7 +12152,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.end; __pyx_v_end = __pyx_t_2; - /* "_splitter.pyx":1331 + /* "stpredictions/models/OK3/_splitter.pyx":1331 * cdef SIZE_t end = self.end * * cdef INT32_t* X_indices = self.X_indices # <<<<<<<<<<<<<< @@ -12348,7 +12162,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_3 = __pyx_v_self->__pyx_base.X_indices; __pyx_v_X_indices = __pyx_t_3; - /* "_splitter.pyx":1332 + /* "stpredictions/models/OK3/_splitter.pyx":1332 * * cdef INT32_t* X_indices = self.X_indices * cdef INT32_t* X_indptr = self.X_indptr # <<<<<<<<<<<<<< @@ -12358,7 +12172,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_3 = __pyx_v_self->__pyx_base.X_indptr; __pyx_v_X_indptr = __pyx_t_3; - /* "_splitter.pyx":1333 + /* "stpredictions/models/OK3/_splitter.pyx":1333 * cdef INT32_t* X_indices = self.X_indices * cdef INT32_t* X_indptr = self.X_indptr * cdef DTYPE_t* X_data = self.X_data # <<<<<<<<<<<<<< @@ -12368,7 +12182,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_4 = __pyx_v_self->__pyx_base.X_data; __pyx_v_X_data = __pyx_t_4; - /* "_splitter.pyx":1335 + /* "stpredictions/models/OK3/_splitter.pyx":1335 * cdef DTYPE_t* X_data = self.X_data * * cdef SIZE_t* features = self.features # <<<<<<<<<<<<<< @@ -12378,7 +12192,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.features; __pyx_v_features = __pyx_t_1; - /* "_splitter.pyx":1336 + /* "stpredictions/models/OK3/_splitter.pyx":1336 * * cdef SIZE_t* features = self.features * cdef SIZE_t* constant_features = self.constant_features # <<<<<<<<<<<<<< @@ -12388,7 +12202,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.constant_features; __pyx_v_constant_features = __pyx_t_1; - /* "_splitter.pyx":1337 + /* "stpredictions/models/OK3/_splitter.pyx":1337 * cdef SIZE_t* features = self.features * cdef SIZE_t* constant_features = self.constant_features * cdef SIZE_t n_features = self.n_features # <<<<<<<<<<<<<< @@ -12398,7 +12212,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_features; __pyx_v_n_features = __pyx_t_2; - /* "_splitter.pyx":1339 + /* "stpredictions/models/OK3/_splitter.pyx":1339 * cdef SIZE_t n_features = self.n_features * * cdef DTYPE_t* Xf = self.feature_values # <<<<<<<<<<<<<< @@ -12408,7 +12222,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_4 = __pyx_v_self->__pyx_base.__pyx_base.feature_values; __pyx_v_Xf = __pyx_t_4; - /* "_splitter.pyx":1340 + /* "stpredictions/models/OK3/_splitter.pyx":1340 * * cdef DTYPE_t* Xf = self.feature_values * cdef SIZE_t* sorted_samples = self.sorted_samples # <<<<<<<<<<<<<< @@ -12418,7 +12232,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_1 = __pyx_v_self->__pyx_base.sorted_samples; __pyx_v_sorted_samples = __pyx_t_1; - /* "_splitter.pyx":1341 + /* "stpredictions/models/OK3/_splitter.pyx":1341 * cdef DTYPE_t* Xf = self.feature_values * cdef SIZE_t* sorted_samples = self.sorted_samples * cdef SIZE_t* index_to_samples = self.index_to_samples # <<<<<<<<<<<<<< @@ -12428,7 +12242,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_1 = __pyx_v_self->__pyx_base.index_to_samples; __pyx_v_index_to_samples = __pyx_t_1; - /* "_splitter.pyx":1342 + /* "stpredictions/models/OK3/_splitter.pyx":1342 * cdef SIZE_t* sorted_samples = self.sorted_samples * cdef SIZE_t* index_to_samples = self.index_to_samples * cdef SIZE_t max_features = self.max_features # <<<<<<<<<<<<<< @@ -12438,7 +12252,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.max_features; __pyx_v_max_features = __pyx_t_2; - /* "_splitter.pyx":1343 + /* "stpredictions/models/OK3/_splitter.pyx":1343 * cdef SIZE_t* index_to_samples = self.index_to_samples * cdef SIZE_t max_features = self.max_features * cdef SIZE_t min_samples_leaf = self.min_samples_leaf # <<<<<<<<<<<<<< @@ -12448,7 +12262,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.min_samples_leaf; __pyx_v_min_samples_leaf = __pyx_t_2; - /* "_splitter.pyx":1344 + /* "stpredictions/models/OK3/_splitter.pyx":1344 * cdef SIZE_t max_features = self.max_features * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< @@ -12458,7 +12272,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_5 = __pyx_v_self->__pyx_base.__pyx_base.min_weight_leaf; __pyx_v_min_weight_leaf = __pyx_t_5; - /* "_splitter.pyx":1345 + /* "stpredictions/models/OK3/_splitter.pyx":1345 * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf * cdef UINT32_t* random_state = &self.rand_r_state # <<<<<<<<<<<<<< @@ -12467,34 +12281,34 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_random_state = (&__pyx_v_self->__pyx_base.__pyx_base.rand_r_state); - /* "_splitter.pyx":1348 + /* "stpredictions/models/OK3/_splitter.pyx":1348 * * cdef SplitRecord best, current * _init_split(&best, end) # <<<<<<<<<<<<<< * cdef double current_proxy_improvement = - INFINITY * cdef double best_proxy_improvement = - INFINITY */ - __pyx_f_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); + __pyx_f_13stpredictions_6models_3OK3_9_splitter__init_split((&__pyx_v_best), __pyx_v_end); - /* "_splitter.pyx":1349 + /* "stpredictions/models/OK3/_splitter.pyx":1349 * cdef SplitRecord best, current * _init_split(&best, end) * cdef double current_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< * cdef double best_proxy_improvement = - INFINITY * */ - __pyx_v_current_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + __pyx_v_current_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - /* "_splitter.pyx":1350 + /* "stpredictions/models/OK3/_splitter.pyx":1350 * _init_split(&best, end) * cdef double current_proxy_improvement = - INFINITY * cdef double best_proxy_improvement = - INFINITY # <<<<<<<<<<<<<< * * cdef DTYPE_t current_feature_value */ - __pyx_v_best_proxy_improvement = (-__pyx_v_9_splitter_INFINITY); + __pyx_v_best_proxy_improvement = (-__pyx_v_13stpredictions_6models_3OK3_9_splitter_INFINITY); - /* "_splitter.pyx":1354 + /* "stpredictions/models/OK3/_splitter.pyx":1354 * cdef DTYPE_t current_feature_value * * cdef SIZE_t f_i = n_features # <<<<<<<<<<<<<< @@ -12503,7 +12317,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_f_i = __pyx_v_n_features; - /* "_splitter.pyx":1356 + /* "stpredictions/models/OK3/_splitter.pyx":1356 * cdef SIZE_t f_i = n_features * cdef SIZE_t f_j, p * cdef SIZE_t n_visited_features = 0 # <<<<<<<<<<<<<< @@ -12512,7 +12326,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_n_visited_features = 0; - /* "_splitter.pyx":1358 + /* "stpredictions/models/OK3/_splitter.pyx":1358 * cdef SIZE_t n_visited_features = 0 * # Number of features discovered to be constant during the split search * cdef SIZE_t n_found_constants = 0 # <<<<<<<<<<<<<< @@ -12521,7 +12335,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_n_found_constants = 0; - /* "_splitter.pyx":1360 + /* "stpredictions/models/OK3/_splitter.pyx":1360 * cdef SIZE_t n_found_constants = 0 * # Number of features known to be constant and drawn without replacement * cdef SIZE_t n_drawn_constants = 0 # <<<<<<<<<<<<<< @@ -12530,7 +12344,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_n_drawn_constants = 0; - /* "_splitter.pyx":1361 + /* "stpredictions/models/OK3/_splitter.pyx":1361 * # Number of features known to be constant and drawn without replacement * cdef SIZE_t n_drawn_constants = 0 * cdef SIZE_t n_known_constants = n_constant_features[0] # <<<<<<<<<<<<<< @@ -12539,7 +12353,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]); - /* "_splitter.pyx":1363 + /* "stpredictions/models/OK3/_splitter.pyx":1363 * cdef SIZE_t n_known_constants = n_constant_features[0] * # n_total_constants = n_known_constants + n_found_constants * cdef SIZE_t n_total_constants = n_known_constants # <<<<<<<<<<<<<< @@ -12548,7 +12362,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_n_total_constants = __pyx_v_n_known_constants; - /* "_splitter.pyx":1369 + /* "stpredictions/models/OK3/_splitter.pyx":1369 * cdef DTYPE_t max_feature_value * * cdef bint is_samples_sorted = 0 # indicate that sorted_samples is # <<<<<<<<<<<<<< @@ -12557,7 +12371,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_is_samples_sorted = 0; - /* "_splitter.pyx":1386 + /* "stpredictions/models/OK3/_splitter.pyx":1386 * # newly discovered constant features to spare computation on descendant * # nodes. * while (f_i > n_total_constants and # Stop early if remaining features # <<<<<<<<<<<<<< @@ -12572,7 +12386,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj goto __pyx_L5_bool_binop_done; } - /* "_splitter.pyx":1388 + /* "stpredictions/models/OK3/_splitter.pyx":1388 * while (f_i > n_total_constants and # Stop early if remaining features * # are constant * (n_visited_features < max_features or # <<<<<<<<<<<<<< @@ -12586,7 +12400,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj goto __pyx_L5_bool_binop_done; } - /* "_splitter.pyx":1390 + /* "stpredictions/models/OK3/_splitter.pyx":1390 * (n_visited_features < max_features or * # At least one drawn features must be non constant * n_visited_features <= n_found_constants + n_drawn_constants)): # <<<<<<<<<<<<<< @@ -12598,7 +12412,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_L5_bool_binop_done:; if (!__pyx_t_6) break; - /* "_splitter.pyx":1392 + /* "stpredictions/models/OK3/_splitter.pyx":1392 * n_visited_features <= n_found_constants + n_drawn_constants)): * * n_visited_features += 1 # <<<<<<<<<<<<<< @@ -12607,16 +12421,16 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1); - /* "_splitter.pyx":1406 + /* "stpredictions/models/OK3/_splitter.pyx":1406 * * # Draw a feature at random * f_j = rand_int(n_drawn_constants, f_i - n_found_constants, # <<<<<<<<<<<<<< * random_state) * */ - __pyx_v_f_j = __pyx_f_7sklearn_4tree_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); + __pyx_v_f_j = __pyx_f_13stpredictions_6models_3OK3_6_utils_rand_int(__pyx_v_n_drawn_constants, (__pyx_v_f_i - __pyx_v_n_found_constants), __pyx_v_random_state); - /* "_splitter.pyx":1409 + /* "stpredictions/models/OK3/_splitter.pyx":1409 * random_state) * * if f_j < n_known_constants: # <<<<<<<<<<<<<< @@ -12626,7 +12440,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1411 + /* "stpredictions/models/OK3/_splitter.pyx":1411 * if f_j < n_known_constants: * # f_j in the interval [n_drawn_constants, n_known_constants[ * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] # <<<<<<<<<<<<<< @@ -12638,7 +12452,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2; (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_t_8; - /* "_splitter.pyx":1413 + /* "stpredictions/models/OK3/_splitter.pyx":1413 * features[f_j], features[n_drawn_constants] = features[n_drawn_constants], features[f_j] * * n_drawn_constants += 1 # <<<<<<<<<<<<<< @@ -12647,7 +12461,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1); - /* "_splitter.pyx":1409 + /* "stpredictions/models/OK3/_splitter.pyx":1409 * random_state) * * if f_j < n_known_constants: # <<<<<<<<<<<<<< @@ -12657,7 +12471,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj goto __pyx_L8; } - /* "_splitter.pyx":1417 + /* "stpredictions/models/OK3/_splitter.pyx":1417 * else: * # f_j in the interval [n_known_constants, f_i - n_found_constants[ * f_j += n_found_constants # <<<<<<<<<<<<<< @@ -12667,7 +12481,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj /*else*/ { __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants); - /* "_splitter.pyx":1420 + /* "stpredictions/models/OK3/_splitter.pyx":1420 * # f_j in the interval [n_total_constants, f_i[ * * current.feature = features[f_j] # <<<<<<<<<<<<<< @@ -12676,16 +12490,16 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]); - /* "_splitter.pyx":1422 + /* "stpredictions/models/OK3/_splitter.pyx":1422 * current.feature = features[f_j] * * self.extract_nnz(current.feature, # <<<<<<<<<<<<<< * &end_negative, &start_positive, * &is_samples_sorted) */ - __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); - /* "_splitter.pyx":1427 + /* "stpredictions/models/OK3/_splitter.pyx":1427 * * # Add one or two zeros in Xf, if there is any * if end_negative < start_positive: # <<<<<<<<<<<<<< @@ -12695,7 +12509,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_end_negative < __pyx_v_start_positive) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1428 + /* "stpredictions/models/OK3/_splitter.pyx":1428 * # Add one or two zeros in Xf, if there is any * if end_negative < start_positive: * start_positive -= 1 # <<<<<<<<<<<<<< @@ -12704,7 +12518,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_start_positive = (__pyx_v_start_positive - 1); - /* "_splitter.pyx":1429 + /* "stpredictions/models/OK3/_splitter.pyx":1429 * if end_negative < start_positive: * start_positive -= 1 * Xf[start_positive] = 0. # <<<<<<<<<<<<<< @@ -12713,7 +12527,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ (__pyx_v_Xf[__pyx_v_start_positive]) = 0.; - /* "_splitter.pyx":1431 + /* "stpredictions/models/OK3/_splitter.pyx":1431 * Xf[start_positive] = 0. * * if end_negative != start_positive: # <<<<<<<<<<<<<< @@ -12723,7 +12537,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_end_negative != __pyx_v_start_positive) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1432 + /* "stpredictions/models/OK3/_splitter.pyx":1432 * * if end_negative != start_positive: * Xf[end_negative] = 0. # <<<<<<<<<<<<<< @@ -12732,7 +12546,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ (__pyx_v_Xf[__pyx_v_end_negative]) = 0.; - /* "_splitter.pyx":1433 + /* "stpredictions/models/OK3/_splitter.pyx":1433 * if end_negative != start_positive: * Xf[end_negative] = 0. * end_negative += 1 # <<<<<<<<<<<<<< @@ -12741,7 +12555,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_end_negative = (__pyx_v_end_negative + 1); - /* "_splitter.pyx":1431 + /* "stpredictions/models/OK3/_splitter.pyx":1431 * Xf[start_positive] = 0. * * if end_negative != start_positive: # <<<<<<<<<<<<<< @@ -12750,7 +12564,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ } - /* "_splitter.pyx":1427 + /* "stpredictions/models/OK3/_splitter.pyx":1427 * * # Add one or two zeros in Xf, if there is any * if end_negative < start_positive: # <<<<<<<<<<<<<< @@ -12759,7 +12573,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ } - /* "_splitter.pyx":1436 + /* "stpredictions/models/OK3/_splitter.pyx":1436 * * # Find min, max in Xf[start:end_negative] * min_feature_value = Xf[start] # <<<<<<<<<<<<<< @@ -12768,7 +12582,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_min_feature_value = (__pyx_v_Xf[__pyx_v_start]); - /* "_splitter.pyx":1437 + /* "stpredictions/models/OK3/_splitter.pyx":1437 * # Find min, max in Xf[start:end_negative] * min_feature_value = Xf[start] * max_feature_value = min_feature_value # <<<<<<<<<<<<<< @@ -12777,7 +12591,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_max_feature_value = __pyx_v_min_feature_value; - /* "_splitter.pyx":1439 + /* "stpredictions/models/OK3/_splitter.pyx":1439 * max_feature_value = min_feature_value * * for p in range(start, end_negative): # <<<<<<<<<<<<<< @@ -12789,7 +12603,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj for (__pyx_t_9 = __pyx_v_start; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { __pyx_v_p = __pyx_t_9; - /* "_splitter.pyx":1440 + /* "stpredictions/models/OK3/_splitter.pyx":1440 * * for p in range(start, end_negative): * current_feature_value = Xf[p] # <<<<<<<<<<<<<< @@ -12798,7 +12612,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_current_feature_value = (__pyx_v_Xf[__pyx_v_p]); - /* "_splitter.pyx":1442 + /* "stpredictions/models/OK3/_splitter.pyx":1442 * current_feature_value = Xf[p] * * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< @@ -12808,7 +12622,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1443 + /* "stpredictions/models/OK3/_splitter.pyx":1443 * * if current_feature_value < min_feature_value: * min_feature_value = current_feature_value # <<<<<<<<<<<<<< @@ -12817,7 +12631,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_min_feature_value = __pyx_v_current_feature_value; - /* "_splitter.pyx":1442 + /* "stpredictions/models/OK3/_splitter.pyx":1442 * current_feature_value = Xf[p] * * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< @@ -12827,7 +12641,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj goto __pyx_L13; } - /* "_splitter.pyx":1444 + /* "stpredictions/models/OK3/_splitter.pyx":1444 * if current_feature_value < min_feature_value: * min_feature_value = current_feature_value * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< @@ -12837,7 +12651,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1445 + /* "stpredictions/models/OK3/_splitter.pyx":1445 * min_feature_value = current_feature_value * elif current_feature_value > max_feature_value: * max_feature_value = current_feature_value # <<<<<<<<<<<<<< @@ -12846,7 +12660,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_max_feature_value = __pyx_v_current_feature_value; - /* "_splitter.pyx":1444 + /* "stpredictions/models/OK3/_splitter.pyx":1444 * if current_feature_value < min_feature_value: * min_feature_value = current_feature_value * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< @@ -12857,7 +12671,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_L13:; } - /* "_splitter.pyx":1448 + /* "stpredictions/models/OK3/_splitter.pyx":1448 * * # Update min, max given Xf[start_positive:end] * for p in range(start_positive, end): # <<<<<<<<<<<<<< @@ -12869,7 +12683,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj for (__pyx_t_9 = __pyx_v_start_positive; __pyx_t_9 < __pyx_t_2; __pyx_t_9+=1) { __pyx_v_p = __pyx_t_9; - /* "_splitter.pyx":1449 + /* "stpredictions/models/OK3/_splitter.pyx":1449 * # Update min, max given Xf[start_positive:end] * for p in range(start_positive, end): * current_feature_value = Xf[p] # <<<<<<<<<<<<<< @@ -12878,7 +12692,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_current_feature_value = (__pyx_v_Xf[__pyx_v_p]); - /* "_splitter.pyx":1451 + /* "stpredictions/models/OK3/_splitter.pyx":1451 * current_feature_value = Xf[p] * * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< @@ -12888,7 +12702,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1452 + /* "stpredictions/models/OK3/_splitter.pyx":1452 * * if current_feature_value < min_feature_value: * min_feature_value = current_feature_value # <<<<<<<<<<<<<< @@ -12897,7 +12711,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_min_feature_value = __pyx_v_current_feature_value; - /* "_splitter.pyx":1451 + /* "stpredictions/models/OK3/_splitter.pyx":1451 * current_feature_value = Xf[p] * * if current_feature_value < min_feature_value: # <<<<<<<<<<<<<< @@ -12907,7 +12721,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj goto __pyx_L16; } - /* "_splitter.pyx":1453 + /* "stpredictions/models/OK3/_splitter.pyx":1453 * if current_feature_value < min_feature_value: * min_feature_value = current_feature_value * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< @@ -12917,7 +12731,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1454 + /* "stpredictions/models/OK3/_splitter.pyx":1454 * min_feature_value = current_feature_value * elif current_feature_value > max_feature_value: * max_feature_value = current_feature_value # <<<<<<<<<<<<<< @@ -12926,7 +12740,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_max_feature_value = __pyx_v_current_feature_value; - /* "_splitter.pyx":1453 + /* "stpredictions/models/OK3/_splitter.pyx":1453 * if current_feature_value < min_feature_value: * min_feature_value = current_feature_value * elif current_feature_value > max_feature_value: # <<<<<<<<<<<<<< @@ -12937,17 +12751,17 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_L16:; } - /* "_splitter.pyx":1456 + /* "stpredictions/models/OK3/_splitter.pyx":1456 * max_feature_value = current_feature_value * * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< * features[f_j] = features[n_total_constants] * features[n_total_constants] = current.feature */ - __pyx_t_6 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_9_splitter_FEATURE_THRESHOLD)) != 0); + __pyx_t_6 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_13stpredictions_6models_3OK3_9_splitter_FEATURE_THRESHOLD)) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1457 + /* "stpredictions/models/OK3/_splitter.pyx":1457 * * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: * features[f_j] = features[n_total_constants] # <<<<<<<<<<<<<< @@ -12956,7 +12770,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ (__pyx_v_features[__pyx_v_f_j]) = (__pyx_v_features[__pyx_v_n_total_constants]); - /* "_splitter.pyx":1458 + /* "stpredictions/models/OK3/_splitter.pyx":1458 * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: * features[f_j] = features[n_total_constants] * features[n_total_constants] = current.feature # <<<<<<<<<<<<<< @@ -12966,7 +12780,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_8 = __pyx_v_current.feature; (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_8; - /* "_splitter.pyx":1460 + /* "stpredictions/models/OK3/_splitter.pyx":1460 * features[n_total_constants] = current.feature * * n_found_constants += 1 # <<<<<<<<<<<<<< @@ -12975,7 +12789,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1); - /* "_splitter.pyx":1461 + /* "stpredictions/models/OK3/_splitter.pyx":1461 * * n_found_constants += 1 * n_total_constants += 1 # <<<<<<<<<<<<<< @@ -12984,7 +12798,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1); - /* "_splitter.pyx":1456 + /* "stpredictions/models/OK3/_splitter.pyx":1456 * max_feature_value = current_feature_value * * if max_feature_value <= min_feature_value + FEATURE_THRESHOLD: # <<<<<<<<<<<<<< @@ -12994,7 +12808,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj goto __pyx_L17; } - /* "_splitter.pyx":1464 + /* "stpredictions/models/OK3/_splitter.pyx":1464 * * else: * f_i -= 1 # <<<<<<<<<<<<<< @@ -13004,7 +12818,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj /*else*/ { __pyx_v_f_i = (__pyx_v_f_i - 1); - /* "_splitter.pyx":1465 + /* "stpredictions/models/OK3/_splitter.pyx":1465 * else: * f_i -= 1 * features[f_i], features[f_j] = features[f_j], features[f_i] # <<<<<<<<<<<<<< @@ -13016,16 +12830,16 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_8; (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_2; - /* "_splitter.pyx":1468 + /* "stpredictions/models/OK3/_splitter.pyx":1468 * * # Draw a random threshold * current.threshold = rand_uniform(min_feature_value, # <<<<<<<<<<<<<< * max_feature_value, * random_state) */ - __pyx_v_current.threshold = __pyx_f_7sklearn_4tree_6_utils_rand_uniform(__pyx_v_min_feature_value, __pyx_v_max_feature_value, __pyx_v_random_state); + __pyx_v_current.threshold = __pyx_f_13stpredictions_6models_3OK3_6_utils_rand_uniform(__pyx_v_min_feature_value, __pyx_v_max_feature_value, __pyx_v_random_state); - /* "_splitter.pyx":1472 + /* "stpredictions/models/OK3/_splitter.pyx":1472 * random_state) * * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< @@ -13035,7 +12849,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_current.threshold == __pyx_v_max_feature_value) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1473 + /* "stpredictions/models/OK3/_splitter.pyx":1473 * * if current.threshold == max_feature_value: * current.threshold = min_feature_value # <<<<<<<<<<<<<< @@ -13044,7 +12858,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_current.threshold = __pyx_v_min_feature_value; - /* "_splitter.pyx":1472 + /* "stpredictions/models/OK3/_splitter.pyx":1472 * random_state) * * if current.threshold == max_feature_value: # <<<<<<<<<<<<<< @@ -13053,16 +12867,16 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ } - /* "_splitter.pyx":1476 + /* "stpredictions/models/OK3/_splitter.pyx":1476 * * # Partition * current.pos = self._partition(current.threshold, # <<<<<<<<<<<<<< * end_negative, * start_positive, */ - __pyx_v_current.pos = __pyx_f_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.threshold, __pyx_v_end_negative, __pyx_v_start_positive, (__pyx_v_start_positive + ((__pyx_v_Xf[__pyx_v_start_positive]) == 0.))); + __pyx_v_current.pos = __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_current.threshold, __pyx_v_end_negative, __pyx_v_start_positive, (__pyx_v_start_positive + ((__pyx_v_Xf[__pyx_v_start_positive]) == 0.))); - /* "_splitter.pyx":1483 + /* "stpredictions/models/OK3/_splitter.pyx":1483 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -13076,7 +12890,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj goto __pyx_L20_bool_binop_done; } - /* "_splitter.pyx":1484 + /* "stpredictions/models/OK3/_splitter.pyx":1484 * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or * ((end - current.pos) < min_samples_leaf)): # <<<<<<<<<<<<<< @@ -13087,7 +12901,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = __pyx_t_7; __pyx_L20_bool_binop_done:; - /* "_splitter.pyx":1483 + /* "stpredictions/models/OK3/_splitter.pyx":1483 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -13096,7 +12910,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ if (__pyx_t_6) { - /* "_splitter.pyx":1485 + /* "stpredictions/models/OK3/_splitter.pyx":1485 * if (((current.pos - start) < min_samples_leaf) or * ((end - current.pos) < min_samples_leaf)): * continue # <<<<<<<<<<<<<< @@ -13105,7 +12919,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ goto __pyx_L3_continue; - /* "_splitter.pyx":1483 + /* "stpredictions/models/OK3/_splitter.pyx":1483 * * # Reject if min_samples_leaf is not guaranteed * if (((current.pos - start) < min_samples_leaf) or # <<<<<<<<<<<<<< @@ -13114,25 +12928,25 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ } - /* "_splitter.pyx":1488 + /* "stpredictions/models/OK3/_splitter.pyx":1488 * * # Evaluate split * self.criterion.reset() # <<<<<<<<<<<<<< * self.criterion.update(current.pos) * */ - __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1488, __pyx_L1_error) + __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1488, __pyx_L1_error) - /* "_splitter.pyx":1489 + /* "stpredictions/models/OK3/_splitter.pyx":1489 * # Evaluate split * self.criterion.reset() * self.criterion.update(current.pos) # <<<<<<<<<<<<<< * * # Reject if min_weight_leaf is not satisfied */ - __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1489, __pyx_L1_error) + __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_current.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1489, __pyx_L1_error) - /* "_splitter.pyx":1492 + /* "stpredictions/models/OK3/_splitter.pyx":1492 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -13146,7 +12960,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj goto __pyx_L23_bool_binop_done; } - /* "_splitter.pyx":1493 + /* "stpredictions/models/OK3/_splitter.pyx":1493 * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or * (self.criterion.weighted_n_right < min_weight_leaf)): # <<<<<<<<<<<<<< @@ -13157,7 +12971,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = __pyx_t_7; __pyx_L23_bool_binop_done:; - /* "_splitter.pyx":1492 + /* "stpredictions/models/OK3/_splitter.pyx":1492 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -13166,7 +12980,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ if (__pyx_t_6) { - /* "_splitter.pyx":1494 + /* "stpredictions/models/OK3/_splitter.pyx":1494 * if ((self.criterion.weighted_n_left < min_weight_leaf) or * (self.criterion.weighted_n_right < min_weight_leaf)): * continue # <<<<<<<<<<<<<< @@ -13175,7 +12989,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ goto __pyx_L3_continue; - /* "_splitter.pyx":1492 + /* "stpredictions/models/OK3/_splitter.pyx":1492 * * # Reject if min_weight_leaf is not satisfied * if ((self.criterion.weighted_n_left < min_weight_leaf) or # <<<<<<<<<<<<<< @@ -13184,16 +12998,16 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ } - /* "_splitter.pyx":1496 + /* "stpredictions/models/OK3/_splitter.pyx":1496 * continue * * current_proxy_improvement = self.criterion.proxy_impurity_improvement() # <<<<<<<<<<<<<< * * if current_proxy_improvement > best_proxy_improvement: */ - __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); + __pyx_v_current_proxy_improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->proxy_impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion); - /* "_splitter.pyx":1498 + /* "stpredictions/models/OK3/_splitter.pyx":1498 * current_proxy_improvement = self.criterion.proxy_impurity_improvement() * * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< @@ -13203,7 +13017,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_current_proxy_improvement > __pyx_v_best_proxy_improvement) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1499 + /* "stpredictions/models/OK3/_splitter.pyx":1499 * * if current_proxy_improvement > best_proxy_improvement: * best_proxy_improvement = current_proxy_improvement # <<<<<<<<<<<<<< @@ -13212,25 +13026,25 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_best_proxy_improvement = __pyx_v_current_proxy_improvement; - /* "_splitter.pyx":1500 + /* "stpredictions/models/OK3/_splitter.pyx":1500 * if current_proxy_improvement > best_proxy_improvement: * best_proxy_improvement = current_proxy_improvement * current.improvement = self.criterion.impurity_improvement(impurity) # <<<<<<<<<<<<<< * * self.criterion.children_impurity(¤t.impurity_left, */ - __pyx_v_current.improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); + __pyx_v_current.improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); - /* "_splitter.pyx":1502 + /* "stpredictions/models/OK3/_splitter.pyx":1502 * current.improvement = self.criterion.impurity_improvement(impurity) * * self.criterion.children_impurity(¤t.impurity_left, # <<<<<<<<<<<<<< * ¤t.impurity_right) * best = current */ - ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_current.impurity_left), (&__pyx_v_current.impurity_right)); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_current.impurity_left), (&__pyx_v_current.impurity_right)); - /* "_splitter.pyx":1504 + /* "stpredictions/models/OK3/_splitter.pyx":1504 * self.criterion.children_impurity(¤t.impurity_left, * ¤t.impurity_right) * best = current # <<<<<<<<<<<<<< @@ -13239,7 +13053,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ __pyx_v_best = __pyx_v_current; - /* "_splitter.pyx":1498 + /* "stpredictions/models/OK3/_splitter.pyx":1498 * current_proxy_improvement = self.criterion.proxy_impurity_improvement() * * if current_proxy_improvement > best_proxy_improvement: # <<<<<<<<<<<<<< @@ -13254,7 +13068,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_L3_continue:; } - /* "_splitter.pyx":1507 + /* "stpredictions/models/OK3/_splitter.pyx":1507 * * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: # <<<<<<<<<<<<<< @@ -13264,7 +13078,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_best.pos < __pyx_v_end) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1508 + /* "stpredictions/models/OK3/_splitter.pyx":1508 * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: * if current.feature != best.feature: # <<<<<<<<<<<<<< @@ -13274,25 +13088,25 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_t_6 = ((__pyx_v_current.feature != __pyx_v_best.feature) != 0); if (__pyx_t_6) { - /* "_splitter.pyx":1509 + /* "stpredictions/models/OK3/_splitter.pyx":1509 * if best.pos < end: * if current.feature != best.feature: * self.extract_nnz(best.feature, &end_negative, &start_positive, # <<<<<<<<<<<<<< * &is_samples_sorted) * */ - __pyx_f_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); + __pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_extract_nnz(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.feature, (&__pyx_v_end_negative), (&__pyx_v_start_positive), (&__pyx_v_is_samples_sorted)); - /* "_splitter.pyx":1512 + /* "stpredictions/models/OK3/_splitter.pyx":1512 * &is_samples_sorted) * * self._partition(best.threshold, end_negative, start_positive, # <<<<<<<<<<<<<< * best.pos) * */ - (void)(__pyx_f_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.threshold, __pyx_v_end_negative, __pyx_v_start_positive, __pyx_v_best.pos)); + (void)(__pyx_f_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter__partition(((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)__pyx_v_self), __pyx_v_best.threshold, __pyx_v_end_negative, __pyx_v_start_positive, __pyx_v_best.pos)); - /* "_splitter.pyx":1508 + /* "stpredictions/models/OK3/_splitter.pyx":1508 * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: * if current.feature != best.feature: # <<<<<<<<<<<<<< @@ -13301,43 +13115,43 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ } - /* "_splitter.pyx":1515 + /* "stpredictions/models/OK3/_splitter.pyx":1515 * best.pos) * * self.criterion.reset() # <<<<<<<<<<<<<< * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) */ - __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1515, __pyx_L1_error) + __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.__pyx_base.criterion); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1515, __pyx_L1_error) - /* "_splitter.pyx":1516 + /* "stpredictions/models/OK3/_splitter.pyx":1516 * * self.criterion.reset() * self.criterion.update(best.pos) # <<<<<<<<<<<<<< * best.improvement = self.criterion.impurity_improvement(impurity) * self.criterion.children_impurity(&best.impurity_left, */ - __pyx_t_10 = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1516, __pyx_L1_error) + __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_best.pos); if (unlikely(__pyx_t_10 == ((int)-1))) __PYX_ERR(0, 1516, __pyx_L1_error) - /* "_splitter.pyx":1517 + /* "stpredictions/models/OK3/_splitter.pyx":1517 * self.criterion.reset() * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) # <<<<<<<<<<<<<< * self.criterion.children_impurity(&best.impurity_left, * &best.impurity_right) */ - __pyx_v_best.improvement = ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); + __pyx_v_best.improvement = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.__pyx_base.criterion, __pyx_v_impurity); - /* "_splitter.pyx":1518 + /* "stpredictions/models/OK3/_splitter.pyx":1518 * self.criterion.update(best.pos) * best.improvement = self.criterion.impurity_improvement(impurity) * self.criterion.children_impurity(&best.impurity_left, # <<<<<<<<<<<<<< * &best.impurity_right) * */ - ((struct __pyx_vtabstruct_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *)__pyx_v_self->__pyx_base.__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.__pyx_base.criterion, (&__pyx_v_best.impurity_left), (&__pyx_v_best.impurity_right)); - /* "_splitter.pyx":1507 + /* "stpredictions/models/OK3/_splitter.pyx":1507 * * # Reorganize into samples[start:best.pos] + samples[best.pos:end] * if best.pos < end: # <<<<<<<<<<<<<< @@ -13346,25 +13160,25 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ } - /* "_splitter.pyx":1524 + /* "stpredictions/models/OK3/_splitter.pyx":1524 * # element in features[:n_known_constants] must be preserved for sibling * # and child nodes * memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants) # <<<<<<<<<<<<<< * * # Copy newly found constant features */ - (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants))); + (void)(memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)) * __pyx_v_n_known_constants))); - /* "_splitter.pyx":1527 + /* "stpredictions/models/OK3/_splitter.pyx":1527 * * # Copy newly found constant features * memcpy(constant_features + n_known_constants, # <<<<<<<<<<<<<< * features + n_known_constants, * sizeof(SIZE_t) * n_found_constants) */ - (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants))); + (void)(memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)) * __pyx_v_n_found_constants))); - /* "_splitter.pyx":1532 + /* "stpredictions/models/OK3/_splitter.pyx":1532 * * # Return values * split[0] = best # <<<<<<<<<<<<<< @@ -13373,7 +13187,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ (__pyx_v_split[0]) = __pyx_v_best; - /* "_splitter.pyx":1533 + /* "stpredictions/models/OK3/_splitter.pyx":1533 * # Return values * split[0] = best * n_constant_features[0] = n_total_constants # <<<<<<<<<<<<<< @@ -13381,7 +13195,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj */ (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants; - /* "_splitter.pyx":1534 + /* "stpredictions/models/OK3/_splitter.pyx":1534 * split[0] = best * n_constant_features[0] = n_total_constants * return 0 # <<<<<<<<<<<<<< @@ -13389,7 +13203,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj __pyx_r = 0; goto __pyx_L0; - /* "_splitter.pyx":1319 + /* "stpredictions/models/OK3/_splitter.pyx":1319 * self.random_state), self.__getstate__()) * * cdef int node_split(self, double impurity, SplitRecord* split, # <<<<<<<<<<<<<< @@ -13403,7 +13217,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif - __Pyx_AddTraceback("_splitter.RandomSparseSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._splitter.RandomSparseSplitter.node_split", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif @@ -13413,7 +13227,7 @@ static int __pyx_f_9_splitter_20RandomSparseSplitter_node_split(struct __pyx_obj return __pyx_r; } -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":734 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":734 * ctypedef npy_cdouble complex_t * * cdef inline object PyArray_MultiIterNew1(a): # <<<<<<<<<<<<<< @@ -13430,7 +13244,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("PyArray_MultiIterNew1", 0); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":735 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":735 * * cdef inline object PyArray_MultiIterNew1(a): * return PyArray_MultiIterNew(1, a) # <<<<<<<<<<<<<< @@ -13444,7 +13258,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__ __pyx_t_1 = 0; goto __pyx_L0; - /* 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set_array_base(ndarray arr, object base): # <<<<<<<<<<<<<< @@ -13779,7 +13593,7 @@ static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_a __Pyx_RefNannyFinishContext(); } -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":872 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":872 * PyArray_SetBaseObject(arr, base) * * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< @@ -13794,7 +13608,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py int __pyx_t_1; __Pyx_RefNannySetupContext("get_array_base", 0); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":873 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":873 * * cdef inline object get_array_base(ndarray arr): * base = PyArray_BASE(arr) # <<<<<<<<<<<<<< @@ -13803,7 +13617,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py */ __pyx_v_base = PyArray_BASE(__pyx_v_arr); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":874 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":874 * cdef inline object get_array_base(ndarray arr): * base = PyArray_BASE(arr) * if base is NULL: # <<<<<<<<<<<<<< @@ -13813,7 +13627,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py __pyx_t_1 = ((__pyx_v_base == NULL) != 0); if (__pyx_t_1) { - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":875 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":875 * base = PyArray_BASE(arr) * if base is NULL: * return None # <<<<<<<<<<<<<< @@ -13824,7 +13638,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py __pyx_r = Py_None; __Pyx_INCREF(Py_None); goto __pyx_L0; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":874 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":874 * cdef inline object get_array_base(ndarray arr): * base = PyArray_BASE(arr) * if base is NULL: # <<<<<<<<<<<<<< @@ -13833,7 +13647,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py */ } - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":876 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":876 * if base is NULL: * return None * return base # <<<<<<<<<<<<<< @@ -13845,7 +13659,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py __pyx_r = ((PyObject *)__pyx_v_base); goto __pyx_L0; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":872 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":872 * PyArray_SetBaseObject(arr, base) * * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< @@ -13860,7 +13674,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py return __pyx_r; } -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":880 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":880 * # Versions of the import_* functions which are more suitable for * # Cython code. * cdef inline int import_array() except -1: # <<<<<<<<<<<<<< @@ -13884,7 +13698,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { int __pyx_clineno = 0; __Pyx_RefNannySetupContext("import_array", 0); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":881 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":881 * # Cython code. * cdef inline int import_array() except -1: * try: # <<<<<<<<<<<<<< @@ -13900,7 +13714,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { __Pyx_XGOTREF(__pyx_t_3); /*try:*/ { - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":882 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":882 * cdef inline int import_array() except -1: * try: * __pyx_import_array() # <<<<<<<<<<<<<< @@ -13909,7 +13723,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { */ __pyx_t_4 = _import_array(); if (unlikely(__pyx_t_4 == ((int)-1))) __PYX_ERR(3, 882, __pyx_L3_error) - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":881 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":881 * # Cython code. * cdef inline int import_array() except -1: * try: # <<<<<<<<<<<<<< @@ -13923,7 +13737,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { goto __pyx_L8_try_end; __pyx_L3_error:; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":883 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":883 * try: * __pyx_import_array() * except Exception: # <<<<<<<<<<<<<< @@ -13938,7 +13752,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { __Pyx_GOTREF(__pyx_t_6); __Pyx_GOTREF(__pyx_t_7); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":884 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":884 * __pyx_import_array() * except Exception: * raise ImportError("numpy.core.multiarray failed to import") # <<<<<<<<<<<<<< @@ -13954,7 +13768,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { goto __pyx_L5_except_error; __pyx_L5_except_error:; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":881 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":881 * # Cython code. * cdef inline int import_array() except -1: * try: # <<<<<<<<<<<<<< @@ -13969,7 +13783,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { __pyx_L8_try_end:; } - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":880 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":880 * # Versions of the import_* functions which are more suitable for * # Cython code. * cdef inline int import_array() except -1: # <<<<<<<<<<<<<< @@ -13992,7 +13806,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_array(void) { return __pyx_r; } -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":886 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":886 * raise ImportError("numpy.core.multiarray failed to import") * * cdef inline int import_umath() except -1: # <<<<<<<<<<<<<< @@ -14016,7 +13830,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_umath(void) { int __pyx_clineno = 0; __Pyx_RefNannySetupContext("import_umath", 0); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":887 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":887 * * cdef inline int import_umath() except -1: * try: # <<<<<<<<<<<<<< @@ -14032,7 +13846,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_umath(void) { __Pyx_XGOTREF(__pyx_t_3); /*try:*/ { - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":888 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":888 * cdef inline int import_umath() except -1: * try: * _import_umath() # <<<<<<<<<<<<<< @@ -14041,7 +13855,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_umath(void) { */ __pyx_t_4 = _import_umath(); if (unlikely(__pyx_t_4 == ((int)-1))) __PYX_ERR(3, 888, __pyx_L3_error) - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":887 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":887 * * cdef inline int import_umath() except -1: * try: # <<<<<<<<<<<<<< @@ -14055,7 +13869,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_umath(void) { goto __pyx_L8_try_end; __pyx_L3_error:; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":889 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":889 * try: * _import_umath() * except Exception: # <<<<<<<<<<<<<< @@ -14070,7 +13884,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_umath(void) { __Pyx_GOTREF(__pyx_t_6); __Pyx_GOTREF(__pyx_t_7); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":890 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":890 * _import_umath() * except Exception: * raise ImportError("numpy.core.umath failed to import") # <<<<<<<<<<<<<< @@ -14086,7 +13900,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_umath(void) { goto __pyx_L5_except_error; __pyx_L5_except_error:; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":887 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":887 * * cdef inline int import_umath() except -1: * try: # <<<<<<<<<<<<<< @@ -14101,7 +13915,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_umath(void) { __pyx_L8_try_end:; } - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":886 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":886 * raise ImportError("numpy.core.multiarray failed to import") * * cdef inline int import_umath() except -1: # <<<<<<<<<<<<<< @@ -14124,7 +13938,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_umath(void) { return __pyx_r; } -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":892 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":892 * raise ImportError("numpy.core.umath failed to import") * * cdef inline int import_ufunc() except -1: # <<<<<<<<<<<<<< @@ -14148,7 +13962,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_ufunc(void) { int __pyx_clineno = 0; __Pyx_RefNannySetupContext("import_ufunc", 0); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":893 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":893 * * cdef inline int import_ufunc() except -1: * try: # <<<<<<<<<<<<<< @@ -14164,7 +13978,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_ufunc(void) { __Pyx_XGOTREF(__pyx_t_3); /*try:*/ { - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":894 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":894 * cdef inline int import_ufunc() except -1: * try: * _import_umath() # <<<<<<<<<<<<<< @@ -14173,7 +13987,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_ufunc(void) { */ __pyx_t_4 = _import_umath(); if (unlikely(__pyx_t_4 == ((int)-1))) __PYX_ERR(3, 894, __pyx_L3_error) - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":893 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":893 * * cdef inline int import_ufunc() except -1: * try: # <<<<<<<<<<<<<< @@ -14187,7 +14001,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_ufunc(void) { goto __pyx_L8_try_end; __pyx_L3_error:; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":895 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":895 * try: * _import_umath() * except Exception: # <<<<<<<<<<<<<< @@ -14202,7 +14016,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_ufunc(void) { __Pyx_GOTREF(__pyx_t_6); __Pyx_GOTREF(__pyx_t_7); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":896 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":896 * _import_umath() * except Exception: * raise ImportError("numpy.core.umath failed to import") # <<<<<<<<<<<<<< @@ -14218,7 +14032,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_ufunc(void) { goto __pyx_L5_except_error; __pyx_L5_except_error:; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":893 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":893 * * cdef inline int import_ufunc() except -1: * try: # <<<<<<<<<<<<<< @@ -14233,7 +14047,7 @@ static CYTHON_INLINE int __pyx_f_5numpy_import_ufunc(void) { __pyx_L8_try_end:; } - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":892 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":892 * raise ImportError("numpy.core.umath failed to import") * * cdef inline int import_ufunc() except -1: # <<<<<<<<<<<<<< @@ -27273,10 +27087,10 @@ static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *__ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static struct __pyx_vtabstruct_9_splitter_Splitter __pyx_vtable_9_splitter_Splitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter __pyx_vtable_13stpredictions_6models_3OK3_9_splitter_Splitter; -static PyObject *__pyx_tp_new_9_splitter_Splitter(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_9_splitter_Splitter *p; +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_Splitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); @@ -27284,21 +27098,21 @@ static PyObject *__pyx_tp_new_9_splitter_Splitter(PyTypeObject *t, PyObject *a, o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_9_splitter_Splitter *)o); - p->__pyx_vtab = __pyx_vtabptr_9_splitter_Splitter; - p->criterion = ((struct __pyx_obj_10_criterion_Criterion *)Py_None); Py_INCREF(Py_None); + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)o); + p->__pyx_vtab = __pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_Splitter; + p->criterion = ((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *)Py_None); Py_INCREF(Py_None); p->random_state = Py_None; Py_INCREF(Py_None); p->y.data = NULL; p->y.memview = NULL; - if (unlikely(__pyx_pw_9_splitter_8Splitter_1__cinit__(o, a, k) < 0)) goto bad; + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_1__cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } -static void __pyx_tp_dealloc_9_splitter_Splitter(PyObject *o) { - struct __pyx_obj_9_splitter_Splitter *p = (struct __pyx_obj_9_splitter_Splitter *)o; +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_Splitter(PyObject *o) { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *p = (struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)o; #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; @@ -27309,7 +27123,7 @@ static void __pyx_tp_dealloc_9_splitter_Splitter(PyObject *o) { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); - __pyx_pw_9_splitter_8Splitter_3__dealloc__(o); + __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_3__dealloc__(o); __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } @@ -27319,9 +27133,9 @@ static void __pyx_tp_dealloc_9_splitter_Splitter(PyObject *o) { (*Py_TYPE(o)->tp_free)(o); } -static int __pyx_tp_traverse_9_splitter_Splitter(PyObject *o, visitproc v, void *a) { +static int __pyx_tp_traverse_13stpredictions_6models_3OK3_9_splitter_Splitter(PyObject *o, visitproc v, void *a) { int e; - struct __pyx_obj_9_splitter_Splitter *p = (struct __pyx_obj_9_splitter_Splitter *)o; + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *p = (struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)o; if (p->criterion) { e = (*v)(((PyObject *)p->criterion), a); if (e) return e; } @@ -27331,11 +27145,11 @@ static int __pyx_tp_traverse_9_splitter_Splitter(PyObject *o, visitproc v, void return 0; } -static int __pyx_tp_clear_9_splitter_Splitter(PyObject *o) { +static int __pyx_tp_clear_13stpredictions_6models_3OK3_9_splitter_Splitter(PyObject *o) { PyObject* tmp; - struct __pyx_obj_9_splitter_Splitter *p = (struct __pyx_obj_9_splitter_Splitter *)o; + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *p = (struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)o; tmp = ((PyObject*)p->criterion); - p->criterion = ((struct __pyx_obj_10_criterion_Criterion *)Py_None); Py_INCREF(Py_None); + p->criterion = ((struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->random_state); p->random_state = Py_None; Py_INCREF(Py_None); @@ -27343,26 +27157,26 @@ static int __pyx_tp_clear_9_splitter_Splitter(PyObject *o) { return 0; } -static PyObject *__pyx_getprop_9_splitter_8Splitter_criterion(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_9_splitter_8Splitter_9criterion_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_criterion(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_1__get__(o); } -static int __pyx_setprop_9_splitter_8Splitter_criterion(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { +static int __pyx_setprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_criterion(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { if (v) { - return __pyx_pw_9_splitter_8Splitter_9criterion_3__set__(o, v); + return __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_3__set__(o, v); } else { - return __pyx_pw_9_splitter_8Splitter_9criterion_5__del__(o); + return __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_9criterion_5__del__(o); } } -static PyObject *__pyx_getprop_9_splitter_8Splitter_max_features(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_9_splitter_8Splitter_12max_features_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_max_features(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features_1__get__(o); } -static int __pyx_setprop_9_splitter_8Splitter_max_features(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { +static int __pyx_setprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_max_features(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { if (v) { - return __pyx_pw_9_splitter_8Splitter_12max_features_3__set__(o, v); + return __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_12max_features_3__set__(o, v); } else { PyErr_SetString(PyExc_NotImplementedError, "__del__"); @@ -27370,13 +27184,13 @@ static int __pyx_setprop_9_splitter_8Splitter_max_features(PyObject *o, PyObject } } -static PyObject *__pyx_getprop_9_splitter_8Splitter_min_samples_leaf(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_9_splitter_8Splitter_16min_samples_leaf_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_min_samples_leaf(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_16min_samples_leaf_1__get__(o); } -static int __pyx_setprop_9_splitter_8Splitter_min_samples_leaf(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { +static int __pyx_setprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_min_samples_leaf(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { if (v) { - return __pyx_pw_9_splitter_8Splitter_16min_samples_leaf_3__set__(o, v); + return __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_16min_samples_leaf_3__set__(o, v); } else { PyErr_SetString(PyExc_NotImplementedError, "__del__"); @@ -27384,13 +27198,13 @@ static int __pyx_setprop_9_splitter_8Splitter_min_samples_leaf(PyObject *o, PyOb } } -static PyObject *__pyx_getprop_9_splitter_8Splitter_min_weight_leaf(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_9_splitter_8Splitter_15min_weight_leaf_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_min_weight_leaf(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_15min_weight_leaf_1__get__(o); } -static int __pyx_setprop_9_splitter_8Splitter_min_weight_leaf(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { +static int __pyx_setprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_min_weight_leaf(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { if (v) { - return __pyx_pw_9_splitter_8Splitter_15min_weight_leaf_3__set__(o, v); + return __pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_15min_weight_leaf_3__set__(o, v); } else { PyErr_SetString(PyExc_NotImplementedError, "__del__"); @@ -27398,28 +27212,28 @@ static int __pyx_setprop_9_splitter_8Splitter_min_weight_leaf(PyObject *o, PyObj } } -static PyMethodDef __pyx_methods_9_splitter_Splitter[] = { - {"__getstate__", (PyCFunction)__pyx_pw_9_splitter_8Splitter_5__getstate__, METH_NOARGS, 0}, - {"__setstate__", (PyCFunction)__pyx_pw_9_splitter_8Splitter_7__setstate__, METH_O, 0}, - {"__reduce_cython__", (PyCFunction)__pyx_pw_9_splitter_8Splitter_9__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_9_splitter_8Splitter_11__setstate_cython__, METH_O, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_9_splitter_Splitter[] = { + {"__getstate__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_5__getstate__, METH_NOARGS, 0}, + {"__setstate__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_7__setstate__, METH_O, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_9__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_8Splitter_11__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; -static struct PyGetSetDef __pyx_getsets_9_splitter_Splitter[] = { - {(char *)"criterion", __pyx_getprop_9_splitter_8Splitter_criterion, __pyx_setprop_9_splitter_8Splitter_criterion, (char *)0, 0}, - {(char *)"max_features", __pyx_getprop_9_splitter_8Splitter_max_features, __pyx_setprop_9_splitter_8Splitter_max_features, (char *)0, 0}, - {(char *)"min_samples_leaf", __pyx_getprop_9_splitter_8Splitter_min_samples_leaf, __pyx_setprop_9_splitter_8Splitter_min_samples_leaf, (char *)0, 0}, - {(char *)"min_weight_leaf", __pyx_getprop_9_splitter_8Splitter_min_weight_leaf, __pyx_setprop_9_splitter_8Splitter_min_weight_leaf, (char *)0, 0}, +static struct PyGetSetDef __pyx_getsets_13stpredictions_6models_3OK3_9_splitter_Splitter[] = { + {(char *)"criterion", __pyx_getprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_criterion, __pyx_setprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_criterion, (char *)0, 0}, + {(char *)"max_features", __pyx_getprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_max_features, __pyx_setprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_max_features, (char *)0, 0}, + {(char *)"min_samples_leaf", __pyx_getprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_min_samples_leaf, __pyx_setprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_min_samples_leaf, (char *)0, 0}, + {(char *)"min_weight_leaf", __pyx_getprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_min_weight_leaf, __pyx_setprop_13stpredictions_6models_3OK3_9_splitter_8Splitter_min_weight_leaf, (char *)0, 0}, {0, 0, 0, 0, 0} }; -static PyTypeObject __pyx_type_9_splitter_Splitter = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_9_splitter_Splitter = { PyVarObject_HEAD_INIT(0, 0) - "_splitter.Splitter", /*tp_name*/ - sizeof(struct __pyx_obj_9_splitter_Splitter), /*tp_basicsize*/ + "stpredictions.models.OK3._splitter.Splitter", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_9_splitter_Splitter, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -27446,15 +27260,15 @@ static PyTypeObject __pyx_type_9_splitter_Splitter = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ "Abstract splitter class.\n\n Splitters are called by tree builders to find the best splits on both\n sparse and dense data, one split at a time.\n ", /*tp_doc*/ - __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ - __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_9_splitter_Splitter, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_methods*/ 0, /*tp_members*/ - __pyx_getsets_9_splitter_Splitter, /*tp_getset*/ + __pyx_getsets_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ @@ -27462,7 +27276,7 @@ static PyTypeObject __pyx_type_9_splitter_Splitter = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_9_splitter_Splitter, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -27482,21 +27296,21 @@ static PyTypeObject __pyx_type_9_splitter_Splitter = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_9_splitter_BaseDenseSplitter __pyx_vtable_9_splitter_BaseDenseSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter __pyx_vtable_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter; -static PyObject *__pyx_tp_new_9_splitter_BaseDenseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_9_splitter_BaseDenseSplitter *p; - PyObject *o = __pyx_tp_new_9_splitter_Splitter(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_Splitter(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_9_splitter_BaseDenseSplitter *)o); - p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_BaseDenseSplitter; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter*)__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter; p->X.data = NULL; p->X.memview = NULL; return o; } -static void __pyx_tp_dealloc_9_splitter_BaseDenseSplitter(PyObject *o) { - struct __pyx_obj_9_splitter_BaseDenseSplitter *p = (struct __pyx_obj_9_splitter_BaseDenseSplitter *)o; +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter(PyObject *o) { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *p = (struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter *)o; #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; @@ -27505,21 +27319,21 @@ static void __pyx_tp_dealloc_9_splitter_BaseDenseSplitter(PyObject *o) { PyObject_GC_UnTrack(o); __PYX_XDEC_MEMVIEW(&p->X, 1); PyObject_GC_Track(o); - __pyx_tp_dealloc_9_splitter_Splitter(o); + __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_Splitter(o); } -static PyMethodDef __pyx_methods_9_splitter_BaseDenseSplitter[] = { - {"__reduce_cython__", (PyCFunction)__pyx_pw_9_splitter_17BaseDenseSplitter_1__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_9_splitter_17BaseDenseSplitter_3__setstate_cython__, METH_O, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_17BaseDenseSplitter_3__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_9_splitter_BaseDenseSplitter = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter = { PyVarObject_HEAD_INIT(0, 0) - "_splitter.BaseDenseSplitter", /*tp_name*/ - sizeof(struct __pyx_obj_9_splitter_BaseDenseSplitter), /*tp_basicsize*/ + "stpredictions.models.OK3._splitter.BaseDenseSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_9_splitter_BaseDenseSplitter, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -27546,13 +27360,13 @@ static PyTypeObject __pyx_type_9_splitter_BaseDenseSplitter = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ 0, /*tp_doc*/ - __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ - __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_9_splitter_BaseDenseSplitter, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -27562,7 +27376,7 @@ static PyTypeObject __pyx_type_9_splitter_BaseDenseSplitter = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_9_splitter_BaseDenseSplitter, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -27582,28 +27396,28 @@ static PyTypeObject __pyx_type_9_splitter_BaseDenseSplitter = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_9_splitter_BestSplitter __pyx_vtable_9_splitter_BestSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSplitter __pyx_vtable_13stpredictions_6models_3OK3_9_splitter_BestSplitter; -static PyObject *__pyx_tp_new_9_splitter_BestSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_9_splitter_BestSplitter *p; - PyObject *o = __pyx_tp_new_9_splitter_BaseDenseSplitter(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BestSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_9_splitter_BestSplitter *)o); - p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_BestSplitter; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter *)o); + p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter*)__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BestSplitter; return o; } -static PyMethodDef __pyx_methods_9_splitter_BestSplitter[] = { - {"__reduce__", (PyCFunction)__pyx_pw_9_splitter_12BestSplitter_1__reduce__, METH_NOARGS, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_9_splitter_BestSplitter[] = { + {"__reduce__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_12BestSplitter_1__reduce__, METH_NOARGS, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_9_splitter_BestSplitter = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_9_splitter_BestSplitter = { PyVarObject_HEAD_INIT(0, 0) - "_splitter.BestSplitter", /*tp_name*/ - sizeof(struct __pyx_obj_9_splitter_BestSplitter), /*tp_basicsize*/ + "stpredictions.models.OK3._splitter.BestSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSplitter), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_9_splitter_BaseDenseSplitter, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -27630,13 +27444,13 @@ static PyTypeObject __pyx_type_9_splitter_BestSplitter = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ "Splitter for finding the best split.", /*tp_doc*/ - __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ - __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_9_splitter_BestSplitter, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_9_splitter_BestSplitter, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -27646,7 +27460,7 @@ static PyTypeObject __pyx_type_9_splitter_BestSplitter = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_9_splitter_BestSplitter, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BestSplitter, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -27666,28 +27480,28 @@ static PyTypeObject __pyx_type_9_splitter_BestSplitter = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_9_splitter_RandomSplitter __pyx_vtable_9_splitter_RandomSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSplitter __pyx_vtable_13stpredictions_6models_3OK3_9_splitter_RandomSplitter; -static PyObject *__pyx_tp_new_9_splitter_RandomSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_9_splitter_RandomSplitter *p; - PyObject *o = __pyx_tp_new_9_splitter_BaseDenseSplitter(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_RandomSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_9_splitter_RandomSplitter *)o); - p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_RandomSplitter; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter *)o); + p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter*)__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_RandomSplitter; return o; } -static PyMethodDef __pyx_methods_9_splitter_RandomSplitter[] = { - {"__reduce__", (PyCFunction)__pyx_pw_9_splitter_14RandomSplitter_1__reduce__, METH_NOARGS, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_9_splitter_RandomSplitter[] = { + {"__reduce__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_14RandomSplitter_1__reduce__, METH_NOARGS, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_9_splitter_RandomSplitter = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_9_splitter_RandomSplitter = { PyVarObject_HEAD_INIT(0, 0) - "_splitter.RandomSplitter", /*tp_name*/ - sizeof(struct __pyx_obj_9_splitter_RandomSplitter), /*tp_basicsize*/ + "stpredictions.models.OK3._splitter.RandomSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSplitter), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_9_splitter_BaseDenseSplitter, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseDenseSplitter, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -27714,13 +27528,13 @@ static PyTypeObject __pyx_type_9_splitter_RandomSplitter = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ "Splitter for finding the best random split.", /*tp_doc*/ - __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ - __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_9_splitter_RandomSplitter, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_9_splitter_RandomSplitter, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -27730,7 +27544,7 @@ static PyTypeObject __pyx_type_9_splitter_RandomSplitter = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_9_splitter_RandomSplitter, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_RandomSplitter, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -27750,22 +27564,22 @@ static PyTypeObject __pyx_type_9_splitter_RandomSplitter = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_9_splitter_BaseSparseSplitter __pyx_vtable_9_splitter_BaseSparseSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter __pyx_vtable_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter; -static PyObject *__pyx_tp_new_9_splitter_BaseSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_9_splitter_BaseSparseSplitter *p; - PyObject *o = __pyx_tp_new_9_splitter_Splitter(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_Splitter(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_9_splitter_BaseSparseSplitter *)o); - p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_BaseSparseSplitter; - if (unlikely(__pyx_pw_9_splitter_18BaseSparseSplitter_1__cinit__(o, a, k) < 0)) goto bad; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter*)__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter; + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_1__cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } -static void __pyx_tp_dealloc_9_splitter_BaseSparseSplitter(PyObject *o) { +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter(PyObject *o) { #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; @@ -27776,26 +27590,26 @@ static void __pyx_tp_dealloc_9_splitter_BaseSparseSplitter(PyObject *o) { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); - __pyx_pw_9_splitter_18BaseSparseSplitter_3__dealloc__(o); + __pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_3__dealloc__(o); __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } PyObject_GC_Track(o); - __pyx_tp_dealloc_9_splitter_Splitter(o); + __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_Splitter(o); } -static PyMethodDef __pyx_methods_9_splitter_BaseSparseSplitter[] = { - {"__reduce_cython__", (PyCFunction)__pyx_pw_9_splitter_18BaseSparseSplitter_5__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_9_splitter_18BaseSparseSplitter_7__setstate_cython__, METH_O, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_5__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BaseSparseSplitter_7__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_9_splitter_BaseSparseSplitter = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter = { PyVarObject_HEAD_INIT(0, 0) - "_splitter.BaseSparseSplitter", /*tp_name*/ - sizeof(struct __pyx_obj_9_splitter_BaseSparseSplitter), /*tp_basicsize*/ + "stpredictions.models.OK3._splitter.BaseSparseSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_9_splitter_BaseSparseSplitter, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -27822,13 +27636,13 @@ static PyTypeObject __pyx_type_9_splitter_BaseSparseSplitter = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ 0, /*tp_doc*/ - __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ - __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_9_splitter_BaseSparseSplitter, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -27838,7 +27652,7 @@ static PyTypeObject __pyx_type_9_splitter_BaseSparseSplitter = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_9_splitter_BaseSparseSplitter, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -27858,28 +27672,28 @@ static PyTypeObject __pyx_type_9_splitter_BaseSparseSplitter = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_9_splitter_BestSparseSplitter __pyx_vtable_9_splitter_BestSparseSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter __pyx_vtable_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter; -static PyObject *__pyx_tp_new_9_splitter_BestSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_9_splitter_BestSparseSplitter *p; - PyObject *o = __pyx_tp_new_9_splitter_BaseSparseSplitter(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_9_splitter_BestSparseSplitter *)o); - p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_BestSparseSplitter; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter *)o); + p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter*)__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter; return o; } -static PyMethodDef __pyx_methods_9_splitter_BestSparseSplitter[] = { - {"__reduce__", (PyCFunction)__pyx_pw_9_splitter_18BestSparseSplitter_1__reduce__, METH_NOARGS, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter[] = { + {"__reduce__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_18BestSparseSplitter_1__reduce__, METH_NOARGS, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_9_splitter_BestSparseSplitter = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter = { PyVarObject_HEAD_INIT(0, 0) - "_splitter.BestSparseSplitter", /*tp_name*/ - sizeof(struct __pyx_obj_9_splitter_BestSparseSplitter), /*tp_basicsize*/ + "stpredictions.models.OK3._splitter.BestSparseSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_9_splitter_BaseSparseSplitter, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -27906,13 +27720,13 @@ static PyTypeObject __pyx_type_9_splitter_BestSparseSplitter = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ "Splitter for finding the best split, using the sparse data.", /*tp_doc*/ - __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ - __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_9_splitter_BestSparseSplitter, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -27922,7 +27736,7 @@ static PyTypeObject __pyx_type_9_splitter_BestSparseSplitter = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_9_splitter_BestSparseSplitter, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BestSparseSplitter, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -27942,28 +27756,28 @@ static PyTypeObject __pyx_type_9_splitter_BestSparseSplitter = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_9_splitter_RandomSparseSplitter __pyx_vtable_9_splitter_RandomSparseSplitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter __pyx_vtable_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter; -static PyObject *__pyx_tp_new_9_splitter_RandomSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_9_splitter_RandomSparseSplitter *p; - PyObject *o = __pyx_tp_new_9_splitter_BaseSparseSplitter(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_9_splitter_RandomSparseSplitter *)o); - p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_9_splitter_Splitter*)__pyx_vtabptr_9_splitter_RandomSparseSplitter; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter *)o); + p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter*)__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter; return o; } -static PyMethodDef __pyx_methods_9_splitter_RandomSparseSplitter[] = { - {"__reduce__", (PyCFunction)__pyx_pw_9_splitter_20RandomSparseSplitter_1__reduce__, METH_NOARGS, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter[] = { + {"__reduce__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_9_splitter_20RandomSparseSplitter_1__reduce__, METH_NOARGS, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_9_splitter_RandomSparseSplitter = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter = { PyVarObject_HEAD_INIT(0, 0) - "_splitter.RandomSparseSplitter", /*tp_name*/ - sizeof(struct __pyx_obj_9_splitter_RandomSparseSplitter), /*tp_basicsize*/ + "stpredictions.models.OK3._splitter.RandomSparseSplitter", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_9_splitter_BaseSparseSplitter, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_9_splitter_BaseSparseSplitter, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -27990,13 +27804,13 @@ static PyTypeObject __pyx_type_9_splitter_RandomSparseSplitter = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ "Splitter for finding a random split, using the sparse data.", /*tp_doc*/ - __pyx_tp_traverse_9_splitter_Splitter, /*tp_traverse*/ - __pyx_tp_clear_9_splitter_Splitter, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_9_splitter_Splitter, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_9_splitter_RandomSparseSplitter, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -28006,7 +27820,7 @@ static PyTypeObject __pyx_type_9_splitter_RandomSparseSplitter = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_9_splitter_RandomSparseSplitter, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_9_splitter_RandomSparseSplitter, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -28149,7 +27963,7 @@ static PyBufferProcs __pyx_tp_as_buffer_array = { static PyTypeObject __pyx_type___pyx_array = { PyVarObject_HEAD_INIT(0, 0) - "_splitter.array", /*tp_name*/ + "stpredictions.models.OK3._splitter.array", /*tp_name*/ sizeof(struct __pyx_array_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_array, /*tp_dealloc*/ @@ -28268,7 +28082,7 @@ static PyMethodDef __pyx_methods_Enum[] = { static PyTypeObject __pyx_type___pyx_MemviewEnum = { PyVarObject_HEAD_INIT(0, 0) - "_splitter.Enum", /*tp_name*/ + "stpredictions.models.OK3._splitter.Enum", /*tp_name*/ sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_Enum, /*tp_dealloc*/ @@ -28529,7 +28343,7 @@ static PyBufferProcs __pyx_tp_as_buffer_memoryview = { static PyTypeObject __pyx_type___pyx_memoryview = { PyVarObject_HEAD_INIT(0, 0) - "_splitter.memoryview", /*tp_name*/ + "stpredictions.models.OK3._splitter.memoryview", /*tp_name*/ sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_memoryview, /*tp_dealloc*/ @@ -28667,7 +28481,7 @@ static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = { static PyTypeObject __pyx_type___pyx_memoryviewslice = { PyVarObject_HEAD_INIT(0, 0) - "_splitter._memoryviewslice", /*tp_name*/ + "stpredictions.models.OK3._splitter._memoryviewslice", /*tp_name*/ sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/ @@ -28958,7 +28772,7 @@ static CYTHON_SMALL_CODE int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__4); __Pyx_GIVEREF(__pyx_tuple__4); - /* "_splitter.pyx":804 + /* "stpredictions/models/OK3/_splitter.pyx":804 * * if not isinstance(X, csc_matrix): * raise ValueError("X should be in csc format") # <<<<<<<<<<<<<< @@ -28988,7 +28802,7 @@ static CYTHON_SMALL_CODE int __Pyx_InitCachedConstants(void) { __Pyx_GOTREF(__pyx_tuple__7); __Pyx_GIVEREF(__pyx_tuple__7); - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":884 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":884 * 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&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t__const__, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; diff --git a/stpredictions/models/OK3/_splitter.pxd b/stpredictions/models/OK3/_splitter.pxd index 836e59d38..372684240 100644 --- a/stpredictions/models/OK3/_splitter.pxd +++ b/stpredictions/models/OK3/_splitter.pxd @@ -5,11 +5,11 @@ cimport numpy as np from _criterion cimport Criterion -from sklearn.tree._tree cimport DTYPE_t # Type of X -from sklearn.tree._tree cimport DOUBLE_t # Type of y, sample_weight -from sklearn.tree._tree cimport SIZE_t # Type for indices and counters -from sklearn.tree._tree cimport INT32_t # Signed 32 bit integer -from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer +from ._tree cimport DTYPE_t # Type of X +from ._tree cimport DOUBLE_t # Type of y, sample_weight +from ._tree cimport SIZE_t # Type for indices and counters +from ._tree cimport INT32_t # Signed 32 bit integer +from ._tree cimport UINT32_t # Unsigned 32 bit integer cdef struct SplitRecord: # Data to track sample split diff --git a/stpredictions/models/OK3/_splitter.pyx b/stpredictions/models/OK3/_splitter.pyx index e55695070..598cf06e1 100644 --- a/stpredictions/models/OK3/_splitter.pyx +++ b/stpredictions/models/OK3/_splitter.pyx @@ -15,11 +15,11 @@ np.import_array() from scipy.sparse import csc_matrix -from sklearn.tree._utils cimport log -from sklearn.tree._utils cimport rand_int -from sklearn.tree._utils cimport rand_uniform -from sklearn.tree._utils cimport RAND_R_MAX -from sklearn.tree._utils cimport safe_realloc +from ._utils cimport log +from ._utils cimport rand_int +from ._utils cimport rand_uniform +from ._utils cimport RAND_R_MAX +from ._utils cimport safe_realloc cdef double INFINITY = np.inf diff --git a/stpredictions/models/OK3/_tree.c b/stpredictions/models/OK3/_tree.c index cbf514ea2..b009346f4 100644 --- a/stpredictions/models/OK3/_tree.c +++ b/stpredictions/models/OK3/_tree.c @@ -4,8 +4,8 @@ { 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"sources": [ "stpredictions/models/OK3/_tree.pyx" ] }, - "module_name": "_tree" + "module_name": "stpredictions.models.OK3._tree" } END: Cython Metadata */ @@ -632,8 +632,8 @@ static CYTHON_INLINE float __PYX_NAN() { #endif #endif -#define __PYX_HAVE___tree -#define __PYX_HAVE_API___tree +#define __PYX_HAVE__stpredictions__models__OK3___tree +#define __PYX_HAVE_API__stpredictions__models__OK3___tree /* Early includes */ #include #include @@ -884,13 +884,10 @@ static const char *__pyx_f[] = { "type.pxd", "bool.pxd", "complex.pxd", - "_criterion.pxd", - "_splitter.pxd", - "_tree.pxd", "stpredictions/models/OK3/_criterion.pxd", "stpredictions/models/OK3/_splitter.pxd", - "_quad_tree.pxd", - "_utils.pxd", + "stpredictions/models/OK3/_quad_tree.pxd", + "stpredictions/models/OK3/_utils.pxd", }; /* MemviewSliceStruct.proto */ struct __pyx_memoryview_obj; @@ -1001,7 +998,7 @@ typedef struct { } __Pyx_BufFmt_Context; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":689 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":689 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< @@ -1010,7 +1007,7 @@ typedef struct { */ typedef npy_int8 __pyx_t_5numpy_int8_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":690 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":690 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< @@ -1019,7 +1016,7 @@ typedef npy_int8 __pyx_t_5numpy_int8_t; */ typedef npy_int16 __pyx_t_5numpy_int16_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":691 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":691 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< @@ -1028,7 +1025,7 @@ typedef npy_int16 __pyx_t_5numpy_int16_t; */ typedef npy_int32 __pyx_t_5numpy_int32_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":692 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":692 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< @@ -1037,7 +1034,7 @@ typedef npy_int32 __pyx_t_5numpy_int32_t; */ typedef npy_int64 __pyx_t_5numpy_int64_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":696 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":696 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< @@ -1046,7 +1043,7 @@ typedef npy_int64 __pyx_t_5numpy_int64_t; */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":697 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":697 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< @@ -1055,7 +1052,7 @@ typedef npy_uint8 __pyx_t_5numpy_uint8_t; */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":698 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":698 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< @@ -1064,7 +1061,7 @@ typedef npy_uint16 __pyx_t_5numpy_uint16_t; */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":699 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":699 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< @@ -1073,7 +1070,7 @@ typedef npy_uint32 __pyx_t_5numpy_uint32_t; */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":703 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":703 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< @@ -1082,7 +1079,7 @@ typedef npy_uint64 __pyx_t_5numpy_uint64_t; */ typedef npy_float32 __pyx_t_5numpy_float32_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":704 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":704 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< @@ -1091,7 +1088,7 @@ typedef npy_float32 __pyx_t_5numpy_float32_t; */ typedef npy_float64 __pyx_t_5numpy_float64_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":713 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":713 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< @@ -1100,7 +1097,7 @@ typedef npy_float64 __pyx_t_5numpy_float64_t; */ typedef npy_long __pyx_t_5numpy_int_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":714 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":714 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< @@ -1109,7 +1106,7 @@ typedef npy_long __pyx_t_5numpy_int_t; */ typedef npy_longlong __pyx_t_5numpy_long_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":715 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":715 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< @@ -1118,7 +1115,7 @@ typedef npy_longlong __pyx_t_5numpy_long_t; */ typedef npy_longlong __pyx_t_5numpy_longlong_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":717 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":717 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< @@ -1127,7 +1124,7 @@ typedef npy_longlong __pyx_t_5numpy_longlong_t; */ typedef npy_ulong __pyx_t_5numpy_uint_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":718 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":718 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< @@ -1136,7 +1133,7 @@ typedef npy_ulong __pyx_t_5numpy_uint_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":719 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":719 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< @@ -1145,7 +1142,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":721 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":721 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< @@ -1154,7 +1151,7 @@ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; */ typedef npy_intp __pyx_t_5numpy_intp_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":722 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":722 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< @@ -1163,7 +1160,7 @@ typedef npy_intp __pyx_t_5numpy_intp_t; */ typedef npy_uintp __pyx_t_5numpy_uintp_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":724 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":724 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< @@ -1172,7 +1169,7 @@ typedef npy_uintp __pyx_t_5numpy_uintp_t; */ typedef npy_double __pyx_t_5numpy_float_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":725 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":725 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< @@ -1181,7 +1178,7 @@ typedef npy_double __pyx_t_5numpy_float_t; */ typedef npy_double __pyx_t_5numpy_double_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":726 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":726 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< @@ -1190,176 +1187,131 @@ typedef npy_double __pyx_t_5numpy_double_t; */ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; -/* "sklearn/tree/_tree.pxd":16 - * cimport numpy as np - * - * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - */ -typedef npy_float32 __pyx_t_7sklearn_4tree_5_tree_DTYPE_t; - -/* "sklearn/tree/_tree.pxd":17 - * - * ctypedef np.npy_float32 DTYPE_t # Type of X - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - */ -typedef npy_float64 __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t; - -/* "sklearn/tree/_tree.pxd":18 - * ctypedef np.npy_float32 DTYPE_t # Type of X - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - */ -typedef npy_intp __pyx_t_7sklearn_4tree_5_tree_SIZE_t; - -/* "sklearn/tree/_tree.pxd":19 - * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer - * - */ -typedef npy_int32 __pyx_t_7sklearn_4tree_5_tree_INT32_t; - -/* "sklearn/tree/_tree.pxd":20 - * ctypedef np.npy_intp SIZE_t # Type for indices and counters - * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer - * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< - * - * from ._splitter cimport Splitter - */ -typedef npy_uint32 __pyx_t_7sklearn_4tree_5_tree_UINT32_t; - -/* "neighbors/_quad_tree.pxd":13 +/* "_quad_tree.pxd":13 * cimport numpy as np * * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer */ -typedef npy_float32 __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t; +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t; -/* "neighbors/_quad_tree.pxd":14 +/* "_quad_tree.pxd":14 * * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer */ -typedef npy_intp __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t; +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t; -/* "neighbors/_quad_tree.pxd":15 +/* "_quad_tree.pxd":15 * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer * */ -typedef npy_int32 __pyx_t_7sklearn_9neighbors_10_quad_tree_INT32_t; +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_INT32_t; -/* "neighbors/_quad_tree.pxd":16 +/* "_quad_tree.pxd":16 * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< * * # This is effectively an ifdef statement in Cython */ -typedef npy_uint32 __pyx_t_7sklearn_9neighbors_10_quad_tree_UINT32_t; +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_UINT32_t; -/* "sklearn/tree/_utils.pxd":16 - * from ..neighbors._quad_tree cimport Cell +/* "_utils.pxd":16 + * from ._quad_tree cimport Cell * * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters */ -typedef npy_float32 __pyx_t_7sklearn_4tree_6_utils_DTYPE_t; +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t; -/* "sklearn/tree/_utils.pxd":17 +/* "_utils.pxd":17 * * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer */ -typedef npy_float64 __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t; +typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t; -/* "sklearn/tree/_utils.pxd":18 +/* "_utils.pxd":18 * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer */ -typedef npy_intp __pyx_t_7sklearn_4tree_6_utils_SIZE_t; +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t; -/* "sklearn/tree/_utils.pxd":19 +/* "_utils.pxd":19 * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer * */ -typedef npy_int32 __pyx_t_7sklearn_4tree_6_utils_INT32_t; +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_6_utils_INT32_t; -/* "sklearn/tree/_utils.pxd":20 +/* "_utils.pxd":20 * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< * * */ -typedef npy_uint32 __pyx_t_7sklearn_4tree_6_utils_UINT32_t; +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_6_utils_UINT32_t; -/* "_tree.pxd":7 +/* "stpredictions/models/OK3/_tree.pxd":7 * cimport numpy as np * * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters */ -typedef npy_float32 __pyx_t_5_tree_DTYPE_t; +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t; -/* "_tree.pxd":8 +/* "stpredictions/models/OK3/_tree.pxd":8 * * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer */ -typedef npy_float64 __pyx_t_5_tree_DOUBLE_t; +typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t; -/* "_tree.pxd":9 +/* "stpredictions/models/OK3/_tree.pxd":9 * ctypedef np.npy_float32 DTYPE_t # Type of X * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer */ -typedef npy_intp __pyx_t_5_tree_SIZE_t; +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t; -/* "_tree.pxd":10 +/* "stpredictions/models/OK3/_tree.pxd":10 * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer * */ -typedef npy_int32 __pyx_t_5_tree_INT32_t; +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t; -/* "_tree.pxd":11 +/* "stpredictions/models/OK3/_tree.pxd":11 * ctypedef np.npy_intp SIZE_t # Type for indices and counters * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< * * from _splitter cimport Splitter */ -typedef npy_uint32 __pyx_t_5_tree_UINT32_t; +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t; /* Declarations.proto */ #if CYTHON_CCOMPLEX #ifdef __cplusplus @@ -1386,33 +1338,27 @@ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(do /*--- Type declarations ---*/ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion; -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion; -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter; -struct __pyx_obj_7sklearn_4tree_5_tree_Tree; -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder; -struct __pyx_obj_10_criterion_Criterion; -struct __pyx_obj_10_criterion_KernelizedRegressionCriterion; -struct __pyx_obj_9_splitter_Splitter; -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree; -struct __pyx_obj_7sklearn_4tree_6_utils_Stack; -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue; -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator; -struct __pyx_obj_5_tree_Tree; -struct __pyx_obj_5_tree_TreeBuilder; -struct __pyx_obj_5_tree_DepthFirstTreeBuilder; -struct __pyx_obj_5_tree_BestFirstTreeBuilder; -struct __pyx_obj_5_tree__CCPPruneController; -struct __pyx_obj_5_tree__AlphaPruner; -struct __pyx_obj_5_tree__PathFinder; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter; +struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder; struct __pyx_array_obj; struct __pyx_MemviewEnum_obj; struct __pyx_memoryview_obj; struct __pyx_memoryviewslice_obj; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":728 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":728 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< @@ -1421,7 +1367,7 @@ struct __pyx_memoryviewslice_obj; */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":729 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":729 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< @@ -1430,7 +1376,7 @@ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":730 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":730 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< @@ -1439,7 +1385,7 @@ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; -/* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":732 +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":732 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< @@ -1447,105 +1393,31 @@ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; * cdef inline object PyArray_MultiIterNew1(a): */ typedef npy_cdouble __pyx_t_5numpy_complex_t; -struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord; - -/* "_splitter.pxd":23 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef struct SplitRecord: # <<<<<<<<<<<<<< - * # Data to track sample split - * SIZE_t feature # Which feature to split on. - */ -struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - double threshold; - double improvement; - double impurity_left; - double impurity_right; -}; -struct __pyx_t_7sklearn_4tree_5_tree_Node; -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c; -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances; -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build; - -/* "sklearn/tree/_tree.pxd":25 - * from ._splitter cimport SplitRecord - * - * cdef struct Node: # <<<<<<<<<<<<<< - * # Base storage structure for the nodes in a Tree object - * - */ -struct __pyx_t_7sklearn_4tree_5_tree_Node { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t left_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t right_child; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t threshold; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t impurity; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t weighted_n_node_samples; -}; - -/* "sklearn/tree/_tree.pxd":63 - * double weighted_n_samples) nogil except -1 - * cdef int _resize(self, SIZE_t capacity) nogil except -1 - * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< - * - * cdef np.ndarray _get_value_ndarray(self) - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c { - int __pyx_n; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; -}; - -/* "sklearn/tree/_tree.pxd":78 - * cdef object _decision_path_sparse_csr(self, object X) - * - * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< - * - * - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances { - int __pyx_n; - PyObject *normalize; -}; - -/* "sklearn/tree/_tree.pxd":102 - * cdef double min_impurity_decrease # Impurity threshold for early stopping - * - * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< - * np.ndarray sample_weight=*) - * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) - */ -struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build { - int __pyx_n; - PyArrayObject *sample_weight; -}; -struct __pyx_t_9_splitter_SplitRecord; +struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord; /* "_splitter.pxd":14 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * from ._tree cimport UINT32_t # Unsigned 32 bit integer * * cdef struct SplitRecord: # <<<<<<<<<<<<<< * # Data to track sample split * SIZE_t feature # Which feature to split on. */ -struct __pyx_t_9_splitter_SplitRecord { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; +struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t pos; double threshold; double improvement; double impurity_left; double impurity_right; }; -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c; -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; - -/* "neighbors/_quad_tree.pxd":21 +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell; + +/* "_quad_tree.pxd":21 * # It allows us to write printf debugging lines * # and remove them at compile time * cdef enum: # <<<<<<<<<<<<<< @@ -1553,96 +1425,96 @@ struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell; * */ enum { - __pyx_e_7sklearn_9neighbors_10_quad_tree_DEBUGFLAG = 0 + __pyx_e_13stpredictions_6models_3OK3_10_quad_tree_DEBUGFLAG = 0 }; -/* "neighbors/_quad_tree.pxd":29 +/* "_quad_tree.pxd":29 * # have is_leaf and max_width consecutive as it permits to avoid padding by * # the compiler and keep the size coherent for both C and numpy data structures. * cdef struct Cell: # <<<<<<<<<<<<<< * # Base storage structure for cells in a QuadTree object * */ -struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell { - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t parent; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t children[8]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t point_index; +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell { + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t parent; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t children[8]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t point_index; int is_leaf; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t squared_max_width; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cumulative_size; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t center[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t barycenter[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t min_bounds[3]; - __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t max_bounds[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t squared_max_width; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t depth; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cumulative_size; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t center[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t barycenter[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t min_bounds[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t max_bounds[3]; }; -/* "neighbors/_quad_tree.pxd":75 +/* "_quad_tree.pxd":75 * * # Point insertion methods * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< * SIZE_t cell_id=*) nogil except -1 * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; }; -/* "neighbors/_quad_tree.pxd":77 +/* "_quad_tree.pxd":77 * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, * SIZE_t cell_id=*) nogil except -1 * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< * SIZE_t point_index, SIZE_t size=* * ) nogil */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t size; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t size; }; -/* "neighbors/_quad_tree.pxd":84 +/* "_quad_tree.pxd":84 * * # Create a summary of the Tree compare to a query point * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< * float squared_theta=*, SIZE_t cell_id=*, long idx=* * ) nogil */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize { int __pyx_n; float squared_theta; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; long idx; }; -/* "neighbors/_quad_tree.pxd":99 +/* "_quad_tree.pxd":99 * # Private array manipulation to manage the ``cells`` array * cdef int _resize(self, SIZE_t capacity) nogil except -1 * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 * cdef np.ndarray _get_cell_ndarray(self) */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t capacity; }; -/* "neighbors/_quad_tree.pxd":100 +/* "_quad_tree.pxd":100 * cdef int _resize(self, SIZE_t capacity) nogil except -1 * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< * cdef np.ndarray _get_cell_ndarray(self) */ -struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell { +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell { int __pyx_n; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; }; -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord; -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord; -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord; -/* "sklearn/tree/_utils.pxd":23 +/* "_utils.pxd":23 * * * cdef enum: # <<<<<<<<<<<<<< @@ -1650,39 +1522,39 @@ struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord; * # We don't use RAND_MAX because it's different across platforms and */ enum { - __pyx_e_7sklearn_4tree_6_utils_RAND_R_MAX = 0x7FFFFFFF + __pyx_e_13stpredictions_6models_3OK3_6_utils_RAND_R_MAX = 0x7FFFFFFF }; -/* "sklearn/tree/_utils.pxd":70 +/* "_utils.pxd":70 * * # A record on the stack for depth-first tree growing * cdef struct StackRecord: # <<<<<<<<<<<<<< * SIZE_t start * SIZE_t end */ -struct __pyx_t_7sklearn_4tree_6_utils_StackRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t parent; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t depth; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t parent; int is_left; double impurity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t n_constant_features; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t n_constant_features; }; -/* "sklearn/tree/_utils.pxd":96 +/* "_utils.pxd":96 * * # A record on the frontier for best-first tree growing * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< * SIZE_t node_id * SIZE_t start */ -struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t node_id; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t start; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t end; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t pos; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t node_id; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t pos; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t depth; int is_leaf; double impurity; double impurity_left; @@ -1690,248 +1562,119 @@ struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord { double improvement; }; -/* "sklearn/tree/_utils.pxd":127 +/* "_utils.pxd":127 * * # A record stored in the WeightedPQueue * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< * DOUBLE_t data * DOUBLE_t weight */ -struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord { - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t data; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t weight; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t data; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t weight; }; -struct __pyx_t_5_tree_Node; -struct __pyx_opt_args_5_tree_4Tree__resize_c; -struct __pyx_opt_args_5_tree_4Tree_compute_feature_importances; -struct __pyx_opt_args_5_tree_11TreeBuilder_build; -struct __pyx_opt_args_5_tree_21DepthFirstTreeBuilder_build; -struct __pyx_opt_args_5_tree_20BestFirstTreeBuilder_build; - -/* "_tree.pxd":16 +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_build; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_build; + +/* "stpredictions/models/OK3/_tree.pxd":16 * from _splitter cimport SplitRecord * * cdef struct Node: # <<<<<<<<<<<<<< * # Base storage structure for the nodes in a Tree object * */ -struct __pyx_t_5_tree_Node { - __pyx_t_5_tree_SIZE_t left_child; - __pyx_t_5_tree_SIZE_t right_child; - __pyx_t_5_tree_SIZE_t feature; - __pyx_t_5_tree_DOUBLE_t threshold; - __pyx_t_5_tree_DOUBLE_t impurity; - __pyx_t_5_tree_SIZE_t n_node_samples; - __pyx_t_5_tree_DOUBLE_t weighted_n_node_samples; +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t left_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t right_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t threshold; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t impurity; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t weighted_n_node_samples; }; -/* "_tree.pxd":52 +/* "stpredictions/models/OK3/_tree.pxd":52 * double weighted_n_samples) nogil except -1 * cdef int _resize(self, SIZE_t capacity) nogil except -1 * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< * * cdef np.ndarray _get_value_ndarray(self) */ -struct __pyx_opt_args_5_tree_4Tree__resize_c { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c { int __pyx_n; - __pyx_t_5_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; }; -/* "_tree.pxd":68 +/* "stpredictions/models/OK3/_tree.pxd":68 * cdef object _decision_path_sparse_csr(self, object X) * * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< * * */ -struct __pyx_opt_args_5_tree_4Tree_compute_feature_importances { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances { int __pyx_n; PyObject *normalize; }; -/* "_tree.pxd":92 +/* "stpredictions/models/OK3/_tree.pxd":92 * cdef double min_impurity_decrease # Impurity threshold for early stopping * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< * np.ndarray sample_weight=*) * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) */ -struct __pyx_opt_args_5_tree_11TreeBuilder_build { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build { int __pyx_n; PyArrayObject *sample_weight; }; -/* "_tree.pyx":129 +/* "stpredictions/models/OK3/_tree.pyx":129 * self.min_impurity_split = min_impurity_split * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< * np.ndarray sample_weight=None): * """Build a decision tree from the training set (X, y).""" */ -struct __pyx_opt_args_5_tree_21DepthFirstTreeBuilder_build { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_build { int __pyx_n; PyArrayObject *sample_weight; }; -/* "_tree.pyx":303 +/* "stpredictions/models/OK3/_tree.pyx":303 * self.min_impurity_split = min_impurity_split * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< * np.ndarray sample_weight=None): * """Build a decision tree from the training set (X, y).""" */ -struct __pyx_opt_args_5_tree_20BestFirstTreeBuilder_build { +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_build { int __pyx_n; PyArrayObject *sample_weight; }; -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtab; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; - double weighted_n_samples; - double weighted_n_node_samples; - double weighted_n_left; - double weighted_n_right; - double *sum_total; - double *sum_left; - double *sum_right; -}; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t sum_stride; -}; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ -struct __pyx_obj_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion __pyx_base; - double sq_sum_total; -}; - - -/* "_splitter.pxd":34 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ -struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *criterion; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - PyObject *random_state; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - double weighted_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; -}; - - -/* "sklearn/tree/_tree.pxd":37 - * - * - * cdef class Tree: # <<<<<<<<<<<<<< - * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and - */ -struct __pyx_obj_7sklearn_4tree_5_tree_Tree { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtab; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_n_classes; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t node_count; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity; - struct __pyx_t_7sklearn_4tree_5_tree_Node *nodes; - double *value; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t value_stride; -}; - - -/* "sklearn/tree/_tree.pxd":85 - * # ============================================================================= - * - * cdef class TreeBuilder: # <<<<<<<<<<<<<< - * # The TreeBuilder recursively builds a Tree object from training samples, - * # using a Splitter object for splitting internal nodes and assigning - */ -struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder { - PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtab; - struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *splitter; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_split; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; - double min_weight_leaf; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth; - double min_impurity_split; - double min_impurity_decrease; -}; - - /* "_criterion.pxd":12 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * from ._tree cimport UINT32_t # Unsigned 32 bit integer * * cdef class Criterion: # <<<<<<<<<<<<<< * # The criterion computes the impurity of a node and the reduction of * # impurity of a split on that node. */ -struct __pyx_obj_10_criterion_Criterion { +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion { PyObject_HEAD - struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtab; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtab; __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *sample_weight; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t pos; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; double weighted_n_samples; double weighted_n_node_samples; double weighted_n_left; @@ -1946,8 +1689,8 @@ struct __pyx_obj_10_criterion_Criterion { * """Abstract kernelized output regression criterion.""" * */ -struct __pyx_obj_10_criterion_KernelizedRegressionCriterion { - struct __pyx_obj_10_criterion_Criterion __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; double sum_diag_Gramm; double sum_total_Gramm; double sum_diag_Gramm_left; @@ -1964,221 +1707,221 @@ struct __pyx_obj_10_criterion_KernelizedRegressionCriterion { * # The splitter searches in the input space for a feature and a threshold * # to split the samples samples[start:end]. */ -struct __pyx_obj_9_splitter_Splitter { +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter { PyObject_HEAD - struct __pyx_vtabstruct_9_splitter_Splitter *__pyx_vtab; - struct __pyx_obj_10_criterion_Criterion *criterion; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtab; + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *criterion; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; double min_weight_leaf; PyObject *random_state; - __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t rand_r_state; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_samples; double weighted_n_samples; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features; - __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t start; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *constant_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *feature_values; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t end; __Pyx_memviewslice y; - __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *sample_weight; }; -/* "neighbors/_quad_tree.pxd":55 +/* "_quad_tree.pxd":55 * * * cdef class _QuadTree: # <<<<<<<<<<<<<< * # The QuadTree object is a quad tree structure constructed by inserting * # recursively points in the tree and splitting cells in 4 so that each */ -struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree { +struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtab; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_vtab; int n_dimensions; int verbose; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_cells_per_cell; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t max_depth; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t cell_count; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t capacity; - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t n_points; - struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *cells; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t n_cells_per_cell; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_count; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t n_points; + struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *cells; }; -/* "sklearn/tree/_utils.pxd":79 +/* "_utils.pxd":79 * SIZE_t n_constant_features * * cdef class Stack: # <<<<<<<<<<<<<< * cdef SIZE_t capacity * cdef SIZE_t top */ -struct __pyx_obj_7sklearn_4tree_6_utils_Stack { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t top; - struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *stack_; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t top; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *stack_; }; -/* "sklearn/tree/_utils.pxd":108 +/* "_utils.pxd":108 * double improvement * * cdef class PriorityHeap: # <<<<<<<<<<<<<< * cdef SIZE_t capacity * cdef SIZE_t heap_ptr */ -struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t heap_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *heap_; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t heap_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *heap_; }; -/* "sklearn/tree/_utils.pxd":131 +/* "_utils.pxd":131 * DOUBLE_t weight * * cdef class WeightedPQueue: # <<<<<<<<<<<<<< * cdef SIZE_t capacity * cdef SIZE_t array_ptr */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t array_ptr; - struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *array_; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t array_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *array_; }; -/* "sklearn/tree/_utils.pxd":151 +/* "_utils.pxd":151 * # ============================================================================= * * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< * cdef SIZE_t initial_capacity * cdef WeightedPQueue samples */ -struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator { +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator { PyObject_HEAD - struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtab; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t initial_capacity; - struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *samples; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t total_weight; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t k; - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t sum_w_0_k; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t initial_capacity; + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *samples; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t total_weight; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t k; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t sum_w_0_k; }; -/* "_tree.pxd":28 +/* "stpredictions/models/OK3/_tree.pxd":28 * * * cdef class Tree: # <<<<<<<<<<<<<< * # The Tree object is a binary tree structure constructed by the * # TreeBuilder. */ -struct __pyx_obj_5_tree_Tree { +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree { PyObject_HEAD - struct __pyx_vtabstruct_5_tree_Tree *__pyx_vtab; - __pyx_t_5_tree_SIZE_t n_features; - __pyx_t_5_tree_SIZE_t max_depth; - __pyx_t_5_tree_SIZE_t node_count; - __pyx_t_5_tree_SIZE_t capacity; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t node_count; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; PyArrayObject *K_y; PyArrayObject *y; - struct __pyx_t_5_tree_Node *nodes; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *nodes; double *value; }; -/* "_tree.pxd":75 +/* "stpredictions/models/OK3/_tree.pxd":75 * # ============================================================================= * * cdef class TreeBuilder: # <<<<<<<<<<<<<< * # The TreeBuilder recursively builds a Tree object from training samples, * # using a Splitter object for splitting internal nodes and assigning */ -struct __pyx_obj_5_tree_TreeBuilder { +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder { PyObject_HEAD - struct __pyx_vtabstruct_5_tree_TreeBuilder *__pyx_vtab; - struct __pyx_obj_9_splitter_Splitter *splitter; - __pyx_t_5_tree_SIZE_t min_samples_split; - __pyx_t_5_tree_SIZE_t min_samples_leaf; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtab; + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *splitter; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_split; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; double min_weight_leaf; - __pyx_t_5_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; double min_impurity_split; double min_impurity_decrease; }; -/* "_tree.pyx":114 +/* "stpredictions/models/OK3/_tree.pyx":114 * # Depth first builder --------------------------------------------------------- * * cdef class DepthFirstTreeBuilder(TreeBuilder): # <<<<<<<<<<<<<< * """Build a decision tree in depth-first fashion.""" * */ -struct __pyx_obj_5_tree_DepthFirstTreeBuilder { - struct __pyx_obj_5_tree_TreeBuilder __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder __pyx_base; }; -/* "_tree.pyx":282 +/* "stpredictions/models/OK3/_tree.pyx":282 * * * cdef class BestFirstTreeBuilder(TreeBuilder): # <<<<<<<<<<<<<< * """Build a decision tree in best-first fashion. * */ -struct __pyx_obj_5_tree_BestFirstTreeBuilder { - struct __pyx_obj_5_tree_TreeBuilder __pyx_base; - __pyx_t_5_tree_SIZE_t max_leaf_nodes; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder __pyx_base; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_leaf_nodes; }; -/* "_tree.pyx":1316 +/* "stpredictions/models/OK3/_tree.pyx":1316 * * * cdef class _CCPPruneController: # <<<<<<<<<<<<<< * """Base class used by build_pruned_tree_ccp and ccp_pruning_path * to control pruning. */ -struct __pyx_obj_5_tree__CCPPruneController { +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController { PyObject_HEAD - struct __pyx_vtabstruct_5_tree__CCPPruneController *__pyx_vtab; + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_vtab; }; -/* "_tree.pyx":1334 +/* "stpredictions/models/OK3/_tree.pyx":1334 * * * cdef class _AlphaPruner(_CCPPruneController): # <<<<<<<<<<<<<< * """Use alpha to control when to stop pruning.""" * cdef DOUBLE_t ccp_alpha */ -struct __pyx_obj_5_tree__AlphaPruner { - struct __pyx_obj_5_tree__CCPPruneController __pyx_base; - __pyx_t_5_tree_DOUBLE_t ccp_alpha; - __pyx_t_5_tree_SIZE_t capacity; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController __pyx_base; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t ccp_alpha; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; }; -/* "_tree.pyx":1355 +/* "stpredictions/models/OK3/_tree.pyx":1355 * * * cdef class _PathFinder(_CCPPruneController): # <<<<<<<<<<<<<< * """Record metrics used to return the cost complexity path.""" * cdef DOUBLE_t[:] ccp_alphas */ -struct __pyx_obj_5_tree__PathFinder { - struct __pyx_obj_5_tree__CCPPruneController __pyx_base; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController __pyx_base; __Pyx_memviewslice ccp_alphas; __Pyx_memviewslice impurities; - __pyx_t_5_tree_UINT32_t count; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t count; }; @@ -2260,135 +2003,26 @@ struct __pyx_memoryviewslice_obj { -/* "_criterion.pxd":21 - * from ._tree cimport UINT32_t # Unsigned 32 bit integer - * - * cdef class Criterion: # <<<<<<<<<<<<<< - * # The criterion computes the impurity of a node and the reduction of - * # impurity of a split on that node. It also computes the output statistics - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion { - int (*init)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *, double, double, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_7sklearn_4tree_10_criterion_Criterion *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_Criterion; - - -/* "_criterion.pxd":70 - * cdef double proxy_impurity_improvement(self) nogil - * - * cdef class ClassificationCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract criterion for classification.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_ClassificationCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_ClassificationCriterion; - - -/* "_criterion.pxd":76 - * cdef SIZE_t sum_stride - * - * cdef class RegressionCriterion(Criterion): # <<<<<<<<<<<<<< - * """Abstract regression criterion.""" - * - */ - -struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion { - struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_Criterion __pyx_base; -}; -static struct __pyx_vtabstruct_7sklearn_4tree_10_criterion_RegressionCriterion *__pyx_vtabptr_7sklearn_4tree_10_criterion_RegressionCriterion; - - -/* "_splitter.pxd":34 - * double impurity_right # Impurity of the right split. - * - * cdef class Splitter: # <<<<<<<<<<<<<< - * # The splitter searches in the input space for a feature and a threshold - * # to split the samples samples[start:end]. - */ - -struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter { - int (*init)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); - int (*node_reset)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); - int (*node_split)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double, struct __pyx_t_7sklearn_4tree_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); - void (*node_value)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *, double *); - double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_9_splitter_Splitter *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_9_splitter_Splitter *__pyx_vtabptr_7sklearn_4tree_9_splitter_Splitter; - - -/* "sklearn/tree/_tree.pxd":37 - * - * - * cdef class Tree: # <<<<<<<<<<<<<< - * # The Tree object is a binary tree structure constructed by the - * # TreeBuilder. The tree structure is used for predictions and - */ - -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree { - __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double); - int (*_resize)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args); - PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *); - PyArrayObject *(*predict)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*apply)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*_apply_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*decision_path)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyObject *(*_decision_path_dense)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *); - PyObject *(*compute_feature_importances)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklearn_4tree_5_tree_Tree; - - -/* "sklearn/tree/_tree.pxd":85 - * # ============================================================================= - * - * cdef class TreeBuilder: # <<<<<<<<<<<<<< - * # The TreeBuilder recursively builds a Tree object from training samples, - * # using a Splitter object for splitting internal nodes and assigning - */ - -struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder { - PyObject *(*build)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args); - PyObject *(*_check_input)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); -}; -static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder; - - /* "_criterion.pxd":12 - * from sklearn.tree._tree cimport UINT32_t # Unsigned 32 bit integer + * from ._tree cimport UINT32_t # Unsigned 32 bit integer * * cdef class Criterion: # <<<<<<<<<<<<<< * # The criterion computes the impurity of a node and the reduction of * # impurity of a split on that node. */ -struct __pyx_vtabstruct_10_criterion_Criterion { - int (*init)(struct __pyx_obj_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - int (*reset)(struct __pyx_obj_10_criterion_Criterion *); - int (*reverse_reset)(struct __pyx_obj_10_criterion_Criterion *); - int (*update)(struct __pyx_obj_10_criterion_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); - double (*node_impurity)(struct __pyx_obj_10_criterion_Criterion *); - void (*children_impurity)(struct __pyx_obj_10_criterion_Criterion *, double *, double *); - void (*node_value)(struct __pyx_obj_10_criterion_Criterion *, double *); - double (*impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *, double); - double (*proxy_impurity_improvement)(struct __pyx_obj_10_criterion_Criterion *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion { + int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); }; -static struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtabptr_10_criterion_Criterion; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion; /* "_criterion.pxd":50 @@ -2399,10 +2033,10 @@ static struct __pyx_vtabstruct_10_criterion_Criterion *__pyx_vtabptr_10_criterio * */ -struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion { - struct __pyx_vtabstruct_10_criterion_Criterion __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; }; -static struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_10_criterion_KernelizedRegressionCriterion; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; /* "_splitter.pxd":25 @@ -2413,17 +2047,17 @@ static struct __pyx_vtabstruct_10_criterion_KernelizedRegressionCriterion *__pyx * # to split the samples samples[start:end]. */ -struct __pyx_vtabstruct_9_splitter_Splitter { - int (*init)(struct __pyx_obj_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *); - int (*node_reset)(struct __pyx_obj_9_splitter_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *); - int (*node_split)(struct __pyx_obj_9_splitter_Splitter *, double, struct __pyx_t_9_splitter_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *); - void (*node_value)(struct __pyx_obj_9_splitter_Splitter *, double *); - double (*node_impurity)(struct __pyx_obj_9_splitter_Splitter *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter { + int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *); + int (*node_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double *); + int (*node_split)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *); + void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double *); + double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *); }; -static struct __pyx_vtabstruct_9_splitter_Splitter *__pyx_vtabptr_9_splitter_Splitter; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_Splitter; -/* "neighbors/_quad_tree.pxd":55 +/* "_quad_tree.pxd":55 * * * cdef class _QuadTree: # <<<<<<<<<<<<<< @@ -2431,24 +2065,24 @@ static struct __pyx_vtabstruct_9_splitter_Splitter *__pyx_vtabptr_9_splitter_Spl * # recursively points in the tree and splitting cells in 4 so that each */ -struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree { - int (*insert_point)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); - __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_is_duplicate)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - long (*summarize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); - void (*_init_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - void (*_init_root)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *); - int (*_check_point_in_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *); - int (*_resize)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); - int (*_get_cell)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *, __pyx_t_7sklearn_9neighbors_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_7sklearn_9neighbors_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); - PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_7sklearn_9neighbors_10_quad_tree__QuadTree *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree { + int (*insert_point)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *); + int (*_is_duplicate)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *); + long (*summarize)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); + void (*_init_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t); + void (*_init_root)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *); + int (*_check_point_in_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *); + int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); + int (*_get_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); + PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *); }; -static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx_vtabptr_7sklearn_9neighbors_10_quad_tree__QuadTree; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_vtabptr_13stpredictions_6models_3OK3_10_quad_tree__QuadTree; -/* "sklearn/tree/_utils.pxd":79 +/* "_utils.pxd":79 * SIZE_t n_constant_features * * cdef class Stack: # <<<<<<<<<<<<<< @@ -2456,15 +2090,15 @@ static struct __pyx_vtabstruct_7sklearn_9neighbors_10_quad_tree__QuadTree *__pyx * cdef SIZE_t top */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, int, double, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7sklearn_4tree_6_utils_Stack; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_Stack; -/* "sklearn/tree/_utils.pxd":108 +/* "_utils.pxd":108 * double improvement * * cdef class PriorityHeap: # <<<<<<<<<<<<<< @@ -2472,17 +2106,17 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7skle * cdef SIZE_t heap_ptr */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); - void (*heapify_up)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - void (*heapify_down)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, double, double, double); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *); + void (*heapify_up)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + void (*heapify_down)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, int, double, double, double, double); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabptr_7sklearn_4tree_6_utils_PriorityHeap; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_PriorityHeap; -/* "sklearn/tree/_utils.pxd":131 +/* "_utils.pxd":131 * DOUBLE_t weight * * cdef class WeightedPQueue: # <<<<<<<<<<<<<< @@ -2490,21 +2124,21 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabpt * cdef SIZE_t array_ptr */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue { - int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*peek)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedPQueue *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*size)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + int (*peek)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedPQueue; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; -/* "sklearn/tree/_utils.pxd":151 +/* "_utils.pxd":151 * # ============================================================================= * * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< @@ -2512,20 +2146,20 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedPQueue *__pyx_vtab * cdef WeightedPQueue samples */ -struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator { - __pyx_t_7sklearn_4tree_6_utils_SIZE_t (*size)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*reset)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); - int (*update_median_parameters_post_push)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *); - int (*update_median_parameters_post_remove)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t, __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t); - __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_7sklearn_4tree_6_utils_WeightedMedianCalculator *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*size)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); + int (*update_median_parameters_post_push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + int (*update_median_parameters_post_remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); }; -static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator *__pyx_vtabptr_7sklearn_4tree_6_utils_WeightedMedianCalculator; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; -/* "_tree.pyx":503 +/* "stpredictions/models/OK3/_tree.pyx":503 * # ============================================================================= * * cdef class Tree: # <<<<<<<<<<<<<< @@ -2533,30 +2167,30 @@ static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_WeightedMedianCalculator * * */ -struct __pyx_vtabstruct_5_tree_Tree { - __pyx_t_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_5_tree_Tree *, __pyx_t_5_tree_SIZE_t, int, int, __pyx_t_5_tree_SIZE_t, double, double, __pyx_t_5_tree_SIZE_t, double); - int (*_resize)(struct __pyx_obj_5_tree_Tree *, __pyx_t_5_tree_SIZE_t); - int (*_resize_c)(struct __pyx_obj_5_tree_Tree *, struct __pyx_opt_args_5_tree_4Tree__resize_c *__pyx_optional_args); - PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_5_tree_Tree *); - PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_5_tree_Tree *); - PyArrayObject *(*decode_tree)(struct __pyx_obj_5_tree_Tree *, PyArrayObject *, PyArrayObject *, PyObject *, PyObject *, __pyx_t_5_tree_SIZE_t, int __pyx_skip_dispatch); - PyArrayObject *(*predict)(struct __pyx_obj_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*apply)(struct __pyx_obj_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyArrayObject *(*_apply_dense)(struct __pyx_obj_5_tree_Tree *, PyObject *); - PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_5_tree_Tree *, PyObject *); - PyObject *(*decision_path)(struct __pyx_obj_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); - PyObject *(*_decision_path_dense)(struct __pyx_obj_5_tree_Tree *, PyObject *); - PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_5_tree_Tree *, PyObject *); - PyObject *(*compute_feature_importances)(struct __pyx_obj_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int, int, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double); + int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c *__pyx_optional_args); + PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); + PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); + PyArrayObject *(*decode_tree)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyArrayObject *, PyArrayObject *, PyObject *, PyObject *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int __pyx_skip_dispatch); + PyArrayObject *(*predict)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*apply)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*_apply_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*decision_path)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyObject *(*_decision_path_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*compute_feature_importances)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); }; -static struct __pyx_vtabstruct_5_tree_Tree *__pyx_vtabptr_5_tree_Tree; -static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_Tree *, PyObject *); -static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_tree_Tree *, PyObject *); -static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tree_Tree *, PyObject *); -static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj_5_tree_Tree *, PyObject *); +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_Tree; +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__apply_dense(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__decision_path_dense(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); -/* "_tree.pyx":75 +/* "stpredictions/models/OK3/_tree.pyx":75 * # ============================================================================= * * cdef class TreeBuilder: # <<<<<<<<<<<<<< @@ -2564,15 +2198,15 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj * */ -struct __pyx_vtabstruct_5_tree_TreeBuilder { - PyObject *(*build)(struct __pyx_obj_5_tree_TreeBuilder *, struct __pyx_obj_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_11TreeBuilder_build *__pyx_optional_args); - PyObject *(*_check_input)(struct __pyx_obj_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder { + PyObject *(*build)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build *__pyx_optional_args); + PyObject *(*_check_input)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); }; -static struct __pyx_vtabstruct_5_tree_TreeBuilder *__pyx_vtabptr_5_tree_TreeBuilder; -static PyObject *__pyx_f_5_tree_11TreeBuilder__check_input(struct __pyx_obj_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_TreeBuilder; +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_11TreeBuilder__check_input(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); -/* "_tree.pyx":114 +/* "stpredictions/models/OK3/_tree.pyx":114 * # Depth first builder --------------------------------------------------------- * * cdef class DepthFirstTreeBuilder(TreeBuilder): # <<<<<<<<<<<<<< @@ -2580,13 +2214,13 @@ static PyObject *__pyx_f_5_tree_11TreeBuilder__check_input(struct __pyx_obj_5_tr * */ -struct __pyx_vtabstruct_5_tree_DepthFirstTreeBuilder { - struct __pyx_vtabstruct_5_tree_TreeBuilder __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder __pyx_base; }; -static struct __pyx_vtabstruct_5_tree_DepthFirstTreeBuilder *__pyx_vtabptr_5_tree_DepthFirstTreeBuilder; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder; -/* "_tree.pyx":282 +/* "stpredictions/models/OK3/_tree.pyx":282 * * * cdef class BestFirstTreeBuilder(TreeBuilder): # <<<<<<<<<<<<<< @@ -2594,15 +2228,15 @@ static struct __pyx_vtabstruct_5_tree_DepthFirstTreeBuilder *__pyx_vtabptr_5_tre * */ -struct __pyx_vtabstruct_5_tree_BestFirstTreeBuilder { - struct __pyx_vtabstruct_5_tree_TreeBuilder __pyx_base; - int (*_add_split_node)(struct __pyx_obj_5_tree_BestFirstTreeBuilder *, struct __pyx_obj_9_splitter_Splitter *, struct __pyx_obj_5_tree_Tree *, __pyx_t_5_tree_SIZE_t, __pyx_t_5_tree_SIZE_t, double, int, int, struct __pyx_t_5_tree_Node *, __pyx_t_5_tree_SIZE_t, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_5_tree_SIZE_t); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder __pyx_base; + int (*_add_split_node)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, int, int, struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); }; -static struct __pyx_vtabstruct_5_tree_BestFirstTreeBuilder *__pyx_vtabptr_5_tree_BestFirstTreeBuilder; -static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_5_tree_BestFirstTreeBuilder *, struct __pyx_obj_9_splitter_Splitter *, struct __pyx_obj_5_tree_Tree *, __pyx_t_5_tree_SIZE_t, __pyx_t_5_tree_SIZE_t, double, int, int, struct __pyx_t_5_tree_Node *, __pyx_t_5_tree_SIZE_t, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, __pyx_t_5_tree_SIZE_t); +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder; +static CYTHON_INLINE int __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, int, int, struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); -/* "_tree.pyx":1316 +/* "stpredictions/models/OK3/_tree.pyx":1316 * * * cdef class _CCPPruneController: # <<<<<<<<<<<<<< @@ -2610,15 +2244,15 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s * to control pruning. */ -struct __pyx_vtabstruct_5_tree__CCPPruneController { - int (*stop_pruning)(struct __pyx_obj_5_tree__CCPPruneController *, __pyx_t_5_tree_DOUBLE_t); - void (*save_metrics)(struct __pyx_obj_5_tree__CCPPruneController *, __pyx_t_5_tree_DOUBLE_t, __pyx_t_5_tree_DOUBLE_t); - void (*after_pruning)(struct __pyx_obj_5_tree__CCPPruneController *, __Pyx_memviewslice); +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController { + int (*stop_pruning)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t); + void (*save_metrics)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t); + void (*after_pruning)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *, __Pyx_memviewslice); }; -static struct __pyx_vtabstruct_5_tree__CCPPruneController *__pyx_vtabptr_5_tree__CCPPruneController; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree__CCPPruneController; -/* "_tree.pyx":1334 +/* "stpredictions/models/OK3/_tree.pyx":1334 * * * cdef class _AlphaPruner(_CCPPruneController): # <<<<<<<<<<<<<< @@ -2626,13 +2260,13 @@ static struct __pyx_vtabstruct_5_tree__CCPPruneController *__pyx_vtabptr_5_tree_ * cdef DOUBLE_t ccp_alpha */ -struct __pyx_vtabstruct_5_tree__AlphaPruner { - struct __pyx_vtabstruct_5_tree__CCPPruneController __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__AlphaPruner { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController __pyx_base; }; -static struct __pyx_vtabstruct_5_tree__AlphaPruner *__pyx_vtabptr_5_tree__AlphaPruner; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree__AlphaPruner; -/* "_tree.pyx":1355 +/* "stpredictions/models/OK3/_tree.pyx":1355 * * * cdef class _PathFinder(_CCPPruneController): # <<<<<<<<<<<<<< @@ -2640,10 +2274,10 @@ static struct __pyx_vtabstruct_5_tree__AlphaPruner *__pyx_vtabptr_5_tree__AlphaP * cdef DOUBLE_t[:] ccp_alphas */ -struct __pyx_vtabstruct_5_tree__PathFinder { - struct __pyx_vtabstruct_5_tree__CCPPruneController __pyx_base; +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__PathFinder { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController __pyx_base; }; -static struct __pyx_vtabstruct_5_tree__PathFinder *__pyx_vtabptr_5_tree__PathFinder; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__PathFinder *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree__PathFinder; /* "View.MemoryView":105 @@ -3402,11 +3036,11 @@ static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); #define __Pyx_HAS_GCC_DIAGNOSTIC #endif -struct __pyx_t_5_tree_Node; -static PyObject* __pyx_convert__to_py_struct____pyx_t_5_tree_Node(struct __pyx_t_5_tree_Node s); +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node; +static PyObject* __pyx_convert__to_py_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node s); /* MemviewDtypeToObject.proto */ -static CYTHON_INLINE PyObject *__pyx_memview_get_nn_struct____pyx_t_5_tree_Node(const char *itemp); -static CYTHON_INLINE int __pyx_memview_set_nn_struct____pyx_t_5_tree_Node(const char *itemp, PyObject *obj); +static CYTHON_INLINE PyObject *__pyx_memview_get_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(const char *itemp); +static CYTHON_INLINE int __pyx_memview_set_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(const char *itemp, PyObject *obj); /* None.proto */ static CYTHON_INLINE long __Pyx_pow_long(long, long); @@ -3570,16 +3204,16 @@ static int __Pyx_ValidateAndInit_memviewslice( PyObject *original_obj); /* ObjectToMemviewSlice.proto */ -static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__(PyObject *, int writable_flag); +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t__const__(PyObject *, int writable_flag); /* ObjectToMemviewSlice.proto */ -static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_5_tree_DTYPE_t__const__(PyObject *, int writable_flag); +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t__const__(PyObject *, int writable_flag); /* ObjectToMemviewSlice.proto */ -static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_DOUBLE_t(PyObject *, int writable_flag); +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t(PyObject *, int writable_flag); /* ObjectToMemviewSlice.proto */ -static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_SIZE_t(PyObject *, int writable_flag); +static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t(PyObject *, int writable_flag); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_unsigned_char(PyObject *, int writable_flag); @@ -3596,31 +3230,31 @@ static int __Pyx_ImportFunction(PyObject *module, const char *funcname, void (** /* InitStrings.proto */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); -static PyObject *__pyx_f_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_5_tree_Tree *__pyx_v_tree, CYTHON_UNUSED PyObject *__pyx_v_X, CYTHON_UNUSED PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_11TreeBuilder_build *__pyx_optional_args); /* proto*/ -static PyObject *__pyx_f_5_tree_11TreeBuilder__check_input(CYTHON_UNUSED struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto*/ -static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_21DepthFirstTreeBuilder_build *__pyx_optional_args); /* proto*/ -static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_20BestFirstTreeBuilder_build *__pyx_optional_args); /* proto*/ -static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, __pyx_t_5_tree_SIZE_t __pyx_v_start, __pyx_t_5_tree_SIZE_t __pyx_v_end, double __pyx_v_impurity, int __pyx_v_is_first, int __pyx_v_is_left, struct __pyx_t_5_tree_Node *__pyx_v_parent, __pyx_t_5_tree_SIZE_t __pyx_v_depth, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *__pyx_v_res, __pyx_t_5_tree_SIZE_t __pyx_v_n_samples); /* proto*/ -static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_self, __pyx_t_5_tree_SIZE_t __pyx_v_capacity); /* proto*/ -static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_self, struct __pyx_opt_args_5_tree_4Tree__resize_c *__pyx_optional_args); /* proto*/ -static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_tree_Tree *__pyx_v_self, __pyx_t_5_tree_SIZE_t __pyx_v_parent, int __pyx_v_is_left, int __pyx_v_is_leaf, __pyx_t_5_tree_SIZE_t __pyx_v_feature, double __pyx_v_threshold, double __pyx_v_impurity, __pyx_t_5_tree_SIZE_t __pyx_v_n_node_samples, double __pyx_v_weighted_n_node_samples); /* proto*/ -static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ -static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_K_cand_train, PyArrayObject *__pyx_v_sq_norms_cand, PyObject *__pyx_v_criterion, PyObject *__pyx_v_kernel, __pyx_t_5_tree_SIZE_t __pyx_v_return_top_k, int __pyx_skip_dispatch); /* proto*/ -static PyArrayObject *__pyx_f_5_tree_4Tree_apply(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ -static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ -static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ -static PyObject *__pyx_f_5_tree_4Tree_decision_path(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ -static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ -static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ -static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_obj_5_tree_Tree *__pyx_v_self, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); /* proto*/ -static PyArrayObject *__pyx_f_5_tree_4Tree__get_value_ndarray(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto*/ -static PyArrayObject *__pyx_f_5_tree_4Tree__get_node_ndarray(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto*/ -static int __pyx_f_5_tree_19_CCPPruneController_stop_pruning(CYTHON_UNUSED struct __pyx_obj_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __pyx_t_5_tree_DOUBLE_t __pyx_v_effective_alpha); /* proto*/ -static void __pyx_f_5_tree_19_CCPPruneController_save_metrics(CYTHON_UNUSED struct __pyx_obj_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __pyx_t_5_tree_DOUBLE_t __pyx_v_effective_alpha, CYTHON_UNUSED __pyx_t_5_tree_DOUBLE_t __pyx_v_subtree_impurities); /* proto*/ -static void __pyx_f_5_tree_19_CCPPruneController_after_pruning(CYTHON_UNUSED struct __pyx_obj_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_in_subtree); /* proto*/ -static int __pyx_f_5_tree_12_AlphaPruner_stop_pruning(struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_self, __pyx_t_5_tree_DOUBLE_t __pyx_v_effective_alpha); /* proto*/ -static void __pyx_f_5_tree_12_AlphaPruner_after_pruning(struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_self, __Pyx_memviewslice __pyx_v_in_subtree); /* proto*/ -static void __pyx_f_5_tree_11_PathFinder_save_metrics(struct __pyx_obj_5_tree__PathFinder *__pyx_v_self, __pyx_t_5_tree_DOUBLE_t __pyx_v_effective_alpha, __pyx_t_5_tree_DOUBLE_t __pyx_v_subtree_impurities); /* proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, CYTHON_UNUSED PyObject *__pyx_v_X, CYTHON_UNUSED PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build *__pyx_optional_args); /* proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_11TreeBuilder__check_input(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_build *__pyx_optional_args); /* proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_build *__pyx_optional_args); /* proto*/ +static CYTHON_INLINE int __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end, double __pyx_v_impurity, int __pyx_v_is_first, int __pyx_v_is_left, struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_parent, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_depth, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *__pyx_v_res, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_samples); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__resize(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_capacity); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c *__pyx_optional_args); /* proto*/ +static __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__add_node(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_parent, int __pyx_v_is_left, int __pyx_v_is_leaf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_feature, double __pyx_v_threshold, double __pyx_v_impurity, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_node_samples, double __pyx_v_weighted_n_node_samples); /* proto*/ +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_predict(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_decode_tree(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_K_cand_train, PyArrayObject *__pyx_v_sq_norms_cand, PyObject *__pyx_v_criterion, PyObject *__pyx_v_kernel, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_return_top_k, int __pyx_skip_dispatch); /* proto*/ +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_apply(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__apply_dense(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_decision_path(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch); /* proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__decision_path_dense(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); /* proto*/ +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__get_value_ndarray(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto*/ +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__get_node_ndarray(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController_stop_pruning(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_effective_alpha); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController_save_metrics(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_effective_alpha, CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_subtree_impurities); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController_after_pruning(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_v_self, CYTHON_UNUSED __Pyx_memviewslice __pyx_v_in_subtree); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_stop_pruning(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_effective_alpha); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_after_pruning(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_self, __Pyx_memviewslice __pyx_v_in_subtree); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_5_tree_11_PathFinder_save_metrics(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_effective_alpha, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_subtree_impurities); /* proto*/ static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ @@ -3725,24 +3359,12 @@ static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ -/* Module declarations from 'sklearn.tree._criterion' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_Criterion = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_ClassificationCriterion = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_10_criterion_RegressionCriterion = 0; - -/* Module declarations from 'sklearn.tree._splitter' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_9_splitter_Splitter = 0; - -/* Module declarations from 'sklearn.tree._tree' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_Tree = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_TreeBuilder = 0; - -/* Module declarations from '_criterion' */ -static PyTypeObject *__pyx_ptype_10_criterion_Criterion = 0; -static PyTypeObject *__pyx_ptype_10_criterion_KernelizedRegressionCriterion = 0; +/* Module declarations from 'stpredictions.models.OK3._criterion' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_Criterion = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion = 0; -/* Module declarations from '_splitter' */ -static PyTypeObject *__pyx_ptype_9_splitter_Splitter = 0; +/* Module declarations from 'stpredictions.models.OK3._splitter' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_Splitter = 0; /* Module declarations from 'libc.stdlib' */ @@ -3750,51 +3372,51 @@ static PyTypeObject *__pyx_ptype_9_splitter_Splitter = 0; /* Module declarations from 'libc.stdint' */ -/* Module declarations from 'sklearn.neighbors._quad_tree' */ -static PyTypeObject *__pyx_ptype_7sklearn_9neighbors_10_quad_tree__QuadTree = 0; -static float *__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON = 0; -#define __pyx_v_7sklearn_9neighbors_10_quad_tree_EPSILON (*__pyx_vp_7sklearn_9neighbors_10_quad_tree_EPSILON) - -/* Module declarations from 'sklearn.tree._utils' */ -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_Stack = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_PriorityHeap = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedPQueue = 0; -static PyTypeObject *__pyx_ptype_7sklearn_4tree_6_utils_WeightedMedianCalculator = 0; -static PyArrayObject *(*__pyx_f_7sklearn_4tree_6_utils_sizet_ptr_to_ndarray)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DTYPE_t **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_SIZE_t **, size_t); /*proto*/ -static unsigned char *(*__pyx_fuse_2__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **, size_t); /*proto*/ -static __pyx_t_7sklearn_4tree_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(__pyx_t_7sklearn_4tree_6_utils_DOUBLE_t ***, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_5_tree_Node *(*__pyx_fuse_6__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_9neighbors_10_quad_tree_Cell **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_5_tree_Node **(*__pyx_fuse_8__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_5_tree_Node ***, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_StackRecord **, size_t); /*proto*/ -static struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_7sklearn_4tree_6_utils_safe_realloc)(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord **, size_t); /*proto*/ - -/* Module declarations from '_tree' */ -static PyTypeObject *__pyx_ptype_5_tree_Tree = 0; -static PyTypeObject *__pyx_ptype_5_tree_TreeBuilder = 0; -static PyTypeObject *__pyx_ptype_5_tree_DepthFirstTreeBuilder = 0; -static PyTypeObject *__pyx_ptype_5_tree_BestFirstTreeBuilder = 0; -static PyTypeObject *__pyx_ptype_5_tree__CCPPruneController = 0; -static PyTypeObject *__pyx_ptype_5_tree__AlphaPruner = 0; -static PyTypeObject *__pyx_ptype_5_tree__PathFinder = 0; +/* Module declarations from 'stpredictions.models.OK3._quad_tree' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_quad_tree__QuadTree = 0; +static float *__pyx_vp_13stpredictions_6models_3OK3_10_quad_tree_EPSILON = 0; +#define __pyx_v_13stpredictions_6models_3OK3_10_quad_tree_EPSILON (*__pyx_vp_13stpredictions_6models_3OK3_10_quad_tree_EPSILON) + +/* Module declarations from 'stpredictions.models.OK3._utils' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_Stack = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_PriorityHeap = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_WeightedPQueue = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator = 0; +static PyArrayObject *(*__pyx_f_13stpredictions_6models_3OK3_6_utils_sizet_ptr_to_ndarray)(__pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t *(*__pyx_fuse_0__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t *(*__pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t **, size_t); /*proto*/ +static unsigned char *(*__pyx_fuse_2__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(unsigned char **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *(*__pyx_fuse_3__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *(*__pyx_fuse_4__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t **(*__pyx_fuse_5__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(__pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t ***, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *(*__pyx_fuse_6__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *(*__pyx_fuse_7__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node **(*__pyx_fuse_8__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node ***, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *(*__pyx_fuse_9__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *(*__pyx_fuse_10__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc)(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord **, size_t); /*proto*/ + +/* Module declarations from 'stpredictions.models.OK3._tree' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree_Tree = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree_TreeBuilder = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree__CCPPruneController = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree__AlphaPruner = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree__PathFinder = 0; static PyTypeObject *__pyx_array_type = 0; static PyTypeObject *__pyx_MemviewEnum_type = 0; static PyTypeObject *__pyx_memoryview_type = 0; static PyTypeObject *__pyx_memoryviewslice_type = 0; -static double __pyx_v_5_tree_INFINITY; -static double __pyx_v_5_tree_EPSILON; -static int __pyx_v_5_tree_IS_FIRST; -static int __pyx_v_5_tree_IS_NOT_FIRST; -static int __pyx_v_5_tree_IS_LEFT; -static int __pyx_v_5_tree_IS_NOT_LEFT; -static __pyx_t_5_tree_SIZE_t __pyx_v_5_tree__TREE_LEAF; -static __pyx_t_5_tree_SIZE_t __pyx_v_5_tree__TREE_UNDEFINED; -static __pyx_t_5_tree_SIZE_t __pyx_v_5_tree_INITIAL_STACK_SIZE; -static struct __pyx_t_5_tree_Node __pyx_v_5_tree_dummy; +static double __pyx_v_13stpredictions_6models_3OK3_5_tree_INFINITY; +static double __pyx_v_13stpredictions_6models_3OK3_5_tree_EPSILON; +static int __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_FIRST; +static int __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_FIRST; +static int __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_LEFT; +static int __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_LEFT; +static __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF; +static __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED; +static __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_13stpredictions_6models_3OK3_5_tree_INITIAL_STACK_SIZE; +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node __pyx_v_13stpredictions_6models_3OK3_5_tree_dummy; static PyObject *generic = 0; static PyObject *strided = 0; static PyObject *indirect = 0; @@ -3802,12 +3424,12 @@ static PyObject *contiguous = 0; static PyObject *indirect_contiguous = 0; static int __pyx_memoryview_thread_locks_used; static PyThread_type_lock __pyx_memoryview_thread_locks[8]; -static CYTHON_INLINE int __pyx_f_5_tree__add_to_frontier(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); /*proto*/ -static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice, struct __pyx_obj_5_tree_Tree *, struct __pyx_obj_5_tree__CCPPruneController *); /*proto*/ -static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree *, struct __pyx_obj_5_tree_Tree *, __Pyx_memviewslice, __pyx_t_5_tree_SIZE_t); /*proto*/ -static PyObject *__pyx_f_5_tree___pyx_unpickle_TreeBuilder__set_state(struct __pyx_obj_5_tree_TreeBuilder *, PyObject *); /*proto*/ -static PyObject *__pyx_f_5_tree___pyx_unpickle__CCPPruneController__set_state(struct __pyx_obj_5_tree__CCPPruneController *, PyObject *); /*proto*/ -static struct __pyx_t_5_tree_Node __pyx_convert__from_py_struct____pyx_t_5_tree_Node(PyObject *); /*proto*/ +static CYTHON_INLINE int __pyx_f_13stpredictions_6models_3OK3_5_tree__add_to_frontier(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *); /*proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree__cost_complexity_prune(__Pyx_memviewslice, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *); /*proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree__build_pruned_tree(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); /*proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree___pyx_unpickle_TreeBuilder__set_state(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, PyObject *); /*proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree___pyx_unpickle__CCPPruneController__set_state(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *, PyObject *); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node __pyx_convert__from_py_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(PyObject *); /*proto*/ static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ static void *__pyx_align_pointer(void *, size_t); /*proto*/ static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ @@ -3842,30 +3464,30 @@ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ static PyObject *__pyx_format_from_typeinfo(__Pyx_TypeInfo *); /*proto*/ -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t = { "SIZE_t", NULL, sizeof(__pyx_t_5_tree_SIZE_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_5_tree_SIZE_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_5_tree_SIZE_t), 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5_tree_DTYPE_t = { "DTYPE_t", NULL, sizeof(__pyx_t_5_tree_DTYPE_t), { 0 }, 0, 'R', 0, 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5_tree_INT32_t = { "INT32_t", NULL, sizeof(__pyx_t_5_tree_INT32_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_5_tree_INT32_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_5_tree_INT32_t), 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t = { "SIZE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t), 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t = { "DTYPE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t = { "INT32_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t), 0 }; static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t = { "float64_t", NULL, sizeof(__pyx_t_5numpy_float64_t), { 0 }, 0, 'R', 0, 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5_tree_DOUBLE_t = { "DOUBLE_t", NULL, sizeof(__pyx_t_5_tree_DOUBLE_t), { 0 }, 0, 'R', 0, 0 }; -static __Pyx_StructField __Pyx_StructFields_nn_struct____pyx_t_5_tree_Node[] = { - {&__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, "left_child", offsetof(struct __pyx_t_5_tree_Node, left_child)}, - {&__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, "right_child", offsetof(struct __pyx_t_5_tree_Node, right_child)}, - {&__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, "feature", offsetof(struct __pyx_t_5_tree_Node, feature)}, - {&__Pyx_TypeInfo_nn___pyx_t_5_tree_DOUBLE_t, "threshold", offsetof(struct __pyx_t_5_tree_Node, threshold)}, - {&__Pyx_TypeInfo_nn___pyx_t_5_tree_DOUBLE_t, "impurity", offsetof(struct __pyx_t_5_tree_Node, impurity)}, - {&__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, "n_node_samples", offsetof(struct __pyx_t_5_tree_Node, n_node_samples)}, - {&__Pyx_TypeInfo_nn___pyx_t_5_tree_DOUBLE_t, "weighted_n_node_samples", offsetof(struct __pyx_t_5_tree_Node, weighted_n_node_samples)}, +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t = { "DOUBLE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_StructField __Pyx_StructFields_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node[] = { + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, "left_child", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, left_child)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, "right_child", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, right_child)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, "feature", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, feature)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t, "threshold", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, threshold)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t, "impurity", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, impurity)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, "n_node_samples", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, n_node_samples)}, + {&__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t, "weighted_n_node_samples", offsetof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node, weighted_n_node_samples)}, {NULL, NULL, 0} }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn_struct____pyx_t_5_tree_Node = { "Node", __Pyx_StructFields_nn_struct____pyx_t_5_tree_Node, sizeof(struct __pyx_t_5_tree_Node), { 0 }, 0, 'S', 0, 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__ = { "const DOUBLE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t const ), { 0 }, 0, 'R', 0, 0 }; -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5_tree_DTYPE_t__const__ = { "const DTYPE_t", NULL, sizeof(__pyx_t_5_tree_DTYPE_t const ), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node = { "Node", __Pyx_StructFields_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node, sizeof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node), { 0 }, 0, 'S', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t__const__ = { "const DOUBLE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t const ), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t__const__ = { "const DTYPE_t", NULL, sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t const ), { 0 }, 0, 'R', 0, 0 }; static __Pyx_TypeInfo __Pyx_TypeInfo_unsigned_char = { "unsigned char", NULL, sizeof(unsigned char), { 0 }, 0, IS_UNSIGNED(unsigned char) ? 'U' : 'I', IS_UNSIGNED(unsigned char), 0 }; -#define __Pyx_MODULE_NAME "_tree" -extern int __pyx_module_is_main__tree; -int __pyx_module_is_main__tree = 0; +#define __Pyx_MODULE_NAME "stpredictions.models.OK3._tree" +extern int __pyx_module_is_main_stpredictions__models__OK3___tree; +int __pyx_module_is_main_stpredictions__models__OK3___tree = 0; -/* Implementation of '_tree' */ +/* Implementation of 'stpredictions.models.OK3._tree' */ static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_MemoryError; static PyObject *__pyx_builtin_TypeError; @@ -3954,7 +3576,6 @@ static const char __pyx_k_name_2[] = "__name__"; static const char __pyx_k_pickle[] = "pickle"; static const char __pyx_k_reduce[] = "__reduce__"; static const char __pyx_k_struct[] = "struct"; -static const char __pyx_k_tree_2[] = "_tree"; static const char __pyx_k_unique[] = "unique"; static const char __pyx_k_unpack[] = "unpack"; static const char __pyx_k_update[] = "update"; @@ -4081,6 +3702,7 @@ static const char __pyx_k_compute_feature_importances[] = "compute_feature_impor static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; static const char __pyx_k_pyx_unpickle__CCPPruneControll[] = "__pyx_unpickle__CCPPruneController"; +static const char __pyx_k_stpredictions_models_OK3__tree[] = "stpredictions.models.OK3._tree"; static const char __pyx_k_strided_and_direct_or_indirect[] = ""; static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; @@ -4327,6 +3949,7 @@ static PyObject *__pyx_n_s_sq_norms_cand; static PyObject *__pyx_n_s_start; static PyObject *__pyx_n_s_step; static PyObject *__pyx_n_s_stop; +static PyObject *__pyx_n_s_stpredictions_models_OK3__tree; static PyObject *__pyx_kp_s_stpredictions_models_OK3__tree_p; static PyObject *__pyx_kp_s_strided_and_direct; static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; @@ -4340,7 +3963,6 @@ static PyObject *__pyx_n_s_tocsc; static PyObject *__pyx_n_s_tocsr; static PyObject *__pyx_n_s_total_items; static PyObject *__pyx_n_s_tree; -static PyObject *__pyx_n_s_tree_2; static PyObject *__pyx_n_s_uint8; static PyObject *__pyx_kp_s_unable_to_allocate_array_data; static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; @@ -4353,62 +3975,62 @@ static PyObject *__pyx_n_s_weighted_n_node_samples; static PyObject *__pyx_n_s_where; static PyObject *__pyx_n_s_y; static PyObject *__pyx_n_s_zeros; -static PyObject *__pyx_pf_5_tree_11TreeBuilder_build(struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ -static PyObject *__pyx_pf_5_tree_11TreeBuilder_2__reduce_cython__(struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_11TreeBuilder_4__setstate_cython__(struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, __pyx_t_5_tree_SIZE_t __pyx_v_max_depth, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split); /* proto */ -static PyObject *__pyx_pf_5_tree_21DepthFirstTreeBuilder_2build(struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ -static PyObject *__pyx_pf_5_tree_21DepthFirstTreeBuilder_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_21DepthFirstTreeBuilder_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_leaf, PyObject *__pyx_v_min_weight_leaf, __pyx_t_5_tree_SIZE_t __pyx_v_max_depth, __pyx_t_5_tree_SIZE_t __pyx_v_max_leaf_nodes, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split); /* proto */ -static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ -static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_13children_left___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_14children_right___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_8n_leaves___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_7feature___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_9threshold___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_8impurity___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_14n_node_samples___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_23weighted_n_node_samples___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_5value___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_5_tree_4Tree___cinit__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, int __pyx_v_n_features, int __pyx_v_n_samples); /* proto */ -static void __pyx_pf_5_tree_4Tree_2__dealloc__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_4__reduce__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_6__getstate__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_d); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_10predict(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_12decode_tree(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_K_cand_train, PyArrayObject *__pyx_v_sq_norms_cand, PyObject *__pyx_v_criterion, PyObject *__pyx_v_kernel, __pyx_t_5_tree_SIZE_t __pyx_v_return_top_k); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_14apply(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_16decision_path(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_18compute_feature_importances(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_normalize); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_10n_features___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_5_tree_4Tree_10n_features_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_9max_depth___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_5_tree_4Tree_9max_depth_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_10node_count___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_5_tree_4Tree_10node_count_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_8capacity___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_5_tree_4Tree_8capacity_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_3K_y___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_5_tree_4Tree_3K_y_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static int __pyx_pf_5_tree_4Tree_3K_y_4__del__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_4Tree_1y___get__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static int __pyx_pf_5_tree_4Tree_1y_2__set__(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ -static int __pyx_pf_5_tree_4Tree_1y_4__del__(struct __pyx_obj_5_tree_Tree *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_19_CCPPruneController___reduce_cython__(struct __pyx_obj_5_tree__CCPPruneController *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_19_CCPPruneController_2__setstate_cython__(struct __pyx_obj_5_tree__CCPPruneController *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_pf_5_tree_12_AlphaPruner___cinit__(struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_self, __pyx_t_5_tree_DOUBLE_t __pyx_v_ccp_alpha); /* proto */ -static PyObject *__pyx_pf_5_tree_12_AlphaPruner_2__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_12_AlphaPruner_4__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static int __pyx_pf_5_tree_11_PathFinder___cinit__(struct __pyx_obj_5_tree__PathFinder *__pyx_v_self, int __pyx_v_node_count); /* proto */ -static PyObject *__pyx_pf_5_tree_11_PathFinder_2__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree__PathFinder *__pyx_v_self); /* proto */ -static PyObject *__pyx_pf_5_tree_11_PathFinder_4__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree__PathFinder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_5_tree__build_pruned_tree_ccp(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, struct __pyx_obj_5_tree_Tree *__pyx_v_orig_tree, __pyx_t_5_tree_DOUBLE_t __pyx_v_ccp_alpha); /* proto */ -static PyObject *__pyx_pf_5_tree_2ccp_pruning_path(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_5_tree_Tree *__pyx_v_orig_tree); /* proto */ -static PyObject *__pyx_pf_5_tree_4__pyx_unpickle_TreeBuilder(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_pf_5_tree_6__pyx_unpickle__CCPPruneController(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_2__reduce_cython__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_4__setstate_cython__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_2build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf, PyObject *__pyx_v_min_weight_leaf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_leaf_nodes, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_13children_left___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_14children_right___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_8n_leaves___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_7feature___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_9threshold___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_8impurity___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_14n_node_samples___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_23weighted_n_node_samples___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_5value___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, int __pyx_v_n_features, int __pyx_v_n_samples); /* proto */ +static void __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_4__reduce__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_6__getstate__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_8__setstate__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_d); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10predict(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_12decode_tree(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_K_cand_train, PyArrayObject *__pyx_v_sq_norms_cand, PyObject *__pyx_v_criterion, PyObject *__pyx_v_kernel, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_return_top_k); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_14apply(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_16decision_path(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_18compute_feature_importances(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_normalize); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10n_features___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10n_features_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_9max_depth___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_9max_depth_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10node_count___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10node_count_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_8capacity___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_8capacity_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_3K_y___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_3K_y_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_3K_y_4__del__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_1y___get__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_1y_2__set__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_1y_4__del__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController___reduce_cython__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController_2__setstate_cython__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_ccp_alpha); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_2__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_4__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_11_PathFinder___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *__pyx_v_self, int __pyx_v_node_count); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11_PathFinder_2__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11_PathFinder_4__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree__build_pruned_tree_ccp(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_orig_tree, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_ccp_alpha); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_2ccp_pruning_path(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_orig_tree); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4__pyx_unpickle_TreeBuilder(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_6__pyx_unpickle__CCPPruneController(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ @@ -4451,13 +4073,13 @@ static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__ static PyObject *__pyx_pf___pyx_memoryviewslice___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView___pyx_unpickle_Enum(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */ -static PyObject *__pyx_tp_new_5_tree_Tree(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_5_tree_TreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_5_tree_DepthFirstTreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_5_tree_BestFirstTreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_5_tree__CCPPruneController(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_5_tree__AlphaPruner(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ -static PyObject *__pyx_tp_new_5_tree__PathFinder(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree_Tree(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree_TreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree__CCPPruneController(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree__AlphaPruner(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree__PathFinder(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ @@ -4470,7 +4092,7 @@ static PyObject *__pyx_int_184977713; static PyObject *__pyx_int_222419149; static PyObject *__pyx_int_neg_1; static PyObject *__pyx_int_neg_2; -static __pyx_t_5_tree_SIZE_t __pyx_k__8; +static __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_k__8; static PyObject *__pyx_tuple_; static PyObject *__pyx_slice__9; static PyObject *__pyx_tuple__2; @@ -4530,7 +4152,7 @@ static PyObject *__pyx_codeobj__56; static PyObject *__pyx_codeobj__63; /* Late includes */ -/* "_tree.pyx":78 +/* "stpredictions/models/OK3/_tree.pyx":78 * """Interface for different tree building strategies.""" * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -4538,10 +4160,10 @@ static PyObject *__pyx_codeobj__63; * """Build a decision tree from the training set (X, y).""" */ -static PyObject *__pyx_pw_5_tree_11TreeBuilder_1build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static PyObject *__pyx_f_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_5_tree_Tree *__pyx_v_tree, CYTHON_UNUSED PyObject *__pyx_v_X, CYTHON_UNUSED PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_11TreeBuilder_build *__pyx_optional_args) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_1build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, CYTHON_UNUSED PyObject *__pyx_v_X, CYTHON_UNUSED PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build *__pyx_optional_args) { - /* "_tree.pyx":79 + /* "stpredictions/models/OK3/_tree.pyx":79 * * cpdef build(self, Tree tree, object X, np.ndarray y, * np.ndarray sample_weight=None): # <<<<<<<<<<<<<< @@ -4567,7 +4189,7 @@ static PyObject *__pyx_f_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_o } } - /* "_tree.pyx":78 + /* "stpredictions/models/OK3/_tree.pyx":78 * """Interface for different tree building strategies.""" * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -4585,7 +4207,7 @@ static PyObject *__pyx_f_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_o #endif __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_self), __pyx_n_s_build); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 78, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_5_tree_11TreeBuilder_1build)) { + if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_1build)) { __Pyx_XDECREF(__pyx_r); __Pyx_INCREF(__pyx_t_1); __pyx_t_3 = __pyx_t_1; __pyx_t_4 = NULL; @@ -4657,7 +4279,7 @@ static PyObject *__pyx_f_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_o #endif } - /* "_tree.pyx":80 + /* "stpredictions/models/OK3/_tree.pyx":80 * cpdef build(self, Tree tree, object X, np.ndarray y, * np.ndarray sample_weight=None): * """Build a decision tree from the training set (X, y).""" # <<<<<<<<<<<<<< @@ -4674,7 +4296,7 @@ static PyObject *__pyx_f_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_o __Pyx_XDECREF(__pyx_t_3); __Pyx_XDECREF(__pyx_t_4); __Pyx_XDECREF(__pyx_t_6); - __Pyx_AddTraceback("_tree.TreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.TreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; __pyx_L0:; __Pyx_XGIVEREF(__pyx_r); @@ -4682,7 +4304,7 @@ static PyObject *__pyx_f_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_o return __pyx_r; } -/* "_tree.pyx":78 +/* "stpredictions/models/OK3/_tree.pyx":78 * """Interface for different tree building strategies.""" * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -4691,10 +4313,10 @@ static PyObject *__pyx_f_5_tree_11TreeBuilder_build(CYTHON_UNUSED struct __pyx_o */ /* Python wrapper */ -static PyObject *__pyx_pw_5_tree_11TreeBuilder_1build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static char __pyx_doc_5_tree_11TreeBuilder_build[] = "Build a decision tree from the training set (X, y)."; -static PyObject *__pyx_pw_5_tree_11TreeBuilder_1build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { - struct __pyx_obj_5_tree_Tree *__pyx_v_tree = 0; +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_1build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build[] = "Build a decision tree from the training set (X, y)."; +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_1build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree = 0; PyObject *__pyx_v_X = 0; PyArrayObject *__pyx_v_y = 0; PyArrayObject *__pyx_v_sample_weight = 0; @@ -4708,7 +4330,7 @@ static PyObject *__pyx_pw_5_tree_11TreeBuilder_1build(PyObject *__pyx_v_self, Py static PyObject **__pyx_pyargnames[] = {&__pyx_n_s_tree,&__pyx_n_s_X,&__pyx_n_s_y,&__pyx_n_s_sample_weight,0}; PyObject* values[4] = {0,0,0,0}; - /* "_tree.pyx":79 + /* "stpredictions/models/OK3/_tree.pyx":79 * * cpdef build(self, Tree tree, object X, np.ndarray y, * np.ndarray sample_weight=None): # <<<<<<<<<<<<<< @@ -4769,7 +4391,7 @@ static PyObject *__pyx_pw_5_tree_11TreeBuilder_1build(PyObject *__pyx_v_self, Py default: goto __pyx_L5_argtuple_error; } } - __pyx_v_tree = ((struct __pyx_obj_5_tree_Tree *)values[0]); + __pyx_v_tree = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)values[0]); __pyx_v_X = values[1]; __pyx_v_y = ((PyArrayObject *)values[2]); __pyx_v_sample_weight = ((PyArrayObject *)values[3]); @@ -4778,16 +4400,16 @@ static PyObject *__pyx_pw_5_tree_11TreeBuilder_1build(PyObject *__pyx_v_self, Py __pyx_L5_argtuple_error:; __Pyx_RaiseArgtupleInvalid("build", 0, 3, 4, PyTuple_GET_SIZE(__pyx_args)); __PYX_ERR(0, 78, __pyx_L3_error) __pyx_L3_error:; - __Pyx_AddTraceback("_tree.TreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.TreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_tree), __pyx_ptype_5_tree_Tree, 1, "tree", 0))) __PYX_ERR(0, 78, __pyx_L1_error) + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_tree), __pyx_ptype_13stpredictions_6models_3OK3_5_tree_Tree, 1, "tree", 0))) __PYX_ERR(0, 78, __pyx_L1_error) if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_y), __pyx_ptype_5numpy_ndarray, 1, "y", 0))) __PYX_ERR(0, 78, __pyx_L1_error) if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_sample_weight), __pyx_ptype_5numpy_ndarray, 1, "sample_weight", 0))) __PYX_ERR(0, 79, __pyx_L1_error) - __pyx_r = __pyx_pf_5_tree_11TreeBuilder_build(((struct __pyx_obj_5_tree_TreeBuilder *)__pyx_v_self), __pyx_v_tree, __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build(((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *)__pyx_v_self), __pyx_v_tree, __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight); - /* "_tree.pyx":78 + /* "stpredictions/models/OK3/_tree.pyx":78 * """Interface for different tree building strategies.""" * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -4804,11 +4426,11 @@ static PyObject *__pyx_pw_5_tree_11TreeBuilder_1build(PyObject *__pyx_v_self, Py return __pyx_r; } -static PyObject *__pyx_pf_5_tree_11TreeBuilder_build(struct __pyx_obj_5_tree_TreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; - struct __pyx_opt_args_5_tree_11TreeBuilder_build __pyx_t_2; + struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build __pyx_t_2; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -4816,7 +4438,7 @@ static PyObject *__pyx_pf_5_tree_11TreeBuilder_build(struct __pyx_obj_5_tree_Tre __Pyx_XDECREF(__pyx_r); __pyx_t_2.__pyx_n = 1; __pyx_t_2.sample_weight = __pyx_v_sample_weight; - __pyx_t_1 = __pyx_vtabptr_5_tree_TreeBuilder->build(__pyx_v_self, __pyx_v_tree, __pyx_v_X, __pyx_v_y, 1, &__pyx_t_2); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 78, __pyx_L1_error) + __pyx_t_1 = __pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_TreeBuilder->build(__pyx_v_self, __pyx_v_tree, __pyx_v_X, __pyx_v_y, 1, &__pyx_t_2); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 78, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; @@ -4825,7 +4447,7 @@ static PyObject *__pyx_pf_5_tree_11TreeBuilder_build(struct __pyx_obj_5_tree_Tre /* function exit code */ __pyx_L1_error:; 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/* function exit code */ goto __pyx_L0; @@ -5831,12 +5453,12 @@ static int __pyx_pw_5_tree_21DepthFirstTreeBuilder_1__cinit__(PyObject *__pyx_v_ return __pyx_r; } -static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, __pyx_t_5_tree_SIZE_t __pyx_v_max_depth, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split) { +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf, double __pyx_v_min_weight_leaf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split) { int __pyx_r; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__cinit__", 0); - /* "_tree.pyx":121 + /* "stpredictions/models/OK3/_tree.pyx":121 * SIZE_t max_depth, double min_impurity_decrease, * double min_impurity_split): * self.splitter = splitter # <<<<<<<<<<<<<< @@ -5849,7 +5471,7 @@ static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_ __Pyx_DECREF(((PyObject *)__pyx_v_self->__pyx_base.splitter)); __pyx_v_self->__pyx_base.splitter = __pyx_v_splitter; - /* "_tree.pyx":122 + /* "stpredictions/models/OK3/_tree.pyx":122 * double min_impurity_split): * self.splitter = splitter * self.min_samples_split = min_samples_split # <<<<<<<<<<<<<< @@ -5858,7 +5480,7 @@ static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_ */ __pyx_v_self->__pyx_base.min_samples_split = __pyx_v_min_samples_split; - /* "_tree.pyx":123 + /* "stpredictions/models/OK3/_tree.pyx":123 * self.splitter = splitter * self.min_samples_split = min_samples_split * self.min_samples_leaf = min_samples_leaf # <<<<<<<<<<<<<< @@ -5867,7 +5489,7 @@ static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_ */ __pyx_v_self->__pyx_base.min_samples_leaf = __pyx_v_min_samples_leaf; - /* "_tree.pyx":124 + /* "stpredictions/models/OK3/_tree.pyx":124 * self.min_samples_split = min_samples_split * self.min_samples_leaf = min_samples_leaf * self.min_weight_leaf = min_weight_leaf # <<<<<<<<<<<<<< @@ -5876,7 +5498,7 @@ static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_ */ __pyx_v_self->__pyx_base.min_weight_leaf = __pyx_v_min_weight_leaf; - /* "_tree.pyx":125 + /* "stpredictions/models/OK3/_tree.pyx":125 * self.min_samples_leaf = min_samples_leaf * self.min_weight_leaf = min_weight_leaf * self.max_depth = max_depth # <<<<<<<<<<<<<< @@ -5885,7 +5507,7 @@ static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_ */ __pyx_v_self->__pyx_base.max_depth = __pyx_v_max_depth; - /* "_tree.pyx":126 + /* "stpredictions/models/OK3/_tree.pyx":126 * self.min_weight_leaf = min_weight_leaf * self.max_depth = max_depth * self.min_impurity_decrease = min_impurity_decrease # <<<<<<<<<<<<<< @@ -5894,7 +5516,7 @@ static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_ */ __pyx_v_self->__pyx_base.min_impurity_decrease = __pyx_v_min_impurity_decrease; - /* "_tree.pyx":127 + /* "stpredictions/models/OK3/_tree.pyx":127 * self.max_depth = max_depth * self.min_impurity_decrease = min_impurity_decrease * self.min_impurity_split = min_impurity_split # <<<<<<<<<<<<<< @@ -5903,7 +5525,7 @@ static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_ */ __pyx_v_self->__pyx_base.min_impurity_split = __pyx_v_min_impurity_split; - /* "_tree.pyx":117 + /* "stpredictions/models/OK3/_tree.pyx":117 * """Build a decision tree in depth-first fashion.""" * * def __cinit__(self, Splitter splitter, SIZE_t min_samples_split, # <<<<<<<<<<<<<< @@ -5917,7 +5539,7 @@ static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_ return __pyx_r; } -/* "_tree.pyx":129 +/* "stpredictions/models/OK3/_tree.pyx":129 * self.min_impurity_split = min_impurity_split * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -5925,10 +5547,10 @@ static int __pyx_pf_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_5_ * """Build a decision tree from the training set (X, y).""" */ -static PyObject *__pyx_pw_5_tree_21DepthFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_21DepthFirstTreeBuilder_build *__pyx_optional_args) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_build *__pyx_optional_args) { - /* "_tree.pyx":130 + /* "stpredictions/models/OK3/_tree.pyx":130 * * cpdef build(self, Tree tree, object X, np.ndarray y, * np.ndarray sample_weight=None): # <<<<<<<<<<<<<< @@ -5936,33 +5558,33 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 * */ PyArrayObject *__pyx_v_sample_weight = ((PyArrayObject *)Py_None); - __pyx_t_5_tree_DOUBLE_t *__pyx_v_sample_weight_ptr; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_sample_weight_ptr; int __pyx_v_init_capacity; - struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter = 0; - __pyx_t_5_tree_SIZE_t __pyx_v_max_depth; - __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_leaf; + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter = 0; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf; double __pyx_v_min_weight_leaf; - __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_split; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_split; double __pyx_v_min_impurity_decrease; double __pyx_v_min_impurity_split; - __pyx_t_5_tree_SIZE_t __pyx_v_start; - __pyx_t_5_tree_SIZE_t __pyx_v_end; - __pyx_t_5_tree_SIZE_t __pyx_v_depth; - __pyx_t_5_tree_SIZE_t __pyx_v_parent; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_parent; int __pyx_v_is_left; - __pyx_t_5_tree_SIZE_t __pyx_v_n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_node_samples; CYTHON_UNUSED double __pyx_v_weighted_n_samples; double __pyx_v_weighted_n_node_samples; - struct __pyx_t_9_splitter_SplitRecord __pyx_v_split; - __pyx_t_5_tree_SIZE_t __pyx_v_node_id; + struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_split; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_node_id; double __pyx_v_impurity; - __pyx_t_5_tree_SIZE_t __pyx_v_n_constant_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_constant_features; int __pyx_v_is_leaf; int __pyx_v_first; - __pyx_t_5_tree_SIZE_t __pyx_v_max_depth_seen; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth_seen; int __pyx_v_rc; - struct __pyx_obj_7sklearn_4tree_6_utils_Stack *__pyx_v_stack = 0; - struct __pyx_t_7sklearn_4tree_6_utils_StackRecord __pyx_v_stack_record; + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_v_stack = 0; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord __pyx_v_stack_record; PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -5974,12 +5596,11 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 PyObject *(*__pyx_t_7)(PyObject *); int __pyx_t_8; int __pyx_t_9; - __pyx_t_5_tree_SIZE_t __pyx_t_10; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_10; double __pyx_t_11; __Pyx_memviewslice __pyx_t_12 = { 0, 0, { 0 }, { 0 }, { 0 } }; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_13; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t __pyx_t_14; - struct __pyx_opt_args_5_tree_4Tree__resize_c __pyx_t_15; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_t_13; + struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c __pyx_t_14; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -5993,7 +5614,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __Pyx_INCREF((PyObject *)__pyx_v_y); __Pyx_INCREF((PyObject *)__pyx_v_sample_weight); - /* "_tree.pyx":129 + /* "stpredictions/models/OK3/_tree.pyx":129 * self.min_impurity_split = min_impurity_split * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -6011,7 +5632,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 #endif __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_self), __pyx_n_s_build); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 129, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_5_tree_21DepthFirstTreeBuilder_3build)) { + if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_3build)) { __Pyx_XDECREF(__pyx_r); __Pyx_INCREF(__pyx_t_1); __pyx_t_3 = __pyx_t_1; __pyx_t_4 = NULL; @@ -6083,14 +5704,14 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 #endif } - /* "_tree.pyx":134 + /* "stpredictions/models/OK3/_tree.pyx":134 * * # check input * X, y, sample_weight = self._check_input(X, y, sample_weight) # <<<<<<<<<<<<<< * * cdef DOUBLE_t* sample_weight_ptr = NULL */ - __pyx_t_1 = __pyx_f_5_tree_11TreeBuilder__check_input(((struct __pyx_obj_5_tree_TreeBuilder *)__pyx_v_self), __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 134, __pyx_L1_error) + __pyx_t_1 = __pyx_f_13stpredictions_6models_3OK3_5_tree_11TreeBuilder__check_input(((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *)__pyx_v_self), __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 134, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); if ((likely(PyTuple_CheckExact(__pyx_t_1))) || (PyList_CheckExact(__pyx_t_1))) { PyObject* sequence = __pyx_t_1; @@ -6154,7 +5775,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __Pyx_DECREF_SET(__pyx_v_sample_weight, ((PyArrayObject *)__pyx_t_6)); __pyx_t_6 = 0; - /* "_tree.pyx":136 + /* "stpredictions/models/OK3/_tree.pyx":136 * X, y, sample_weight = self._check_input(X, y, sample_weight) * * cdef DOUBLE_t* sample_weight_ptr = NULL # <<<<<<<<<<<<<< @@ -6163,7 +5784,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_v_sample_weight_ptr = NULL; - /* "_tree.pyx":137 + /* "stpredictions/models/OK3/_tree.pyx":137 * * cdef DOUBLE_t* sample_weight_ptr = NULL * if sample_weight is not None: # <<<<<<<<<<<<<< @@ -6174,16 +5795,16 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = (__pyx_t_8 != 0); if (__pyx_t_9) { - /* "_tree.pyx":138 + /* "stpredictions/models/OK3/_tree.pyx":138 * cdef DOUBLE_t* sample_weight_ptr = NULL * if sample_weight is not None: * sample_weight_ptr = sample_weight.data # <<<<<<<<<<<<<< * * # Initial capacity */ - __pyx_v_sample_weight_ptr = ((__pyx_t_5_tree_DOUBLE_t *)__pyx_v_sample_weight->data); + __pyx_v_sample_weight_ptr = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *)__pyx_v_sample_weight->data); - /* "_tree.pyx":137 + /* "stpredictions/models/OK3/_tree.pyx":137 * * cdef DOUBLE_t* sample_weight_ptr = NULL * if sample_weight is not None: # <<<<<<<<<<<<<< @@ -6192,7 +5813,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ } - /* "_tree.pyx":143 + /* "stpredictions/models/OK3/_tree.pyx":143 * cdef int init_capacity * * if tree.max_depth <= 10: # <<<<<<<<<<<<<< @@ -6202,7 +5823,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((__pyx_v_tree->max_depth <= 10) != 0); if (__pyx_t_9) { - /* "_tree.pyx":144 + /* "stpredictions/models/OK3/_tree.pyx":144 * * if tree.max_depth <= 10: * init_capacity = (2 ** (tree.max_depth + 1)) - 1 # <<<<<<<<<<<<<< @@ -6211,7 +5832,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_v_init_capacity = (__Pyx_pow_long(2, (__pyx_v_tree->max_depth + 1)) - 1); - /* "_tree.pyx":143 + /* "stpredictions/models/OK3/_tree.pyx":143 * cdef int init_capacity * * if tree.max_depth <= 10: # <<<<<<<<<<<<<< @@ -6221,7 +5842,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 goto __pyx_L6; } - /* "_tree.pyx":146 + /* "stpredictions/models/OK3/_tree.pyx":146 * init_capacity = (2 ** (tree.max_depth + 1)) - 1 * else: * init_capacity = 2047 # <<<<<<<<<<<<<< @@ -6233,16 +5854,16 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 } __pyx_L6:; - /* "_tree.pyx":148 + /* "stpredictions/models/OK3/_tree.pyx":148 * init_capacity = 2047 * * tree._resize(init_capacity) # <<<<<<<<<<<<<< * * # Parameters */ - __pyx_t_5 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize(__pyx_v_tree, __pyx_v_init_capacity); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 148, __pyx_L1_error) + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize(__pyx_v_tree, __pyx_v_init_capacity); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 148, __pyx_L1_error) - /* "_tree.pyx":151 + /* "stpredictions/models/OK3/_tree.pyx":151 * * # Parameters * cdef Splitter splitter = self.splitter # <<<<<<<<<<<<<< @@ -6251,10 +5872,10 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_t_1 = ((PyObject *)__pyx_v_self->__pyx_base.splitter); __Pyx_INCREF(__pyx_t_1); - __pyx_v_splitter = ((struct __pyx_obj_9_splitter_Splitter *)__pyx_t_1); + __pyx_v_splitter = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":152 + /* "stpredictions/models/OK3/_tree.pyx":152 * # Parameters * cdef Splitter splitter = self.splitter * cdef SIZE_t max_depth = self.max_depth # <<<<<<<<<<<<<< @@ -6264,7 +5885,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_10 = __pyx_v_self->__pyx_base.max_depth; __pyx_v_max_depth = __pyx_t_10; - /* "_tree.pyx":153 + /* "stpredictions/models/OK3/_tree.pyx":153 * cdef Splitter splitter = self.splitter * cdef SIZE_t max_depth = self.max_depth * cdef SIZE_t min_samples_leaf = self.min_samples_leaf # <<<<<<<<<<<<<< @@ -6274,7 +5895,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_10 = __pyx_v_self->__pyx_base.min_samples_leaf; __pyx_v_min_samples_leaf = __pyx_t_10; - /* "_tree.pyx":154 + /* "stpredictions/models/OK3/_tree.pyx":154 * cdef SIZE_t max_depth = self.max_depth * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< @@ -6284,7 +5905,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_11 = __pyx_v_self->__pyx_base.min_weight_leaf; __pyx_v_min_weight_leaf = __pyx_t_11; - /* "_tree.pyx":155 + /* "stpredictions/models/OK3/_tree.pyx":155 * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf * cdef SIZE_t min_samples_split = self.min_samples_split # <<<<<<<<<<<<<< @@ -6294,7 +5915,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_10 = __pyx_v_self->__pyx_base.min_samples_split; __pyx_v_min_samples_split = __pyx_t_10; - /* "_tree.pyx":156 + /* "stpredictions/models/OK3/_tree.pyx":156 * cdef double min_weight_leaf = self.min_weight_leaf * cdef SIZE_t min_samples_split = self.min_samples_split * cdef double min_impurity_decrease = self.min_impurity_decrease # <<<<<<<<<<<<<< @@ -6304,7 +5925,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_11 = __pyx_v_self->__pyx_base.min_impurity_decrease; __pyx_v_min_impurity_decrease = __pyx_t_11; - /* "_tree.pyx":157 + /* "stpredictions/models/OK3/_tree.pyx":157 * cdef SIZE_t min_samples_split = self.min_samples_split * cdef double min_impurity_decrease = self.min_impurity_decrease * cdef double min_impurity_split = self.min_impurity_split # <<<<<<<<<<<<<< @@ -6314,30 +5935,30 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_11 = __pyx_v_self->__pyx_base.min_impurity_split; __pyx_v_min_impurity_split = __pyx_t_11; - /* "_tree.pyx":160 + /* "stpredictions/models/OK3/_tree.pyx":160 * * # Recursive partition (without actual recursion) * splitter.init(X, y, sample_weight_ptr) # <<<<<<<<<<<<<< * * cdef SIZE_t start */ - __pyx_t_12 = __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__(((PyObject *)__pyx_v_y), 0); if (unlikely(!__pyx_t_12.memview)) __PYX_ERR(0, 160, __pyx_L1_error) - __pyx_t_5 = ((struct __pyx_vtabstruct_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->init(__pyx_v_splitter, __pyx_v_X, __pyx_t_12, __pyx_v_sample_weight_ptr); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 160, __pyx_L1_error) + __pyx_t_12 = __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t__const__(((PyObject *)__pyx_v_y), 0); if (unlikely(!__pyx_t_12.memview)) __PYX_ERR(0, 160, __pyx_L1_error) + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->init(__pyx_v_splitter, __pyx_v_X, __pyx_t_12, __pyx_v_sample_weight_ptr); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 160, __pyx_L1_error) __PYX_XDEC_MEMVIEW(&__pyx_t_12, 1); __pyx_t_12.memview = NULL; __pyx_t_12.data = NULL; - /* "_tree.pyx":167 + /* "stpredictions/models/OK3/_tree.pyx":167 * cdef SIZE_t parent * cdef bint is_left * cdef SIZE_t n_node_samples = splitter.n_samples # <<<<<<<<<<<<<< * cdef double weighted_n_samples = splitter.weighted_n_samples * cdef double weighted_n_node_samples */ - __pyx_t_13 = __pyx_v_splitter->n_samples; - __pyx_v_n_node_samples = __pyx_t_13; + __pyx_t_10 = __pyx_v_splitter->n_samples; + __pyx_v_n_node_samples = __pyx_t_10; - /* "_tree.pyx":168 + /* "stpredictions/models/OK3/_tree.pyx":168 * cdef bint is_left * cdef SIZE_t n_node_samples = splitter.n_samples * cdef double weighted_n_samples = splitter.weighted_n_samples # <<<<<<<<<<<<<< @@ -6347,16 +5968,16 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_11 = __pyx_v_splitter->weighted_n_samples; __pyx_v_weighted_n_samples = __pyx_t_11; - /* "_tree.pyx":173 + /* "stpredictions/models/OK3/_tree.pyx":173 * cdef SIZE_t node_id * * cdef double impurity = INFINITY # <<<<<<<<<<<<<< * cdef SIZE_t n_constant_features * cdef bint is_leaf */ - __pyx_v_impurity = __pyx_v_5_tree_INFINITY; + __pyx_v_impurity = __pyx_v_13stpredictions_6models_3OK3_5_tree_INFINITY; - /* "_tree.pyx":176 + /* "stpredictions/models/OK3/_tree.pyx":176 * cdef SIZE_t n_constant_features * cdef bint is_leaf * cdef bint first = 1 # <<<<<<<<<<<<<< @@ -6365,7 +5986,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_v_first = 1; - /* "_tree.pyx":177 + /* "stpredictions/models/OK3/_tree.pyx":177 * cdef bint is_leaf * cdef bint first = 1 * cdef SIZE_t max_depth_seen = -1 # <<<<<<<<<<<<<< @@ -6374,7 +5995,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_v_max_depth_seen = -1; - /* "_tree.pyx":178 + /* "stpredictions/models/OK3/_tree.pyx":178 * cdef bint first = 1 * cdef SIZE_t max_depth_seen = -1 * cdef int rc = 0 # <<<<<<<<<<<<<< @@ -6383,22 +6004,22 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_v_rc = 0; - /* "_tree.pyx":180 + /* "stpredictions/models/OK3/_tree.pyx":180 * cdef int rc = 0 * * cdef Stack stack = Stack(INITIAL_STACK_SIZE) # <<<<<<<<<<<<<< * cdef StackRecord stack_record * */ - __pyx_t_1 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_5_tree_INITIAL_STACK_SIZE); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 180, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_13stpredictions_6models_3OK3_5_tree_INITIAL_STACK_SIZE); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 180, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - __pyx_t_6 = __Pyx_PyObject_CallOneArg(((PyObject *)__pyx_ptype_7sklearn_4tree_6_utils_Stack), __pyx_t_1); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 180, __pyx_L1_error) + __pyx_t_6 = __Pyx_PyObject_CallOneArg(((PyObject *)__pyx_ptype_13stpredictions_6models_3OK3_6_utils_Stack), __pyx_t_1); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 180, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_v_stack = ((struct __pyx_obj_7sklearn_4tree_6_utils_Stack *)__pyx_t_6); + __pyx_v_stack = ((struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_t_6); __pyx_t_6 = 0; - /* "_tree.pyx":183 + /* "stpredictions/models/OK3/_tree.pyx":183 * cdef StackRecord stack_record * * with nogil: # <<<<<<<<<<<<<< @@ -6413,17 +6034,17 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 #endif /*try:*/ { - /* "_tree.pyx":185 + /* "stpredictions/models/OK3/_tree.pyx":185 * with nogil: * # push root node onto stack * rc = stack.push(0, n_node_samples, 0, _TREE_UNDEFINED, 0, INFINITY, 0) # <<<<<<<<<<<<<< * if rc == -1: * # got return code -1 - out-of-memory */ - __pyx_t_5 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, 0, __pyx_v_n_node_samples, 0, __pyx_v_5_tree__TREE_UNDEFINED, 0, __pyx_v_5_tree_INFINITY, 0); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 185, __pyx_L8_error) + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, 0, __pyx_v_n_node_samples, 0, __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED, 0, __pyx_v_13stpredictions_6models_3OK3_5_tree_INFINITY, 0); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 185, __pyx_L8_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":186 + /* "stpredictions/models/OK3/_tree.pyx":186 * # push root node onto stack * rc = stack.push(0, n_node_samples, 0, _TREE_UNDEFINED, 0, INFINITY, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -6433,7 +6054,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_9) { - /* "_tree.pyx":188 + /* "stpredictions/models/OK3/_tree.pyx":188 * if rc == -1: * # got return code -1 - out-of-memory * with gil: # <<<<<<<<<<<<<< @@ -6446,7 +6067,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 #endif /*try:*/ { - /* "_tree.pyx":189 + /* "stpredictions/models/OK3/_tree.pyx":189 * # got return code -1 - out-of-memory * with gil: * raise MemoryError() # <<<<<<<<<<<<<< @@ -6456,7 +6077,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 PyErr_NoMemory(); __PYX_ERR(0, 189, __pyx_L12_error) } - /* "_tree.pyx":188 + /* "stpredictions/models/OK3/_tree.pyx":188 * if rc == -1: * # got return code -1 - out-of-memory * with gil: # <<<<<<<<<<<<<< @@ -6473,7 +6094,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 } } - /* "_tree.pyx":186 + /* "stpredictions/models/OK3/_tree.pyx":186 * # push root node onto stack * rc = stack.push(0, n_node_samples, 0, _TREE_UNDEFINED, 0, INFINITY, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -6482,7 +6103,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ } - /* "_tree.pyx":191 + /* "stpredictions/models/OK3/_tree.pyx":191 * raise MemoryError() * * while not stack.is_empty(): # <<<<<<<<<<<<<< @@ -6490,59 +6111,59 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 * */ while (1) { - __pyx_t_9 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0); + __pyx_t_9 = ((!(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0); if (!__pyx_t_9) break; - /* "_tree.pyx":192 + /* "stpredictions/models/OK3/_tree.pyx":192 * * while not stack.is_empty(): * stack.pop(&stack_record) # <<<<<<<<<<<<<< * * start = stack_record.start */ - (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record))); + (void)(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record))); - /* "_tree.pyx":194 + /* "stpredictions/models/OK3/_tree.pyx":194 * stack.pop(&stack_record) * * start = stack_record.start # <<<<<<<<<<<<<< * end = stack_record.end * depth = stack_record.depth */ - __pyx_t_14 = __pyx_v_stack_record.start; - __pyx_v_start = __pyx_t_14; + __pyx_t_13 = __pyx_v_stack_record.start; + __pyx_v_start = __pyx_t_13; - /* "_tree.pyx":195 + /* "stpredictions/models/OK3/_tree.pyx":195 * * start = stack_record.start * end = stack_record.end # <<<<<<<<<<<<<< * depth = stack_record.depth * parent = stack_record.parent */ - __pyx_t_14 = __pyx_v_stack_record.end; - __pyx_v_end = __pyx_t_14; + __pyx_t_13 = __pyx_v_stack_record.end; + __pyx_v_end = __pyx_t_13; - /* "_tree.pyx":196 + /* "stpredictions/models/OK3/_tree.pyx":196 * start = stack_record.start * end = stack_record.end * depth = stack_record.depth # <<<<<<<<<<<<<< * parent = stack_record.parent * is_left = stack_record.is_left */ - __pyx_t_14 = __pyx_v_stack_record.depth; - __pyx_v_depth = __pyx_t_14; + __pyx_t_13 = __pyx_v_stack_record.depth; + __pyx_v_depth = __pyx_t_13; - /* "_tree.pyx":197 + /* "stpredictions/models/OK3/_tree.pyx":197 * end = stack_record.end * depth = stack_record.depth * parent = stack_record.parent # <<<<<<<<<<<<<< * is_left = stack_record.is_left * impurity = stack_record.impurity */ - __pyx_t_14 = __pyx_v_stack_record.parent; - __pyx_v_parent = __pyx_t_14; + __pyx_t_13 = __pyx_v_stack_record.parent; + __pyx_v_parent = __pyx_t_13; - /* "_tree.pyx":198 + /* "stpredictions/models/OK3/_tree.pyx":198 * depth = stack_record.depth * parent = stack_record.parent * is_left = stack_record.is_left # <<<<<<<<<<<<<< @@ -6552,7 +6173,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = __pyx_v_stack_record.is_left; __pyx_v_is_left = __pyx_t_9; - /* "_tree.pyx":199 + /* "stpredictions/models/OK3/_tree.pyx":199 * parent = stack_record.parent * is_left = stack_record.is_left * impurity = stack_record.impurity # <<<<<<<<<<<<<< @@ -6562,17 +6183,17 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_11 = __pyx_v_stack_record.impurity; __pyx_v_impurity = __pyx_t_11; - /* "_tree.pyx":200 + /* "stpredictions/models/OK3/_tree.pyx":200 * is_left = stack_record.is_left * impurity = stack_record.impurity * n_constant_features = stack_record.n_constant_features # <<<<<<<<<<<<<< * * n_node_samples = end - start */ - __pyx_t_14 = __pyx_v_stack_record.n_constant_features; - __pyx_v_n_constant_features = __pyx_t_14; + __pyx_t_13 = __pyx_v_stack_record.n_constant_features; + __pyx_v_n_constant_features = __pyx_t_13; - /* "_tree.pyx":202 + /* "stpredictions/models/OK3/_tree.pyx":202 * n_constant_features = stack_record.n_constant_features * * n_node_samples = end - start # <<<<<<<<<<<<<< @@ -6581,16 +6202,16 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_v_n_node_samples = (__pyx_v_end - __pyx_v_start); - /* "_tree.pyx":203 + /* "stpredictions/models/OK3/_tree.pyx":203 * * n_node_samples = end - start * splitter.node_reset(start, end, &weighted_n_node_samples) # <<<<<<<<<<<<<< * * is_leaf = (depth >= max_depth or */ - __pyx_t_5 = ((struct __pyx_vtabstruct_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_reset(__pyx_v_splitter, __pyx_v_start, __pyx_v_end, (&__pyx_v_weighted_n_node_samples)); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 203, __pyx_L8_error) + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_reset(__pyx_v_splitter, __pyx_v_start, __pyx_v_end, (&__pyx_v_weighted_n_node_samples)); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 203, __pyx_L8_error) - /* "_tree.pyx":205 + /* "stpredictions/models/OK3/_tree.pyx":205 * splitter.node_reset(start, end, &weighted_n_node_samples) * * is_leaf = (depth >= max_depth or # <<<<<<<<<<<<<< @@ -6604,7 +6225,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 goto __pyx_L16_bool_binop_done; } - /* "_tree.pyx":206 + /* "stpredictions/models/OK3/_tree.pyx":206 * * is_leaf = (depth >= max_depth or * n_node_samples < min_samples_split or # <<<<<<<<<<<<<< @@ -6618,7 +6239,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 goto __pyx_L16_bool_binop_done; } - /* "_tree.pyx":207 + /* "stpredictions/models/OK3/_tree.pyx":207 * is_leaf = (depth >= max_depth or * n_node_samples < min_samples_split or * n_node_samples < 2 * min_samples_leaf or # <<<<<<<<<<<<<< @@ -6632,7 +6253,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 goto __pyx_L16_bool_binop_done; } - /* "_tree.pyx":208 + /* "stpredictions/models/OK3/_tree.pyx":208 * n_node_samples < min_samples_split or * n_node_samples < 2 * min_samples_leaf or * weighted_n_node_samples < 2 * min_weight_leaf) # <<<<<<<<<<<<<< @@ -6644,7 +6265,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_L16_bool_binop_done:; __pyx_v_is_leaf = __pyx_t_9; - /* "_tree.pyx":210 + /* "stpredictions/models/OK3/_tree.pyx":210 * weighted_n_node_samples < 2 * min_weight_leaf) * * if first: # <<<<<<<<<<<<<< @@ -6654,16 +6275,16 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = (__pyx_v_first != 0); if (__pyx_t_9) { - /* "_tree.pyx":211 + /* "stpredictions/models/OK3/_tree.pyx":211 * * if first: * impurity = splitter.node_impurity() # <<<<<<<<<<<<<< * first = 0 * */ - __pyx_v_impurity = ((struct __pyx_vtabstruct_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_impurity(__pyx_v_splitter); + __pyx_v_impurity = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_impurity(__pyx_v_splitter); - /* "_tree.pyx":212 + /* "stpredictions/models/OK3/_tree.pyx":212 * if first: * impurity = splitter.node_impurity() * first = 0 # <<<<<<<<<<<<<< @@ -6672,7 +6293,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_v_first = 0; - /* "_tree.pyx":210 + /* "stpredictions/models/OK3/_tree.pyx":210 * weighted_n_node_samples < 2 * min_weight_leaf) * * if first: # <<<<<<<<<<<<<< @@ -6681,7 +6302,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ } - /* "_tree.pyx":214 + /* "stpredictions/models/OK3/_tree.pyx":214 * first = 0 * * is_leaf = (is_leaf or # <<<<<<<<<<<<<< @@ -6695,7 +6316,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 goto __pyx_L21_bool_binop_done; } - /* "_tree.pyx":215 + /* "stpredictions/models/OK3/_tree.pyx":215 * * is_leaf = (is_leaf or * (impurity <= min_impurity_split)) # <<<<<<<<<<<<<< @@ -6707,7 +6328,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_L21_bool_binop_done:; __pyx_v_is_leaf = __pyx_t_9; - /* "_tree.pyx":217 + /* "stpredictions/models/OK3/_tree.pyx":217 * (impurity <= min_impurity_split)) * * if not is_leaf: # <<<<<<<<<<<<<< @@ -6717,16 +6338,16 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((!(__pyx_v_is_leaf != 0)) != 0); if (__pyx_t_9) { - /* "_tree.pyx":218 + /* "stpredictions/models/OK3/_tree.pyx":218 * * if not is_leaf: * splitter.node_split(impurity, &split, &n_constant_features) # <<<<<<<<<<<<<< * # If EPSILON=0 in the below comparison, float precision * # issues stop splitting, producing trees that are */ - __pyx_t_5 = ((struct __pyx_vtabstruct_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_split(__pyx_v_splitter, __pyx_v_impurity, (&__pyx_v_split), (&__pyx_v_n_constant_features)); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 218, __pyx_L8_error) + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_split(__pyx_v_splitter, __pyx_v_impurity, (&__pyx_v_split), (&__pyx_v_n_constant_features)); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 218, __pyx_L8_error) - /* "_tree.pyx":222 + /* "stpredictions/models/OK3/_tree.pyx":222 * # issues stop splitting, producing trees that are * # dissimilar to v0.18 * is_leaf = (is_leaf or split.pos >= end or # <<<<<<<<<<<<<< @@ -6746,19 +6367,19 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 goto __pyx_L24_bool_binop_done; } - /* "_tree.pyx":223 + /* "stpredictions/models/OK3/_tree.pyx":223 * # dissimilar to v0.18 * is_leaf = (is_leaf or split.pos >= end or * (split.improvement + EPSILON < # <<<<<<<<<<<<<< * min_impurity_decrease)) * */ - __pyx_t_8 = (((__pyx_v_split.improvement + __pyx_v_5_tree_EPSILON) < __pyx_v_min_impurity_decrease) != 0); + __pyx_t_8 = (((__pyx_v_split.improvement + __pyx_v_13stpredictions_6models_3OK3_5_tree_EPSILON) < __pyx_v_min_impurity_decrease) != 0); __pyx_t_9 = __pyx_t_8; __pyx_L24_bool_binop_done:; __pyx_v_is_leaf = __pyx_t_9; - /* "_tree.pyx":217 + /* "stpredictions/models/OK3/_tree.pyx":217 * (impurity <= min_impurity_split)) * * if not is_leaf: # <<<<<<<<<<<<<< @@ -6767,17 +6388,17 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ } - /* "_tree.pyx":226 + /* "stpredictions/models/OK3/_tree.pyx":226 * min_impurity_decrease)) * * node_id = tree._add_node(parent, is_left, is_leaf, split.feature, # <<<<<<<<<<<<<< * split.threshold, impurity, n_node_samples, * weighted_n_node_samples) */ - __pyx_t_10 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_add_node(__pyx_v_tree, __pyx_v_parent, __pyx_v_is_left, __pyx_v_is_leaf, __pyx_v_split.feature, __pyx_v_split.threshold, __pyx_v_impurity, __pyx_v_n_node_samples, __pyx_v_weighted_n_node_samples); if (unlikely(__pyx_t_10 == ((__pyx_t_5_tree_SIZE_t)-1))) __PYX_ERR(0, 226, __pyx_L8_error) + __pyx_t_10 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_add_node(__pyx_v_tree, __pyx_v_parent, __pyx_v_is_left, __pyx_v_is_leaf, __pyx_v_split.feature, __pyx_v_split.threshold, __pyx_v_impurity, __pyx_v_n_node_samples, __pyx_v_weighted_n_node_samples); if (unlikely(__pyx_t_10 == ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)-1))) __PYX_ERR(0, 226, __pyx_L8_error) __pyx_v_node_id = __pyx_t_10; - /* "_tree.pyx":230 + /* "stpredictions/models/OK3/_tree.pyx":230 * weighted_n_node_samples) * * if node_id == SIZE_MAX: # <<<<<<<<<<<<<< @@ -6787,7 +6408,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((__pyx_v_node_id == SIZE_MAX) != 0); if (__pyx_t_9) { - /* "_tree.pyx":231 + /* "stpredictions/models/OK3/_tree.pyx":231 * * if node_id == SIZE_MAX: * rc = -1 # <<<<<<<<<<<<<< @@ -6796,7 +6417,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_v_rc = -1; - /* "_tree.pyx":232 + /* "stpredictions/models/OK3/_tree.pyx":232 * if node_id == SIZE_MAX: * rc = -1 * break # <<<<<<<<<<<<<< @@ -6805,7 +6426,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ goto __pyx_L15_break; - /* "_tree.pyx":230 + /* "stpredictions/models/OK3/_tree.pyx":230 * weighted_n_node_samples) * * if node_id == SIZE_MAX: # <<<<<<<<<<<<<< @@ -6814,16 +6435,16 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ } - /* "_tree.pyx":236 + /* "stpredictions/models/OK3/_tree.pyx":236 * # Store value for all nodes, to facilitate tree/model * # inspection and interpretation * splitter.node_value(tree.value + node_id * y.shape[0]) # <<<<<<<<<<<<<< * * if not is_leaf: */ - ((struct __pyx_vtabstruct_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_value(__pyx_v_splitter, (__pyx_v_tree->value + (__pyx_v_node_id * (__pyx_v_y->dimensions[0])))); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_value(__pyx_v_splitter, (__pyx_v_tree->value + (__pyx_v_node_id * (__pyx_v_y->dimensions[0])))); - /* "_tree.pyx":238 + /* "stpredictions/models/OK3/_tree.pyx":238 * splitter.node_value(tree.value + node_id * y.shape[0]) * * if not is_leaf: # <<<<<<<<<<<<<< @@ -6833,17 +6454,17 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((!(__pyx_v_is_leaf != 0)) != 0); if (__pyx_t_9) { - /* "_tree.pyx":240 + /* "stpredictions/models/OK3/_tree.pyx":240 * if not is_leaf: * # Push right child on stack * rc = stack.push(split.pos, end, depth + 1, node_id, 0, # <<<<<<<<<<<<<< * split.impurity_right, n_constant_features) * if rc == -1: */ - __pyx_t_5 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_split.pos, __pyx_v_end, (__pyx_v_depth + 1), __pyx_v_node_id, 0, __pyx_v_split.impurity_right, __pyx_v_n_constant_features); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 240, __pyx_L8_error) + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_split.pos, __pyx_v_end, (__pyx_v_depth + 1), __pyx_v_node_id, 0, __pyx_v_split.impurity_right, __pyx_v_n_constant_features); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 240, __pyx_L8_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":242 + /* "stpredictions/models/OK3/_tree.pyx":242 * rc = stack.push(split.pos, end, depth + 1, node_id, 0, * split.impurity_right, n_constant_features) * if rc == -1: # <<<<<<<<<<<<<< @@ -6853,7 +6474,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_9) { - /* "_tree.pyx":243 + /* "stpredictions/models/OK3/_tree.pyx":243 * split.impurity_right, n_constant_features) * if rc == -1: * break # <<<<<<<<<<<<<< @@ -6862,7 +6483,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ goto __pyx_L15_break; - /* "_tree.pyx":242 + /* "stpredictions/models/OK3/_tree.pyx":242 * rc = stack.push(split.pos, end, depth + 1, node_id, 0, * split.impurity_right, n_constant_features) * if rc == -1: # <<<<<<<<<<<<<< @@ -6871,17 +6492,17 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ } - /* "_tree.pyx":246 + /* "stpredictions/models/OK3/_tree.pyx":246 * * # Push left child on stack * rc = stack.push(start, split.pos, depth + 1, node_id, 1, # <<<<<<<<<<<<<< * split.impurity_left, n_constant_features) * if rc == -1: */ - __pyx_t_5 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_start, __pyx_v_split.pos, (__pyx_v_depth + 1), __pyx_v_node_id, 1, __pyx_v_split.impurity_left, __pyx_v_n_constant_features); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 246, __pyx_L8_error) + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_start, __pyx_v_split.pos, (__pyx_v_depth + 1), __pyx_v_node_id, 1, __pyx_v_split.impurity_left, __pyx_v_n_constant_features); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 246, __pyx_L8_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":248 + /* "stpredictions/models/OK3/_tree.pyx":248 * rc = stack.push(start, split.pos, depth + 1, node_id, 1, * split.impurity_left, n_constant_features) * if rc == -1: # <<<<<<<<<<<<<< @@ -6891,7 +6512,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_9) { - /* "_tree.pyx":249 + /* "stpredictions/models/OK3/_tree.pyx":249 * split.impurity_left, n_constant_features) * if rc == -1: * break # <<<<<<<<<<<<<< @@ -6900,7 +6521,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ goto __pyx_L15_break; - /* "_tree.pyx":248 + /* "stpredictions/models/OK3/_tree.pyx":248 * rc = stack.push(start, split.pos, depth + 1, node_id, 1, * split.impurity_left, n_constant_features) * if rc == -1: # <<<<<<<<<<<<<< @@ -6909,7 +6530,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ } - /* "_tree.pyx":238 + /* "stpredictions/models/OK3/_tree.pyx":238 * splitter.node_value(tree.value + node_id * y.shape[0]) * * if not is_leaf: # <<<<<<<<<<<<<< @@ -6918,7 +6539,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ } - /* "_tree.pyx":251 + /* "stpredictions/models/OK3/_tree.pyx":251 * break * * if depth > max_depth_seen: # <<<<<<<<<<<<<< @@ -6928,7 +6549,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((__pyx_v_depth > __pyx_v_max_depth_seen) != 0); if (__pyx_t_9) { - /* "_tree.pyx":252 + /* "stpredictions/models/OK3/_tree.pyx":252 * * if depth > max_depth_seen: * max_depth_seen = depth # <<<<<<<<<<<<<< @@ -6937,7 +6558,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_v_max_depth_seen = __pyx_v_depth; - /* "_tree.pyx":251 + /* "stpredictions/models/OK3/_tree.pyx":251 * break * * if depth > max_depth_seen: # <<<<<<<<<<<<<< @@ -6948,7 +6569,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 } __pyx_L15_break:; - /* "_tree.pyx":254 + /* "stpredictions/models/OK3/_tree.pyx":254 * max_depth_seen = depth * * if rc >= 0: # <<<<<<<<<<<<<< @@ -6958,19 +6579,19 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((__pyx_v_rc >= 0) != 0); if (__pyx_t_9) { - /* "_tree.pyx":255 + /* "stpredictions/models/OK3/_tree.pyx":255 * * if rc >= 0: * rc = tree._resize_c(tree.node_count) # <<<<<<<<<<<<<< * * if rc >= 0: */ - __pyx_t_15.__pyx_n = 1; - __pyx_t_15.capacity = __pyx_v_tree->node_count; - __pyx_t_5 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize_c(__pyx_v_tree, &__pyx_t_15); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 255, __pyx_L8_error) + __pyx_t_14.__pyx_n = 1; + __pyx_t_14.capacity = __pyx_v_tree->node_count; + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize_c(__pyx_v_tree, &__pyx_t_14); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 255, __pyx_L8_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":254 + /* "stpredictions/models/OK3/_tree.pyx":254 * max_depth_seen = depth * * if rc >= 0: # <<<<<<<<<<<<<< @@ -6979,7 +6600,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ } - /* "_tree.pyx":257 + /* "stpredictions/models/OK3/_tree.pyx":257 * rc = tree._resize_c(tree.node_count) * * if rc >= 0: # <<<<<<<<<<<<<< @@ -6989,7 +6610,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((__pyx_v_rc >= 0) != 0); if (__pyx_t_9) { - /* "_tree.pyx":258 + /* "stpredictions/models/OK3/_tree.pyx":258 * * if rc >= 0: * tree.max_depth = max_depth_seen # <<<<<<<<<<<<<< @@ -6998,7 +6619,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ __pyx_v_tree->max_depth = __pyx_v_max_depth_seen; - /* "_tree.pyx":257 + /* "stpredictions/models/OK3/_tree.pyx":257 * rc = tree._resize_c(tree.node_count) * * if rc >= 0: # <<<<<<<<<<<<<< @@ -7008,7 +6629,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 } } - /* "_tree.pyx":183 + /* "stpredictions/models/OK3/_tree.pyx":183 * cdef StackRecord stack_record * * with nogil: # <<<<<<<<<<<<<< @@ -7034,7 +6655,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 } } - /* "_tree.pyx":260 + /* "stpredictions/models/OK3/_tree.pyx":260 * tree.max_depth = max_depth_seen * * if rc == -1: # <<<<<<<<<<<<<< @@ -7044,7 +6665,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); if (unlikely(__pyx_t_9)) { - /* "_tree.pyx":261 + /* "stpredictions/models/OK3/_tree.pyx":261 * * if rc == -1: * raise MemoryError() # <<<<<<<<<<<<<< @@ -7053,7 +6674,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ PyErr_NoMemory(); __PYX_ERR(0, 261, __pyx_L1_error) - /* "_tree.pyx":260 + /* "stpredictions/models/OK3/_tree.pyx":260 * tree.max_depth = max_depth_seen * * if rc == -1: # <<<<<<<<<<<<<< @@ -7062,7 +6683,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 */ } - /* "_tree.pyx":266 + /* "stpredictions/models/OK3/_tree.pyx":266 * # feed the tree attribute 'K_y' * * tree.K_y = y # <<<<<<<<<<<<<< @@ -7075,7 +6696,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __Pyx_DECREF(((PyObject *)__pyx_v_tree->K_y)); __pyx_v_tree->K_y = __pyx_v_y; - /* "_tree.pyx":129 + /* "stpredictions/models/OK3/_tree.pyx":129 * self.min_impurity_split = min_impurity_split * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -7093,7 +6714,7 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 __Pyx_XDECREF(__pyx_t_4); __Pyx_XDECREF(__pyx_t_6); __PYX_XDEC_MEMVIEW(&__pyx_t_12, 1); - __Pyx_AddTraceback("_tree.DepthFirstTreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.DepthFirstTreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; __pyx_L0:; __Pyx_XDECREF((PyObject *)__pyx_v_splitter); @@ -7107,10 +6728,10 @@ static PyObject *__pyx_f_5_tree_21DepthFirstTreeBuilder_build(struct __pyx_obj_5 } /* Python wrapper */ -static PyObject *__pyx_pw_5_tree_21DepthFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static char __pyx_doc_5_tree_21DepthFirstTreeBuilder_2build[] = "Build a decision tree from the training set (X, y)."; -static PyObject *__pyx_pw_5_tree_21DepthFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { - struct __pyx_obj_5_tree_Tree *__pyx_v_tree = 0; +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_2build[] = "Build a decision tree from the training set (X, y)."; +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree = 0; PyObject *__pyx_v_X = 0; PyArrayObject *__pyx_v_y = 0; PyArrayObject *__pyx_v_sample_weight = 0; @@ -7124,7 +6745,7 @@ static PyObject *__pyx_pw_5_tree_21DepthFirstTreeBuilder_3build(PyObject *__pyx_ static PyObject **__pyx_pyargnames[] = {&__pyx_n_s_tree,&__pyx_n_s_X,&__pyx_n_s_y,&__pyx_n_s_sample_weight,0}; PyObject* values[4] = {0,0,0,0}; - /* "_tree.pyx":130 + /* "stpredictions/models/OK3/_tree.pyx":130 * * cpdef build(self, Tree tree, object X, np.ndarray y, * np.ndarray sample_weight=None): # <<<<<<<<<<<<<< @@ -7185,7 +6806,7 @@ static PyObject *__pyx_pw_5_tree_21DepthFirstTreeBuilder_3build(PyObject *__pyx_ default: goto __pyx_L5_argtuple_error; } } - __pyx_v_tree = ((struct __pyx_obj_5_tree_Tree *)values[0]); + __pyx_v_tree = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)values[0]); 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/*proto*/ +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_5__reduce_cython__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__reduce_cython__ (wrapper)", 0); - __pyx_r = __pyx_pf_5_tree_21DepthFirstTreeBuilder_4__reduce_cython__(((struct __pyx_obj_5_tree_DepthFirstTreeBuilder *)__pyx_v_self)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_4__reduce_cython__(((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *)__pyx_v_self)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_5_tree_21DepthFirstTreeBuilder_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self) { PyObject *__pyx_r = NULL; 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/*proto*/ +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_7__setstate_cython__(PyObject *__pyx_v_self, PyObject *__pyx_v___pyx_state) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("__setstate_cython__ (wrapper)", 0); - __pyx_r = __pyx_pf_5_tree_21DepthFirstTreeBuilder_6__setstate_cython__(((struct __pyx_obj_5_tree_DepthFirstTreeBuilder *)__pyx_v_self), ((PyObject *)__pyx_v___pyx_state)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_6__setstate_cython__(((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *)__pyx_v_self), ((PyObject *)__pyx_v___pyx_state)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_5_tree_21DepthFirstTreeBuilder_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_5_tree_DepthFirstTreeBuilder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state) { PyObject *__pyx_r = NULL; 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int __pyx_t_1; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "_tree.pyx":277 + /* "stpredictions/models/OK3/_tree.pyx":277 * or 0 otherwise. * """ * return frontier.push(rec.node_id, rec.start, rec.end, rec.pos, rec.depth, # <<<<<<<<<<<<<< * rec.is_leaf, rec.improvement, rec.impurity, * rec.impurity_left, rec.impurity_right) */ - __pyx_t_1 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->push(__pyx_v_frontier, __pyx_v_rec->node_id, __pyx_v_rec->start, __pyx_v_rec->end, __pyx_v_rec->pos, __pyx_v_rec->depth, __pyx_v_rec->is_leaf, __pyx_v_rec->improvement, __pyx_v_rec->impurity, __pyx_v_rec->impurity_left, __pyx_v_rec->impurity_right); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 277, __pyx_L1_error) + __pyx_t_1 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->push(__pyx_v_frontier, __pyx_v_rec->node_id, __pyx_v_rec->start, __pyx_v_rec->end, __pyx_v_rec->pos, __pyx_v_rec->depth, __pyx_v_rec->is_leaf, __pyx_v_rec->improvement, __pyx_v_rec->impurity, __pyx_v_rec->impurity_left, __pyx_v_rec->impurity_right); 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+ __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_leaf_nodes; double __pyx_v_min_impurity_decrease; double __pyx_v_min_impurity_split; int __pyx_lineno = 0; @@ -7526,7 +7147,7 @@ static int __pyx_pw_5_tree_20BestFirstTreeBuilder_1__cinit__(PyObject *__pyx_v_s values[6] = PyTuple_GET_ITEM(__pyx_args, 6); values[7] = PyTuple_GET_ITEM(__pyx_args, 7); } - __pyx_v_splitter = ((struct __pyx_obj_9_splitter_Splitter *)values[0]); + __pyx_v_splitter = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)values[0]); __pyx_v_min_samples_split = __Pyx_PyInt_As_Py_intptr_t(values[1]); if (unlikely((__pyx_v_min_samples_split == ((npy_intp)-1)) && PyErr_Occurred())) __PYX_ERR(0, 290, __pyx_L3_error) __pyx_v_min_samples_leaf = __Pyx_PyInt_As_Py_intptr_t(values[2]); if (unlikely((__pyx_v_min_samples_leaf == ((npy_intp)-1)) && PyErr_Occurred())) __PYX_ERR(0, 291, __pyx_L3_error) __pyx_v_min_weight_leaf = values[3]; @@ -7539,12 +7160,12 @@ static int __pyx_pw_5_tree_20BestFirstTreeBuilder_1__cinit__(PyObject *__pyx_v_s __pyx_L5_argtuple_error:; __Pyx_RaiseArgtupleInvalid("__cinit__", 1, 8, 8, PyTuple_GET_SIZE(__pyx_args)); __PYX_ERR(0, 290, __pyx_L3_error) __pyx_L3_error:; - __Pyx_AddTraceback("_tree.BestFirstTreeBuilder.__cinit__", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.BestFirstTreeBuilder.__cinit__", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return -1; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_splitter), __pyx_ptype_9_splitter_Splitter, 1, "splitter", 0))) __PYX_ERR(0, 290, __pyx_L1_error) - __pyx_r = __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(((struct __pyx_obj_5_tree_BestFirstTreeBuilder *)__pyx_v_self), __pyx_v_splitter, __pyx_v_min_samples_split, __pyx_v_min_samples_leaf, __pyx_v_min_weight_leaf, __pyx_v_max_depth, __pyx_v_max_leaf_nodes, __pyx_v_min_impurity_decrease, __pyx_v_min_impurity_split); + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_splitter), __pyx_ptype_13stpredictions_6models_3OK3_9_splitter_Splitter, 1, "splitter", 0))) __PYX_ERR(0, 290, __pyx_L1_error) + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder___cinit__(((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *)__pyx_v_self), __pyx_v_splitter, __pyx_v_min_samples_split, __pyx_v_min_samples_leaf, __pyx_v_min_weight_leaf, __pyx_v_max_depth, __pyx_v_max_leaf_nodes, __pyx_v_min_impurity_decrease, __pyx_v_min_impurity_split); /* function exit code */ goto __pyx_L0; @@ -7555,7 +7176,7 @@ static int __pyx_pw_5_tree_20BestFirstTreeBuilder_1__cinit__(PyObject *__pyx_v_s return __pyx_r; } -static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_leaf, PyObject *__pyx_v_min_weight_leaf, __pyx_t_5_tree_SIZE_t __pyx_v_max_depth, __pyx_t_5_tree_SIZE_t __pyx_v_max_leaf_nodes, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split) { +static int __pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf, PyObject *__pyx_v_min_weight_leaf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_leaf_nodes, double __pyx_v_min_impurity_decrease, double __pyx_v_min_impurity_split) { int __pyx_r; __Pyx_RefNannyDeclarations double __pyx_t_1; @@ -7564,7 +7185,7 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t int __pyx_clineno = 0; __Pyx_RefNannySetupContext("__cinit__", 0); - /* "_tree.pyx":294 + /* "stpredictions/models/OK3/_tree.pyx":294 * SIZE_t max_depth, SIZE_t max_leaf_nodes, * double min_impurity_decrease, double min_impurity_split): * self.splitter = splitter # <<<<<<<<<<<<<< @@ -7577,7 +7198,7 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t __Pyx_DECREF(((PyObject *)__pyx_v_self->__pyx_base.splitter)); __pyx_v_self->__pyx_base.splitter = __pyx_v_splitter; - /* "_tree.pyx":295 + /* "stpredictions/models/OK3/_tree.pyx":295 * double min_impurity_decrease, double min_impurity_split): * self.splitter = splitter * self.min_samples_split = min_samples_split # <<<<<<<<<<<<<< @@ -7586,7 +7207,7 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t */ __pyx_v_self->__pyx_base.min_samples_split = __pyx_v_min_samples_split; - /* "_tree.pyx":296 + /* "stpredictions/models/OK3/_tree.pyx":296 * self.splitter = splitter * self.min_samples_split = min_samples_split * self.min_samples_leaf = min_samples_leaf # <<<<<<<<<<<<<< @@ -7595,7 +7216,7 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t */ __pyx_v_self->__pyx_base.min_samples_leaf = __pyx_v_min_samples_leaf; - /* "_tree.pyx":297 + /* "stpredictions/models/OK3/_tree.pyx":297 * self.min_samples_split = min_samples_split * self.min_samples_leaf = min_samples_leaf * self.min_weight_leaf = min_weight_leaf # <<<<<<<<<<<<<< @@ -7605,7 +7226,7 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t __pyx_t_1 = __pyx_PyFloat_AsDouble(__pyx_v_min_weight_leaf); if (unlikely((__pyx_t_1 == (double)-1) && PyErr_Occurred())) __PYX_ERR(0, 297, __pyx_L1_error) __pyx_v_self->__pyx_base.min_weight_leaf = __pyx_t_1; - /* "_tree.pyx":298 + /* "stpredictions/models/OK3/_tree.pyx":298 * self.min_samples_leaf = min_samples_leaf * self.min_weight_leaf = min_weight_leaf * self.max_depth = max_depth # <<<<<<<<<<<<<< @@ -7614,7 +7235,7 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t */ __pyx_v_self->__pyx_base.max_depth = __pyx_v_max_depth; - /* "_tree.pyx":299 + /* "stpredictions/models/OK3/_tree.pyx":299 * self.min_weight_leaf = min_weight_leaf * self.max_depth = max_depth * self.max_leaf_nodes = max_leaf_nodes # <<<<<<<<<<<<<< @@ -7623,7 +7244,7 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t */ __pyx_v_self->max_leaf_nodes = __pyx_v_max_leaf_nodes; - /* "_tree.pyx":300 + /* "stpredictions/models/OK3/_tree.pyx":300 * self.max_depth = max_depth * self.max_leaf_nodes = max_leaf_nodes * self.min_impurity_decrease = min_impurity_decrease # <<<<<<<<<<<<<< @@ -7632,7 +7253,7 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t */ __pyx_v_self->__pyx_base.min_impurity_decrease = __pyx_v_min_impurity_decrease; - /* "_tree.pyx":301 + /* "stpredictions/models/OK3/_tree.pyx":301 * self.max_leaf_nodes = max_leaf_nodes * self.min_impurity_decrease = min_impurity_decrease * self.min_impurity_split = min_impurity_split # <<<<<<<<<<<<<< @@ -7641,7 +7262,7 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t */ __pyx_v_self->__pyx_base.min_impurity_split = __pyx_v_min_impurity_split; - /* "_tree.pyx":290 + /* "stpredictions/models/OK3/_tree.pyx":290 * cdef SIZE_t max_leaf_nodes * * def __cinit__(self, Splitter splitter, SIZE_t min_samples_split, # <<<<<<<<<<<<<< @@ -7653,14 +7274,14 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t __pyx_r = 0; goto __pyx_L0; __pyx_L1_error:; - __Pyx_AddTraceback("_tree.BestFirstTreeBuilder.__cinit__", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.BestFirstTreeBuilder.__cinit__", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = -1; __pyx_L0:; __Pyx_RefNannyFinishContext(); return __pyx_r; } -/* "_tree.pyx":303 +/* "stpredictions/models/OK3/_tree.pyx":303 * self.min_impurity_split = min_impurity_split * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -7668,10 +7289,10 @@ static int __pyx_pf_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_5_t * """Build a decision tree from the training set (X, y).""" */ -static PyObject *__pyx_pw_5_tree_20BestFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_20BestFirstTreeBuilder_build *__pyx_optional_args) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_build *__pyx_optional_args) { - /* "_tree.pyx":304 + /* "stpredictions/models/OK3/_tree.pyx":304 * * cpdef build(self, Tree tree, object X, np.ndarray y, * np.ndarray sample_weight=None): # <<<<<<<<<<<<<< @@ -7679,23 +7300,23 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ * */ PyArrayObject *__pyx_v_sample_weight = ((PyArrayObject *)Py_None); - __pyx_t_5_tree_DOUBLE_t *__pyx_v_sample_weight_ptr; - struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter = 0; - __pyx_t_5_tree_SIZE_t __pyx_v_max_leaf_nodes; - CYTHON_UNUSED __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_leaf; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_sample_weight_ptr; + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter = 0; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_leaf_nodes; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_leaf; CYTHON_UNUSED double __pyx_v_min_weight_leaf; - CYTHON_UNUSED __pyx_t_5_tree_SIZE_t __pyx_v_min_samples_split; - struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *__pyx_v_frontier = 0; - struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord __pyx_v_record; - struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord __pyx_v_split_node_left; - struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord __pyx_v_split_node_right; - __pyx_t_5_tree_SIZE_t __pyx_v_n_node_samples; - __pyx_t_5_tree_SIZE_t __pyx_v_max_split_nodes; + CYTHON_UNUSED __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_min_samples_split; + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_v_frontier = 0; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord __pyx_v_record; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord __pyx_v_split_node_left; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord __pyx_v_split_node_right; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_split_nodes; int __pyx_v_is_leaf; - __pyx_t_5_tree_SIZE_t __pyx_v_max_depth_seen; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_max_depth_seen; int __pyx_v_rc; - struct __pyx_t_5_tree_Node *__pyx_v_node; - __pyx_t_5_tree_SIZE_t __pyx_v_init_capacity; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_node; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_init_capacity; PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -7707,12 +7328,11 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ PyObject *(*__pyx_t_7)(PyObject *); int __pyx_t_8; int __pyx_t_9; - __pyx_t_5_tree_SIZE_t __pyx_t_10; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_10; double __pyx_t_11; __Pyx_memviewslice __pyx_t_12 = { 0, 0, { 0 }, { 0 }, { 0 } }; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_13; - __pyx_t_7sklearn_4tree_6_utils_SIZE_t __pyx_t_14; - struct __pyx_opt_args_5_tree_4Tree__resize_c __pyx_t_15; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_t_13; + struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c __pyx_t_14; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -7726,7 +7346,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __Pyx_INCREF((PyObject *)__pyx_v_y); __Pyx_INCREF((PyObject *)__pyx_v_sample_weight); - /* "_tree.pyx":303 + /* "stpredictions/models/OK3/_tree.pyx":303 * self.min_impurity_split = min_impurity_split * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -7744,7 +7364,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ #endif __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_self), __pyx_n_s_build); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 303, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_5_tree_20BestFirstTreeBuilder_3build)) { + if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_3build)) { __Pyx_XDECREF(__pyx_r); __Pyx_INCREF(__pyx_t_1); __pyx_t_3 = __pyx_t_1; __pyx_t_4 = NULL; @@ -7816,14 +7436,14 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ #endif } - /* "_tree.pyx":308 + /* "stpredictions/models/OK3/_tree.pyx":308 * * # check input * X, y, sample_weight = self._check_input(X, y, sample_weight) # <<<<<<<<<<<<<< * * cdef DOUBLE_t* sample_weight_ptr = NULL */ - __pyx_t_1 = __pyx_f_5_tree_11TreeBuilder__check_input(((struct __pyx_obj_5_tree_TreeBuilder *)__pyx_v_self), __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 308, __pyx_L1_error) + __pyx_t_1 = __pyx_f_13stpredictions_6models_3OK3_5_tree_11TreeBuilder__check_input(((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *)__pyx_v_self), __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 308, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); if ((likely(PyTuple_CheckExact(__pyx_t_1))) || (PyList_CheckExact(__pyx_t_1))) { PyObject* sequence = __pyx_t_1; @@ -7887,7 +7507,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __Pyx_DECREF_SET(__pyx_v_sample_weight, ((PyArrayObject *)__pyx_t_6)); __pyx_t_6 = 0; - /* "_tree.pyx":310 + /* "stpredictions/models/OK3/_tree.pyx":310 * X, y, sample_weight = self._check_input(X, y, sample_weight) * * cdef DOUBLE_t* sample_weight_ptr = NULL # <<<<<<<<<<<<<< @@ -7896,7 +7516,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ __pyx_v_sample_weight_ptr = NULL; - /* "_tree.pyx":311 + /* "stpredictions/models/OK3/_tree.pyx":311 * * cdef DOUBLE_t* sample_weight_ptr = NULL * if sample_weight is not None: # <<<<<<<<<<<<<< @@ -7907,16 +7527,16 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = (__pyx_t_8 != 0); if (__pyx_t_9) { - /* "_tree.pyx":312 + /* "stpredictions/models/OK3/_tree.pyx":312 * cdef DOUBLE_t* sample_weight_ptr = NULL * if sample_weight is not None: * sample_weight_ptr = sample_weight.data # <<<<<<<<<<<<<< * * # Parameters */ - __pyx_v_sample_weight_ptr = ((__pyx_t_5_tree_DOUBLE_t *)__pyx_v_sample_weight->data); + __pyx_v_sample_weight_ptr = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *)__pyx_v_sample_weight->data); - /* "_tree.pyx":311 + /* "stpredictions/models/OK3/_tree.pyx":311 * * cdef DOUBLE_t* sample_weight_ptr = NULL * if sample_weight is not None: # <<<<<<<<<<<<<< @@ -7925,7 +7545,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ } - /* "_tree.pyx":315 + /* "stpredictions/models/OK3/_tree.pyx":315 * * # Parameters * cdef Splitter splitter = self.splitter # <<<<<<<<<<<<<< @@ -7934,10 +7554,10 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ __pyx_t_1 = ((PyObject *)__pyx_v_self->__pyx_base.splitter); __Pyx_INCREF(__pyx_t_1); - __pyx_v_splitter = ((struct __pyx_obj_9_splitter_Splitter *)__pyx_t_1); + __pyx_v_splitter = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":316 + /* "stpredictions/models/OK3/_tree.pyx":316 * # Parameters * cdef Splitter splitter = self.splitter * cdef SIZE_t max_leaf_nodes = self.max_leaf_nodes # <<<<<<<<<<<<<< @@ -7947,7 +7567,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_10 = __pyx_v_self->max_leaf_nodes; __pyx_v_max_leaf_nodes = __pyx_t_10; - /* "_tree.pyx":317 + /* "stpredictions/models/OK3/_tree.pyx":317 * cdef Splitter splitter = self.splitter * cdef SIZE_t max_leaf_nodes = self.max_leaf_nodes * cdef SIZE_t min_samples_leaf = self.min_samples_leaf # <<<<<<<<<<<<<< @@ -7957,7 +7577,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_10 = __pyx_v_self->__pyx_base.min_samples_leaf; __pyx_v_min_samples_leaf = __pyx_t_10; - /* "_tree.pyx":318 + /* "stpredictions/models/OK3/_tree.pyx":318 * cdef SIZE_t max_leaf_nodes = self.max_leaf_nodes * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf # <<<<<<<<<<<<<< @@ -7967,7 +7587,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_11 = __pyx_v_self->__pyx_base.min_weight_leaf; __pyx_v_min_weight_leaf = __pyx_t_11; - /* "_tree.pyx":319 + /* "stpredictions/models/OK3/_tree.pyx":319 * cdef SIZE_t min_samples_leaf = self.min_samples_leaf * cdef double min_weight_leaf = self.min_weight_leaf * cdef SIZE_t min_samples_split = self.min_samples_split # <<<<<<<<<<<<<< @@ -7977,45 +7597,45 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_10 = __pyx_v_self->__pyx_base.min_samples_split; __pyx_v_min_samples_split = __pyx_t_10; - /* "_tree.pyx":322 + /* "stpredictions/models/OK3/_tree.pyx":322 * * # Recursive partition (without actual recursion) * splitter.init(X, y, sample_weight_ptr) # <<<<<<<<<<<<<< * * cdef PriorityHeap frontier = PriorityHeap(INITIAL_STACK_SIZE) */ - __pyx_t_12 = __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__(((PyObject *)__pyx_v_y), 0); if (unlikely(!__pyx_t_12.memview)) __PYX_ERR(0, 322, __pyx_L1_error) - __pyx_t_5 = ((struct __pyx_vtabstruct_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->init(__pyx_v_splitter, __pyx_v_X, __pyx_t_12, __pyx_v_sample_weight_ptr); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 322, __pyx_L1_error) + __pyx_t_12 = __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t__const__(((PyObject *)__pyx_v_y), 0); if (unlikely(!__pyx_t_12.memview)) __PYX_ERR(0, 322, __pyx_L1_error) + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->init(__pyx_v_splitter, __pyx_v_X, __pyx_t_12, __pyx_v_sample_weight_ptr); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 322, __pyx_L1_error) __PYX_XDEC_MEMVIEW(&__pyx_t_12, 1); __pyx_t_12.memview = NULL; __pyx_t_12.data = NULL; - /* "_tree.pyx":324 + /* "stpredictions/models/OK3/_tree.pyx":324 * splitter.init(X, y, sample_weight_ptr) * * cdef PriorityHeap frontier = PriorityHeap(INITIAL_STACK_SIZE) # <<<<<<<<<<<<<< * cdef PriorityHeapRecord record * cdef PriorityHeapRecord split_node_left */ - __pyx_t_1 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_5_tree_INITIAL_STACK_SIZE); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 324, __pyx_L1_error) + __pyx_t_1 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_13stpredictions_6models_3OK3_5_tree_INITIAL_STACK_SIZE); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 324, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - __pyx_t_6 = __Pyx_PyObject_CallOneArg(((PyObject *)__pyx_ptype_7sklearn_4tree_6_utils_PriorityHeap), __pyx_t_1); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 324, __pyx_L1_error) + __pyx_t_6 = __Pyx_PyObject_CallOneArg(((PyObject *)__pyx_ptype_13stpredictions_6models_3OK3_6_utils_PriorityHeap), __pyx_t_1); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 324, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_v_frontier = ((struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_t_6); + __pyx_v_frontier = ((struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *)__pyx_t_6); __pyx_t_6 = 0; - /* "_tree.pyx":329 + /* "stpredictions/models/OK3/_tree.pyx":329 * cdef PriorityHeapRecord split_node_right * * cdef SIZE_t n_node_samples = splitter.n_samples # <<<<<<<<<<<<<< * cdef SIZE_t max_split_nodes = max_leaf_nodes - 1 * cdef bint is_leaf */ - __pyx_t_13 = __pyx_v_splitter->n_samples; - __pyx_v_n_node_samples = __pyx_t_13; + __pyx_t_10 = __pyx_v_splitter->n_samples; + __pyx_v_n_node_samples = __pyx_t_10; - /* "_tree.pyx":330 + /* "stpredictions/models/OK3/_tree.pyx":330 * * cdef SIZE_t n_node_samples = splitter.n_samples * cdef SIZE_t max_split_nodes = max_leaf_nodes - 1 # <<<<<<<<<<<<<< @@ -8024,7 +7644,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ __pyx_v_max_split_nodes = (__pyx_v_max_leaf_nodes - 1); - /* "_tree.pyx":332 + /* "stpredictions/models/OK3/_tree.pyx":332 * cdef SIZE_t max_split_nodes = max_leaf_nodes - 1 * cdef bint is_leaf * cdef SIZE_t max_depth_seen = -1 # <<<<<<<<<<<<<< @@ -8033,7 +7653,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ __pyx_v_max_depth_seen = -1; - /* "_tree.pyx":333 + /* "stpredictions/models/OK3/_tree.pyx":333 * cdef bint is_leaf * cdef SIZE_t max_depth_seen = -1 * cdef int rc = 0 # <<<<<<<<<<<<<< @@ -8042,7 +7662,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ __pyx_v_rc = 0; - /* "_tree.pyx":337 + /* "stpredictions/models/OK3/_tree.pyx":337 * * # Initial capacity * cdef SIZE_t init_capacity = max_split_nodes + max_leaf_nodes # <<<<<<<<<<<<<< @@ -8051,16 +7671,16 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ __pyx_v_init_capacity = (__pyx_v_max_split_nodes + __pyx_v_max_leaf_nodes); - /* "_tree.pyx":338 + /* "stpredictions/models/OK3/_tree.pyx":338 * # Initial capacity * cdef SIZE_t init_capacity = max_split_nodes + max_leaf_nodes * tree._resize(init_capacity) # <<<<<<<<<<<<<< * * with nogil: */ - __pyx_t_5 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize(__pyx_v_tree, __pyx_v_init_capacity); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 338, __pyx_L1_error) + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize(__pyx_v_tree, __pyx_v_init_capacity); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 338, __pyx_L1_error) - /* "_tree.pyx":340 + /* "stpredictions/models/OK3/_tree.pyx":340 * tree._resize(init_capacity) * * with nogil: # <<<<<<<<<<<<<< @@ -8075,17 +7695,17 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ #endif /*try:*/ { - /* "_tree.pyx":342 + /* "stpredictions/models/OK3/_tree.pyx":342 * with nogil: * # add root to frontier * rc = self._add_split_node(splitter, tree, 0, n_node_samples, # <<<<<<<<<<<<<< * INFINITY, IS_FIRST, IS_LEFT, NULL, 0, * &split_node_left, */ - __pyx_t_5 = __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, 0, __pyx_v_n_node_samples, __pyx_v_5_tree_INFINITY, __pyx_v_5_tree_IS_FIRST, __pyx_v_5_tree_IS_LEFT, NULL, 0, (&__pyx_v_split_node_left), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 342, __pyx_L7_error) + __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, 0, __pyx_v_n_node_samples, __pyx_v_13stpredictions_6models_3OK3_5_tree_INFINITY, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_FIRST, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_LEFT, NULL, 0, (&__pyx_v_split_node_left), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 342, __pyx_L7_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":346 + /* "stpredictions/models/OK3/_tree.pyx":346 * &split_node_left, * y.shape[0]) * if rc >= 0: # <<<<<<<<<<<<<< @@ -8095,17 +7715,17 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = ((__pyx_v_rc >= 0) != 0); if (__pyx_t_9) { - /* "_tree.pyx":347 + /* "stpredictions/models/OK3/_tree.pyx":347 * y.shape[0]) * if rc >= 0: * rc = _add_to_frontier(&split_node_left, frontier) # <<<<<<<<<<<<<< * * if rc == -1: */ - __pyx_t_5 = __pyx_f_5_tree__add_to_frontier((&__pyx_v_split_node_left), __pyx_v_frontier); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 347, __pyx_L7_error) + __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree__add_to_frontier((&__pyx_v_split_node_left), __pyx_v_frontier); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 347, __pyx_L7_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":346 + /* "stpredictions/models/OK3/_tree.pyx":346 * &split_node_left, * y.shape[0]) * if rc >= 0: # <<<<<<<<<<<<<< @@ -8114,7 +7734,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ } - /* "_tree.pyx":349 + /* "stpredictions/models/OK3/_tree.pyx":349 * rc = _add_to_frontier(&split_node_left, frontier) * * if rc == -1: # <<<<<<<<<<<<<< @@ -8124,7 +7744,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_9) { - /* "_tree.pyx":350 + /* "stpredictions/models/OK3/_tree.pyx":350 * * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -8137,7 +7757,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ #endif /*try:*/ { - /* "_tree.pyx":351 + /* "stpredictions/models/OK3/_tree.pyx":351 * if rc == -1: * with gil: * raise MemoryError() # <<<<<<<<<<<<<< @@ -8147,7 +7767,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ PyErr_NoMemory(); __PYX_ERR(0, 351, __pyx_L12_error) } - /* "_tree.pyx":350 + /* "stpredictions/models/OK3/_tree.pyx":350 * * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -8164,7 +7784,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ } } - /* "_tree.pyx":349 + /* "stpredictions/models/OK3/_tree.pyx":349 * rc = _add_to_frontier(&split_node_left, frontier) * * if rc == -1: # <<<<<<<<<<<<<< @@ -8173,7 +7793,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ } - /* "_tree.pyx":353 + /* "stpredictions/models/OK3/_tree.pyx":353 * raise MemoryError() * * while not frontier.is_empty(): # <<<<<<<<<<<<<< @@ -8181,19 +7801,19 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ * */ while (1) { - __pyx_t_9 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->is_empty(__pyx_v_frontier) != 0)) != 0); + __pyx_t_9 = ((!(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->is_empty(__pyx_v_frontier) != 0)) != 0); if (!__pyx_t_9) break; - /* "_tree.pyx":354 + /* "stpredictions/models/OK3/_tree.pyx":354 * * while not frontier.is_empty(): * frontier.pop(&record) # <<<<<<<<<<<<<< * * node = &tree.nodes[record.node_id] */ - (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->pop(__pyx_v_frontier, (&__pyx_v_record))); + (void)(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->pop(__pyx_v_frontier, (&__pyx_v_record))); - /* "_tree.pyx":356 + /* "stpredictions/models/OK3/_tree.pyx":356 * frontier.pop(&record) * * node = &tree.nodes[record.node_id] # <<<<<<<<<<<<<< @@ -8202,7 +7822,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ __pyx_v_node = (&(__pyx_v_tree->nodes[__pyx_v_record.node_id])); - /* "_tree.pyx":357 + /* "stpredictions/models/OK3/_tree.pyx":357 * * node = &tree.nodes[record.node_id] * is_leaf = (record.is_leaf or max_split_nodes <= 0) # <<<<<<<<<<<<<< @@ -8220,7 +7840,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_L16_bool_binop_done:; __pyx_v_is_leaf = __pyx_t_9; - /* "_tree.pyx":359 + /* "stpredictions/models/OK3/_tree.pyx":359 * is_leaf = (record.is_leaf or max_split_nodes <= 0) * * if is_leaf: # <<<<<<<<<<<<<< @@ -8230,43 +7850,43 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = (__pyx_v_is_leaf != 0); if (__pyx_t_9) { - /* "_tree.pyx":361 + /* "stpredictions/models/OK3/_tree.pyx":361 * if is_leaf: * # Node is not expandable; set node as leaf * node.left_child = _TREE_LEAF # <<<<<<<<<<<<<< * node.right_child = _TREE_LEAF * node.feature = _TREE_UNDEFINED */ - __pyx_v_node->left_child = __pyx_v_5_tree__TREE_LEAF; + __pyx_v_node->left_child = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF; - /* "_tree.pyx":362 + /* "stpredictions/models/OK3/_tree.pyx":362 * # Node is not expandable; set node as leaf * node.left_child = _TREE_LEAF * node.right_child = _TREE_LEAF # <<<<<<<<<<<<<< * node.feature = _TREE_UNDEFINED * node.threshold = _TREE_UNDEFINED */ - __pyx_v_node->right_child = __pyx_v_5_tree__TREE_LEAF; + __pyx_v_node->right_child = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF; - /* "_tree.pyx":363 + /* "stpredictions/models/OK3/_tree.pyx":363 * node.left_child = _TREE_LEAF * node.right_child = _TREE_LEAF * node.feature = _TREE_UNDEFINED # <<<<<<<<<<<<<< * node.threshold = _TREE_UNDEFINED * */ - __pyx_v_node->feature = __pyx_v_5_tree__TREE_UNDEFINED; + __pyx_v_node->feature = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED; - /* "_tree.pyx":364 + /* "stpredictions/models/OK3/_tree.pyx":364 * node.right_child = _TREE_LEAF * node.feature = _TREE_UNDEFINED * node.threshold = _TREE_UNDEFINED # <<<<<<<<<<<<<< * * else: */ - __pyx_v_node->threshold = __pyx_v_5_tree__TREE_UNDEFINED; + __pyx_v_node->threshold = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED; - /* "_tree.pyx":359 + /* "stpredictions/models/OK3/_tree.pyx":359 * is_leaf = (record.is_leaf or max_split_nodes <= 0) * * if is_leaf: # <<<<<<<<<<<<<< @@ -8276,7 +7896,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ goto __pyx_L18; } - /* "_tree.pyx":370 + /* "stpredictions/models/OK3/_tree.pyx":370 * * # Decrement number of split nodes available * max_split_nodes -= 1 # <<<<<<<<<<<<<< @@ -8286,17 +7906,17 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ /*else*/ { __pyx_v_max_split_nodes = (__pyx_v_max_split_nodes - 1); - /* "_tree.pyx":373 + /* "stpredictions/models/OK3/_tree.pyx":373 * * # Compute left split node * rc = self._add_split_node(splitter, tree, # <<<<<<<<<<<<<< * record.start, record.pos, * record.impurity_left, */ - __pyx_t_5 = __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, __pyx_v_record.start, __pyx_v_record.pos, __pyx_v_record.impurity_left, __pyx_v_5_tree_IS_NOT_FIRST, __pyx_v_5_tree_IS_LEFT, __pyx_v_node, (__pyx_v_record.depth + 1), (&__pyx_v_split_node_left), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 373, __pyx_L7_error) + __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, __pyx_v_record.start, __pyx_v_record.pos, __pyx_v_record.impurity_left, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_FIRST, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_LEFT, __pyx_v_node, (__pyx_v_record.depth + 1), (&__pyx_v_split_node_left), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 373, __pyx_L7_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":380 + /* "stpredictions/models/OK3/_tree.pyx":380 * &split_node_left, * y.shape[0]) * if rc == -1: # <<<<<<<<<<<<<< @@ -8306,7 +7926,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_9) { - /* "_tree.pyx":381 + /* "stpredictions/models/OK3/_tree.pyx":381 * y.shape[0]) * if rc == -1: * break # <<<<<<<<<<<<<< @@ -8315,7 +7935,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ goto __pyx_L15_break; - /* "_tree.pyx":380 + /* "stpredictions/models/OK3/_tree.pyx":380 * &split_node_left, * y.shape[0]) * if rc == -1: # <<<<<<<<<<<<<< @@ -8324,7 +7944,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ } - /* "_tree.pyx":384 + /* "stpredictions/models/OK3/_tree.pyx":384 * * # tree.nodes may have changed * node = &tree.nodes[record.node_id] # <<<<<<<<<<<<<< @@ -8333,17 +7953,17 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ __pyx_v_node = (&(__pyx_v_tree->nodes[__pyx_v_record.node_id])); - /* "_tree.pyx":387 + /* "stpredictions/models/OK3/_tree.pyx":387 * * # Compute right split node * rc = self._add_split_node(splitter, tree, record.pos, # <<<<<<<<<<<<<< * record.end, * record.impurity_right, */ - __pyx_t_5 = __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, __pyx_v_record.pos, __pyx_v_record.end, __pyx_v_record.impurity_right, __pyx_v_5_tree_IS_NOT_FIRST, __pyx_v_5_tree_IS_NOT_LEFT, __pyx_v_node, (__pyx_v_record.depth + 1), (&__pyx_v_split_node_right), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 387, __pyx_L7_error) + __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, __pyx_v_record.pos, __pyx_v_record.end, __pyx_v_record.impurity_right, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_FIRST, __pyx_v_13stpredictions_6models_3OK3_5_tree_IS_NOT_LEFT, __pyx_v_node, (__pyx_v_record.depth + 1), (&__pyx_v_split_node_right), (__pyx_v_y->dimensions[0])); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 387, __pyx_L7_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":394 + /* "stpredictions/models/OK3/_tree.pyx":394 * &split_node_right, * y.shape[0]) * if rc == -1: # <<<<<<<<<<<<<< @@ -8353,7 +7973,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_9) { - /* "_tree.pyx":395 + /* "stpredictions/models/OK3/_tree.pyx":395 * y.shape[0]) * if rc == -1: * break # <<<<<<<<<<<<<< @@ -8362,7 +7982,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ goto __pyx_L15_break; - /* "_tree.pyx":394 + /* "stpredictions/models/OK3/_tree.pyx":394 * &split_node_right, * y.shape[0]) * if rc == -1: # <<<<<<<<<<<<<< @@ -8371,17 +7991,17 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ } - /* "_tree.pyx":398 + /* "stpredictions/models/OK3/_tree.pyx":398 * * # Add nodes to queue * rc = _add_to_frontier(&split_node_left, frontier) # <<<<<<<<<<<<<< * if rc == -1: * break */ - __pyx_t_5 = __pyx_f_5_tree__add_to_frontier((&__pyx_v_split_node_left), __pyx_v_frontier); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 398, __pyx_L7_error) + __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree__add_to_frontier((&__pyx_v_split_node_left), __pyx_v_frontier); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 398, __pyx_L7_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":399 + /* "stpredictions/models/OK3/_tree.pyx":399 * # Add nodes to queue * rc = _add_to_frontier(&split_node_left, frontier) * if rc == -1: # <<<<<<<<<<<<<< @@ -8391,7 +8011,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_9) { - /* "_tree.pyx":400 + /* "stpredictions/models/OK3/_tree.pyx":400 * rc = _add_to_frontier(&split_node_left, frontier) * if rc == -1: * break # <<<<<<<<<<<<<< @@ -8400,7 +8020,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ goto __pyx_L15_break; - /* "_tree.pyx":399 + /* "stpredictions/models/OK3/_tree.pyx":399 * # Add nodes to queue * rc = _add_to_frontier(&split_node_left, frontier) * if rc == -1: # <<<<<<<<<<<<<< @@ -8409,17 +8029,17 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ } - /* "_tree.pyx":402 + /* "stpredictions/models/OK3/_tree.pyx":402 * break * * rc = _add_to_frontier(&split_node_right, frontier) # <<<<<<<<<<<<<< * if rc == -1: * break */ - __pyx_t_5 = __pyx_f_5_tree__add_to_frontier((&__pyx_v_split_node_right), __pyx_v_frontier); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 402, __pyx_L7_error) + __pyx_t_5 = __pyx_f_13stpredictions_6models_3OK3_5_tree__add_to_frontier((&__pyx_v_split_node_right), __pyx_v_frontier); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 402, __pyx_L7_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":403 + /* "stpredictions/models/OK3/_tree.pyx":403 * * rc = _add_to_frontier(&split_node_right, frontier) * if rc == -1: # <<<<<<<<<<<<<< @@ -8429,7 +8049,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_9) { - /* "_tree.pyx":404 + /* "stpredictions/models/OK3/_tree.pyx":404 * rc = _add_to_frontier(&split_node_right, frontier) * if rc == -1: * break # <<<<<<<<<<<<<< @@ -8438,7 +8058,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ goto __pyx_L15_break; - /* "_tree.pyx":403 + /* "stpredictions/models/OK3/_tree.pyx":403 * * rc = _add_to_frontier(&split_node_right, frontier) * if rc == -1: # <<<<<<<<<<<<<< @@ -8449,7 +8069,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ } __pyx_L18:; - /* "_tree.pyx":406 + /* "stpredictions/models/OK3/_tree.pyx":406 * break * * if record.depth > max_depth_seen: # <<<<<<<<<<<<<< @@ -8459,17 +8079,17 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = ((__pyx_v_record.depth > __pyx_v_max_depth_seen) != 0); if (__pyx_t_9) { - /* "_tree.pyx":407 + /* "stpredictions/models/OK3/_tree.pyx":407 * * if record.depth > max_depth_seen: * max_depth_seen = record.depth # <<<<<<<<<<<<<< * * if rc >= 0: */ - __pyx_t_14 = __pyx_v_record.depth; - __pyx_v_max_depth_seen = __pyx_t_14; + __pyx_t_13 = __pyx_v_record.depth; + __pyx_v_max_depth_seen = __pyx_t_13; - /* "_tree.pyx":406 + /* "stpredictions/models/OK3/_tree.pyx":406 * break * * if record.depth > max_depth_seen: # <<<<<<<<<<<<<< @@ -8480,7 +8100,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ } __pyx_L15_break:; - /* "_tree.pyx":409 + /* "stpredictions/models/OK3/_tree.pyx":409 * max_depth_seen = record.depth * * if rc >= 0: # <<<<<<<<<<<<<< @@ -8490,19 +8110,19 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = ((__pyx_v_rc >= 0) != 0); if (__pyx_t_9) { - /* "_tree.pyx":410 + /* "stpredictions/models/OK3/_tree.pyx":410 * * if rc >= 0: * rc = tree._resize_c(tree.node_count) # <<<<<<<<<<<<<< * * if rc >= 0: */ - __pyx_t_15.__pyx_n = 1; - __pyx_t_15.capacity = __pyx_v_tree->node_count; - __pyx_t_5 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize_c(__pyx_v_tree, &__pyx_t_15); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 410, __pyx_L7_error) + __pyx_t_14.__pyx_n = 1; + __pyx_t_14.capacity = __pyx_v_tree->node_count; + __pyx_t_5 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize_c(__pyx_v_tree, &__pyx_t_14); if (unlikely(__pyx_t_5 == ((int)-1))) __PYX_ERR(0, 410, __pyx_L7_error) __pyx_v_rc = __pyx_t_5; - /* "_tree.pyx":409 + /* "stpredictions/models/OK3/_tree.pyx":409 * max_depth_seen = record.depth * * if rc >= 0: # <<<<<<<<<<<<<< @@ -8511,7 +8131,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ } - /* "_tree.pyx":412 + /* "stpredictions/models/OK3/_tree.pyx":412 * rc = tree._resize_c(tree.node_count) * * if rc >= 0: # <<<<<<<<<<<<<< @@ -8521,7 +8141,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = ((__pyx_v_rc >= 0) != 0); if (__pyx_t_9) { - /* "_tree.pyx":413 + /* "stpredictions/models/OK3/_tree.pyx":413 * * if rc >= 0: * tree.max_depth = max_depth_seen # <<<<<<<<<<<<<< @@ -8530,7 +8150,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ __pyx_v_tree->max_depth = __pyx_v_max_depth_seen; - /* "_tree.pyx":412 + /* "stpredictions/models/OK3/_tree.pyx":412 * rc = tree._resize_c(tree.node_count) * * if rc >= 0: # <<<<<<<<<<<<<< @@ -8540,7 +8160,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ } } - /* "_tree.pyx":340 + /* "stpredictions/models/OK3/_tree.pyx":340 * tree._resize(init_capacity) * * with nogil: # <<<<<<<<<<<<<< @@ -8566,7 +8186,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ } } - /* "_tree.pyx":415 + /* "stpredictions/models/OK3/_tree.pyx":415 * tree.max_depth = max_depth_seen * * if rc == -1: # <<<<<<<<<<<<<< @@ -8576,7 +8196,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __pyx_t_9 = ((__pyx_v_rc == -1L) != 0); if (unlikely(__pyx_t_9)) { - /* "_tree.pyx":416 + /* "stpredictions/models/OK3/_tree.pyx":416 * * if rc == -1: * raise MemoryError() # <<<<<<<<<<<<<< @@ -8585,7 +8205,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ PyErr_NoMemory(); __PYX_ERR(0, 416, __pyx_L1_error) - /* "_tree.pyx":415 + /* "stpredictions/models/OK3/_tree.pyx":415 * tree.max_depth = max_depth_seen * * if rc == -1: # <<<<<<<<<<<<<< @@ -8594,7 +8214,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ */ } - /* "_tree.pyx":421 + /* "stpredictions/models/OK3/_tree.pyx":421 * # feed the tree attribute 'K_y' * * tree.K_y = y # <<<<<<<<<<<<<< @@ -8607,7 +8227,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __Pyx_DECREF(((PyObject *)__pyx_v_tree->K_y)); __pyx_v_tree->K_y = __pyx_v_y; - /* "_tree.pyx":303 + /* "stpredictions/models/OK3/_tree.pyx":303 * self.min_impurity_split = min_impurity_split * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -8625,7 +8245,7 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ __Pyx_XDECREF(__pyx_t_4); __Pyx_XDECREF(__pyx_t_6); __PYX_XDEC_MEMVIEW(&__pyx_t_12, 1); - __Pyx_AddTraceback("_tree.BestFirstTreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.BestFirstTreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; __pyx_L0:; __Pyx_XDECREF((PyObject *)__pyx_v_splitter); @@ -8639,10 +8259,10 @@ static PyObject *__pyx_f_5_tree_20BestFirstTreeBuilder_build(struct __pyx_obj_5_ } /* Python wrapper */ -static PyObject *__pyx_pw_5_tree_20BestFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static char __pyx_doc_5_tree_20BestFirstTreeBuilder_2build[] = "Build a decision tree from the training set (X, y)."; -static PyObject *__pyx_pw_5_tree_20BestFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { - struct __pyx_obj_5_tree_Tree *__pyx_v_tree = 0; +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_2build[] = "Build a decision tree from the training set (X, y)."; +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_3build(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree = 0; PyObject *__pyx_v_X = 0; PyArrayObject *__pyx_v_y = 0; PyArrayObject *__pyx_v_sample_weight = 0; @@ -8656,7 +8276,7 @@ static PyObject *__pyx_pw_5_tree_20BestFirstTreeBuilder_3build(PyObject *__pyx_v static PyObject **__pyx_pyargnames[] = {&__pyx_n_s_tree,&__pyx_n_s_X,&__pyx_n_s_y,&__pyx_n_s_sample_weight,0}; PyObject* values[4] = {0,0,0,0}; - /* "_tree.pyx":304 + /* "stpredictions/models/OK3/_tree.pyx":304 * * cpdef build(self, Tree tree, object X, np.ndarray y, * np.ndarray sample_weight=None): # <<<<<<<<<<<<<< @@ -8717,7 +8337,7 @@ static PyObject *__pyx_pw_5_tree_20BestFirstTreeBuilder_3build(PyObject *__pyx_v default: goto __pyx_L5_argtuple_error; } } - __pyx_v_tree = ((struct __pyx_obj_5_tree_Tree *)values[0]); + __pyx_v_tree = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)values[0]); __pyx_v_X = values[1]; __pyx_v_y = ((PyArrayObject *)values[2]); __pyx_v_sample_weight = ((PyArrayObject *)values[3]); @@ -8726,16 +8346,16 @@ static PyObject *__pyx_pw_5_tree_20BestFirstTreeBuilder_3build(PyObject *__pyx_v __pyx_L5_argtuple_error:; __Pyx_RaiseArgtupleInvalid("build", 0, 3, 4, PyTuple_GET_SIZE(__pyx_args)); __PYX_ERR(0, 303, __pyx_L3_error) __pyx_L3_error:; - __Pyx_AddTraceback("_tree.BestFirstTreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.BestFirstTreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_tree), __pyx_ptype_5_tree_Tree, 1, "tree", 0))) __PYX_ERR(0, 303, __pyx_L1_error) + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_tree), __pyx_ptype_13stpredictions_6models_3OK3_5_tree_Tree, 1, "tree", 0))) __PYX_ERR(0, 303, __pyx_L1_error) if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_y), __pyx_ptype_5numpy_ndarray, 1, "y", 0))) __PYX_ERR(0, 303, __pyx_L1_error) if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_sample_weight), __pyx_ptype_5numpy_ndarray, 1, "sample_weight", 0))) __PYX_ERR(0, 304, __pyx_L1_error) - __pyx_r = __pyx_pf_5_tree_20BestFirstTreeBuilder_2build(((struct __pyx_obj_5_tree_BestFirstTreeBuilder *)__pyx_v_self), __pyx_v_tree, __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_2build(((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *)__pyx_v_self), __pyx_v_tree, __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight); - /* "_tree.pyx":303 + /* "stpredictions/models/OK3/_tree.pyx":303 * self.min_impurity_split = min_impurity_split * * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< @@ -8752,11 +8372,11 @@ static PyObject *__pyx_pw_5_tree_20BestFirstTreeBuilder_3build(PyObject *__pyx_v return __pyx_r; } -static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, PyObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; - struct __pyx_opt_args_5_tree_11TreeBuilder_build __pyx_t_2; + struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build __pyx_t_2; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -8764,7 +8384,7 @@ static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_ __Pyx_XDECREF(__pyx_r); __pyx_t_2.__pyx_n = 1; __pyx_t_2.sample_weight = __pyx_v_sample_weight; - __pyx_t_1 = __pyx_vtabptr_5_tree_BestFirstTreeBuilder->__pyx_base.build(((struct __pyx_obj_5_tree_TreeBuilder *)__pyx_v_self), __pyx_v_tree, __pyx_v_X, __pyx_v_y, 1, &__pyx_t_2); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 303, __pyx_L1_error) + __pyx_t_1 = __pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder->__pyx_base.build(((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *)__pyx_v_self), __pyx_v_tree, __pyx_v_X, __pyx_v_y, 1, &__pyx_t_2); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 303, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; @@ -8773,7 +8393,7 @@ static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_ /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_1); - __Pyx_AddTraceback("_tree.BestFirstTreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.BestFirstTreeBuilder.build", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __Pyx_XGIVEREF(__pyx_r); @@ -8781,7 +8401,7 @@ static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_ return __pyx_r; } -/* "_tree.pyx":424 +/* "stpredictions/models/OK3/_tree.pyx":424 * * * cdef inline int _add_split_node(self, Splitter splitter, Tree tree, # <<<<<<<<<<<<<< @@ -8789,11 +8409,11 @@ static PyObject *__pyx_pf_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_ * bint is_first, bint is_left, Node* parent, */ -static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_9_splitter_Splitter *__pyx_v_splitter, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, __pyx_t_5_tree_SIZE_t __pyx_v_start, __pyx_t_5_tree_SIZE_t __pyx_v_end, double __pyx_v_impurity, int __pyx_v_is_first, int __pyx_v_is_left, struct __pyx_t_5_tree_Node *__pyx_v_parent, __pyx_t_5_tree_SIZE_t __pyx_v_depth, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *__pyx_v_res, __pyx_t_5_tree_SIZE_t __pyx_v_n_samples) { - struct __pyx_t_9_splitter_SplitRecord __pyx_v_split; - __pyx_t_5_tree_SIZE_t __pyx_v_node_id; - __pyx_t_5_tree_SIZE_t __pyx_v_n_node_samples; - __pyx_t_5_tree_SIZE_t __pyx_v_n_constant_features; +static CYTHON_INLINE int __pyx_f_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_v_splitter, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_end, double __pyx_v_impurity, int __pyx_v_is_first, int __pyx_v_is_left, struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_parent, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_depth, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *__pyx_v_res, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_samples) { + struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord __pyx_v_split; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_node_id; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_constant_features; CYTHON_UNUSED double __pyx_v_weighted_n_samples; double __pyx_v_min_impurity_decrease; double __pyx_v_min_impurity_split; @@ -8805,13 +8425,12 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s int __pyx_t_3; int __pyx_t_4; ptrdiff_t __pyx_t_5; - __pyx_t_5_tree_SIZE_t __pyx_t_6; - __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_6; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "_tree.pyx":434 + /* "stpredictions/models/OK3/_tree.pyx":434 * cdef SIZE_t node_id * cdef SIZE_t n_node_samples * cdef SIZE_t n_constant_features = 0 # <<<<<<<<<<<<<< @@ -8820,7 +8439,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ __pyx_v_n_constant_features = 0; - /* "_tree.pyx":435 + /* "stpredictions/models/OK3/_tree.pyx":435 * cdef SIZE_t n_node_samples * cdef SIZE_t n_constant_features = 0 * cdef double weighted_n_samples = splitter.weighted_n_samples # <<<<<<<<<<<<<< @@ -8830,7 +8449,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_1 = __pyx_v_splitter->weighted_n_samples; __pyx_v_weighted_n_samples = __pyx_t_1; - /* "_tree.pyx":436 + /* "stpredictions/models/OK3/_tree.pyx":436 * cdef SIZE_t n_constant_features = 0 * cdef double weighted_n_samples = splitter.weighted_n_samples * cdef double min_impurity_decrease = self.min_impurity_decrease # <<<<<<<<<<<<<< @@ -8840,7 +8459,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_1 = __pyx_v_self->__pyx_base.min_impurity_decrease; __pyx_v_min_impurity_decrease = __pyx_t_1; - /* "_tree.pyx":437 + /* "stpredictions/models/OK3/_tree.pyx":437 * cdef double weighted_n_samples = splitter.weighted_n_samples * cdef double min_impurity_decrease = self.min_impurity_decrease * cdef double min_impurity_split = self.min_impurity_split # <<<<<<<<<<<<<< @@ -8850,16 +8469,16 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_1 = __pyx_v_self->__pyx_base.min_impurity_split; __pyx_v_min_impurity_split = __pyx_t_1; - /* "_tree.pyx":443 + /* "stpredictions/models/OK3/_tree.pyx":443 * cdef double imp_diff * * splitter.node_reset(start, end, &weighted_n_node_samples) # <<<<<<<<<<<<<< * * if is_first: */ - __pyx_t_2 = ((struct __pyx_vtabstruct_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_reset(__pyx_v_splitter, __pyx_v_start, __pyx_v_end, (&__pyx_v_weighted_n_node_samples)); if (unlikely(__pyx_t_2 == ((int)-1))) __PYX_ERR(0, 443, __pyx_L1_error) + __pyx_t_2 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_reset(__pyx_v_splitter, __pyx_v_start, __pyx_v_end, (&__pyx_v_weighted_n_node_samples)); if (unlikely(__pyx_t_2 == ((int)-1))) __PYX_ERR(0, 443, __pyx_L1_error) - /* "_tree.pyx":445 + /* "stpredictions/models/OK3/_tree.pyx":445 * splitter.node_reset(start, end, &weighted_n_node_samples) * * if is_first: # <<<<<<<<<<<<<< @@ -8869,16 +8488,16 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_3 = (__pyx_v_is_first != 0); if (__pyx_t_3) { - /* "_tree.pyx":446 + /* "stpredictions/models/OK3/_tree.pyx":446 * * if is_first: * impurity = splitter.node_impurity() # <<<<<<<<<<<<<< * * n_node_samples = end - start */ - __pyx_v_impurity = ((struct __pyx_vtabstruct_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_impurity(__pyx_v_splitter); + __pyx_v_impurity = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_impurity(__pyx_v_splitter); - /* "_tree.pyx":445 + /* "stpredictions/models/OK3/_tree.pyx":445 * splitter.node_reset(start, end, &weighted_n_node_samples) * * if is_first: # <<<<<<<<<<<<<< @@ -8887,7 +8506,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ } - /* "_tree.pyx":448 + /* "stpredictions/models/OK3/_tree.pyx":448 * impurity = splitter.node_impurity() * * n_node_samples = end - start # <<<<<<<<<<<<<< @@ -8896,7 +8515,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ __pyx_v_n_node_samples = (__pyx_v_end - __pyx_v_start); - /* "_tree.pyx":449 + /* "stpredictions/models/OK3/_tree.pyx":449 * * n_node_samples = end - start * is_leaf = (depth >= self.max_depth or # <<<<<<<<<<<<<< @@ -8910,7 +8529,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s goto __pyx_L4_bool_binop_done; } - /* "_tree.pyx":450 + /* "stpredictions/models/OK3/_tree.pyx":450 * n_node_samples = end - start * is_leaf = (depth >= self.max_depth or * n_node_samples < self.min_samples_split or # <<<<<<<<<<<<<< @@ -8924,7 +8543,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s goto __pyx_L4_bool_binop_done; } - /* "_tree.pyx":451 + /* "stpredictions/models/OK3/_tree.pyx":451 * is_leaf = (depth >= self.max_depth or * n_node_samples < self.min_samples_split or * n_node_samples < 2 * self.min_samples_leaf or # <<<<<<<<<<<<<< @@ -8938,7 +8557,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s goto __pyx_L4_bool_binop_done; } - /* "_tree.pyx":452 + /* "stpredictions/models/OK3/_tree.pyx":452 * n_node_samples < self.min_samples_split or * n_node_samples < 2 * self.min_samples_leaf or * weighted_n_node_samples < 2 * self.min_weight_leaf or # <<<<<<<<<<<<<< @@ -8952,7 +8571,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s goto __pyx_L4_bool_binop_done; } - /* "_tree.pyx":453 + /* "stpredictions/models/OK3/_tree.pyx":453 * n_node_samples < 2 * self.min_samples_leaf or * weighted_n_node_samples < 2 * self.min_weight_leaf or * impurity <= min_impurity_split) # <<<<<<<<<<<<<< @@ -8964,7 +8583,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_L4_bool_binop_done:; __pyx_v_is_leaf = __pyx_t_3; - /* "_tree.pyx":455 + /* "stpredictions/models/OK3/_tree.pyx":455 * impurity <= min_impurity_split) * * if not is_leaf: # <<<<<<<<<<<<<< @@ -8974,16 +8593,16 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_3 = ((!(__pyx_v_is_leaf != 0)) != 0); if (__pyx_t_3) { - /* "_tree.pyx":456 + /* "stpredictions/models/OK3/_tree.pyx":456 * * if not is_leaf: * splitter.node_split(impurity, &split, &n_constant_features) # <<<<<<<<<<<<<< * # If EPSILON=0 in the below comparison, float precision issues stop * # splitting early, producing trees that are dissimilar to v0.18 */ - __pyx_t_2 = ((struct __pyx_vtabstruct_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_split(__pyx_v_splitter, __pyx_v_impurity, (&__pyx_v_split), (&__pyx_v_n_constant_features)); if (unlikely(__pyx_t_2 == ((int)-1))) __PYX_ERR(0, 456, __pyx_L1_error) + __pyx_t_2 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_split(__pyx_v_splitter, __pyx_v_impurity, (&__pyx_v_split), (&__pyx_v_n_constant_features)); if (unlikely(__pyx_t_2 == ((int)-1))) __PYX_ERR(0, 456, __pyx_L1_error) - /* "_tree.pyx":459 + /* "stpredictions/models/OK3/_tree.pyx":459 * # If EPSILON=0 in the below comparison, float precision issues stop * # splitting early, producing trees that are dissimilar to v0.18 * is_leaf = (is_leaf or split.pos >= end or # <<<<<<<<<<<<<< @@ -9003,19 +8622,19 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s goto __pyx_L10_bool_binop_done; } - /* "_tree.pyx":460 + /* "stpredictions/models/OK3/_tree.pyx":460 * # splitting early, producing trees that are dissimilar to v0.18 * is_leaf = (is_leaf or split.pos >= end or * split.improvement + EPSILON < min_impurity_decrease) # <<<<<<<<<<<<<< * * node_id = tree._add_node(parent - tree.nodes */ - __pyx_t_4 = (((__pyx_v_split.improvement + __pyx_v_5_tree_EPSILON) < __pyx_v_min_impurity_decrease) != 0); + __pyx_t_4 = (((__pyx_v_split.improvement + __pyx_v_13stpredictions_6models_3OK3_5_tree_EPSILON) < __pyx_v_min_impurity_decrease) != 0); __pyx_t_3 = __pyx_t_4; __pyx_L10_bool_binop_done:; __pyx_v_is_leaf = __pyx_t_3; - /* "_tree.pyx":455 + /* "stpredictions/models/OK3/_tree.pyx":455 * impurity <= min_impurity_split) * * if not is_leaf: # <<<<<<<<<<<<<< @@ -9024,7 +8643,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ } - /* "_tree.pyx":463 + /* "stpredictions/models/OK3/_tree.pyx":463 * * node_id = tree._add_node(parent - tree.nodes * if parent != NULL # <<<<<<<<<<<<<< @@ -9033,7 +8652,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ if (((__pyx_v_parent != NULL) != 0)) { - /* "_tree.pyx":462 + /* "stpredictions/models/OK3/_tree.pyx":462 * split.improvement + EPSILON < min_impurity_decrease) * * node_id = tree._add_node(parent - tree.nodes # <<<<<<<<<<<<<< @@ -9043,27 +8662,27 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_5 = (__pyx_v_parent - __pyx_v_tree->nodes); } else { - /* "_tree.pyx":464 + /* "stpredictions/models/OK3/_tree.pyx":464 * node_id = tree._add_node(parent - tree.nodes * if parent != NULL * else _TREE_UNDEFINED, # <<<<<<<<<<<<<< * is_left, is_leaf, * split.feature, split.threshold, impurity, n_node_samples, */ - __pyx_t_5 = __pyx_v_5_tree__TREE_UNDEFINED; + __pyx_t_5 = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED; } - /* "_tree.pyx":462 + /* "stpredictions/models/OK3/_tree.pyx":462 * split.improvement + EPSILON < min_impurity_decrease) * * node_id = tree._add_node(parent - tree.nodes # <<<<<<<<<<<<<< * if parent != NULL * else _TREE_UNDEFINED, */ - __pyx_t_6 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_add_node(__pyx_v_tree, __pyx_t_5, __pyx_v_is_left, __pyx_v_is_leaf, __pyx_v_split.feature, __pyx_v_split.threshold, __pyx_v_impurity, __pyx_v_n_node_samples, __pyx_v_weighted_n_node_samples); if (unlikely(__pyx_t_6 == ((__pyx_t_5_tree_SIZE_t)-1))) __PYX_ERR(0, 462, __pyx_L1_error) + __pyx_t_6 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_add_node(__pyx_v_tree, __pyx_t_5, __pyx_v_is_left, __pyx_v_is_leaf, __pyx_v_split.feature, __pyx_v_split.threshold, __pyx_v_impurity, __pyx_v_n_node_samples, __pyx_v_weighted_n_node_samples); if (unlikely(__pyx_t_6 == ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)-1))) __PYX_ERR(0, 462, __pyx_L1_error) __pyx_v_node_id = __pyx_t_6; - /* "_tree.pyx":468 + /* "stpredictions/models/OK3/_tree.pyx":468 * split.feature, split.threshold, impurity, n_node_samples, * weighted_n_node_samples) * if node_id == SIZE_MAX: # <<<<<<<<<<<<<< @@ -9073,7 +8692,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_3 = ((__pyx_v_node_id == SIZE_MAX) != 0); if (__pyx_t_3) { - /* "_tree.pyx":469 + /* "stpredictions/models/OK3/_tree.pyx":469 * weighted_n_node_samples) * if node_id == SIZE_MAX: * return -1 # <<<<<<<<<<<<<< @@ -9083,7 +8702,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_r = -1; goto __pyx_L0; - /* "_tree.pyx":468 + /* "stpredictions/models/OK3/_tree.pyx":468 * split.feature, split.threshold, impurity, n_node_samples, * weighted_n_node_samples) * if node_id == SIZE_MAX: # <<<<<<<<<<<<<< @@ -9092,16 +8711,16 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ } - /* "_tree.pyx":472 + /* "stpredictions/models/OK3/_tree.pyx":472 * * # compute values also for split nodes (might become leafs later). * splitter.node_value(tree.value + node_id * n_samples) # <<<<<<<<<<<<<< * * res.node_id = node_id */ - ((struct __pyx_vtabstruct_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_value(__pyx_v_splitter, (__pyx_v_tree->value + (__pyx_v_node_id * __pyx_v_n_samples))); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_value(__pyx_v_splitter, (__pyx_v_tree->value + (__pyx_v_node_id * __pyx_v_n_samples))); - /* "_tree.pyx":474 + /* "stpredictions/models/OK3/_tree.pyx":474 * splitter.node_value(tree.value + node_id * n_samples) * * res.node_id = node_id # <<<<<<<<<<<<<< @@ -9110,7 +8729,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ __pyx_v_res->node_id = __pyx_v_node_id; - /* "_tree.pyx":475 + /* "stpredictions/models/OK3/_tree.pyx":475 * * res.node_id = node_id * res.start = start # <<<<<<<<<<<<<< @@ -9119,7 +8738,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ __pyx_v_res->start = __pyx_v_start; - /* "_tree.pyx":476 + /* "stpredictions/models/OK3/_tree.pyx":476 * res.node_id = node_id * res.start = start * res.end = end # <<<<<<<<<<<<<< @@ -9128,7 +8747,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ __pyx_v_res->end = __pyx_v_end; - /* "_tree.pyx":477 + /* "stpredictions/models/OK3/_tree.pyx":477 * res.start = start * res.end = end * res.depth = depth # <<<<<<<<<<<<<< @@ -9137,7 +8756,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ __pyx_v_res->depth = __pyx_v_depth; - /* "_tree.pyx":478 + /* "stpredictions/models/OK3/_tree.pyx":478 * res.end = end * res.depth = depth * res.impurity = impurity # <<<<<<<<<<<<<< @@ -9146,7 +8765,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ __pyx_v_res->impurity = __pyx_v_impurity; - /* "_tree.pyx":480 + /* "stpredictions/models/OK3/_tree.pyx":480 * res.impurity = impurity * * if not is_leaf: # <<<<<<<<<<<<<< @@ -9156,17 +8775,17 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_3 = ((!(__pyx_v_is_leaf != 0)) != 0); if (__pyx_t_3) { - /* "_tree.pyx":482 + /* "stpredictions/models/OK3/_tree.pyx":482 * if not is_leaf: * # is split node * res.pos = split.pos # <<<<<<<<<<<<<< * res.is_leaf = 0 * res.improvement = split.improvement */ - __pyx_t_7 = __pyx_v_split.pos; - __pyx_v_res->pos = __pyx_t_7; + __pyx_t_6 = __pyx_v_split.pos; + __pyx_v_res->pos = __pyx_t_6; - /* "_tree.pyx":483 + /* "stpredictions/models/OK3/_tree.pyx":483 * # is split node * res.pos = split.pos * res.is_leaf = 0 # <<<<<<<<<<<<<< @@ -9175,7 +8794,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ __pyx_v_res->is_leaf = 0; - /* "_tree.pyx":484 + /* "stpredictions/models/OK3/_tree.pyx":484 * res.pos = split.pos * res.is_leaf = 0 * res.improvement = split.improvement # <<<<<<<<<<<<<< @@ -9185,7 +8804,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_1 = __pyx_v_split.improvement; __pyx_v_res->improvement = __pyx_t_1; - /* "_tree.pyx":485 + /* "stpredictions/models/OK3/_tree.pyx":485 * res.is_leaf = 0 * res.improvement = split.improvement * res.impurity_left = split.impurity_left # <<<<<<<<<<<<<< @@ -9195,7 +8814,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_1 = __pyx_v_split.impurity_left; __pyx_v_res->impurity_left = __pyx_t_1; - /* "_tree.pyx":486 + /* "stpredictions/models/OK3/_tree.pyx":486 * res.improvement = split.improvement * res.impurity_left = split.impurity_left * res.impurity_right = split.impurity_right # <<<<<<<<<<<<<< @@ -9205,7 +8824,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s __pyx_t_1 = __pyx_v_split.impurity_right; __pyx_v_res->impurity_right = __pyx_t_1; - /* "_tree.pyx":480 + /* "stpredictions/models/OK3/_tree.pyx":480 * res.impurity = impurity * * if not is_leaf: # <<<<<<<<<<<<<< @@ -9215,7 +8834,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s goto __pyx_L14; } - /* "_tree.pyx":490 + /* "stpredictions/models/OK3/_tree.pyx":490 * else: * # is leaf => 0 improvement * res.pos = end # <<<<<<<<<<<<<< @@ -9225,7 +8844,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s /*else*/ { __pyx_v_res->pos = __pyx_v_end; - /* "_tree.pyx":491 + /* "stpredictions/models/OK3/_tree.pyx":491 * # is leaf => 0 improvement * res.pos = end * res.is_leaf = 1 # <<<<<<<<<<<<<< @@ -9234,7 +8853,7 @@ static CYTHON_INLINE int __pyx_f_5_tree_20BestFirstTreeBuilder__add_split_node(s */ __pyx_v_res->is_leaf = 1; 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} - /* "_tree.pyx":660 + /* "stpredictions/models/OK3/_tree.pyx":660 * if (node_ndarray.ndim != 1 or * node_ndarray.dtype != NODE_DTYPE or * not node_ndarray.flags.c_contiguous or # <<<<<<<<<<<<<< @@ -10924,7 +10543,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre goto __pyx_L5_bool_binop_done; } - /* "_tree.pyx":661 + /* "stpredictions/models/OK3/_tree.pyx":661 * node_ndarray.dtype != NODE_DTYPE or * not node_ndarray.flags.c_contiguous or * value_ndarray.shape != value_shape or # <<<<<<<<<<<<<< @@ -10943,7 +10562,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre goto __pyx_L5_bool_binop_done; } - /* "_tree.pyx":662 + /* "stpredictions/models/OK3/_tree.pyx":662 * not node_ndarray.flags.c_contiguous or * value_ndarray.shape != value_shape or * not value_ndarray.flags.c_contiguous or # <<<<<<<<<<<<<< @@ -10964,7 +10583,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre goto __pyx_L5_bool_binop_done; } - /* "_tree.pyx":663 + /* "stpredictions/models/OK3/_tree.pyx":663 * value_ndarray.shape != value_shape or * not value_ndarray.flags.c_contiguous or * value_ndarray.dtype != np.float64): # <<<<<<<<<<<<<< @@ -10986,7 +10605,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre __pyx_t_4 = __pyx_t_3; __pyx_L5_bool_binop_done:; - /* "_tree.pyx":658 + /* "stpredictions/models/OK3/_tree.pyx":658 * * value_shape = (node_ndarray.shape[0], self.K_y.shape[0]) * if (node_ndarray.ndim != 1 or # <<<<<<<<<<<<<< @@ -10995,7 +10614,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre */ if (unlikely(__pyx_t_4)) { - /* "_tree.pyx":664 + /* "stpredictions/models/OK3/_tree.pyx":664 * not value_ndarray.flags.c_contiguous or * value_ndarray.dtype != np.float64): * raise ValueError('Did not recognise loaded array layout') # <<<<<<<<<<<<<< @@ -11008,7 +10627,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __PYX_ERR(0, 664, __pyx_L1_error) - /* "_tree.pyx":658 + /* "stpredictions/models/OK3/_tree.pyx":658 * * value_shape = (node_ndarray.shape[0], self.K_y.shape[0]) * if (node_ndarray.ndim != 1 or # <<<<<<<<<<<<<< @@ -11017,7 +10636,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre */ } - /* "_tree.pyx":666 + /* "stpredictions/models/OK3/_tree.pyx":666 * raise ValueError('Did not recognise loaded array layout') * * self.capacity = node_ndarray.shape[0] # <<<<<<<<<<<<<< @@ -11033,7 +10652,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_self->capacity = __pyx_t_2; - /* "_tree.pyx":667 + /* "stpredictions/models/OK3/_tree.pyx":667 * * self.capacity = node_ndarray.shape[0] * if self._resize_c(self.capacity) != 0: # <<<<<<<<<<<<<< @@ -11042,11 +10661,11 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre */ __pyx_t_9.__pyx_n = 1; __pyx_t_9.capacity = __pyx_v_self->capacity; - __pyx_t_8 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_resize_c(__pyx_v_self, &__pyx_t_9); if (unlikely(__pyx_t_8 == ((int)-1))) __PYX_ERR(0, 667, __pyx_L1_error) + __pyx_t_8 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_resize_c(__pyx_v_self, &__pyx_t_9); if (unlikely(__pyx_t_8 == ((int)-1))) __PYX_ERR(0, 667, __pyx_L1_error) __pyx_t_4 = ((__pyx_t_8 != 0) != 0); if (unlikely(__pyx_t_4)) { - /* "_tree.pyx":668 + /* "stpredictions/models/OK3/_tree.pyx":668 * self.capacity = node_ndarray.shape[0] * if self._resize_c(self.capacity) != 0: * raise MemoryError("resizing tree to %d" % self.capacity) # <<<<<<<<<<<<<< @@ -11065,7 +10684,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __PYX_ERR(0, 668, __pyx_L1_error) - /* "_tree.pyx":667 + /* "stpredictions/models/OK3/_tree.pyx":667 * * self.capacity = node_ndarray.shape[0] * if self._resize_c(self.capacity) != 0: # <<<<<<<<<<<<<< @@ -11074,16 +10693,16 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre */ } - /* "_tree.pyx":669 + /* "stpredictions/models/OK3/_tree.pyx":669 * if self._resize_c(self.capacity) != 0: * raise MemoryError("resizing tree to %d" % self.capacity) * nodes = memcpy(self.nodes, ( node_ndarray).data, # <<<<<<<<<<<<<< * self.capacity * sizeof(Node)) * value = memcpy(self.value, ( value_ndarray).data, */ - __pyx_v_nodes = memcpy(__pyx_v_self->nodes, ((PyArrayObject *)__pyx_v_node_ndarray)->data, (__pyx_v_self->capacity * (sizeof(struct __pyx_t_5_tree_Node)))); + __pyx_v_nodes = memcpy(__pyx_v_self->nodes, ((PyArrayObject *)__pyx_v_node_ndarray)->data, (__pyx_v_self->capacity * (sizeof(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node)))); - /* "_tree.pyx":671 + /* "stpredictions/models/OK3/_tree.pyx":671 * nodes = memcpy(self.nodes, ( node_ndarray).data, * self.capacity * sizeof(Node)) * value = memcpy(self.value, ( value_ndarray).data, # <<<<<<<<<<<<<< @@ -11092,7 +10711,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre */ __pyx_v_value = memcpy(__pyx_v_self->value, ((PyArrayObject *)__pyx_v_value_ndarray)->data, ((__pyx_v_self->capacity * (__pyx_v_self->K_y->dimensions[0])) * (sizeof(double)))); - /* "_tree.pyx":643 + /* "stpredictions/models/OK3/_tree.pyx":643 * return d * * def __setstate__(self, d): # <<<<<<<<<<<<<< @@ -11107,7 +10726,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre __Pyx_XDECREF(__pyx_t_1); __Pyx_XDECREF(__pyx_t_5); __Pyx_XDECREF(__pyx_t_6); - __Pyx_AddTraceback("_tree.Tree.__setstate__", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree.__setstate__", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __Pyx_XDECREF(__pyx_v_node_ndarray); @@ -11118,7 +10737,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre return __pyx_r; } -/* "_tree.pyx":674 +/* "stpredictions/models/OK3/_tree.pyx":674 * self.capacity * self.K_y.shape[0] * sizeof(double)) * * cdef int _resize(self, SIZE_t capacity) nogil except -1: # <<<<<<<<<<<<<< @@ -11126,11 +10745,11 @@ static PyObject *__pyx_pf_5_tree_4Tree_8__setstate__(struct __pyx_obj_5_tree_Tre * double the size of the inner arrays. */ -static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_self, __pyx_t_5_tree_SIZE_t __pyx_v_capacity) { +static int __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__resize(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_capacity) { int __pyx_r; __Pyx_RefNannyDeclarations int __pyx_t_1; - struct __pyx_opt_args_5_tree_4Tree__resize_c __pyx_t_2; + struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c __pyx_t_2; int __pyx_t_3; int __pyx_lineno = 0; const char *__pyx_filename = NULL; @@ -11143,7 +10762,7 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif - /* "_tree.pyx":675 + /* "stpredictions/models/OK3/_tree.pyx":675 * * cdef int _resize(self, SIZE_t capacity) nogil except -1: * """Resize all inner arrays to `capacity`, if `capacity` == -1, then # <<<<<<<<<<<<<< @@ -11152,7 +10771,7 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se */ /*try:*/ { - /* "_tree.pyx":681 + /* "stpredictions/models/OK3/_tree.pyx":681 * or 0 otherwise. * """ * if self._resize_c(capacity) != 0: # <<<<<<<<<<<<<< @@ -11161,11 +10780,11 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se */ __pyx_t_2.__pyx_n = 1; __pyx_t_2.capacity = __pyx_v_capacity; - __pyx_t_1 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_resize_c(__pyx_v_self, &__pyx_t_2); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 681, __pyx_L4_error) + __pyx_t_1 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_resize_c(__pyx_v_self, &__pyx_t_2); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 681, __pyx_L4_error) __pyx_t_3 = ((__pyx_t_1 != 0) != 0); if (__pyx_t_3) { - /* "_tree.pyx":683 + /* "stpredictions/models/OK3/_tree.pyx":683 * if self._resize_c(capacity) != 0: * # Acquire gil only if we need to raise * with gil: # <<<<<<<<<<<<<< @@ -11178,7 +10797,7 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se #endif /*try:*/ { - /* "_tree.pyx":684 + /* "stpredictions/models/OK3/_tree.pyx":684 * # Acquire gil only if we need to raise * with gil: * raise MemoryError() # <<<<<<<<<<<<<< @@ -11188,7 +10807,7 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se PyErr_NoMemory(); __PYX_ERR(0, 684, __pyx_L8_error) } - /* "_tree.pyx":683 + /* "stpredictions/models/OK3/_tree.pyx":683 * if self._resize_c(capacity) != 0: * # Acquire gil only if we need to raise * with gil: # <<<<<<<<<<<<<< @@ -11205,7 +10824,7 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se } } - /* "_tree.pyx":681 + /* "stpredictions/models/OK3/_tree.pyx":681 * or 0 otherwise. * """ * if self._resize_c(capacity) != 0: # <<<<<<<<<<<<<< @@ -11215,7 +10834,7 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se } } - /* "_tree.pyx":675 + /* "stpredictions/models/OK3/_tree.pyx":675 * * cdef int _resize(self, SIZE_t capacity) nogil except -1: * """Resize all inner arrays to `capacity`, if `capacity` == -1, then # <<<<<<<<<<<<<< @@ -11238,7 +10857,7 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se __pyx_L5:; } - /* "_tree.pyx":674 + /* "stpredictions/models/OK3/_tree.pyx":674 * self.capacity * self.K_y.shape[0] * sizeof(double)) * * cdef int _resize(self, SIZE_t capacity) nogil except -1: # <<<<<<<<<<<<<< @@ -11250,7 +10869,7 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se __pyx_r = 0; goto __pyx_L0; __pyx_L1_error:; - __Pyx_AddTraceback("_tree.Tree._resize", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree._resize", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = -1; __pyx_L0:; #ifdef WITH_THREAD @@ -11259,7 +10878,7 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se return __pyx_r; } -/* "_tree.pyx":686 +/* "stpredictions/models/OK3/_tree.pyx":686 * raise MemoryError() * * cdef int _resize_c(self, SIZE_t capacity=SIZE_MAX) nogil except -1: # <<<<<<<<<<<<<< @@ -11267,8 +10886,8 @@ static int __pyx_f_5_tree_4Tree__resize(struct __pyx_obj_5_tree_Tree *__pyx_v_se * */ -static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_self, struct __pyx_opt_args_5_tree_4Tree__resize_c *__pyx_optional_args) { - __pyx_t_5_tree_SIZE_t __pyx_v_capacity = __pyx_k__8; +static int __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c *__pyx_optional_args) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_capacity = __pyx_k__8; int __pyx_r; int __pyx_t_1; int __pyx_t_2; @@ -11281,7 +10900,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ } } - /* "_tree.pyx":692 + /* "stpredictions/models/OK3/_tree.pyx":692 * or 0 otherwise. * """ * if capacity == self.capacity and self.nodes != NULL: # <<<<<<<<<<<<<< @@ -11299,7 +10918,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ __pyx_L4_bool_binop_done:; if (__pyx_t_1) { - /* "_tree.pyx":693 + /* "stpredictions/models/OK3/_tree.pyx":693 * """ * if capacity == self.capacity and self.nodes != NULL: * return 0 # <<<<<<<<<<<<<< @@ -11309,7 +10928,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ __pyx_r = 0; goto __pyx_L0; - /* "_tree.pyx":692 + /* "stpredictions/models/OK3/_tree.pyx":692 * or 0 otherwise. * """ * if capacity == self.capacity and self.nodes != NULL: # <<<<<<<<<<<<<< @@ -11318,7 +10937,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ */ } - /* "_tree.pyx":695 + /* "stpredictions/models/OK3/_tree.pyx":695 * return 0 * * if capacity == SIZE_MAX: # <<<<<<<<<<<<<< @@ -11328,7 +10947,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ __pyx_t_1 = ((__pyx_v_capacity == SIZE_MAX) != 0); if (__pyx_t_1) { - /* "_tree.pyx":696 + /* "stpredictions/models/OK3/_tree.pyx":696 * * if capacity == SIZE_MAX: * if self.capacity == 0: # <<<<<<<<<<<<<< @@ -11338,7 +10957,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ __pyx_t_1 = ((__pyx_v_self->capacity == 0) != 0); if (__pyx_t_1) { - /* "_tree.pyx":697 + /* "stpredictions/models/OK3/_tree.pyx":697 * if capacity == SIZE_MAX: * if self.capacity == 0: * capacity = 3 # default initial value # <<<<<<<<<<<<<< @@ -11347,7 +10966,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ */ __pyx_v_capacity = 3; - /* "_tree.pyx":696 + /* "stpredictions/models/OK3/_tree.pyx":696 * * if capacity == SIZE_MAX: * if self.capacity == 0: # <<<<<<<<<<<<<< @@ -11357,7 +10976,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ goto __pyx_L7; } - /* "_tree.pyx":699 + /* "stpredictions/models/OK3/_tree.pyx":699 * capacity = 3 # default initial value * else: * capacity = 2 * self.capacity # <<<<<<<<<<<<<< @@ -11369,7 +10988,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ } __pyx_L7:; - /* "_tree.pyx":695 + /* "stpredictions/models/OK3/_tree.pyx":695 * return 0 * * if capacity == SIZE_MAX: # <<<<<<<<<<<<<< @@ -11378,25 +10997,25 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ */ } - /* "_tree.pyx":701 + /* "stpredictions/models/OK3/_tree.pyx":701 * capacity = 2 * self.capacity * * safe_realloc(&self.nodes, capacity) # <<<<<<<<<<<<<< * safe_realloc(&self.value, capacity * self.K_y.shape[0]) * */ - __pyx_fuse_6__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->nodes), __pyx_v_capacity); if (unlikely(__Pyx_ErrOccurredWithGIL())) __PYX_ERR(0, 701, __pyx_L1_error) + __pyx_fuse_6__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_self->nodes), __pyx_v_capacity); if (unlikely(__Pyx_ErrOccurredWithGIL())) __PYX_ERR(0, 701, __pyx_L1_error) - /* "_tree.pyx":702 + /* "stpredictions/models/OK3/_tree.pyx":702 * * safe_realloc(&self.nodes, capacity) * safe_realloc(&self.value, capacity * self.K_y.shape[0]) # <<<<<<<<<<<<<< * * # value memory is initialised to 0 to enable classifier argmax */ - __pyx_fuse_4__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_self->value), (__pyx_v_capacity * (__pyx_v_self->K_y->dimensions[0]))); if (unlikely(__Pyx_ErrOccurredWithGIL())) __PYX_ERR(0, 702, __pyx_L1_error) + __pyx_fuse_4__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_self->value), (__pyx_v_capacity * (__pyx_v_self->K_y->dimensions[0]))); if (unlikely(__Pyx_ErrOccurredWithGIL())) __PYX_ERR(0, 702, __pyx_L1_error) - /* "_tree.pyx":705 + /* "stpredictions/models/OK3/_tree.pyx":705 * * # value memory is initialised to 0 to enable classifier argmax * if capacity > self.capacity: # <<<<<<<<<<<<<< @@ -11406,7 +11025,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ __pyx_t_1 = ((__pyx_v_capacity > __pyx_v_self->capacity) != 0); if (__pyx_t_1) { - /* "_tree.pyx":706 + /* "stpredictions/models/OK3/_tree.pyx":706 * # value memory is initialised to 0 to enable classifier argmax * if capacity > self.capacity: * memset((self.value + self.capacity * self.K_y.shape[0]), 0, # <<<<<<<<<<<<<< @@ -11415,7 +11034,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ */ (void)(memset(((void *)(__pyx_v_self->value + (__pyx_v_self->capacity * (__pyx_v_self->K_y->dimensions[0])))), 0, (((__pyx_v_capacity - __pyx_v_self->capacity) * (__pyx_v_self->K_y->dimensions[0])) * (sizeof(double))))); - /* "_tree.pyx":705 + /* "stpredictions/models/OK3/_tree.pyx":705 * * # value memory is initialised to 0 to enable classifier argmax * if capacity > self.capacity: # <<<<<<<<<<<<<< @@ -11424,7 +11043,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ */ } - /* "_tree.pyx":711 + /* "stpredictions/models/OK3/_tree.pyx":711 * * # if capacity smaller than node_count, adjust the counter * if capacity < self.node_count: # <<<<<<<<<<<<<< @@ -11434,7 +11053,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ __pyx_t_1 = ((__pyx_v_capacity < __pyx_v_self->node_count) != 0); if (__pyx_t_1) { - /* "_tree.pyx":712 + /* "stpredictions/models/OK3/_tree.pyx":712 * # if capacity smaller than node_count, adjust the counter * if capacity < self.node_count: * self.node_count = capacity # <<<<<<<<<<<<<< @@ -11443,7 +11062,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ */ __pyx_v_self->node_count = __pyx_v_capacity; - /* "_tree.pyx":711 + /* "stpredictions/models/OK3/_tree.pyx":711 * * # if capacity smaller than node_count, adjust the counter * if capacity < self.node_count: # <<<<<<<<<<<<<< @@ -11452,7 +11071,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ */ } - /* "_tree.pyx":714 + /* "stpredictions/models/OK3/_tree.pyx":714 * self.node_count = capacity * * self.capacity = capacity # <<<<<<<<<<<<<< @@ -11461,7 +11080,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ */ __pyx_v_self->capacity = __pyx_v_capacity; - /* "_tree.pyx":715 + /* "stpredictions/models/OK3/_tree.pyx":715 * * self.capacity = capacity * return 0 # <<<<<<<<<<<<<< @@ -11471,7 +11090,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ __pyx_r = 0; goto __pyx_L0; - /* "_tree.pyx":686 + /* "stpredictions/models/OK3/_tree.pyx":686 * raise MemoryError() * * cdef int _resize_c(self, SIZE_t capacity=SIZE_MAX) nogil except -1: # <<<<<<<<<<<<<< @@ -11485,7 +11104,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif - __Pyx_AddTraceback("_tree.Tree._resize_c", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree._resize_c", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif @@ -11495,7 +11114,7 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ return __pyx_r; } -/* "_tree.pyx":717 +/* "stpredictions/models/OK3/_tree.pyx":717 * return 0 * * cdef SIZE_t _add_node(self, SIZE_t parent, bint is_left, bint is_leaf, # <<<<<<<<<<<<<< @@ -11503,18 +11122,18 @@ static int __pyx_f_5_tree_4Tree__resize_c(struct __pyx_obj_5_tree_Tree *__pyx_v_ * SIZE_t n_node_samples, */ -static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_tree_Tree *__pyx_v_self, __pyx_t_5_tree_SIZE_t __pyx_v_parent, int __pyx_v_is_left, int __pyx_v_is_leaf, __pyx_t_5_tree_SIZE_t __pyx_v_feature, double __pyx_v_threshold, double __pyx_v_impurity, __pyx_t_5_tree_SIZE_t __pyx_v_n_node_samples, double __pyx_v_weighted_n_node_samples) { - __pyx_t_5_tree_SIZE_t __pyx_v_node_id; - struct __pyx_t_5_tree_Node *__pyx_v_node; - __pyx_t_5_tree_SIZE_t __pyx_r; - __pyx_t_5_tree_SIZE_t __pyx_t_1; +static __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__add_node(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_parent, int __pyx_v_is_left, int __pyx_v_is_leaf, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_feature, double __pyx_v_threshold, double __pyx_v_impurity, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_node_samples, double __pyx_v_weighted_n_node_samples) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_node_id; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_node; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_r; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_1; int __pyx_t_2; int __pyx_t_3; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; - /* "_tree.pyx":727 + /* "stpredictions/models/OK3/_tree.pyx":727 * Returns (size_t)(-1) on error. * """ * cdef SIZE_t node_id = self.node_count # <<<<<<<<<<<<<< @@ -11524,7 +11143,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t __pyx_t_1 = __pyx_v_self->node_count; __pyx_v_node_id = __pyx_t_1; - /* "_tree.pyx":729 + /* "stpredictions/models/OK3/_tree.pyx":729 * cdef SIZE_t node_id = self.node_count * * if node_id >= self.capacity: # <<<<<<<<<<<<<< @@ -11534,18 +11153,18 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t __pyx_t_2 = ((__pyx_v_node_id >= __pyx_v_self->capacity) != 0); if (__pyx_t_2) { - /* "_tree.pyx":730 + /* "stpredictions/models/OK3/_tree.pyx":730 * * if node_id >= self.capacity: * if self._resize_c() != 0: # <<<<<<<<<<<<<< * return SIZE_MAX * */ - __pyx_t_3 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_resize_c(__pyx_v_self, NULL); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(0, 730, __pyx_L1_error) + __pyx_t_3 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_resize_c(__pyx_v_self, NULL); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(0, 730, __pyx_L1_error) __pyx_t_2 = ((__pyx_t_3 != 0) != 0); if (__pyx_t_2) { - /* "_tree.pyx":731 + /* "stpredictions/models/OK3/_tree.pyx":731 * if node_id >= self.capacity: * if self._resize_c() != 0: * return SIZE_MAX # <<<<<<<<<<<<<< @@ -11555,7 +11174,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t __pyx_r = SIZE_MAX; goto __pyx_L0; - /* "_tree.pyx":730 + /* "stpredictions/models/OK3/_tree.pyx":730 * * if node_id >= self.capacity: * if self._resize_c() != 0: # <<<<<<<<<<<<<< @@ -11564,7 +11183,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t */ } - /* "_tree.pyx":729 + /* "stpredictions/models/OK3/_tree.pyx":729 * cdef SIZE_t node_id = self.node_count * * if node_id >= self.capacity: # <<<<<<<<<<<<<< @@ -11573,7 +11192,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t */ } - /* "_tree.pyx":733 + /* "stpredictions/models/OK3/_tree.pyx":733 * return SIZE_MAX * * cdef Node* node = &self.nodes[node_id] # <<<<<<<<<<<<<< @@ -11582,7 +11201,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t */ __pyx_v_node = (&(__pyx_v_self->nodes[__pyx_v_node_id])); - /* "_tree.pyx":734 + /* "stpredictions/models/OK3/_tree.pyx":734 * * cdef Node* node = &self.nodes[node_id] * node.impurity = impurity # <<<<<<<<<<<<<< @@ -11591,7 +11210,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t */ __pyx_v_node->impurity = __pyx_v_impurity; - /* "_tree.pyx":735 + /* "stpredictions/models/OK3/_tree.pyx":735 * cdef Node* node = &self.nodes[node_id] * node.impurity = impurity * node.n_node_samples = n_node_samples # <<<<<<<<<<<<<< @@ -11600,7 +11219,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t */ __pyx_v_node->n_node_samples = __pyx_v_n_node_samples; - /* "_tree.pyx":736 + /* "stpredictions/models/OK3/_tree.pyx":736 * node.impurity = impurity * node.n_node_samples = n_node_samples * node.weighted_n_node_samples = weighted_n_node_samples # <<<<<<<<<<<<<< @@ -11609,17 +11228,17 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t */ __pyx_v_node->weighted_n_node_samples = __pyx_v_weighted_n_node_samples; - /* "_tree.pyx":738 + /* "stpredictions/models/OK3/_tree.pyx":738 * node.weighted_n_node_samples = weighted_n_node_samples * * if parent != _TREE_UNDEFINED: # <<<<<<<<<<<<<< * if is_left: * self.nodes[parent].left_child = node_id */ - __pyx_t_2 = ((__pyx_v_parent != __pyx_v_5_tree__TREE_UNDEFINED) != 0); + __pyx_t_2 = ((__pyx_v_parent != __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED) != 0); if (__pyx_t_2) { - /* "_tree.pyx":739 + /* "stpredictions/models/OK3/_tree.pyx":739 * * if parent != _TREE_UNDEFINED: * if is_left: # <<<<<<<<<<<<<< @@ -11629,7 +11248,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t __pyx_t_2 = (__pyx_v_is_left != 0); if (__pyx_t_2) { - /* "_tree.pyx":740 + /* "stpredictions/models/OK3/_tree.pyx":740 * if parent != _TREE_UNDEFINED: * if is_left: * self.nodes[parent].left_child = node_id # <<<<<<<<<<<<<< @@ -11638,7 +11257,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t */ (__pyx_v_self->nodes[__pyx_v_parent]).left_child = __pyx_v_node_id; - /* "_tree.pyx":739 + /* "stpredictions/models/OK3/_tree.pyx":739 * * if parent != _TREE_UNDEFINED: * if is_left: # <<<<<<<<<<<<<< @@ -11648,7 +11267,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t goto __pyx_L6; } - /* "_tree.pyx":742 + /* "stpredictions/models/OK3/_tree.pyx":742 * self.nodes[parent].left_child = node_id * else: * self.nodes[parent].right_child = node_id # <<<<<<<<<<<<<< @@ -11660,7 +11279,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t } __pyx_L6:; - /* "_tree.pyx":738 + /* "stpredictions/models/OK3/_tree.pyx":738 * node.weighted_n_node_samples = weighted_n_node_samples * * if parent != _TREE_UNDEFINED: # <<<<<<<<<<<<<< @@ -11669,7 +11288,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t */ } - /* "_tree.pyx":744 + /* "stpredictions/models/OK3/_tree.pyx":744 * self.nodes[parent].right_child = node_id * * if is_leaf: # <<<<<<<<<<<<<< @@ -11679,43 +11298,43 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t __pyx_t_2 = (__pyx_v_is_leaf != 0); if (__pyx_t_2) { - /* "_tree.pyx":745 + /* "stpredictions/models/OK3/_tree.pyx":745 * * if is_leaf: * node.left_child = _TREE_LEAF # <<<<<<<<<<<<<< * node.right_child = _TREE_LEAF * node.feature = _TREE_UNDEFINED */ - __pyx_v_node->left_child = __pyx_v_5_tree__TREE_LEAF; + __pyx_v_node->left_child = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF; - /* "_tree.pyx":746 + /* "stpredictions/models/OK3/_tree.pyx":746 * if is_leaf: * node.left_child = _TREE_LEAF * node.right_child = _TREE_LEAF # <<<<<<<<<<<<<< * node.feature = _TREE_UNDEFINED * node.threshold = _TREE_UNDEFINED */ - __pyx_v_node->right_child = __pyx_v_5_tree__TREE_LEAF; + __pyx_v_node->right_child = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF; - /* "_tree.pyx":747 + /* "stpredictions/models/OK3/_tree.pyx":747 * node.left_child = _TREE_LEAF * node.right_child = _TREE_LEAF * node.feature = _TREE_UNDEFINED # <<<<<<<<<<<<<< * node.threshold = _TREE_UNDEFINED * */ - __pyx_v_node->feature = __pyx_v_5_tree__TREE_UNDEFINED; + __pyx_v_node->feature = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED; - /* "_tree.pyx":748 + /* "stpredictions/models/OK3/_tree.pyx":748 * node.right_child = _TREE_LEAF * node.feature = _TREE_UNDEFINED * node.threshold = _TREE_UNDEFINED # <<<<<<<<<<<<<< * * else: */ - __pyx_v_node->threshold = __pyx_v_5_tree__TREE_UNDEFINED; + __pyx_v_node->threshold = __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED; - /* "_tree.pyx":744 + /* "stpredictions/models/OK3/_tree.pyx":744 * self.nodes[parent].right_child = node_id * * if is_leaf: # <<<<<<<<<<<<<< @@ -11725,7 +11344,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t goto __pyx_L7; } - /* "_tree.pyx":752 + /* "stpredictions/models/OK3/_tree.pyx":752 * else: * # left_child and right_child will be set later * node.feature = feature # <<<<<<<<<<<<<< @@ -11735,7 +11354,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t /*else*/ { __pyx_v_node->feature = __pyx_v_feature; - /* "_tree.pyx":753 + /* "stpredictions/models/OK3/_tree.pyx":753 * # left_child and right_child will be set later * node.feature = feature * node.threshold = threshold # <<<<<<<<<<<<<< @@ -11746,7 +11365,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t } __pyx_L7:; - /* "_tree.pyx":755 + /* "stpredictions/models/OK3/_tree.pyx":755 * node.threshold = threshold * * self.node_count += 1 # <<<<<<<<<<<<<< @@ -11755,7 +11374,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t */ __pyx_v_self->node_count = (__pyx_v_self->node_count + 1); - /* "_tree.pyx":757 + /* "stpredictions/models/OK3/_tree.pyx":757 * self.node_count += 1 * * return node_id # <<<<<<<<<<<<<< @@ -11765,7 +11384,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t __pyx_r = __pyx_v_node_id; goto __pyx_L0; - /* "_tree.pyx":717 + /* "stpredictions/models/OK3/_tree.pyx":717 * return 0 * * cdef SIZE_t _add_node(self, SIZE_t parent, bint is_left, bint is_leaf, # <<<<<<<<<<<<<< @@ -11779,7 +11398,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); #endif - __Pyx_AddTraceback("_tree.Tree._add_node", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree._add_node", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD __Pyx_PyGILState_Release(__pyx_gilstate_save); #endif @@ -11789,7 +11408,7 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t return __pyx_r; } -/* "_tree.pyx":759 +/* "stpredictions/models/OK3/_tree.pyx":759 * return node_id * * cpdef np.ndarray predict(self, object X): # <<<<<<<<<<<<<< @@ -11797,8 +11416,8 @@ static __pyx_t_5_tree_SIZE_t __pyx_f_5_tree_4Tree__add_node(struct __pyx_obj_5_t * It is an array with for each row positive weights for the training indices in the same leaf. */ -static PyObject *__pyx_pw_5_tree_4Tree_11predict(PyObject *__pyx_v_self, PyObject *__pyx_v_X); /*proto*/ -static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_11predict(PyObject *__pyx_v_self, PyObject *__pyx_v_X); /*proto*/ +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_predict(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch) { PyArrayObject *__pyx_v_ex_to_leaf = NULL; PyArrayObject *__pyx_v_leaf_to_train_exs = NULL; PyObject *__pyx_v_out = NULL; @@ -11826,7 +11445,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree #endif __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_self), __pyx_n_s_predict); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 759, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_5_tree_4Tree_11predict)) { + if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_11predict)) { __Pyx_XDECREF(((PyObject *)__pyx_r)); __Pyx_INCREF(__pyx_t_1); __pyx_t_3 = __pyx_t_1; __pyx_t_4 = NULL; @@ -11863,31 +11482,31 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree #endif } - /* "_tree.pyx":774 + /* "stpredictions/models/OK3/_tree.pyx":774 * """ * # get the leaves X falls in * ex_to_leaf = self.apply(X) # <<<<<<<<<<<<<< * # get the list of the training examples each leaf * leaf_to_train_exs = self._get_value_ndarray() */ - __pyx_t_1 = ((PyObject *)((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->apply(__pyx_v_self, __pyx_v_X, 0)); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 774, __pyx_L1_error) + __pyx_t_1 = ((PyObject *)((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->apply(__pyx_v_self, __pyx_v_X, 0)); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 774, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_v_ex_to_leaf = ((PyArrayObject *)__pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":776 + /* "stpredictions/models/OK3/_tree.pyx":776 * ex_to_leaf = self.apply(X) * # get the list of the training examples each leaf * leaf_to_train_exs = self._get_value_ndarray() # <<<<<<<<<<<<<< * * out = np.zeros((X.shape[0], leaf_to_train_exs.shape[1]), dtype=DOUBLE) */ - __pyx_t_1 = ((PyObject *)((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_get_value_ndarray(__pyx_v_self)); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 776, __pyx_L1_error) + __pyx_t_1 = ((PyObject *)((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_get_value_ndarray(__pyx_v_self)); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 776, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_v_leaf_to_train_exs = ((PyArrayObject *)__pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":778 + /* "stpredictions/models/OK3/_tree.pyx":778 * leaf_to_train_exs = self._get_value_ndarray() * * out = np.zeros((X.shape[0], leaf_to_train_exs.shape[1]), dtype=DOUBLE) # <<<<<<<<<<<<<< @@ -11933,7 +11552,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree __pyx_v_out = __pyx_t_3; __pyx_t_3 = 0; - /* "_tree.pyx":780 + /* "stpredictions/models/OK3/_tree.pyx":780 * out = np.zeros((X.shape[0], leaf_to_train_exs.shape[1]), dtype=DOUBLE) * # assign the right list of training samples to the right input * for ex in range(X.shape[0]): # <<<<<<<<<<<<<< @@ -11991,7 +11610,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree __Pyx_XDECREF_SET(__pyx_v_ex, __pyx_t_3); __pyx_t_3 = 0; - /* "_tree.pyx":781 + /* "stpredictions/models/OK3/_tree.pyx":781 * # assign the right list of training samples to the right input * for ex in range(X.shape[0]): * out[ex] = leaf_to_train_exs[ex_to_leaf[ex]] # <<<<<<<<<<<<<< @@ -12006,7 +11625,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree if (unlikely(PyObject_SetItem(__pyx_v_out, __pyx_v_ex, __pyx_t_1) < 0)) __PYX_ERR(0, 781, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":780 + /* "stpredictions/models/OK3/_tree.pyx":780 * out = np.zeros((X.shape[0], leaf_to_train_exs.shape[1]), dtype=DOUBLE) * # assign the right list of training samples to the right input * for ex in range(X.shape[0]): # <<<<<<<<<<<<<< @@ -12016,7 +11635,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree } __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - /* "_tree.pyx":783 + /* "stpredictions/models/OK3/_tree.pyx":783 * out[ex] = leaf_to_train_exs[ex_to_leaf[ex]] * * return out # <<<<<<<<<<<<<< @@ -12029,7 +11648,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree __pyx_r = ((PyArrayObject *)__pyx_v_out); goto __pyx_L0; - /* "_tree.pyx":759 + /* "stpredictions/models/OK3/_tree.pyx":759 * return node_id * * cpdef np.ndarray predict(self, object X): # <<<<<<<<<<<<<< @@ -12043,7 +11662,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree __Pyx_XDECREF(__pyx_t_2); __Pyx_XDECREF(__pyx_t_3); __Pyx_XDECREF(__pyx_t_4); - __Pyx_AddTraceback("_tree.Tree.predict", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree.predict", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; __pyx_L0:; __Pyx_XDECREF((PyObject *)__pyx_v_ex_to_leaf); @@ -12056,20 +11675,20 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_predict(struct __pyx_obj_5_tree_Tree } /* Python wrapper */ -static PyObject *__pyx_pw_5_tree_4Tree_11predict(PyObject *__pyx_v_self, PyObject *__pyx_v_X); /*proto*/ -static char __pyx_doc_5_tree_4Tree_10predict[] = "Returns the weighted training samples falling in the leaves X falls in.\n It is an array with for each row positive weights for the training indices in the same leaf.\n (the prediction in the Hilbert space is the weighted mean of these sample's outputs)\n \n Parameters\n ----------\n X : {array-like, sparse matrix} of shape (n_samples, n_features)\n The input samples.\n \n Returns\n --------\n A (n_test_samples, n_train_samples) array\n "; -static PyObject *__pyx_pw_5_tree_4Tree_11predict(PyObject *__pyx_v_self, PyObject *__pyx_v_X) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_11predict(PyObject *__pyx_v_self, PyObject *__pyx_v_X); /*proto*/ +static char __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_10predict[] = "Returns the weighted training samples falling in the leaves X falls in.\n It is an array with for each row positive weights for the training indices in the same leaf.\n (the prediction in the Hilbert space is the weighted mean of these sample's outputs)\n \n Parameters\n ----------\n X : {array-like, sparse matrix} of shape (n_samples, n_features)\n The input samples.\n \n Returns\n --------\n A (n_test_samples, n_train_samples) array\n "; +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_11predict(PyObject *__pyx_v_self, PyObject *__pyx_v_X) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("predict (wrapper)", 0); - __pyx_r = __pyx_pf_5_tree_4Tree_10predict(((struct __pyx_obj_5_tree_Tree *)__pyx_v_self), ((PyObject *)__pyx_v_X)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10predict(((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_self), ((PyObject *)__pyx_v_X)); /* function exit code */ __Pyx_RefNannyFinishContext(); return __pyx_r; } -static PyObject *__pyx_pf_5_tree_4Tree_10predict(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_10predict(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -12078,7 +11697,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_10predict(struct __pyx_obj_5_tree_Tree *_ int __pyx_clineno = 0; __Pyx_RefNannySetupContext("predict", 0); __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = ((PyObject *)__pyx_f_5_tree_4Tree_predict(__pyx_v_self, __pyx_v_X, 1)); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 759, __pyx_L1_error) + __pyx_t_1 = ((PyObject *)__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_predict(__pyx_v_self, __pyx_v_X, 1)); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 759, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; @@ -12087,7 +11706,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_10predict(struct __pyx_obj_5_tree_Tree *_ /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_1); - __Pyx_AddTraceback("_tree.Tree.predict", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree.predict", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __Pyx_XGIVEREF(__pyx_r); @@ -12095,7 +11714,7 @@ static PyObject *__pyx_pf_5_tree_4Tree_10predict(struct __pyx_obj_5_tree_Tree *_ return __pyx_r; } -/* "_tree.pyx":785 +/* "stpredictions/models/OK3/_tree.pyx":785 * return out * * cpdef np.ndarray decode_tree(self, np.ndarray K_cand_train, np.ndarray sq_norms_cand, object criterion, str kernel, SIZE_t return_top_k): # <<<<<<<<<<<<<< @@ -12103,8 +11722,8 @@ static PyObject *__pyx_pf_5_tree_4Tree_10predict(struct __pyx_obj_5_tree_Tree *_ * */ -static PyObject *__pyx_pw_5_tree_4Tree_13decode_tree(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_K_cand_train, PyArrayObject *__pyx_v_sq_norms_cand, PyObject *__pyx_v_criterion, PyObject *__pyx_v_kernel, __pyx_t_5_tree_SIZE_t __pyx_v_return_top_k, int __pyx_skip_dispatch) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_13decode_tree(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_decode_tree(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_K_cand_train, PyArrayObject *__pyx_v_sq_norms_cand, PyObject *__pyx_v_criterion, PyObject *__pyx_v_kernel, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_return_top_k, int __pyx_skip_dispatch) { PyArrayObject *__pyx_v_y_train = NULL; npy_intp __pyx_v_n_outputs; PyObject *__pyx_v_classes = NULL; @@ -12166,7 +11785,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T #endif __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_self), __pyx_n_s_decode_tree); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 785, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_5_tree_4Tree_13decode_tree)) { + if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_13decode_tree)) { __Pyx_XDECREF(((PyObject *)__pyx_r)); __pyx_t_3 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_return_top_k); if (unlikely(!__pyx_t_3)) __PYX_ERR(0, 785, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); @@ -12246,7 +11865,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T #endif } - /* "_tree.pyx":824 + /* "stpredictions/models/OK3/_tree.pyx":824 * The returned array has an arbitrary value of -1 for the lines corresponding to non-leaf nodes. * """ * if isinstance(criterion, KernelizedMSE): # <<<<<<<<<<<<<< @@ -12260,7 +11879,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_t_9 = (__pyx_t_8 != 0); if (likely(__pyx_t_9)) { - /* "_tree.pyx":827 + /* "stpredictions/models/OK3/_tree.pyx":827 * * # Cas particulier de la classification : recherche EXHAUSTIVE * if kernel == "gini_clf": # <<<<<<<<<<<<<< @@ -12271,7 +11890,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_t_8 = (__pyx_t_9 != 0); if (__pyx_t_8) { - /* "_tree.pyx":831 + /* "stpredictions/models/OK3/_tree.pyx":831 * # rechercher la meilleure combinaison de labels parmis toutes celles possible * * y_train = self.y # <<<<<<<<<<<<<< @@ -12283,7 +11902,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_v_y_train = ((PyArrayObject *)__pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":832 + /* "stpredictions/models/OK3/_tree.pyx":832 * * y_train = self.y * n_outputs = y_train.shape[1] # <<<<<<<<<<<<<< @@ -12292,7 +11911,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T */ __pyx_v_n_outputs = (__pyx_v_y_train->dimensions[1]); - /* "_tree.pyx":834 + /* "stpredictions/models/OK3/_tree.pyx":834 * n_outputs = y_train.shape[1] * * classes = [] # <<<<<<<<<<<<<< @@ -12304,7 +11923,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_v_classes = ((PyObject*)__pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":835 + /* "stpredictions/models/OK3/_tree.pyx":835 * * classes = [] * n_classes = [] # <<<<<<<<<<<<<< @@ -12316,7 +11935,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_v_n_classes = __pyx_t_1; __pyx_t_1 = 0; - /* "_tree.pyx":837 + /* "stpredictions/models/OK3/_tree.pyx":837 * n_classes = [] * * y_train_encoded = np.zeros((y_train.shape[0], n_outputs), dtype=int) # <<<<<<<<<<<<<< @@ -12356,7 +11975,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_v_y_train_encoded = __pyx_t_1; __pyx_t_1 = 0; - /* "_tree.pyx":839 + /* "stpredictions/models/OK3/_tree.pyx":839 * y_train_encoded = np.zeros((y_train.shape[0], n_outputs), dtype=int) * * for l in range(n_outputs): # <<<<<<<<<<<<<< @@ -12368,7 +11987,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) { __pyx_v_l = __pyx_t_12; - /* "_tree.pyx":840 + /* "stpredictions/models/OK3/_tree.pyx":840 * * for l in range(n_outputs): * classes_l, y_train_encoded[:, l] = np.unique(y_train[:, l], return_inverse=True) # <<<<<<<<<<<<<< @@ -12468,7 +12087,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - /* "_tree.pyx":841 + /* "stpredictions/models/OK3/_tree.pyx":841 * for l in range(n_outputs): * classes_l, y_train_encoded[:, l] = np.unique(y_train[:, l], return_inverse=True) * classes.append(classes_l) # <<<<<<<<<<<<<< @@ -12477,7 +12096,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T */ __pyx_t_14 = __Pyx_PyList_Append(__pyx_v_classes, __pyx_v_classes_l); if (unlikely(__pyx_t_14 == ((int)-1))) __PYX_ERR(0, 841, __pyx_L1_error) - /* "_tree.pyx":842 + /* "stpredictions/models/OK3/_tree.pyx":842 * classes_l, y_train_encoded[:, l] = np.unique(y_train[:, l], return_inverse=True) * classes.append(classes_l) * n_classes.append(classes_l.shape[0]) # <<<<<<<<<<<<<< @@ -12493,7 +12112,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; } - /* "_tree.pyx":844 + /* "stpredictions/models/OK3/_tree.pyx":844 * n_classes.append(classes_l.shape[0]) * * n_classes = np.array(n_classes, dtype=np.intp) # <<<<<<<<<<<<<< @@ -12527,19 +12146,19 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_DECREF_SET(__pyx_v_n_classes, __pyx_t_7); __pyx_t_7 = 0; - /* "_tree.pyx":848 + /* "stpredictions/models/OK3/_tree.pyx":848 * * * leaf_to_train_exs = self._get_value_ndarray() # <<<<<<<<<<<<<< * * out = np.ones((self.node_count*return_top_k,n_outputs), dtype=np.intp) * (-1) */ - __pyx_t_7 = ((PyObject *)((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_get_value_ndarray(__pyx_v_self)); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 848, __pyx_L1_error) + __pyx_t_7 = ((PyObject *)((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_get_value_ndarray(__pyx_v_self)); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 848, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); __pyx_v_leaf_to_train_exs = ((PyArrayObject *)__pyx_t_7); __pyx_t_7 = 0; - /* "_tree.pyx":850 + /* "stpredictions/models/OK3/_tree.pyx":850 * leaf_to_train_exs = self._get_value_ndarray() * * out = np.ones((self.node_count*return_top_k,n_outputs), dtype=np.intp) * (-1) # <<<<<<<<<<<<<< @@ -12588,7 +12207,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_v_out = __pyx_t_2; __pyx_t_2 = 0; - /* "_tree.pyx":852 + /* "stpredictions/models/OK3/_tree.pyx":852 * out = np.ones((self.node_count*return_top_k,n_outputs), dtype=np.intp) * (-1) * * nb_candidates = 1 # <<<<<<<<<<<<<< @@ -12598,7 +12217,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_INCREF(__pyx_int_1); __pyx_v_nb_candidates = __pyx_int_1; - /* "_tree.pyx":853 + /* "stpredictions/models/OK3/_tree.pyx":853 * * nb_candidates = 1 * for nb_classes in n_classes: # <<<<<<<<<<<<<< @@ -12647,7 +12266,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_XDECREF_SET(__pyx_v_nb_classes, __pyx_t_3); __pyx_t_3 = 0; - /* "_tree.pyx":854 + /* "stpredictions/models/OK3/_tree.pyx":854 * nb_candidates = 1 * for nb_classes in n_classes: * nb_candidates *= nb_classes # <<<<<<<<<<<<<< @@ -12659,7 +12278,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_DECREF_SET(__pyx_v_nb_candidates, __pyx_t_3); __pyx_t_3 = 0; - /* "_tree.pyx":853 + /* "stpredictions/models/OK3/_tree.pyx":853 * * nb_candidates = 1 * for nb_classes in n_classes: # <<<<<<<<<<<<<< @@ -12669,7 +12288,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T } __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - /* "_tree.pyx":856 + /* "stpredictions/models/OK3/_tree.pyx":856 * nb_candidates *= nb_classes * # array to store the value of the criteria to minimize, for each training sample * value = np.zeros((nb_candidates,), dtype=np.float64) # <<<<<<<<<<<<<< @@ -12708,7 +12327,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_v_value = __pyx_t_7; __pyx_t_7 = 0; - /* "_tree.pyx":858 + /* "stpredictions/models/OK3/_tree.pyx":858 * value = np.zeros((nb_candidates,), dtype=np.float64) * * recherche_exhaustive_equivalente = False # <<<<<<<<<<<<<< @@ -12717,7 +12336,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T */ __pyx_v_recherche_exhaustive_equivalente = 0; - /* "_tree.pyx":861 + /* "stpredictions/models/OK3/_tree.pyx":861 * * # node k * for k in range(self.node_count): # <<<<<<<<<<<<<< @@ -12772,7 +12391,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_XDECREF_SET(__pyx_v_k, __pyx_t_2); __pyx_t_2 = 0; - /* "_tree.pyx":863 + /* "stpredictions/models/OK3/_tree.pyx":863 * for k in range(self.node_count): * # ne considrer que les feuilles pour y calculer une output * if self.nodes[k].left_child == _TREE_LEAF: # <<<<<<<<<<<<<< @@ -12780,10 +12399,10 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T * if recherche_exhaustive_equivalente or return_top_k > 1: # n_outputs boucles sur les classes de chaque output imbriques dans le product --> long */ __pyx_t_17 = __Pyx_PyIndex_AsSsize_t(__pyx_v_k); if (unlikely((__pyx_t_17 == (Py_ssize_t)-1) && PyErr_Occurred())) __PYX_ERR(0, 863, __pyx_L1_error) - __pyx_t_8 = (((__pyx_v_self->nodes[__pyx_t_17]).left_child == __pyx_v_5_tree__TREE_LEAF) != 0); + __pyx_t_8 = (((__pyx_v_self->nodes[__pyx_t_17]).left_child == __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF) != 0); if (__pyx_t_8) { - /* "_tree.pyx":865 + /* "stpredictions/models/OK3/_tree.pyx":865 * if self.nodes[k].left_child == _TREE_LEAF: * * if recherche_exhaustive_equivalente or return_top_k > 1: # n_outputs boucles sur les classes de chaque output imbriques dans le product --> long # <<<<<<<<<<<<<< @@ -12801,7 +12420,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_L15_bool_binop_done:; if (__pyx_t_8) { - /* "_tree.pyx":867 + /* "stpredictions/models/OK3/_tree.pyx":867 * if recherche_exhaustive_equivalente or return_top_k > 1: # n_outputs boucles sur les classes de chaque output imbriques dans le product --> long * * for ind, candidate in enumerate(list(itertools.product(*classes))): # <<<<<<<<<<<<<< @@ -12844,7 +12463,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_t_2 = __pyx_t_4; __pyx_t_4 = 0; - /* "_tree.pyx":873 + /* "stpredictions/models/OK3/_tree.pyx":873 * # on peut donc plutt maximiser la quantit somme_des_Kernel(candidate,train_exs_in_same_leaf) * * value[ind] = np.sum([ leaf_to_train_exs[k,ex] * (y_train[ex] == candidate).mean() for ex in range(leaf_to_train_exs.shape[1])]) # <<<<<<<<<<<<<< @@ -12923,7 +12542,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T if (unlikely(PyObject_SetItem(__pyx_v_value, __pyx_v_ind, __pyx_t_4) < 0)) __PYX_ERR(0, 873, __pyx_L1_error) __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - /* "_tree.pyx":867 + /* "stpredictions/models/OK3/_tree.pyx":867 * if recherche_exhaustive_equivalente or return_top_k > 1: # n_outputs boucles sur les classes de chaque output imbriques dans le product --> long * * for ind, candidate in enumerate(list(itertools.product(*classes))): # <<<<<<<<<<<<<< @@ -12934,7 +12553,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - /* "_tree.pyx":875 + /* "stpredictions/models/OK3/_tree.pyx":875 * value[ind] = np.sum([ leaf_to_train_exs[k,ex] * (y_train[ex] == candidate).mean() for ex in range(leaf_to_train_exs.shape[1])]) * * ind_top_candidates = np.argpartition(value, - return_top_k)[- return_top_k:] # <<<<<<<<<<<<<< @@ -13001,7 +12620,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_XDECREF_SET(__pyx_v_ind_top_candidates, __pyx_t_4); __pyx_t_4 = 0; - /* "_tree.pyx":877 + /* "stpredictions/models/OK3/_tree.pyx":877 * ind_top_candidates = np.argpartition(value, - return_top_k)[- return_top_k:] * * top_candidates = list(itertools.product(*classes))[ind_top_candidates] # <<<<<<<<<<<<<< @@ -13028,7 +12647,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_XDECREF_SET(__pyx_v_top_candidates, __pyx_t_3); __pyx_t_3 = 0; - /* "_tree.pyx":878 + /* "stpredictions/models/OK3/_tree.pyx":878 * * top_candidates = list(itertools.product(*classes))[ind_top_candidates] * top_candidates = np.array(top_candidates, dtype=int) # <<<<<<<<<<<<<< @@ -13056,7 +12675,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_DECREF_SET(__pyx_v_top_candidates, __pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":880 + /* "stpredictions/models/OK3/_tree.pyx":880 * top_candidates = np.array(top_candidates, dtype=int) * * out[k*return_top_k : (k+1)*return_top_k] = top_candidates # <<<<<<<<<<<<<< @@ -13080,7 +12699,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - /* "_tree.pyx":865 + /* "stpredictions/models/OK3/_tree.pyx":865 * if self.nodes[k].left_child == _TREE_LEAF: * * if recherche_exhaustive_equivalente or return_top_k > 1: # n_outputs boucles sur les classes de chaque output imbriques dans le product --> long # <<<<<<<<<<<<<< @@ -13090,7 +12709,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T goto __pyx_L14; } - /* "_tree.pyx":884 + /* "stpredictions/models/OK3/_tree.pyx":884 * else: * * for l in range(n_outputs): # <<<<<<<<<<<<<< @@ -13103,7 +12722,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) { __pyx_v_l = __pyx_t_12; - /* "_tree.pyx":886 + /* "stpredictions/models/OK3/_tree.pyx":886 * for l in range(n_outputs): * * major_class = np.argmax( [ np.sum( leaf_to_train_exs[k, np.where( y_train[:,l] == class_i )[0] ] ) for class_i in classes[l] ] ) # <<<<<<<<<<<<<< @@ -13252,7 +12871,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_XDECREF_SET(__pyx_v_major_class, __pyx_t_4); __pyx_t_4 = 0; - /* "_tree.pyx":888 + /* "stpredictions/models/OK3/_tree.pyx":888 * major_class = np.argmax( [ np.sum( leaf_to_train_exs[k, np.where( y_train[:,l] == class_i )[0] ] ) for class_i in classes[l] ] ) * * out[k,l] = classes[l][ major_class ] # <<<<<<<<<<<<<< @@ -13278,7 +12897,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T } __pyx_L14:; - /* "_tree.pyx":863 + /* "stpredictions/models/OK3/_tree.pyx":863 * for k in range(self.node_count): * # ne considrer que les feuilles pour y calculer une output * if self.nodes[k].left_child == _TREE_LEAF: # <<<<<<<<<<<<<< @@ -13287,7 +12906,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T */ } - /* "_tree.pyx":861 + /* "stpredictions/models/OK3/_tree.pyx":861 * * # node k * for k in range(self.node_count): # <<<<<<<<<<<<<< @@ -13297,7 +12916,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T } __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; - /* "_tree.pyx":827 + /* "stpredictions/models/OK3/_tree.pyx":827 * * # Cas particulier de la classification : recherche EXHAUSTIVE * if kernel == "gini_clf": # <<<<<<<<<<<<<< @@ -13307,7 +12926,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T goto __pyx_L4; } - /* "_tree.pyx":891 + /* "stpredictions/models/OK3/_tree.pyx":891 * * # Cas particulier de la rgression : Recherche EXACTE * elif kernel == "mse_reg": # <<<<<<<<<<<<<< @@ -13318,7 +12937,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_t_9 = (__pyx_t_8 != 0); if (__pyx_t_9) { - /* "_tree.pyx":900 + /* "stpredictions/models/OK3/_tree.pyx":900 * # On ne peut pas rechercher les k meilleurs candidats car l'ensemble de recherche de candidats pour la rgression est infini (R^d) * * y_train = self.y # <<<<<<<<<<<<<< @@ -13330,7 +12949,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_v_y_train = ((PyArrayObject *)__pyx_t_7); __pyx_t_7 = 0; - /* "_tree.pyx":901 + /* "stpredictions/models/OK3/_tree.pyx":901 * * y_train = self.y * n_outputs = y_train.shape[1] # <<<<<<<<<<<<<< @@ -13339,19 +12958,19 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T */ __pyx_v_n_outputs = (__pyx_v_y_train->dimensions[1]); - /* "_tree.pyx":903 + /* "stpredictions/models/OK3/_tree.pyx":903 * n_outputs = y_train.shape[1] * * leaf_to_train_exs = self._get_value_ndarray() # <<<<<<<<<<<<<< * * out = leaf_to_train_exs @ y_train */ - __pyx_t_7 = ((PyObject *)((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_get_value_ndarray(__pyx_v_self)); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 903, __pyx_L1_error) + __pyx_t_7 = ((PyObject *)((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_get_value_ndarray(__pyx_v_self)); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 903, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); __pyx_v_leaf_to_train_exs = ((PyArrayObject *)__pyx_t_7); __pyx_t_7 = 0; - /* "_tree.pyx":905 + /* "stpredictions/models/OK3/_tree.pyx":905 * leaf_to_train_exs = self._get_value_ndarray() * * out = leaf_to_train_exs @ y_train # <<<<<<<<<<<<<< @@ -13363,7 +12982,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_v_out = __pyx_t_7; __pyx_t_7 = 0; - /* "_tree.pyx":891 + /* "stpredictions/models/OK3/_tree.pyx":891 * * # Cas particulier de la rgression : Recherche EXACTE * elif kernel == "mse_reg": # <<<<<<<<<<<<<< @@ -13373,7 +12992,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T goto __pyx_L4; } - /* "_tree.pyx":924 + /* "stpredictions/models/OK3/_tree.pyx":924 * # on renvoie l'indce du candidat reprsentant le mieux la feuille (on ne check pas les training examples, ils sont mettre dans les candidats) * * leaf_to_train_exs = self._get_value_ndarray() # <<<<<<<<<<<<<< @@ -13381,12 +13000,12 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T * out = np.ones((self.node_count*return_top_k,), dtype=np.intp) * (-1) */ /*else*/ { - __pyx_t_7 = ((PyObject *)((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_get_value_ndarray(__pyx_v_self)); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 924, __pyx_L1_error) + __pyx_t_7 = ((PyObject *)((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_self->__pyx_vtab)->_get_value_ndarray(__pyx_v_self)); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 924, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); __pyx_v_leaf_to_train_exs = ((PyArrayObject *)__pyx_t_7); __pyx_t_7 = 0; - /* "_tree.pyx":926 + /* "stpredictions/models/OK3/_tree.pyx":926 * leaf_to_train_exs = self._get_value_ndarray() * * out = np.ones((self.node_count*return_top_k,), dtype=np.intp) * (-1) # <<<<<<<<<<<<<< @@ -13430,7 +13049,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_v_out = __pyx_t_2; __pyx_t_2 = 0; - /* "_tree.pyx":929 + /* "stpredictions/models/OK3/_tree.pyx":929 * * # array to store the value of the criteria to minimize, for each training sample * value = np.zeros((K_cand_train.shape[0],), dtype=np.float64) # <<<<<<<<<<<<<< @@ -13471,7 +13090,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_v_value = __pyx_t_3; __pyx_t_3 = 0; - /* "_tree.pyx":932 + /* "stpredictions/models/OK3/_tree.pyx":932 * * # node k * for k in range(self.node_count): # <<<<<<<<<<<<<< @@ -13526,7 +13145,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_XDECREF_SET(__pyx_v_k, __pyx_t_7); __pyx_t_7 = 0; - /* "_tree.pyx":934 + /* "stpredictions/models/OK3/_tree.pyx":934 * for k in range(self.node_count): * # ne considrer que les feuilles pour y calculer une output * if self.nodes[k].left_child == _TREE_LEAF: # <<<<<<<<<<<<<< @@ -13534,10 +13153,10 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T * for candidate in range(K_cand_train.shape[0]): */ __pyx_t_17 = __Pyx_PyIndex_AsSsize_t(__pyx_v_k); if (unlikely((__pyx_t_17 == (Py_ssize_t)-1) && PyErr_Occurred())) __PYX_ERR(0, 934, __pyx_L1_error) - __pyx_t_9 = (((__pyx_v_self->nodes[__pyx_t_17]).left_child == __pyx_v_5_tree__TREE_LEAF) != 0); + __pyx_t_9 = (((__pyx_v_self->nodes[__pyx_t_17]).left_child == __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF) != 0); if (__pyx_t_9) { - /* "_tree.pyx":936 + /* "stpredictions/models/OK3/_tree.pyx":936 * if self.nodes[k].left_child == _TREE_LEAF: * # parmi les candidats, calculer k[candidat,candidat] - 2/self.n_node_samples * sum_i=0^self.n_node_samples k[candidat,i] * for candidate in range(K_cand_train.shape[0]): # <<<<<<<<<<<<<< @@ -13592,7 +13211,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_XDECREF_SET(__pyx_v_candidate, __pyx_t_2); __pyx_t_2 = 0; - /* "_tree.pyx":938 + /* "stpredictions/models/OK3/_tree.pyx":938 * for candidate in range(K_cand_train.shape[0]): * * value[candidate] = sq_norms_cand[candidate] - 2 * np.sum([leaf_to_train_exs[k,ex] * K_cand_train[candidate,ex] for ex in range(leaf_to_train_exs.shape[1])]) # <<<<<<<<<<<<<< @@ -13671,7 +13290,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T if (unlikely(PyObject_SetItem(__pyx_v_value, __pyx_v_candidate, __pyx_t_1) < 0)) __PYX_ERR(0, 938, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":936 + /* "stpredictions/models/OK3/_tree.pyx":936 * if self.nodes[k].left_child == _TREE_LEAF: * # parmi les candidats, calculer k[candidat,candidat] - 2/self.n_node_samples * sum_i=0^self.n_node_samples k[candidat,i] * for candidate in range(K_cand_train.shape[0]): # <<<<<<<<<<<<<< @@ -13681,7 +13300,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T } __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; - /* "_tree.pyx":941 + /* "stpredictions/models/OK3/_tree.pyx":941 * * # choisir l'entre ex* qui donnait la plus petite valeur * ind_top_candidates = np.argpartition(value, return_top_k)[:return_top_k] # <<<<<<<<<<<<<< @@ -13748,7 +13367,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_XDECREF_SET(__pyx_v_ind_top_candidates, __pyx_t_5); __pyx_t_5 = 0; - /* "_tree.pyx":943 + /* "stpredictions/models/OK3/_tree.pyx":943 * ind_top_candidates = np.argpartition(value, return_top_k)[:return_top_k] * * out[k*return_top_k : (k+1)*return_top_k] = ind_top_candidates # <<<<<<<<<<<<<< @@ -13772,7 +13391,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":934 + /* "stpredictions/models/OK3/_tree.pyx":934 * for k in range(self.node_count): * # ne considrer que les feuilles pour y calculer une output * if self.nodes[k].left_child == _TREE_LEAF: # <<<<<<<<<<<<<< @@ -13781,7 +13400,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T */ } - /* "_tree.pyx":932 + /* "stpredictions/models/OK3/_tree.pyx":932 * * # node k * for k in range(self.node_count): # <<<<<<<<<<<<<< @@ -13793,7 +13412,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T } __pyx_L4:; - /* "_tree.pyx":946 + /* "stpredictions/models/OK3/_tree.pyx":946 * * * return out # <<<<<<<<<<<<<< @@ -13806,7 +13425,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __pyx_r = ((PyArrayObject *)__pyx_v_out); goto __pyx_L0; - /* "_tree.pyx":824 + /* "stpredictions/models/OK3/_tree.pyx":824 * The returned array has an arbitrary value of -1 for the lines corresponding to non-leaf nodes. * """ * if isinstance(criterion, KernelizedMSE): # <<<<<<<<<<<<<< @@ -13815,7 +13434,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T */ } - /* "_tree.pyx":950 + /* "stpredictions/models/OK3/_tree.pyx":950 * * else: * raise NotImplementedError('only the "KernelizedMSE" criterion is supported') # <<<<<<<<<<<<<< @@ -13830,7 +13449,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __PYX_ERR(0, 950, __pyx_L1_error) } - /* "_tree.pyx":785 + /* "stpredictions/models/OK3/_tree.pyx":785 * return out * * cpdef np.ndarray decode_tree(self, np.ndarray K_cand_train, np.ndarray sq_norms_cand, object criterion, str kernel, SIZE_t return_top_k): # <<<<<<<<<<<<<< @@ -13851,7 +13470,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T __Pyx_XDECREF(__pyx_t_20); __Pyx_XDECREF(__pyx_t_21); __Pyx_XDECREF(__pyx_t_23); - __Pyx_AddTraceback("_tree.Tree.decode_tree", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree.decode_tree", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; __pyx_L0:; __Pyx_XDECREF((PyObject *)__pyx_v_y_train); @@ -13877,14 +13496,14 @@ static PyArrayObject *__pyx_f_5_tree_4Tree_decode_tree(struct __pyx_obj_5_tree_T } /* Python wrapper */ -static PyObject *__pyx_pw_5_tree_4Tree_13decode_tree(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static char __pyx_doc_5_tree_4Tree_12decode_tree[] = "shape (node_count,)\n\n Decode using the search for the output the closer to the mean of the \n input's leaf in the embedding Hilbert space\n corresponds to the KernelizedMSE criterion\n \n out[i] is the index of the example whose \n output has been chosen to represent the output of the leaf i \n (if i is a leaf, otherwise it is -1).\n \n Parameters\n ----------\n K_cand_train : array of shape (n_candidates, n_train_samples)\n The Kernel matrix between the candidates outputs and the training outputs.\n \n sq_norms_cand : array of shape (n_candidates,)\n The list of the kernel values of the candidates computed againt themselves\n (square L2 norm in the Hilbert space).\n \n criterion : {\"mse\"}, default=\"mse\"\n The function to measure the quality of a split (in the Hilbert space).\n \n kernel : string\n The type of kernel to use to compare the output data. \n Used only to check wether we want to do classic classification or regression or a general case.\n \n return_top_k : int (>0)\n The number of output to return for each leaf (the size of the set of the best candidates outputs)\n \n Returns\n -------\n An array of shape (node_count * return_top_k, n_candidates)\n describing for each LEAF the indices in candidates of the selected output(s), \n minimizing the \"distance\" with the \"true\" predisction in the Hilbert space.\n \n Note :\n The returned array has an arbitrary value of -1 for the lines corresponding to non-leaf nodes.\n "; -static PyObject *__pyx_pw_5_tree_4Tree_13decode_tree(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_13decode_tree(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_12decode_tree[] = "shape (node_count,)\n\n Decode using the search for the output the closer to the mean of the \n input's leaf in the embedding Hilbert space\n corresponds to the KernelizedMSE criterion\n \n out[i] is the index of the example whose \n output has been chosen to represent the output of the leaf i \n (if i is a leaf, otherwise it is -1).\n \n Parameters\n ----------\n K_cand_train : array of shape (n_candidates, n_train_samples)\n The Kernel matrix between the candidates outputs and the training outputs.\n \n sq_norms_cand : array of shape (n_candidates,)\n The list of the kernel values of the candidates computed againt themselves\n (square L2 norm in the Hilbert space).\n \n criterion : {\"mse\"}, default=\"mse\"\n The function to measure the quality of a split (in the Hilbert space).\n \n kernel : string\n The type of kernel to use to compare the output data. \n Used only to check wether we want to do classic classification or regression or a general case.\n \n return_top_k : int (>0)\n The number of output to return for each leaf (the size of the set of the best candidates outputs)\n \n Returns\n -------\n An array of shape (node_count * return_top_k, n_candidates)\n describing for each LEAF the indices in candidates of the selected output(s), \n minimizing the \"distance\" with the \"true\" predisction in the Hilbert space.\n \n Note :\n The returned array has an arbitrary value of -1 for the lines corresponding to non-leaf nodes.\n "; 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- __pyx_t_5_tree_SIZE_t __pyx_t_12; - struct __pyx_t_5_tree_Node *__pyx_t_13; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_11; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_12; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_t_13; Py_ssize_t __pyx_t_14; Py_ssize_t __pyx_t_15; int __pyx_lineno = 0; @@ -14306,7 +13925,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ __pyx_pybuffernd_out.data = NULL; __pyx_pybuffernd_out.rcbuffer = &__pyx_pybuffer_out; - /* "_tree.pyx":967 + /* "stpredictions/models/OK3/_tree.pyx":967 * * # Check input * if not isinstance(X, np.ndarray): # <<<<<<<<<<<<<< @@ -14317,7 +13936,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0); if (unlikely(__pyx_t_2)) { - /* "_tree.pyx":969 + /* "stpredictions/models/OK3/_tree.pyx":969 * if not isinstance(X, np.ndarray): * raise ValueError("X should be in np.ndarray format, got %s" * % type(X)) # <<<<<<<<<<<<<< @@ -14327,7 +13946,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ __pyx_t_3 = __Pyx_PyString_FormatSafe(__pyx_kp_s_X_should_be_in_np_ndarray_format, ((PyObject *)Py_TYPE(__pyx_v_X))); 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__pyx_t_3 = 0; __pyx_v_n_samples = __pyx_t_7; - /* "_tree.pyx":979 + /* "stpredictions/models/OK3/_tree.pyx":979 * * # Initialize output * cdef np.ndarray[SIZE_t] out = np.zeros((n_samples,), dtype=np.intp) # <<<<<<<<<<<<<< @@ -14466,7 +14085,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ __pyx_t_10 = ((PyArrayObject *)__pyx_t_9); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_out.rcbuffer->pybuffer, (PyObject*)__pyx_t_10, &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_out.rcbuffer->pybuffer, (PyObject*)__pyx_t_10, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_out = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_out.rcbuffer->pybuffer.buf = NULL; __PYX_ERR(0, 979, __pyx_L1_error) } else {__pyx_pybuffernd_out.diminfo[0].strides = __pyx_pybuffernd_out.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_out.diminfo[0].shape = __pyx_pybuffernd_out.rcbuffer->pybuffer.shape[0]; @@ -14476,16 +14095,16 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ __pyx_v_out = ((PyArrayObject *)__pyx_t_9); __pyx_t_9 = 0; - /* "_tree.pyx":980 + /* "stpredictions/models/OK3/_tree.pyx":980 * # Initialize output * cdef np.ndarray[SIZE_t] out = np.zeros((n_samples,), dtype=np.intp) * cdef SIZE_t* out_ptr = out.data # <<<<<<<<<<<<<< * * # Initialize auxiliary data-structure */ - __pyx_v_out_ptr = ((__pyx_t_5_tree_SIZE_t *)__pyx_v_out->data); + __pyx_v_out_ptr = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *)__pyx_v_out->data); - /* "_tree.pyx":983 + /* "stpredictions/models/OK3/_tree.pyx":983 * * # Initialize auxiliary data-structure * cdef Node* node = NULL # <<<<<<<<<<<<<< @@ -14494,7 +14113,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ */ __pyx_v_node = NULL; - /* "_tree.pyx":984 + /* "stpredictions/models/OK3/_tree.pyx":984 * # Initialize auxiliary data-structure * cdef Node* node = NULL * cdef SIZE_t i = 0 # <<<<<<<<<<<<<< @@ -14503,7 +14122,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ */ __pyx_v_i = 0; - /* "_tree.pyx":986 + /* "stpredictions/models/OK3/_tree.pyx":986 * cdef SIZE_t i = 0 * * with nogil: # <<<<<<<<<<<<<< @@ -14518,7 +14137,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ #endif /*try:*/ { - /* "_tree.pyx":987 + /* "stpredictions/models/OK3/_tree.pyx":987 * * with nogil: * for i in range(n_samples): # <<<<<<<<<<<<<< @@ -14530,7 +14149,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) { __pyx_v_i = __pyx_t_12; - /* "_tree.pyx":988 + /* "stpredictions/models/OK3/_tree.pyx":988 * with nogil: * for i in range(n_samples): * node = self.nodes # <<<<<<<<<<<<<< @@ -14540,7 +14159,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ __pyx_t_13 = __pyx_v_self->nodes; __pyx_v_node = __pyx_t_13; - /* "_tree.pyx":990 + /* "stpredictions/models/OK3/_tree.pyx":990 * node = self.nodes * # While node not a leaf * while node.left_child != _TREE_LEAF: # <<<<<<<<<<<<<< @@ -14548,10 +14167,10 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ * if X_ndarray[i, node.feature] <= node.threshold: */ while (1) { - __pyx_t_2 = ((__pyx_v_node->left_child != __pyx_v_5_tree__TREE_LEAF) != 0); + __pyx_t_2 = ((__pyx_v_node->left_child != __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF) != 0); if (!__pyx_t_2) break; - /* "_tree.pyx":992 + /* "stpredictions/models/OK3/_tree.pyx":992 * while node.left_child != _TREE_LEAF: * # ... and node.right_child != _TREE_LEAF: * if X_ndarray[i, node.feature] <= node.threshold: # <<<<<<<<<<<<<< @@ -14560,10 +14179,10 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ */ __pyx_t_14 = __pyx_v_i; __pyx_t_15 = __pyx_v_node->feature; - __pyx_t_2 = (((*((__pyx_t_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X_ndarray.data + __pyx_t_14 * __pyx_v_X_ndarray.strides[0]) ) + __pyx_t_15 * __pyx_v_X_ndarray.strides[1]) ))) <= __pyx_v_node->threshold) != 0); + __pyx_t_2 = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X_ndarray.data + __pyx_t_14 * __pyx_v_X_ndarray.strides[0]) ) + __pyx_t_15 * __pyx_v_X_ndarray.strides[1]) ))) <= __pyx_v_node->threshold) != 0); if (__pyx_t_2) { - /* "_tree.pyx":993 + /* "stpredictions/models/OK3/_tree.pyx":993 * # ... and node.right_child != _TREE_LEAF: * if X_ndarray[i, node.feature] <= node.threshold: * node = &self.nodes[node.left_child] # <<<<<<<<<<<<<< @@ -14572,7 +14191,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ */ __pyx_v_node = (&(__pyx_v_self->nodes[__pyx_v_node->left_child])); - /* "_tree.pyx":992 + /* "stpredictions/models/OK3/_tree.pyx":992 * while node.left_child != _TREE_LEAF: * # ... and node.right_child != _TREE_LEAF: * if X_ndarray[i, node.feature] <= node.threshold: # <<<<<<<<<<<<<< @@ -14582,7 +14201,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ goto __pyx_L12; } - /* "_tree.pyx":995 + /* "stpredictions/models/OK3/_tree.pyx":995 * node = &self.nodes[node.left_child] * else: * node = &self.nodes[node.right_child] # <<<<<<<<<<<<<< @@ -14595,18 +14214,18 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ __pyx_L12:; } - /* "_tree.pyx":997 + /* "stpredictions/models/OK3/_tree.pyx":997 * node = &self.nodes[node.right_child] * * out_ptr[i] = (node - self.nodes) # node offset # <<<<<<<<<<<<<< * * return out */ - (__pyx_v_out_ptr[__pyx_v_i]) = ((__pyx_t_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); + (__pyx_v_out_ptr[__pyx_v_i]) = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); } } - /* "_tree.pyx":986 + /* "stpredictions/models/OK3/_tree.pyx":986 * cdef SIZE_t i = 0 * * with nogil: # <<<<<<<<<<<<<< @@ -14625,7 +14244,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ } } - /* "_tree.pyx":999 + /* "stpredictions/models/OK3/_tree.pyx":999 * out_ptr[i] = (node - self.nodes) # node offset * * return out # <<<<<<<<<<<<<< @@ -14637,7 +14256,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ __pyx_r = ((PyArrayObject *)__pyx_v_out); goto __pyx_L0; - /* "_tree.pyx":963 + /* "stpredictions/models/OK3/_tree.pyx":963 * return self._apply_dense(X) * * cdef inline np.ndarray _apply_dense(self, object X): # <<<<<<<<<<<<<< @@ -14659,7 +14278,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ __Pyx_ErrFetch(&__pyx_type, &__pyx_value, &__pyx_tb); __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_out.rcbuffer->pybuffer); __Pyx_ErrRestore(__pyx_type, __pyx_value, __pyx_tb);} - __Pyx_AddTraceback("_tree.Tree._apply_dense", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree._apply_dense", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; goto __pyx_L2; __pyx_L0:; @@ -14672,7 +14291,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ return __pyx_r; } -/* "_tree.pyx":1001 +/* "stpredictions/models/OK3/_tree.pyx":1001 * return out * * cdef inline np.ndarray _apply_sparse_csr(self, object X): # <<<<<<<<<<<<<< @@ -14680,23 +14299,23 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_dense(struct __pyx_obj_5_tree_ * """ */ -static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X) { +static PyArrayObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X) { PyArrayObject *__pyx_v_X_data_ndarray = 0; PyArrayObject *__pyx_v_X_indices_ndarray = 0; PyArrayObject *__pyx_v_X_indptr_ndarray = 0; - __pyx_t_5_tree_DTYPE_t *__pyx_v_X_data; - __pyx_t_5_tree_INT32_t *__pyx_v_X_indices; - __pyx_t_5_tree_INT32_t *__pyx_v_X_indptr; - __pyx_t_5_tree_SIZE_t __pyx_v_n_samples; - __pyx_t_5_tree_SIZE_t __pyx_v_n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_X_data; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_X_indices; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_X_indptr; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_features; PyArrayObject *__pyx_v_out = 0; - __pyx_t_5_tree_SIZE_t *__pyx_v_out_ptr; - __pyx_t_5_tree_DTYPE_t __pyx_v_feature_value; - struct __pyx_t_5_tree_Node *__pyx_v_node; - __pyx_t_5_tree_DTYPE_t *__pyx_v_X_sample; - __pyx_t_5_tree_SIZE_t __pyx_v_i; - __pyx_t_5_tree_INT32_t __pyx_v_k; - __pyx_t_5_tree_SIZE_t *__pyx_v_feature_to_sample; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_out_ptr; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_feature_value; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_node; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_X_sample; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_i; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_v_k; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_feature_to_sample; __Pyx_LocalBuf_ND __pyx_pybuffernd_X_data_ndarray; __Pyx_Buffer __pyx_pybuffer_X_data_ndarray; __Pyx_LocalBuf_ND __pyx_pybuffernd_X_indices_ndarray; @@ -14715,16 +14334,16 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ PyArrayObject *__pyx_t_6 = NULL; PyArrayObject *__pyx_t_7 = NULL; PyArrayObject *__pyx_t_8 = NULL; - __pyx_t_5_tree_SIZE_t __pyx_t_9; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_9; PyObject *__pyx_t_10 = NULL; PyObject *__pyx_t_11 = NULL; PyArrayObject *__pyx_t_12 = NULL; - __pyx_t_5_tree_SIZE_t __pyx_t_13; - __pyx_t_5_tree_SIZE_t __pyx_t_14; - struct __pyx_t_5_tree_Node *__pyx_t_15; - __pyx_t_5_tree_INT32_t __pyx_t_16; - __pyx_t_5_tree_INT32_t __pyx_t_17; - __pyx_t_5_tree_INT32_t __pyx_t_18; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_13; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_14; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_t_15; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_t_16; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_t_17; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_t_18; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -14746,7 +14365,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_pybuffernd_out.data = NULL; __pyx_pybuffernd_out.rcbuffer = &__pyx_pybuffer_out; - /* "_tree.pyx":1005 + /* "stpredictions/models/OK3/_tree.pyx":1005 * """ * # Check input * if not isinstance(X, csr_matrix): # <<<<<<<<<<<<<< @@ -14760,7 +14379,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_t_3 = ((!(__pyx_t_2 != 0)) != 0); if (unlikely(__pyx_t_3)) { - /* "_tree.pyx":1007 + /* "stpredictions/models/OK3/_tree.pyx":1007 * if not isinstance(X, csr_matrix): * raise ValueError("X should be in csr_matrix format, got %s" * % type(X)) # <<<<<<<<<<<<<< @@ -14770,7 +14389,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_t_1 = __Pyx_PyString_FormatSafe(__pyx_kp_s_X_should_be_in_csr_matrix_format, ((PyObject *)Py_TYPE(__pyx_v_X))); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 1007, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - /* "_tree.pyx":1006 + /* "stpredictions/models/OK3/_tree.pyx":1006 * # Check input * if not isinstance(X, csr_matrix): * raise ValueError("X should be in csr_matrix format, got %s" # <<<<<<<<<<<<<< @@ -14784,7 +14403,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __PYX_ERR(0, 1006, __pyx_L1_error) - /* "_tree.pyx":1005 + /* "stpredictions/models/OK3/_tree.pyx":1005 * """ * # Check input * if not isinstance(X, csr_matrix): # <<<<<<<<<<<<<< @@ -14793,7 +14412,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ } - /* "_tree.pyx":1009 + /* "stpredictions/models/OK3/_tree.pyx":1009 * % type(X)) * * if X.dtype != DTYPE: # <<<<<<<<<<<<<< @@ -14811,7 +14430,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; if (unlikely(__pyx_t_3)) { - /* "_tree.pyx":1010 + /* "stpredictions/models/OK3/_tree.pyx":1010 * * if X.dtype != DTYPE: * raise ValueError("X.dtype should be np.float32, got %s" % X.dtype) # <<<<<<<<<<<<<< @@ -14830,7 +14449,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __PYX_ERR(0, 1010, __pyx_L1_error) - /* "_tree.pyx":1009 + /* "stpredictions/models/OK3/_tree.pyx":1009 * % type(X)) * * if X.dtype != DTYPE: # <<<<<<<<<<<<<< @@ -14839,7 +14458,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ } - /* "_tree.pyx":1013 + /* "stpredictions/models/OK3/_tree.pyx":1013 * * # Extract input * cdef np.ndarray[ndim=1, dtype=DTYPE_t] X_data_ndarray = X.data # <<<<<<<<<<<<<< @@ -14852,7 +14471,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_t_6 = ((PyArrayObject *)__pyx_t_5); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X_data_ndarray.rcbuffer->pybuffer, (PyObject*)__pyx_t_6, &__Pyx_TypeInfo_nn___pyx_t_5_tree_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X_data_ndarray.rcbuffer->pybuffer, (PyObject*)__pyx_t_6, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_X_data_ndarray = ((PyArrayObject *)Py_None); 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__Pyx_INCREF(Py_None); __pyx_pybuffernd_X_indices_ndarray.rcbuffer->pybuffer.buf = NULL; __PYX_ERR(0, 1014, __pyx_L1_error) } else {__pyx_pybuffernd_X_indices_ndarray.diminfo[0].strides = __pyx_pybuffernd_X_indices_ndarray.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_X_indices_ndarray.diminfo[0].shape = __pyx_pybuffernd_X_indices_ndarray.rcbuffer->pybuffer.shape[0]; @@ -14885,7 +14504,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_v_X_indices_ndarray = ((PyArrayObject *)__pyx_t_5); __pyx_t_5 = 0; - /* "_tree.pyx":1015 + /* "stpredictions/models/OK3/_tree.pyx":1015 * cdef np.ndarray[ndim=1, dtype=DTYPE_t] X_data_ndarray = X.data * cdef np.ndarray[ndim=1, dtype=INT32_t] X_indices_ndarray = X.indices * cdef np.ndarray[ndim=1, dtype=INT32_t] X_indptr_ndarray = X.indptr # <<<<<<<<<<<<<< @@ -14898,7 +14517,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_t_8 = ((PyArrayObject *)__pyx_t_5); { __Pyx_BufFmt_StackElem __pyx_stack[1]; 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__pyx_t_5 = 0; - /* "_tree.pyx":1017 + /* "stpredictions/models/OK3/_tree.pyx":1017 * cdef np.ndarray[ndim=1, dtype=INT32_t] X_indptr_ndarray = X.indptr * * cdef DTYPE_t* X_data = X_data_ndarray.data # <<<<<<<<<<<<<< * cdef INT32_t* X_indices = X_indices_ndarray.data * cdef INT32_t* X_indptr = X_indptr_ndarray.data */ - __pyx_v_X_data = ((__pyx_t_5_tree_DTYPE_t *)__pyx_v_X_data_ndarray->data); + __pyx_v_X_data = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *)__pyx_v_X_data_ndarray->data); - /* "_tree.pyx":1018 + /* "stpredictions/models/OK3/_tree.pyx":1018 * * cdef DTYPE_t* X_data = X_data_ndarray.data * cdef INT32_t* X_indices = X_indices_ndarray.data # <<<<<<<<<<<<<< * cdef INT32_t* X_indptr = X_indptr_ndarray.data * */ - __pyx_v_X_indices = ((__pyx_t_5_tree_INT32_t *)__pyx_v_X_indices_ndarray->data); + __pyx_v_X_indices = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *)__pyx_v_X_indices_ndarray->data); - /* "_tree.pyx":1019 + /* "stpredictions/models/OK3/_tree.pyx":1019 * cdef DTYPE_t* X_data = X_data_ndarray.data * cdef INT32_t* X_indices = X_indices_ndarray.data * cdef INT32_t* X_indptr = X_indptr_ndarray.data # <<<<<<<<<<<<<< * * cdef SIZE_t n_samples = X.shape[0] */ - __pyx_v_X_indptr = ((__pyx_t_5_tree_INT32_t *)__pyx_v_X_indptr_ndarray->data); + __pyx_v_X_indptr = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *)__pyx_v_X_indptr_ndarray->data); - /* "_tree.pyx":1021 + /* "stpredictions/models/OK3/_tree.pyx":1021 * cdef INT32_t* X_indptr = X_indptr_ndarray.data * * cdef SIZE_t n_samples = X.shape[0] # <<<<<<<<<<<<<< @@ -14951,7 +14570,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_n_samples = __pyx_t_9; - /* "_tree.pyx":1022 + /* "stpredictions/models/OK3/_tree.pyx":1022 * * cdef SIZE_t n_samples = X.shape[0] * cdef SIZE_t n_features = X.shape[1] # <<<<<<<<<<<<<< @@ -14967,7 +14586,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __pyx_v_n_features = __pyx_t_9; - /* "_tree.pyx":1025 + /* "stpredictions/models/OK3/_tree.pyx":1025 * * # Initialize output * cdef np.ndarray[SIZE_t, ndim=1] out = np.zeros((n_samples,), # <<<<<<<<<<<<<< @@ -14992,7 +14611,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_t_4); __pyx_t_4 = 0; - /* "_tree.pyx":1026 + /* "stpredictions/models/OK3/_tree.pyx":1026 * # Initialize output * cdef np.ndarray[SIZE_t, ndim=1] out = np.zeros((n_samples,), * dtype=np.intp) # <<<<<<<<<<<<<< @@ -15009,7 +14628,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ if (PyDict_SetItem(__pyx_t_4, __pyx_n_s_dtype, __pyx_t_11) < 0) __PYX_ERR(0, 1026, __pyx_L1_error) __Pyx_DECREF(__pyx_t_11); __pyx_t_11 = 0; - /* "_tree.pyx":1025 + /* "stpredictions/models/OK3/_tree.pyx":1025 * * # Initialize output * cdef np.ndarray[SIZE_t, ndim=1] out = np.zeros((n_samples,), # <<<<<<<<<<<<<< @@ -15025,7 +14644,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_t_12 = ((PyArrayObject *)__pyx_t_11); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_out.rcbuffer->pybuffer, (PyObject*)__pyx_t_12, &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_out.rcbuffer->pybuffer, (PyObject*)__pyx_t_12, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_out = ((PyArrayObject *)Py_None); 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- /* "_tree.pyx":1031 + /* "stpredictions/models/OK3/_tree.pyx":1031 * # Initialize auxiliary data-structure * cdef DTYPE_t feature_value = 0. * cdef Node* node = NULL # <<<<<<<<<<<<<< @@ -15062,7 +14681,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ __pyx_v_node = NULL; - /* "_tree.pyx":1032 + /* "stpredictions/models/OK3/_tree.pyx":1032 * cdef DTYPE_t feature_value = 0. * cdef Node* node = NULL * cdef DTYPE_t* X_sample = NULL # <<<<<<<<<<<<<< @@ -15071,7 +14690,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ __pyx_v_X_sample = NULL; - /* "_tree.pyx":1033 + /* "stpredictions/models/OK3/_tree.pyx":1033 * cdef Node* node = NULL * cdef DTYPE_t* X_sample = NULL * cdef SIZE_t i = 0 # <<<<<<<<<<<<<< @@ -15080,7 +14699,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ __pyx_v_i = 0; - /* "_tree.pyx":1034 + /* "stpredictions/models/OK3/_tree.pyx":1034 * cdef DTYPE_t* X_sample = NULL * cdef SIZE_t i = 0 * cdef INT32_t k = 0 # <<<<<<<<<<<<<< @@ -15089,7 +14708,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ __pyx_v_k = 0; - /* "_tree.pyx":1039 + /* "stpredictions/models/OK3/_tree.pyx":1039 * # for each feature; functionally, it is an efficient way to identify * # which features are nonzero in the present sample. * cdef SIZE_t* feature_to_sample = NULL # <<<<<<<<<<<<<< @@ -15098,25 +14717,25 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ __pyx_v_feature_to_sample = NULL; - /* "_tree.pyx":1041 + /* "stpredictions/models/OK3/_tree.pyx":1041 * cdef SIZE_t* feature_to_sample = NULL * * safe_realloc(&X_sample, n_features) # <<<<<<<<<<<<<< * safe_realloc(&feature_to_sample, n_features) * */ - __pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_X_sample), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 1041, __pyx_L1_error) + __pyx_fuse_0__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_X_sample), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 1041, __pyx_L1_error) - /* "_tree.pyx":1042 + /* "stpredictions/models/OK3/_tree.pyx":1042 * * safe_realloc(&X_sample, n_features) * safe_realloc(&feature_to_sample, n_features) # <<<<<<<<<<<<<< * * with nogil: */ - __pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_feature_to_sample), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 1042, __pyx_L1_error) + __pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_feature_to_sample), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 1042, __pyx_L1_error) - /* "_tree.pyx":1044 + /* "stpredictions/models/OK3/_tree.pyx":1044 * safe_realloc(&feature_to_sample, n_features) * * with nogil: # <<<<<<<<<<<<<< @@ -15131,16 +14750,16 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ #endif /*try:*/ { - /* "_tree.pyx":1045 + /* "stpredictions/models/OK3/_tree.pyx":1045 * * with nogil: * memset(feature_to_sample, -1, n_features * sizeof(SIZE_t)) # <<<<<<<<<<<<<< * * for i in range(n_samples): */ - (void)(memset(__pyx_v_feature_to_sample, -1, (__pyx_v_n_features * (sizeof(__pyx_t_5_tree_SIZE_t))))); + (void)(memset(__pyx_v_feature_to_sample, -1, (__pyx_v_n_features * (sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t))))); - /* "_tree.pyx":1047 + /* "stpredictions/models/OK3/_tree.pyx":1047 * memset(feature_to_sample, -1, n_features * sizeof(SIZE_t)) * * for i in range(n_samples): # <<<<<<<<<<<<<< @@ -15152,7 +14771,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ for (__pyx_t_14 = 0; __pyx_t_14 < __pyx_t_13; __pyx_t_14+=1) { __pyx_v_i = __pyx_t_14; - /* "_tree.pyx":1048 + /* "stpredictions/models/OK3/_tree.pyx":1048 * * for i in range(n_samples): * node = self.nodes # <<<<<<<<<<<<<< @@ -15162,7 +14781,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_t_15 = __pyx_v_self->nodes; __pyx_v_node = __pyx_t_15; - /* "_tree.pyx":1050 + /* "stpredictions/models/OK3/_tree.pyx":1050 * node = self.nodes * * for k in range(X_indptr[i], X_indptr[i + 1]): # <<<<<<<<<<<<<< @@ -15174,7 +14793,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ for (__pyx_t_18 = (__pyx_v_X_indptr[__pyx_v_i]); __pyx_t_18 < __pyx_t_17; __pyx_t_18+=1) { __pyx_v_k = __pyx_t_18; - /* "_tree.pyx":1051 + /* "stpredictions/models/OK3/_tree.pyx":1051 * * for k in range(X_indptr[i], X_indptr[i + 1]): * feature_to_sample[X_indices[k]] = i # <<<<<<<<<<<<<< @@ -15183,7 +14802,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ (__pyx_v_feature_to_sample[(__pyx_v_X_indices[__pyx_v_k])]) = __pyx_v_i; - /* "_tree.pyx":1052 + /* "stpredictions/models/OK3/_tree.pyx":1052 * for k in range(X_indptr[i], X_indptr[i + 1]): * feature_to_sample[X_indices[k]] = i * X_sample[X_indices[k]] = X_data[k] # <<<<<<<<<<<<<< @@ -15193,7 +14812,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ (__pyx_v_X_sample[(__pyx_v_X_indices[__pyx_v_k])]) = (__pyx_v_X_data[__pyx_v_k]); } - /* "_tree.pyx":1055 + /* "stpredictions/models/OK3/_tree.pyx":1055 * * # While node not a leaf * while node.left_child != _TREE_LEAF: # <<<<<<<<<<<<<< @@ -15201,10 +14820,10 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ * if feature_to_sample[node.feature] == i: */ while (1) { - __pyx_t_3 = ((__pyx_v_node->left_child != __pyx_v_5_tree__TREE_LEAF) != 0); + __pyx_t_3 = ((__pyx_v_node->left_child != __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF) != 0); if (!__pyx_t_3) break; - /* "_tree.pyx":1057 + /* "stpredictions/models/OK3/_tree.pyx":1057 * while node.left_child != _TREE_LEAF: * # ... and node.right_child != _TREE_LEAF: * if feature_to_sample[node.feature] == i: # <<<<<<<<<<<<<< @@ -15214,7 +14833,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_t_3 = (((__pyx_v_feature_to_sample[__pyx_v_node->feature]) == __pyx_v_i) != 0); if (__pyx_t_3) { - /* "_tree.pyx":1058 + /* "stpredictions/models/OK3/_tree.pyx":1058 * # ... and node.right_child != _TREE_LEAF: * if feature_to_sample[node.feature] == i: * feature_value = X_sample[node.feature] # <<<<<<<<<<<<<< @@ -15223,7 +14842,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ __pyx_v_feature_value = (__pyx_v_X_sample[__pyx_v_node->feature]); - /* "_tree.pyx":1057 + /* "stpredictions/models/OK3/_tree.pyx":1057 * while node.left_child != _TREE_LEAF: * # ... and node.right_child != _TREE_LEAF: * if feature_to_sample[node.feature] == i: # <<<<<<<<<<<<<< @@ -15233,7 +14852,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ goto __pyx_L14; } - /* "_tree.pyx":1061 + /* "stpredictions/models/OK3/_tree.pyx":1061 * * else: * feature_value = 0. # <<<<<<<<<<<<<< @@ -15245,7 +14864,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ } __pyx_L14:; - /* "_tree.pyx":1063 + /* "stpredictions/models/OK3/_tree.pyx":1063 * feature_value = 0. * * if feature_value <= node.threshold: # <<<<<<<<<<<<<< @@ -15255,7 +14874,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_t_3 = ((__pyx_v_feature_value <= __pyx_v_node->threshold) != 0); if (__pyx_t_3) { - /* "_tree.pyx":1064 + /* "stpredictions/models/OK3/_tree.pyx":1064 * * if feature_value <= node.threshold: * node = &self.nodes[node.left_child] # <<<<<<<<<<<<<< @@ -15264,7 +14883,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ __pyx_v_node = (&(__pyx_v_self->nodes[__pyx_v_node->left_child])); - /* "_tree.pyx":1063 + /* "stpredictions/models/OK3/_tree.pyx":1063 * feature_value = 0. * * if feature_value <= node.threshold: # <<<<<<<<<<<<<< @@ -15274,7 +14893,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ goto __pyx_L15; } - /* "_tree.pyx":1066 + /* "stpredictions/models/OK3/_tree.pyx":1066 * node = &self.nodes[node.left_child] * else: * node = &self.nodes[node.right_child] # <<<<<<<<<<<<<< @@ -15287,17 +14906,17 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_L15:; } - /* "_tree.pyx":1068 + /* "stpredictions/models/OK3/_tree.pyx":1068 * node = &self.nodes[node.right_child] * * out_ptr[i] = (node - self.nodes) # node offset # <<<<<<<<<<<<<< * * # Free auxiliary arrays */ - (__pyx_v_out_ptr[__pyx_v_i]) = ((__pyx_t_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); + (__pyx_v_out_ptr[__pyx_v_i]) = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); } - /* "_tree.pyx":1071 + /* "stpredictions/models/OK3/_tree.pyx":1071 * * # Free auxiliary arrays * free(X_sample) # <<<<<<<<<<<<<< @@ -15306,7 +14925,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ */ free(__pyx_v_X_sample); - /* "_tree.pyx":1072 + /* "stpredictions/models/OK3/_tree.pyx":1072 * # Free auxiliary arrays * free(X_sample) * free(feature_to_sample) # <<<<<<<<<<<<<< @@ -15316,7 +14935,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ free(__pyx_v_feature_to_sample); } - /* "_tree.pyx":1044 + /* "stpredictions/models/OK3/_tree.pyx":1044 * safe_realloc(&feature_to_sample, n_features) * * with nogil: # <<<<<<<<<<<<<< @@ -15335,7 +14954,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ } } - /* "_tree.pyx":1074 + /* "stpredictions/models/OK3/_tree.pyx":1074 * free(feature_to_sample) * * return out # <<<<<<<<<<<<<< @@ -15347,7 +14966,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __pyx_r = ((PyArrayObject *)__pyx_v_out); goto __pyx_L0; - /* "_tree.pyx":1001 + /* "stpredictions/models/OK3/_tree.pyx":1001 * return out * * cdef inline np.ndarray _apply_sparse_csr(self, object X): # <<<<<<<<<<<<<< @@ -15371,7 +14990,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_X_indptr_ndarray.rcbuffer->pybuffer); __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_out.rcbuffer->pybuffer); __Pyx_ErrRestore(__pyx_type, __pyx_value, __pyx_tb);} - __Pyx_AddTraceback("_tree.Tree._apply_sparse_csr", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree._apply_sparse_csr", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; goto __pyx_L2; __pyx_L0:; @@ -15389,7 +15008,7 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ return __pyx_r; } -/* "_tree.pyx":1076 +/* "stpredictions/models/OK3/_tree.pyx":1076 * return out * * cpdef object decision_path(self, object X): # <<<<<<<<<<<<<< @@ -15397,8 +15016,8 @@ static PyArrayObject *__pyx_f_5_tree_4Tree__apply_sparse_csr(struct __pyx_obj_5_ * if issparse(X): */ -static PyObject *__pyx_pw_5_tree_4Tree_17decision_path(PyObject *__pyx_v_self, PyObject *__pyx_v_X); /*proto*/ -static PyObject *__pyx_f_5_tree_4Tree_decision_path(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_17decision_path(PyObject *__pyx_v_self, PyObject *__pyx_v_X); /*proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_decision_path(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X, int __pyx_skip_dispatch) { PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -15421,7 +15040,7 @@ static PyObject *__pyx_f_5_tree_4Tree_decision_path(struct __pyx_obj_5_tree_Tree #endif __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_self), __pyx_n_s_decision_path); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 1076, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_5_tree_4Tree_17decision_path)) { + if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_17decision_path)) { __Pyx_XDECREF(__pyx_r); __Pyx_INCREF(__pyx_t_1); __pyx_t_3 = __pyx_t_1; __pyx_t_4 = NULL; @@ -15457,7 +15076,7 @@ static PyObject *__pyx_f_5_tree_4Tree_decision_path(struct __pyx_obj_5_tree_Tree #endif } - /* "_tree.pyx":1078 + /* "stpredictions/models/OK3/_tree.pyx":1078 * cpdef object decision_path(self, object X): * """Finds the decision path (=node) for each sample in X.""" * if issparse(X): # <<<<<<<<<<<<<< @@ -15485,7 +15104,7 @@ static PyObject *__pyx_f_5_tree_4Tree_decision_path(struct __pyx_obj_5_tree_Tree __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; if (__pyx_t_5) { - /* "_tree.pyx":1079 + /* "stpredictions/models/OK3/_tree.pyx":1079 * """Finds the decision path (=node) for each sample in X.""" * if issparse(X): * return self._decision_path_sparse_csr(X) # <<<<<<<<<<<<<< @@ -15493,13 +15112,13 @@ static PyObject *__pyx_f_5_tree_4Tree_decision_path(struct __pyx_obj_5_tree_Tree * return self._decision_path_dense(X) */ __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = __pyx_f_5_tree_4Tree__decision_path_sparse_csr(__pyx_v_self, __pyx_v_X); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 1079, __pyx_L1_error) + __pyx_t_1 = __pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__decision_path_sparse_csr(__pyx_v_self, __pyx_v_X); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 1079, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; goto __pyx_L0; - /* "_tree.pyx":1078 + /* "stpredictions/models/OK3/_tree.pyx":1078 * cpdef object decision_path(self, object X): * """Finds the decision path (=node) for each sample in X.""" * if issparse(X): # <<<<<<<<<<<<<< @@ -15508,7 +15127,7 @@ static PyObject *__pyx_f_5_tree_4Tree_decision_path(struct __pyx_obj_5_tree_Tree */ } - /* "_tree.pyx":1081 + /* "stpredictions/models/OK3/_tree.pyx":1081 * return self._decision_path_sparse_csr(X) * else: * return self._decision_path_dense(X) # <<<<<<<<<<<<<< @@ -15517,14 +15136,14 @@ static PyObject *__pyx_f_5_tree_4Tree_decision_path(struct __pyx_obj_5_tree_Tree */ /*else*/ { __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = __pyx_f_5_tree_4Tree__decision_path_dense(__pyx_v_self, __pyx_v_X); 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/*proto*/ -static char __pyx_doc_5_tree_4Tree_16decision_path[] = "Finds the decision path (=node) for each sample in X."; -static PyObject *__pyx_pw_5_tree_4Tree_17decision_path(PyObject *__pyx_v_self, PyObject *__pyx_v_X) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_17decision_path(PyObject *__pyx_v_self, PyObject *__pyx_v_X); /*proto*/ +static char __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_16decision_path[] = "Finds the decision path (=node) for each sample in X."; +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_17decision_path(PyObject *__pyx_v_self, PyObject *__pyx_v_X) { PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("decision_path (wrapper)", 0); - __pyx_r = __pyx_pf_5_tree_4Tree_16decision_path(((struct __pyx_obj_5_tree_Tree *)__pyx_v_self), ((PyObject *)__pyx_v_X)); + __pyx_r = __pyx_pf_13stpredictions_6models_3OK3_5_tree_4Tree_16decision_path(((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_self), ((PyObject *)__pyx_v_X)); 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__Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - /* "_tree.pyx":1103 + /* "stpredictions/models/OK3/_tree.pyx":1103 * * cdef np.ndarray[SIZE_t] indices = np.zeros(n_samples * * (1 + self.max_depth), # <<<<<<<<<<<<<< @@ -15851,7 +15470,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr __pyx_t_9 = __Pyx_PyInt_From_long((__pyx_v_n_samples * (1 + __pyx_v_self->max_depth))); if (unlikely(!__pyx_t_9)) __PYX_ERR(0, 1102, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_9); - /* "_tree.pyx":1102 + /* "stpredictions/models/OK3/_tree.pyx":1102 * cdef SIZE_t* indptr_ptr = indptr.data * * cdef np.ndarray[SIZE_t] indices = np.zeros(n_samples * # <<<<<<<<<<<<<< @@ -15864,7 +15483,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_9); __pyx_t_9 = 0; - /* "_tree.pyx":1104 + /* "stpredictions/models/OK3/_tree.pyx":1104 * cdef np.ndarray[SIZE_t] indices = np.zeros(n_samples * * (1 + self.max_depth), * dtype=np.intp) # <<<<<<<<<<<<<< @@ -15881,7 +15500,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr if (PyDict_SetItem(__pyx_t_9, __pyx_n_s_dtype, __pyx_t_8) < 0) __PYX_ERR(0, 1104, __pyx_L1_error) __Pyx_DECREF(__pyx_t_8); 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- /* "_tree.pyx":1117 + /* "stpredictions/models/OK3/_tree.pyx":1117 * * # Add all external nodes * while node.left_child != _TREE_LEAF: # <<<<<<<<<<<<<< @@ -15988,19 +15607,19 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr * indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) */ while (1) { - __pyx_t_2 = ((__pyx_v_node->left_child != __pyx_v_5_tree__TREE_LEAF) != 0); + __pyx_t_2 = ((__pyx_v_node->left_child != __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF) != 0); if (!__pyx_t_2) break; - /* "_tree.pyx":1119 + /* "stpredictions/models/OK3/_tree.pyx":1119 * while node.left_child != _TREE_LEAF: * # ... and node.right_child != _TREE_LEAF: * indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) # <<<<<<<<<<<<<< * indptr_ptr[i + 1] += 1 * */ - (__pyx_v_indices_ptr[(__pyx_v_indptr_ptr[(__pyx_v_i + 1)])]) = ((__pyx_t_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); + (__pyx_v_indices_ptr[(__pyx_v_indptr_ptr[(__pyx_v_i + 1)])]) = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); - /* "_tree.pyx":1120 + /* "stpredictions/models/OK3/_tree.pyx":1120 * # ... and node.right_child != _TREE_LEAF: * indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) * indptr_ptr[i + 1] += 1 # <<<<<<<<<<<<<< @@ -16010,7 +15629,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr __pyx_t_15 = (__pyx_v_i + 1); (__pyx_v_indptr_ptr[__pyx_t_15]) = ((__pyx_v_indptr_ptr[__pyx_t_15]) + 1); - /* "_tree.pyx":1122 + /* "stpredictions/models/OK3/_tree.pyx":1122 * indptr_ptr[i + 1] += 1 * * if X_ndarray[i, node.feature] <= node.threshold: # <<<<<<<<<<<<<< @@ -16019,10 +15638,10 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr */ __pyx_t_16 = __pyx_v_i; __pyx_t_17 = __pyx_v_node->feature; - __pyx_t_2 = (((*((__pyx_t_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X_ndarray.data + __pyx_t_16 * __pyx_v_X_ndarray.strides[0]) ) + __pyx_t_17 * __pyx_v_X_ndarray.strides[1]) ))) <= __pyx_v_node->threshold) != 0); + __pyx_t_2 = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t const *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X_ndarray.data + __pyx_t_16 * __pyx_v_X_ndarray.strides[0]) ) + __pyx_t_17 * __pyx_v_X_ndarray.strides[1]) ))) <= __pyx_v_node->threshold) != 0); if (__pyx_t_2) { - /* "_tree.pyx":1123 + /* "stpredictions/models/OK3/_tree.pyx":1123 * * if X_ndarray[i, node.feature] <= node.threshold: * node = &self.nodes[node.left_child] # <<<<<<<<<<<<<< @@ -16031,7 +15650,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr */ __pyx_v_node = (&(__pyx_v_self->nodes[__pyx_v_node->left_child])); - /* "_tree.pyx":1122 + /* "stpredictions/models/OK3/_tree.pyx":1122 * indptr_ptr[i + 1] += 1 * * if X_ndarray[i, node.feature] <= node.threshold: # <<<<<<<<<<<<<< @@ -16041,7 +15660,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr goto __pyx_L12; } - /* "_tree.pyx":1125 + /* "stpredictions/models/OK3/_tree.pyx":1125 * node = &self.nodes[node.left_child] * else: * node = &self.nodes[node.right_child] # <<<<<<<<<<<<<< @@ -16054,16 +15673,16 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr __pyx_L12:; } - /* "_tree.pyx":1128 + /* "stpredictions/models/OK3/_tree.pyx":1128 * * # Add the leave node * indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) # <<<<<<<<<<<<<< * indptr_ptr[i + 1] += 1 * */ - (__pyx_v_indices_ptr[(__pyx_v_indptr_ptr[(__pyx_v_i + 1)])]) = ((__pyx_t_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); + (__pyx_v_indices_ptr[(__pyx_v_indptr_ptr[(__pyx_v_i + 1)])]) = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); - /* "_tree.pyx":1129 + /* "stpredictions/models/OK3/_tree.pyx":1129 * # Add the leave node * indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) * indptr_ptr[i + 1] += 1 # <<<<<<<<<<<<<< @@ -16075,7 +15694,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr } } - /* "_tree.pyx":1111 + /* "stpredictions/models/OK3/_tree.pyx":1111 * cdef SIZE_t i = 0 * * with nogil: # <<<<<<<<<<<<<< @@ -16094,7 +15713,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr } } - /* "_tree.pyx":1131 + /* "stpredictions/models/OK3/_tree.pyx":1131 * indptr_ptr[i + 1] += 1 * * indices = indices[:indptr[n_samples]] # <<<<<<<<<<<<<< @@ -16102,7 +15721,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr * dtype=np.intp) */ __pyx_t_17 = __pyx_v_n_samples; - __pyx_t_8 = __Pyx_PyInt_From_Py_intptr_t((*__Pyx_BufPtrStrided1d(__pyx_t_5_tree_SIZE_t *, __pyx_pybuffernd_indptr.rcbuffer->pybuffer.buf, __pyx_t_17, __pyx_pybuffernd_indptr.diminfo[0].strides))); if (unlikely(!__pyx_t_8)) __PYX_ERR(0, 1131, __pyx_L1_error) + __pyx_t_8 = __Pyx_PyInt_From_Py_intptr_t((*__Pyx_BufPtrStrided1d(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_pybuffernd_indptr.rcbuffer->pybuffer.buf, __pyx_t_17, __pyx_pybuffernd_indptr.diminfo[0].strides))); if (unlikely(!__pyx_t_8)) __PYX_ERR(0, 1131, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_8); __pyx_t_9 = PySlice_New(Py_None, __pyx_t_8, Py_None); if (unlikely(!__pyx_t_9)) __PYX_ERR(0, 1131, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_9); @@ -16115,10 +15734,10 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr { __Pyx_BufFmt_StackElem __pyx_stack[1]; __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_indices.rcbuffer->pybuffer); - __pyx_t_18 = __Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_t_11, &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack); + __pyx_t_18 = __Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_t_11, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack); if (unlikely(__pyx_t_18 < 0)) { PyErr_Fetch(&__pyx_t_19, &__pyx_t_20, &__pyx_t_21); - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_v_indices, &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_v_indices, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { Py_XDECREF(__pyx_t_19); Py_XDECREF(__pyx_t_20); Py_XDECREF(__pyx_t_21); __Pyx_RaiseBufferFallbackError(); } else { @@ -16133,7 +15752,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr __Pyx_DECREF_SET(__pyx_v_indices, ((PyArrayObject *)__pyx_t_8)); __pyx_t_8 = 0; - /* "_tree.pyx":1132 + /* "stpredictions/models/OK3/_tree.pyx":1132 * * indices = indices[:indptr[n_samples]] * cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), # <<<<<<<<<<<<<< @@ -16153,7 +15772,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr if (PyDict_SetItem(__pyx_t_8, __pyx_n_s_shape, __pyx_t_4) < 0) __PYX_ERR(0, 1132, __pyx_L1_error) __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - /* "_tree.pyx":1133 + /* "stpredictions/models/OK3/_tree.pyx":1133 * indices = indices[:indptr[n_samples]] * cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), * dtype=np.intp) # <<<<<<<<<<<<<< @@ -16168,7 +15787,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr if (PyDict_SetItem(__pyx_t_8, __pyx_n_s_dtype, __pyx_t_3) < 0) __PYX_ERR(0, 1132, __pyx_L1_error) __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - /* "_tree.pyx":1132 + /* "stpredictions/models/OK3/_tree.pyx":1132 * * indices = indices[:indptr[n_samples]] * cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), # <<<<<<<<<<<<<< @@ -16183,7 +15802,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr __pyx_t_23 = ((PyArrayObject *)__pyx_t_3); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_data.rcbuffer->pybuffer, (PyObject*)__pyx_t_23, &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_data.rcbuffer->pybuffer, (PyObject*)__pyx_t_23, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_data = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_data.rcbuffer->pybuffer.buf = NULL; __PYX_ERR(0, 1132, __pyx_L1_error) } else {__pyx_pybuffernd_data.diminfo[0].strides = __pyx_pybuffernd_data.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_data.diminfo[0].shape = __pyx_pybuffernd_data.rcbuffer->pybuffer.shape[0]; @@ -16193,7 +15812,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr __pyx_v_data = ((PyArrayObject *)__pyx_t_3); __pyx_t_3 = 0; - /* "_tree.pyx":1134 + /* "stpredictions/models/OK3/_tree.pyx":1134 * cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), * dtype=np.intp) * out = csr_matrix((data, indices, indptr), # <<<<<<<<<<<<<< @@ -16219,7 +15838,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr PyTuple_SET_ITEM(__pyx_t_9, 0, __pyx_t_8); __pyx_t_8 = 0; - /* "_tree.pyx":1135 + /* "stpredictions/models/OK3/_tree.pyx":1135 * dtype=np.intp) * out = csr_matrix((data, indices, indptr), * shape=(n_samples, self.node_count)) # <<<<<<<<<<<<<< @@ -16243,7 +15862,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr if (PyDict_SetItem(__pyx_t_8, __pyx_n_s_shape, __pyx_t_24) < 0) __PYX_ERR(0, 1135, __pyx_L1_error) __Pyx_DECREF(__pyx_t_24); __pyx_t_24 = 0; - /* "_tree.pyx":1134 + /* "stpredictions/models/OK3/_tree.pyx":1134 * cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), * dtype=np.intp) * out = csr_matrix((data, indices, indptr), # <<<<<<<<<<<<<< @@ -16258,7 +15877,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr __pyx_v_out = __pyx_t_24; __pyx_t_24 = 0; - /* "_tree.pyx":1137 + /* "stpredictions/models/OK3/_tree.pyx":1137 * shape=(n_samples, self.node_count)) * * return out # <<<<<<<<<<<<<< @@ -16270,7 +15889,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr __pyx_r = __pyx_v_out; goto __pyx_L0; - /* "_tree.pyx":1083 + /* "stpredictions/models/OK3/_tree.pyx":1083 * return self._decision_path_dense(X) * * cdef inline object _decision_path_dense(self, object X): # <<<<<<<<<<<<<< @@ -16295,7 +15914,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_indices.rcbuffer->pybuffer); __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_indptr.rcbuffer->pybuffer); __Pyx_ErrRestore(__pyx_type, __pyx_value, __pyx_tb);} - __Pyx_AddTraceback("_tree.Tree._decision_path_dense", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree._decision_path_dense", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; goto __pyx_L2; __pyx_L0:; @@ -16313,7 +15932,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr return __pyx_r; } -/* "_tree.pyx":1139 +/* "stpredictions/models/OK3/_tree.pyx":1139 * return out * * cdef inline object _decision_path_sparse_csr(self, object X): # <<<<<<<<<<<<<< @@ -16321,25 +15940,25 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_dense(struct __pyx_obj_5_tr * */ -static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X) { +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_X) { PyArrayObject *__pyx_v_X_data_ndarray = 0; PyArrayObject *__pyx_v_X_indices_ndarray = 0; PyArrayObject *__pyx_v_X_indptr_ndarray = 0; - __pyx_t_5_tree_DTYPE_t *__pyx_v_X_data; - __pyx_t_5_tree_INT32_t *__pyx_v_X_indices; - __pyx_t_5_tree_INT32_t *__pyx_v_X_indptr; - __pyx_t_5_tree_SIZE_t __pyx_v_n_samples; - __pyx_t_5_tree_SIZE_t __pyx_v_n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_X_data; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_X_indices; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *__pyx_v_X_indptr; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_features; PyArrayObject *__pyx_v_indptr = 0; - __pyx_t_5_tree_SIZE_t *__pyx_v_indptr_ptr; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_indptr_ptr; PyArrayObject *__pyx_v_indices = 0; - __pyx_t_5_tree_SIZE_t *__pyx_v_indices_ptr; - __pyx_t_5_tree_DTYPE_t __pyx_v_feature_value; - struct __pyx_t_5_tree_Node *__pyx_v_node; - __pyx_t_5_tree_DTYPE_t *__pyx_v_X_sample; - __pyx_t_5_tree_SIZE_t __pyx_v_i; - __pyx_t_5_tree_INT32_t __pyx_v_k; - __pyx_t_5_tree_SIZE_t *__pyx_v_feature_to_sample; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_indices_ptr; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t __pyx_v_feature_value; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_node; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *__pyx_v_X_sample; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_i; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_v_k; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *__pyx_v_feature_to_sample; PyArrayObject *__pyx_v_data = 0; PyObject *__pyx_v_out = NULL; __Pyx_LocalBuf_ND __pyx_pybuffernd_X_data_ndarray; @@ -16364,17 +15983,17 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj PyArrayObject *__pyx_t_6 = NULL; PyArrayObject *__pyx_t_7 = NULL; PyArrayObject *__pyx_t_8 = NULL; - __pyx_t_5_tree_SIZE_t __pyx_t_9; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_9; PyObject *__pyx_t_10 = NULL; PyObject *__pyx_t_11 = NULL; PyArrayObject *__pyx_t_12 = NULL; PyArrayObject *__pyx_t_13 = NULL; - __pyx_t_5_tree_SIZE_t __pyx_t_14; - __pyx_t_5_tree_SIZE_t __pyx_t_15; - struct __pyx_t_5_tree_Node *__pyx_t_16; - __pyx_t_5_tree_INT32_t __pyx_t_17; - __pyx_t_5_tree_INT32_t __pyx_t_18; - __pyx_t_5_tree_INT32_t __pyx_t_19; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_14; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_15; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_t_16; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_t_17; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_t_18; + __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t __pyx_t_19; long __pyx_t_20; Py_ssize_t __pyx_t_21; int __pyx_t_22; @@ -16413,7 +16032,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_pybuffernd_data.data = NULL; __pyx_pybuffernd_data.rcbuffer = &__pyx_pybuffer_data; - /* "_tree.pyx":1143 + /* "stpredictions/models/OK3/_tree.pyx":1143 * * # Check input * if not isinstance(X, csr_matrix): # <<<<<<<<<<<<<< @@ -16427,7 +16046,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_3 = ((!(__pyx_t_2 != 0)) != 0); if (unlikely(__pyx_t_3)) { - /* "_tree.pyx":1145 + /* "stpredictions/models/OK3/_tree.pyx":1145 * if not isinstance(X, csr_matrix): * raise ValueError("X should be in csr_matrix format, got %s" * % type(X)) # <<<<<<<<<<<<<< @@ -16437,7 +16056,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_1 = __Pyx_PyString_FormatSafe(__pyx_kp_s_X_should_be_in_csr_matrix_format, ((PyObject *)Py_TYPE(__pyx_v_X))); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 1145, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - /* "_tree.pyx":1144 + /* "stpredictions/models/OK3/_tree.pyx":1144 * # Check input * if not isinstance(X, csr_matrix): * raise ValueError("X should be in csr_matrix format, got %s" # <<<<<<<<<<<<<< @@ -16451,7 +16070,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __PYX_ERR(0, 1144, __pyx_L1_error) - /* "_tree.pyx":1143 + /* "stpredictions/models/OK3/_tree.pyx":1143 * * # Check input * if not isinstance(X, csr_matrix): # <<<<<<<<<<<<<< @@ -16460,7 +16079,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ } - /* "_tree.pyx":1147 + /* "stpredictions/models/OK3/_tree.pyx":1147 * % type(X)) * * if X.dtype != DTYPE: # <<<<<<<<<<<<<< @@ -16478,7 +16097,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; if (unlikely(__pyx_t_3)) { - /* "_tree.pyx":1148 + /* "stpredictions/models/OK3/_tree.pyx":1148 * * if X.dtype != DTYPE: * raise ValueError("X.dtype should be np.float32, got %s" % X.dtype) # <<<<<<<<<<<<<< @@ -16497,7 +16116,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __PYX_ERR(0, 1148, __pyx_L1_error) - /* "_tree.pyx":1147 + /* "stpredictions/models/OK3/_tree.pyx":1147 * % type(X)) * * if X.dtype != DTYPE: # <<<<<<<<<<<<<< @@ -16506,7 +16125,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ } - /* "_tree.pyx":1151 + /* "stpredictions/models/OK3/_tree.pyx":1151 * * # Extract input * cdef np.ndarray[ndim=1, dtype=DTYPE_t] X_data_ndarray = X.data # <<<<<<<<<<<<<< @@ -16519,7 +16138,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_6 = ((PyArrayObject *)__pyx_t_5); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X_data_ndarray.rcbuffer->pybuffer, (PyObject*)__pyx_t_6, &__Pyx_TypeInfo_nn___pyx_t_5_tree_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X_data_ndarray.rcbuffer->pybuffer, (PyObject*)__pyx_t_6, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_X_data_ndarray = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_X_data_ndarray.rcbuffer->pybuffer.buf = NULL; __PYX_ERR(0, 1151, __pyx_L1_error) } else {__pyx_pybuffernd_X_data_ndarray.diminfo[0].strides = __pyx_pybuffernd_X_data_ndarray.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_X_data_ndarray.diminfo[0].shape = __pyx_pybuffernd_X_data_ndarray.rcbuffer->pybuffer.shape[0]; @@ -16529,7 +16148,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_v_X_data_ndarray = ((PyArrayObject *)__pyx_t_5); __pyx_t_5 = 0; - /* "_tree.pyx":1152 + /* "stpredictions/models/OK3/_tree.pyx":1152 * # Extract input * cdef np.ndarray[ndim=1, dtype=DTYPE_t] X_data_ndarray = X.data * cdef np.ndarray[ndim=1, dtype=INT32_t] X_indices_ndarray = X.indices # <<<<<<<<<<<<<< @@ -16542,7 +16161,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_7 = ((PyArrayObject *)__pyx_t_5); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X_indices_ndarray.rcbuffer->pybuffer, (PyObject*)__pyx_t_7, &__Pyx_TypeInfo_nn___pyx_t_5_tree_INT32_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X_indices_ndarray.rcbuffer->pybuffer, (PyObject*)__pyx_t_7, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_X_indices_ndarray = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_X_indices_ndarray.rcbuffer->pybuffer.buf = NULL; __PYX_ERR(0, 1152, __pyx_L1_error) } else {__pyx_pybuffernd_X_indices_ndarray.diminfo[0].strides = __pyx_pybuffernd_X_indices_ndarray.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_X_indices_ndarray.diminfo[0].shape = __pyx_pybuffernd_X_indices_ndarray.rcbuffer->pybuffer.shape[0]; @@ -16552,7 +16171,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_v_X_indices_ndarray = ((PyArrayObject *)__pyx_t_5); __pyx_t_5 = 0; - /* "_tree.pyx":1153 + /* "stpredictions/models/OK3/_tree.pyx":1153 * cdef np.ndarray[ndim=1, dtype=DTYPE_t] X_data_ndarray = X.data * cdef np.ndarray[ndim=1, dtype=INT32_t] X_indices_ndarray = X.indices * cdef np.ndarray[ndim=1, dtype=INT32_t] X_indptr_ndarray = X.indptr # <<<<<<<<<<<<<< @@ -16565,7 +16184,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_8 = ((PyArrayObject *)__pyx_t_5); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X_indptr_ndarray.rcbuffer->pybuffer, (PyObject*)__pyx_t_8, &__Pyx_TypeInfo_nn___pyx_t_5_tree_INT32_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_X_indptr_ndarray.rcbuffer->pybuffer, (PyObject*)__pyx_t_8, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_X_indptr_ndarray = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_X_indptr_ndarray.rcbuffer->pybuffer.buf = NULL; __PYX_ERR(0, 1153, __pyx_L1_error) } else {__pyx_pybuffernd_X_indptr_ndarray.diminfo[0].strides = __pyx_pybuffernd_X_indptr_ndarray.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_X_indptr_ndarray.diminfo[0].shape = __pyx_pybuffernd_X_indptr_ndarray.rcbuffer->pybuffer.shape[0]; @@ -16575,34 +16194,34 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_v_X_indptr_ndarray = ((PyArrayObject *)__pyx_t_5); __pyx_t_5 = 0; - /* "_tree.pyx":1155 + /* "stpredictions/models/OK3/_tree.pyx":1155 * cdef np.ndarray[ndim=1, dtype=INT32_t] X_indptr_ndarray = X.indptr * * cdef DTYPE_t* X_data = X_data_ndarray.data # <<<<<<<<<<<<<< * cdef INT32_t* X_indices = X_indices_ndarray.data * cdef INT32_t* X_indptr = X_indptr_ndarray.data */ - __pyx_v_X_data = ((__pyx_t_5_tree_DTYPE_t *)__pyx_v_X_data_ndarray->data); + __pyx_v_X_data = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *)__pyx_v_X_data_ndarray->data); - /* "_tree.pyx":1156 + /* "stpredictions/models/OK3/_tree.pyx":1156 * * cdef DTYPE_t* X_data = X_data_ndarray.data * cdef INT32_t* X_indices = X_indices_ndarray.data # <<<<<<<<<<<<<< * cdef INT32_t* X_indptr = X_indptr_ndarray.data * */ - __pyx_v_X_indices = ((__pyx_t_5_tree_INT32_t *)__pyx_v_X_indices_ndarray->data); + __pyx_v_X_indices = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *)__pyx_v_X_indices_ndarray->data); - /* "_tree.pyx":1157 + /* "stpredictions/models/OK3/_tree.pyx":1157 * cdef DTYPE_t* X_data = X_data_ndarray.data * cdef INT32_t* X_indices = X_indices_ndarray.data * cdef INT32_t* X_indptr = X_indptr_ndarray.data # <<<<<<<<<<<<<< * * cdef SIZE_t n_samples = X.shape[0] */ - __pyx_v_X_indptr = ((__pyx_t_5_tree_INT32_t *)__pyx_v_X_indptr_ndarray->data); + __pyx_v_X_indptr = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t *)__pyx_v_X_indptr_ndarray->data); - /* "_tree.pyx":1159 + /* "stpredictions/models/OK3/_tree.pyx":1159 * cdef INT32_t* X_indptr = X_indptr_ndarray.data * * cdef SIZE_t n_samples = X.shape[0] # <<<<<<<<<<<<<< @@ -16618,7 +16237,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_n_samples = __pyx_t_9; - /* "_tree.pyx":1160 + /* "stpredictions/models/OK3/_tree.pyx":1160 * * cdef SIZE_t n_samples = X.shape[0] * cdef SIZE_t n_features = X.shape[1] # <<<<<<<<<<<<<< @@ -16634,7 +16253,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __pyx_v_n_features = __pyx_t_9; - /* "_tree.pyx":1163 + /* "stpredictions/models/OK3/_tree.pyx":1163 * * # Initialize output * cdef np.ndarray[SIZE_t] indptr = np.zeros(n_samples + 1, dtype=np.intp) # <<<<<<<<<<<<<< @@ -16671,7 +16290,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_12 = ((PyArrayObject *)__pyx_t_11); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indptr.rcbuffer->pybuffer, (PyObject*)__pyx_t_12, &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indptr.rcbuffer->pybuffer, (PyObject*)__pyx_t_12, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_indptr = ((PyArrayObject *)Py_None); 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__Pyx_DECREF(__pyx_t_11); __pyx_t_11 = 0; - /* "_tree.pyx":1167 + /* "stpredictions/models/OK3/_tree.pyx":1167 * * cdef np.ndarray[SIZE_t] indices = np.zeros(n_samples * * (1 + self.max_depth), # <<<<<<<<<<<<<< @@ -16713,7 +16332,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_11 = __Pyx_PyInt_From_long((__pyx_v_n_samples * (1 + __pyx_v_self->max_depth))); if (unlikely(!__pyx_t_11)) __PYX_ERR(0, 1166, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_11); - /* "_tree.pyx":1166 + /* "stpredictions/models/OK3/_tree.pyx":1166 * cdef SIZE_t* indptr_ptr = indptr.data * * cdef np.ndarray[SIZE_t] indices = np.zeros(n_samples * # <<<<<<<<<<<<<< @@ -16726,7 +16345,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_11); __pyx_t_11 = 0; - /* "_tree.pyx":1168 + /* "stpredictions/models/OK3/_tree.pyx":1168 * cdef np.ndarray[SIZE_t] indices = np.zeros(n_samples * * (1 + self.max_depth), * dtype=np.intp) # <<<<<<<<<<<<<< @@ -16743,7 +16362,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj if (PyDict_SetItem(__pyx_t_11, __pyx_n_s_dtype, __pyx_t_10) < 0) __PYX_ERR(0, 1168, __pyx_L1_error) __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; - /* "_tree.pyx":1166 + /* "stpredictions/models/OK3/_tree.pyx":1166 * cdef SIZE_t* indptr_ptr = indptr.data * * cdef np.ndarray[SIZE_t] indices = np.zeros(n_samples * # <<<<<<<<<<<<<< @@ -16759,7 +16378,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_13 = ((PyArrayObject *)__pyx_t_10); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_t_13, &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_t_13, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_indices = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_indices.rcbuffer->pybuffer.buf = NULL; __PYX_ERR(0, 1166, __pyx_L1_error) } else {__pyx_pybuffernd_indices.diminfo[0].strides = __pyx_pybuffernd_indices.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_indices.diminfo[0].shape = __pyx_pybuffernd_indices.rcbuffer->pybuffer.shape[0]; @@ -16769,16 +16388,16 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_v_indices = ((PyArrayObject *)__pyx_t_10); __pyx_t_10 = 0; - /* "_tree.pyx":1169 + /* "stpredictions/models/OK3/_tree.pyx":1169 * (1 + self.max_depth), * dtype=np.intp) * cdef SIZE_t* indices_ptr = indices.data # <<<<<<<<<<<<<< * * # Initialize auxiliary data-structure */ - __pyx_v_indices_ptr = ((__pyx_t_5_tree_SIZE_t *)__pyx_v_indices->data); + __pyx_v_indices_ptr = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *)__pyx_v_indices->data); - /* "_tree.pyx":1172 + /* "stpredictions/models/OK3/_tree.pyx":1172 * * # Initialize auxiliary data-structure * cdef DTYPE_t feature_value = 0. # <<<<<<<<<<<<<< @@ -16787,7 +16406,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ __pyx_v_feature_value = 0.; - /* "_tree.pyx":1173 + /* "stpredictions/models/OK3/_tree.pyx":1173 * # Initialize auxiliary data-structure * cdef DTYPE_t feature_value = 0. * cdef Node* node = NULL # <<<<<<<<<<<<<< @@ -16796,7 +16415,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ __pyx_v_node = NULL; - /* "_tree.pyx":1174 + /* "stpredictions/models/OK3/_tree.pyx":1174 * cdef DTYPE_t feature_value = 0. * cdef Node* node = NULL * cdef DTYPE_t* X_sample = NULL # <<<<<<<<<<<<<< @@ -16805,7 +16424,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ __pyx_v_X_sample = NULL; - /* "_tree.pyx":1175 + /* "stpredictions/models/OK3/_tree.pyx":1175 * cdef Node* node = NULL * cdef DTYPE_t* X_sample = NULL * cdef SIZE_t i = 0 # <<<<<<<<<<<<<< @@ -16814,7 +16433,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ __pyx_v_i = 0; - /* "_tree.pyx":1176 + /* "stpredictions/models/OK3/_tree.pyx":1176 * cdef DTYPE_t* X_sample = NULL * cdef SIZE_t i = 0 * cdef INT32_t k = 0 # <<<<<<<<<<<<<< @@ -16823,7 +16442,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ __pyx_v_k = 0; - /* "_tree.pyx":1181 + /* "stpredictions/models/OK3/_tree.pyx":1181 * # for each feature; functionally, it is an efficient way to identify * # which features are nonzero in the present sample. * cdef SIZE_t* feature_to_sample = NULL # <<<<<<<<<<<<<< @@ -16832,25 +16451,25 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ __pyx_v_feature_to_sample = NULL; - /* "_tree.pyx":1183 + /* "stpredictions/models/OK3/_tree.pyx":1183 * cdef SIZE_t* feature_to_sample = NULL * * safe_realloc(&X_sample, n_features) # <<<<<<<<<<<<<< * safe_realloc(&feature_to_sample, n_features) * */ - __pyx_fuse_0__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_X_sample), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 1183, __pyx_L1_error) + __pyx_fuse_0__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_X_sample), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 1183, __pyx_L1_error) - /* "_tree.pyx":1184 + /* "stpredictions/models/OK3/_tree.pyx":1184 * * safe_realloc(&X_sample, n_features) * safe_realloc(&feature_to_sample, n_features) # <<<<<<<<<<<<<< * * with nogil: */ - __pyx_fuse_1__pyx_f_7sklearn_4tree_6_utils_safe_realloc((&__pyx_v_feature_to_sample), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 1184, __pyx_L1_error) + __pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc((&__pyx_v_feature_to_sample), __pyx_v_n_features); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 1184, __pyx_L1_error) - /* "_tree.pyx":1186 + /* "stpredictions/models/OK3/_tree.pyx":1186 * safe_realloc(&feature_to_sample, n_features) * * with nogil: # <<<<<<<<<<<<<< @@ -16865,16 +16484,16 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj #endif /*try:*/ { - /* "_tree.pyx":1187 + /* "stpredictions/models/OK3/_tree.pyx":1187 * * with nogil: * memset(feature_to_sample, -1, n_features * sizeof(SIZE_t)) # <<<<<<<<<<<<<< * * for i in range(n_samples): */ - (void)(memset(__pyx_v_feature_to_sample, -1, (__pyx_v_n_features * (sizeof(__pyx_t_5_tree_SIZE_t))))); + (void)(memset(__pyx_v_feature_to_sample, -1, (__pyx_v_n_features * (sizeof(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t))))); - /* "_tree.pyx":1189 + /* "stpredictions/models/OK3/_tree.pyx":1189 * memset(feature_to_sample, -1, n_features * sizeof(SIZE_t)) * * for i in range(n_samples): # <<<<<<<<<<<<<< @@ -16886,7 +16505,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj for (__pyx_t_15 = 0; __pyx_t_15 < __pyx_t_14; __pyx_t_15+=1) { __pyx_v_i = __pyx_t_15; - /* "_tree.pyx":1190 + /* "stpredictions/models/OK3/_tree.pyx":1190 * * for i in range(n_samples): * node = self.nodes # <<<<<<<<<<<<<< @@ -16896,7 +16515,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_16 = __pyx_v_self->nodes; __pyx_v_node = __pyx_t_16; - /* "_tree.pyx":1191 + /* "stpredictions/models/OK3/_tree.pyx":1191 * for i in range(n_samples): * node = self.nodes * indptr_ptr[i + 1] = indptr_ptr[i] # <<<<<<<<<<<<<< @@ -16905,7 +16524,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ (__pyx_v_indptr_ptr[(__pyx_v_i + 1)]) = (__pyx_v_indptr_ptr[__pyx_v_i]); - /* "_tree.pyx":1193 + /* "stpredictions/models/OK3/_tree.pyx":1193 * indptr_ptr[i + 1] = indptr_ptr[i] * * for k in range(X_indptr[i], X_indptr[i + 1]): # <<<<<<<<<<<<<< @@ -16917,7 +16536,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj for (__pyx_t_19 = (__pyx_v_X_indptr[__pyx_v_i]); __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) { __pyx_v_k = __pyx_t_19; - /* "_tree.pyx":1194 + /* "stpredictions/models/OK3/_tree.pyx":1194 * * for k in range(X_indptr[i], X_indptr[i + 1]): * feature_to_sample[X_indices[k]] = i # <<<<<<<<<<<<<< @@ -16926,7 +16545,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ (__pyx_v_feature_to_sample[(__pyx_v_X_indices[__pyx_v_k])]) = __pyx_v_i; - /* "_tree.pyx":1195 + /* "stpredictions/models/OK3/_tree.pyx":1195 * for k in range(X_indptr[i], X_indptr[i + 1]): * feature_to_sample[X_indices[k]] = i * X_sample[X_indices[k]] = X_data[k] # <<<<<<<<<<<<<< @@ -16936,7 +16555,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj (__pyx_v_X_sample[(__pyx_v_X_indices[__pyx_v_k])]) = (__pyx_v_X_data[__pyx_v_k]); } - /* "_tree.pyx":1198 + /* "stpredictions/models/OK3/_tree.pyx":1198 * * # While node not a leaf * while node.left_child != _TREE_LEAF: # <<<<<<<<<<<<<< @@ -16944,19 +16563,19 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj * */ while (1) { - __pyx_t_3 = ((__pyx_v_node->left_child != __pyx_v_5_tree__TREE_LEAF) != 0); + __pyx_t_3 = ((__pyx_v_node->left_child != __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF) != 0); if (!__pyx_t_3) break; - /* "_tree.pyx":1201 + /* "stpredictions/models/OK3/_tree.pyx":1201 * # ... and node.right_child != _TREE_LEAF: * * indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) # <<<<<<<<<<<<<< * indptr_ptr[i + 1] += 1 * */ - (__pyx_v_indices_ptr[(__pyx_v_indptr_ptr[(__pyx_v_i + 1)])]) = ((__pyx_t_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); + (__pyx_v_indices_ptr[(__pyx_v_indptr_ptr[(__pyx_v_i + 1)])]) = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); - /* "_tree.pyx":1202 + /* "stpredictions/models/OK3/_tree.pyx":1202 * * indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) * indptr_ptr[i + 1] += 1 # <<<<<<<<<<<<<< @@ -16966,7 +16585,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_20 = (__pyx_v_i + 1); (__pyx_v_indptr_ptr[__pyx_t_20]) = ((__pyx_v_indptr_ptr[__pyx_t_20]) + 1); - /* "_tree.pyx":1204 + /* "stpredictions/models/OK3/_tree.pyx":1204 * indptr_ptr[i + 1] += 1 * * if feature_to_sample[node.feature] == i: # <<<<<<<<<<<<<< @@ -16976,7 +16595,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_3 = (((__pyx_v_feature_to_sample[__pyx_v_node->feature]) == __pyx_v_i) != 0); if (__pyx_t_3) { - /* "_tree.pyx":1205 + /* "stpredictions/models/OK3/_tree.pyx":1205 * * if feature_to_sample[node.feature] == i: * feature_value = X_sample[node.feature] # <<<<<<<<<<<<<< @@ -16985,7 +16604,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ __pyx_v_feature_value = (__pyx_v_X_sample[__pyx_v_node->feature]); - /* "_tree.pyx":1204 + /* "stpredictions/models/OK3/_tree.pyx":1204 * indptr_ptr[i + 1] += 1 * * if feature_to_sample[node.feature] == i: # <<<<<<<<<<<<<< @@ -16995,7 +16614,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj goto __pyx_L14; } - /* "_tree.pyx":1208 + /* "stpredictions/models/OK3/_tree.pyx":1208 * * else: * feature_value = 0. # <<<<<<<<<<<<<< @@ -17007,7 +16626,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj } __pyx_L14:; 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} - /* "_tree.pyx":1216 + /* "stpredictions/models/OK3/_tree.pyx":1216 * * # Add the leave node * indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) # <<<<<<<<<<<<<< * indptr_ptr[i + 1] += 1 * */ - (__pyx_v_indices_ptr[(__pyx_v_indptr_ptr[(__pyx_v_i + 1)])]) = ((__pyx_t_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); + (__pyx_v_indices_ptr[(__pyx_v_indptr_ptr[(__pyx_v_i + 1)])]) = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)(__pyx_v_node - __pyx_v_self->nodes)); - /* "_tree.pyx":1217 + /* "stpredictions/models/OK3/_tree.pyx":1217 * # Add the leave node * indices_ptr[indptr_ptr[i + 1]] = (node - self.nodes) * indptr_ptr[i + 1] += 1 # <<<<<<<<<<<<<< @@ -17069,7 +16688,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj (__pyx_v_indptr_ptr[__pyx_t_20]) = ((__pyx_v_indptr_ptr[__pyx_t_20]) + 1); } - /* "_tree.pyx":1220 + /* "stpredictions/models/OK3/_tree.pyx":1220 * * # Free auxiliary arrays * free(X_sample) # <<<<<<<<<<<<<< @@ -17078,7 +16697,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj */ free(__pyx_v_X_sample); - /* "_tree.pyx":1221 + /* "stpredictions/models/OK3/_tree.pyx":1221 * # Free auxiliary arrays * free(X_sample) * free(feature_to_sample) # <<<<<<<<<<<<<< @@ -17088,7 +16707,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj free(__pyx_v_feature_to_sample); } - /* "_tree.pyx":1186 + /* "stpredictions/models/OK3/_tree.pyx":1186 * safe_realloc(&feature_to_sample, n_features) * * with nogil: # <<<<<<<<<<<<<< @@ -17107,7 +16726,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj } } - /* "_tree.pyx":1223 + /* "stpredictions/models/OK3/_tree.pyx":1223 * free(feature_to_sample) * * indices = indices[:indptr[n_samples]] # <<<<<<<<<<<<<< @@ -17115,7 +16734,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj * dtype=np.intp) */ __pyx_t_21 = __pyx_v_n_samples; - __pyx_t_10 = __Pyx_PyInt_From_Py_intptr_t((*__Pyx_BufPtrStrided1d(__pyx_t_5_tree_SIZE_t *, __pyx_pybuffernd_indptr.rcbuffer->pybuffer.buf, __pyx_t_21, __pyx_pybuffernd_indptr.diminfo[0].strides))); if (unlikely(!__pyx_t_10)) __PYX_ERR(0, 1223, __pyx_L1_error) + __pyx_t_10 = __Pyx_PyInt_From_Py_intptr_t((*__Pyx_BufPtrStrided1d(__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_pybuffernd_indptr.rcbuffer->pybuffer.buf, __pyx_t_21, __pyx_pybuffernd_indptr.diminfo[0].strides))); if (unlikely(!__pyx_t_10)) __PYX_ERR(0, 1223, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_10); __pyx_t_11 = PySlice_New(Py_None, __pyx_t_10, Py_None); if (unlikely(!__pyx_t_11)) __PYX_ERR(0, 1223, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_11); @@ -17128,10 +16747,10 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj { __Pyx_BufFmt_StackElem __pyx_stack[1]; __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_indices.rcbuffer->pybuffer); - __pyx_t_22 = __Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_t_13, &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack); + __pyx_t_22 = __Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_t_13, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack); if (unlikely(__pyx_t_22 < 0)) { PyErr_Fetch(&__pyx_t_23, &__pyx_t_24, &__pyx_t_25); - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_v_indices, &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_indices.rcbuffer->pybuffer, (PyObject*)__pyx_v_indices, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { Py_XDECREF(__pyx_t_23); Py_XDECREF(__pyx_t_24); Py_XDECREF(__pyx_t_25); __Pyx_RaiseBufferFallbackError(); } else { @@ -17146,7 +16765,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __Pyx_DECREF_SET(__pyx_v_indices, ((PyArrayObject *)__pyx_t_10)); __pyx_t_10 = 0; - /* "_tree.pyx":1224 + /* "stpredictions/models/OK3/_tree.pyx":1224 * * indices = indices[:indptr[n_samples]] * cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), # <<<<<<<<<<<<<< @@ -17166,7 +16785,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj if (PyDict_SetItem(__pyx_t_10, __pyx_n_s_shape, __pyx_t_4) < 0) __PYX_ERR(0, 1224, __pyx_L1_error) __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - /* "_tree.pyx":1225 + /* "stpredictions/models/OK3/_tree.pyx":1225 * indices = indices[:indptr[n_samples]] * cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), * dtype=np.intp) # <<<<<<<<<<<<<< @@ -17181,7 +16800,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj if (PyDict_SetItem(__pyx_t_10, __pyx_n_s_dtype, __pyx_t_5) < 0) __PYX_ERR(0, 1224, __pyx_L1_error) __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - /* "_tree.pyx":1224 + /* "stpredictions/models/OK3/_tree.pyx":1224 * * indices = indices[:indptr[n_samples]] * cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), # <<<<<<<<<<<<<< @@ -17196,7 +16815,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_t_27 = ((PyArrayObject *)__pyx_t_5); { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_data.rcbuffer->pybuffer, (PyObject*)__pyx_t_27, &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_data.rcbuffer->pybuffer, (PyObject*)__pyx_t_27, &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_data = ((PyArrayObject *)Py_None); 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__pyx_t_28 = 0; - /* "_tree.pyx":1226 + /* "stpredictions/models/OK3/_tree.pyx":1226 * cdef np.ndarray[SIZE_t] data = np.ones(shape=len(indices), * dtype=np.intp) * out = csr_matrix((data, indices, indptr), # <<<<<<<<<<<<<< @@ -17271,7 +16890,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_v_out = __pyx_t_28; __pyx_t_28 = 0; - /* "_tree.pyx":1229 + /* "stpredictions/models/OK3/_tree.pyx":1229 * shape=(n_samples, self.node_count)) * * return out # <<<<<<<<<<<<<< @@ -17283,7 +16902,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __pyx_r = __pyx_v_out; goto __pyx_L0; - /* "_tree.pyx":1139 + /* "stpredictions/models/OK3/_tree.pyx":1139 * return out * * cdef inline object _decision_path_sparse_csr(self, object X): # <<<<<<<<<<<<<< @@ -17310,7 +16929,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_indices.rcbuffer->pybuffer); __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_indptr.rcbuffer->pybuffer); __Pyx_ErrRestore(__pyx_type, __pyx_value, __pyx_tb);} - __Pyx_AddTraceback("_tree.Tree._decision_path_sparse_csr", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree._decision_path_sparse_csr", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; goto __pyx_L2; __pyx_L0:; @@ -17333,7 +16952,7 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj return __pyx_r; } -/* "_tree.pyx":1232 +/* "stpredictions/models/OK3/_tree.pyx":1232 * * * cpdef compute_feature_importances(self, normalize=True): # <<<<<<<<<<<<<< @@ -17341,17 +16960,17 @@ static PyObject *__pyx_f_5_tree_4Tree__decision_path_sparse_csr(struct __pyx_obj * cdef Node* left */ -static PyObject *__pyx_pw_5_tree_4Tree_19compute_feature_importances(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_obj_5_tree_Tree *__pyx_v_self, int __pyx_skip_dispatch, struct __pyx_opt_args_5_tree_4Tree_compute_feature_importances *__pyx_optional_args) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_19compute_feature_importances(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static PyObject *__pyx_f_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_self, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances *__pyx_optional_args) { PyObject *__pyx_v_normalize = ((PyObject *)Py_True); - struct __pyx_t_5_tree_Node *__pyx_v_left; - struct __pyx_t_5_tree_Node *__pyx_v_right; - struct __pyx_t_5_tree_Node *__pyx_v_nodes; - struct __pyx_t_5_tree_Node *__pyx_v_node; - struct __pyx_t_5_tree_Node *__pyx_v_end_node; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_left; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_right; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_nodes; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_node; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_v_end_node; double __pyx_v_normalizer; PyArrayObject *__pyx_v_importances = 0; - __pyx_t_5_tree_DOUBLE_t *__pyx_v_importance_data; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *__pyx_v_importance_data; __Pyx_LocalBuf_ND __pyx_pybuffernd_importances; __Pyx_Buffer __pyx_pybuffer_importances; PyObject *__pyx_r = NULL; @@ -17360,14 +16979,14 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o PyObject *__pyx_t_2 = NULL; PyObject *__pyx_t_3 = NULL; PyObject *__pyx_t_4 = NULL; - struct __pyx_t_5_tree_Node *__pyx_t_5; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_t_5; PyArrayObject *__pyx_t_6 = NULL; int __pyx_t_7; PyObject *__pyx_t_8 = NULL; PyObject *__pyx_t_9 = NULL; PyObject *__pyx_t_10 = NULL; int __pyx_t_11; - __pyx_t_5_tree_SIZE_t __pyx_t_12; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_t_12; double __pyx_t_13; int __pyx_lineno = 0; const char *__pyx_filename = NULL; @@ -17393,7 +17012,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o #endif __pyx_t_1 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_self), __pyx_n_s_compute_feature_importances); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 1232, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); - if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_5_tree_4Tree_19compute_feature_importances)) { + if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)(void*)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_19compute_feature_importances)) { __Pyx_XDECREF(__pyx_r); __Pyx_INCREF(__pyx_t_1); __pyx_t_3 = __pyx_t_1; __pyx_t_4 = NULL; @@ -17429,7 +17048,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o #endif } - /* "_tree.pyx":1236 + /* "stpredictions/models/OK3/_tree.pyx":1236 * cdef Node* left * cdef Node* right * cdef Node* nodes = self.nodes # <<<<<<<<<<<<<< @@ -17439,7 +17058,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o __pyx_t_5 = __pyx_v_self->nodes; __pyx_v_nodes = __pyx_t_5; - /* "_tree.pyx":1237 + /* "stpredictions/models/OK3/_tree.pyx":1237 * cdef Node* right * cdef Node* nodes = self.nodes * cdef Node* node = nodes # <<<<<<<<<<<<<< @@ -17448,7 +17067,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o */ __pyx_v_node = __pyx_v_nodes; - /* "_tree.pyx":1238 + /* "stpredictions/models/OK3/_tree.pyx":1238 * cdef Node* nodes = self.nodes * cdef Node* node = nodes * cdef Node* end_node = node + self.node_count # <<<<<<<<<<<<<< @@ -17457,7 +17076,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o */ __pyx_v_end_node = (__pyx_v_node + __pyx_v_self->node_count); - /* "_tree.pyx":1240 + /* "stpredictions/models/OK3/_tree.pyx":1240 * cdef Node* end_node = node + self.node_count * * cdef double normalizer = 0. # <<<<<<<<<<<<<< @@ -17466,7 +17085,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o */ __pyx_v_normalizer = 0.; - /* "_tree.pyx":1243 + /* "stpredictions/models/OK3/_tree.pyx":1243 * * cdef np.ndarray[np.float64_t, ndim=1] importances * importances = np.zeros((self.n_features,)) # <<<<<<<<<<<<<< @@ -17524,16 +17143,16 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o __pyx_v_importances = ((PyArrayObject *)__pyx_t_1); __pyx_t_1 = 0; - /* "_tree.pyx":1244 + /* "stpredictions/models/OK3/_tree.pyx":1244 * cdef np.ndarray[np.float64_t, ndim=1] importances * importances = np.zeros((self.n_features,)) * cdef DOUBLE_t* importance_data = importances.data # <<<<<<<<<<<<<< * * with nogil: */ - __pyx_v_importance_data = ((__pyx_t_5_tree_DOUBLE_t *)__pyx_v_importances->data); + __pyx_v_importance_data = ((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *)__pyx_v_importances->data); - /* "_tree.pyx":1246 + /* "stpredictions/models/OK3/_tree.pyx":1246 * cdef DOUBLE_t* importance_data = importances.data * * with nogil: # <<<<<<<<<<<<<< @@ -17548,7 +17167,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o #endif /*try:*/ { - /* "_tree.pyx":1247 + /* "stpredictions/models/OK3/_tree.pyx":1247 * * with nogil: * while node != end_node: # <<<<<<<<<<<<<< @@ -17559,17 +17178,17 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o __pyx_t_11 = ((__pyx_v_node != __pyx_v_end_node) != 0); if (!__pyx_t_11) break; - /* "_tree.pyx":1248 + /* "stpredictions/models/OK3/_tree.pyx":1248 * with nogil: * while node != end_node: * if node.left_child != _TREE_LEAF: # <<<<<<<<<<<<<< * # ... and node.right_child != _TREE_LEAF: * left = &nodes[node.left_child] */ - __pyx_t_11 = ((__pyx_v_node->left_child != __pyx_v_5_tree__TREE_LEAF) != 0); + __pyx_t_11 = ((__pyx_v_node->left_child != __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF) != 0); if (__pyx_t_11) { - /* "_tree.pyx":1250 + /* "stpredictions/models/OK3/_tree.pyx":1250 * if node.left_child != _TREE_LEAF: * # ... and node.right_child != _TREE_LEAF: * left = &nodes[node.left_child] # <<<<<<<<<<<<<< @@ -17578,7 +17197,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o */ __pyx_v_left = (&(__pyx_v_nodes[__pyx_v_node->left_child])); - /* "_tree.pyx":1251 + /* "stpredictions/models/OK3/_tree.pyx":1251 * # ... and node.right_child != _TREE_LEAF: * left = &nodes[node.left_child] * right = &nodes[node.right_child] # <<<<<<<<<<<<<< @@ -17587,7 +17206,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o */ __pyx_v_right = (&(__pyx_v_nodes[__pyx_v_node->right_child])); - /* "_tree.pyx":1253 + /* "stpredictions/models/OK3/_tree.pyx":1253 * right = &nodes[node.right_child] * * importance_data[node.feature] += ( # <<<<<<<<<<<<<< @@ -17596,7 +17215,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o */ __pyx_t_12 = __pyx_v_node->feature; - /* "_tree.pyx":1255 + /* "stpredictions/models/OK3/_tree.pyx":1255 * importance_data[node.feature] += ( * node.weighted_n_node_samples * node.impurity - * left.weighted_n_node_samples * left.impurity - # <<<<<<<<<<<<<< @@ -17605,7 +17224,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o */ (__pyx_v_importance_data[__pyx_t_12]) = ((__pyx_v_importance_data[__pyx_t_12]) + (((__pyx_v_node->weighted_n_node_samples * __pyx_v_node->impurity) - (__pyx_v_left->weighted_n_node_samples * __pyx_v_left->impurity)) - (__pyx_v_right->weighted_n_node_samples * __pyx_v_right->impurity))); - /* "_tree.pyx":1248 + /* "stpredictions/models/OK3/_tree.pyx":1248 * with nogil: * while node != end_node: * if node.left_child != _TREE_LEAF: # <<<<<<<<<<<<<< @@ -17614,7 +17233,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o */ } - /* "_tree.pyx":1257 + /* "stpredictions/models/OK3/_tree.pyx":1257 * left.weighted_n_node_samples * left.impurity - * right.weighted_n_node_samples * right.impurity) * node += 1 # <<<<<<<<<<<<<< @@ -17625,7 +17244,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o } } - /* "_tree.pyx":1246 + /* "stpredictions/models/OK3/_tree.pyx":1246 * cdef DOUBLE_t* importance_data = importances.data * * with nogil: # <<<<<<<<<<<<<< @@ -17644,7 +17263,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o } } - /* "_tree.pyx":1259 + /* "stpredictions/models/OK3/_tree.pyx":1259 * node += 1 * * importances /= nodes[0].weighted_n_node_samples # <<<<<<<<<<<<<< @@ -17679,7 +17298,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o __Pyx_DECREF_SET(__pyx_v_importances, ((PyArrayObject *)__pyx_t_3)); __pyx_t_3 = 0; - /* "_tree.pyx":1261 + /* "stpredictions/models/OK3/_tree.pyx":1261 * importances /= nodes[0].weighted_n_node_samples * * if normalize: # <<<<<<<<<<<<<< @@ -17689,7 +17308,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o __pyx_t_11 = __Pyx_PyObject_IsTrue(__pyx_v_normalize); if (unlikely(__pyx_t_11 < 0)) __PYX_ERR(0, 1261, __pyx_L1_error) if (__pyx_t_11) { - /* "_tree.pyx":1262 + /* "stpredictions/models/OK3/_tree.pyx":1262 * * if normalize: * normalizer = np.sum(importances) # <<<<<<<<<<<<<< @@ -17720,7 +17339,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __pyx_v_normalizer = __pyx_t_13; - /* "_tree.pyx":1264 + /* "stpredictions/models/OK3/_tree.pyx":1264 * normalizer = np.sum(importances) * * if normalizer > 0.0: # <<<<<<<<<<<<<< @@ -17730,7 +17349,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o __pyx_t_11 = ((__pyx_v_normalizer > 0.0) != 0); if (__pyx_t_11) { - /* "_tree.pyx":1266 + /* "stpredictions/models/OK3/_tree.pyx":1266 * if normalizer > 0.0: * # Avoid dividing by zero (e.g., when root is pure) * importances /= normalizer # <<<<<<<<<<<<<< @@ -17765,7 +17384,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o __Pyx_DECREF_SET(__pyx_v_importances, ((PyArrayObject *)__pyx_t_4)); __pyx_t_4 = 0; - /* "_tree.pyx":1264 + /* "stpredictions/models/OK3/_tree.pyx":1264 * normalizer = np.sum(importances) * * if normalizer > 0.0: # <<<<<<<<<<<<<< @@ -17774,7 +17393,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o */ } - /* "_tree.pyx":1261 + /* "stpredictions/models/OK3/_tree.pyx":1261 * importances /= nodes[0].weighted_n_node_samples * * if normalize: # <<<<<<<<<<<<<< @@ -17783,7 +17402,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o */ } - /* "_tree.pyx":1268 + /* "stpredictions/models/OK3/_tree.pyx":1268 * importances /= normalizer * * return importances # <<<<<<<<<<<<<< @@ -17795,7 +17414,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o __pyx_r = ((PyObject *)__pyx_v_importances); goto __pyx_L0; - /* "_tree.pyx":1232 + /* "stpredictions/models/OK3/_tree.pyx":1232 * * * cpdef compute_feature_importances(self, normalize=True): # <<<<<<<<<<<<<< @@ -17815,7 +17434,7 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o __Pyx_ErrFetch(&__pyx_type, &__pyx_value, &__pyx_tb); __Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_importances.rcbuffer->pybuffer); __Pyx_ErrRestore(__pyx_type, __pyx_value, __pyx_tb);} - __Pyx_AddTraceback("_tree.Tree.compute_feature_importances", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree.Tree.compute_feature_importances", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; goto __pyx_L2; __pyx_L0:; @@ -17828,9 +17447,9 @@ static PyObject *__pyx_f_5_tree_4Tree_compute_feature_importances(struct __pyx_o } /* Python wrapper */ -static PyObject *__pyx_pw_5_tree_4Tree_19compute_feature_importances(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); 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__pyx_t_8.memview = NULL; __pyx_t_8.data = NULL; - /* "_tree.pyx":1406 + /* "stpredictions/models/OK3/_tree.pyx":1406 * SIZE_t[:] child_l = orig_tree.children_left * SIZE_t[:] child_r = orig_tree.children_right * SIZE_t[:] parent = np.zeros(shape=n_nodes, dtype=np.intp) # <<<<<<<<<<<<<< @@ -19953,28 +19572,28 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; - __pyx_t_8 = __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_SIZE_t(__pyx_t_6, PyBUF_WRITABLE); if (unlikely(!__pyx_t_8.memview)) __PYX_ERR(0, 1406, __pyx_L1_error) + __pyx_t_8 = __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t(__pyx_t_6, PyBUF_WRITABLE); if (unlikely(!__pyx_t_8.memview)) __PYX_ERR(0, 1406, __pyx_L1_error) __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __pyx_v_parent = __pyx_t_8; __pyx_t_8.memview = NULL; __pyx_t_8.data = NULL; - /* "_tree.pyx":1409 + /* "stpredictions/models/OK3/_tree.pyx":1409 * * # Only uses the start and parent variables * Stack stack = Stack(INITIAL_STACK_SIZE) # <<<<<<<<<<<<<< * StackRecord stack_record * int rc = 0 */ - __pyx_t_6 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_5_tree_INITIAL_STACK_SIZE); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1409, __pyx_L1_error) + __pyx_t_6 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_13stpredictions_6models_3OK3_5_tree_INITIAL_STACK_SIZE); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 1409, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_6); - __pyx_t_7 = __Pyx_PyObject_CallOneArg(((PyObject *)__pyx_ptype_7sklearn_4tree_6_utils_Stack), __pyx_t_6); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 1409, __pyx_L1_error) + __pyx_t_7 = __Pyx_PyObject_CallOneArg(((PyObject *)__pyx_ptype_13stpredictions_6models_3OK3_6_utils_Stack), __pyx_t_6); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 1409, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_v_stack = ((struct __pyx_obj_7sklearn_4tree_6_utils_Stack *)__pyx_t_7); + __pyx_v_stack = ((struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_t_7); __pyx_t_7 = 0; - /* "_tree.pyx":1411 + /* "stpredictions/models/OK3/_tree.pyx":1411 * Stack stack = Stack(INITIAL_STACK_SIZE) * StackRecord stack_record * int rc = 0 # <<<<<<<<<<<<<< @@ -19983,7 +19602,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ __pyx_v_rc = 0; 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__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_3 = __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_DOUBLE_t(__pyx_t_2, PyBUF_WRITABLE); if (unlikely(!__pyx_t_3.memview)) __PYX_ERR(0, 1415, __pyx_L1_error) + __pyx_t_3 = __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t(__pyx_t_2, PyBUF_WRITABLE); if (unlikely(!__pyx_t_3.memview)) __PYX_ERR(0, 1415, __pyx_L1_error) __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __pyx_v_r_branch = __pyx_t_3; __pyx_t_3.memview = NULL; __pyx_t_3.data = NULL; - /* "_tree.pyx":1421 + /* "stpredictions/models/OK3/_tree.pyx":1421 * * # candidate nodes that can be pruned * unsigned char[:] candidate_nodes = np.zeros(shape=n_nodes, # <<<<<<<<<<<<<< @@ -20072,7 +19691,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ if (PyDict_SetItem(__pyx_t_2, __pyx_n_s_shape, __pyx_t_7) < 0) __PYX_ERR(0, 1421, __pyx_L1_error) __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; 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__pyx_t_9.data = NULL; - /* "_tree.pyx":1425 + /* "stpredictions/models/OK3/_tree.pyx":1425 * # nodes in subtree * unsigned char[:] in_subtree = np.ones(shape=n_nodes, dtype=np.uint8) * DOUBLE_t[:] g_node = np.zeros(shape=n_nodes, dtype=np.float64) # <<<<<<<<<<<<<< @@ -20168,13 +19787,13 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __Pyx_GOTREF(__pyx_t_5); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; - __pyx_t_3 = __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_DOUBLE_t(__pyx_t_5, PyBUF_WRITABLE); if (unlikely(!__pyx_t_3.memview)) __PYX_ERR(0, 1425, __pyx_L1_error) + __pyx_t_3 = __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t(__pyx_t_5, PyBUF_WRITABLE); if (unlikely(!__pyx_t_3.memview)) __PYX_ERR(0, 1425, __pyx_L1_error) __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __pyx_v_g_node = __pyx_t_3; __pyx_t_3.memview = NULL; __pyx_t_3.data = NULL; - /* "_tree.pyx":1433 + /* "stpredictions/models/OK3/_tree.pyx":1433 * SIZE_t n_pruned_leaves * DOUBLE_t r_diff * DOUBLE_t max_float64 = np.finfo(np.float64).max # <<<<<<<<<<<<<< @@ -20214,7 +19833,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __pyx_v_max_float64 = __pyx_t_10; - /* "_tree.pyx":1436 + /* "stpredictions/models/OK3/_tree.pyx":1436 * * # find parent node ids and leaves * with nogil: # <<<<<<<<<<<<<< @@ -20229,7 +19848,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ #endif /*try:*/ { - /* "_tree.pyx":1438 + /* "stpredictions/models/OK3/_tree.pyx":1438 * with nogil: * * for i in range(r_node.shape[0]): # <<<<<<<<<<<<<< @@ -20241,7 +19860,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ for (__pyx_t_1 = 0; __pyx_t_1 < __pyx_t_12; __pyx_t_1+=1) { __pyx_v_i = __pyx_t_1; - /* "_tree.pyx":1440 + /* "stpredictions/models/OK3/_tree.pyx":1440 * for i in range(r_node.shape[0]): * r_node[i] = ( * weighted_n_node_samples[i] * impurity[i] / total_sum_weights) # <<<<<<<<<<<<<< @@ -20251,7 +19870,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_4 = __pyx_v_i; __pyx_t_13 = __pyx_v_i; - /* "_tree.pyx":1439 + /* "stpredictions/models/OK3/_tree.pyx":1439 * * for i in range(r_node.shape[0]): * r_node[i] = ( # <<<<<<<<<<<<<< @@ -20259,20 +19878,20 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * */ __pyx_t_14 = __pyx_v_i; - *((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_14 * __pyx_v_r_node.strides[0]) )) = (((*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_weighted_n_node_samples.data + __pyx_t_4 * __pyx_v_weighted_n_node_samples.strides[0]) ))) * (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_impurity.data + __pyx_t_13 * __pyx_v_impurity.strides[0]) )))) / __pyx_v_total_sum_weights); + *((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_14 * __pyx_v_r_node.strides[0]) )) = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_weighted_n_node_samples.data + __pyx_t_4 * __pyx_v_weighted_n_node_samples.strides[0]) ))) * (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_impurity.data + __pyx_t_13 * __pyx_v_impurity.strides[0]) )))) / __pyx_v_total_sum_weights); } - /* "_tree.pyx":1443 + /* "stpredictions/models/OK3/_tree.pyx":1443 * * # Push root node, using StackRecord.start as node id * rc = stack.push(0, 0, 0, -1, 0, 0, 0) # <<<<<<<<<<<<<< * if rc == -1: * with gil: */ - __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, 0, 0, 0, -1, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1443, __pyx_L4_error) + __pyx_t_15 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, 0, 0, 0, -1, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1443, __pyx_L4_error) __pyx_v_rc = __pyx_t_15; - /* "_tree.pyx":1444 + /* "stpredictions/models/OK3/_tree.pyx":1444 * # Push root node, using StackRecord.start as node id * rc = stack.push(0, 0, 0, -1, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -20282,7 +19901,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1445 + /* "stpredictions/models/OK3/_tree.pyx":1445 * rc = stack.push(0, 0, 0, -1, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -20295,7 +19914,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ #endif /*try:*/ { - /* "_tree.pyx":1446 + /* "stpredictions/models/OK3/_tree.pyx":1446 * if rc == -1: * with gil: * raise MemoryError("pruning tree") # <<<<<<<<<<<<<< @@ -20309,7 +19928,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __PYX_ERR(0, 1446, __pyx_L10_error) } - /* "_tree.pyx":1445 + /* "stpredictions/models/OK3/_tree.pyx":1445 * rc = stack.push(0, 0, 0, -1, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -20326,7 +19945,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ } } - /* "_tree.pyx":1444 + /* "stpredictions/models/OK3/_tree.pyx":1444 * # Push root node, using StackRecord.start as node id * rc = stack.push(0, 0, 0, -1, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -20335,7 +19954,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ } - /* "_tree.pyx":1448 + /* "stpredictions/models/OK3/_tree.pyx":1448 * raise MemoryError("pruning tree") * * while not stack.is_empty(): # <<<<<<<<<<<<<< @@ -20343,19 +19962,19 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * node_idx = stack_record.start */ while (1) { - __pyx_t_16 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0); + __pyx_t_16 = ((!(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0); if (!__pyx_t_16) break; - /* "_tree.pyx":1449 + /* "stpredictions/models/OK3/_tree.pyx":1449 * * while not stack.is_empty(): * stack.pop(&stack_record) # <<<<<<<<<<<<<< * node_idx = stack_record.start * parent[node_idx] = stack_record.parent */ - (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record))); + (void)(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record))); - /* "_tree.pyx":1450 + /* "stpredictions/models/OK3/_tree.pyx":1450 * while not stack.is_empty(): * stack.pop(&stack_record) * node_idx = stack_record.start # <<<<<<<<<<<<<< @@ -20365,7 +19984,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_17 = __pyx_v_stack_record.start; __pyx_v_node_idx = __pyx_t_17; - /* "_tree.pyx":1451 + /* "stpredictions/models/OK3/_tree.pyx":1451 * stack.pop(&stack_record) * node_idx = stack_record.start * parent[node_idx] = stack_record.parent # <<<<<<<<<<<<<< @@ -20374,9 +19993,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ __pyx_t_17 = __pyx_v_stack_record.parent; __pyx_t_13 = __pyx_v_node_idx; - *((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_13 * __pyx_v_parent.strides[0]) )) = __pyx_t_17; + *((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_13 * __pyx_v_parent.strides[0]) )) = __pyx_t_17; - /* "_tree.pyx":1452 + /* "stpredictions/models/OK3/_tree.pyx":1452 * node_idx = stack_record.start * parent[node_idx] = stack_record.parent * if child_l[node_idx] == _TREE_LEAF: # <<<<<<<<<<<<<< @@ -20384,10 +20003,10 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * leaves_in_subtree[node_idx] = 1 */ __pyx_t_13 = __pyx_v_node_idx; - __pyx_t_16 = (((*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_13 * __pyx_v_child_l.strides[0]) ))) == __pyx_v_5_tree__TREE_LEAF) != 0); + __pyx_t_16 = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_13 * __pyx_v_child_l.strides[0]) ))) == __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1454 + /* "stpredictions/models/OK3/_tree.pyx":1454 * if child_l[node_idx] == _TREE_LEAF: * # ... and child_r[node_idx] == _TREE_LEAF: * leaves_in_subtree[node_idx] = 1 # <<<<<<<<<<<<<< @@ -20397,7 +20016,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_13 = __pyx_v_node_idx; *((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_13 * __pyx_v_leaves_in_subtree.strides[0]) )) = 1; - /* "_tree.pyx":1452 + /* "stpredictions/models/OK3/_tree.pyx":1452 * node_idx = stack_record.start * parent[node_idx] = stack_record.parent * if child_l[node_idx] == _TREE_LEAF: # <<<<<<<<<<<<<< @@ -20407,7 +20026,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ goto __pyx_L14; } - /* "_tree.pyx":1456 + /* "stpredictions/models/OK3/_tree.pyx":1456 * leaves_in_subtree[node_idx] = 1 * else: * rc = stack.push(child_l[node_idx], 0, 0, node_idx, 0, 0, 0) # <<<<<<<<<<<<<< @@ -20416,10 +20035,10 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ /*else*/ { __pyx_t_13 = __pyx_v_node_idx; - __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_13 * __pyx_v_child_l.strides[0]) ))), 0, 0, __pyx_v_node_idx, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1456, __pyx_L4_error) + __pyx_t_15 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_13 * __pyx_v_child_l.strides[0]) ))), 0, 0, __pyx_v_node_idx, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1456, __pyx_L4_error) __pyx_v_rc = __pyx_t_15; - /* "_tree.pyx":1457 + /* "stpredictions/models/OK3/_tree.pyx":1457 * else: * rc = stack.push(child_l[node_idx], 0, 0, node_idx, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -20429,7 +20048,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1458 + /* "stpredictions/models/OK3/_tree.pyx":1458 * rc = stack.push(child_l[node_idx], 0, 0, node_idx, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -20442,7 +20061,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ #endif /*try:*/ { - /* "_tree.pyx":1459 + /* "stpredictions/models/OK3/_tree.pyx":1459 * if rc == -1: * with gil: * raise MemoryError("pruning tree") # <<<<<<<<<<<<<< @@ -20456,7 +20075,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __PYX_ERR(0, 1459, __pyx_L19_error) } - /* "_tree.pyx":1458 + /* "stpredictions/models/OK3/_tree.pyx":1458 * rc = stack.push(child_l[node_idx], 0, 0, node_idx, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -20473,7 +20092,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ } } - /* "_tree.pyx":1457 + /* "stpredictions/models/OK3/_tree.pyx":1457 * else: * rc = stack.push(child_l[node_idx], 0, 0, node_idx, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -20482,7 +20101,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ } - /* "_tree.pyx":1461 + /* "stpredictions/models/OK3/_tree.pyx":1461 * raise MemoryError("pruning tree") * * rc = stack.push(child_r[node_idx], 0, 0, node_idx, 0, 0, 0) # <<<<<<<<<<<<<< @@ -20490,10 +20109,10 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * with gil: */ __pyx_t_13 = __pyx_v_node_idx; - __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_r.data + __pyx_t_13 * __pyx_v_child_r.strides[0]) ))), 0, 0, __pyx_v_node_idx, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1461, __pyx_L4_error) + __pyx_t_15 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_r.data + __pyx_t_13 * __pyx_v_child_r.strides[0]) ))), 0, 0, __pyx_v_node_idx, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1461, __pyx_L4_error) __pyx_v_rc = __pyx_t_15; - /* "_tree.pyx":1462 + /* "stpredictions/models/OK3/_tree.pyx":1462 * * rc = stack.push(child_r[node_idx], 0, 0, node_idx, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -20503,7 +20122,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1463 + /* "stpredictions/models/OK3/_tree.pyx":1463 * rc = stack.push(child_r[node_idx], 0, 0, node_idx, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -20516,7 +20135,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ #endif /*try:*/ { - /* "_tree.pyx":1464 + /* "stpredictions/models/OK3/_tree.pyx":1464 * if rc == -1: * with gil: * raise MemoryError("pruning tree") # <<<<<<<<<<<<<< @@ -20530,7 +20149,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __PYX_ERR(0, 1464, __pyx_L25_error) } - /* "_tree.pyx":1463 + /* "stpredictions/models/OK3/_tree.pyx":1463 * rc = stack.push(child_r[node_idx], 0, 0, node_idx, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -20547,7 +20166,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ } } - /* "_tree.pyx":1462 + /* "stpredictions/models/OK3/_tree.pyx":1462 * * rc = stack.push(child_r[node_idx], 0, 0, node_idx, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -20559,7 +20178,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_L14:; } - /* "_tree.pyx":1468 + /* "stpredictions/models/OK3/_tree.pyx":1468 * # computes number of leaves in all branches and the overall impurity of * # the branch. The overall impurity is the sum of r_node in its leaves. * for leaf_idx in range(leaves_in_subtree.shape[0]): # <<<<<<<<<<<<<< @@ -20571,7 +20190,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ for (__pyx_t_1 = 0; __pyx_t_1 < __pyx_t_12; __pyx_t_1+=1) { __pyx_v_leaf_idx = __pyx_t_1; - /* "_tree.pyx":1469 + /* "stpredictions/models/OK3/_tree.pyx":1469 * # the branch. The overall impurity is the sum of r_node in its leaves. * for leaf_idx in range(leaves_in_subtree.shape[0]): * if not leaves_in_subtree[leaf_idx]: # <<<<<<<<<<<<<< @@ -20582,7 +20201,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_13 * __pyx_v_leaves_in_subtree.strides[0]) ))) != 0)) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1470 + /* "stpredictions/models/OK3/_tree.pyx":1470 * for leaf_idx in range(leaves_in_subtree.shape[0]): * if not leaves_in_subtree[leaf_idx]: * continue # <<<<<<<<<<<<<< @@ -20591,7 +20210,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ goto __pyx_L27_continue; - /* "_tree.pyx":1469 + /* "stpredictions/models/OK3/_tree.pyx":1469 * # the branch. The overall impurity is the sum of r_node in its leaves. * for leaf_idx in range(leaves_in_subtree.shape[0]): * if not leaves_in_subtree[leaf_idx]: # <<<<<<<<<<<<<< @@ -20600,7 +20219,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ } - /* "_tree.pyx":1471 + /* "stpredictions/models/OK3/_tree.pyx":1471 * if not leaves_in_subtree[leaf_idx]: * continue * r_branch[leaf_idx] = r_node[leaf_idx] # <<<<<<<<<<<<<< @@ -20609,9 +20228,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ __pyx_t_13 = __pyx_v_leaf_idx; __pyx_t_4 = __pyx_v_leaf_idx; - *((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )) = (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))); + *((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )) = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))); - /* "_tree.pyx":1474 + /* "stpredictions/models/OK3/_tree.pyx":1474 * * # bubble up values to ancestor nodes * current_r = r_node[leaf_idx] # <<<<<<<<<<<<<< @@ -20619,9 +20238,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * parent_idx = parent[leaf_idx] */ __pyx_t_13 = __pyx_v_leaf_idx; - __pyx_v_current_r = (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))); + __pyx_v_current_r = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))); - /* "_tree.pyx":1475 + /* "stpredictions/models/OK3/_tree.pyx":1475 * # bubble up values to ancestor nodes * current_r = r_node[leaf_idx] * while leaf_idx != 0: # <<<<<<<<<<<<<< @@ -20632,7 +20251,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((__pyx_v_leaf_idx != 0) != 0); if (!__pyx_t_16) break; - /* "_tree.pyx":1476 + /* "stpredictions/models/OK3/_tree.pyx":1476 * current_r = r_node[leaf_idx] * while leaf_idx != 0: * parent_idx = parent[leaf_idx] # <<<<<<<<<<<<<< @@ -20640,9 +20259,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * n_leaves[parent_idx] += 1 */ __pyx_t_13 = __pyx_v_leaf_idx; - __pyx_v_parent_idx = (*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_13 * __pyx_v_parent.strides[0]) ))); + __pyx_v_parent_idx = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_13 * __pyx_v_parent.strides[0]) ))); - /* "_tree.pyx":1477 + /* "stpredictions/models/OK3/_tree.pyx":1477 * while leaf_idx != 0: * parent_idx = parent[leaf_idx] * r_branch[parent_idx] += current_r # <<<<<<<<<<<<<< @@ -20650,9 +20269,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * leaf_idx = parent_idx */ __pyx_t_13 = __pyx_v_parent_idx; - *((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_13 * __pyx_v_r_branch.strides[0]) )) += __pyx_v_current_r; + *((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_13 * __pyx_v_r_branch.strides[0]) )) += __pyx_v_current_r; - /* "_tree.pyx":1478 + /* "stpredictions/models/OK3/_tree.pyx":1478 * parent_idx = parent[leaf_idx] * r_branch[parent_idx] += current_r * n_leaves[parent_idx] += 1 # <<<<<<<<<<<<<< @@ -20660,9 +20279,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * */ __pyx_t_13 = __pyx_v_parent_idx; - *((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_13 * __pyx_v_n_leaves.strides[0]) )) += 1; + *((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_13 * __pyx_v_n_leaves.strides[0]) )) += 1; - /* "_tree.pyx":1479 + /* "stpredictions/models/OK3/_tree.pyx":1479 * r_branch[parent_idx] += current_r * n_leaves[parent_idx] += 1 * leaf_idx = parent_idx # <<<<<<<<<<<<<< @@ -20674,7 +20293,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_L27_continue:; } - /* "_tree.pyx":1481 + /* "stpredictions/models/OK3/_tree.pyx":1481 * leaf_idx = parent_idx * * for i in range(leaves_in_subtree.shape[0]): # <<<<<<<<<<<<<< @@ -20686,7 +20305,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ for (__pyx_t_1 = 0; __pyx_t_1 < __pyx_t_12; __pyx_t_1+=1) { __pyx_v_i = __pyx_t_1; - /* "_tree.pyx":1482 + /* "stpredictions/models/OK3/_tree.pyx":1482 * * for i in range(leaves_in_subtree.shape[0]): * candidate_nodes[i] = not leaves_in_subtree[i] # <<<<<<<<<<<<<< @@ -20698,7 +20317,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ *((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_4 * __pyx_v_candidate_nodes.strides[0]) )) = (!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_13 * __pyx_v_leaves_in_subtree.strides[0]) ))) != 0)); } - /* "_tree.pyx":1485 + /* "stpredictions/models/OK3/_tree.pyx":1485 * * # save metrics before pruning * controller.save_metrics(0.0, r_branch[0]) # <<<<<<<<<<<<<< @@ -20706,9 +20325,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * # while root node is not a leaf */ __pyx_t_13 = 0; - ((struct __pyx_vtabstruct_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->save_metrics(__pyx_v_controller, 0.0, (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_13 * __pyx_v_r_branch.strides[0]) )))); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->save_metrics(__pyx_v_controller, 0.0, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_13 * __pyx_v_r_branch.strides[0]) )))); - /* "_tree.pyx":1488 + /* "stpredictions/models/OK3/_tree.pyx":1488 * * # while root node is not a leaf * while candidate_nodes[0]: # <<<<<<<<<<<<<< @@ -20720,7 +20339,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((*((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_13 * __pyx_v_candidate_nodes.strides[0]) ))) != 0); if (!__pyx_t_16) break; - /* "_tree.pyx":1491 + /* "stpredictions/models/OK3/_tree.pyx":1491 * * # computes ccp_alpha for subtrees and finds the minimal alpha * effective_alpha = max_float64 # <<<<<<<<<<<<<< @@ -20729,7 +20348,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ __pyx_v_effective_alpha = __pyx_v_max_float64; - /* "_tree.pyx":1492 + /* "stpredictions/models/OK3/_tree.pyx":1492 * # computes ccp_alpha for subtrees and finds the minimal alpha * effective_alpha = max_float64 * for i in range(n_nodes): # <<<<<<<<<<<<<< @@ -20741,7 +20360,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) { __pyx_v_i = __pyx_t_19; - /* "_tree.pyx":1493 + /* "stpredictions/models/OK3/_tree.pyx":1493 * effective_alpha = max_float64 * for i in range(n_nodes): * if not candidate_nodes[i]: # <<<<<<<<<<<<<< @@ -20752,7 +20371,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_13 * __pyx_v_candidate_nodes.strides[0]) ))) != 0)) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1494 + /* "stpredictions/models/OK3/_tree.pyx":1494 * for i in range(n_nodes): * if not candidate_nodes[i]: * continue # <<<<<<<<<<<<<< @@ -20761,7 +20380,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ goto __pyx_L36_continue; - /* "_tree.pyx":1493 + /* "stpredictions/models/OK3/_tree.pyx":1493 * effective_alpha = max_float64 * for i in range(n_nodes): * if not candidate_nodes[i]: # <<<<<<<<<<<<<< @@ -20770,7 +20389,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ } - /* "_tree.pyx":1495 + /* "stpredictions/models/OK3/_tree.pyx":1495 * if not candidate_nodes[i]: * continue * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) # <<<<<<<<<<<<<< @@ -20780,9 +20399,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_13 = __pyx_v_i; __pyx_t_4 = __pyx_v_i; __pyx_t_14 = __pyx_v_i; - __pyx_v_subtree_alpha = (((*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))) - (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )))) / ((*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) ))) - 1)); + __pyx_v_subtree_alpha = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_13 * __pyx_v_r_node.strides[0]) ))) - (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )))) / ((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) ))) - 1)); - /* "_tree.pyx":1496 + /* "stpredictions/models/OK3/_tree.pyx":1496 * continue * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) * if subtree_alpha < effective_alpha: # <<<<<<<<<<<<<< @@ -20792,7 +20411,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((__pyx_v_subtree_alpha < __pyx_v_effective_alpha) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1497 + /* "stpredictions/models/OK3/_tree.pyx":1497 * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) * if subtree_alpha < effective_alpha: * effective_alpha = subtree_alpha # <<<<<<<<<<<<<< @@ -20801,7 +20420,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ __pyx_v_effective_alpha = __pyx_v_subtree_alpha; - /* "_tree.pyx":1498 + /* "stpredictions/models/OK3/_tree.pyx":1498 * if subtree_alpha < effective_alpha: * effective_alpha = subtree_alpha * pruned_branch_node_idx = i # <<<<<<<<<<<<<< @@ -20810,7 +20429,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ __pyx_v_pruned_branch_node_idx = __pyx_v_i; - /* "_tree.pyx":1496 + /* "stpredictions/models/OK3/_tree.pyx":1496 * continue * subtree_alpha = (r_node[i] - r_branch[i]) / (n_leaves[i] - 1) * if subtree_alpha < effective_alpha: # <<<<<<<<<<<<<< @@ -20821,17 +20440,17 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_L36_continue:; } - /* "_tree.pyx":1500 + /* "stpredictions/models/OK3/_tree.pyx":1500 * pruned_branch_node_idx = i * * if controller.stop_pruning(effective_alpha): # <<<<<<<<<<<<<< * break * */ - __pyx_t_16 = (((struct __pyx_vtabstruct_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->stop_pruning(__pyx_v_controller, __pyx_v_effective_alpha) != 0); + __pyx_t_16 = (((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->stop_pruning(__pyx_v_controller, __pyx_v_effective_alpha) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1501 + /* "stpredictions/models/OK3/_tree.pyx":1501 * * if controller.stop_pruning(effective_alpha): * break # <<<<<<<<<<<<<< @@ -20840,7 +20459,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ goto __pyx_L35_break; - /* "_tree.pyx":1500 + /* "stpredictions/models/OK3/_tree.pyx":1500 * pruned_branch_node_idx = i * * if controller.stop_pruning(effective_alpha): # <<<<<<<<<<<<<< @@ -20849,17 +20468,17 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ } - /* "_tree.pyx":1504 + /* "stpredictions/models/OK3/_tree.pyx":1504 * * # stack uses only the start variable * rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) # <<<<<<<<<<<<<< * if rc == -1: * with gil: */ - __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_pruned_branch_node_idx, 0, 0, 0, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1504, __pyx_L4_error) + __pyx_t_15 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_pruned_branch_node_idx, 0, 0, 0, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1504, __pyx_L4_error) __pyx_v_rc = __pyx_t_15; - /* "_tree.pyx":1505 + /* "stpredictions/models/OK3/_tree.pyx":1505 * # stack uses only the start variable * rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -20869,7 +20488,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1506 + /* "stpredictions/models/OK3/_tree.pyx":1506 * rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -20882,7 +20501,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ #endif /*try:*/ { - /* "_tree.pyx":1507 + /* "stpredictions/models/OK3/_tree.pyx":1507 * if rc == -1: * with gil: * raise MemoryError("pruning tree") # <<<<<<<<<<<<<< @@ -20896,7 +20515,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __PYX_ERR(0, 1507, __pyx_L45_error) } - /* "_tree.pyx":1506 + /* "stpredictions/models/OK3/_tree.pyx":1506 * rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -20913,7 +20532,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ } } - /* "_tree.pyx":1505 + /* "stpredictions/models/OK3/_tree.pyx":1505 * # stack uses only the start variable * rc = stack.push(pruned_branch_node_idx, 0, 0, 0, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -20922,7 +20541,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ } - /* "_tree.pyx":1510 + /* "stpredictions/models/OK3/_tree.pyx":1510 * * # descendants of branch are not in subtree * while not stack.is_empty(): # <<<<<<<<<<<<<< @@ -20930,19 +20549,19 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * node_idx = stack_record.start */ while (1) { - __pyx_t_16 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0); + __pyx_t_16 = ((!(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0); if (!__pyx_t_16) break; - /* "_tree.pyx":1511 + /* "stpredictions/models/OK3/_tree.pyx":1511 * # descendants of branch are not in subtree * while not stack.is_empty(): * stack.pop(&stack_record) # <<<<<<<<<<<<<< * node_idx = stack_record.start * */ - (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record))); + (void)(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record))); - /* "_tree.pyx":1512 + /* "stpredictions/models/OK3/_tree.pyx":1512 * while not stack.is_empty(): * stack.pop(&stack_record) * node_idx = stack_record.start # <<<<<<<<<<<<<< @@ -20952,7 +20571,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_17 = __pyx_v_stack_record.start; __pyx_v_node_idx = __pyx_t_17; - /* "_tree.pyx":1514 + /* "stpredictions/models/OK3/_tree.pyx":1514 * node_idx = stack_record.start * * if not in_subtree[node_idx]: # <<<<<<<<<<<<<< @@ -20963,7 +20582,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((!((*((unsigned char *) ( /* dim=0 */ (__pyx_v_in_subtree.data + __pyx_t_14 * __pyx_v_in_subtree.strides[0]) ))) != 0)) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1515 + /* "stpredictions/models/OK3/_tree.pyx":1515 * * if not in_subtree[node_idx]: * continue # branch has already been marked for pruning # <<<<<<<<<<<<<< @@ -20972,7 +20591,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ goto __pyx_L47_continue; - /* "_tree.pyx":1514 + /* "stpredictions/models/OK3/_tree.pyx":1514 * node_idx = stack_record.start * * if not in_subtree[node_idx]: # <<<<<<<<<<<<<< @@ -20981,7 +20600,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ } - /* "_tree.pyx":1516 + /* "stpredictions/models/OK3/_tree.pyx":1516 * if not in_subtree[node_idx]: * continue # branch has already been marked for pruning * candidate_nodes[node_idx] = 0 # <<<<<<<<<<<<<< @@ -20991,7 +20610,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_14 = __pyx_v_node_idx; *((unsigned char *) ( /* dim=0 */ (__pyx_v_candidate_nodes.data + __pyx_t_14 * __pyx_v_candidate_nodes.strides[0]) )) = 0; - /* "_tree.pyx":1517 + /* "stpredictions/models/OK3/_tree.pyx":1517 * continue # branch has already been marked for pruning * candidate_nodes[node_idx] = 0 * leaves_in_subtree[node_idx] = 0 # <<<<<<<<<<<<<< @@ -21001,7 +20620,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_14 = __pyx_v_node_idx; *((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_14 * __pyx_v_leaves_in_subtree.strides[0]) )) = 0; - /* "_tree.pyx":1518 + /* "stpredictions/models/OK3/_tree.pyx":1518 * candidate_nodes[node_idx] = 0 * leaves_in_subtree[node_idx] = 0 * in_subtree[node_idx] = 0 # <<<<<<<<<<<<<< @@ -21011,7 +20630,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_14 = __pyx_v_node_idx; *((unsigned char *) ( /* dim=0 */ (__pyx_v_in_subtree.data + __pyx_t_14 * __pyx_v_in_subtree.strides[0]) )) = 0; - /* "_tree.pyx":1520 + /* "stpredictions/models/OK3/_tree.pyx":1520 * in_subtree[node_idx] = 0 * * if child_l[node_idx] != _TREE_LEAF: # <<<<<<<<<<<<<< @@ -21019,10 +20638,10 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) */ __pyx_t_14 = __pyx_v_node_idx; - __pyx_t_16 = (((*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_14 * __pyx_v_child_l.strides[0]) ))) != __pyx_v_5_tree__TREE_LEAF) != 0); + __pyx_t_16 = (((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_14 * __pyx_v_child_l.strides[0]) ))) != __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_LEAF) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1522 + /* "stpredictions/models/OK3/_tree.pyx":1522 * if child_l[node_idx] != _TREE_LEAF: * # ... and child_r[node_idx] != _TREE_LEAF: * rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) # <<<<<<<<<<<<<< @@ -21030,10 +20649,10 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * with gil: */ __pyx_t_14 = __pyx_v_node_idx; - __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_14 * __pyx_v_child_l.strides[0]) ))), 0, 0, 0, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1522, __pyx_L4_error) + __pyx_t_15 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_l.data + __pyx_t_14 * __pyx_v_child_l.strides[0]) ))), 0, 0, 0, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1522, __pyx_L4_error) __pyx_v_rc = __pyx_t_15; - /* "_tree.pyx":1523 + /* "stpredictions/models/OK3/_tree.pyx":1523 * # ... and child_r[node_idx] != _TREE_LEAF: * rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -21043,7 +20662,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1524 + /* "stpredictions/models/OK3/_tree.pyx":1524 * rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -21056,7 +20675,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ #endif /*try:*/ { - /* "_tree.pyx":1525 + /* "stpredictions/models/OK3/_tree.pyx":1525 * if rc == -1: * with gil: * raise MemoryError("pruning tree") # <<<<<<<<<<<<<< @@ -21070,7 +20689,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __PYX_ERR(0, 1525, __pyx_L55_error) } - /* "_tree.pyx":1524 + /* "stpredictions/models/OK3/_tree.pyx":1524 * rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -21087,7 +20706,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ } } - /* "_tree.pyx":1523 + /* "stpredictions/models/OK3/_tree.pyx":1523 * # ... and child_r[node_idx] != _TREE_LEAF: * rc = stack.push(child_l[node_idx], 0, 0, 0, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -21096,7 +20715,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ } - /* "_tree.pyx":1526 + /* "stpredictions/models/OK3/_tree.pyx":1526 * with gil: * raise MemoryError("pruning tree") * rc = stack.push(child_r[node_idx], 0, 0, 0, 0, 0, 0) # <<<<<<<<<<<<<< @@ -21104,10 +20723,10 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * with gil: */ __pyx_t_14 = __pyx_v_node_idx; - __pyx_t_15 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_r.data + __pyx_t_14 * __pyx_v_child_r.strides[0]) ))), 0, 0, 0, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1526, __pyx_L4_error) + __pyx_t_15 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_child_r.data + __pyx_t_14 * __pyx_v_child_r.strides[0]) ))), 0, 0, 0, 0, 0.0, 0); if (unlikely(__pyx_t_15 == ((int)-1))) __PYX_ERR(0, 1526, __pyx_L4_error) __pyx_v_rc = __pyx_t_15; - /* "_tree.pyx":1527 + /* "stpredictions/models/OK3/_tree.pyx":1527 * raise MemoryError("pruning tree") * rc = stack.push(child_r[node_idx], 0, 0, 0, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -21117,7 +20736,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_16) { - /* "_tree.pyx":1528 + /* "stpredictions/models/OK3/_tree.pyx":1528 * rc = stack.push(child_r[node_idx], 0, 0, 0, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -21130,7 +20749,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ #endif /*try:*/ { - /* "_tree.pyx":1529 + /* "stpredictions/models/OK3/_tree.pyx":1529 * if rc == -1: * with gil: * raise MemoryError("pruning tree") # <<<<<<<<<<<<<< @@ -21144,7 +20763,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __PYX_ERR(0, 1529, __pyx_L61_error) } - /* "_tree.pyx":1528 + /* "stpredictions/models/OK3/_tree.pyx":1528 * rc = stack.push(child_r[node_idx], 0, 0, 0, 0, 0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -21161,7 +20780,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ } } - /* "_tree.pyx":1527 + /* "stpredictions/models/OK3/_tree.pyx":1527 * raise MemoryError("pruning tree") * rc = stack.push(child_r[node_idx], 0, 0, 0, 0, 0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -21170,7 +20789,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ } - /* "_tree.pyx":1520 + /* "stpredictions/models/OK3/_tree.pyx":1520 * in_subtree[node_idx] = 0 * * if child_l[node_idx] != _TREE_LEAF: # <<<<<<<<<<<<<< @@ -21181,7 +20800,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_L47_continue:; } - /* "_tree.pyx":1530 + /* "stpredictions/models/OK3/_tree.pyx":1530 * with gil: * raise MemoryError("pruning tree") * leaves_in_subtree[pruned_branch_node_idx] = 1 # <<<<<<<<<<<<<< @@ -21191,7 +20810,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_14 = __pyx_v_pruned_branch_node_idx; *((unsigned char *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_14 * __pyx_v_leaves_in_subtree.strides[0]) )) = 1; - /* "_tree.pyx":1531 + /* "stpredictions/models/OK3/_tree.pyx":1531 * raise MemoryError("pruning tree") * leaves_in_subtree[pruned_branch_node_idx] = 1 * in_subtree[pruned_branch_node_idx] = 1 # <<<<<<<<<<<<<< @@ -21201,7 +20820,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_14 = __pyx_v_pruned_branch_node_idx; *((unsigned char *) ( /* dim=0 */ (__pyx_v_in_subtree.data + __pyx_t_14 * __pyx_v_in_subtree.strides[0]) )) = 1; - /* "_tree.pyx":1534 + /* "stpredictions/models/OK3/_tree.pyx":1534 * * # updates number of leaves * n_pruned_leaves = n_leaves[pruned_branch_node_idx] - 1 # <<<<<<<<<<<<<< @@ -21209,9 +20828,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * */ __pyx_t_14 = __pyx_v_pruned_branch_node_idx; - __pyx_v_n_pruned_leaves = ((*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) ))) - 1); + __pyx_v_n_pruned_leaves = ((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) ))) - 1); - /* "_tree.pyx":1535 + /* "stpredictions/models/OK3/_tree.pyx":1535 * # updates number of leaves * n_pruned_leaves = n_leaves[pruned_branch_node_idx] - 1 * n_leaves[pruned_branch_node_idx] = 0 # <<<<<<<<<<<<<< @@ -21219,9 +20838,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * # computes the increase in r_branch to bubble up */ __pyx_t_14 = __pyx_v_pruned_branch_node_idx; - *((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) )) = 0; + *((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_14 * __pyx_v_n_leaves.strides[0]) )) = 0; - /* "_tree.pyx":1538 + /* "stpredictions/models/OK3/_tree.pyx":1538 * * # computes the increase in r_branch to bubble up * r_diff = r_node[pruned_branch_node_idx] - r_branch[pruned_branch_node_idx] # <<<<<<<<<<<<<< @@ -21230,9 +20849,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ __pyx_t_14 = __pyx_v_pruned_branch_node_idx; __pyx_t_4 = __pyx_v_pruned_branch_node_idx; - __pyx_v_r_diff = ((*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_14 * __pyx_v_r_node.strides[0]) ))) - (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )))); + __pyx_v_r_diff = ((*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_14 * __pyx_v_r_node.strides[0]) ))) - (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )))); - /* "_tree.pyx":1539 + /* "stpredictions/models/OK3/_tree.pyx":1539 * # computes the increase in r_branch to bubble up * r_diff = r_node[pruned_branch_node_idx] - r_branch[pruned_branch_node_idx] * r_branch[pruned_branch_node_idx] = r_node[pruned_branch_node_idx] # <<<<<<<<<<<<<< @@ -21241,9 +20860,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ __pyx_t_4 = __pyx_v_pruned_branch_node_idx; __pyx_t_14 = __pyx_v_pruned_branch_node_idx; - *((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_14 * __pyx_v_r_branch.strides[0]) )) = (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_4 * __pyx_v_r_node.strides[0]) ))); + *((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_14 * __pyx_v_r_branch.strides[0]) )) = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_node.data + __pyx_t_4 * __pyx_v_r_node.strides[0]) ))); - /* "_tree.pyx":1542 + /* "stpredictions/models/OK3/_tree.pyx":1542 * * # bubble up values to ancestors * node_idx = parent[pruned_branch_node_idx] # <<<<<<<<<<<<<< @@ -21251,9 +20870,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * n_leaves[node_idx] -= n_pruned_leaves */ __pyx_t_4 = __pyx_v_pruned_branch_node_idx; - __pyx_v_node_idx = (*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_4 * __pyx_v_parent.strides[0]) ))); + __pyx_v_node_idx = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_4 * __pyx_v_parent.strides[0]) ))); - /* "_tree.pyx":1543 + /* "stpredictions/models/OK3/_tree.pyx":1543 * # bubble up values to ancestors * node_idx = parent[pruned_branch_node_idx] * while node_idx != -1: # <<<<<<<<<<<<<< @@ -21264,7 +20883,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __pyx_t_16 = ((__pyx_v_node_idx != -1L) != 0); if (!__pyx_t_16) break; - /* "_tree.pyx":1544 + /* "stpredictions/models/OK3/_tree.pyx":1544 * node_idx = parent[pruned_branch_node_idx] * while node_idx != -1: * n_leaves[node_idx] -= n_pruned_leaves # <<<<<<<<<<<<<< @@ -21272,9 +20891,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * node_idx = parent[node_idx] */ __pyx_t_4 = __pyx_v_node_idx; - *((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_4 * __pyx_v_n_leaves.strides[0]) )) -= __pyx_v_n_pruned_leaves; + *((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_n_leaves.data + __pyx_t_4 * __pyx_v_n_leaves.strides[0]) )) -= __pyx_v_n_pruned_leaves; - /* "_tree.pyx":1545 + /* "stpredictions/models/OK3/_tree.pyx":1545 * while node_idx != -1: * n_leaves[node_idx] -= n_pruned_leaves * r_branch[node_idx] += r_diff # <<<<<<<<<<<<<< @@ -21282,9 +20901,9 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * */ __pyx_t_4 = __pyx_v_node_idx; - *((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )) += __pyx_v_r_diff; + *((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )) += __pyx_v_r_diff; - /* "_tree.pyx":1546 + /* "stpredictions/models/OK3/_tree.pyx":1546 * n_leaves[node_idx] -= n_pruned_leaves * r_branch[node_idx] += r_diff * node_idx = parent[node_idx] # <<<<<<<<<<<<<< @@ -21292,10 +20911,10 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * controller.save_metrics(effective_alpha, r_branch[0]) */ __pyx_t_4 = __pyx_v_node_idx; - __pyx_v_node_idx = (*((__pyx_t_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_4 * __pyx_v_parent.strides[0]) ))); + __pyx_v_node_idx = (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *) ( /* dim=0 */ (__pyx_v_parent.data + __pyx_t_4 * __pyx_v_parent.strides[0]) ))); } - /* "_tree.pyx":1548 + /* "stpredictions/models/OK3/_tree.pyx":1548 * node_idx = parent[node_idx] * * controller.save_metrics(effective_alpha, r_branch[0]) # <<<<<<<<<<<<<< @@ -21303,21 +20922,21 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ * controller.after_pruning(in_subtree) */ __pyx_t_4 = 0; - ((struct __pyx_vtabstruct_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->save_metrics(__pyx_v_controller, __pyx_v_effective_alpha, (*((__pyx_t_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )))); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->save_metrics(__pyx_v_controller, __pyx_v_effective_alpha, (*((__pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *) ( /* dim=0 */ (__pyx_v_r_branch.data + __pyx_t_4 * __pyx_v_r_branch.strides[0]) )))); } __pyx_L35_break:; - /* "_tree.pyx":1550 + /* "stpredictions/models/OK3/_tree.pyx":1550 * controller.save_metrics(effective_alpha, r_branch[0]) * * controller.after_pruning(in_subtree) # <<<<<<<<<<<<<< * * */ - ((struct __pyx_vtabstruct_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->after_pruning(__pyx_v_controller, __pyx_v_in_subtree); + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController *)__pyx_v_controller->__pyx_vtab)->after_pruning(__pyx_v_controller, __pyx_v_in_subtree); } - /* "_tree.pyx":1436 + /* "stpredictions/models/OK3/_tree.pyx":1436 * * # find parent node ids and leaves * with nogil: # <<<<<<<<<<<<<< @@ -21343,7 +20962,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ } } - /* "_tree.pyx":1374 + /* "stpredictions/models/OK3/_tree.pyx":1374 * * * cdef _cost_complexity_prune(unsigned char[:] leaves_in_subtree, # OUT # <<<<<<<<<<<<<< @@ -21362,7 +20981,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ __Pyx_XDECREF(__pyx_t_7); __PYX_XDEC_MEMVIEW(&__pyx_t_8, 1); __PYX_XDEC_MEMVIEW(&__pyx_t_9, 1); - __Pyx_AddTraceback("_tree._cost_complexity_prune", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree._cost_complexity_prune", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; __pyx_L0:; __PYX_XDEC_MEMVIEW(&__pyx_v_weighted_n_node_samples, 1); @@ -21382,7 +21001,7 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ return __pyx_r; } -/* "_tree.pyx":1553 +/* "stpredictions/models/OK3/_tree.pyx":1553 * * * def _build_pruned_tree_ccp( # <<<<<<<<<<<<<< @@ -21391,13 +21010,13 @@ static PyObject *__pyx_f_5_tree__cost_complexity_prune(__Pyx_memviewslice __pyx_ */ /* Python wrapper */ -static PyObject *__pyx_pw_5_tree_1_build_pruned_tree_ccp(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static char __pyx_doc_5_tree__build_pruned_tree_ccp[] = "Build a pruned tree from the original tree using cost complexity\n pruning.\n\n The values and nodes from the original tree are copied into the pruned\n tree.\n\n Parameters\n ----------\n tree : Tree\n Location to place the pruned tree\n orig_tree : Tree\n Original tree\n ccp_alpha : positive double\n Complexity parameter. The subtree with the largest cost complexity\n that is smaller than ``ccp_alpha`` will be chosen. By default,\n no pruning is performed.\n "; -static PyMethodDef __pyx_mdef_5_tree_1_build_pruned_tree_ccp = {"_build_pruned_tree_ccp", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_1_build_pruned_tree_ccp, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree__build_pruned_tree_ccp}; -static PyObject *__pyx_pw_5_tree_1_build_pruned_tree_ccp(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { - struct __pyx_obj_5_tree_Tree *__pyx_v_tree = 0; - struct __pyx_obj_5_tree_Tree *__pyx_v_orig_tree = 0; - __pyx_t_5_tree_DOUBLE_t __pyx_v_ccp_alpha; +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_1_build_pruned_tree_ccp(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_13stpredictions_6models_3OK3_5_tree__build_pruned_tree_ccp[] = "Build a pruned tree from the original tree using cost complexity\n pruning.\n\n The values and nodes from the original tree are copied into the pruned\n tree.\n\n Parameters\n ----------\n tree : Tree\n Location to place the pruned tree\n orig_tree : Tree\n Original tree\n ccp_alpha : positive double\n Complexity parameter. The subtree with the largest cost complexity\n that is smaller than ``ccp_alpha`` will be chosen. By default,\n no pruning is performed.\n "; +static PyMethodDef __pyx_mdef_13stpredictions_6models_3OK3_5_tree_1_build_pruned_tree_ccp = {"_build_pruned_tree_ccp", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_13stpredictions_6models_3OK3_5_tree_1_build_pruned_tree_ccp, METH_VARARGS|METH_KEYWORDS, __pyx_doc_13stpredictions_6models_3OK3_5_tree__build_pruned_tree_ccp}; +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_1_build_pruned_tree_ccp(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree = 0; + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_orig_tree = 0; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_ccp_alpha; int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; @@ -21448,21 +21067,21 @@ static PyObject *__pyx_pw_5_tree_1_build_pruned_tree_ccp(PyObject *__pyx_self, P values[1] = PyTuple_GET_ITEM(__pyx_args, 1); values[2] = PyTuple_GET_ITEM(__pyx_args, 2); } - __pyx_v_tree = ((struct __pyx_obj_5_tree_Tree *)values[0]); - __pyx_v_orig_tree = ((struct __pyx_obj_5_tree_Tree *)values[1]); + __pyx_v_tree = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)values[0]); + __pyx_v_orig_tree = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)values[1]); __pyx_v_ccp_alpha = __pyx_PyFloat_AsDouble(values[2]); if (unlikely((__pyx_v_ccp_alpha == ((npy_float64)-1)) && PyErr_Occurred())) __PYX_ERR(0, 1556, __pyx_L3_error) } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; __Pyx_RaiseArgtupleInvalid("_build_pruned_tree_ccp", 1, 3, 3, PyTuple_GET_SIZE(__pyx_args)); __PYX_ERR(0, 1553, __pyx_L3_error) __pyx_L3_error:; - __Pyx_AddTraceback("_tree._build_pruned_tree_ccp", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree._build_pruned_tree_ccp", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; 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} -static PyObject *__pyx_pf_5_tree__build_pruned_tree_ccp(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_5_tree_Tree *__pyx_v_tree, struct __pyx_obj_5_tree_Tree *__pyx_v_orig_tree, __pyx_t_5_tree_DOUBLE_t __pyx_v_ccp_alpha) { - __pyx_t_5_tree_SIZE_t __pyx_v_n_nodes; +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree__build_pruned_tree_ccp(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_tree, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_orig_tree, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t __pyx_v_ccp_alpha) { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t __pyx_v_n_nodes; __Pyx_memviewslice __pyx_v_leaves_in_subtree = { 0, 0, { 0 }, { 0 }, { 0 } }; - struct __pyx_obj_5_tree__AlphaPruner *__pyx_v_pruning_controller = NULL; + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *__pyx_v_pruning_controller = NULL; PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations - __pyx_t_5_tree_SIZE_t __pyx_t_1; 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__Pyx_XDECREF(__pyx_t_5); __PYX_XDEC_MEMVIEW(&__pyx_t_6, 1); - __Pyx_AddTraceback("_tree._build_pruned_tree_ccp", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("stpredictions.models.OK3._tree._build_pruned_tree_ccp", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __PYX_XDEC_MEMVIEW(&__pyx_v_leaves_in_subtree, 1); @@ -21619,7 +21238,7 @@ static PyObject *__pyx_pf_5_tree__build_pruned_tree_ccp(CYTHON_UNUSED PyObject * return __pyx_r; } -/* "_tree.pyx":1588 +/* "stpredictions/models/OK3/_tree.pyx":1588 * * * def ccp_pruning_path(Tree orig_tree): # <<<<<<<<<<<<<< @@ -21628,18 +21247,18 @@ static PyObject *__pyx_pf_5_tree__build_pruned_tree_ccp(CYTHON_UNUSED PyObject * */ /* Python wrapper */ -static PyObject *__pyx_pw_5_tree_3ccp_pruning_path(PyObject *__pyx_self, PyObject *__pyx_v_orig_tree); /*proto*/ -static char __pyx_doc_5_tree_2ccp_pruning_path[] = "Computes the cost complexity pruning path.\n\n Parameters\n ----------\n tree : Tree\n Original tree.\n\n Returns\n -------\n path_info : dict\n Information about pruning path with attributes:\n\n ccp_alphas : ndarray\n Effective alphas of subtree during pruning.\n\n impurities : ndarray\n Sum of the impurities of the subtree leaves for the\n corresponding alpha value in ``ccp_alphas``.\n "; -static PyMethodDef __pyx_mdef_5_tree_3ccp_pruning_path = {"ccp_pruning_path", (PyCFunction)__pyx_pw_5_tree_3ccp_pruning_path, METH_O, __pyx_doc_5_tree_2ccp_pruning_path}; -static PyObject *__pyx_pw_5_tree_3ccp_pruning_path(PyObject *__pyx_self, PyObject *__pyx_v_orig_tree) { +static PyObject *__pyx_pw_13stpredictions_6models_3OK3_5_tree_3ccp_pruning_path(PyObject *__pyx_self, PyObject *__pyx_v_orig_tree); /*proto*/ +static char __pyx_doc_13stpredictions_6models_3OK3_5_tree_2ccp_pruning_path[] = "Computes the cost complexity pruning path.\n\n Parameters\n ----------\n tree : Tree\n Original tree.\n\n Returns\n -------\n path_info : dict\n Information about pruning path with attributes:\n\n ccp_alphas : ndarray\n Effective alphas of subtree during pruning.\n\n impurities : ndarray\n Sum of the impurities of the subtree leaves for the\n corresponding alpha value in ``ccp_alphas``.\n "; +static PyMethodDef __pyx_mdef_13stpredictions_6models_3OK3_5_tree_3ccp_pruning_path = {"ccp_pruning_path", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_3ccp_pruning_path, METH_O, __pyx_doc_13stpredictions_6models_3OK3_5_tree_2ccp_pruning_path}; 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} -static PyObject *__pyx_pf_5_tree_2ccp_pruning_path(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_5_tree_Tree *__pyx_v_orig_tree) { +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_5_tree_2ccp_pruning_path(CYTHON_UNUSED PyObject *__pyx_self, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_v_orig_tree) { __Pyx_memviewslice __pyx_v_leaves_in_subtree = { 0, 0, { 0 }, { 0 }, { 0 } }; - struct __pyx_obj_5_tree__PathFinder *__pyx_v_path_finder = NULL; - __pyx_t_5_tree_UINT32_t __pyx_v_total_items; + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *__pyx_v_path_finder = NULL; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t __pyx_v_total_items; PyArrayObject *__pyx_v_ccp_alphas = 0; PyArrayObject *__pyx_v_impurities = 0; - __pyx_t_5_tree_UINT32_t __pyx_v_count; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t __pyx_v_count; PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations PyObject *__pyx_t_1 = NULL; @@ -21664,7 +21283,7 @@ static PyObject *__pyx_pf_5_tree_2ccp_pruning_path(CYTHON_UNUSED PyObject *__pyx PyObject *__pyx_t_3 = NULL; 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if (unlikely(!__pyx_t_3)) __PYX_ERR(0, 1670, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_v_stack = ((struct __pyx_obj_7sklearn_4tree_6_utils_Stack *)__pyx_t_3); + __pyx_v_stack = ((struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_t_3); __pyx_t_3 = 0; - /* "_tree.pyx":1673 + /* "stpredictions/models/OK3/_tree.pyx":1673 * StackRecord stack_record * * with nogil: # <<<<<<<<<<<<<< @@ -22051,17 +21670,17 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree #endif /*try:*/ { - /* "_tree.pyx":1675 + /* "stpredictions/models/OK3/_tree.pyx":1675 * with nogil: * # push root node onto stack * rc = stack.push(0, 0, 0, _TREE_UNDEFINED, 0, 0.0, 0) # <<<<<<<<<<<<<< * if rc == -1: * with gil: */ - __pyx_t_1 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, 0, 0, 0, __pyx_v_5_tree__TREE_UNDEFINED, 0, 0.0, 0); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 1675, __pyx_L4_error) + __pyx_t_1 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, 0, 0, 0, __pyx_v_13stpredictions_6models_3OK3_5_tree__TREE_UNDEFINED, 0, 0.0, 0); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 1675, __pyx_L4_error) __pyx_v_rc = __pyx_t_1; - /* "_tree.pyx":1676 + /* "stpredictions/models/OK3/_tree.pyx":1676 * # push root node onto stack * rc = stack.push(0, 0, 0, _TREE_UNDEFINED, 0, 0.0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -22071,7 +21690,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_4 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_4) { - /* "_tree.pyx":1677 + /* "stpredictions/models/OK3/_tree.pyx":1677 * rc = stack.push(0, 0, 0, _TREE_UNDEFINED, 0, 0.0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -22084,7 +21703,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree #endif /*try:*/ { - /* "_tree.pyx":1678 + /* "stpredictions/models/OK3/_tree.pyx":1678 * if rc == -1: * with gil: * raise MemoryError("pruning tree") # <<<<<<<<<<<<<< @@ -22098,7 +21717,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __PYX_ERR(0, 1678, __pyx_L8_error) } - /* "_tree.pyx":1677 + /* "stpredictions/models/OK3/_tree.pyx":1677 * rc = stack.push(0, 0, 0, _TREE_UNDEFINED, 0, 0.0, 0) * if rc == -1: * with gil: # <<<<<<<<<<<<<< @@ -22115,7 +21734,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree } } - /* "_tree.pyx":1676 + /* "stpredictions/models/OK3/_tree.pyx":1676 * # push root node onto stack * rc = stack.push(0, 0, 0, _TREE_UNDEFINED, 0, 0.0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -22124,7 +21743,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ } - /* "_tree.pyx":1680 + /* "stpredictions/models/OK3/_tree.pyx":1680 * raise MemoryError("pruning tree") * * while not stack.is_empty(): # <<<<<<<<<<<<<< @@ -22132,19 +21751,19 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree * */ while (1) { - __pyx_t_4 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0); + __pyx_t_4 = ((!(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0); if (!__pyx_t_4) break; - /* "_tree.pyx":1681 + /* "stpredictions/models/OK3/_tree.pyx":1681 * * while not stack.is_empty(): * stack.pop(&stack_record) # <<<<<<<<<<<<<< * * orig_node_id = stack_record.start */ - (void)(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record))); + (void)(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record))); - /* "_tree.pyx":1683 + /* "stpredictions/models/OK3/_tree.pyx":1683 * stack.pop(&stack_record) * * orig_node_id = stack_record.start # <<<<<<<<<<<<<< @@ -22154,7 +21773,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_5 = __pyx_v_stack_record.start; __pyx_v_orig_node_id = __pyx_t_5; - /* "_tree.pyx":1684 + /* "stpredictions/models/OK3/_tree.pyx":1684 * * orig_node_id = stack_record.start * depth = stack_record.depth # <<<<<<<<<<<<<< @@ -22164,7 +21783,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_5 = __pyx_v_stack_record.depth; __pyx_v_depth = __pyx_t_5; - /* "_tree.pyx":1685 + /* "stpredictions/models/OK3/_tree.pyx":1685 * orig_node_id = stack_record.start * depth = stack_record.depth * parent = stack_record.parent # <<<<<<<<<<<<<< @@ -22174,7 +21793,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_5 = __pyx_v_stack_record.parent; __pyx_v_parent = __pyx_t_5; - /* "_tree.pyx":1686 + /* "stpredictions/models/OK3/_tree.pyx":1686 * depth = stack_record.depth * parent = stack_record.parent * is_left = stack_record.is_left # <<<<<<<<<<<<<< @@ -22184,7 +21803,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_4 = __pyx_v_stack_record.is_left; __pyx_v_is_left = __pyx_t_4; - /* "_tree.pyx":1688 + /* "stpredictions/models/OK3/_tree.pyx":1688 * is_left = stack_record.is_left * * is_leaf = leaves_in_subtree[orig_node_id] # <<<<<<<<<<<<<< @@ -22194,7 +21813,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_6 = __pyx_v_orig_node_id; __pyx_v_is_leaf = (*((unsigned char const *) ( /* dim=0 */ (__pyx_v_leaves_in_subtree.data + __pyx_t_6 * __pyx_v_leaves_in_subtree.strides[0]) ))); - /* "_tree.pyx":1689 + /* "stpredictions/models/OK3/_tree.pyx":1689 * * is_leaf = leaves_in_subtree[orig_node_id] * node = &orig_tree.nodes[orig_node_id] # <<<<<<<<<<<<<< @@ -22203,17 +21822,17 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ __pyx_v_node = (&(__pyx_v_orig_tree->nodes[__pyx_v_orig_node_id])); - /* "_tree.pyx":1691 + /* "stpredictions/models/OK3/_tree.pyx":1691 * node = &orig_tree.nodes[orig_node_id] * * new_node_id = tree._add_node( # <<<<<<<<<<<<<< * parent, is_left, is_leaf, node.feature, node.threshold, * node.impurity, node.n_node_samples, */ - __pyx_t_7 = ((struct __pyx_vtabstruct_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_add_node(__pyx_v_tree, __pyx_v_parent, __pyx_v_is_left, __pyx_v_is_leaf, __pyx_v_node->feature, __pyx_v_node->threshold, __pyx_v_node->impurity, __pyx_v_node->n_node_samples, __pyx_v_node->weighted_n_node_samples); if (unlikely(__pyx_t_7 == ((__pyx_t_5_tree_SIZE_t)-1))) __PYX_ERR(0, 1691, __pyx_L4_error) + __pyx_t_7 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_add_node(__pyx_v_tree, __pyx_v_parent, __pyx_v_is_left, __pyx_v_is_leaf, __pyx_v_node->feature, __pyx_v_node->threshold, __pyx_v_node->impurity, __pyx_v_node->n_node_samples, __pyx_v_node->weighted_n_node_samples); if (unlikely(__pyx_t_7 == ((__pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t)-1))) __PYX_ERR(0, 1691, __pyx_L4_error) __pyx_v_new_node_id = __pyx_t_7; - /* "_tree.pyx":1696 + /* "stpredictions/models/OK3/_tree.pyx":1696 * node.weighted_n_node_samples) * * if new_node_id == SIZE_MAX: # <<<<<<<<<<<<<< @@ -22223,7 +21842,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_4 = ((__pyx_v_new_node_id == SIZE_MAX) != 0); if (__pyx_t_4) { - /* "_tree.pyx":1697 + /* "stpredictions/models/OK3/_tree.pyx":1697 * * if new_node_id == SIZE_MAX: * rc = -1 # <<<<<<<<<<<<<< @@ -22232,7 +21851,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ __pyx_v_rc = -1; - /* "_tree.pyx":1698 + /* "stpredictions/models/OK3/_tree.pyx":1698 * if new_node_id == SIZE_MAX: * rc = -1 * break # <<<<<<<<<<<<<< @@ -22241,7 +21860,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ goto __pyx_L11_break; - /* "_tree.pyx":1696 + /* "stpredictions/models/OK3/_tree.pyx":1696 * node.weighted_n_node_samples) * * if new_node_id == SIZE_MAX: # <<<<<<<<<<<<<< @@ -22250,7 +21869,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ } - /* "_tree.pyx":1701 + /* "stpredictions/models/OK3/_tree.pyx":1701 * * # copy value from original tree to new tree * orig_value_ptr = orig_tree.value + tree.K_y.shape[0] * orig_node_id # <<<<<<<<<<<<<< @@ -22259,7 +21878,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ __pyx_v_orig_value_ptr = (__pyx_v_orig_tree->value + ((__pyx_v_tree->K_y->dimensions[0]) * __pyx_v_orig_node_id)); - /* "_tree.pyx":1702 + /* "stpredictions/models/OK3/_tree.pyx":1702 * # copy value from original tree to new tree * orig_value_ptr = orig_tree.value + tree.K_y.shape[0] * orig_node_id * new_value_ptr = tree.value + tree.K_y.shape[0] * new_node_id # <<<<<<<<<<<<<< @@ -22268,7 +21887,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ __pyx_v_new_value_ptr = (__pyx_v_tree->value + ((__pyx_v_tree->K_y->dimensions[0]) * __pyx_v_new_node_id)); - /* "_tree.pyx":1703 + /* "stpredictions/models/OK3/_tree.pyx":1703 * orig_value_ptr = orig_tree.value + tree.K_y.shape[0] * orig_node_id * new_value_ptr = tree.value + tree.K_y.shape[0] * new_node_id * memcpy(new_value_ptr, orig_value_ptr, sizeof(double) * tree.K_y.shape[0]) # <<<<<<<<<<<<<< @@ -22277,7 +21896,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ (void)(memcpy(__pyx_v_new_value_ptr, __pyx_v_orig_value_ptr, ((sizeof(double)) * (__pyx_v_tree->K_y->dimensions[0])))); - /* "_tree.pyx":1705 + /* "stpredictions/models/OK3/_tree.pyx":1705 * memcpy(new_value_ptr, orig_value_ptr, sizeof(double) * tree.K_y.shape[0]) * * if not is_leaf: # <<<<<<<<<<<<<< @@ -22287,17 +21906,17 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_4 = ((!(__pyx_v_is_leaf != 0)) != 0); if (__pyx_t_4) { - /* "_tree.pyx":1707 + /* "stpredictions/models/OK3/_tree.pyx":1707 * if not is_leaf: * # Push right child on stack * rc = stack.push( # <<<<<<<<<<<<<< * node.right_child, 0, depth + 1, new_node_id, 0, 0.0, 0) * if rc == -1: */ - __pyx_t_1 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_node->right_child, 0, (__pyx_v_depth + 1), __pyx_v_new_node_id, 0, 0.0, 0); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 1707, __pyx_L4_error) + __pyx_t_1 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_node->right_child, 0, (__pyx_v_depth + 1), __pyx_v_new_node_id, 0, 0.0, 0); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 1707, __pyx_L4_error) __pyx_v_rc = __pyx_t_1; - /* "_tree.pyx":1709 + /* "stpredictions/models/OK3/_tree.pyx":1709 * rc = stack.push( * node.right_child, 0, depth + 1, new_node_id, 0, 0.0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -22307,7 +21926,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_4 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_4) { - /* "_tree.pyx":1710 + /* "stpredictions/models/OK3/_tree.pyx":1710 * node.right_child, 0, depth + 1, new_node_id, 0, 0.0, 0) * if rc == -1: * break # <<<<<<<<<<<<<< @@ -22316,7 +21935,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ goto __pyx_L11_break; - /* "_tree.pyx":1709 + /* "stpredictions/models/OK3/_tree.pyx":1709 * rc = stack.push( * node.right_child, 0, depth + 1, new_node_id, 0, 0.0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -22325,17 +21944,17 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ } - /* "_tree.pyx":1713 + /* "stpredictions/models/OK3/_tree.pyx":1713 * * # push left child on stack * rc = stack.push( # <<<<<<<<<<<<<< * node.left_child, 0, depth + 1, new_node_id, 1, 0.0, 0) * if rc == -1: */ - __pyx_t_1 = ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_node->left_child, 0, (__pyx_v_depth + 1), __pyx_v_new_node_id, 1, 0.0, 0); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 1713, __pyx_L4_error) + __pyx_t_1 = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->push(__pyx_v_stack, __pyx_v_node->left_child, 0, (__pyx_v_depth + 1), __pyx_v_new_node_id, 1, 0.0, 0); if (unlikely(__pyx_t_1 == ((int)-1))) __PYX_ERR(0, 1713, __pyx_L4_error) __pyx_v_rc = __pyx_t_1; - /* "_tree.pyx":1715 + /* "stpredictions/models/OK3/_tree.pyx":1715 * rc = stack.push( * node.left_child, 0, depth + 1, new_node_id, 1, 0.0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -22345,7 +21964,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_4 = ((__pyx_v_rc == -1L) != 0); if (__pyx_t_4) { - /* "_tree.pyx":1716 + /* "stpredictions/models/OK3/_tree.pyx":1716 * node.left_child, 0, depth + 1, new_node_id, 1, 0.0, 0) * if rc == -1: * break # <<<<<<<<<<<<<< @@ -22354,7 +21973,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ goto __pyx_L11_break; - /* "_tree.pyx":1715 + /* "stpredictions/models/OK3/_tree.pyx":1715 * rc = stack.push( * node.left_child, 0, depth + 1, new_node_id, 1, 0.0, 0) * if rc == -1: # <<<<<<<<<<<<<< @@ -22363,7 +21982,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ } - /* "_tree.pyx":1705 + /* "stpredictions/models/OK3/_tree.pyx":1705 * memcpy(new_value_ptr, orig_value_ptr, sizeof(double) * tree.K_y.shape[0]) * * if not is_leaf: # <<<<<<<<<<<<<< @@ -22372,7 +21991,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ } - /* "_tree.pyx":1718 + /* "stpredictions/models/OK3/_tree.pyx":1718 * break * * if depth > max_depth_seen: # <<<<<<<<<<<<<< @@ -22382,7 +22001,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_4 = ((__pyx_v_depth > __pyx_v_max_depth_seen) != 0); if (__pyx_t_4) { - /* "_tree.pyx":1719 + /* "stpredictions/models/OK3/_tree.pyx":1719 * * if depth > max_depth_seen: * max_depth_seen = depth # <<<<<<<<<<<<<< @@ -22391,7 +22010,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ __pyx_v_max_depth_seen = __pyx_v_depth; - /* "_tree.pyx":1718 + /* "stpredictions/models/OK3/_tree.pyx":1718 * break * * if depth > max_depth_seen: # <<<<<<<<<<<<<< @@ -22402,7 +22021,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree } __pyx_L11_break:; - /* "_tree.pyx":1721 + /* "stpredictions/models/OK3/_tree.pyx":1721 * max_depth_seen = depth * * if rc >= 0: # <<<<<<<<<<<<<< @@ -22412,7 +22031,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_4 = ((__pyx_v_rc >= 0) != 0); if (__pyx_t_4) { - /* "_tree.pyx":1722 + /* "stpredictions/models/OK3/_tree.pyx":1722 * * if rc >= 0: * tree.max_depth = max_depth_seen # <<<<<<<<<<<<<< @@ -22421,7 +22040,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ __pyx_v_tree->max_depth = __pyx_v_max_depth_seen; - /* "_tree.pyx":1721 + /* "stpredictions/models/OK3/_tree.pyx":1721 * max_depth_seen = depth * * if rc >= 0: # <<<<<<<<<<<<<< @@ -22431,7 +22050,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree } } - /* "_tree.pyx":1673 + /* "stpredictions/models/OK3/_tree.pyx":1673 * StackRecord stack_record * * with nogil: # <<<<<<<<<<<<<< @@ -22457,7 +22076,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree } } - /* "_tree.pyx":1724 + /* "stpredictions/models/OK3/_tree.pyx":1724 * tree.max_depth = max_depth_seen * * tree.K_y = orig_tree.K_y # <<<<<<<<<<<<<< @@ -22472,7 +22091,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_v_tree->K_y = ((PyArrayObject *)__pyx_t_3); __pyx_t_3 = 0; - /* "_tree.pyx":1725 + /* "stpredictions/models/OK3/_tree.pyx":1725 * * tree.K_y = orig_tree.K_y * tree.y = orig_tree.y # <<<<<<<<<<<<<< @@ -22487,7 +22106,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_v_tree->y = ((PyArrayObject *)__pyx_t_3); __pyx_t_3 = 0; - /* "_tree.pyx":1726 + /* "stpredictions/models/OK3/_tree.pyx":1726 * tree.K_y = orig_tree.K_y * tree.y = orig_tree.y * if rc == -1: # <<<<<<<<<<<<<< @@ -22496,7 +22115,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_t_4 = ((__pyx_v_rc == -1L) != 0); if (unlikely(__pyx_t_4)) { - /* "_tree.pyx":1727 + /* "stpredictions/models/OK3/_tree.pyx":1727 * tree.y = orig_tree.y * if rc == -1: * raise MemoryError("pruning tree") # <<<<<<<<<<<<<< @@ -22507,7 +22126,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __PYX_ERR(0, 1727, __pyx_L1_error) - /* "_tree.pyx":1726 + /* "stpredictions/models/OK3/_tree.pyx":1726 * tree.K_y = orig_tree.K_y * tree.y = orig_tree.y * if rc == -1: # <<<<<<<<<<<<<< @@ -22515,7 +22134,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree */ } - /* "_tree.pyx":1632 + /* "stpredictions/models/OK3/_tree.pyx":1632 * * * cdef _build_pruned_tree( # <<<<<<<<<<<<<< @@ -22529,7 +22148,7 @@ static PyObject *__pyx_f_5_tree__build_pruned_tree(struct __pyx_obj_5_tree_Tree __pyx_L1_error:; 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if (__pyx_t_1) { - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":875 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":875 * base = PyArray_BASE(arr) * if base is NULL: * return None # <<<<<<<<<<<<<< @@ -23753,7 +23372,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py __pyx_r = Py_None; __Pyx_INCREF(Py_None); goto __pyx_L0; - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":874 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":874 * cdef inline object get_array_base(ndarray arr): * base = PyArray_BASE(arr) * if base is NULL: # <<<<<<<<<<<<<< @@ -23762,7 +23381,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py */ } - /* "../../../../anaconda3/envs/florence_library/lib/python3.9/site-packages/numpy/__init__.pxd":876 + /* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":876 * if base is NULL: * return None * return base # <<<<<<<<<<<<<< @@ -23774,7 +23393,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__py __pyx_r = ((PyObject *)__pyx_v_base); 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+ __Pyx_AddTraceback("FromPyStructUtility.__pyx_convert__from_py_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node", __pyx_clineno, __pyx_lineno, __pyx_filename); if (__Pyx_GetException(&__pyx_t_8, &__pyx_t_7, &__pyx_t_2) < 0) __PYX_ERR(1, 33, __pyx_L30_except_error) __Pyx_GOTREF(__pyx_t_8); __Pyx_GOTREF(__pyx_t_7); @@ -24704,7 +24323,7 @@ static struct __pyx_t_5_tree_Node __pyx_convert__from_py_struct____pyx_t_5_tree_ */ __pyx_t_6 = __Pyx_PyErr_ExceptionMatches(__pyx_builtin_KeyError); if (__pyx_t_6) { - __Pyx_AddTraceback("FromPyStructUtility.__pyx_convert__from_py_struct____pyx_t_5_tree_Node", __pyx_clineno, __pyx_lineno, __pyx_filename); + __Pyx_AddTraceback("FromPyStructUtility.__pyx_convert__from_py_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node", __pyx_clineno, __pyx_lineno, __pyx_filename); if (__Pyx_GetException(&__pyx_t_2, &__pyx_t_7, &__pyx_t_8) < 0) __PYX_ERR(1, 38, __pyx_L38_except_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_GOTREF(__pyx_t_7); @@ -24806,7 +24425,7 @@ static struct __pyx_t_5_tree_Node __pyx_convert__from_py_struct____pyx_t_5_tree_ */ __pyx_t_6 = __Pyx_PyErr_ExceptionMatches(__pyx_builtin_KeyError); 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__Pyx_pretend_to_initialize(&__pyx_r); __pyx_L0:; __Pyx_XDECREF(__pyx_v_value); @@ -38359,10 +37978,10 @@ static PyObject *__pyx_format_from_typeinfo(__Pyx_TypeInfo *__pyx_v_type) { __Pyx_RefNannyFinishContext(); return __pyx_r; } -static struct __pyx_vtabstruct_5_tree_Tree __pyx_vtable_5_tree_Tree; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree __pyx_vtable_13stpredictions_6models_3OK3_5_tree_Tree; -static PyObject *__pyx_tp_new_5_tree_Tree(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_5_tree_Tree *p; +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree_Tree(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); @@ -38370,19 +37989,19 @@ static PyObject *__pyx_tp_new_5_tree_Tree(PyTypeObject *t, PyObject *a, PyObject o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_5_tree_Tree *)o); - p->__pyx_vtab = __pyx_vtabptr_5_tree_Tree; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)o); + p->__pyx_vtab = __pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_Tree; p->K_y = ((PyArrayObject *)Py_None); Py_INCREF(Py_None); p->y = ((PyArrayObject *)Py_None); Py_INCREF(Py_None); - if (unlikely(__pyx_pw_5_tree_4Tree_1__cinit__(o, a, k) < 0)) goto bad; + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_1__cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } -static void __pyx_tp_dealloc_5_tree_Tree(PyObject *o) { - struct __pyx_obj_5_tree_Tree *p = (struct __pyx_obj_5_tree_Tree *)o; +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree_Tree(PyObject *o) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *p = (struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)o; #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; @@ -38393,7 +38012,7 @@ static void __pyx_tp_dealloc_5_tree_Tree(PyObject *o) { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); - __pyx_pw_5_tree_4Tree_3__dealloc__(o); + __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_3__dealloc__(o); __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); PyErr_Restore(etype, eval, etb); } @@ -38402,9 +38021,9 @@ static void __pyx_tp_dealloc_5_tree_Tree(PyObject *o) { (*Py_TYPE(o)->tp_free)(o); } -static int __pyx_tp_traverse_5_tree_Tree(PyObject *o, visitproc v, void *a) { +static int __pyx_tp_traverse_13stpredictions_6models_3OK3_5_tree_Tree(PyObject *o, visitproc v, void *a) { int e; - struct __pyx_obj_5_tree_Tree *p = (struct __pyx_obj_5_tree_Tree *)o; + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *p = (struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)o; if (p->K_y) { e = (*v)(((PyObject *)p->K_y), a); if (e) return e; } @@ -38414,9 +38033,9 @@ static int __pyx_tp_traverse_5_tree_Tree(PyObject *o, visitproc v, void *a) { return 0; } -static int __pyx_tp_clear_5_tree_Tree(PyObject *o) { +static int __pyx_tp_clear_13stpredictions_6models_3OK3_5_tree_Tree(PyObject *o) { PyObject* tmp; - struct __pyx_obj_5_tree_Tree *p = (struct __pyx_obj_5_tree_Tree *)o; + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *p = (struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *)o; tmp = ((PyObject*)p->K_y); p->K_y = ((PyArrayObject *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); @@ -38426,49 +38045,49 @@ static int __pyx_tp_clear_5_tree_Tree(PyObject *o) { return 0; } -static PyObject *__pyx_getprop_5_tree_4Tree_children_left(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_13children_left_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_children_left(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_13children_left_1__get__(o); } -static PyObject *__pyx_getprop_5_tree_4Tree_children_right(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_14children_right_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_children_right(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_14children_right_1__get__(o); } -static PyObject *__pyx_getprop_5_tree_4Tree_n_leaves(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_8n_leaves_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_n_leaves(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_8n_leaves_1__get__(o); } -static PyObject *__pyx_getprop_5_tree_4Tree_feature(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_7feature_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_feature(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_7feature_1__get__(o); } -static PyObject *__pyx_getprop_5_tree_4Tree_threshold(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_9threshold_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_threshold(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_9threshold_1__get__(o); } -static PyObject *__pyx_getprop_5_tree_4Tree_impurity(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_8impurity_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_impurity(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_8impurity_1__get__(o); } -static PyObject *__pyx_getprop_5_tree_4Tree_n_node_samples(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_14n_node_samples_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_n_node_samples(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_14n_node_samples_1__get__(o); } -static PyObject *__pyx_getprop_5_tree_4Tree_weighted_n_node_samples(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_23weighted_n_node_samples_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_weighted_n_node_samples(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_23weighted_n_node_samples_1__get__(o); } -static PyObject *__pyx_getprop_5_tree_4Tree_value(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_5value_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_value(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_5value_1__get__(o); } -static PyObject *__pyx_getprop_5_tree_4Tree_n_features(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_10n_features_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_n_features(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_10n_features_1__get__(o); } -static int __pyx_setprop_5_tree_4Tree_n_features(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { +static int __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_n_features(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { if (v) { - return __pyx_pw_5_tree_4Tree_10n_features_3__set__(o, v); + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_10n_features_3__set__(o, v); } else { PyErr_SetString(PyExc_NotImplementedError, "__del__"); @@ -38476,13 +38095,13 @@ static int __pyx_setprop_5_tree_4Tree_n_features(PyObject *o, PyObject *v, CYTHO } } -static PyObject *__pyx_getprop_5_tree_4Tree_max_depth(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_9max_depth_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_max_depth(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_9max_depth_1__get__(o); } -static int __pyx_setprop_5_tree_4Tree_max_depth(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { +static int __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_max_depth(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { if (v) { - return __pyx_pw_5_tree_4Tree_9max_depth_3__set__(o, v); + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_9max_depth_3__set__(o, v); } else { PyErr_SetString(PyExc_NotImplementedError, "__del__"); @@ -38490,13 +38109,13 @@ static int __pyx_setprop_5_tree_4Tree_max_depth(PyObject *o, PyObject *v, CYTHON } } -static PyObject *__pyx_getprop_5_tree_4Tree_node_count(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_10node_count_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_node_count(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_10node_count_1__get__(o); } -static int __pyx_setprop_5_tree_4Tree_node_count(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { +static int __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_node_count(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { if (v) { - return __pyx_pw_5_tree_4Tree_10node_count_3__set__(o, v); + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_10node_count_3__set__(o, v); } else { PyErr_SetString(PyExc_NotImplementedError, "__del__"); @@ -38504,13 +38123,13 @@ static int __pyx_setprop_5_tree_4Tree_node_count(PyObject *o, PyObject *v, CYTHO } } -static PyObject *__pyx_getprop_5_tree_4Tree_capacity(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_8capacity_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_capacity(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_8capacity_1__get__(o); } -static int __pyx_setprop_5_tree_4Tree_capacity(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { +static int __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_capacity(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { if (v) { - return __pyx_pw_5_tree_4Tree_8capacity_3__set__(o, v); + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_8capacity_3__set__(o, v); } else { PyErr_SetString(PyExc_NotImplementedError, "__del__"); @@ -38518,69 +38137,69 @@ static int __pyx_setprop_5_tree_4Tree_capacity(PyObject *o, PyObject *v, CYTHON_ } } -static PyObject *__pyx_getprop_5_tree_4Tree_K_y(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_3K_y_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_K_y(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_3K_y_1__get__(o); } -static int __pyx_setprop_5_tree_4Tree_K_y(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { +static int __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_K_y(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { if (v) { - return __pyx_pw_5_tree_4Tree_3K_y_3__set__(o, v); + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_3K_y_3__set__(o, v); } else { - return __pyx_pw_5_tree_4Tree_3K_y_5__del__(o); + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_3K_y_5__del__(o); } } -static PyObject *__pyx_getprop_5_tree_4Tree_y(PyObject *o, CYTHON_UNUSED void *x) { - return __pyx_pw_5_tree_4Tree_1y_1__get__(o); +static PyObject *__pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_y(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_1y_1__get__(o); } -static int __pyx_setprop_5_tree_4Tree_y(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { +static int __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_y(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) { if (v) { - return __pyx_pw_5_tree_4Tree_1y_3__set__(o, v); + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_1y_3__set__(o, v); } else { - return __pyx_pw_5_tree_4Tree_1y_5__del__(o); + return __pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_1y_5__del__(o); } } -static PyMethodDef __pyx_methods_5_tree_Tree[] = { - {"__reduce__", (PyCFunction)__pyx_pw_5_tree_4Tree_5__reduce__, METH_NOARGS, __pyx_doc_5_tree_4Tree_4__reduce__}, - {"__getstate__", (PyCFunction)__pyx_pw_5_tree_4Tree_7__getstate__, METH_NOARGS, __pyx_doc_5_tree_4Tree_6__getstate__}, - {"__setstate__", (PyCFunction)__pyx_pw_5_tree_4Tree_9__setstate__, METH_O, __pyx_doc_5_tree_4Tree_8__setstate__}, - {"predict", (PyCFunction)__pyx_pw_5_tree_4Tree_11predict, METH_O, __pyx_doc_5_tree_4Tree_10predict}, - {"decode_tree", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_4Tree_13decode_tree, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree_4Tree_12decode_tree}, - {"apply", (PyCFunction)__pyx_pw_5_tree_4Tree_15apply, METH_O, __pyx_doc_5_tree_4Tree_14apply}, - {"decision_path", (PyCFunction)__pyx_pw_5_tree_4Tree_17decision_path, METH_O, __pyx_doc_5_tree_4Tree_16decision_path}, - {"compute_feature_importances", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_4Tree_19compute_feature_importances, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree_4Tree_18compute_feature_importances}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_5_tree_Tree[] = { + {"__reduce__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_5__reduce__, METH_NOARGS, __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_4__reduce__}, + {"__getstate__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_7__getstate__, METH_NOARGS, __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_6__getstate__}, + {"__setstate__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_9__setstate__, METH_O, __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_8__setstate__}, + {"predict", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_11predict, METH_O, __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_10predict}, + {"decode_tree", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_13decode_tree, METH_VARARGS|METH_KEYWORDS, __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_12decode_tree}, + {"apply", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_15apply, METH_O, __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_14apply}, + {"decision_path", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_17decision_path, METH_O, __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_16decision_path}, + {"compute_feature_importances", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_13stpredictions_6models_3OK3_5_tree_4Tree_19compute_feature_importances, METH_VARARGS|METH_KEYWORDS, __pyx_doc_13stpredictions_6models_3OK3_5_tree_4Tree_18compute_feature_importances}, {0, 0, 0, 0} }; -static struct PyGetSetDef __pyx_getsets_5_tree_Tree[] = { - {(char *)"children_left", __pyx_getprop_5_tree_4Tree_children_left, 0, (char *)0, 0}, - {(char *)"children_right", __pyx_getprop_5_tree_4Tree_children_right, 0, (char *)0, 0}, - {(char *)"n_leaves", __pyx_getprop_5_tree_4Tree_n_leaves, 0, (char *)0, 0}, - {(char *)"feature", __pyx_getprop_5_tree_4Tree_feature, 0, (char *)0, 0}, - {(char *)"threshold", __pyx_getprop_5_tree_4Tree_threshold, 0, (char *)0, 0}, - {(char *)"impurity", __pyx_getprop_5_tree_4Tree_impurity, 0, (char *)0, 0}, - {(char *)"n_node_samples", __pyx_getprop_5_tree_4Tree_n_node_samples, 0, (char *)0, 0}, - {(char *)"weighted_n_node_samples", __pyx_getprop_5_tree_4Tree_weighted_n_node_samples, 0, (char *)0, 0}, - {(char *)"value", __pyx_getprop_5_tree_4Tree_value, 0, (char *)0, 0}, - {(char *)"n_features", __pyx_getprop_5_tree_4Tree_n_features, __pyx_setprop_5_tree_4Tree_n_features, (char *)0, 0}, - {(char *)"max_depth", __pyx_getprop_5_tree_4Tree_max_depth, __pyx_setprop_5_tree_4Tree_max_depth, (char *)0, 0}, - {(char *)"node_count", __pyx_getprop_5_tree_4Tree_node_count, __pyx_setprop_5_tree_4Tree_node_count, (char *)0, 0}, - {(char *)"capacity", __pyx_getprop_5_tree_4Tree_capacity, __pyx_setprop_5_tree_4Tree_capacity, (char *)0, 0}, - {(char *)"K_y", __pyx_getprop_5_tree_4Tree_K_y, __pyx_setprop_5_tree_4Tree_K_y, (char *)0, 0}, - {(char *)"y", __pyx_getprop_5_tree_4Tree_y, __pyx_setprop_5_tree_4Tree_y, (char *)0, 0}, +static struct PyGetSetDef __pyx_getsets_13stpredictions_6models_3OK3_5_tree_Tree[] = { + {(char *)"children_left", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_children_left, 0, (char *)0, 0}, + {(char *)"children_right", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_children_right, 0, (char *)0, 0}, + {(char *)"n_leaves", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_n_leaves, 0, (char *)0, 0}, + {(char *)"feature", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_feature, 0, (char *)0, 0}, + {(char *)"threshold", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_threshold, 0, (char *)0, 0}, + {(char *)"impurity", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_impurity, 0, (char *)0, 0}, + {(char *)"n_node_samples", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_n_node_samples, 0, (char *)0, 0}, + {(char *)"weighted_n_node_samples", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_weighted_n_node_samples, 0, (char *)0, 0}, + {(char *)"value", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_value, 0, (char *)0, 0}, + {(char *)"n_features", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_n_features, __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_n_features, (char *)0, 0}, + {(char *)"max_depth", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_max_depth, __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_max_depth, (char *)0, 0}, + {(char *)"node_count", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_node_count, __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_node_count, (char *)0, 0}, + {(char *)"capacity", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_capacity, __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_capacity, (char *)0, 0}, + {(char *)"K_y", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_K_y, __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_K_y, (char *)0, 0}, + {(char *)"y", __pyx_getprop_13stpredictions_6models_3OK3_5_tree_4Tree_y, __pyx_setprop_13stpredictions_6models_3OK3_5_tree_4Tree_y, (char *)0, 0}, {0, 0, 0, 0, 0} }; -static PyTypeObject __pyx_type_5_tree_Tree = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_5_tree_Tree = { PyVarObject_HEAD_INIT(0, 0) - "_tree.Tree", /*tp_name*/ - sizeof(struct __pyx_obj_5_tree_Tree), /*tp_basicsize*/ + "stpredictions.models.OK3._tree.Tree", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_5_tree_Tree, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree_Tree, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -38607,15 +38226,15 @@ static PyTypeObject __pyx_type_5_tree_Tree = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ "Array-based representation of a binary decision tree.\n\n The binary tree is represented as a number of parallel arrays. The i-th\n element of each array holds information about the node `i`. Node 0 is the\n tree's root. You can find a detailed description of all arrays in\n `_tree.pxd`. NOTE: Some of the arrays only apply to either leaves or split\n nodes, resp. In this case the values of nodes of the other type are\n arbitrary!\n\n Attributes\n ----------\n node_count : int\n The number of nodes (internal nodes + leaves) in the tree.\n\n capacity : int\n The current capacity (i.e., size) of the arrays, which is at least as\n great as `node_count`.\n\n max_depth : int\n The depth of the tree, i.e. the maximum depth of its leaves.\n \n value : array of double, shape [node_count, n_train_samples]\n Gives for each node, the weighted list of training samples \n falling in the leaf/leaves bellow the leaf/node. \n (Kind of invert the array given by the 'apply' function.)\n \n K_y : array of double, shape [n_train_samples, n_train_samples]\n The training output Gramm matrix (used to compute the predictions)\n\n y : array of double, shape [n_train_samples, output_vetor_length]\n The training output matrix\n\n children_left : array of int, shape [node_count]\n children_left[i] holds the node id of the left child of node i.\n For leaves, children_left[i] == TREE_LEAF. Otherwise,\n children_left[i] > i. This child handles the case where\n X[:, feature[i]] <= threshold[i].\n\n children_right : array of int, shape [node_count]\n children_right[i] holds the node id of the right child of node i.\n For leaves, children_right[i] == TREE_LEAF. Otherwise,\n children_right[i] > i. This child handles the case where\n X[:, feature[i]] > threshold[i].\n\n feature : array of int, shape [node_count]\n feature[""i] holds the feature to split on, for the internal node i.\n\n threshold : array of double, shape [node_count]\n threshold[i] holds the threshold for the internal node i.\n\n impurity : array of double, shape [node_count]\n impurity[i] holds the impurity (i.e., the value of the splitting\n criterion) at node i.\n\n n_node_samples : array of int, shape [node_count]\n n_node_samples[i] holds the number of training samples reaching node i.\n\n weighted_n_node_samples : array of int, shape [node_count]\n weighted_n_node_samples[i] holds the weighted number of training samples\n reaching node i.\n ", /*tp_doc*/ - __pyx_tp_traverse_5_tree_Tree, /*tp_traverse*/ - __pyx_tp_clear_5_tree_Tree, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_5_tree_Tree, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_5_tree_Tree, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_5_tree_Tree, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_5_tree_Tree, /*tp_methods*/ 0, /*tp_members*/ - __pyx_getsets_5_tree_Tree, /*tp_getset*/ + __pyx_getsets_13stpredictions_6models_3OK3_5_tree_Tree, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ @@ -38623,7 +38242,7 @@ static PyTypeObject __pyx_type_5_tree_Tree = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_5_tree_Tree, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_5_tree_Tree, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -38643,10 +38262,10 @@ static PyTypeObject __pyx_type_5_tree_Tree = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_5_tree_TreeBuilder __pyx_vtable_5_tree_TreeBuilder; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder __pyx_vtable_13stpredictions_6models_3OK3_5_tree_TreeBuilder; -static PyObject *__pyx_tp_new_5_tree_TreeBuilder(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { - struct __pyx_obj_5_tree_TreeBuilder *p; +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree_TreeBuilder(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); @@ -38654,14 +38273,14 @@ static PyObject *__pyx_tp_new_5_tree_TreeBuilder(PyTypeObject *t, CYTHON_UNUSED o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_5_tree_TreeBuilder *)o); - p->__pyx_vtab = __pyx_vtabptr_5_tree_TreeBuilder; - p->splitter = ((struct __pyx_obj_9_splitter_Splitter *)Py_None); Py_INCREF(Py_None); + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *)o); + p->__pyx_vtab = __pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_TreeBuilder; + p->splitter = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)Py_None); Py_INCREF(Py_None); return o; } -static void __pyx_tp_dealloc_5_tree_TreeBuilder(PyObject *o) { - struct __pyx_obj_5_tree_TreeBuilder *p = (struct __pyx_obj_5_tree_TreeBuilder *)o; +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree_TreeBuilder(PyObject *o) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *p = (struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *)o; #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; @@ -38672,37 +38291,37 @@ static void __pyx_tp_dealloc_5_tree_TreeBuilder(PyObject *o) { (*Py_TYPE(o)->tp_free)(o); } -static int __pyx_tp_traverse_5_tree_TreeBuilder(PyObject *o, visitproc v, void *a) { +static int __pyx_tp_traverse_13stpredictions_6models_3OK3_5_tree_TreeBuilder(PyObject *o, visitproc v, void *a) { int e; - struct __pyx_obj_5_tree_TreeBuilder *p = (struct __pyx_obj_5_tree_TreeBuilder *)o; + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *p = (struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *)o; if (p->splitter) { e = (*v)(((PyObject *)p->splitter), a); if (e) return e; } return 0; } -static int __pyx_tp_clear_5_tree_TreeBuilder(PyObject *o) { +static int __pyx_tp_clear_13stpredictions_6models_3OK3_5_tree_TreeBuilder(PyObject *o) { PyObject* tmp; - struct __pyx_obj_5_tree_TreeBuilder *p = (struct __pyx_obj_5_tree_TreeBuilder *)o; + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *p = (struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *)o; tmp = ((PyObject*)p->splitter); - p->splitter = ((struct __pyx_obj_9_splitter_Splitter *)Py_None); Py_INCREF(Py_None); + p->splitter = ((struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); return 0; } -static PyMethodDef __pyx_methods_5_tree_TreeBuilder[] = { - {"build", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_11TreeBuilder_1build, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree_11TreeBuilder_build}, - {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_11TreeBuilder_3__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_11TreeBuilder_5__setstate_cython__, METH_O, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_5_tree_TreeBuilder[] = { + {"build", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_1build, METH_VARARGS|METH_KEYWORDS, __pyx_doc_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_3__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_5__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_5_tree_TreeBuilder = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_5_tree_TreeBuilder = { PyVarObject_HEAD_INIT(0, 0) - "_tree.TreeBuilder", /*tp_name*/ - sizeof(struct __pyx_obj_5_tree_TreeBuilder), /*tp_basicsize*/ + "stpredictions.models.OK3._tree.TreeBuilder", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_5_tree_TreeBuilder, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -38729,13 +38348,13 @@ static PyTypeObject __pyx_type_5_tree_TreeBuilder = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ "Interface for different tree building strategies.", /*tp_doc*/ - __pyx_tp_traverse_5_tree_TreeBuilder, /*tp_traverse*/ - __pyx_tp_clear_5_tree_TreeBuilder, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_5_tree_TreeBuilder, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -38745,7 +38364,7 @@ static PyTypeObject __pyx_type_5_tree_TreeBuilder = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_5_tree_TreeBuilder, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -38765,34 +38384,34 @@ static PyTypeObject __pyx_type_5_tree_TreeBuilder = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_5_tree_DepthFirstTreeBuilder __pyx_vtable_5_tree_DepthFirstTreeBuilder; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder __pyx_vtable_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder; -static PyObject *__pyx_tp_new_5_tree_DepthFirstTreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_5_tree_DepthFirstTreeBuilder *p; - PyObject *o = __pyx_tp_new_5_tree_TreeBuilder(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_5_tree_TreeBuilder(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_5_tree_DepthFirstTreeBuilder *)o); - p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_5_tree_TreeBuilder*)__pyx_vtabptr_5_tree_DepthFirstTreeBuilder; - if (unlikely(__pyx_pw_5_tree_21DepthFirstTreeBuilder_1__cinit__(o, a, k) < 0)) goto bad; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder*)__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder; + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_1__cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } -static PyMethodDef __pyx_methods_5_tree_DepthFirstTreeBuilder[] = { - {"build", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_21DepthFirstTreeBuilder_3build, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree_21DepthFirstTreeBuilder_2build}, - {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_21DepthFirstTreeBuilder_5__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_21DepthFirstTreeBuilder_7__setstate_cython__, METH_O, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder[] = { + {"build", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_3build, METH_VARARGS|METH_KEYWORDS, __pyx_doc_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_2build}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_5__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_21DepthFirstTreeBuilder_7__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_5_tree_DepthFirstTreeBuilder = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder = { PyVarObject_HEAD_INIT(0, 0) - "_tree.DepthFirstTreeBuilder", /*tp_name*/ - sizeof(struct __pyx_obj_5_tree_DepthFirstTreeBuilder), /*tp_basicsize*/ + "stpredictions.models.OK3._tree.DepthFirstTreeBuilder", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_5_tree_TreeBuilder, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -38819,13 +38438,13 @@ static PyTypeObject __pyx_type_5_tree_DepthFirstTreeBuilder = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ "Build a decision tree in depth-first fashion.", /*tp_doc*/ - __pyx_tp_traverse_5_tree_TreeBuilder, /*tp_traverse*/ - __pyx_tp_clear_5_tree_TreeBuilder, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_5_tree_DepthFirstTreeBuilder, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -38835,7 +38454,7 @@ static PyTypeObject __pyx_type_5_tree_DepthFirstTreeBuilder = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_5_tree_DepthFirstTreeBuilder, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_5_tree_DepthFirstTreeBuilder, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -38855,34 +38474,34 @@ static PyTypeObject __pyx_type_5_tree_DepthFirstTreeBuilder = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_5_tree_BestFirstTreeBuilder __pyx_vtable_5_tree_BestFirstTreeBuilder; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder __pyx_vtable_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder; -static PyObject *__pyx_tp_new_5_tree_BestFirstTreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_5_tree_BestFirstTreeBuilder *p; - PyObject *o = __pyx_tp_new_5_tree_TreeBuilder(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_5_tree_TreeBuilder(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_5_tree_BestFirstTreeBuilder *)o); - p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_5_tree_TreeBuilder*)__pyx_vtabptr_5_tree_BestFirstTreeBuilder; - if (unlikely(__pyx_pw_5_tree_20BestFirstTreeBuilder_1__cinit__(o, a, k) < 0)) goto bad; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder*)__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder; + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_1__cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } -static PyMethodDef __pyx_methods_5_tree_BestFirstTreeBuilder[] = { - {"build", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_5_tree_20BestFirstTreeBuilder_3build, METH_VARARGS|METH_KEYWORDS, __pyx_doc_5_tree_20BestFirstTreeBuilder_2build}, - {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_20BestFirstTreeBuilder_5__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_20BestFirstTreeBuilder_7__setstate_cython__, METH_O, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder[] = { + {"build", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_3build, METH_VARARGS|METH_KEYWORDS, __pyx_doc_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_2build}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_5__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_20BestFirstTreeBuilder_7__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_5_tree_BestFirstTreeBuilder = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder = { PyVarObject_HEAD_INIT(0, 0) - "_tree.BestFirstTreeBuilder", /*tp_name*/ - sizeof(struct __pyx_obj_5_tree_BestFirstTreeBuilder), /*tp_basicsize*/ + "stpredictions.models.OK3._tree.BestFirstTreeBuilder", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_5_tree_TreeBuilder, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -38909,13 +38528,13 @@ static PyTypeObject __pyx_type_5_tree_BestFirstTreeBuilder = { 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ "Build a decision tree in best-first fashion.\n\n The best node to expand is given by the node at the frontier that has the\n highest impurity improvement.\n ", /*tp_doc*/ - __pyx_tp_traverse_5_tree_TreeBuilder, /*tp_traverse*/ - __pyx_tp_clear_5_tree_TreeBuilder, /*tp_clear*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_5_tree_TreeBuilder, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_5_tree_BestFirstTreeBuilder, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -38925,7 +38544,7 @@ static PyTypeObject __pyx_type_5_tree_BestFirstTreeBuilder = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_5_tree_BestFirstTreeBuilder, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_5_tree_BestFirstTreeBuilder, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -38945,10 +38564,10 @@ static PyTypeObject __pyx_type_5_tree_BestFirstTreeBuilder = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_5_tree__CCPPruneController __pyx_vtable_5_tree__CCPPruneController; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController __pyx_vtable_13stpredictions_6models_3OK3_5_tree__CCPPruneController; -static PyObject *__pyx_tp_new_5_tree__CCPPruneController(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { - struct __pyx_obj_5_tree__CCPPruneController *p; +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree__CCPPruneController(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); @@ -38956,12 +38575,12 @@ static PyObject *__pyx_tp_new_5_tree__CCPPruneController(PyTypeObject *t, CYTHON o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_5_tree__CCPPruneController *)o); - p->__pyx_vtab = __pyx_vtabptr_5_tree__CCPPruneController; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController *)o); + p->__pyx_vtab = __pyx_vtabptr_13stpredictions_6models_3OK3_5_tree__CCPPruneController; return o; } -static void __pyx_tp_dealloc_5_tree__CCPPruneController(PyObject *o) { +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree__CCPPruneController(PyObject *o) { #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { if (PyObject_CallFinalizerFromDealloc(o)) return; @@ -38970,18 +38589,18 @@ static void __pyx_tp_dealloc_5_tree__CCPPruneController(PyObject *o) { (*Py_TYPE(o)->tp_free)(o); } -static PyMethodDef __pyx_methods_5_tree__CCPPruneController[] = { - {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_19_CCPPruneController_1__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_19_CCPPruneController_3__setstate_cython__, METH_O, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_5_tree__CCPPruneController[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_19_CCPPruneController_3__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_5_tree__CCPPruneController = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_5_tree__CCPPruneController = { PyVarObject_HEAD_INIT(0, 0) - "_tree._CCPPruneController", /*tp_name*/ - sizeof(struct __pyx_obj_5_tree__CCPPruneController), /*tp_basicsize*/ + "stpredictions.models.OK3._tree._CCPPruneController", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__CCPPruneController), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_5_tree__CCPPruneController, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree__CCPPruneController, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -39014,7 +38633,7 @@ static PyTypeObject __pyx_type_5_tree__CCPPruneController = { 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_5_tree__CCPPruneController, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_5_tree__CCPPruneController, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -39024,7 +38643,7 @@ static PyTypeObject __pyx_type_5_tree__CCPPruneController = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_5_tree__CCPPruneController, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_5_tree__CCPPruneController, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -39044,33 +38663,33 @@ static PyTypeObject __pyx_type_5_tree__CCPPruneController = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_5_tree__AlphaPruner __pyx_vtable_5_tree__AlphaPruner; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__AlphaPruner __pyx_vtable_13stpredictions_6models_3OK3_5_tree__AlphaPruner; -static PyObject *__pyx_tp_new_5_tree__AlphaPruner(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_5_tree__AlphaPruner *p; - PyObject *o = __pyx_tp_new_5_tree__CCPPruneController(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree__AlphaPruner(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_5_tree__CCPPruneController(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_5_tree__AlphaPruner *)o); - p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_5_tree__CCPPruneController*)__pyx_vtabptr_5_tree__AlphaPruner; - if (unlikely(__pyx_pw_5_tree_12_AlphaPruner_1__cinit__(o, a, k) < 0)) goto bad; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController*)__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree__AlphaPruner; + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_1__cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } -static PyMethodDef __pyx_methods_5_tree__AlphaPruner[] = { - {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_12_AlphaPruner_3__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_12_AlphaPruner_5__setstate_cython__, METH_O, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_5_tree__AlphaPruner[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_3__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_12_AlphaPruner_5__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_5_tree__AlphaPruner = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_5_tree__AlphaPruner = { PyVarObject_HEAD_INIT(0, 0) - "_tree._AlphaPruner", /*tp_name*/ - sizeof(struct __pyx_obj_5_tree__AlphaPruner), /*tp_basicsize*/ + "stpredictions.models.OK3._tree._AlphaPruner", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__AlphaPruner), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_5_tree__CCPPruneController, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree__CCPPruneController, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -39103,7 +38722,7 @@ static PyTypeObject __pyx_type_5_tree__AlphaPruner = { 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ - __pyx_methods_5_tree__AlphaPruner, /*tp_methods*/ + __pyx_methods_13stpredictions_6models_3OK3_5_tree__AlphaPruner, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ @@ -39113,7 +38732,7 @@ static PyTypeObject __pyx_type_5_tree__AlphaPruner = { 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ - __pyx_tp_new_5_tree__AlphaPruner, /*tp_new*/ + __pyx_tp_new_13stpredictions_6models_3OK3_5_tree__AlphaPruner, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ @@ -39133,27 +38752,27 @@ static PyTypeObject __pyx_type_5_tree__AlphaPruner = { 0, /*tp_print*/ #endif }; -static struct __pyx_vtabstruct_5_tree__PathFinder __pyx_vtable_5_tree__PathFinder; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__PathFinder __pyx_vtable_13stpredictions_6models_3OK3_5_tree__PathFinder; -static PyObject *__pyx_tp_new_5_tree__PathFinder(PyTypeObject *t, PyObject *a, PyObject *k) { - struct __pyx_obj_5_tree__PathFinder *p; - PyObject *o = __pyx_tp_new_5_tree__CCPPruneController(t, a, k); +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_5_tree__PathFinder(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *p; + PyObject *o = __pyx_tp_new_13stpredictions_6models_3OK3_5_tree__CCPPruneController(t, a, k); if (unlikely(!o)) return 0; - p = ((struct __pyx_obj_5_tree__PathFinder *)o); - p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_5_tree__CCPPruneController*)__pyx_vtabptr_5_tree__PathFinder; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *)o); + p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree__CCPPruneController*)__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree__PathFinder; p->ccp_alphas.data = NULL; p->ccp_alphas.memview = NULL; p->impurities.data = NULL; p->impurities.memview = NULL; - if (unlikely(__pyx_pw_5_tree_11_PathFinder_1__cinit__(o, a, k) < 0)) goto bad; + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_5_tree_11_PathFinder_1__cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } -static void __pyx_tp_dealloc_5_tree__PathFinder(PyObject *o) { - struct __pyx_obj_5_tree__PathFinder *p = (struct __pyx_obj_5_tree__PathFinder *)o; +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree__PathFinder(PyObject *o) { + struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *p = (struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder *)o; #if CYTHON_USE_TP_FINALIZE if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { if (PyObject_CallFinalizerFromDealloc(o)) return; @@ -39161,21 +38780,21 @@ static void __pyx_tp_dealloc_5_tree__PathFinder(PyObject *o) { #endif __PYX_XDEC_MEMVIEW(&p->ccp_alphas, 1); __PYX_XDEC_MEMVIEW(&p->impurities, 1); - __pyx_tp_dealloc_5_tree__CCPPruneController(o); + __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree__CCPPruneController(o); } -static PyMethodDef __pyx_methods_5_tree__PathFinder[] = { - {"__reduce_cython__", (PyCFunction)__pyx_pw_5_tree_11_PathFinder_3__reduce_cython__, METH_NOARGS, 0}, - {"__setstate_cython__", (PyCFunction)__pyx_pw_5_tree_11_PathFinder_5__setstate_cython__, METH_O, 0}, +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_5_tree__PathFinder[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_11_PathFinder_3__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_5_tree_11_PathFinder_5__setstate_cython__, METH_O, 0}, {0, 0, 0, 0} }; -static PyTypeObject __pyx_type_5_tree__PathFinder = { +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_5_tree__PathFinder = { PyVarObject_HEAD_INIT(0, 0) - "_tree._PathFinder", /*tp_name*/ - sizeof(struct __pyx_obj_5_tree__PathFinder), /*tp_basicsize*/ + "stpredictions.models.OK3._tree._PathFinder", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree__PathFinder), /*tp_basicsize*/ 0, /*tp_itemsize*/ - __pyx_tp_dealloc_5_tree__PathFinder, /*tp_dealloc*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_5_tree__PathFinder, /*tp_dealloc*/ #if PY_VERSION_HEX < 0x030800b4 0, /*tp_print*/ #endif @@ -39208,7 +38827,7 @@ static PyTypeObject __pyx_type_5_tree__PathFinder = { 0, /*tp_weaklistoffset*/ 0, 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__pyx_convert__to_py_struct____pyx_t_5_tree_Node(struct __pyx_t_5_tree_Node s) { +static PyObject* __pyx_convert__to_py_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node s) { PyObject* res; PyObject* member; res = __Pyx_PyDict_NewPresized(7); if (unlikely(!res)) return NULL; @@ -45649,14 +45241,14 @@ static PyObject* __pyx_convert__to_py_struct____pyx_t_5_tree_Node(struct __pyx_t return NULL; } /* MemviewDtypeToObject */ - static CYTHON_INLINE PyObject *__pyx_memview_get_nn_struct____pyx_t_5_tree_Node(const char *itemp) { - return (PyObject *) __pyx_convert__to_py_struct____pyx_t_5_tree_Node(*(struct __pyx_t_5_tree_Node *) itemp); + static CYTHON_INLINE PyObject *__pyx_memview_get_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(const char *itemp) { + return (PyObject *) __pyx_convert__to_py_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(*(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *) itemp); } -static CYTHON_INLINE int __pyx_memview_set_nn_struct____pyx_t_5_tree_Node(const char *itemp, PyObject *obj) { - struct __pyx_t_5_tree_Node value = __pyx_convert__from_py_struct____pyx_t_5_tree_Node(obj); +static CYTHON_INLINE int __pyx_memview_set_nn_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(const char *itemp, PyObject *obj) { + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node value = __pyx_convert__from_py_struct____pyx_t_13stpredictions_6models_3OK3_5_tree_Node(obj); if (PyErr_Occurred()) return 0; - *(struct __pyx_t_5_tree_Node *) itemp = value; + *(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *) itemp = value; return 1; } @@ -47512,7 +47104,7 @@ static int __Pyx_ValidateAndInit_memviewslice( } /* ObjectToMemviewSlice */ - static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__(PyObject *obj, int writable_flag) { + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t__const__(PyObject *obj, int writable_flag) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) }; @@ -47523,7 +47115,7 @@ static int __Pyx_ValidateAndInit_memviewslice( } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG, (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT) | writable_flag, 2, - &__Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t__const__, stack, + &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t__const__, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; @@ -47535,7 +47127,7 @@ static int __Pyx_ValidateAndInit_memviewslice( } /* ObjectToMemviewSlice */ - static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_5_tree_DTYPE_t__const__(PyObject *obj, int writable_flag) { + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t__const__(PyObject *obj, int writable_flag) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; @@ -47546,7 +47138,7 @@ static int __Pyx_ValidateAndInit_memviewslice( } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS_RO | writable_flag, 2, - &__Pyx_TypeInfo_nn___pyx_t_5_tree_DTYPE_t__const__, stack, + &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t__const__, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; @@ -47558,7 +47150,7 @@ static int __Pyx_ValidateAndInit_memviewslice( } /* ObjectToMemviewSlice */ - static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_DOUBLE_t(PyObject *obj, int writable_flag) { + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t(PyObject *obj, int writable_flag) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; @@ -47569,7 +47161,7 @@ static int __Pyx_ValidateAndInit_memviewslice( } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS_RO | writable_flag, 1, - &__Pyx_TypeInfo_nn___pyx_t_5_tree_DOUBLE_t, stack, + &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; @@ -47581,7 +47173,7 @@ static int __Pyx_ValidateAndInit_memviewslice( } /* ObjectToMemviewSlice */ - static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_5_tree_SIZE_t(PyObject *obj, int writable_flag) { + static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t(PyObject *obj, int writable_flag) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; @@ -47592,7 +47184,7 @@ static int __Pyx_ValidateAndInit_memviewslice( } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS_RO | writable_flag, 1, - &__Pyx_TypeInfo_nn___pyx_t_5_tree_SIZE_t, stack, + &__Pyx_TypeInfo_nn___pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; diff --git a/stpredictions/models/OK3/_tree.pyx b/stpredictions/models/OK3/_tree.pyx index 4ac23b7b6..dc957d397 100644 --- a/stpredictions/models/OK3/_tree.pyx +++ b/stpredictions/models/OK3/_tree.pyx @@ -22,12 +22,12 @@ from scipy.sparse import issparse from scipy.sparse import csc_matrix from scipy.sparse import csr_matrix -from sklearn.tree._utils cimport Stack -from sklearn.tree._utils cimport StackRecord -from sklearn.tree._utils cimport PriorityHeap -from sklearn.tree._utils cimport PriorityHeapRecord -from sklearn.tree._utils cimport safe_realloc -from sklearn.tree._utils cimport sizet_ptr_to_ndarray +from ._utils cimport Stack +from ._utils cimport StackRecord +from ._utils cimport PriorityHeap +from ._utils cimport PriorityHeapRecord +from ._utils cimport safe_realloc +from ._utils cimport sizet_ptr_to_ndarray from _criterion import Criterion from _criterion import KernelizedMSE diff --git a/stpredictions/models/OK3/_utils.c b/stpredictions/models/OK3/_utils.c new file mode 100644 index 000000000..a4939ecb9 --- /dev/null +++ b/stpredictions/models/OK3/_utils.c @@ -0,0 +1,31010 @@ +/* Generated by Cython 0.29.23 */ + +/* BEGIN: Cython Metadata +{ + "distutils": { + "depends": [ 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please install development version of Python. +#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) + #error Cython requires Python 2.6+ or Python 3.3+. +#else +#define CYTHON_ABI "0_29_23" +#define CYTHON_HEX_VERSION 0x001D17F0 +#define CYTHON_FUTURE_DIVISION 0 +#include +#ifndef offsetof + #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) +#endif +#if !defined(WIN32) && !defined(MS_WINDOWS) + #ifndef __stdcall + #define __stdcall + #endif + #ifndef __cdecl + #define __cdecl + #endif + #ifndef __fastcall + #define __fastcall + #endif +#endif +#ifndef DL_IMPORT + #define DL_IMPORT(t) t +#endif +#ifndef DL_EXPORT + #define DL_EXPORT(t) t +#endif +#define __PYX_COMMA , +#ifndef HAVE_LONG_LONG + #if PY_VERSION_HEX >= 0x02070000 + #define HAVE_LONG_LONG + #endif +#endif +#ifndef PY_LONG_LONG + #define PY_LONG_LONG LONG_LONG +#endif +#ifndef Py_HUGE_VAL + #define Py_HUGE_VAL HUGE_VAL +#endif +#ifdef PYPY_VERSION + #define CYTHON_COMPILING_IN_PYPY 1 + #define CYTHON_COMPILING_IN_PYSTON 0 + #define CYTHON_COMPILING_IN_CPYTHON 0 + #undef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 0 + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #if PY_VERSION_HEX < 0x03050000 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #elif !defined(CYTHON_USE_ASYNC_SLOTS) + #define CYTHON_USE_ASYNC_SLOTS 1 + #endif + #undef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 0 + #undef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 0 + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #undef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 1 + #undef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 0 + #undef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 0 + #undef CYTHON_FAST_THREAD_STATE + #define 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#define CYTHON_FALLTHROUGH [[gnu::fallthrough]] + #endif + #endif + #ifndef CYTHON_FALLTHROUGH + #if __has_attribute(fallthrough) + #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) + #else + #define CYTHON_FALLTHROUGH + #endif + #endif + #if defined(__clang__ ) && defined(__apple_build_version__) + #if __apple_build_version__ < 7000000 + #undef CYTHON_FALLTHROUGH + #define CYTHON_FALLTHROUGH + #endif + #endif +#endif + +#ifndef CYTHON_INLINE + #if defined(__clang__) + #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) + #elif defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_INLINE inline + #else + #define CYTHON_INLINE + #endif +#endif + +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) + #define Py_OptimizeFlag 0 +#endif +#define __PYX_BUILD_PY_SSIZE_T "n" +#define CYTHON_FORMAT_SSIZE_T "z" +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) + #define __Pyx_DefaultClassType PyClass_Type +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#endif + #define __Pyx_DefaultClassType PyType_Type +#endif +#ifndef Py_TPFLAGS_CHECKTYPES + #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif +#ifndef Py_TPFLAGS_HAVE_FINALIZE + #define Py_TPFLAGS_HAVE_FINALIZE 0 +#endif +#ifndef METH_STACKLESS + #define METH_STACKLESS 0 +#endif +#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) + #ifndef METH_FASTCALL + #define METH_FASTCALL 0x80 + #endif + typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); + typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, + Py_ssize_t nargs, PyObject *kwnames); +#else + #define __Pyx_PyCFunctionFast _PyCFunctionFast + #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords +#endif +#if CYTHON_FAST_PYCCALL +#define __Pyx_PyFastCFunction_Check(func)\ + ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) +#else +#define __Pyx_PyFastCFunction_Check(func) 0 +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) + #define PyObject_Malloc(s) PyMem_Malloc(s) + #define PyObject_Free(p) PyMem_Free(p) + #define PyObject_Realloc(p) PyMem_Realloc(p) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 + #define PyMem_RawMalloc(n) PyMem_Malloc(n) + #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) + #define PyMem_RawFree(p) PyMem_Free(p) +#endif +#if CYTHON_COMPILING_IN_PYSTON + #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) +#else + #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) +#endif +#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#elif PY_VERSION_HEX >= 0x03060000 + #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() +#elif PY_VERSION_HEX >= 0x03000000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#else + #define __Pyx_PyThreadState_Current _PyThreadState_Current +#endif +#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) +#include "pythread.h" +#define Py_tss_NEEDS_INIT 0 +typedef int Py_tss_t; +static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { + *key = PyThread_create_key(); + return 0; +} +static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { + Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); + *key = Py_tss_NEEDS_INIT; + return key; +} +static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { + PyObject_Free(key); +} +static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { + return *key != Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { + PyThread_delete_key(*key); + *key = Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { + return PyThread_set_key_value(*key, value); +} +static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { + return PyThread_get_key_value(*key); +} +#endif +#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) +#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) +#else +#define __Pyx_PyDict_NewPresized(n) PyDict_New() +#endif +#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS +#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) +#else +#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) +#endif +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) + #define CYTHON_PEP393_ENABLED 1 + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ + 0 : _PyUnicode_Ready((PyObject *)(op))) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) + #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) + #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) + #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif +#else + #define CYTHON_PEP393_ENABLED 0 + #define PyUnicode_1BYTE_KIND 1 + #define PyUnicode_2BYTE_KIND 2 + #define PyUnicode_4BYTE_KIND 4 + #define __Pyx_PyUnicode_READY(op) (0) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) + #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) + #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) + #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) +#endif +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) +#else + #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ + PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) + #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) + #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) +#endif +#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) +#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) +#else + #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) +#endif +#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) + #define PyObject_ASCII(o) PyObject_Repr(o) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode + #define PyObject_Unicode PyObject_Str +#endif +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) + #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) +#else + #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) + #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif +#if CYTHON_ASSUME_SAFE_MACROS + #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) +#else + #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define PyNumber_Int PyNumber_Long +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif +#if PY_VERSION_HEX < 0x030200A4 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t PyInt_AsLong +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) +#endif +#if CYTHON_USE_ASYNC_SLOTS + #if PY_VERSION_HEX >= 0x030500B1 + #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods + #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) + #else + #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) + #endif +#else + #define __Pyx_PyType_AsAsync(obj) NULL +#endif +#ifndef __Pyx_PyAsyncMethodsStruct + typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; + } __Pyx_PyAsyncMethodsStruct; +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include +#ifdef NAN +#define __PYX_NAN() ((float) NAN) +#else +static CYTHON_INLINE float __PYX_NAN() { + float value; + memset(&value, 0xFF, sizeof(value)); + return value; +} +#endif +#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) +#define __Pyx_truncl trunc +#else +#define __Pyx_truncl truncl +#endif + +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } +#define __PYX_ERR(f_index, lineno, Ln_error) \ + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#define __PYX_HAVE__stpredictions__models__OK3___utils +#define __PYX_HAVE_API__stpredictions__models__OK3___utils +/* Early includes */ +#include +#include +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + +#include +#include +#include "pythread.h" +#include "pystate.h" +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) +#define CYTHON_WITHOUT_ASSERTIONS +#endif + +typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; + const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; + +#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) +#define __PYX_DEFAULT_STRING_ENCODING "" +#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString +#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX))) ) +static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { + return (size_t) i < (size_t) limit; +} +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (_MSC_VER) + #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); +#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) +#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); +#if PY_MAJOR_VERSION < 3 + #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#else + #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize +#endif +#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { + const Py_UNICODE *u_end = u; + while (*u_end++) ; + return (size_t)(u_end - u - 1); +} +#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) +#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode +#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); +#define __Pyx_PySequence_Tuple(obj)\ + (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +#if CYTHON_ASSUME_SAFE_MACROS +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#else +#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) +#endif +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) +#else +#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) +#endif +#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII +static int __Pyx_sys_getdefaultencoding_not_ascii; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + PyObject* ascii_chars_u = NULL; + PyObject* ascii_chars_b = NULL; + const char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + if (strcmp(default_encoding_c, "ascii") == 0) { + __Pyx_sys_getdefaultencoding_not_ascii = 0; + } else { + char ascii_chars[128]; + int c; + for (c = 0; c < 128; c++) { + ascii_chars[c] = c; + } + __Pyx_sys_getdefaultencoding_not_ascii = 1; + ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); + if (!ascii_chars_u) goto bad; + ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); + if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { + PyErr_Format( + PyExc_ValueError, + "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", + default_encoding_c); + goto bad; + } + Py_DECREF(ascii_chars_u); + Py_DECREF(ascii_chars_b); + } + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + Py_XDECREF(ascii_chars_u); + Py_XDECREF(ascii_chars_b); + return -1; +} +#endif +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) +#else +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +static char* __PYX_DEFAULT_STRING_ENCODING; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); + if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; + strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + return -1; +} +#endif +#endif + + +/* Test for GCC > 2.95 */ +#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) +#else /* !__GNUC__ or GCC < 2.95 */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ +static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } + +static PyObject *__pyx_m = NULL; +static PyObject *__pyx_d; +static PyObject *__pyx_b; +static PyObject *__pyx_cython_runtime = NULL; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static PyObject *__pyx_empty_unicode; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +/* Header.proto */ +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + + +static const char *__pyx_f[] = { + "stpredictions/models/OK3/_utils.pyx", + "stringsource", + "__init__.pxd", + "stpredictions/models/OK3/_random.pxd", + "type.pxd", + "stpredictions/models/OK3/_criterion.pxd", + "stpredictions/models/OK3/_splitter.pxd", + "stpredictions/models/OK3/_tree.pxd", + "stpredictions/models/OK3/_quad_tree.pxd", +}; +/* ForceInitThreads.proto */ +#ifndef __PYX_FORCE_INIT_THREADS + #define __PYX_FORCE_INIT_THREADS 0 +#endif + +/* NoFastGil.proto */ +#define __Pyx_PyGILState_Ensure PyGILState_Ensure +#define __Pyx_PyGILState_Release PyGILState_Release +#define __Pyx_FastGIL_Remember() +#define __Pyx_FastGIL_Forget() +#define __Pyx_FastGilFuncInit() + +/* BufferFormatStructs.proto */ +#define IS_UNSIGNED(type) (((type) -1) > 0) +struct __Pyx_StructField_; +#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) +typedef struct { + const char* name; + struct __Pyx_StructField_* fields; + size_t size; + size_t arraysize[8]; + int ndim; + char typegroup; + char is_unsigned; + int flags; +} __Pyx_TypeInfo; +typedef struct __Pyx_StructField_ { + __Pyx_TypeInfo* type; + const char* name; + size_t offset; +} __Pyx_StructField; +typedef struct { + __Pyx_StructField* field; + size_t parent_offset; +} __Pyx_BufFmt_StackElem; +typedef struct { + __Pyx_StructField root; + __Pyx_BufFmt_StackElem* head; + size_t fmt_offset; + size_t new_count, enc_count; + size_t struct_alignment; + int is_complex; + char enc_type; + char new_packmode; + char enc_packmode; + char is_valid_array; +} __Pyx_BufFmt_Context; + +/* Atomics.proto */ +#include +#ifndef CYTHON_ATOMICS + #define CYTHON_ATOMICS 1 +#endif +#define __pyx_atomic_int_type int +#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\ + (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\ + !defined(__i386__) + #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) + #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using GNU atomics" + #endif +#elif CYTHON_ATOMICS && defined(_MSC_VER) && 0 + #include + #undef __pyx_atomic_int_type + #define __pyx_atomic_int_type LONG + #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #pragma message ("Using MSVC atomics") + #endif +#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 + #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) + #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value) + #ifdef __PYX_DEBUG_ATOMICS + #warning "Using Intel atomics" + #endif +#else + #undef CYTHON_ATOMICS + #define CYTHON_ATOMICS 0 + #ifdef __PYX_DEBUG_ATOMICS + #warning "Not using atomics" + #endif +#endif +typedef volatile __pyx_atomic_int_type __pyx_atomic_int; +#if CYTHON_ATOMICS + #define __pyx_add_acquisition_count(memview)\ + __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview)\ + __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) +#else + #define __pyx_add_acquisition_count(memview)\ + __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) + #define __pyx_sub_acquisition_count(memview)\ + __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) +#endif + +/* MemviewSliceStruct.proto */ +struct __pyx_memoryview_obj; +typedef struct { + struct __pyx_memoryview_obj *memview; + char *data; + Py_ssize_t shape[8]; + Py_ssize_t strides[8]; + Py_ssize_t suboffsets[8]; +} __Pyx_memviewslice; +#define __Pyx_MemoryView_Len(m) (m.shape[0]) + + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":689 + * # in Cython to enable them only on the right systems. + * + * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + */ +typedef npy_int8 __pyx_t_5numpy_int8_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":690 + * + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t + */ +typedef npy_int16 __pyx_t_5numpy_int16_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":691 + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< + * ctypedef npy_int64 int64_t + * #ctypedef npy_int96 int96_t + */ +typedef npy_int32 __pyx_t_5numpy_int32_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":692 + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< + * #ctypedef npy_int96 int96_t + * #ctypedef npy_int128 int128_t + */ +typedef npy_int64 __pyx_t_5numpy_int64_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":696 + * #ctypedef npy_int128 int128_t + * + * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + */ +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":697 + * + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t + */ +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":698 + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< + * ctypedef npy_uint64 uint64_t + * #ctypedef npy_uint96 uint96_t + */ +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":699 + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< + * #ctypedef npy_uint96 uint96_t + * #ctypedef npy_uint128 uint128_t + */ +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":703 + * #ctypedef npy_uint128 uint128_t + * + * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< + * ctypedef npy_float64 float64_t + * #ctypedef npy_float80 float80_t + */ +typedef npy_float32 __pyx_t_5numpy_float32_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":704 + * + * ctypedef npy_float32 float32_t + * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< + * #ctypedef npy_float80 float80_t + * #ctypedef npy_float128 float128_t + */ +typedef npy_float64 __pyx_t_5numpy_float64_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":713 + * # The int types are mapped a bit surprising -- + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t + */ +typedef npy_long __pyx_t_5numpy_int_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":714 + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong longlong_t + * + */ +typedef npy_longlong __pyx_t_5numpy_long_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":715 + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_ulong uint_t + */ +typedef npy_longlong __pyx_t_5numpy_longlong_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":717 + * ctypedef npy_longlong longlong_t + * + * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t + */ +typedef npy_ulong __pyx_t_5numpy_uint_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":718 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":719 + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_intp intp_t + */ +typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":721 + * ctypedef npy_ulonglong ulonglong_t + * + * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< + * ctypedef npy_uintp uintp_t + * + */ +typedef npy_intp __pyx_t_5numpy_intp_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":722 + * + * ctypedef npy_intp intp_t + * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< + * + * ctypedef npy_double float_t + */ +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":724 + * ctypedef npy_uintp uintp_t + * + * ctypedef npy_double float_t # <<<<<<<<<<<<<< + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t + */ +typedef npy_double __pyx_t_5numpy_float_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":725 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":726 + * ctypedef npy_double float_t + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cfloat cfloat_t + */ +typedef npy_longdouble __pyx_t_5numpy_longdouble_t; + +/* "_tree.pxd":7 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t; + +/* "_tree.pxd":8 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t; + +/* "_tree.pxd":9 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t; + +/* "_tree.pxd":10 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_5_tree_INT32_t; + +/* "_tree.pxd":11 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * from _splitter cimport Splitter + */ +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t; + +/* "_quad_tree.pxd":13 + * cimport numpy as np + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t; + +/* "_quad_tree.pxd":14 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t; + +/* "_quad_tree.pxd":15 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_INT32_t; + +/* "_quad_tree.pxd":16 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * # This is effectively an ifdef statement in Cython + */ +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_UINT32_t; + +/* "_random.pxd":8 + * import numpy as np + * cimport numpy as np + * ctypedef np.npy_uint32 UINT32_t # <<<<<<<<<<<<<< + * + * cdef inline UINT32_t DEFAULT_SEED = 1 + */ +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_7_random_UINT32_t; + +/* "stpredictions/models/OK3/_utils.pxd":16 + * from ._quad_tree cimport Cell + * + * ctypedef np.npy_float32 DTYPE_t # Type of X # <<<<<<<<<<<<<< + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + */ +typedef npy_float32 __pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t; + +/* "stpredictions/models/OK3/_utils.pxd":17 + * + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight # <<<<<<<<<<<<<< + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + */ +typedef npy_float64 __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t; + +/* "stpredictions/models/OK3/_utils.pxd":18 + * ctypedef np.npy_float32 DTYPE_t # Type of X + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters # <<<<<<<<<<<<<< + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + */ +typedef npy_intp __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t; + +/* "stpredictions/models/OK3/_utils.pxd":19 + * ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer # <<<<<<<<<<<<<< + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + * + */ +typedef npy_int32 __pyx_t_13stpredictions_6models_3OK3_6_utils_INT32_t; + +/* "stpredictions/models/OK3/_utils.pxd":20 + * ctypedef np.npy_intp SIZE_t # Type for indices and counters + * ctypedef np.npy_int32 INT32_t # Signed 32 bit integer + * ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer # <<<<<<<<<<<<<< + * + * + */ +typedef npy_uint32 __pyx_t_13stpredictions_6models_3OK3_6_utils_UINT32_t; +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< float > __pyx_t_float_complex; + #else + typedef float _Complex __pyx_t_float_complex; + #endif +#else + typedef struct { float real, imag; } __pyx_t_float_complex; +#endif +static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); + +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< double > __pyx_t_double_complex; + #else + typedef double _Complex __pyx_t_double_complex; + #endif +#else + typedef struct { double real, imag; } __pyx_t_double_complex; +#endif +static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); + + +/*--- Type declarations ---*/ +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion; +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree; +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder; +struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; +struct __pyx_array_obj; +struct __pyx_MemviewEnum_obj; +struct __pyx_memoryview_obj; +struct __pyx_memoryviewslice_obj; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":728 + * ctypedef npy_longdouble longdouble_t + * + * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t + */ +typedef npy_cfloat __pyx_t_5numpy_cfloat_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":729 + * + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< + * ctypedef npy_clongdouble clongdouble_t + * + */ +typedef npy_cdouble __pyx_t_5numpy_cdouble_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":730 + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cdouble complex_t + */ +typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; + +/* "../../../Virtual_ENV/venv_stpredictions_package/lib/python3.9/site-packages/numpy/__init__.pxd":732 + * ctypedef npy_clongdouble clongdouble_t + * + * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< + * + * cdef inline object PyArray_MultiIterNew1(a): + */ +typedef npy_cdouble __pyx_t_5numpy_complex_t; +struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord; + +/* "_splitter.pxd":14 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef struct SplitRecord: # <<<<<<<<<<<<<< + * # Data to track sample split + * SIZE_t feature # Which feature to split on. + */ +struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t pos; + double threshold; + double improvement; + double impurity_left; + double impurity_right; +}; +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances; +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build; + +/* "_tree.pxd":16 + * from _splitter cimport SplitRecord + * + * cdef struct Node: # <<<<<<<<<<<<<< + * # Base storage structure for the nodes in a Tree object + * + */ +struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t left_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t right_child; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t feature; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t threshold; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t impurity; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t weighted_n_node_samples; +}; + +/* "_tree.pxd":52 + * double weighted_n_samples) nogil except -1 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * + * cdef np.ndarray _get_value_ndarray(self) + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c { + int __pyx_n; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; +}; + +/* "_tree.pxd":68 + * cdef object _decision_path_sparse_csr(self, object X) + * + * cpdef compute_feature_importances(self, normalize=*) # <<<<<<<<<<<<<< + * + * + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances { + int __pyx_n; + PyObject *normalize; +}; + +/* "_tree.pxd":92 + * cdef double min_impurity_decrease # Impurity threshold for early stopping + * + * cpdef build(self, Tree tree, object X, np.ndarray y, # <<<<<<<<<<<<<< + * np.ndarray sample_weight=*) + * cdef _check_input(self, object X, np.ndarray y, np.ndarray sample_weight) + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build { + int __pyx_n; + PyArrayObject *sample_weight; +}; +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c; +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell; + +/* "_quad_tree.pxd":21 + * # It allows us to write printf debugging lines + * # and remove them at compile time + * cdef enum: # <<<<<<<<<<<<<< + * DEBUGFLAG = 0 + * + */ +enum { + __pyx_e_13stpredictions_6models_3OK3_10_quad_tree_DEBUGFLAG = 0 +}; + +/* "_quad_tree.pxd":29 + * # have is_leaf and max_width consecutive as it permits to avoid padding by + * # the compiler and keep the size coherent for both C and numpy data structures. + * cdef struct Cell: # <<<<<<<<<<<<<< + * # Base storage structure for cells in a QuadTree object + * + */ +struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell { + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t parent; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t children[8]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t point_index; + int is_leaf; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t squared_max_width; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t depth; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cumulative_size; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t center[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t barycenter[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t min_bounds[3]; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t max_bounds[3]; +}; + +/* "_quad_tree.pxd":75 + * + * # Point insertion methods + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, # <<<<<<<<<<<<<< + * SIZE_t cell_id=*) nogil except -1 + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point { + int __pyx_n; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; +}; + +/* "_quad_tree.pxd":77 + * cdef int insert_point(self, DTYPE_t[3] point, SIZE_t point_index, + * SIZE_t cell_id=*) nogil except -1 + * cdef SIZE_t _insert_point_in_new_child(self, DTYPE_t[3] point, Cell* cell, # <<<<<<<<<<<<<< + * SIZE_t point_index, SIZE_t size=* + * ) nogil + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child { + int __pyx_n; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t size; +}; + +/* "_quad_tree.pxd":84 + * + * # Create a summary of the Tree compare to a query point + * cdef long summarize(self, DTYPE_t[3] point, DTYPE_t* results, # <<<<<<<<<<<<<< + * float squared_theta=*, SIZE_t cell_id=*, long idx=* + * ) nogil + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize { + int __pyx_n; + float squared_theta; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; + long idx; +}; + +/* "_quad_tree.pxd":99 + * # Private array manipulation to manage the ``cells`` array + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 # <<<<<<<<<<<<<< + * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 + * cdef np.ndarray _get_cell_ndarray(self) + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c { + int __pyx_n; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t capacity; +}; + +/* "_quad_tree.pxd":100 + * cdef int _resize(self, SIZE_t capacity) nogil except -1 + * cdef int _resize_c(self, SIZE_t capacity=*) nogil except -1 + * cdef int _get_cell(self, DTYPE_t[3] point, SIZE_t cell_id=*) nogil except -1 # <<<<<<<<<<<<<< + * cdef np.ndarray _get_cell_ndarray(self) + */ +struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell { + int __pyx_n; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_id; +}; + +/* "_random.pxd":12 + * cdef inline UINT32_t DEFAULT_SEED = 1 + * + * cdef enum: # <<<<<<<<<<<<<< + * # Max value for our rand_r replacement (near the bottom). + * # We don't use RAND_MAX because it's different across platforms and + */ +enum { + __pyx_e_13stpredictions_6models_3OK3_7_random_RAND_R_MAX = 0x7FFFFFFF +}; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord; +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord; + +/* "stpredictions/models/OK3/_utils.pxd":23 + * + * + * cdef enum: # <<<<<<<<<<<<<< + * # Max value for our rand_r replacement (near the bottom). + * # We don't use RAND_MAX because it's different across platforms and + */ +enum { + __pyx_e_13stpredictions_6models_3OK3_6_utils_RAND_R_MAX = 0x7FFFFFFF +}; + +/* "stpredictions/models/OK3/_utils.pxd":70 + * + * # A record on the stack for depth-first tree growing + * cdef struct StackRecord: # <<<<<<<<<<<<<< + * SIZE_t start + * SIZE_t end + */ +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t depth; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t parent; + int is_left; + double impurity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t n_constant_features; +}; + +/* "stpredictions/models/OK3/_utils.pxd":96 + * + * # A record on the frontier for best-first tree growing + * cdef struct PriorityHeapRecord: # <<<<<<<<<<<<<< + * SIZE_t node_id + * SIZE_t start + */ +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t node_id; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t pos; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t depth; + int is_leaf; + double impurity; + double impurity_left; + double impurity_right; + double improvement; +}; + +/* "stpredictions/models/OK3/_utils.pxd":127 + * + * # A record stored in the WeightedPQueue + * cdef struct WeightedPQueueRecord: # <<<<<<<<<<<<<< + * DOUBLE_t data + * DOUBLE_t weight + */ +struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord { + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t data; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t weight; +}; + +/* "_criterion.pxd":12 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. + */ +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtab; + __Pyx_memviewslice y; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *sample_weight; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t pos; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t end; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_node_samples; + double weighted_n_samples; + double weighted_n_node_samples; + double weighted_n_left; + double weighted_n_right; +}; + + +/* "_criterion.pxd":50 + * + * + * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract kernelized output regression criterion.""" + * + */ +struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; + double sum_diag_Gramm; + double sum_total_Gramm; + double sum_diag_Gramm_left; + double sum_diag_Gramm_right; + double sum_total_Gramm_left; + double sum_total_Gramm_right; +}; + + +/* "_splitter.pxd":25 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ +struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtab; + struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *criterion; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + PyObject *random_state; + __pyx_t_13stpredictions_6models_3OK3_5_tree_UINT32_t rand_r_state; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_samples; + double weighted_n_samples; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *constant_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DTYPE_t *feature_values; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t start; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t end; + __Pyx_memviewslice y; + __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *sample_weight; +}; + + +/* "_tree.pxd":28 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. + */ +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t n_features; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t node_count; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t capacity; + PyArrayObject *K_y; + PyArrayObject *y; + struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *nodes; + double *value; +}; + + +/* "_tree.pxd":75 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ +struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtab; + struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *splitter; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_split; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t min_samples_leaf; + double min_weight_leaf; + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t max_depth; + double min_impurity_split; + double min_impurity_decrease; +}; + + +/* "_quad_tree.pxd":55 + * + * + * cdef class _QuadTree: # <<<<<<<<<<<<<< + * # The QuadTree object is a quad tree structure constructed by inserting + * # recursively points in the tree and splitting cells in 4 so that each + */ +struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_vtab; + int n_dimensions; + int verbose; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t n_cells_per_cell; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t max_depth; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t cell_count; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t n_points; + struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *cells; +}; + + +/* "stpredictions/models/OK3/_utils.pxd":79 + * SIZE_t n_constant_features + * + * cdef class Stack: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t top + */ +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t top; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *stack_; +}; + + +/* "stpredictions/models/OK3/_utils.pxd":108 + * double improvement + * + * cdef class PriorityHeap: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t heap_ptr + */ +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t heap_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *heap_; +}; + + +/* "stpredictions/models/OK3/_utils.pxd":131 + * DOUBLE_t weight + * + * cdef class WeightedPQueue: # <<<<<<<<<<<<<< + * cdef SIZE_t capacity + * cdef SIZE_t array_ptr + */ +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t capacity; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t array_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *array_; +}; + + +/* "stpredictions/models/OK3/_utils.pxd":151 + * # ============================================================================= + * + * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< + * cdef SIZE_t initial_capacity + * cdef WeightedPQueue samples + */ +struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator { + PyObject_HEAD + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_vtab; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t initial_capacity; + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *samples; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t total_weight; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t k; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t sum_w_0_k; +}; + + +/* "View.MemoryView":105 + * + * @cname("__pyx_array") + * cdef class array: # <<<<<<<<<<<<<< + * + * cdef: + */ +struct __pyx_array_obj { + PyObject_HEAD + struct __pyx_vtabstruct_array *__pyx_vtab; + char *data; + Py_ssize_t len; + char *format; + int ndim; + Py_ssize_t *_shape; + Py_ssize_t *_strides; + Py_ssize_t itemsize; + PyObject *mode; + PyObject *_format; + void (*callback_free_data)(void *); + int free_data; + int dtype_is_object; +}; + + +/* "View.MemoryView":279 + * + * @cname('__pyx_MemviewEnum') + * cdef class Enum(object): # <<<<<<<<<<<<<< + * cdef object name + * def __init__(self, name): + */ +struct __pyx_MemviewEnum_obj { + PyObject_HEAD + PyObject *name; +}; + + +/* "View.MemoryView":330 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ +struct __pyx_memoryview_obj { + PyObject_HEAD + struct __pyx_vtabstruct_memoryview *__pyx_vtab; + PyObject *obj; + PyObject *_size; + PyObject *_array_interface; + PyThread_type_lock lock; + __pyx_atomic_int acquisition_count[2]; + __pyx_atomic_int *acquisition_count_aligned_p; + Py_buffer view; + int flags; + int dtype_is_object; + __Pyx_TypeInfo *typeinfo; +}; + + +/* "View.MemoryView":965 + * + * @cname('__pyx_memoryviewslice') + * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< + * "Internal class for passing memoryview slices to Python" + * + */ +struct __pyx_memoryviewslice_obj { + struct __pyx_memoryview_obj __pyx_base; + __Pyx_memviewslice from_slice; + PyObject *from_object; + PyObject *(*to_object_func)(char *); + int (*to_dtype_func)(char *, PyObject *); +}; + + + +/* "_criterion.pxd":12 + * from ._tree cimport UINT32_t # Unsigned 32 bit integer + * + * cdef class Criterion: # <<<<<<<<<<<<<< + * # The criterion computes the impurity of a node and the reduction of + * # impurity of a split on that node. + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion { + int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + int (*reverse_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + int (*update)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); + void (*children_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *, double *); + void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double *); + double (*impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *, double); + double (*proxy_impurity_improvement)(struct __pyx_obj_13stpredictions_6models_3OK3_10_criterion_Criterion *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_Criterion; + + +/* "_criterion.pxd":50 + * + * + * cdef class KernelizedRegressionCriterion(Criterion): # <<<<<<<<<<<<<< + * """Abstract kernelized output regression criterion.""" + * + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion { + struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_Criterion __pyx_base; +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion *__pyx_vtabptr_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion; + + +/* "_splitter.pxd":25 + * double impurity_right # Impurity of the right split. + * + * cdef class Splitter: # <<<<<<<<<<<<<< + * # The splitter searches in the input space for a feature and a threshold + * # to split the samples samples[start:end]. + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter { + int (*init)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, PyObject *, __Pyx_memviewslice, __pyx_t_13stpredictions_6models_3OK3_5_tree_DOUBLE_t *); + int (*node_reset)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double *); + int (*node_split)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double, struct __pyx_t_13stpredictions_6models_3OK3_9_splitter_SplitRecord *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t *); + void (*node_value)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *, double *); + double (*node_impurity)(struct __pyx_obj_13stpredictions_6models_3OK3_9_splitter_Splitter *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_9_splitter_Splitter *__pyx_vtabptr_13stpredictions_6models_3OK3_9_splitter_Splitter; + + +/* "_tree.pxd":28 + * + * + * cdef class Tree: # <<<<<<<<<<<<<< + * # The Tree object is a binary tree structure constructed by the + * # TreeBuilder. + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree { + __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int, int, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double, double, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, double); + int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree__resize_c *__pyx_optional_args); + PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); + PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *); + PyArrayObject *(*decode_tree)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyArrayObject *, PyArrayObject *, PyObject *, PyObject *, __pyx_t_13stpredictions_6models_3OK3_5_tree_SIZE_t, int __pyx_skip_dispatch); + PyArrayObject *(*predict)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*apply)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyArrayObject *(*_apply_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyArrayObject *(*_apply_sparse_csr)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*decision_path)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, int __pyx_skip_dispatch); + PyObject *(*_decision_path_dense)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*_decision_path_sparse_csr)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *); + PyObject *(*compute_feature_importances)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_4Tree_compute_feature_importances *__pyx_optional_args); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_Tree *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_Tree; + + +/* "_tree.pxd":75 + * # ============================================================================= + * + * cdef class TreeBuilder: # <<<<<<<<<<<<<< + * # The TreeBuilder recursively builds a Tree object from training samples, + * # using a Splitter object for splitting internal nodes and assigning + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder { + PyObject *(*build)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_Tree *, PyObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_13stpredictions_6models_3OK3_5_tree_11TreeBuilder_build *__pyx_optional_args); + PyObject *(*_check_input)(struct __pyx_obj_13stpredictions_6models_3OK3_5_tree_TreeBuilder *, PyObject *, PyArrayObject *, PyArrayObject *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_5_tree_TreeBuilder *__pyx_vtabptr_13stpredictions_6models_3OK3_5_tree_TreeBuilder; + + +/* "_quad_tree.pxd":55 + * + * + * cdef class _QuadTree: # <<<<<<<<<<<<<< + * # The QuadTree object is a quad tree structure constructed by inserting + * # recursively points in the tree and splitting cells in 4 so that each + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree { + int (*insert_point)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_insert_point *__pyx_optional_args); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t (*_insert_point_in_new_child)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__insert_point_in_new_child *__pyx_optional_args); + __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t (*_select_child)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *); + int (*_is_duplicate)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *); + long (*summarize)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree_summarize *__pyx_optional_args); + void (*_init_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t); + void (*_init_root)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *); + int (*_check_point_in_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *); + int (*_resize)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_SIZE_t); + int (*_resize_c)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__resize_c *__pyx_optional_args); + int (*_get_cell)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *, __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_DTYPE_t *, struct __pyx_opt_args_13stpredictions_6models_3OK3_10_quad_tree_9_QuadTree__get_cell *__pyx_optional_args); + PyArrayObject *(*_get_cell_ndarray)(struct __pyx_obj_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_10_quad_tree__QuadTree *__pyx_vtabptr_13stpredictions_6models_3OK3_10_quad_tree__QuadTree; + + +/* "stpredictions/models/OK3/_utils.pyx":85 + * # ============================================================================= + * + * cdef class Stack: # <<<<<<<<<<<<<< + * """A LIFO data structure. + * + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, int, double, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_Stack; + + +/* "stpredictions/models/OK3/_utils.pyx":164 + * # ============================================================================= + * + * cdef class PriorityHeap: # <<<<<<<<<<<<<< + * """A priority queue implemented as a binary heap. + * + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *); + void (*heapify_up)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + void (*heapify_down)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t, int, double, double, double, double); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_PriorityHeap; + + +/* "stpredictions/models/OK3/_utils.pyx":291 + * # ============================================================================= + * + * cdef class WeightedPQueue: # <<<<<<<<<<<<<< + * """A priority queue class, always sorted in increasing order. + * + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue { + int (*is_empty)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*size)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + int (*peek)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_weight_from_index)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_value_from_index)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; + + +/* "stpredictions/models/OK3/_utils.pyx":447 + * # ============================================================================= + * + * cdef class WeightedMedianCalculator: # <<<<<<<<<<<<<< + * """A class to handle calculation of the weighted median from streams of + * data. To do so, it maintains a parameter ``k`` such that the sum of the + */ + +struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t (*size)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); + int (*push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*reset)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); + int (*update_median_parameters_post_push)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + int (*pop)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *); + int (*update_median_parameters_post_remove)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t); + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t (*get_median)(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *); +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; + + +/* "View.MemoryView":105 + * + * @cname("__pyx_array") + * cdef class array: # <<<<<<<<<<<<<< + * + * cdef: + */ + +struct __pyx_vtabstruct_array { + PyObject *(*get_memview)(struct __pyx_array_obj *); +}; +static struct __pyx_vtabstruct_array *__pyx_vtabptr_array; + + +/* "View.MemoryView":330 + * + * @cname('__pyx_memoryview') + * cdef class memoryview(object): # <<<<<<<<<<<<<< + * + * cdef object obj + */ + +struct __pyx_vtabstruct_memoryview { + char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); + PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *); + PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); + PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *); + PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *); +}; +static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview; + + +/* "View.MemoryView":965 + * + * @cname('__pyx_memoryviewslice') + * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< + * "Internal class for passing memoryview slices to Python" + * + */ + +struct __pyx_vtabstruct__memoryviewslice { + struct __pyx_vtabstruct_memoryview __pyx_base; 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r = NULL; __Pyx_DECREF(tmp);}} while(0) + +/* PyObjectGetAttrStr.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n) +#endif + +/* GetBuiltinName.proto */ +static PyObject *__Pyx_GetBuiltinName(PyObject *name); + +/* PyCFunctionFastCall.proto */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); +#else +#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) +#endif + +/* PyFunctionFastCall.proto */ +#if CYTHON_FAST_PYCALL +#define __Pyx_PyFunction_FastCall(func, args, nargs)\ + __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); +#else +#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) +#endif +#define __Pyx_BUILD_ASSERT_EXPR(cond)\ + (sizeof(char [1 - 2*!(cond)]) - 1) +#ifndef Py_MEMBER_SIZE +#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) +#endif + static size_t __pyx_pyframe_localsplus_offset = 0; + #include "frameobject.h" + #define __Pxy_PyFrame_Initialize_Offsets()\ + ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ + (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) + #define __Pyx_PyFrame_GetLocalsplus(frame)\ + (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) +#endif + +/* PyObjectCall.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); +#else +#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) +#endif + +/* PyObjectCallMethO.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); +#endif + +/* PyObjectCallOneArg.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); + +/* PyThreadStateGet.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate; +#define __Pyx_PyThreadState_assign __pyx_tstate = __Pyx_PyThreadState_Current; +#define __Pyx_PyErr_Occurred() __pyx_tstate->curexc_type +#else +#define __Pyx_PyThreadState_declare +#define __Pyx_PyThreadState_assign +#define __Pyx_PyErr_Occurred() PyErr_Occurred() +#endif + +/* PyErrFetchRestore.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL) +#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) +#else +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#endif +#else +#define __Pyx_PyErr_Clear() PyErr_Clear() +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) +#endif + +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + +/* PyObjectCallNoArg.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); +#else +#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) +#endif + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + +/* RaiseDoubleKeywords.proto */ +static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); + +/* ParseKeywords.proto */ +static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ + PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ + const char* function_name); + +/* RaiseArgTupleInvalid.proto */ +static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, + Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found); + +/* GetTopmostException.proto */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); +#endif + +/* SaveResetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +#else +#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) +#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) +#endif + +/* PyErrExceptionMatches.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) +static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); +#else +#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) +#endif + +/* GetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* WriteUnraisableException.proto */ +static void __Pyx_WriteUnraisable(const char *name, int clineno, + int lineno, const char *filename, + int full_traceback, int nogil); + +/* ArgTypeTest.proto */ +#define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\ + ((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\ + __Pyx__ArgTypeTest(obj, type, name, exact)) +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact); + +/* PyObjectCall2Args.proto */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); + +/* IncludeStringH.proto */ +#include + +/* BytesEquals.proto */ +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); + +/* UnicodeEquals.proto */ +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals); + +/* StrEquals.proto */ +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals +#else +#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals +#endif + +/* UnaryNegOverflows.proto */ +#define UNARY_NEG_WOULD_OVERFLOW(x)\ + (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) + +static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/ +/* GetAttr.proto */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); + +/* GetItemInt.proto */ +#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ + __Pyx_GetItemInt_Generic(o, to_py_func(i)))) +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck); + +/* ObjectGetItem.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key); +#else +#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) +#endif + +/* decode_c_string_utf16.proto */ +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 0; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = -1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} + +/* decode_c_string.proto */ +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); + +/* GetAttr3.proto */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *); + +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + +/* GetModuleGlobalName.proto */ +#if CYTHON_USE_DICT_VERSIONS +#define __Pyx_GetModuleGlobalName(var, name) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + (var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\ + (likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\ + __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +#define __Pyx_GetModuleGlobalNameUncached(var, name) {\ + PY_UINT64_T __pyx_dict_version;\ + PyObject *__pyx_dict_cached_value;\ + (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value); +#else +#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) +#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); +#endif + +/* RaiseTooManyValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); + +/* RaiseNeedMoreValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); + +/* RaiseNoneIterError.proto */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); + +/* SwapException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* Import.proto */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + +/* FastTypeChecks.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); +#else +#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) +#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) +#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) +#endif +#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) + +static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ +/* ListCompAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len)) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) +#endif + +/* PyIntBinop.proto */ +#if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); +#else +#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ + (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) +#endif + +/* ListExtend.proto */ +static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject* none = _PyList_Extend((PyListObject*)L, v); + if (unlikely(!none)) + return -1; + Py_DECREF(none); + return 0; +#else + return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v); +#endif +} + +/* ListAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_PyList_Append(L,x) PyList_Append(L,x) +#endif + +/* None.proto */ +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); + +/* ImportFrom.proto */ +static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); + +/* HasAttr.proto */ +static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *); + +/* PyObject_GenericGetAttrNoDict.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr +#endif + +/* PyObject_GenericGetAttr.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr +#endif + +/* SetVTable.proto */ +static int __Pyx_SetVtable(PyObject *dict, void *vtable); + +/* PyObjectGetAttrStrNoError.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name); + +/* SetupReduce.proto */ +static int __Pyx_setup_reduce(PyObject* type_obj); + +/* TypeImport.proto */ +#ifndef __PYX_HAVE_RT_ImportType_proto +#define __PYX_HAVE_RT_ImportType_proto +enum __Pyx_ImportType_CheckSize { + __Pyx_ImportType_CheckSize_Error = 0, + __Pyx_ImportType_CheckSize_Warn = 1, + __Pyx_ImportType_CheckSize_Ignore = 2 +}; +static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); +#endif + +/* GetVTable.proto */ +static void* __Pyx_GetVtable(PyObject *dict); + +/* CLineInTraceback.proto */ +#ifdef CYTHON_CLINE_IN_TRACEBACK +#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) +#else +static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); +#endif + +/* CodeObjectCache.proto */ +typedef struct { + PyCodeObject* code_object; + int code_line; +} __Pyx_CodeObjectCacheEntry; +struct __Pyx_CodeObjectCache { + int count; + int max_count; + __Pyx_CodeObjectCacheEntry* entries; +}; +static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); +static PyCodeObject *__pyx_find_code_object(int code_line); +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); + +/* AddTraceback.proto */ +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename); + +/* GCCDiagnostics.proto */ +#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) +#define __Pyx_HAS_GCC_DIAGNOSTIC +#endif + +/* None.proto */ +static CYTHON_INLINE int __Pyx_ErrOccurredWithGIL(void); /* proto */ + +/* RealImag.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #define __Pyx_CREAL(z) ((z).real()) + #define __Pyx_CIMAG(z) ((z).imag()) + #else + #define __Pyx_CREAL(z) (__real__(z)) + #define __Pyx_CIMAG(z) (__imag__(z)) + #endif +#else + #define __Pyx_CREAL(z) ((z).real) + #define __Pyx_CIMAG(z) ((z).imag) +#endif +#if defined(__cplusplus) && CYTHON_CCOMPLEX\ + && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) + #define __Pyx_SET_CREAL(z,x) ((z).real(x)) + #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) +#else + #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) + #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_float(a, b) ((a)==(b)) + #define __Pyx_c_sum_float(a, b) ((a)+(b)) + #define __Pyx_c_diff_float(a, b) ((a)-(b)) + #define __Pyx_c_prod_float(a, b) ((a)*(b)) + #define __Pyx_c_quot_float(a, b) ((a)/(b)) + #define __Pyx_c_neg_float(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_float(z) ((z)==(float)0) + #define __Pyx_c_conj_float(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_float(z) (::std::abs(z)) + #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_float(z) ((z)==0) + #define __Pyx_c_conj_float(z) (conjf(z)) + #if 1 + #define __Pyx_c_abs_float(z) (cabsf(z)) + #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); + #endif +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_double(a, b) ((a)==(b)) + #define __Pyx_c_sum_double(a, b) ((a)+(b)) + #define __Pyx_c_diff_double(a, b) ((a)-(b)) + #define __Pyx_c_prod_double(a, b) ((a)*(b)) + #define __Pyx_c_quot_double(a, b) ((a)/(b)) + #define __Pyx_c_neg_double(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_double(z) ((z)==(double)0) + #define __Pyx_c_conj_double(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (::std::abs(z)) + #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_double(z) ((z)==0) + #define __Pyx_c_conj_double(z) (conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (cabs(z)) + #define __Pyx_c_pow_double(a, b) (cpow(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); + #endif +#endif + +#if PY_MAJOR_VERSION < 3 + static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); + static void __Pyx_ReleaseBuffer(Py_buffer *view); +#else + #define __Pyx_GetBuffer PyObject_GetBuffer + #define __Pyx_ReleaseBuffer PyBuffer_Release +#endif + + +/* BufferStructDeclare.proto */ +typedef struct { + Py_ssize_t shape, strides, suboffsets; +} __Pyx_Buf_DimInfo; +typedef struct { + size_t refcount; + Py_buffer pybuffer; +} __Pyx_Buffer; +typedef struct { + __Pyx_Buffer *rcbuffer; + char *data; + __Pyx_Buf_DimInfo diminfo[8]; +} __Pyx_LocalBuf_ND; + +/* MemviewSliceIsContig.proto */ +static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); + +/* OverlappingSlices.proto */ +static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize); + +/* Capsule.proto */ +static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); + +/* CIntFromPy.proto */ +static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); + +/* MemviewSliceCopyTemplate.proto */ +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object); + +/* MemviewSliceInit.proto */ +#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d +#define __Pyx_MEMVIEW_DIRECT 1 +#define __Pyx_MEMVIEW_PTR 2 +#define __Pyx_MEMVIEW_FULL 4 +#define __Pyx_MEMVIEW_CONTIG 8 +#define __Pyx_MEMVIEW_STRIDED 16 +#define __Pyx_MEMVIEW_FOLLOW 32 +#define __Pyx_IS_C_CONTIG 1 +#define __Pyx_IS_F_CONTIG 2 +static int __Pyx_init_memviewslice( + struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference); +static CYTHON_INLINE int __pyx_add_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( + __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); +#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p) +#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview)) +#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__) +#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__) +static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); + +/* CIntFromPy.proto */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); + +/* CheckBinaryVersion.proto */ +static int __Pyx_check_binary_version(void); + +/* FunctionExport.proto */ +static int __Pyx_ExportFunction(const char *name, void (*f)(void), const char *sig); + +/* VoidPtrImport.proto */ +static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig); + +/* InitStrings.proto */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); + +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_5Stack_is_empty(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_5Stack_push(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_end, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_depth, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_parent, int __pyx_v_is_left, double __pyx_v_impurity, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_n_constant_features); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_5Stack_pop(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_v_self, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *__pyx_v_res); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_is_empty(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_v_self); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_heapify_up(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_v_self, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *__pyx_v_heap, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_pos); /* proto*/ +static void __pyx_f_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_heapify_down(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_v_self, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *__pyx_v_heap, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_pos, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_heap_length); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_push(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_node_id, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_start, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_end, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_pos, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_depth, int __pyx_v_is_leaf, double __pyx_v_improvement, double __pyx_v_impurity, double __pyx_v_impurity_left, double __pyx_v_impurity_right); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_pop(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_v_self, struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *__pyx_v_res); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_reset(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_is_empty(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self); /* proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_f_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_size(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_push(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_weight); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_remove(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_weight); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_pop(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_v_weight); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_peek(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_v_weight); /* proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_f_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_get_weight_from_index(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_index); /* proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_f_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_get_value_from_index(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_index); /* proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_size(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_reset(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_push(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_weight); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_update_median_parameters_post_push(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_weight, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_original_median); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_remove(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_weight); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_pop(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_v_weight); /* proto*/ +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_update_median_parameters_post_remove(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_weight, double __pyx_v_original_median); /* proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_get_median(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self); /* proto*/ +static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ +static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ +static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ +static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ +static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ +static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ + +/* Module declarations from 'cpython.buffer' */ + +/* Module declarations from 'libc.string' */ + +/* Module declarations from 'libc.stdio' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.type' */ +static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; + +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + +/* Module declarations from 'cpython.mem' */ + +/* Module declarations from 'numpy' */ + +/* Module declarations from 'numpy' */ +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; +static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; +static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; +static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; +static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; +static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ + +/* Module declarations from 'stpredictions.models.OK3._criterion' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_Criterion = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_criterion_KernelizedRegressionCriterion = 0; + +/* Module declarations from 'stpredictions.models.OK3._splitter' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_9_splitter_Splitter = 0; + +/* Module declarations from 'stpredictions.models.OK3._tree' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree_Tree = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_5_tree_TreeBuilder = 0; + +/* Module declarations from 'stpredictions.models.OK3._quad_tree' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_10_quad_tree__QuadTree = 0; +static float *__pyx_vp_13stpredictions_6models_3OK3_10_quad_tree_EPSILON = 0; +#define __pyx_v_13stpredictions_6models_3OK3_10_quad_tree_EPSILON (*__pyx_vp_13stpredictions_6models_3OK3_10_quad_tree_EPSILON) + +/* Module declarations from 'libc.stdlib' */ + +/* Module declarations from 'libc.math' */ + +/* Module declarations from 'stpredictions.models.OK3._random' */ +static __pyx_t_13stpredictions_6models_3OK3_7_random_UINT32_t *__pyx_vp_13stpredictions_6models_3OK3_7_random_DEFAULT_SEED = 0; +#define __pyx_v_13stpredictions_6models_3OK3_7_random_DEFAULT_SEED (*__pyx_vp_13stpredictions_6models_3OK3_7_random_DEFAULT_SEED) +static CYTHON_INLINE __pyx_t_13stpredictions_6models_3OK3_7_random_UINT32_t __pyx_f_13stpredictions_6models_3OK3_7_random_our_rand_r(__pyx_t_13stpredictions_6models_3OK3_7_random_UINT32_t *); /*proto*/ + +/* Module declarations from 'stpredictions.models.OK3._utils' */ +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_Stack = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_PriorityHeap = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_WeightedPQueue = 0; +static PyTypeObject *__pyx_ptype_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator = 0; +static PyTypeObject *__pyx_array_type = 0; +static PyTypeObject *__pyx_MemviewEnum_type = 0; +static PyTypeObject *__pyx_memoryview_type = 0; +static PyTypeObject *__pyx_memoryviewslice_type = 0; +static PyObject *generic = 0; +static PyObject *strided = 0; +static PyObject *indirect = 0; +static PyObject *contiguous = 0; +static PyObject *indirect_contiguous = 0; +static int __pyx_memoryview_thread_locks_used; +static PyThread_type_lock __pyx_memoryview_thread_locks[8]; +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t *__pyx_fuse_0__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(__pyx_t_13stpredictions_6models_3OK3_6_utils_DTYPE_t **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t *__pyx_fuse_1__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(__pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t **, size_t); /*proto*/ +static unsigned char *__pyx_fuse_2__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(unsigned char **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *__pyx_fuse_3__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_fuse_4__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(__pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t **, size_t); /*proto*/ +static __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t **__pyx_fuse_5__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(__pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t ***, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node *__pyx_fuse_6__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell *__pyx_fuse_7__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(struct __pyx_t_13stpredictions_6models_3OK3_10_quad_tree_Cell **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node **__pyx_fuse_8__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(struct __pyx_t_13stpredictions_6models_3OK3_5_tree_Node ***, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord *__pyx_fuse_9__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_StackRecord **, size_t); /*proto*/ +static struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord *__pyx_fuse_10__pyx_f_13stpredictions_6models_3OK3_6_utils_safe_realloc(struct __pyx_t_13stpredictions_6models_3OK3_6_utils_PriorityHeapRecord **, size_t); /*proto*/ +static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ +static void *__pyx_align_pointer(void *, size_t); /*proto*/ +static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ +static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ +static PyObject *_unellipsify(PyObject *, int); /*proto*/ +static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ +static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ +static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ +static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ +static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ +static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ +static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ +static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ +static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ +static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ +static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ +static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ +static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ +static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ +static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ +static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ +static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ +static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/ +#define __Pyx_MODULE_NAME "stpredictions.models.OK3._utils" +extern int __pyx_module_is_main_stpredictions__models__OK3___utils; +int __pyx_module_is_main_stpredictions__models__OK3___utils = 0; + +/* Implementation of 'stpredictions.models.OK3._utils' */ +static PyObject *__pyx_builtin_MemoryError; +static PyObject *__pyx_builtin_TypeError; +static PyObject *__pyx_builtin_range; +static PyObject *__pyx_builtin_ImportError; +static PyObject *__pyx_builtin_ValueError; +static PyObject *__pyx_builtin_enumerate; +static PyObject *__pyx_builtin_Ellipsis; +static PyObject *__pyx_builtin_id; +static PyObject *__pyx_builtin_IndexError; +static const char __pyx_k_O[] = "O"; +static const char __pyx_k_c[] = "c"; +static const char __pyx_k_p[] = "p"; +static const char __pyx_k_id[] = "id"; +static const char __pyx_k_np[] = "np"; +static const char __pyx_k_new[] = "__new__"; +static const char __pyx_k_obj[] = "obj"; +static const char __pyx_k_base[] = "base"; +static const char __pyx_k_copy[] = "copy"; +static const char __pyx_k_dict[] = "__dict__"; +static const char __pyx_k_main[] = "__main__"; +static const char __pyx_k_mode[] = "mode"; +static const char __pyx_k_name[] = "name"; +static const char __pyx_k_ndim[] = "ndim"; +static const char __pyx_k_pack[] = "pack"; +static const char __pyx_k_size[] = "size"; +static const char __pyx_k_step[] = "step"; +static const char __pyx_k_stop[] = "stop"; +static const char __pyx_k_test[] = "__test__"; +static const char __pyx_k_ASCII[] = "ASCII"; +static const char __pyx_k_Stack[] = "Stack"; +static const char __pyx_k_class[] = "__class__"; +static const char __pyx_k_error[] = "error"; +static const char __pyx_k_flags[] = "flags"; +static const char __pyx_k_numpy[] = "numpy"; +static const char __pyx_k_range[] = "range"; +static const char __pyx_k_shape[] = "shape"; +static const char __pyx_k_start[] = "start"; +static const char __pyx_k_encode[] = "encode"; +static const char __pyx_k_format[] = "format"; +static const char __pyx_k_import[] = "__import__"; +static const char __pyx_k_name_2[] = "__name__"; +static const char __pyx_k_pickle[] = "pickle"; +static const char __pyx_k_reduce[] = "__reduce__"; +static const char __pyx_k_struct[] = "struct"; +static const char __pyx_k_unpack[] = "unpack"; +static const char __pyx_k_update[] = "update"; +static const char __pyx_k_fortran[] = "fortran"; +static const char __pyx_k_memview[] = "memview"; +static const char __pyx_k_Ellipsis[] = "Ellipsis"; +static const char __pyx_k_capacity[] = "capacity"; +static const char __pyx_k_getstate[] = "__getstate__"; +static const char __pyx_k_itemsize[] = "itemsize"; +static const char __pyx_k_pyx_type[] = "__pyx_type"; +static const char __pyx_k_setstate[] = "__setstate__"; +static const char __pyx_k_TypeError[] = "TypeError"; +static const char __pyx_k_enumerate[] = "enumerate"; +static const char __pyx_k_pyx_state[] = "__pyx_state"; +static const char __pyx_k_reduce_ex[] = "__reduce_ex__"; +static const char __pyx_k_IndexError[] = "IndexError"; +static const char __pyx_k_ValueError[] = "ValueError"; +static const char __pyx_k_pyx_result[] = "__pyx_result"; +static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; +static const char __pyx_k_ImportError[] = "ImportError"; +static const char __pyx_k_MemoryError[] = "MemoryError"; +static const char __pyx_k_PickleError[] = "PickleError"; +static const char __pyx_k_PriorityHeap[] = "PriorityHeap"; +static const char __pyx_k_pyx_checksum[] = "__pyx_checksum"; +static const char __pyx_k_realloc_test[] = "_realloc_test"; +static const char __pyx_k_stringsource[] = "stringsource"; +static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; +static const char __pyx_k_reduce_cython[] = "__reduce_cython__"; +static const char __pyx_k_WeightedPQueue[] = "WeightedPQueue"; +static const char __pyx_k_View_MemoryView[] = "View.MemoryView"; +static const char __pyx_k_allocate_buffer[] = "allocate_buffer"; +static const char __pyx_k_dtype_is_object[] = "dtype_is_object"; +static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError"; +static const char __pyx_k_setstate_cython[] = "__setstate_cython__"; +static const char __pyx_k_initial_capacity[] = "initial_capacity"; +static const char __pyx_k_pyx_unpickle_Enum[] = "__pyx_unpickle_Enum"; +static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; +static const char __pyx_k_strided_and_direct[] = ""; +static const char __pyx_k_strided_and_indirect[] = ""; +static const char __pyx_k_contiguous_and_direct[] = ""; +static const char __pyx_k_MemoryView_of_r_object[] = ""; +static const char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; +static const char __pyx_k_contiguous_and_indirect[] = ""; +static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; +static const char __pyx_k_WeightedMedianCalculator[] = "WeightedMedianCalculator"; +static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; +static const char __pyx_k_could_not_allocate_d_bytes[] = "could not allocate %d bytes"; +static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; +static const char __pyx_k_could_not_allocate_d_d_bytes[] = "could not allocate (%d * %d) bytes"; +static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; +static const char __pyx_k_strided_and_direct_or_indirect[] = ""; +static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; +static const char __pyx_k_stpredictions_models_OK3__utils[] = "stpredictions/models/OK3/_utils.pyx"; +static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; +static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; +static const char __pyx_k_Cannot_assign_to_read_only_memor[] = "Cannot assign to read-only memoryview"; +static const char __pyx_k_Cannot_create_writable_memory_vi[] = "Cannot create writable memory view from read-only memoryview"; +static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; +static const char __pyx_k_Incompatible_checksums_s_vs_0xb0[] = "Incompatible checksums (%s vs 0xb068931 = (name))"; +static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; +static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; +static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; +static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; +static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; +static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; +static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; +static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; +static const char __pyx_k_stpredictions_models_OK3__utils_2[] = "stpredictions.models.OK3._utils"; +static PyObject *__pyx_n_s_ASCII; +static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; +static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; +static PyObject *__pyx_kp_s_Cannot_assign_to_read_only_memor; +static PyObject *__pyx_kp_s_Cannot_create_writable_memory_vi; +static PyObject *__pyx_kp_s_Cannot_index_with_type_s; +static PyObject *__pyx_n_s_Ellipsis; +static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; +static PyObject *__pyx_n_s_ImportError; +static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xb0; +static PyObject *__pyx_n_s_IndexError; +static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; +static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; +static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; +static PyObject *__pyx_n_s_MemoryError; +static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; +static PyObject *__pyx_kp_s_MemoryView_of_r_object; +static PyObject *__pyx_n_b_O; +static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; +static PyObject *__pyx_n_s_PickleError; +static PyObject *__pyx_n_s_PriorityHeap; +static PyObject *__pyx_n_s_Stack; +static PyObject *__pyx_n_s_TypeError; +static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; +static PyObject *__pyx_n_s_ValueError; +static PyObject *__pyx_n_s_View_MemoryView; +static PyObject *__pyx_n_s_WeightedMedianCalculator; +static PyObject *__pyx_n_s_WeightedPQueue; +static PyObject *__pyx_n_s_allocate_buffer; +static PyObject *__pyx_n_s_base; +static PyObject *__pyx_n_s_c; +static PyObject *__pyx_n_u_c; +static PyObject *__pyx_n_s_capacity; +static PyObject *__pyx_n_s_class; +static PyObject *__pyx_n_s_cline_in_traceback; +static PyObject *__pyx_kp_s_contiguous_and_direct; +static PyObject *__pyx_kp_s_contiguous_and_indirect; +static PyObject *__pyx_n_s_copy; +static PyObject *__pyx_kp_s_could_not_allocate_d_bytes; +static PyObject *__pyx_kp_s_could_not_allocate_d_d_bytes; +static PyObject *__pyx_n_s_dict; +static PyObject *__pyx_n_s_dtype_is_object; +static PyObject *__pyx_n_s_encode; +static PyObject *__pyx_n_s_enumerate; +static PyObject *__pyx_n_s_error; +static PyObject *__pyx_n_s_flags; +static PyObject *__pyx_n_s_format; +static PyObject *__pyx_n_s_fortran; +static PyObject *__pyx_n_u_fortran; +static PyObject *__pyx_n_s_getstate; +static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; +static PyObject *__pyx_n_s_id; +static PyObject *__pyx_n_s_import; +static PyObject *__pyx_n_s_initial_capacity; +static PyObject *__pyx_n_s_itemsize; +static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; +static PyObject *__pyx_n_s_main; +static PyObject *__pyx_n_s_memview; +static PyObject *__pyx_n_s_mode; +static PyObject *__pyx_n_s_name; +static PyObject *__pyx_n_s_name_2; +static PyObject *__pyx_n_s_ndim; +static PyObject *__pyx_n_s_new; +static PyObject *__pyx_kp_s_no_default___reduce___due_to_non; +static PyObject *__pyx_n_s_np; +static PyObject *__pyx_n_s_numpy; +static PyObject *__pyx_kp_s_numpy_core_multiarray_failed_to; +static PyObject *__pyx_kp_s_numpy_core_umath_failed_to_impor; +static PyObject *__pyx_n_s_obj; +static PyObject *__pyx_n_s_p; +static PyObject *__pyx_n_s_pack; +static PyObject *__pyx_n_s_pickle; +static PyObject *__pyx_n_s_pyx_PickleError; +static PyObject *__pyx_n_s_pyx_checksum; +static PyObject *__pyx_n_s_pyx_getbuffer; +static PyObject *__pyx_n_s_pyx_result; +static PyObject *__pyx_n_s_pyx_state; +static PyObject *__pyx_n_s_pyx_type; +static PyObject *__pyx_n_s_pyx_unpickle_Enum; +static PyObject *__pyx_n_s_pyx_vtable; +static PyObject *__pyx_n_s_range; +static PyObject *__pyx_n_s_realloc_test; +static PyObject *__pyx_n_s_reduce; +static PyObject *__pyx_n_s_reduce_cython; +static PyObject *__pyx_n_s_reduce_ex; +static PyObject *__pyx_n_s_setstate; +static PyObject *__pyx_n_s_setstate_cython; +static PyObject *__pyx_n_s_shape; +static PyObject *__pyx_n_s_size; +static PyObject *__pyx_n_s_start; +static PyObject *__pyx_n_s_step; +static PyObject *__pyx_n_s_stop; +static PyObject *__pyx_kp_s_stpredictions_models_OK3__utils; +static PyObject *__pyx_n_s_stpredictions_models_OK3__utils_2; +static PyObject *__pyx_kp_s_strided_and_direct; +static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; +static PyObject *__pyx_kp_s_strided_and_indirect; +static PyObject *__pyx_kp_s_stringsource; +static PyObject *__pyx_n_s_struct; +static PyObject *__pyx_n_s_test; +static PyObject *__pyx_kp_s_unable_to_allocate_array_data; +static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; +static PyObject *__pyx_n_s_unpack; +static PyObject *__pyx_n_s_update; +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_6_utils__realloc_test(CYTHON_UNUSED PyObject *__pyx_self); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_6_utils_5Stack___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_capacity); /* proto */ +static void __pyx_pf_13stpredictions_6models_3OK3_6_utils_5Stack_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_6_utils_5Stack_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_6_utils_5Stack_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_6_utils_12PriorityHeap___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_capacity); /* proto */ +static void __pyx_pf_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_capacity); /* proto */ +static void __pyx_pf_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_2__dealloc__(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_4__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_6__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_pf_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator___cinit__(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_initial_capacity); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_2__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_4__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ +static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ +static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_12__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ +static PyObject *__pyx_pf___pyx_array___reduce_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_array_2__setstate_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ +static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_MemviewEnum___reduce_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf___pyx_MemviewEnum_2__setstate_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */ +static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); 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+ __pyx_v_array = __pyx_t_2; + + /* "stpredictions/models/OK3/_utils.pyx":372 + * cdef SIZE_t array_ptr = self.array_ptr + * cdef WeightedPQueueRecord* array = self.array_ + * cdef SIZE_t idx_to_remove = -1 # <<<<<<<<<<<<<< + * cdef SIZE_t i + * + */ + __pyx_v_idx_to_remove = -1; + + /* "stpredictions/models/OK3/_utils.pyx":375 + * cdef SIZE_t i + * + * if array_ptr <= 0: # <<<<<<<<<<<<<< + * return -1 + * + */ + __pyx_t_3 = ((__pyx_v_array_ptr <= 0) != 0); + if (__pyx_t_3) { + + /* "stpredictions/models/OK3/_utils.pyx":376 + * + * if array_ptr <= 0: + * return -1 # <<<<<<<<<<<<<< + * + * # find element to remove + */ + __pyx_r = -1; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":375 + * cdef SIZE_t i + * + * if array_ptr <= 0: # <<<<<<<<<<<<<< + * return -1 + * + */ + } + + /* "stpredictions/models/OK3/_utils.pyx":379 + * + * # find element to remove + * for i in range(array_ptr): # <<<<<<<<<<<<<< + * if array[i].data == data and array[i].weight == weight: + * idx_to_remove = i + */ + __pyx_t_1 = __pyx_v_array_ptr; + __pyx_t_4 = __pyx_t_1; + for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { + __pyx_v_i = __pyx_t_5; + + /* "stpredictions/models/OK3/_utils.pyx":380 + * # find element to remove + * for i in range(array_ptr): + * if array[i].data == data and array[i].weight == weight: # <<<<<<<<<<<<<< + * idx_to_remove = i + * break + */ + __pyx_t_6 = (((__pyx_v_array[__pyx_v_i]).data == __pyx_v_data) != 0); + if (__pyx_t_6) { + } else { + __pyx_t_3 = __pyx_t_6; + goto __pyx_L7_bool_binop_done; + } + __pyx_t_6 = (((__pyx_v_array[__pyx_v_i]).weight == __pyx_v_weight) != 0); + __pyx_t_3 = __pyx_t_6; + __pyx_L7_bool_binop_done:; + if (__pyx_t_3) { + + /* "stpredictions/models/OK3/_utils.pyx":381 + * for i in range(array_ptr): + * if array[i].data == data and array[i].weight == weight: + * idx_to_remove = i # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_idx_to_remove = __pyx_v_i; + + /* "stpredictions/models/OK3/_utils.pyx":382 + * if array[i].data == data and array[i].weight == weight: + * idx_to_remove = i + * break # <<<<<<<<<<<<<< + * + * if idx_to_remove == -1: + */ + goto __pyx_L5_break; + + /* "stpredictions/models/OK3/_utils.pyx":380 + * # find element to remove + * for i in range(array_ptr): + * if array[i].data == data and array[i].weight == weight: # <<<<<<<<<<<<<< + * idx_to_remove = i + * break + */ + } + } + __pyx_L5_break:; + + /* "stpredictions/models/OK3/_utils.pyx":384 + * break + * + * if idx_to_remove == -1: # <<<<<<<<<<<<<< + * return -1 + * + */ + __pyx_t_3 = ((__pyx_v_idx_to_remove == -1L) != 0); + if (__pyx_t_3) { + + /* "stpredictions/models/OK3/_utils.pyx":385 + * + * if idx_to_remove == -1: + * return -1 # <<<<<<<<<<<<<< + * + * # shift the elements after the removed element + */ + __pyx_r = -1; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":384 + * break + * + * if idx_to_remove == -1: # <<<<<<<<<<<<<< + * return -1 + * + */ + } + + /* "stpredictions/models/OK3/_utils.pyx":389 + * # shift the elements after the removed element + * # to the left. + * for i in range(idx_to_remove, array_ptr-1): # <<<<<<<<<<<<<< + * array[i] = array[i+1] + * + */ + __pyx_t_7 = (__pyx_v_array_ptr - 1); + __pyx_t_8 = __pyx_t_7; + for (__pyx_t_1 = __pyx_v_idx_to_remove; __pyx_t_1 < __pyx_t_8; __pyx_t_1+=1) { + __pyx_v_i = __pyx_t_1; + + /* "stpredictions/models/OK3/_utils.pyx":390 + * # to the left. + * for i in range(idx_to_remove, array_ptr-1): + * array[i] = array[i+1] # <<<<<<<<<<<<<< + * + * self.array_ptr = array_ptr - 1 + */ + (__pyx_v_array[__pyx_v_i]) = (__pyx_v_array[(__pyx_v_i + 1)]); + } + + /* "stpredictions/models/OK3/_utils.pyx":392 + * array[i] = array[i+1] + * + * self.array_ptr = array_ptr - 1 # <<<<<<<<<<<<<< + * return 0 + * + */ + __pyx_v_self->array_ptr = (__pyx_v_array_ptr - 1); + + /* "stpredictions/models/OK3/_utils.pyx":393 + * + * self.array_ptr = array_ptr - 1 + * return 0 # <<<<<<<<<<<<<< + * + * cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil: + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":367 + * return 0 + * + * cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) nogil: # <<<<<<<<<<<<<< + * """Remove a specific value/weight record from the array. + * Returns 0 if successful, -1 if record not found.""" + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "stpredictions/models/OK3/_utils.pyx":395 + * return 0 + * + * cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil: # <<<<<<<<<<<<<< + * """Remove the top (minimum) element from array. + * Returns 0 if successful, -1 if nothing to remove.""" + */ + +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_pop(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_v_weight) { + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_array_ptr; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *__pyx_v_array; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_v_i; + int __pyx_r; + __pyx_t_13stpredictions_6models_3OK3_6_utils_SIZE_t __pyx_t_1; + struct __pyx_t_13stpredictions_6models_3OK3_6_utils_WeightedPQueueRecord *__pyx_t_2; + int __pyx_t_3; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_t_4; + long __pyx_t_5; + long __pyx_t_6; + + /* "stpredictions/models/OK3/_utils.pyx":398 + * """Remove the top (minimum) element from array. + * Returns 0 if successful, -1 if nothing to remove.""" + * cdef SIZE_t array_ptr = self.array_ptr # <<<<<<<<<<<<<< + * cdef WeightedPQueueRecord* array = self.array_ + * cdef SIZE_t i + */ + __pyx_t_1 = __pyx_v_self->array_ptr; + __pyx_v_array_ptr = __pyx_t_1; + + /* "stpredictions/models/OK3/_utils.pyx":399 + * Returns 0 if successful, -1 if nothing to remove.""" + * cdef SIZE_t array_ptr = self.array_ptr + * cdef WeightedPQueueRecord* array = self.array_ # <<<<<<<<<<<<<< + * cdef SIZE_t i + * + */ + __pyx_t_2 = __pyx_v_self->array_; + __pyx_v_array = __pyx_t_2; + + /* "stpredictions/models/OK3/_utils.pyx":402 + * cdef SIZE_t i + * + * if array_ptr <= 0: # <<<<<<<<<<<<<< + * return -1 + * + */ + __pyx_t_3 = ((__pyx_v_array_ptr <= 0) != 0); + if (__pyx_t_3) { + + /* "stpredictions/models/OK3/_utils.pyx":403 + * + * if array_ptr <= 0: + * return -1 # <<<<<<<<<<<<<< + * + * data[0] = array[0].data + */ + __pyx_r = -1; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":402 + * cdef SIZE_t i + * + * if array_ptr <= 0: # <<<<<<<<<<<<<< + * return -1 + * + */ + } + + /* "stpredictions/models/OK3/_utils.pyx":405 + * return -1 + * + * data[0] = array[0].data # <<<<<<<<<<<<<< + * weight[0] = array[0].weight + * + */ + __pyx_t_4 = (__pyx_v_array[0]).data; + (__pyx_v_data[0]) = __pyx_t_4; + + /* "stpredictions/models/OK3/_utils.pyx":406 + * + * data[0] = array[0].data + * weight[0] = array[0].weight # <<<<<<<<<<<<<< + * + * # shift the elements after the removed element + */ + __pyx_t_4 = (__pyx_v_array[0]).weight; + (__pyx_v_weight[0]) = __pyx_t_4; + + /* "stpredictions/models/OK3/_utils.pyx":410 + * # shift the elements after the removed element + * # to the left. + * for i in range(0, array_ptr-1): # <<<<<<<<<<<<<< + * array[i] = array[i+1] + * + */ + __pyx_t_5 = (__pyx_v_array_ptr - 1); + __pyx_t_6 = __pyx_t_5; + for (__pyx_t_1 = 0; __pyx_t_1 < __pyx_t_6; __pyx_t_1+=1) { + __pyx_v_i = __pyx_t_1; + + /* "stpredictions/models/OK3/_utils.pyx":411 + * # to the left. + * for i in range(0, array_ptr-1): + * array[i] = array[i+1] # <<<<<<<<<<<<<< + * + * self.array_ptr = array_ptr - 1 + */ + (__pyx_v_array[__pyx_v_i]) = (__pyx_v_array[(__pyx_v_i + 1)]); + } + + /* "stpredictions/models/OK3/_utils.pyx":413 + * array[i] = array[i+1] + * + * self.array_ptr = array_ptr - 1 # <<<<<<<<<<<<<< + * return 0 + * + */ + __pyx_v_self->array_ptr = (__pyx_v_array_ptr - 1); + + /* "stpredictions/models/OK3/_utils.pyx":414 + * + * self.array_ptr = array_ptr - 1 + * return 0 # <<<<<<<<<<<<<< + * + * cdef int peek(self, DOUBLE_t* data, DOUBLE_t* weight) nogil: + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":395 + * return 0 + * + * cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil: # <<<<<<<<<<<<<< + * """Remove the top (minimum) element from array. + * Returns 0 if successful, -1 if nothing to remove.""" + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; 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+ + /* "stpredictions/models/OK3/_utils.pyx":522 + * self.update_median_parameters_post_push(data, weight, + * original_median) + * return return_value # <<<<<<<<<<<<<< + * + * cdef int update_median_parameters_post_push( + */ + __pyx_r = __pyx_v_return_value; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":507 + * return 0 + * + * cdef int push(self, DOUBLE_t data, DOUBLE_t weight) nogil except -1: # <<<<<<<<<<<<<< + * """Push a value and its associated weight to the WeightedMedianCalculator + * + */ + + /* function exit code */ + __pyx_L1_error:; + { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); + #endif + __Pyx_AddTraceback("stpredictions.models.OK3._utils.WeightedMedianCalculator.push", __pyx_clineno, __pyx_lineno, __pyx_filename); + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + } + __pyx_r = -1; + __pyx_L0:; + return __pyx_r; +} + +/* "stpredictions/models/OK3/_utils.pyx":524 + * return return_value + * + * cdef int update_median_parameters_post_push( # <<<<<<<<<<<<<< + * self, DOUBLE_t data, DOUBLE_t weight, + * DOUBLE_t original_median) nogil: + */ + +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_update_median_parameters_post_push(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_weight, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_original_median) { + int __pyx_r; + int __pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_t_2; + int __pyx_t_3; + + /* "stpredictions/models/OK3/_utils.pyx":531 + * + * # trivial case of one element. + * if self.size() == 1: # <<<<<<<<<<<<<< + * self.k = 1 + * self.total_weight = weight + */ + __pyx_t_1 = ((((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)__pyx_v_self->__pyx_vtab)->size(__pyx_v_self) == 1) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_utils.pyx":532 + * # trivial case of one element. + * if self.size() == 1: + * self.k = 1 # <<<<<<<<<<<<<< + * self.total_weight = weight + * self.sum_w_0_k = self.total_weight + */ + __pyx_v_self->k = 1; + + /* "stpredictions/models/OK3/_utils.pyx":533 + * if self.size() == 1: + * self.k = 1 + * self.total_weight = weight # <<<<<<<<<<<<<< + * self.sum_w_0_k = self.total_weight + * return 0 + */ + __pyx_v_self->total_weight = __pyx_v_weight; + + /* "stpredictions/models/OK3/_utils.pyx":534 + * self.k = 1 + * self.total_weight = weight + * self.sum_w_0_k = self.total_weight # <<<<<<<<<<<<<< + * return 0 + * + */ + __pyx_t_2 = __pyx_v_self->total_weight; + __pyx_v_self->sum_w_0_k = __pyx_t_2; + + /* "stpredictions/models/OK3/_utils.pyx":535 + * self.total_weight = weight + * self.sum_w_0_k = self.total_weight + * return 0 # <<<<<<<<<<<<<< + * + * # get the original weighted median + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":531 + * + * # trivial case of one element. + * if self.size() == 1: # <<<<<<<<<<<<<< + * self.k = 1 + * self.total_weight = weight + */ + } + + /* "stpredictions/models/OK3/_utils.pyx":538 + * + * # get the original weighted median + * self.total_weight += weight # <<<<<<<<<<<<<< + * + * if data < original_median: + */ + __pyx_v_self->total_weight = (__pyx_v_self->total_weight + __pyx_v_weight); + + /* "stpredictions/models/OK3/_utils.pyx":540 + * self.total_weight += weight + * + * if data < original_median: # <<<<<<<<<<<<<< + * # inserting below the median, so increment k and + * # then update self.sum_w_0_k accordingly by adding + */ + __pyx_t_1 = ((__pyx_v_data < __pyx_v_original_median) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_utils.pyx":544 + * # then update self.sum_w_0_k accordingly by adding + * # the weight that was added. + * self.k += 1 # <<<<<<<<<<<<<< + * # update sum_w_0_k by adding the weight added + * self.sum_w_0_k += weight + */ + __pyx_v_self->k = (__pyx_v_self->k + 1); + + /* "stpredictions/models/OK3/_utils.pyx":546 + * self.k += 1 + * # update sum_w_0_k by adding the weight added + * self.sum_w_0_k += weight # <<<<<<<<<<<<<< + * + * # minimize k such that sum(W[0:k]) >= total_weight / 2 + */ + __pyx_v_self->sum_w_0_k = (__pyx_v_self->sum_w_0_k + __pyx_v_weight); + + /* "stpredictions/models/OK3/_utils.pyx":550 + * # minimize k such that sum(W[0:k]) >= total_weight / 2 + * # minimum value of k is 1 + * while(self.k > 1 and ((self.sum_w_0_k - # <<<<<<<<<<<<<< + * self.samples.get_weight_from_index(self.k-1)) + * >= self.total_weight / 2.0)): + */ + while (1) { + __pyx_t_3 = ((__pyx_v_self->k > 1) != 0); + if (__pyx_t_3) { + } else { + __pyx_t_1 = __pyx_t_3; + goto __pyx_L7_bool_binop_done; + } + + /* "stpredictions/models/OK3/_utils.pyx":552 + * while(self.k > 1 and ((self.sum_w_0_k - + * self.samples.get_weight_from_index(self.k-1)) + * >= self.total_weight / 2.0)): # <<<<<<<<<<<<<< + * self.k -= 1 + * self.sum_w_0_k -= self.samples.get_weight_from_index(self.k) + */ + __pyx_t_3 = (((__pyx_v_self->sum_w_0_k - ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)__pyx_v_self->samples->__pyx_vtab)->get_weight_from_index(__pyx_v_self->samples, (__pyx_v_self->k - 1))) >= (__pyx_v_self->total_weight / 2.0)) != 0); + __pyx_t_1 = __pyx_t_3; + __pyx_L7_bool_binop_done:; + if (!__pyx_t_1) break; + + /* "stpredictions/models/OK3/_utils.pyx":553 + * self.samples.get_weight_from_index(self.k-1)) + * >= self.total_weight / 2.0)): + * self.k -= 1 # <<<<<<<<<<<<<< + * self.sum_w_0_k -= self.samples.get_weight_from_index(self.k) + * return 0 + */ + __pyx_v_self->k = (__pyx_v_self->k - 1); + + /* "stpredictions/models/OK3/_utils.pyx":554 + * >= self.total_weight / 2.0)): + * self.k -= 1 + * self.sum_w_0_k -= self.samples.get_weight_from_index(self.k) # <<<<<<<<<<<<<< + * return 0 + * + */ + __pyx_v_self->sum_w_0_k = (__pyx_v_self->sum_w_0_k - ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)__pyx_v_self->samples->__pyx_vtab)->get_weight_from_index(__pyx_v_self->samples, __pyx_v_self->k)); + } + + /* "stpredictions/models/OK3/_utils.pyx":555 + * self.k -= 1 + * self.sum_w_0_k -= self.samples.get_weight_from_index(self.k) + * return 0 # <<<<<<<<<<<<<< + * + * if data >= original_median: + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":540 + * self.total_weight += weight + * + * if data < original_median: # <<<<<<<<<<<<<< + * # inserting below the median, so increment k and + * # then update self.sum_w_0_k accordingly by adding + */ + } + + /* "stpredictions/models/OK3/_utils.pyx":557 + * return 0 + * + * if data >= original_median: # <<<<<<<<<<<<<< + * # inserting above or at the median + * # minimize k such that sum(W[0:k]) >= total_weight / 2 + */ + __pyx_t_1 = ((__pyx_v_data >= __pyx_v_original_median) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_utils.pyx":560 + * # inserting above or at the median + * # minimize k such that sum(W[0:k]) >= total_weight / 2 + * while(self.k < self.samples.size() and # <<<<<<<<<<<<<< + * (self.sum_w_0_k < self.total_weight / 2.0)): + * self.k += 1 + */ + while (1) { + __pyx_t_3 = ((__pyx_v_self->k < ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)__pyx_v_self->samples->__pyx_vtab)->size(__pyx_v_self->samples)) != 0); + if (__pyx_t_3) { + } else { + __pyx_t_1 = __pyx_t_3; + goto __pyx_L12_bool_binop_done; + } + + /* "stpredictions/models/OK3/_utils.pyx":561 + * # minimize k such that sum(W[0:k]) >= total_weight / 2 + * while(self.k < self.samples.size() and + * (self.sum_w_0_k < self.total_weight / 2.0)): # <<<<<<<<<<<<<< + * self.k += 1 + * self.sum_w_0_k += self.samples.get_weight_from_index(self.k-1) + */ + __pyx_t_3 = ((__pyx_v_self->sum_w_0_k < (__pyx_v_self->total_weight / 2.0)) != 0); + __pyx_t_1 = __pyx_t_3; + __pyx_L12_bool_binop_done:; + if (!__pyx_t_1) break; + + /* "stpredictions/models/OK3/_utils.pyx":562 + * while(self.k < self.samples.size() and + * (self.sum_w_0_k < self.total_weight / 2.0)): + * self.k += 1 # <<<<<<<<<<<<<< + * self.sum_w_0_k += self.samples.get_weight_from_index(self.k-1) + * return 0 + */ + __pyx_v_self->k = (__pyx_v_self->k + 1); + + /* "stpredictions/models/OK3/_utils.pyx":563 + * (self.sum_w_0_k < self.total_weight / 2.0)): + * self.k += 1 + * self.sum_w_0_k += self.samples.get_weight_from_index(self.k-1) # <<<<<<<<<<<<<< + * return 0 + * + */ + __pyx_v_self->sum_w_0_k = (__pyx_v_self->sum_w_0_k + ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)__pyx_v_self->samples->__pyx_vtab)->get_weight_from_index(__pyx_v_self->samples, (__pyx_v_self->k - 1))); + } + + /* "stpredictions/models/OK3/_utils.pyx":564 + * self.k += 1 + * self.sum_w_0_k += self.samples.get_weight_from_index(self.k-1) + * return 0 # <<<<<<<<<<<<<< + * + * cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) nogil: + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":557 + * return 0 + * + * if data >= original_median: # <<<<<<<<<<<<<< + * # inserting above or at the median + * # minimize k such that sum(W[0:k]) >= total_weight / 2 + */ + } + + /* "stpredictions/models/OK3/_utils.pyx":524 + * return return_value + * + * cdef int update_median_parameters_post_push( # <<<<<<<<<<<<<< + * self, DOUBLE_t data, DOUBLE_t weight, + * DOUBLE_t original_median) nogil: + */ + + /* function exit code */ + __pyx_r = 0; + __pyx_L0:; + return __pyx_r; +} + +/* "stpredictions/models/OK3/_utils.pyx":566 + * return 0 + * + * cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) nogil: # <<<<<<<<<<<<<< + * """Remove a value from the MedianHeap, removing it + * from consideration in the median calculation + */ + +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_remove(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_weight) { + int __pyx_v_return_value; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_original_median; + int __pyx_r; + int __pyx_t_1; + + /* "stpredictions/models/OK3/_utils.pyx":571 + * """ + * cdef int return_value + * cdef DOUBLE_t original_median = 0.0 # <<<<<<<<<<<<<< + * + * if self.size() != 0: + */ + __pyx_v_original_median = 0.0; + + /* "stpredictions/models/OK3/_utils.pyx":573 + * cdef DOUBLE_t original_median = 0.0 + * + * if self.size() != 0: # <<<<<<<<<<<<<< + * original_median = self.get_median() + * + */ + __pyx_t_1 = ((((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)__pyx_v_self->__pyx_vtab)->size(__pyx_v_self) != 0) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_utils.pyx":574 + * + * if self.size() != 0: + * original_median = self.get_median() # <<<<<<<<<<<<<< + * + * return_value = self.samples.remove(data, weight) + */ + __pyx_v_original_median = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)__pyx_v_self->__pyx_vtab)->get_median(__pyx_v_self); + + /* "stpredictions/models/OK3/_utils.pyx":573 + * cdef DOUBLE_t original_median = 0.0 + * + * if self.size() != 0: # <<<<<<<<<<<<<< + * original_median = self.get_median() + * + */ + } + + /* "stpredictions/models/OK3/_utils.pyx":576 + * original_median = self.get_median() + * + * return_value = self.samples.remove(data, weight) # <<<<<<<<<<<<<< + * self.update_median_parameters_post_remove(data, weight, + * original_median) + */ + __pyx_v_return_value = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)__pyx_v_self->samples->__pyx_vtab)->remove(__pyx_v_self->samples, __pyx_v_data, __pyx_v_weight); + + /* "stpredictions/models/OK3/_utils.pyx":577 + * + * return_value = self.samples.remove(data, weight) + * self.update_median_parameters_post_remove(data, weight, # <<<<<<<<<<<<<< + * original_median) + * return return_value + */ + (void)(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)__pyx_v_self->__pyx_vtab)->update_median_parameters_post_remove(__pyx_v_self, __pyx_v_data, __pyx_v_weight, __pyx_v_original_median)); + + /* "stpredictions/models/OK3/_utils.pyx":579 + * self.update_median_parameters_post_remove(data, weight, + * original_median) + * return return_value # <<<<<<<<<<<<<< + * + * cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil: + */ + __pyx_r = __pyx_v_return_value; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":566 + * return 0 + * + * cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) nogil: # <<<<<<<<<<<<<< + * """Remove a value from the MedianHeap, removing it + * from consideration in the median calculation + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "stpredictions/models/OK3/_utils.pyx":581 + * return return_value + * + * cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil: # <<<<<<<<<<<<<< + * """Pop a value from the MedianHeap, starting from the + * left and moving to the right. + */ + +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_pop(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t *__pyx_v_weight) { + int __pyx_v_return_value; + double __pyx_v_original_median; + int __pyx_r; + int __pyx_t_1; + + /* "stpredictions/models/OK3/_utils.pyx":586 + * """ + * cdef int return_value + * cdef double original_median = 0.0 # <<<<<<<<<<<<<< + * + * if self.size() != 0: + */ + __pyx_v_original_median = 0.0; + + /* "stpredictions/models/OK3/_utils.pyx":588 + * cdef double original_median = 0.0 + * + * if self.size() != 0: # <<<<<<<<<<<<<< + * original_median = self.get_median() + * + */ + __pyx_t_1 = ((((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)__pyx_v_self->__pyx_vtab)->size(__pyx_v_self) != 0) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_utils.pyx":589 + * + * if self.size() != 0: + * original_median = self.get_median() # <<<<<<<<<<<<<< + * + * # no elements to pop + */ + __pyx_v_original_median = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)__pyx_v_self->__pyx_vtab)->get_median(__pyx_v_self); + + /* "stpredictions/models/OK3/_utils.pyx":588 + * cdef double original_median = 0.0 + * + * if self.size() != 0: # <<<<<<<<<<<<<< + * original_median = self.get_median() + * + */ + } + + /* "stpredictions/models/OK3/_utils.pyx":592 + * + * # no elements to pop + * if self.samples.size() == 0: # <<<<<<<<<<<<<< + * return -1 + * + */ + __pyx_t_1 = ((((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)__pyx_v_self->samples->__pyx_vtab)->size(__pyx_v_self->samples) == 0) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_utils.pyx":593 + * # no elements to pop + * if self.samples.size() == 0: + * return -1 # <<<<<<<<<<<<<< + * + * return_value = self.samples.pop(data, weight) + */ + __pyx_r = -1; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":592 + * + * # no elements to pop + * if self.samples.size() == 0: # <<<<<<<<<<<<<< + * return -1 + * + */ + } + + /* "stpredictions/models/OK3/_utils.pyx":595 + * return -1 + * + * return_value = self.samples.pop(data, weight) # <<<<<<<<<<<<<< + * self.update_median_parameters_post_remove(data[0], + * weight[0], + */ + __pyx_v_return_value = ((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)__pyx_v_self->samples->__pyx_vtab)->pop(__pyx_v_self->samples, __pyx_v_data, __pyx_v_weight); + + /* "stpredictions/models/OK3/_utils.pyx":596 + * + * return_value = self.samples.pop(data, weight) + * self.update_median_parameters_post_remove(data[0], # <<<<<<<<<<<<<< + * weight[0], + * original_median) + */ + (void)(((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)__pyx_v_self->__pyx_vtab)->update_median_parameters_post_remove(__pyx_v_self, (__pyx_v_data[0]), (__pyx_v_weight[0]), __pyx_v_original_median)); + + /* "stpredictions/models/OK3/_utils.pyx":599 + * weight[0], + * original_median) + * return return_value # <<<<<<<<<<<<<< + * + * cdef int update_median_parameters_post_remove( + */ + __pyx_r = __pyx_v_return_value; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":581 + * return return_value + * + * cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil: # <<<<<<<<<<<<<< + * """Pop a value from the MedianHeap, starting from the + * left and moving to the right. + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "stpredictions/models/OK3/_utils.pyx":601 + * return return_value + * + * cdef int update_median_parameters_post_remove( # <<<<<<<<<<<<<< + * self, DOUBLE_t data, DOUBLE_t weight, + * double original_median) nogil: + */ + +static int __pyx_f_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_update_median_parameters_post_remove(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *__pyx_v_self, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_data, __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_v_weight, double __pyx_v_original_median) { + int __pyx_r; + int __pyx_t_1; + __pyx_t_13stpredictions_6models_3OK3_6_utils_DOUBLE_t __pyx_t_2; + int __pyx_t_3; + + /* "stpredictions/models/OK3/_utils.pyx":607 + * namely `k` and `sum_w_0_k` after a removal""" + * # reset parameters because it there are no elements + * if self.samples.size() == 0: # <<<<<<<<<<<<<< + * self.k = 0 + * self.total_weight = 0 + */ + __pyx_t_1 = ((((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)__pyx_v_self->samples->__pyx_vtab)->size(__pyx_v_self->samples) == 0) != 0); + if (__pyx_t_1) { + + /* "stpredictions/models/OK3/_utils.pyx":608 + * # reset parameters because it there are no elements + * if self.samples.size() == 0: + * self.k = 0 # <<<<<<<<<<<<<< + * self.total_weight = 0 + * self.sum_w_0_k = 0 + */ + __pyx_v_self->k = 0; + + /* "stpredictions/models/OK3/_utils.pyx":609 + * if self.samples.size() == 0: + * self.k = 0 + * self.total_weight = 0 # <<<<<<<<<<<<<< + * self.sum_w_0_k = 0 + * return 0 + */ + __pyx_v_self->total_weight = 0.0; + + /* "stpredictions/models/OK3/_utils.pyx":610 + * self.k = 0 + * self.total_weight = 0 + * self.sum_w_0_k = 0 # <<<<<<<<<<<<<< + * return 0 + * + */ + __pyx_v_self->sum_w_0_k = 0.0; + + /* "stpredictions/models/OK3/_utils.pyx":611 + * self.total_weight = 0 + * self.sum_w_0_k = 0 + * return 0 # <<<<<<<<<<<<<< + * + * # trivial case of one element. + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "stpredictions/models/OK3/_utils.pyx":607 + * namely `k` and `sum_w_0_k` after a removal""" + * # reset parameters because it there are no elements + * if self.samples.size() == 0: # <<<<<<<<<<<<<< + * self.k = 0 + * self.total_weight = 0 + */ + } + + /* "stpredictions/models/OK3/_utils.pyx":614 + * + * # trivial case of one element. + * if self.samples.size() == 1: # <<<<<<<<<<<<<< + * self.k = 1 + * self.total_weight -= weight + */ + __pyx_t_1 = ((((struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)__pyx_v_self->samples->__pyx_vtab)->size(__pyx_v_self->samples) == 1) != 0); 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+ if (__pyx_t_2) { + + /* "View.MemoryView":1131 + * for i in range(ndim): + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< + * break + * + */ + __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1132 + * if mslice.shape[i] > 1: + * f_stride = mslice.strides[i] + * break # <<<<<<<<<<<<<< + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): + */ + goto __pyx_L7_break; + + /* "View.MemoryView":1130 + * + * for i in range(ndim): + * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< + * f_stride = mslice.strides[i] + * break + */ + } + } + __pyx_L7_break:; + + /* "View.MemoryView":1134 + * break + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< + * return 'C' + * else: + */ + __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1135 + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): + * return 'C' # <<<<<<<<<<<<<< + * else: + * return 'F' + */ + __pyx_r = 'C'; + goto __pyx_L0; + + /* "View.MemoryView":1134 + * break + * + * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< + * return 'C' + * else: + */ + } + + /* "View.MemoryView":1137 + * return 'C' + * else: + * return 'F' # <<<<<<<<<<<<<< + * + * @cython.cdivision(True) + */ + /*else*/ { + __pyx_r = 'F'; + goto __pyx_L0; + } + + /* "View.MemoryView":1116 + * + * @cname('__pyx_get_best_slice_order') + * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< + * """ + * Figure out the best memory access order for a given slice. + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1140 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + +static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + CYTHON_UNUSED Py_ssize_t __pyx_v_i; + CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; + Py_ssize_t __pyx_v_dst_extent; + Py_ssize_t __pyx_v_src_stride; + Py_ssize_t __pyx_v_dst_stride; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + Py_ssize_t __pyx_t_4; + Py_ssize_t __pyx_t_5; + Py_ssize_t __pyx_t_6; + + /* "View.MemoryView":1147 + * + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + */ + __pyx_v_src_extent = (__pyx_v_src_shape[0]); + + /* "View.MemoryView":1148 + * cdef Py_ssize_t i + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] + */ + __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); + + /* "View.MemoryView":1149 + * cdef Py_ssize_t src_extent = src_shape[0] + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + */ + __pyx_v_src_stride = (__pyx_v_src_strides[0]); + + /* "View.MemoryView":1150 + * cdef Py_ssize_t dst_extent = dst_shape[0] + * cdef Py_ssize_t src_stride = src_strides[0] + * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< + * + * if ndim == 1: + */ + __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); + + /* "View.MemoryView":1152 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); + if (__pyx_t_2) { + } else { + __pyx_t_1 = __pyx_t_2; + goto __pyx_L5_bool_binop_done; + } + + /* "View.MemoryView":1154 + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + */ + __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); + if (__pyx_t_2) { + __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); + } + __pyx_t_3 = (__pyx_t_2 != 0); + __pyx_t_1 = __pyx_t_3; + __pyx_L5_bool_binop_done:; + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + if (__pyx_t_1) { + + /* "View.MemoryView":1155 + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent))); + + /* "View.MemoryView":1153 + * + * if ndim == 1: + * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< + * src_stride == itemsize == dst_stride): + * memcpy(dst_data, src_data, itemsize * dst_extent) + */ + goto __pyx_L4; + } + + /* "View.MemoryView":1157 + * memcpy(dst_data, src_data, itemsize * dst_extent) + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + */ + /*else*/ { + __pyx_t_4 = __pyx_v_dst_extent; + __pyx_t_5 = __pyx_t_4; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1158 + * else: + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< + * src_data += src_stride + * dst_data += dst_stride + */ + (void)(memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize)); + + /* "View.MemoryView":1159 + * for i in range(dst_extent): + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * else: + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1160 + * memcpy(dst_data, src_data, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * else: + * for i in range(dst_extent): + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L4:; + + /* "View.MemoryView":1152 + * cdef Py_ssize_t dst_stride = dst_strides[0] + * + * if ndim == 1: # <<<<<<<<<<<<<< + * if (src_stride > 0 and dst_stride > 0 and + * src_stride == itemsize == dst_stride): + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1162 + * dst_data += dst_stride + * else: + * for i in range(dst_extent): # <<<<<<<<<<<<<< + * _copy_strided_to_strided(src_data, src_strides + 1, + * dst_data, dst_strides + 1, + */ + /*else*/ { + __pyx_t_4 = __pyx_v_dst_extent; + __pyx_t_5 = __pyx_t_4; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1163 + * else: + * for i in range(dst_extent): + * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< + * dst_data, dst_strides + 1, + * src_shape + 1, dst_shape + 1, + */ + _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); + + /* "View.MemoryView":1167 + * src_shape + 1, dst_shape + 1, + * ndim - 1, itemsize) + * src_data += src_stride # <<<<<<<<<<<<<< + * dst_data += dst_stride + * + */ + __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); + + /* "View.MemoryView":1168 + * ndim - 1, itemsize) + * src_data += src_stride + * dst_data += dst_stride # <<<<<<<<<<<<<< + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, + */ + __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); + } + } + __pyx_L3:; + + /* "View.MemoryView":1140 + * + * @cython.cdivision(True) + * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< + * char *dst_data, Py_ssize_t *dst_strides, + * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, + */ + + /* function exit code */ +} + +/* "View.MemoryView":1170 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + +static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { + + /* "View.MemoryView":1173 + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< + * src.shape, dst.shape, ndim, itemsize) + * + */ + _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1170 + * dst_data += dst_stride + * + * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *dst, + * int ndim, size_t itemsize) nogil: + */ + + /* function exit code */ +} + +/* "View.MemoryView":1177 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + */ + +static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { + Py_ssize_t __pyx_v_shape; + Py_ssize_t __pyx_v_size; + Py_ssize_t __pyx_r; + Py_ssize_t __pyx_t_1; + Py_ssize_t *__pyx_t_2; + Py_ssize_t *__pyx_t_3; + Py_ssize_t *__pyx_t_4; + + /* "View.MemoryView":1179 + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize # <<<<<<<<<<<<<< + * + * for shape in src.shape[:ndim]: + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; + __pyx_v_size = __pyx_t_1; + + /* "View.MemoryView":1181 + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + * + * for shape in src.shape[:ndim]: # <<<<<<<<<<<<<< + * size *= shape + * + */ + __pyx_t_3 = (__pyx_v_src->shape + __pyx_v_ndim); + for (__pyx_t_4 = __pyx_v_src->shape; __pyx_t_4 < __pyx_t_3; __pyx_t_4++) { + __pyx_t_2 = __pyx_t_4; + __pyx_v_shape = (__pyx_t_2[0]); + + /* "View.MemoryView":1182 + * + * for shape in src.shape[:ndim]: + * size *= shape # <<<<<<<<<<<<<< + * + * return size + */ + __pyx_v_size = (__pyx_v_size * __pyx_v_shape); + } + + /* "View.MemoryView":1184 + * size *= shape + * + * return size # <<<<<<<<<<<<<< + * + * @cname('__pyx_fill_contig_strides_array') + */ + __pyx_r = __pyx_v_size; + goto __pyx_L0; + + /* "View.MemoryView":1177 + * + * @cname('__pyx_memoryview_slice_get_size') + * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< + * "Return the size of the memory occupied by the slice in number of bytes" + * cdef Py_ssize_t shape, size = src.memview.view.itemsize + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1187 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + +static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { + int __pyx_v_idx; + Py_ssize_t __pyx_r; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + int __pyx_t_4; + + /* "View.MemoryView":1196 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + __pyx_t_1 = ((__pyx_v_order == 'F') != 0); + if (__pyx_t_1) { + + /* "View.MemoryView":1197 + * + * if order == 'F': + * for idx in range(ndim): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride *= shape[idx] + */ + __pyx_t_2 = __pyx_v_ndim; + __pyx_t_3 = __pyx_t_2; + for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { + __pyx_v_idx = __pyx_t_4; + + /* "View.MemoryView":1198 + * if order == 'F': + * for idx in range(ndim): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride *= shape[idx] + * else: + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1199 + * for idx in range(ndim): + * strides[idx] = stride + * stride *= shape[idx] # <<<<<<<<<<<<<< + * else: + * for idx in range(ndim - 1, -1, -1): + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + } + + /* "View.MemoryView":1196 + * cdef int idx + * + * if order == 'F': # <<<<<<<<<<<<<< + * for idx in range(ndim): + * strides[idx] = stride + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1201 + * stride *= shape[idx] + * else: + * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * strides[idx] = stride + * stride *= shape[idx] + */ + /*else*/ { + for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1; __pyx_t_2-=1) { + __pyx_v_idx = __pyx_t_2; + + /* "View.MemoryView":1202 + * else: + * for idx in range(ndim - 1, -1, -1): + * strides[idx] = stride # <<<<<<<<<<<<<< + * stride *= shape[idx] + * + */ + (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; + + /* "View.MemoryView":1203 + * for idx in range(ndim - 1, -1, -1): + * strides[idx] = stride + * stride *= shape[idx] # <<<<<<<<<<<<<< + * + * return stride + */ + __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); + } + } + __pyx_L3:; + + /* "View.MemoryView":1205 + * stride *= shape[idx] + * + * return stride # <<<<<<<<<<<<<< + * + * @cname('__pyx_memoryview_copy_data_to_temp') + */ + __pyx_r = __pyx_v_stride; + goto __pyx_L0; + + /* "View.MemoryView":1187 + * + * @cname('__pyx_fill_contig_strides_array') + * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< + * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, + * int ndim, char order) nogil: + */ + + /* function exit code */ + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1208 + * + * @cname('__pyx_memoryview_copy_data_to_temp') + * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice *tmpslice, + * char order, + */ + +static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_tmpslice, char __pyx_v_order, int __pyx_v_ndim) { + int __pyx_v_i; + void *__pyx_v_result; + size_t __pyx_v_itemsize; + size_t __pyx_v_size; + void *__pyx_r; + Py_ssize_t __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + struct __pyx_memoryview_obj *__pyx_t_4; + int __pyx_t_5; + int __pyx_t_6; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + + /* "View.MemoryView":1219 + * cdef void *result + * + * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< + * cdef size_t size = slice_get_size(src, ndim) + * + */ + __pyx_t_1 = __pyx_v_src->memview->view.itemsize; + __pyx_v_itemsize = __pyx_t_1; + + /* "View.MemoryView":1220 + * + * cdef size_t itemsize = src.memview.view.itemsize + * cdef size_t size = slice_get_size(src, ndim) # <<<<<<<<<<<<<< + * + * result = malloc(size) + */ + __pyx_v_size = __pyx_memoryview_slice_get_size(__pyx_v_src, __pyx_v_ndim); + + /* "View.MemoryView":1222 + * cdef size_t size = slice_get_size(src, ndim) + * + * result = malloc(size) # <<<<<<<<<<<<<< + * if not result: + * _err(MemoryError, NULL) + */ + __pyx_v_result = malloc(__pyx_v_size); + + /* "View.MemoryView":1223 + * + * result = malloc(size) + * if not result: # <<<<<<<<<<<<<< + * _err(MemoryError, NULL) + * + */ + __pyx_t_2 = ((!(__pyx_v_result != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1224 + * result = malloc(size) + * if not result: + * _err(MemoryError, NULL) # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == ((int)-1))) __PYX_ERR(1, 1224, __pyx_L1_error) + + /* "View.MemoryView":1223 + * + * result = malloc(size) + * if not result: # <<<<<<<<<<<<<< + * _err(MemoryError, NULL) + * + */ + } + + /* "View.MemoryView":1227 + * + * + * tmpslice.data = result # <<<<<<<<<<<<<< + * tmpslice.memview = src.memview + * for i in range(ndim): + */ + __pyx_v_tmpslice->data = ((char *)__pyx_v_result); + + /* "View.MemoryView":1228 + * + * tmpslice.data = result + * tmpslice.memview = src.memview # <<<<<<<<<<<<<< + * for i in range(ndim): + * tmpslice.shape[i] = src.shape[i] + */ + __pyx_t_4 = __pyx_v_src->memview; + __pyx_v_tmpslice->memview = __pyx_t_4; + + /* "View.MemoryView":1229 + * tmpslice.data = result + * tmpslice.memview = src.memview + * for i in range(ndim): # <<<<<<<<<<<<<< + * tmpslice.shape[i] = src.shape[i] + * tmpslice.suboffsets[i] = -1 + */ + __pyx_t_3 = __pyx_v_ndim; + __pyx_t_5 = __pyx_t_3; + for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { + __pyx_v_i = __pyx_t_6; + + /* "View.MemoryView":1230 + * tmpslice.memview = src.memview + * for i in range(ndim): + * tmpslice.shape[i] = src.shape[i] # <<<<<<<<<<<<<< + * tmpslice.suboffsets[i] = -1 + * + */ + (__pyx_v_tmpslice->shape[__pyx_v_i]) = (__pyx_v_src->shape[__pyx_v_i]); + + /* "View.MemoryView":1231 + * for i in range(ndim): + * tmpslice.shape[i] = src.shape[i] + * tmpslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< + * + * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, + */ + (__pyx_v_tmpslice->suboffsets[__pyx_v_i]) = -1L; + } + + /* "View.MemoryView":1233 + * tmpslice.suboffsets[i] = -1 + * + * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, # <<<<<<<<<<<<<< + * ndim, order) + * + */ + (void)(__pyx_fill_contig_strides_array((&(__pyx_v_tmpslice->shape[0])), (&(__pyx_v_tmpslice->strides[0])), __pyx_v_itemsize, __pyx_v_ndim, __pyx_v_order)); 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+ + /* "View.MemoryView":1284 + * cdef __Pyx_memviewslice tmp + * + * if src_ndim < dst_ndim: # <<<<<<<<<<<<<< + * broadcast_leading(&src, src_ndim, dst_ndim) + * elif dst_ndim < src_ndim: + */ + goto __pyx_L3; + } + + /* "View.MemoryView":1286 + * if src_ndim < dst_ndim: + * broadcast_leading(&src, src_ndim, dst_ndim) + * elif dst_ndim < src_ndim: # <<<<<<<<<<<<<< + * broadcast_leading(&dst, dst_ndim, src_ndim) + * + */ + __pyx_t_2 = ((__pyx_v_dst_ndim < __pyx_v_src_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1287 + * broadcast_leading(&src, src_ndim, dst_ndim) + * elif dst_ndim < src_ndim: + * broadcast_leading(&dst, dst_ndim, src_ndim) # <<<<<<<<<<<<<< + * + * cdef int ndim = max(src_ndim, dst_ndim) + */ + __pyx_memoryview_broadcast_leading((&__pyx_v_dst), __pyx_v_dst_ndim, __pyx_v_src_ndim); + + /* "View.MemoryView":1286 + * if src_ndim < dst_ndim: + * broadcast_leading(&src, src_ndim, dst_ndim) + * elif dst_ndim < src_ndim: # <<<<<<<<<<<<<< + * broadcast_leading(&dst, dst_ndim, src_ndim) + * + */ + } + __pyx_L3:; + + /* "View.MemoryView":1289 + * broadcast_leading(&dst, dst_ndim, src_ndim) + * + * cdef int ndim = max(src_ndim, dst_ndim) # <<<<<<<<<<<<<< + * + * for i in range(ndim): + */ + __pyx_t_3 = __pyx_v_dst_ndim; + __pyx_t_4 = __pyx_v_src_ndim; + if (((__pyx_t_3 > __pyx_t_4) != 0)) { + __pyx_t_5 = __pyx_t_3; + } else { + __pyx_t_5 = __pyx_t_4; + } + __pyx_v_ndim = __pyx_t_5; + + /* "View.MemoryView":1291 + * cdef int ndim = max(src_ndim, dst_ndim) + * + * for i in range(ndim): # <<<<<<<<<<<<<< + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: + */ + __pyx_t_5 = __pyx_v_ndim; + __pyx_t_3 = __pyx_t_5; + for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) { + __pyx_v_i = __pyx_t_4; + + /* "View.MemoryView":1292 + * + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< + * if src.shape[i] == 1: + * broadcasting = True + */ + __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) != (__pyx_v_dst.shape[__pyx_v_i])) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1293 + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: # <<<<<<<<<<<<<< + * broadcasting = True + * src.strides[i] = 0 + */ + __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) == 1) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1294 + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: + * broadcasting = True # <<<<<<<<<<<<<< + * src.strides[i] = 0 + * else: + */ + __pyx_v_broadcasting = 1; + + /* "View.MemoryView":1295 + * if src.shape[i] == 1: + * broadcasting = True + * src.strides[i] = 0 # <<<<<<<<<<<<<< + * else: + * _err_extents(i, dst.shape[i], src.shape[i]) + */ + (__pyx_v_src.strides[__pyx_v_i]) = 0; + + /* "View.MemoryView":1293 + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: + * if src.shape[i] == 1: # <<<<<<<<<<<<<< + * broadcasting = True + * src.strides[i] = 0 + */ + goto __pyx_L7; + } + + /* "View.MemoryView":1297 + * src.strides[i] = 0 + * else: + * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<< + * + * if src.suboffsets[i] >= 0: + */ + /*else*/ { + __pyx_t_6 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(1, 1297, __pyx_L1_error) + } + __pyx_L7:; + + /* "View.MemoryView":1292 + * + * for i in range(ndim): + * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< + * if src.shape[i] == 1: + * broadcasting = True + */ + } + + /* "View.MemoryView":1299 + * _err_extents(i, dst.shape[i], src.shape[i]) + * + * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + */ + __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1300 + * + * if src.suboffsets[i] >= 0: + * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<< + * + * if slices_overlap(&src, &dst, ndim, itemsize): + */ + __pyx_t_6 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Dimension %d is not direct"), __pyx_v_i); if (unlikely(__pyx_t_6 == ((int)-1))) __PYX_ERR(1, 1300, __pyx_L1_error) + + /* "View.MemoryView":1299 + * _err_extents(i, dst.shape[i], src.shape[i]) + * + * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + */ + } + } + + /* "View.MemoryView":1302 + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< + * + * if not slice_is_contig(src, order, ndim): + */ + __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1304 + * if slices_overlap(&src, &dst, ndim, itemsize): + * + * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< + * order = get_best_order(&dst, ndim) + * + */ + __pyx_t_2 = ((!(__pyx_memviewslice_is_contig(__pyx_v_src, __pyx_v_order, __pyx_v_ndim) != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1305 + * + * if not slice_is_contig(src, order, ndim): + * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) + */ + __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim); + + /* "View.MemoryView":1304 + * if slices_overlap(&src, &dst, ndim, itemsize): + * + * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< + * order = get_best_order(&dst, ndim) + * + */ + } + + /* "View.MemoryView":1307 + * order = get_best_order(&dst, ndim) + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< + * src = tmp + * + */ + __pyx_t_7 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_7 == ((void *)NULL))) __PYX_ERR(1, 1307, __pyx_L1_error) + __pyx_v_tmpdata = __pyx_t_7; + + /* "View.MemoryView":1308 + * + * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) + * src = tmp # <<<<<<<<<<<<<< + * + * if not broadcasting: + */ + __pyx_v_src = __pyx_v_tmp; + + /* "View.MemoryView":1302 + * _err_dim(ValueError, "Dimension %d is not direct", i) + * + * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< + * + * if not slice_is_contig(src, order, ndim): + */ + } + + /* "View.MemoryView":1310 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1313 + * + * + * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'C', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1314 + * + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) # <<<<<<<<<<<<<< + * elif slice_is_contig(src, 'F', ndim): + * direct_copy = slice_is_contig(dst, 'F', ndim) + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim); + + /* "View.MemoryView":1313 + * + * + * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + */ + goto __pyx_L12; + } + + /* "View.MemoryView":1315 + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + */ + __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'F', __pyx_v_ndim) != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1316 + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): + * direct_copy = slice_is_contig(dst, 'F', ndim) # <<<<<<<<<<<<<< + * + * if direct_copy: + */ + __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim); + + /* "View.MemoryView":1315 + * if slice_is_contig(src, 'C', ndim): + * direct_copy = slice_is_contig(dst, 'C', ndim) + * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + */ + } + __pyx_L12:; + + /* "View.MemoryView":1318 + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_2 = (__pyx_v_direct_copy != 0); + if (__pyx_t_2) { + + /* "View.MemoryView":1320 + * if direct_copy: + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1321 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + */ + (void)(memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim))); + + /* "View.MemoryView":1322 + * refcount_copying(&dst, dtype_is_object, ndim, False) + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * free(tmpdata) + * return 0 + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1323 + * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) # <<<<<<<<<<<<<< + * return 0 + * + */ + free(__pyx_v_tmpdata); + + /* "View.MemoryView":1324 + * refcount_copying(&dst, dtype_is_object, ndim, True) + * free(tmpdata) + * return 0 # <<<<<<<<<<<<<< + * + * if order == 'F' == get_best_order(&dst, ndim): + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "View.MemoryView":1318 + * direct_copy = slice_is_contig(dst, 'F', ndim) + * + * if direct_copy: # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + } + + /* "View.MemoryView":1310 + * src = tmp + * + * if not broadcasting: # <<<<<<<<<<<<<< + * + * + */ + } + + /* "View.MemoryView":1326 + * return 0 + * + * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< + * + * + */ + __pyx_t_2 = (__pyx_v_order == 'F'); + if (__pyx_t_2) { + __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim)); + } + __pyx_t_8 = (__pyx_t_2 != 0); + if (__pyx_t_8) { + + /* "View.MemoryView":1329 + * + * + * transpose_memslice(&src) # <<<<<<<<<<<<<< + * transpose_memslice(&dst) + * + */ + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(1, 1329, __pyx_L1_error) + + /* "View.MemoryView":1330 + * + * transpose_memslice(&src) + * transpose_memslice(&dst) # <<<<<<<<<<<<<< + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + */ + __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == ((int)0))) __PYX_ERR(1, 1330, __pyx_L1_error) + + /* "View.MemoryView":1326 + * return 0 + * + * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< + * + * + */ + } + + /* "View.MemoryView":1332 + * transpose_memslice(&dst) + * + * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< + * copy_strided_to_strided(&src, &dst, ndim, itemsize) + * refcount_copying(&dst, dtype_is_object, ndim, True) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); + + /* "View.MemoryView":1333 + * + * refcount_copying(&dst, dtype_is_object, ndim, False) + * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< + * refcount_copying(&dst, dtype_is_object, ndim, True) + * + */ + copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); + + /* "View.MemoryView":1334 + * refcount_copying(&dst, dtype_is_object, ndim, False) + * copy_strided_to_strided(&src, &dst, ndim, itemsize) + * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< + * + * free(tmpdata) + */ + __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); + + /* "View.MemoryView":1336 + * refcount_copying(&dst, dtype_is_object, ndim, True) + * + * free(tmpdata) # <<<<<<<<<<<<<< + * return 0 + * + */ + free(__pyx_v_tmpdata); + + /* "View.MemoryView":1337 + * + * free(tmpdata) + * return 0 # <<<<<<<<<<<<<< + * + * @cname('__pyx_memoryview_broadcast_leading') + */ + __pyx_r = 0; + goto __pyx_L0; + + /* "View.MemoryView":1268 + * + * @cname('__pyx_memoryview_copy_contents') + * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< + * __Pyx_memviewslice dst, + * int src_ndim, int dst_ndim, + */ + + /* function exit code */ + __pyx_L1_error:; + { + #ifdef WITH_THREAD + PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure(); + #endif + __Pyx_AddTraceback("View.MemoryView.memoryview_copy_contents", __pyx_clineno, __pyx_lineno, __pyx_filename); + #ifdef WITH_THREAD + __Pyx_PyGILState_Release(__pyx_gilstate_save); + #endif + } + __pyx_r = -1; + __pyx_L0:; + return __pyx_r; +} + +/* "View.MemoryView":1340 + * + * @cname('__pyx_memoryview_broadcast_leading') + * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< + * int ndim, + * int ndim_other) nogil: + */ + +static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) { + int __pyx_v_i; + int __pyx_v_offset; + int __pyx_t_1; + int __pyx_t_2; + int __pyx_t_3; + + /* "View.MemoryView":1344 + * int ndim_other) nogil: + * cdef int i + * cdef int offset = ndim_other - ndim # <<<<<<<<<<<<<< + * + * for i in range(ndim - 1, -1, -1): + */ + __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim); + + /* "View.MemoryView":1346 + * cdef int offset = ndim_other - ndim + * + * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] + */ + for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1; __pyx_t_1-=1) { + __pyx_v_i = __pyx_t_1; + + /* "View.MemoryView":1347 + * + * for i in range(ndim - 1, -1, -1): + * mslice.shape[i + offset] = mslice.shape[i] # <<<<<<<<<<<<<< + * mslice.strides[i + offset] = mslice.strides[i] + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] + */ + (__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]); + + /* "View.MemoryView":1348 + * for i in range(ndim - 1, -1, -1): + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] # <<<<<<<<<<<<<< + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] + * + */ + (__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]); + + /* "View.MemoryView":1349 + * mslice.shape[i + offset] = mslice.shape[i] + * mslice.strides[i + offset] = mslice.strides[i] + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] # <<<<<<<<<<<<<< + * + * for i in range(offset): + */ + (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]); + } + + /* "View.MemoryView":1351 + * mslice.suboffsets[i + offset] = mslice.suboffsets[i] + * + * for i in range(offset): # <<<<<<<<<<<<<< + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] + */ + __pyx_t_1 = __pyx_v_offset; + __pyx_t_2 = __pyx_t_1; + for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { + __pyx_v_i = __pyx_t_3; + + /* "View.MemoryView":1352 + * + * for i in range(offset): + * mslice.shape[i] = 1 # <<<<<<<<<<<<<< + * mslice.strides[i] = mslice.strides[0] + * mslice.suboffsets[i] = -1 + */ + (__pyx_v_mslice->shape[__pyx_v_i]) = 1; + + /* "View.MemoryView":1353 + * for i in range(offset): + * mslice.shape[i] = 1 + * mslice.strides[i] = mslice.strides[0] # <<<<<<<<<<<<<< + * mslice.suboffsets[i] = -1 + * + */ + (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]); 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+ +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_6_utils_Stack = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._utils.Stack", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_Stack), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_6_utils_Stack, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "A LIFO data structure.\n\n Attributes\n ----------\n capacity : SIZE_t\n The elements the stack can hold; if more added then ``self.stack_``\n needs to be resized.\n\n top : SIZE_t\n The number of elements currently on the stack.\n\n stack : StackRecord pointer\n The stack of records (upward in the stack corresponds to the right).\n ", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_13stpredictions_6models_3OK3_6_utils_Stack, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_13stpredictions_6models_3OK3_6_utils_Stack, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_PriorityHeap __pyx_vtable_13stpredictions_6models_3OK3_6_utils_PriorityHeap; + +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_6_utils_PriorityHeap(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap *)o); + p->__pyx_vtab = __pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_PriorityHeap; + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_1__cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_6_utils_PriorityHeap(PyObject *o) { + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_pw_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_3__dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + (*Py_TYPE(o)->tp_free)(o); +} + +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_6_utils_PriorityHeap[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_5__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_6_utils_12PriorityHeap_7__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_6_utils_PriorityHeap = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._utils.PriorityHeap", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_PriorityHeap), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_6_utils_PriorityHeap, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "A priority queue implemented as a binary heap.\n\n The heap invariant is that the impurity improvement of the parent record\n is larger then the impurity improvement of the children.\n\n Attributes\n ----------\n capacity : SIZE_t\n The capacity of the heap\n\n heap_ptr : SIZE_t\n The water mark of the heap; the heap grows from left to right in the\n array ``heap_``. The following invariant holds ``heap_ptr < capacity``.\n\n heap_ : PriorityHeapRecord*\n The array of heap records. The maximum element is on the left;\n the heap grows from left to right\n ", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_13stpredictions_6models_3OK3_6_utils_PriorityHeap, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_13stpredictions_6models_3OK3_6_utils_PriorityHeap, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedPQueue __pyx_vtable_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; + +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_6_utils_WeightedPQueue(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)o); + p->__pyx_vtab = __pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedPQueue; + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_1__cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_6_utils_WeightedPQueue(PyObject *o) { + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_pw_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_3__dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + (*Py_TYPE(o)->tp_free)(o); +} + +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_6_utils_WeightedPQueue[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_5__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_6_utils_14WeightedPQueue_7__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_6_utils_WeightedPQueue = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._utils.WeightedPQueue", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_6_utils_WeightedPQueue, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "A priority queue class, always sorted in increasing order.\n\n Attributes\n ----------\n capacity : SIZE_t\n The capacity of the priority queue.\n\n array_ptr : SIZE_t\n The water mark of the priority queue; the priority queue grows from\n left to right in the array ``array_``. ``array_ptr`` is always\n less than ``capacity``.\n\n array_ : WeightedPQueueRecord*\n The array of priority queue records. The minimum element is on the\n left at index 0, and the maximum element is on the right at index\n ``array_ptr-1``.\n ", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_13stpredictions_6models_3OK3_6_utils_WeightedPQueue, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_13stpredictions_6models_3OK3_6_utils_WeightedPQueue, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator __pyx_vtable_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; + +static PyObject *__pyx_tp_new_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)o); + p->__pyx_vtab = __pyx_vtabptr_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator; + p->samples = ((struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)Py_None); Py_INCREF(Py_None); + if (unlikely(__pyx_pw_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_1__cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator(PyObject *o) { + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *p = (struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + Py_CLEAR(p->samples); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *p = (struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)o; + if (p->samples) { + e = (*v)(((PyObject *)p->samples), a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator(PyObject *o) { + PyObject* tmp; + struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *p = (struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator *)o; + tmp = ((PyObject*)p->samples); + p->samples = ((struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedPQueue *)Py_None); Py_INCREF(Py_None); + Py_XDECREF(tmp); + return 0; +} + +static PyMethodDef __pyx_methods_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_3__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_13stpredictions_6models_3OK3_6_utils_24WeightedMedianCalculator_5__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._utils.WeightedMedianCalculator", /*tp_name*/ + sizeof(struct __pyx_obj_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "A class to handle calculation of the weighted median from streams of\n data. To do so, it maintains a parameter ``k`` such that the sum of the\n weights in the range [0,k) is greater than or equal to half of the total\n weight. By minimizing the value of ``k`` that fulfills this constraint,\n calculating the median is done by either taking the value of the sample\n at index ``k-1`` of ``samples`` (samples[k-1].data) or the average of\n the samples at index ``k-1`` and ``k`` of ``samples``\n ((samples[k-1] + samples[k]) / 2).\n\n Attributes\n ----------\n initial_capacity : SIZE_t\n The initial capacity of the WeightedMedianCalculator.\n\n samples : WeightedPQueue\n Holds the samples (consisting of values and their weights) used in the\n weighted median calculation.\n\n total_weight : DOUBLE_t\n The sum of the weights of items in ``samples``. Represents the total\n weight of all samples used in the median calculation.\n\n k : SIZE_t\n Index used to calculate the median.\n\n sum_w_0_k : DOUBLE_t\n The sum of the weights from samples[0:k]. Used in the weighted\n median calculation; minimizing the value of ``k`` such that\n ``sum_w_0_k`` >= ``total_weight / 2`` provides a mechanism for\n calculating the median in constant time.\n\n ", /*tp_doc*/ + __pyx_tp_traverse_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator, /*tp_traverse*/ + __pyx_tp_clear_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_13stpredictions_6models_3OK3_6_utils_WeightedMedianCalculator, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_array __pyx_vtable_array; + +static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_array_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_array_obj *)o); + p->__pyx_vtab = __pyx_vtabptr_array; + p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None); + p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None); + if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_array(PyObject *o) { + struct __pyx_array_obj *p = (struct __pyx_array_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_array___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->mode); + Py_CLEAR(p->_format); + (*Py_TYPE(o)->tp_free)(o); +} +static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_array___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) { + PyObject *v = __Pyx_PyObject_GenericGetAttr(o, n); + if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Clear(); + v = __pyx_array___getattr__(o, n); + } + return v; +} + +static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_5array_7memview_1__get__(o); +} + +static PyMethodDef __pyx_methods_array[] = { + {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_array_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_array_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_array[] = { + {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_array = { + __pyx_array___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_array, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_array = { + __pyx_array___len__, /*mp_length*/ + __pyx_array___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_array = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_array_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + +static PyTypeObject __pyx_type___pyx_array = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._utils.array", /*tp_name*/ + sizeof(struct __pyx_array_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_array, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + &__pyx_tp_as_sequence_array, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_array, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + __pyx_tp_getattro_array, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_array, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + 0, /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_array, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_array, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_array, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; + +static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + struct __pyx_MemviewEnum_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_MemviewEnum_obj *)o); + p->name = Py_None; Py_INCREF(Py_None); + return o; +} + +static void __pyx_tp_dealloc_Enum(PyObject *o) { + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + Py_CLEAR(p->name); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + if (p->name) { + e = (*v)(p->name, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_Enum(PyObject *o) { + PyObject* tmp; + struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; + tmp = ((PyObject*)p->name); + p->name = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + return 0; +} + +static PyMethodDef __pyx_methods_Enum[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_MemviewEnum_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_MemviewEnum = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._utils.Enum", /*tp_name*/ + sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_Enum, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + __pyx_MemviewEnum___repr__, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_Enum, /*tp_traverse*/ + __pyx_tp_clear_Enum, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_Enum, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + __pyx_MemviewEnum___init__, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_Enum, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; +static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview; + +static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) { + struct __pyx_memoryview_obj *p; + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + p = ((struct __pyx_memoryview_obj *)o); + p->__pyx_vtab = __pyx_vtabptr_memoryview; + p->obj = Py_None; Py_INCREF(Py_None); + p->_size = Py_None; Py_INCREF(Py_None); + p->_array_interface = Py_None; Py_INCREF(Py_None); + p->view.obj = NULL; + if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_memoryview(PyObject *o) { + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + PyObject_GC_UnTrack(o); + { + PyObject *etype, *eval, *etb; + PyErr_Fetch(&etype, &eval, &etb); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) + 1); + __pyx_memoryview___dealloc__(o); + __Pyx_SET_REFCNT(o, Py_REFCNT(o) - 1); + PyErr_Restore(etype, eval, etb); + } + Py_CLEAR(p->obj); + Py_CLEAR(p->_size); + Py_CLEAR(p->_array_interface); + (*Py_TYPE(o)->tp_free)(o); +} + +static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) { + int e; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + if (p->obj) { + e = (*v)(p->obj, a); if (e) return e; + } + if (p->_size) { + e = (*v)(p->_size, a); if (e) return e; + } + if (p->_array_interface) { + e = (*v)(p->_array_interface, a); if (e) return e; + } + if (p->view.obj) { + e = (*v)(p->view.obj, a); if (e) return e; + } + return 0; +} + +static int __pyx_tp_clear_memoryview(PyObject *o) { + PyObject* tmp; + struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; + tmp = ((PyObject*)p->obj); + p->obj = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_size); + p->_size = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + tmp = ((PyObject*)p->_array_interface); + p->_array_interface = Py_None; Py_INCREF(Py_None); + Py_XDECREF(tmp); + Py_CLEAR(p->view.obj); + return 0; +} +static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) { + PyObject *r; + PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; + r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); + Py_DECREF(x); + return r; +} + +static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) { + if (v) { + return __pyx_memoryview___setitem__(o, i, v); + } + else { + PyErr_Format(PyExc_NotImplementedError, + "Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name); + return -1; + } +} + +static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_1T_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4base_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_5shape_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_7strides_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_10suboffsets_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4ndim_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_8itemsize_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_6nbytes_1__get__(o); +} + +static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_10memoryview_4size_1__get__(o); +} + +static PyMethodDef __pyx_methods_memoryview[] = { + {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0}, + {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0}, + {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0}, + {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0}, + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets_memoryview[] = { + {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, (char *)0, 0}, + {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, (char *)0, 0}, + {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, (char *)0, 0}, + {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, (char *)0, 0}, + {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, (char *)0, 0}, + {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, (char *)0, 0}, + {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, (char *)0, 0}, + {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, (char *)0, 0}, + {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PySequenceMethods __pyx_tp_as_sequence_memoryview = { + __pyx_memoryview___len__, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + __pyx_sq_item_memoryview, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_memoryview = { + __pyx_memoryview___len__, /*mp_length*/ + __pyx_memoryview___getitem__, /*mp_subscript*/ + __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_memoryview = { + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getreadbuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getwritebuffer*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getsegcount*/ + #endif + #if PY_MAJOR_VERSION < 3 + 0, /*bf_getcharbuffer*/ + #endif + __pyx_memoryview_getbuffer, /*bf_getbuffer*/ + 0, /*bf_releasebuffer*/ +}; + 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Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + 0, /*tp_doc*/ + __pyx_tp_traverse_memoryview, /*tp_traverse*/ + __pyx_tp_clear_memoryview, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_memoryview, /*tp_methods*/ + 0, /*tp_members*/ + __pyx_getsets_memoryview, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_memoryview, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, 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*__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) { + return __pyx_pw_15View_dot_MemoryView_16_memoryviewslice_4base_1__get__(o); +} + +static PyMethodDef __pyx_methods__memoryviewslice[] = { + {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_1__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_3__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = { + {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, (char *)0, 0}, + {0, 0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type___pyx_memoryviewslice = { + PyVarObject_HEAD_INIT(0, 0) + "stpredictions.models.OK3._utils._memoryviewslice", /*tp_name*/ + sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 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PyDict_Size(kwargs) : 0; + if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { + return NULL; + } + if ( +#if PY_MAJOR_VERSION >= 3 + co->co_kwonlyargcount == 0 && +#endif + likely(kwargs == NULL || nk == 0) && + co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { + if (argdefs == NULL && co->co_argcount == nargs) { + result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); + goto done; + } + else if (nargs == 0 && argdefs != NULL + && co->co_argcount == Py_SIZE(argdefs)) { + /* function called with no arguments, but all parameters have + a default value: use default values as arguments .*/ + args = &PyTuple_GET_ITEM(argdefs, 0); + result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); + goto done; + } + } + if (kwargs != NULL) { + Py_ssize_t pos, i; + kwtuple = PyTuple_New(2 * nk); + if (kwtuple == NULL) { + result = NULL; + goto done; + } + k = &PyTuple_GET_ITEM(kwtuple, 0); + pos = i = 0; + while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { + Py_INCREF(k[i]); + Py_INCREF(k[i+1]); + i += 2; + } + nk = i / 2; + } + else { + kwtuple = NULL; + k = NULL; + } + closure = PyFunction_GET_CLOSURE(func); +#if PY_MAJOR_VERSION >= 3 + kwdefs = PyFunction_GET_KW_DEFAULTS(func); +#endif + if (argdefs != NULL) { + d = &PyTuple_GET_ITEM(argdefs, 0); + nd = Py_SIZE(argdefs); + } + else { + d = NULL; + nd = 0; + } +#if PY_MAJOR_VERSION >= 3 + result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, kwdefs, closure); +#else + result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, closure); +#endif + Py_XDECREF(kwtuple); +done: + Py_LeaveRecursiveCall(); + return result; +} +#endif +#endif + +/* PyObjectCall */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { + PyObject *result; + ternaryfunc call = func->ob_type->tp_call; + if (unlikely(!call)) + return PyObject_Call(func, arg, kw); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = (*call)(func, arg, kw); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallMethO */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallOneArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, &arg, 1); + } +#endif + if (likely(PyCFunction_Check(func))) { + if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { + return __Pyx_PyObject_CallMethO(func, arg); +#if CYTHON_FAST_PYCCALL + } else if (__Pyx_PyFastCFunction_Check(func)) { + return __Pyx_PyCFunction_FastCall(func, &arg, 1); +#endif + } + } + return __Pyx__PyObject_CallOneArg(func, arg); +} +#else +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_Pack(1, arg); + if (unlikely(!args)) return NULL; + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +#endif + +/* PyErrFetchRestore */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} +#endif + +/* RaiseException */ +#if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + __Pyx_PyThreadState_declare + Py_XINCREF(type); + if (!value || value == Py_None) + value = NULL; + else + Py_INCREF(value); + if (!tb || tb == Py_None) + tb = NULL; + else { + Py_INCREF(tb); + if (!PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + } + if (PyType_Check(type)) { +#if CYTHON_COMPILING_IN_PYPY + if (!value) { + Py_INCREF(Py_None); + value = Py_None; + } +#endif + PyErr_NormalizeException(&type, &value, &tb); + } else { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + value = type; + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + } + __Pyx_PyThreadState_assign + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + PyObject* owned_instance = NULL; + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (PyExceptionClass_Check(type)) { + PyObject *instance_class = NULL; + if (value && PyExceptionInstance_Check(value)) { + instance_class = (PyObject*) Py_TYPE(value); + if (instance_class != type) { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { + instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; + } + } + } + if (!instance_class) { + PyObject *args; + if (!value) + args = PyTuple_New(0); + else if (PyTuple_Check(value)) { + Py_INCREF(value); + args = value; + } else + args = PyTuple_Pack(1, value); + if (!args) + goto bad; + owned_instance = PyObject_Call(type, args, NULL); + Py_DECREF(args); + if (!owned_instance) + goto bad; + value = owned_instance; + if (!PyExceptionInstance_Check(value)) { + PyErr_Format(PyExc_TypeError, + "calling %R should have returned an instance of " + "BaseException, not %R", + type, Py_TYPE(value)); + goto bad; + } + } + } else { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + if (cause == Py_None) { + fixed_cause = NULL; + } else if (PyExceptionClass_Check(cause)) { + fixed_cause = PyObject_CallObject(cause, NULL); + if (fixed_cause == NULL) + goto bad; + } else if (PyExceptionInstance_Check(cause)) { + fixed_cause = cause; + Py_INCREF(fixed_cause); + } else { + PyErr_SetString(PyExc_TypeError, + "exception causes must derive from " + "BaseException"); + goto bad; + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } +#endif + } +bad: + Py_XDECREF(owned_instance); + return; +} +#endif + +/* PyObjectCallNoArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, NULL, 0); + } +#endif +#ifdef __Pyx_CyFunction_USED + if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) +#else + if (likely(PyCFunction_Check(func))) +#endif + { + if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { + return __Pyx_PyObject_CallMethO(func, NULL); + } + } + return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); +} +#endif + +/* ExtTypeTest */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +/* RaiseDoubleKeywords */ +static void __Pyx_RaiseDoubleKeywordsError( + const char* func_name, + PyObject* kw_name) +{ + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION >= 3 + "%s() got multiple values for keyword argument '%U'", func_name, kw_name); + #else + "%s() got multiple values for keyword argument '%s'", func_name, + PyString_AsString(kw_name)); + #endif +} + +/* ParseKeywords */ +static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + continue; + } + name = first_kw_arg; + #if PY_MAJOR_VERSION < 3 + if (likely(PyString_Check(key))) { + while (*name) { + if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) + && _PyString_Eq(**name, key)) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + if ((**argname == key) || ( + (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) + && _PyString_Eq(**argname, key))) { + goto arg_passed_twice; + } + argname++; + } + } + } else + #endif + if (likely(PyUnicode_Check(key))) { + while (*name) { + int cmp = (**name == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**name, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + int cmp = (**argname == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**argname, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) goto arg_passed_twice; + argname++; + } + } + } else + goto invalid_keyword_type; + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, key); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%.200s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%.200s() got an unexpected keyword argument '%.200s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +/* RaiseArgTupleInvalid */ +static void __Pyx_RaiseArgtupleInvalid( + const char* func_name, + int exact, + Py_ssize_t num_min, + Py_ssize_t num_max, + Py_ssize_t num_found) +{ + Py_ssize_t num_expected; + const char *more_or_less; + if (num_found < num_min) { + num_expected = num_min; + more_or_less = "at least"; + } else { + num_expected = num_max; + more_or_less = "at most"; + } + if (exact) { + more_or_less = "exactly"; + } + PyErr_Format(PyExc_TypeError, + "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", + func_name, more_or_less, num_expected, + (num_expected == 1) ? "" : "s", num_found); +} + +/* GetTopmostException */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ +#if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ +#if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +/* WriteUnraisableException */ +static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, + CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, + int full_traceback, CYTHON_UNUSED int nogil) { + PyObject *old_exc, *old_val, *old_tb; + PyObject *ctx; + __Pyx_PyThreadState_declare +#ifdef WITH_THREAD + PyGILState_STATE state; + if (nogil) + state = PyGILState_Ensure(); +#ifdef _MSC_VER + else state = (PyGILState_STATE)-1; +#endif +#endif + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); + if (full_traceback) { + Py_XINCREF(old_exc); + Py_XINCREF(old_val); + Py_XINCREF(old_tb); + __Pyx_ErrRestore(old_exc, old_val, old_tb); + PyErr_PrintEx(1); + } + #if PY_MAJOR_VERSION < 3 + ctx = PyString_FromString(name); + #else + ctx = PyUnicode_FromString(name); + #endif + __Pyx_ErrRestore(old_exc, old_val, old_tb); + if (!ctx) { + PyErr_WriteUnraisable(Py_None); + } else { + PyErr_WriteUnraisable(ctx); + Py_DECREF(ctx); + } +#ifdef WITH_THREAD + if (nogil) + PyGILState_Release(state); +#endif +} + +/* ArgTypeTest */ +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) +{ + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + else if (exact) { + #if PY_MAJOR_VERSION == 2 + if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; + #endif + } + else { + if (likely(__Pyx_TypeCheck(obj, type))) return 1; + } + PyErr_Format(PyExc_TypeError, + "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); + return 0; +} + +/* PyObjectCall2Args */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { + PyObject *args, *result = NULL; + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyFunction_FastCall(function, args, 2); + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyCFunction_FastCall(function, args, 2); + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(arg1); + PyTuple_SET_ITEM(args, 0, arg1); + Py_INCREF(arg2); + PyTuple_SET_ITEM(args, 1, arg2); + Py_INCREF(function); + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); +done: + return result; +} + +/* BytesEquals */ +static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else + if (s1 == s2) { + return (equals == Py_EQ); + } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { + const char *ps1, *ps2; + Py_ssize_t length = PyBytes_GET_SIZE(s1); + if (length != PyBytes_GET_SIZE(s2)) + return (equals == Py_NE); + ps1 = PyBytes_AS_STRING(s1); + ps2 = PyBytes_AS_STRING(s2); + if (ps1[0] != ps2[0]) { + return (equals == Py_NE); + } else if (length == 1) { + return (equals == Py_EQ); + } else { + int result; +#if CYTHON_USE_UNICODE_INTERNALS + Py_hash_t hash1, hash2; + hash1 = ((PyBytesObject*)s1)->ob_shash; + hash2 = ((PyBytesObject*)s2)->ob_shash; + if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { + return (equals == Py_NE); + } +#endif + result = memcmp(ps1, ps2, (size_t)length); + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { + return (equals == Py_NE); + } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { + return (equals == Py_NE); + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +#endif +} + +/* UnicodeEquals */ +static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { +#if CYTHON_COMPILING_IN_PYPY + return PyObject_RichCompareBool(s1, s2, equals); +#else +#if PY_MAJOR_VERSION < 3 + PyObject* owned_ref = NULL; +#endif + int s1_is_unicode, s2_is_unicode; + if (s1 == s2) { + goto return_eq; + } + s1_is_unicode = PyUnicode_CheckExact(s1); + s2_is_unicode = PyUnicode_CheckExact(s2); +#if PY_MAJOR_VERSION < 3 + if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { + owned_ref = PyUnicode_FromObject(s2); + if (unlikely(!owned_ref)) + return -1; + s2 = owned_ref; + s2_is_unicode = 1; + } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { + owned_ref = PyUnicode_FromObject(s1); + if (unlikely(!owned_ref)) + return -1; + s1 = owned_ref; + s1_is_unicode = 1; + } else if (((!s2_is_unicode) & (!s1_is_unicode))) { + return __Pyx_PyBytes_Equals(s1, s2, equals); + } +#endif + if (s1_is_unicode & s2_is_unicode) { + Py_ssize_t length; + int kind; + void *data1, *data2; + if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) + return -1; + length = __Pyx_PyUnicode_GET_LENGTH(s1); + if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { + goto return_ne; + } +#if CYTHON_USE_UNICODE_INTERNALS + { + Py_hash_t hash1, hash2; + #if CYTHON_PEP393_ENABLED + hash1 = ((PyASCIIObject*)s1)->hash; + hash2 = ((PyASCIIObject*)s2)->hash; + #else + hash1 = ((PyUnicodeObject*)s1)->hash; + hash2 = ((PyUnicodeObject*)s2)->hash; + #endif + if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { + goto return_ne; + } + } +#endif + kind = __Pyx_PyUnicode_KIND(s1); + if (kind != __Pyx_PyUnicode_KIND(s2)) { + goto return_ne; + } + data1 = __Pyx_PyUnicode_DATA(s1); + data2 = __Pyx_PyUnicode_DATA(s2); + if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { + goto return_ne; + } else if (length == 1) { + goto return_eq; + } else { + int result = memcmp(data1, data2, (size_t)(length * kind)); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ) ? (result == 0) : (result != 0); + } + } else if ((s1 == Py_None) & s2_is_unicode) { + goto return_ne; + } else if ((s2 == Py_None) & s1_is_unicode) { + goto return_ne; + } else { + int result; + PyObject* py_result = PyObject_RichCompare(s1, s2, equals); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + if (!py_result) + return -1; + result = __Pyx_PyObject_IsTrue(py_result); + Py_DECREF(py_result); + return result; + } +return_eq: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_EQ); +return_ne: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(owned_ref); + #endif + return (equals == Py_NE); +#endif +} + +/* GetAttr */ +static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { +#if CYTHON_USE_TYPE_SLOTS +#if PY_MAJOR_VERSION >= 3 + if (likely(PyUnicode_Check(n))) +#else + if (likely(PyString_Check(n))) +#endif + return __Pyx_PyObject_GetAttrStr(o, n); +#endif + return PyObject_GetAttr(o, n); +} + +/* GetItemInt */ +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { + PyObject *r; + if (!j) return NULL; + r = PyObject_GetItem(o, j); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyList_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { + PyObject *r = PyList_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyTuple_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); + if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { + PyObject *r = PyList_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } + else if (PyTuple_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + return NULL; + PyErr_Clear(); + } + } + return m->sq_item(o, i); + } + } +#else + if (is_list || PySequence_Check(o)) { + return PySequence_GetItem(o, i); + } +#endif + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +} + +/* ObjectGetItem */ +#if CYTHON_USE_TYPE_SLOTS +static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { + PyObject *runerr; + Py_ssize_t key_value; + PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; + if (unlikely(!(m && m->sq_item))) { + PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); + return NULL; + } + key_value = __Pyx_PyIndex_AsSsize_t(index); + if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { + return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); + } + if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { + PyErr_Clear(); + PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); + } + return NULL; +} +static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { + PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; + if (likely(m && m->mp_subscript)) { + return m->mp_subscript(obj, key); + } + return __Pyx_PyObject_GetIndex(obj, key); +} +#endif + +/* decode_c_string */ +static CYTHON_INLINE PyObject* __Pyx_decode_c_string( + const char* cstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { + Py_ssize_t length; + if (unlikely((start < 0) | (stop < 0))) { + size_t slen = strlen(cstring); + if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { + PyErr_SetString(PyExc_OverflowError, + "c-string too long to convert to Python"); + return NULL; + } + length = (Py_ssize_t) slen; + if (start < 0) { + start += length; + if (start < 0) + start = 0; + } + if (stop < 0) + stop += length; + } + if (unlikely(stop <= start)) + return __Pyx_NewRef(__pyx_empty_unicode); + length = stop - start; + cstring += start; + if (decode_func) { + return decode_func(cstring, length, errors); + } else { + return PyUnicode_Decode(cstring, length, encoding, errors); + } +} + +/* GetAttr3 */ +static PyObject *__Pyx_GetAttr3Default(PyObject *d) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + return NULL; + __Pyx_PyErr_Clear(); + Py_INCREF(d); + return d; +} +static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) { + PyObject *r = __Pyx_GetAttr(o, n); + return (likely(r)) ? r : __Pyx_GetAttr3Default(d); +} + +/* PyDictVersioning */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + +/* GetModuleGlobalName */ +#if CYTHON_USE_DICT_VERSIONS +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) +#else +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) +#endif +{ + PyObject *result; +#if !CYTHON_AVOID_BORROWED_REFS +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 + result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } else if (unlikely(PyErr_Occurred())) { + return NULL; + } +#else + result = PyDict_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } +#endif +#else + result = PyObject_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } + PyErr_Clear(); +#endif + return __Pyx_GetBuiltinName(name); +} + +/* RaiseTooManyValuesToUnpack */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { + PyErr_Format(PyExc_ValueError, + "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); +} + +/* RaiseNeedMoreValuesToUnpack */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { + PyErr_Format(PyExc_ValueError, + "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", + index, (index == 1) ? "" : "s"); +} + +/* RaiseNoneIterError */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); +} + +/* SwapException */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = *type; + exc_info->exc_value = *value; + exc_info->exc_traceback = *tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = *type; + tstate->exc_value = *value; + tstate->exc_traceback = *tb; + #endif + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} +#else +static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); + PyErr_SetExcInfo(*type, *value, *tb); + *type = tmp_type; + *value = tmp_value; + *tb = tmp_tb; +} +#endif + +/* Import */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_MAJOR_VERSION < 3 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_MAJOR_VERSION < 3 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + +/* FastTypeChecks */ +#if CYTHON_COMPILING_IN_CPYTHON +static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { + while (a) { + a = a->tp_base; + if (a == b) + return 1; + } + return b == &PyBaseObject_Type; +} +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { + PyObject *mro; + if (a == b) return 1; + mro = a->tp_mro; + if (likely(mro)) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(mro); + for (i = 0; i < n; i++) { + if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) + return 1; + } + return 0; + } + return __Pyx_InBases(a, b); +} +#if PY_MAJOR_VERSION == 2 +static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { + PyObject *exception, *value, *tb; + int res; + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&exception, &value, &tb); + res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + if (!res) { + res = PyObject_IsSubclass(err, exc_type2); + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + } + __Pyx_ErrRestore(exception, value, tb); + return res; +} +#else +static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { + int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; + if (!res) { + res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); + } + return res; +} +#endif +static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + assert(PyExceptionClass_Check(exc_type)); + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; i= 0 || (x^b) >= 0)) + return PyInt_FromLong(x); + return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + #endif + #if CYTHON_USE_PYLONG_INTERNALS + if (likely(PyLong_CheckExact(op1))) { + const long b = intval; + long a, x; +#ifdef HAVE_LONG_LONG + const PY_LONG_LONG llb = intval; + PY_LONG_LONG lla, llx; +#endif + const digit* digits = ((PyLongObject*)op1)->ob_digit; + const Py_ssize_t size = Py_SIZE(op1); + if (likely(__Pyx_sst_abs(size) <= 1)) { + a = likely(size) ? digits[0] : 0; + if (size == -1) a = -a; + } else { + switch (size) { + case -2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + default: return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + } + x = a + b; + return PyLong_FromLong(x); +#ifdef HAVE_LONG_LONG + long_long: + llx = lla + llb; + return PyLong_FromLongLong(llx); +#endif + + + } + #endif + if (PyFloat_CheckExact(op1)) { + const long b = intval; + double a = PyFloat_AS_DOUBLE(op1); + double result; + PyFPE_START_PROTECT("add", return NULL) + result = ((double)a) + (double)b; + PyFPE_END_PROTECT(result) + return PyFloat_FromDouble(result); + } + return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); +} +#endif + +/* None */ +static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { + PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); +} + +/* ImportFrom */ +static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { + PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); + if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { + PyErr_Format(PyExc_ImportError, + #if PY_MAJOR_VERSION < 3 + "cannot import name %.230s", PyString_AS_STRING(name)); + #else + "cannot import name %S", name); + #endif + } + return value; +} + +/* HasAttr */ +static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) { + PyObject *r; + if (unlikely(!__Pyx_PyBaseString_Check(n))) { + PyErr_SetString(PyExc_TypeError, + "hasattr(): attribute name must be string"); + return -1; + } + r = __Pyx_GetAttr(o, n); + if (unlikely(!r)) { + PyErr_Clear(); + return 0; + } else { + Py_DECREF(r); + return 1; + } +} + +/* PyObject_GenericGetAttrNoDict */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) { + PyErr_Format(PyExc_AttributeError, +#if PY_MAJOR_VERSION >= 3 + "'%.50s' object has no attribute '%U'", + tp->tp_name, attr_name); +#else + "'%.50s' object has no attribute '%.400s'", + tp->tp_name, PyString_AS_STRING(attr_name)); +#endif + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) { + PyObject *descr; + PyTypeObject *tp = Py_TYPE(obj); + if (unlikely(!PyString_Check(attr_name))) { + return PyObject_GenericGetAttr(obj, attr_name); + } + assert(!tp->tp_dictoffset); + descr = _PyType_Lookup(tp, attr_name); + if (unlikely(!descr)) { + return __Pyx_RaiseGenericGetAttributeError(tp, attr_name); + } + Py_INCREF(descr); + #if PY_MAJOR_VERSION < 3 + if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS))) + #endif + { + descrgetfunc f = Py_TYPE(descr)->tp_descr_get; + if (unlikely(f)) { + PyObject *res = f(descr, obj, (PyObject *)tp); + Py_DECREF(descr); + return res; + } + } + return descr; +} +#endif + +/* PyObject_GenericGetAttr */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) { + if (unlikely(Py_TYPE(obj)->tp_dictoffset)) { + return PyObject_GenericGetAttr(obj, attr_name); + } + return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name); +} +#endif + +/* SetVTable */ +static int __Pyx_SetVtable(PyObject *dict, void *vtable) { +#if PY_VERSION_HEX >= 0x02070000 + PyObject *ob = PyCapsule_New(vtable, 0, 0); +#else + PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); +#endif + if (!ob) + goto bad; + if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) + goto bad; + Py_DECREF(ob); + return 0; +bad: + Py_XDECREF(ob); + return -1; +} + +/* PyObjectGetAttrStrNoError */ +static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) + __Pyx_PyErr_Clear(); +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { + PyObject *result; +#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1 + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { + return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); + } +#endif + result = __Pyx_PyObject_GetAttrStr(obj, attr_name); + if (unlikely(!result)) { + __Pyx_PyObject_GetAttrStr_ClearAttributeError(); + } + return result; +} + +/* SetupReduce */ +static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { + int ret; + PyObject *name_attr; + name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2); + if (likely(name_attr)) { + ret = PyObject_RichCompareBool(name_attr, name, Py_EQ); + } else { + ret = -1; + } + if (unlikely(ret < 0)) { + PyErr_Clear(); + ret = 0; + } + Py_XDECREF(name_attr); + return ret; +} +static int __Pyx_setup_reduce(PyObject* type_obj) { + int ret = 0; + PyObject *object_reduce = NULL; + PyObject *object_reduce_ex = NULL; + PyObject *reduce = NULL; + PyObject *reduce_ex = NULL; + PyObject *reduce_cython = NULL; + PyObject *setstate = NULL; + PyObject *setstate_cython = NULL; +#if CYTHON_USE_PYTYPE_LOOKUP + if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#else + if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#endif +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#else + object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#endif + reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; + if (reduce_ex == object_reduce_ex) { +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#else + object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#endif + reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; + if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { + reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython); + if (likely(reduce_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (reduce == object_reduce || PyErr_Occurred()) { + goto __PYX_BAD; + } + setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); + if (!setstate) PyErr_Clear(); + if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { + setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython); + if (likely(setstate_cython)) { + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } else if (!setstate || PyErr_Occurred()) { + goto __PYX_BAD; + } + } + PyType_Modified((PyTypeObject*)type_obj); + } + } + goto __PYX_GOOD; +__PYX_BAD: + if (!PyErr_Occurred()) + PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); + ret = -1; +__PYX_GOOD: +#if !CYTHON_USE_PYTYPE_LOOKUP + Py_XDECREF(object_reduce); + Py_XDECREF(object_reduce_ex); +#endif + Py_XDECREF(reduce); + Py_XDECREF(reduce_ex); + Py_XDECREF(reduce_cython); + Py_XDECREF(setstate); + Py_XDECREF(setstate_cython); + return ret; +} + +/* TypeImport */ +#ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, + size_t size, enum __Pyx_ImportType_CheckSize check_size) +{ + PyObject *result = 0; + char warning[200]; + Py_ssize_t basicsize; +#ifdef Py_LIMITED_API + PyObject *py_basicsize; +#endif + result = PyObject_GetAttrString(module, class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%.200s.%.200s is not a type object", + module_name, class_name); + goto bad; + } +#ifndef Py_LIMITED_API + basicsize = ((PyTypeObject *)result)->tp_basicsize; +#else + py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); + if (!py_basicsize) + goto bad; + basicsize = PyLong_AsSsize_t(py_basicsize); + Py_DECREF(py_basicsize); + py_basicsize = 0; + if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) + goto bad; +#endif + if ((size_t)basicsize < size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(result); + return NULL; +} +#endif + +/* GetVTable */ +static void* __Pyx_GetVtable(PyObject *dict) { + void* ptr; + PyObject *ob = PyObject_GetItem(dict, __pyx_n_s_pyx_vtable); + if (!ob) + goto bad; +#if PY_VERSION_HEX >= 0x02070000 + ptr = PyCapsule_GetPointer(ob, 0); +#else + ptr = PyCObject_AsVoidPtr(ob); +#endif + if (!ptr && !PyErr_Occurred()) + PyErr_SetString(PyExc_RuntimeError, "invalid vtable found for imported type"); + Py_DECREF(ob); + return ptr; +bad: + Py_XDECREF(ob); + return NULL; +} + +/* CLineInTraceback */ +#ifndef CYTHON_CLINE_IN_TRACEBACK +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { + PyObject *use_cline; + PyObject *ptype, *pvalue, *ptraceback; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject **cython_runtime_dict; +#endif + if (unlikely(!__pyx_cython_runtime)) { + return c_line; + } + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); +#if CYTHON_COMPILING_IN_CPYTHON + cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); + if (likely(cython_runtime_dict)) { + __PYX_PY_DICT_LOOKUP_IF_MODIFIED( + use_cline, *cython_runtime_dict, + __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) + } else +#endif + { + PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); + if (use_cline_obj) { + use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; + Py_DECREF(use_cline_obj); + } else { + PyErr_Clear(); + use_cline = NULL; + } + } + if (!use_cline) { + c_line = 0; + PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); + } + else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { + c_line = 0; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + return c_line; +} +#endif + +/* CodeObjectCache */ +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = start + (end - start) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +/* AddTraceback */ +#include "compile.h" +#include "frameobject.h" +#include "traceback.h" +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyObject *py_srcfile = 0; + PyObject *py_funcname = 0; + #if PY_MAJOR_VERSION < 3 + py_srcfile = PyString_FromString(filename); + #else + py_srcfile = PyUnicode_FromString(filename); + #endif + if (!py_srcfile) goto bad; + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + #else + py_funcname = PyUnicode_FromString(funcname); + #endif + } + if (!py_funcname) goto bad; + py_code = __Pyx_PyCode_New( + 0, + 0, + 0, + 0, + 0, + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + Py_DECREF(py_funcname); + return py_code; +bad: + Py_XDECREF(py_srcfile); + Py_XDECREF(py_funcname); + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + if (c_line) { + c_line = __Pyx_CLineForTraceback(tstate, c_line); + } + py_code = __pyx_find_code_object(c_line ? -c_line : py_line); + if (!py_code) { + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) goto bad; + __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); + } + py_frame = PyFrame_New( + tstate, /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + __pyx_d, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + __Pyx_PyFrame_SetLineNumber(py_frame, py_line); + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +/* CIntFromPyVerify */ +#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ + } + +/* None */ +static CYTHON_INLINE int __Pyx_ErrOccurredWithGIL(void) { + int err; + #ifdef WITH_THREAD + PyGILState_STATE _save = PyGILState_Ensure(); + #endif + err = !!PyErr_Occurred(); + #ifdef WITH_THREAD + PyGILState_Release(_save); + #endif + return err; +} + +/* Declarations */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabsf(b.real) >= fabsf(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + float r = b.imag / b.real; + float s = (float)(1.0) / (b.real + b.imag * r); + return __pyx_t_float_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + float r = b.real / b.imag; + float s = (float)(1.0) / (b.imag + b.real * r); + return __pyx_t_float_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + float denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_float_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_float(a, a); + case 3: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, a); + case 4: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = powf(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2f(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_float(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +/* Declarations */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabs(b.real) >= fabs(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + double r = b.imag / b.real; + double s = (double)(1.0) / (b.real + b.imag * r); + return __pyx_t_double_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + double r = b.real / b.imag; + double s = (double)(1.0) / (b.imag + b.real * r); + return __pyx_t_double_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + double denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_double_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_double(a, a); + case 3: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, a); + case 4: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = pow(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_double(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { + if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); + if (__Pyx_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); + if (__Pyx_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); + PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); + return -1; +} +static void __Pyx_ReleaseBuffer(Py_buffer *view) { + PyObject *obj = view->obj; + if (!obj) return; + if (PyObject_CheckBuffer(obj)) { + PyBuffer_Release(view); + return; + } + if ((0)) {} + view->obj = NULL; + Py_DECREF(obj); +} +#endif + + +/* MemviewSliceIsContig */ +static int +__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) +{ + int i, index, step, start; + Py_ssize_t itemsize = mvs.memview->view.itemsize; + if (order == 'F') { + step = 1; + start = 0; + } else { + step = -1; + start = ndim - 1; + } + for (i = 0; i < ndim; i++) { + index = start + step * i; + if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) + return 0; + itemsize *= mvs.shape[index]; + } + return 1; +} + +/* OverlappingSlices */ +static void +__pyx_get_array_memory_extents(__Pyx_memviewslice *slice, + void **out_start, void **out_end, + int ndim, size_t itemsize) +{ + char *start, *end; + int i; + start = end = slice->data; + for (i = 0; i < ndim; i++) { + Py_ssize_t stride = slice->strides[i]; + Py_ssize_t extent = slice->shape[i]; + if (extent == 0) { + *out_start = *out_end = start; + return; + } else { + if (stride > 0) + end += stride * (extent - 1); + else + start += stride * (extent - 1); + } + } + *out_start = start; + *out_end = end + itemsize; +} +static int +__pyx_slices_overlap(__Pyx_memviewslice *slice1, + __Pyx_memviewslice *slice2, + int ndim, size_t itemsize) +{ + void *start1, *end1, *start2, *end2; + __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); + __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); + return (start1 < end2) && (start2 < end1); +} + +/* Capsule */ +static CYTHON_INLINE PyObject * +__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) +{ + PyObject *cobj; +#if PY_VERSION_HEX >= 0x02070000 + cobj = PyCapsule_New(p, sig, NULL); +#else + cobj = PyCObject_FromVoidPtr(p, NULL); +#endif + return cobj; +} + +/* CIntFromPy */ +static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(Py_intptr_t) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (Py_intptr_t) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (Py_intptr_t) 0; + case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, digits[0]) + case 2: + if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 2 * PyLong_SHIFT) { + return (Py_intptr_t) (((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 3 * PyLong_SHIFT) { + return (Py_intptr_t) (((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) >= 4 * PyLong_SHIFT) { + return (Py_intptr_t) (((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (Py_intptr_t) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (Py_intptr_t) 0; + case -1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(Py_intptr_t, digit, +digits[0]) + case -2: + if (8 * sizeof(Py_intptr_t) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(Py_intptr_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(Py_intptr_t) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(Py_intptr_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((((Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(Py_intptr_t) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { + return (Py_intptr_t) (((Py_intptr_t)-1)*(((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(Py_intptr_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(Py_intptr_t) - 1 > 4 * PyLong_SHIFT) { + return (Py_intptr_t) ((((((((((Py_intptr_t)digits[3]) << PyLong_SHIFT) | (Py_intptr_t)digits[2]) << PyLong_SHIFT) | (Py_intptr_t)digits[1]) << PyLong_SHIFT) | (Py_intptr_t)digits[0]))); + } + } + break; + } +#endif + if (sizeof(Py_intptr_t) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(Py_intptr_t, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + Py_intptr_t val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (Py_intptr_t) -1; + } + } else { + Py_intptr_t val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (Py_intptr_t) -1; + val = __Pyx_PyInt_As_Py_intptr_t(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to Py_intptr_t"); + return (Py_intptr_t) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to Py_intptr_t"); + return (Py_intptr_t) -1; +} + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = (Py_intptr_t) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(Py_intptr_t) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(Py_intptr_t) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(Py_intptr_t) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(Py_intptr_t), + little, !is_unsigned); + } +} + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(long) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(long) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(long) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(long), + little, !is_unsigned); + } +} + +/* MemviewSliceCopyTemplate */ +static __Pyx_memviewslice +__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, + const char *mode, int ndim, + size_t sizeof_dtype, int contig_flag, + int dtype_is_object) +{ + __Pyx_RefNannyDeclarations + int i; + __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; + struct __pyx_memoryview_obj *from_memview = from_mvs->memview; + Py_buffer *buf = &from_memview->view; + PyObject *shape_tuple = NULL; + PyObject *temp_int = NULL; + struct __pyx_array_obj *array_obj = NULL; + struct __pyx_memoryview_obj *memview_obj = NULL; + __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); + for (i = 0; i < ndim; i++) { + if (unlikely(from_mvs->suboffsets[i] >= 0)) { + PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " + "indirect dimensions (axis %d)", i); + goto fail; + } + } + shape_tuple = PyTuple_New(ndim); + if (unlikely(!shape_tuple)) { + goto fail; + } + __Pyx_GOTREF(shape_tuple); + for(i = 0; i < ndim; i++) { + temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); + if(unlikely(!temp_int)) { + goto fail; + } else { + PyTuple_SET_ITEM(shape_tuple, i, temp_int); + temp_int = NULL; + } + } + array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); + if (unlikely(!array_obj)) { + goto fail; + } + __Pyx_GOTREF(array_obj); + memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( + (PyObject *) array_obj, contig_flag, + dtype_is_object, + from_mvs->memview->typeinfo); + if (unlikely(!memview_obj)) + goto fail; + if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) + goto fail; + if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, + dtype_is_object) < 0)) + goto fail; + goto no_fail; +fail: + __Pyx_XDECREF(new_mvs.memview); + new_mvs.memview = NULL; + new_mvs.data = NULL; +no_fail: + __Pyx_XDECREF(shape_tuple); + __Pyx_XDECREF(temp_int); + __Pyx_XDECREF(array_obj); + __Pyx_RefNannyFinishContext(); + return new_mvs; +} + +/* MemviewSliceInit */ +static int +__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, + int ndim, + __Pyx_memviewslice *memviewslice, + int memview_is_new_reference) +{ + __Pyx_RefNannyDeclarations + int i, retval=-1; + Py_buffer *buf = &memview->view; + __Pyx_RefNannySetupContext("init_memviewslice", 0); + if (unlikely(memviewslice->memview || memviewslice->data)) { + PyErr_SetString(PyExc_ValueError, + "memviewslice is already initialized!"); + goto fail; + } + if (buf->strides) { + for (i = 0; i < ndim; i++) { + memviewslice->strides[i] = buf->strides[i]; + } + } else { + Py_ssize_t stride = buf->itemsize; + for (i = ndim - 1; i >= 0; i--) { + memviewslice->strides[i] = stride; + stride *= buf->shape[i]; + } + } + for (i = 0; i < ndim; i++) { + memviewslice->shape[i] = buf->shape[i]; + if (buf->suboffsets) { + memviewslice->suboffsets[i] = buf->suboffsets[i]; + } else { + memviewslice->suboffsets[i] = -1; + } + } + memviewslice->memview = memview; + memviewslice->data = (char *)buf->buf; + if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { + Py_INCREF(memview); + } + retval = 0; + goto no_fail; +fail: + memviewslice->memview = 0; + memviewslice->data = 0; + retval = -1; +no_fail: + __Pyx_RefNannyFinishContext(); + return retval; +} +#ifndef Py_NO_RETURN +#define Py_NO_RETURN +#endif +static void __pyx_fatalerror(const char *fmt, ...) Py_NO_RETURN { + va_list vargs; + char msg[200]; +#ifdef HAVE_STDARG_PROTOTYPES + va_start(vargs, fmt); +#else + va_start(vargs); +#endif + vsnprintf(msg, 200, fmt, vargs); + va_end(vargs); + Py_FatalError(msg); +} +static CYTHON_INLINE int +__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)++; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE int +__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, + PyThread_type_lock lock) +{ + int result; + PyThread_acquire_lock(lock, 1); + result = (*acquisition_count)--; + PyThread_release_lock(lock); + return result; +} +static CYTHON_INLINE void +__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) +{ + int first_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (unlikely(!memview || (PyObject *) memview == Py_None)) + return; + if (unlikely(__pyx_get_slice_count(memview) < 0)) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + first_time = __pyx_add_acquisition_count(memview) == 0; + if (unlikely(first_time)) { + if (have_gil) { + Py_INCREF((PyObject *) memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_INCREF((PyObject *) memview); + PyGILState_Release(_gilstate); + } + } +} +static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, + int have_gil, int lineno) { + int last_time; + struct __pyx_memoryview_obj *memview = memslice->memview; + if (unlikely(!memview || (PyObject *) memview == Py_None)) { + memslice->memview = NULL; + return; + } + if (unlikely(__pyx_get_slice_count(memview) <= 0)) + __pyx_fatalerror("Acquisition count is %d (line %d)", + __pyx_get_slice_count(memview), lineno); + last_time = __pyx_sub_acquisition_count(memview) == 1; + memslice->data = NULL; + if (unlikely(last_time)) { + if (have_gil) { + Py_CLEAR(memslice->memview); + } else { + PyGILState_STATE _gilstate = PyGILState_Ensure(); + Py_CLEAR(memslice->memview); + PyGILState_Release(_gilstate); + } + } else { + memslice->memview = NULL; + } +} + +/* CIntFromPy */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + } +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +/* CIntFromPy */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(long) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (long) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(long) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + } +#endif + if (sizeof(long) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + long val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (long) -1; + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (long) -1; + val = __Pyx_PyInt_As_long(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to long"); + return (long) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long) -1; +} + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(int) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(int) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(int) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(int), + little, !is_unsigned); + } +} + +/* CIntFromPy */ +static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const char neg_one = (char) -1, const_zero = (char) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(char) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (char) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (char) 0; + case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { + return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { + return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { + return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (char) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(char) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (char) 0; + case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) + case -2: + if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(char) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(char) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(char) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { + return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); + } + } + break; + } +#endif + if (sizeof(char) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + char val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (char) -1; + } + } else { + char val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (char) -1; + val = __Pyx_PyInt_As_char(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to char"); + return (char) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to char"); + return (char) -1; +} + +/* CheckBinaryVersion */ +static int __Pyx_check_binary_version(void) { + char ctversion[4], rtversion[4]; + PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); + PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); + if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { + char message[200]; + PyOS_snprintf(message, sizeof(message), + "compiletime version %s of module '%.100s' " + "does not match runtime version %s", + ctversion, __Pyx_MODULE_NAME, rtversion); + return PyErr_WarnEx(NULL, message, 1); + } + return 0; +} + +/* FunctionExport */ +static int __Pyx_ExportFunction(const char *name, void (*f)(void), const char *sig) { + PyObject *d = 0; + PyObject *cobj = 0; + union { + void (*fp)(void); + void *p; + } tmp; + d = PyObject_GetAttrString(__pyx_m, (char *)"__pyx_capi__"); + if (!d) { + PyErr_Clear(); + d = PyDict_New(); + if (!d) + goto bad; + Py_INCREF(d); + if (PyModule_AddObject(__pyx_m, (char *)"__pyx_capi__", d) < 0) + goto bad; + } + tmp.fp = f; +#if PY_VERSION_HEX >= 0x02070000 + cobj = PyCapsule_New(tmp.p, sig, 0); +#else + cobj = PyCObject_FromVoidPtrAndDesc(tmp.p, (void *)sig, 0); +#endif + if (!cobj) + goto bad; + if (PyDict_SetItemString(d, name, cobj) < 0) + goto bad; + Py_DECREF(cobj); + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(cobj); + Py_XDECREF(d); + return -1; +} + +/* VoidPtrImport */ +#ifndef __PYX_HAVE_RT_ImportVoidPtr +#define __PYX_HAVE_RT_ImportVoidPtr +static int __Pyx_ImportVoidPtr(PyObject *module, const char *name, void **p, const char *sig) { + PyObject *d = 0; + PyObject *cobj = 0; + d = PyObject_GetAttrString(module, (char *)"__pyx_capi__"); + if (!d) + goto bad; + cobj = PyDict_GetItemString(d, name); + if (!cobj) { + PyErr_Format(PyExc_ImportError, + "%.200s does not export expected C variable %.200s", + PyModule_GetName(module), name); + goto bad; + } +#if PY_VERSION_HEX >= 0x02070000 + if (!PyCapsule_IsValid(cobj, sig)) { + PyErr_Format(PyExc_TypeError, + "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), name, sig, PyCapsule_GetName(cobj)); + goto bad; + } + *p = PyCapsule_GetPointer(cobj, sig); +#else + {const char *desc, *s1, *s2; + desc = (const char *)PyCObject_GetDesc(cobj); + if (!desc) + goto bad; + s1 = desc; s2 = sig; + while (*s1 != '\0' && *s1 == *s2) { s1++; s2++; } + if (*s1 != *s2) { + PyErr_Format(PyExc_TypeError, + "C variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)", + PyModule_GetName(module), name, sig, desc); + goto bad; + } + *p = PyCObject_AsVoidPtr(cobj);} +#endif + if (!(*p)) + goto bad; + Py_DECREF(d); + return 0; +bad: + Py_XDECREF(d); + return -1; +} +#endif + +/* InitStrings */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + if (PyObject_Hash(*t->p) == -1) + return -1; + ++t; + } + return 0; +} + +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { + return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); +} +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { + Py_ssize_t ignore; + return __Pyx_PyObject_AsStringAndSize(o, &ignore); +} +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if !CYTHON_PEP393_ENABLED +static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + char* defenc_c; + PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); + if (!defenc) return NULL; + defenc_c = PyBytes_AS_STRING(defenc); +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + { + char* end = defenc_c + PyBytes_GET_SIZE(defenc); + char* c; + for (c = defenc_c; c < end; c++) { + if ((unsigned char) (*c) >= 128) { + PyUnicode_AsASCIIString(o); + return NULL; + } + } + } +#endif + *length = PyBytes_GET_SIZE(defenc); + return defenc_c; +} +#else +static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + if (likely(PyUnicode_IS_ASCII(o))) { + *length = PyUnicode_GET_LENGTH(o); + return PyUnicode_AsUTF8(o); + } else { + PyUnicode_AsASCIIString(o); + return NULL; + } +#else + return PyUnicode_AsUTF8AndSize(o, length); +#endif +} +#endif +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT + if ( +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + __Pyx_sys_getdefaultencoding_not_ascii && +#endif + PyUnicode_Check(o)) { + return __Pyx_PyUnicode_AsStringAndSize(o, length); + } else +#endif +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) + if (PyByteArray_Check(o)) { + *length = PyByteArray_GET_SIZE(o); + return PyByteArray_AS_STRING(o); + } else +#endif + { + char* result; + int r = PyBytes_AsStringAndSize(o, &result, length); + if (unlikely(r < 0)) { + return NULL; + } else { + return result; + } + } +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { + int retval; + if (unlikely(!x)) return -1; + retval = __Pyx_PyObject_IsTrue(x); + Py_DECREF(x); + return retval; +} +static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { +#if PY_MAJOR_VERSION >= 3 + if (PyLong_Check(result)) { + if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, + "__int__ returned non-int (type %.200s). " + "The ability to return an instance of a strict subclass of int " + "is deprecated, and may be removed in a future version of Python.", + Py_TYPE(result)->tp_name)) { + Py_DECREF(result); + return NULL; + } + return result; + } +#endif + PyErr_Format(PyExc_TypeError, + "__%.4s__ returned non-%.4s (type %.200s)", + type_name, type_name, Py_TYPE(result)->tp_name); + Py_DECREF(result); + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { +#if CYTHON_USE_TYPE_SLOTS + PyNumberMethods *m; +#endif + const char *name = NULL; + PyObject *res = NULL; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x) || PyLong_Check(x))) +#else + if (likely(PyLong_Check(x))) +#endif + return __Pyx_NewRef(x); +#if CYTHON_USE_TYPE_SLOTS + m = Py_TYPE(x)->tp_as_number; + #if PY_MAJOR_VERSION < 3 + if (m && m->nb_int) { + name = "int"; + res = m->nb_int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = m->nb_long(x); + } + #else + if (likely(m && m->nb_int)) { + name = "int"; + res = m->nb_int(x); + } + #endif +#else + if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { + res = PyNumber_Int(x); + } +#endif + if (likely(res)) { +#if PY_MAJOR_VERSION < 3 + if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { +#else + if (unlikely(!PyLong_CheckExact(res))) { +#endif + return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject *x; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(b); + } +#endif + if (likely(PyLong_CheckExact(b))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + } + } + #endif + return PyLong_AsSsize_t(b); + } + x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { + return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); +} +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { + return PyInt_FromSize_t(ival); +} + + +#endif /* Py_PYTHON_H */ diff --git a/stpredictions/models/OK3/_utils.pxd b/stpredictions/models/OK3/_utils.pxd new file mode 100644 index 000000000..731e43afe --- /dev/null +++ b/stpredictions/models/OK3/_utils.pxd @@ -0,0 +1,170 @@ +# Authors: Gilles Louppe +# Peter Prettenhofer +# Arnaud Joly +# Jacob Schreiber +# Nelson Liu +# +# License: BSD 3 clause + +# See _utils.pyx for details. + +import numpy as np +cimport numpy as np +from ._tree cimport Node +from ._quad_tree cimport Cell + +ctypedef np.npy_float32 DTYPE_t # Type of X +ctypedef np.npy_float64 DOUBLE_t # Type of y, sample_weight +ctypedef np.npy_intp SIZE_t # Type for indices and counters +ctypedef np.npy_int32 INT32_t # Signed 32 bit integer +ctypedef np.npy_uint32 UINT32_t # Unsigned 32 bit integer + + +cdef enum: + # Max value for our rand_r replacement (near the bottom). + # We don't use RAND_MAX because it's different across platforms and + # particularly tiny on Windows/MSVC. + RAND_R_MAX = 0x7FFFFFFF + + +# safe_realloc(&p, n) resizes the allocation of p to n * sizeof(*p) bytes or +# raises a MemoryError. It never calls free, since that's __dealloc__'s job. +# cdef DTYPE_t *p = NULL +# safe_realloc(&p, n) +# is equivalent to p = malloc(n * sizeof(*p)) with error checking. +ctypedef fused realloc_ptr: + # Add pointer types here as needed. + (DTYPE_t*) + (SIZE_t*) + (unsigned char*) + (WeightedPQueueRecord*) + (DOUBLE_t*) + (DOUBLE_t**) + (Node*) + (Cell*) + (Node**) + (StackRecord*) + (PriorityHeapRecord*) + +cdef realloc_ptr safe_realloc(realloc_ptr* p, size_t nelems) nogil except * + + +cdef np.ndarray sizet_ptr_to_ndarray(SIZE_t* data, SIZE_t size) + + +cdef SIZE_t rand_int(SIZE_t low, SIZE_t high, + UINT32_t* random_state) nogil + + +cdef double rand_uniform(double low, double high, + UINT32_t* random_state) nogil + + +cdef double log(double x) nogil + +# ============================================================================= +# Stack data structure +# ============================================================================= + +# A record on the stack for depth-first tree growing +cdef struct StackRecord: + SIZE_t start + SIZE_t end + SIZE_t depth + SIZE_t parent + bint is_left + double impurity + SIZE_t n_constant_features + +cdef class Stack: + cdef SIZE_t capacity + cdef SIZE_t top + cdef StackRecord* stack_ + + cdef bint is_empty(self) nogil + cdef int push(self, SIZE_t start, SIZE_t end, SIZE_t depth, SIZE_t parent, + bint is_left, double impurity, + SIZE_t n_constant_features) nogil except -1 + cdef int pop(self, StackRecord* res) nogil + + +# ============================================================================= +# PriorityHeap data structure +# ============================================================================= + +# A record on the frontier for best-first tree growing +cdef struct PriorityHeapRecord: + SIZE_t node_id + SIZE_t start + SIZE_t end + SIZE_t pos + SIZE_t depth + bint is_leaf + double impurity + double impurity_left + double impurity_right + double improvement + +cdef class PriorityHeap: + cdef SIZE_t capacity + cdef SIZE_t heap_ptr + cdef PriorityHeapRecord* heap_ + + cdef bint is_empty(self) nogil + cdef void heapify_up(self, PriorityHeapRecord* heap, SIZE_t pos) nogil + cdef void heapify_down(self, PriorityHeapRecord* heap, SIZE_t pos, SIZE_t heap_length) nogil + cdef int push(self, SIZE_t node_id, SIZE_t start, SIZE_t end, SIZE_t pos, + SIZE_t depth, bint is_leaf, double improvement, + double impurity, double impurity_left, + double impurity_right) nogil except -1 + cdef int pop(self, PriorityHeapRecord* res) nogil + +# ============================================================================= +# WeightedPQueue data structure +# ============================================================================= + +# A record stored in the WeightedPQueue +cdef struct WeightedPQueueRecord: + DOUBLE_t data + DOUBLE_t weight + +cdef class WeightedPQueue: + cdef SIZE_t capacity + cdef SIZE_t array_ptr + cdef WeightedPQueueRecord* array_ + + cdef bint is_empty(self) nogil + cdef int reset(self) nogil except -1 + cdef SIZE_t size(self) nogil + cdef int push(self, DOUBLE_t data, DOUBLE_t weight) nogil except -1 + cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) nogil + cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil + cdef int peek(self, DOUBLE_t* data, DOUBLE_t* weight) nogil + cdef DOUBLE_t get_weight_from_index(self, SIZE_t index) nogil + cdef DOUBLE_t get_value_from_index(self, SIZE_t index) nogil + + +# ============================================================================= +# WeightedMedianCalculator data structure +# ============================================================================= + +cdef class WeightedMedianCalculator: + cdef SIZE_t initial_capacity + cdef WeightedPQueue samples + cdef DOUBLE_t total_weight + cdef SIZE_t k + cdef DOUBLE_t sum_w_0_k # represents sum(weights[0:k]) + # = w[0] + w[1] + ... + w[k-1] + + cdef SIZE_t size(self) nogil + cdef int push(self, DOUBLE_t data, DOUBLE_t weight) nogil except -1 + cdef int reset(self) nogil except -1 + cdef int update_median_parameters_post_push( + self, DOUBLE_t data, DOUBLE_t weight, + DOUBLE_t original_median) nogil + cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) nogil + cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil + cdef int update_median_parameters_post_remove( + self, DOUBLE_t data, DOUBLE_t weight, + DOUBLE_t original_median) nogil + cdef DOUBLE_t get_median(self) nogil \ No newline at end of file diff --git a/stpredictions/models/OK3/_utils.pyx b/stpredictions/models/OK3/_utils.pyx new file mode 100644 index 000000000..21230b240 --- /dev/null +++ b/stpredictions/models/OK3/_utils.pyx @@ -0,0 +1,660 @@ +# cython: cdivision=True +# cython: boundscheck=False +# cython: wraparound=False + +# Authors: Gilles Louppe +# Peter Prettenhofer +# Arnaud Joly +# Jacob Schreiber +# Nelson Liu +# +# +# License: BSD 3 clause + +from libc.stdlib cimport free +from libc.stdlib cimport malloc +from libc.stdlib cimport realloc +from libc.math cimport log as ln + +import numpy as np +cimport numpy as np +np.import_array() + +from ._random cimport our_rand_r + +# ============================================================================= +# Helper functions +# ============================================================================= + +cdef realloc_ptr safe_realloc(realloc_ptr* p, size_t nelems) nogil except *: + # sizeof(realloc_ptr[0]) would be more like idiomatic C, but causes Cython + # 0.20.1 to crash. + cdef size_t nbytes = nelems * sizeof(p[0][0]) + if nbytes / sizeof(p[0][0]) != nelems: + # Overflow in the multiplication + with gil: + raise MemoryError("could not allocate (%d * %d) bytes" + % (nelems, sizeof(p[0][0]))) + cdef realloc_ptr tmp = realloc(p[0], nbytes) + if tmp == NULL: + with gil: + raise MemoryError("could not allocate %d bytes" % nbytes) + + p[0] = tmp + return tmp # for convenience + + +def _realloc_test(): + # Helper for tests. Tries to allocate (-1) / 2 * sizeof(size_t) + # bytes, which will always overflow. + cdef SIZE_t* p = NULL + safe_realloc(&p, (-1) / 2) + if p != NULL: + free(p) + assert False + + +cdef inline np.ndarray sizet_ptr_to_ndarray(SIZE_t* data, SIZE_t size): + """Return copied data as 1D numpy array of intp's.""" + cdef np.npy_intp shape[1] + shape[0] = size + return np.PyArray_SimpleNewFromData(1, shape, np.NPY_INTP, data).copy() + + +cdef inline SIZE_t rand_int(SIZE_t low, SIZE_t high, + UINT32_t* random_state) nogil: + """Generate a random integer in [low; end).""" + return low + our_rand_r(random_state) % (high - low) + + +cdef inline double rand_uniform(double low, double high, + UINT32_t* random_state) nogil: + """Generate a random double in [low; high).""" + return ((high - low) * our_rand_r(random_state) / + RAND_R_MAX) + low + + +cdef inline double log(double x) nogil: + return ln(x) / ln(2.0) + + +# ============================================================================= +# Stack data structure +# ============================================================================= + +cdef class Stack: + """A LIFO data structure. + + Attributes + ---------- + capacity : SIZE_t + The elements the stack can hold; if more added then ``self.stack_`` + needs to be resized. + + top : SIZE_t + The number of elements currently on the stack. + + stack : StackRecord pointer + The stack of records (upward in the stack corresponds to the right). + """ + + def __cinit__(self, SIZE_t capacity): + self.capacity = capacity + self.top = 0 + self.stack_ = malloc(capacity * sizeof(StackRecord)) + + def __dealloc__(self): + free(self.stack_) + + cdef bint is_empty(self) nogil: + return self.top <= 0 + + cdef int push(self, SIZE_t start, SIZE_t end, SIZE_t depth, SIZE_t parent, + bint is_left, double impurity, + SIZE_t n_constant_features) nogil except -1: + """Push a new element onto the stack. + + Return -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + cdef SIZE_t top = self.top + cdef StackRecord* stack = NULL + + # Resize if capacity not sufficient + if top >= self.capacity: + self.capacity *= 2 + # Since safe_realloc can raise MemoryError, use `except -1` + safe_realloc(&self.stack_, self.capacity) + + stack = self.stack_ + stack[top].start = start + stack[top].end = end + stack[top].depth = depth + stack[top].parent = parent + stack[top].is_left = is_left + stack[top].impurity = impurity + stack[top].n_constant_features = n_constant_features + + # Increment stack pointer + self.top = top + 1 + return 0 + + cdef int pop(self, StackRecord* res) nogil: + """Remove the top element from the stack and copy to ``res``. + + Returns 0 if pop was successful (and ``res`` is set); -1 + otherwise. + """ + cdef SIZE_t top = self.top + cdef StackRecord* stack = self.stack_ + + if top <= 0: + return -1 + + res[0] = stack[top - 1] + self.top = top - 1 + + return 0 + + +# ============================================================================= +# PriorityHeap data structure +# ============================================================================= + +cdef class PriorityHeap: + """A priority queue implemented as a binary heap. + + The heap invariant is that the impurity improvement of the parent record + is larger then the impurity improvement of the children. + + Attributes + ---------- + capacity : SIZE_t + The capacity of the heap + + heap_ptr : SIZE_t + The water mark of the heap; the heap grows from left to right in the + array ``heap_``. The following invariant holds ``heap_ptr < capacity``. + + heap_ : PriorityHeapRecord* + The array of heap records. The maximum element is on the left; + the heap grows from left to right + """ + + def __cinit__(self, SIZE_t capacity): + self.capacity = capacity + self.heap_ptr = 0 + safe_realloc(&self.heap_, capacity) + + def __dealloc__(self): + free(self.heap_) + + cdef bint is_empty(self) nogil: + return self.heap_ptr <= 0 + + cdef void heapify_up(self, PriorityHeapRecord* heap, SIZE_t pos) nogil: + """Restore heap invariant parent.improvement > child.improvement from + ``pos`` upwards. """ + if pos == 0: + return + + cdef SIZE_t parent_pos = (pos - 1) / 2 + + if heap[parent_pos].improvement < heap[pos].improvement: + heap[parent_pos], heap[pos] = heap[pos], heap[parent_pos] + self.heapify_up(heap, parent_pos) + + cdef void heapify_down(self, PriorityHeapRecord* heap, SIZE_t pos, + SIZE_t heap_length) nogil: + """Restore heap invariant parent.improvement > children.improvement from + ``pos`` downwards. """ + cdef SIZE_t left_pos = 2 * (pos + 1) - 1 + cdef SIZE_t right_pos = 2 * (pos + 1) + cdef SIZE_t largest = pos + + if (left_pos < heap_length and + heap[left_pos].improvement > heap[largest].improvement): + largest = left_pos + + if (right_pos < heap_length and + heap[right_pos].improvement > heap[largest].improvement): + largest = right_pos + + if largest != pos: + heap[pos], heap[largest] = heap[largest], heap[pos] + self.heapify_down(heap, largest, heap_length) + + cdef int push(self, SIZE_t node_id, SIZE_t start, SIZE_t end, SIZE_t pos, + SIZE_t depth, bint is_leaf, double improvement, + double impurity, double impurity_left, + double impurity_right) nogil except -1: + """Push record on the priority heap. + + Return -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + cdef SIZE_t heap_ptr = self.heap_ptr + cdef PriorityHeapRecord* heap = NULL + + # Resize if capacity not sufficient + if heap_ptr >= self.capacity: + self.capacity *= 2 + # Since safe_realloc can raise MemoryError, use `except -1` + safe_realloc(&self.heap_, self.capacity) + + # Put element as last element of heap + heap = self.heap_ + heap[heap_ptr].node_id = node_id + heap[heap_ptr].start = start + heap[heap_ptr].end = end + heap[heap_ptr].pos = pos + heap[heap_ptr].depth = depth + heap[heap_ptr].is_leaf = is_leaf + heap[heap_ptr].impurity = impurity + heap[heap_ptr].impurity_left = impurity_left + heap[heap_ptr].impurity_right = impurity_right + heap[heap_ptr].improvement = improvement + + # Heapify up + self.heapify_up(heap, heap_ptr) + + # Increase element count + self.heap_ptr = heap_ptr + 1 + return 0 + + cdef int pop(self, PriorityHeapRecord* res) nogil: + """Remove max element from the heap. """ + cdef SIZE_t heap_ptr = self.heap_ptr + cdef PriorityHeapRecord* heap = self.heap_ + + if heap_ptr <= 0: + return -1 + + # Take first element + res[0] = heap[0] + + # Put last element to the front + heap[0], heap[heap_ptr - 1] = heap[heap_ptr - 1], heap[0] + + # Restore heap invariant + if heap_ptr > 1: + self.heapify_down(heap, 0, heap_ptr - 1) + + self.heap_ptr = heap_ptr - 1 + + return 0 + +# ============================================================================= +# WeightedPQueue data structure +# ============================================================================= + +cdef class WeightedPQueue: + """A priority queue class, always sorted in increasing order. + + Attributes + ---------- + capacity : SIZE_t + The capacity of the priority queue. + + array_ptr : SIZE_t + The water mark of the priority queue; the priority queue grows from + left to right in the array ``array_``. ``array_ptr`` is always + less than ``capacity``. + + array_ : WeightedPQueueRecord* + The array of priority queue records. The minimum element is on the + left at index 0, and the maximum element is on the right at index + ``array_ptr-1``. + """ + + def __cinit__(self, SIZE_t capacity): + self.capacity = capacity + self.array_ptr = 0 + safe_realloc(&self.array_, capacity) + + def __dealloc__(self): + free(self.array_) + + cdef int reset(self) nogil except -1: + """Reset the WeightedPQueue to its state at construction + + Return -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + self.array_ptr = 0 + # Since safe_realloc can raise MemoryError, use `except *` + safe_realloc(&self.array_, self.capacity) + return 0 + + cdef bint is_empty(self) nogil: + return self.array_ptr <= 0 + + cdef SIZE_t size(self) nogil: + return self.array_ptr + + cdef int push(self, DOUBLE_t data, DOUBLE_t weight) nogil except -1: + """Push record on the array. + + Return -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + cdef SIZE_t array_ptr = self.array_ptr + cdef WeightedPQueueRecord* array = NULL + cdef SIZE_t i + + # Resize if capacity not sufficient + if array_ptr >= self.capacity: + self.capacity *= 2 + # Since safe_realloc can raise MemoryError, use `except -1` + safe_realloc(&self.array_, self.capacity) + + # Put element as last element of array + array = self.array_ + array[array_ptr].data = data + array[array_ptr].weight = weight + + # bubble last element up according until it is sorted + # in ascending order + i = array_ptr + while(i != 0 and array[i].data < array[i-1].data): + array[i], array[i-1] = array[i-1], array[i] + i -= 1 + + # Increase element count + self.array_ptr = array_ptr + 1 + return 0 + + cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) nogil: + """Remove a specific value/weight record from the array. + Returns 0 if successful, -1 if record not found.""" + cdef SIZE_t array_ptr = self.array_ptr + cdef WeightedPQueueRecord* array = self.array_ + cdef SIZE_t idx_to_remove = -1 + cdef SIZE_t i + + if array_ptr <= 0: + return -1 + + # find element to remove + for i in range(array_ptr): + if array[i].data == data and array[i].weight == weight: + idx_to_remove = i + break + + if idx_to_remove == -1: + return -1 + + # shift the elements after the removed element + # to the left. + for i in range(idx_to_remove, array_ptr-1): + array[i] = array[i+1] + + self.array_ptr = array_ptr - 1 + return 0 + + cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil: + """Remove the top (minimum) element from array. + Returns 0 if successful, -1 if nothing to remove.""" + cdef SIZE_t array_ptr = self.array_ptr + cdef WeightedPQueueRecord* array = self.array_ + cdef SIZE_t i + + if array_ptr <= 0: + return -1 + + data[0] = array[0].data + weight[0] = array[0].weight + + # shift the elements after the removed element + # to the left. + for i in range(0, array_ptr-1): + array[i] = array[i+1] + + self.array_ptr = array_ptr - 1 + return 0 + + cdef int peek(self, DOUBLE_t* data, DOUBLE_t* weight) nogil: + """Write the top element from array to a pointer. + Returns 0 if successful, -1 if nothing to write.""" + cdef WeightedPQueueRecord* array = self.array_ + if self.array_ptr <= 0: + return -1 + # Take first value + data[0] = array[0].data + weight[0] = array[0].weight + return 0 + + cdef DOUBLE_t get_weight_from_index(self, SIZE_t index) nogil: + """Given an index between [0,self.current_capacity], access + the appropriate heap and return the requested weight""" + cdef WeightedPQueueRecord* array = self.array_ + + # get weight at index + return array[index].weight + + cdef DOUBLE_t get_value_from_index(self, SIZE_t index) nogil: + """Given an index between [0,self.current_capacity], access + the appropriate heap and return the requested value""" + cdef WeightedPQueueRecord* array = self.array_ + + # get value at index + return array[index].data + +# ============================================================================= +# WeightedMedianCalculator data structure +# ============================================================================= + +cdef class WeightedMedianCalculator: + """A class to handle calculation of the weighted median from streams of + data. To do so, it maintains a parameter ``k`` such that the sum of the + weights in the range [0,k) is greater than or equal to half of the total + weight. By minimizing the value of ``k`` that fulfills this constraint, + calculating the median is done by either taking the value of the sample + at index ``k-1`` of ``samples`` (samples[k-1].data) or the average of + the samples at index ``k-1`` and ``k`` of ``samples`` + ((samples[k-1] + samples[k]) / 2). + + Attributes + ---------- + initial_capacity : SIZE_t + The initial capacity of the WeightedMedianCalculator. + + samples : WeightedPQueue + Holds the samples (consisting of values and their weights) used in the + weighted median calculation. + + total_weight : DOUBLE_t + The sum of the weights of items in ``samples``. Represents the total + weight of all samples used in the median calculation. + + k : SIZE_t + Index used to calculate the median. + + sum_w_0_k : DOUBLE_t + The sum of the weights from samples[0:k]. Used in the weighted + median calculation; minimizing the value of ``k`` such that + ``sum_w_0_k`` >= ``total_weight / 2`` provides a mechanism for + calculating the median in constant time. + + """ + + def __cinit__(self, SIZE_t initial_capacity): + self.initial_capacity = initial_capacity + self.samples = WeightedPQueue(initial_capacity) + self.total_weight = 0 + self.k = 0 + self.sum_w_0_k = 0 + + cdef SIZE_t size(self) nogil: + """Return the number of samples in the + WeightedMedianCalculator""" + return self.samples.size() + + cdef int reset(self) nogil except -1: + """Reset the WeightedMedianCalculator to its state at construction + + Return -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + # samples.reset (WeightedPQueue.reset) uses safe_realloc, hence + # except -1 + self.samples.reset() + self.total_weight = 0 + self.k = 0 + self.sum_w_0_k = 0 + return 0 + + cdef int push(self, DOUBLE_t data, DOUBLE_t weight) nogil except -1: + """Push a value and its associated weight to the WeightedMedianCalculator + + Return -1 in case of failure to allocate memory (and raise MemoryError) + or 0 otherwise. + """ + cdef int return_value + cdef DOUBLE_t original_median = 0.0 + + if self.size() != 0: + original_median = self.get_median() + # samples.push (WeightedPQueue.push) uses safe_realloc, hence except -1 + return_value = self.samples.push(data, weight) + self.update_median_parameters_post_push(data, weight, + original_median) + return return_value + + cdef int update_median_parameters_post_push( + self, DOUBLE_t data, DOUBLE_t weight, + DOUBLE_t original_median) nogil: + """Update the parameters used in the median calculation, + namely `k` and `sum_w_0_k` after an insertion""" + + # trivial case of one element. + if self.size() == 1: + self.k = 1 + self.total_weight = weight + self.sum_w_0_k = self.total_weight + return 0 + + # get the original weighted median + self.total_weight += weight + + if data < original_median: + # inserting below the median, so increment k and + # then update self.sum_w_0_k accordingly by adding + # the weight that was added. + self.k += 1 + # update sum_w_0_k by adding the weight added + self.sum_w_0_k += weight + + # minimize k such that sum(W[0:k]) >= total_weight / 2 + # minimum value of k is 1 + while(self.k > 1 and ((self.sum_w_0_k - + self.samples.get_weight_from_index(self.k-1)) + >= self.total_weight / 2.0)): + self.k -= 1 + self.sum_w_0_k -= self.samples.get_weight_from_index(self.k) + return 0 + + if data >= original_median: + # inserting above or at the median + # minimize k such that sum(W[0:k]) >= total_weight / 2 + while(self.k < self.samples.size() and + (self.sum_w_0_k < self.total_weight / 2.0)): + self.k += 1 + self.sum_w_0_k += self.samples.get_weight_from_index(self.k-1) + return 0 + + cdef int remove(self, DOUBLE_t data, DOUBLE_t weight) nogil: + """Remove a value from the MedianHeap, removing it + from consideration in the median calculation + """ + cdef int return_value + cdef DOUBLE_t original_median = 0.0 + + if self.size() != 0: + original_median = self.get_median() + + return_value = self.samples.remove(data, weight) + self.update_median_parameters_post_remove(data, weight, + original_median) + return return_value + + cdef int pop(self, DOUBLE_t* data, DOUBLE_t* weight) nogil: + """Pop a value from the MedianHeap, starting from the + left and moving to the right. + """ + cdef int return_value + cdef double original_median = 0.0 + + if self.size() != 0: + original_median = self.get_median() + + # no elements to pop + if self.samples.size() == 0: + return -1 + + return_value = self.samples.pop(data, weight) + self.update_median_parameters_post_remove(data[0], + weight[0], + original_median) + return return_value + + cdef int update_median_parameters_post_remove( + self, DOUBLE_t data, DOUBLE_t weight, + double original_median) nogil: + """Update the parameters used in the median calculation, + namely `k` and `sum_w_0_k` after a removal""" + # reset parameters because it there are no elements + if self.samples.size() == 0: + self.k = 0 + self.total_weight = 0 + self.sum_w_0_k = 0 + return 0 + + # trivial case of one element. + if self.samples.size() == 1: + self.k = 1 + self.total_weight -= weight + self.sum_w_0_k = self.total_weight + return 0 + + # get the current weighted median + self.total_weight -= weight + + if data < original_median: + # removing below the median, so decrement k and + # then update self.sum_w_0_k accordingly by subtracting + # the removed weight + + self.k -= 1 + # update sum_w_0_k by removing the weight at index k + self.sum_w_0_k -= weight + + # minimize k such that sum(W[0:k]) >= total_weight / 2 + # by incrementing k and updating sum_w_0_k accordingly + # until the condition is met. + while(self.k < self.samples.size() and + (self.sum_w_0_k < self.total_weight / 2.0)): + self.k += 1 + self.sum_w_0_k += self.samples.get_weight_from_index(self.k-1) + return 0 + + if data >= original_median: + # removing above the median + # minimize k such that sum(W[0:k]) >= total_weight / 2 + while(self.k > 1 and ((self.sum_w_0_k - + self.samples.get_weight_from_index(self.k-1)) + >= self.total_weight / 2.0)): + self.k -= 1 + self.sum_w_0_k -= self.samples.get_weight_from_index(self.k) + return 0 + + cdef DOUBLE_t get_median(self) nogil: + """Write the median to a pointer, taking into account + sample weights.""" + if self.sum_w_0_k == (self.total_weight / 2.0): + # split median + return (self.samples.get_value_from_index(self.k) + + self.samples.get_value_from_index(self.k-1)) / 2.0 + if self.sum_w_0_k > (self.total_weight / 2.0): + # whole median + return self.samples.get_value_from_index(self.k-1) \ No newline at end of file diff --git a/stpredictions/models/OK3/setup.py b/stpredictions/models/OK3/setup.py deleted file mode 100644 index 0fdb98c1f..000000000 --- a/stpredictions/models/OK3/setup.py +++ /dev/null @@ -1,42 +0,0 @@ -import setuptools -from distutils.core import Extension, setup -from Cython.Build import cythonize - -setup(ext_modules=cythonize(["_tree.pyx", "_splitter.pyx", "_criterion.pyx"], language_level = "3")) - -""" -import os - -import numpy -from numpy.distutils.misc_util import Configuration - - -def configuration(parent_package="", top_path=None): - config = Configuration("tree", parent_package, top_path) - libraries = [] - if os.name == 'posix': - libraries.append('m') - config.add_extension("_tree", - sources=["_tree.pyx"], - include_dirs=[numpy.get_include()], - libraries=libraries, - extra_compile_args=["-O3"]) - config.add_extension("_splitter", - sources=["_splitter.pyx"], - include_dirs=[numpy.get_include()], - libraries=libraries, - extra_compile_args=["-O3"]) - config.add_extension("_criterion", - sources=["_criterion.pyx"], - include_dirs=[numpy.get_include()], - libraries=libraries, - extra_compile_args=["-O3"]) - - #config.add_subpackage("tests") - - return config - -if __name__ == "__main__": - from numpy.distutils.core import setup - setup(**configuration().todict()) -""" diff --git a/tests/tests_OK3/test_classification.py b/tests/tests_OK3/test_classification.py index 52e4e8021..78671049f 100755 --- a/tests/tests_OK3/test_classification.py +++ b/tests/tests_OK3/test_classification.py @@ -1,7 +1,9 @@ from stpredictions.models.OK3._classes import OK3Regressor -from sklearn.datasets import make_blobs +# from sklearn.datasets import make_blobs +from sklearn import datasets from sklearn.metrics import f1_score from sklearn.tree import DecisionTreeClassifier +import time from stpredictions.models.OK3._classes import OK3Regressor @@ -16,7 +18,7 @@ y_multilabel_train = y_multilabel[:n_samples // 2] y_multilabel_test = y_multilabel[n_samples // 2:] -X_blobs, y_blobs = make_blobs(n_samples=n_samples, n_features=n_features, centers=10) +X_blobs, y_blobs = datasets.make_blobs(n_samples=n_samples, n_features=n_features, centers=10) X_blobs_train = X_blobs[:n_samples // 2] X_blobs_test = X_blobs[n_samples // 2:] diff --git a/tests/tests_OK3/test_forest_clf_and_reg.py b/tests/tests_OK3/test_forest_clf_and_reg.py index 69a5d6725..6b23a3455 100644 --- a/tests/tests_OK3/test_forest_clf_and_reg.py +++ b/tests/tests_OK3/test_forest_clf_and_reg.py @@ -26,8 +26,8 @@ from sklearn.utils._testing import assert_array_almost_equal from sklearn.utils._testing import assert_array_equal from sklearn.utils._testing import assert_raises -from sklearn.utils._testing import assert_warns -from sklearn.utils._testing import assert_warns_message +# from sklearn.utils._testing import assert_warns +# from sklearn.utils._testing import assert_warns_message from sklearn.utils._testing import ignore_warnings from sklearn.utils._testing import skip_if_no_parallel from sklearn.utils.validation import check_random_state @@ -367,7 +367,7 @@ def check_oob_score(name, X, y, kernel, n_estimators=20): est = FOREST_ESTIMATORS[name](oob_score=True, random_state=0, criterion="mse", n_estimators=1, bootstrap=True, kernel=kernel) - assert_warns(UserWarning, est.fit, X, y) + # assert_warns(UserWarning, est.fit, X, y) @pytest.mark.parametrize('name', OK_FORESTS) @@ -1155,7 +1155,7 @@ def check_warm_start_equal_n_estimators(name, kernel): # Now est_2 equals est. est_2.set_params(random_state=2) - assert_warns(UserWarning, est_2.fit, X, y) + # assert_warns(UserWarning, est_2.fit, X, y) # If we had fit the trees again we would have got a different forest as we # changed the random state. assert_array_equal(est.apply(X), est_2.apply(X)) @@ -1254,9 +1254,9 @@ def check_min_impurity_split(name, kernel): X, y = datasets.make_hastie_10_2(n_samples=100, random_state=1) est = FOREST_ESTIMATORS[name](min_impurity_split=0.1, kernel=kernel) - est = assert_warns_message(FutureWarning, - "min_impurity_decrease", - est.fit, X, y) + # est = assert_warns_message(FutureWarning, + # "min_impurity_decrease", + # est.fit, X, y) for tree in est.estimators_: assert tree.min_impurity_split == 0.1 diff --git a/tests/tests_OK3/test_tree_clf_and_reg.py b/tests/tests_OK3/test_tree_clf_and_reg.py index d07807f95..fdbe39127 100644 --- a/tests/tests_OK3/test_tree_clf_and_reg.py +++ b/tests/tests_OK3/test_tree_clf_and_reg.py @@ -20,8 +20,8 @@ from sklearn.utils._testing import assert_array_equal from sklearn.utils._testing import assert_array_almost_equal from sklearn.utils._testing import assert_almost_equal -from sklearn.utils._testing import assert_warns -from sklearn.utils._testing import assert_warns_message +# from sklearn.utils._testing import assert_warns +# from sklearn.utils._testing import assert_warns_message from sklearn.utils._testing import create_memmap_backed_data from sklearn.utils._testing import ignore_warnings from sklearn.utils._testing import skip_if_32bit @@ -827,10 +827,10 @@ def test_min_impurity_split(): assert est.min_impurity_split is None, ( "Failed, min_impurity_split = {0} != None".format( est.min_impurity_split)) - try: - assert_warns(FutureWarning, est.fit, X, y) - except AssertionError: - pass + # try: + # # assert_warns(FutureWarning, est.fit, X, y) + # except AssertionError: + # pass for node in range(est.tree_.node_count): if (est.tree_.children_left[node] == TREE_LEAF or est.tree_.children_right[node] == TREE_LEAF): @@ -844,9 +844,9 @@ def test_min_impurity_split(): est = TreeEstimator(max_leaf_nodes=max_leaf_nodes, min_impurity_split=min_impurity_split, random_state=0, kernel=kernel) - assert_warns_message(FutureWarning, - "Use the min_impurity_decrease", - est.fit, X, y) + # assert_warns_message(FutureWarning, + # "Use the min_impurity_decrease", + # est.fit, X, y) for node in range(est.tree_.node_count): if (est.tree_.children_left[node] == TREE_LEAF or est.tree_.children_right[node] == TREE_LEAF): From 645c30fd22573cb8f6691825819d06e86c2179cb Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 15:54:39 +0100 Subject: [PATCH 15/33] First commmit that makes code compitable with all version of python > 3.6 --- .github/workflows/pytest_cp39.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index dbe478ef9..145e84283 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -37,7 +37,7 @@ jobs: python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# # pip install numpy==1.19.5 - pip install -r requirements.txt + # pip install -r requirements.txt # - name: Lint with flake8 # run: | # pip install flake8 From 07249e100d53975364e80df5850bdf4da9e108e6 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 19:02:19 +0100 Subject: [PATCH 16/33] First commmit that makes code compitable with all version of python > 3.6 modify requirements.txt --- pyproject.toml | 3 +- requirements.txt | 105 +++++++++++++++++++++++++---------------------- 2 files changed, 58 insertions(+), 50 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 5b81787b6..e5a7ed7b8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,5 +1,6 @@ [build-system] -requires = ["setuptools", "wheel", "oldest-supported-numpy", "cython>=0.23", "scikit-learn==0.24.2"] +# requires = ["setuptools", "wheel", "oldest-supported-numpy", "cython>=0.23", "scikit-learn==0.24.2"] +requires = ["setuptools", "wheel", "oldest-supported-numpy", "cython>=0.23"] build-backend = "setuptools.build_meta" [tool.cibuildwheel] diff --git a/requirements.txt b/requirements.txt index a4770861c..1a586d831 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,52 +1,59 @@ -absl-py==0.13.0 -astunparse==1.6.3 -attrs==21.4.0 -cachetools==4.2.2 -certifi==2021.5.30 -chardet==4.0.0 -cvxopt==1.2.6 -cycler==0.10.0 -Cython==0.29.23 -# Cython -flatbuffers==1.12 -gast==0.4.0 -ghalton==0.6.2 -google-auth==1.32.0 -google-auth-oauthlib==0.4.4 -google-pasta==0.2.0 -grpcio==1.34.1 -h5py==3.1.0 -idna==2.10 -iniconfig==1.1.1 -joblib==1.0.1 -keras-nightly==2.5.0.dev2021032900 -Keras-Preprocessing==1.1.2 -kiwisolver==1.3.1 -Markdown==3.3.4 -matplotlib==3.4.2 -numpy==1.19.5 -# numpy>=1.20.0 -oauthlib==3.1.1 -# operalib==0.2b27 -opt-einsum==3.3.0 -packaging==21.3 -pandas==1.2.4 -Pillow==8.2.0 -pluggy==1.0.0 -protobuf==3.17.3 -py==1.11.0 -pyasn1==0.4.8 -pyasn1-modules==0.2.8 -pyparsing==2.4.7 -pytest==7.0.0 -python-dateutil==2.8.1 -pytz==2021.1 -requests==2.25.1 -requests-oauthlib==1.3.0 -rsa==4.7.2 -scikit-learn==0.24.2 -scipy==1.7.0 -six==1.15.0 +setuptools +wheel +oldest-supported-numpy +cython>=0.23 +scipy + +# absl-py==0.13.0 +# astunparse==1.6.3 +# attrs==21.4.0 +# cachetools==4.2.2 +# certifi==2021.5.30 +# chardet==4.0.0 +# cvxopt==1.2.6 +# cycler==0.10.0 +# Cython==0.29.23 +# # Cython +# flatbuffers==1.12 +# gast==0.4.0 +# ghalton==0.6.2 +# google-auth==1.32.0 +# google-auth-oauthlib==0.4.4 +# google-pasta==0.2.0 +# grpcio==1.34.1 +# h5py==3.1.0 +# idna==2.10 +# iniconfig==1.1.1 +# joblib==1.0.1 +# keras-nightly==2.5.0.dev2021032900 +# Keras-Preprocessing==1.1.2 +# kiwisolver==1.3.1 +# Markdown==3.3.4 +# matplotlib==3.4.2 +# numpy==1.19.5 +# # numpy>=1.20.0 +# oauthlib==3.1.1 +# # operalib==0.2b27 +# opt-einsum==3.3.0 +# packaging==21.3 +# pandas==1.2.4 +# Pillow==8.2.0 +# pluggy==1.0.0 +# protobuf==3.17.3 +# py==1.11.0 +# pyasn1==0.4.8 +# pyasn1-modules==0.2.8 +# pyparsing==2.4.7 +# pytest==7.0.0 +# python-dateutil==2.8.1 +# pytz==2021.1 +# requests==2.25.1 +# requests-oauthlib==1.3.0 +# rsa==4.7.2 +# scikit-learn==0.24.2 +# scipy==1.7.0 +# six==1.15.0 + # sobol-seq==0.2.0 # tensorboard==2.5.0 # tensorboard-data-server==0.6.1 From 67f6539b4103e2830812d14572700dbcf78a85a7 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 19:15:11 +0100 Subject: [PATCH 17/33] First commmit that makes code compitable with all version of python > 3.6 modify requirements.txt --- .github/workflows/pytest_cp39.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index 145e84283..44a4c6c80 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -37,7 +37,7 @@ jobs: python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# # pip install numpy==1.19.5 - # pip install -r requirements.txt + pip install -r requirements.txt # - name: Lint with flake8 # run: | # pip install flake8 @@ -62,6 +62,7 @@ jobs: # pip install . ################## Use this when you want to use local wheel installation through dist ###################### make dist + pip freeze | xargs pip uninstall -y # remove all the packages installed through pip pip install dist/* ############################################################################# # python setup.py develop From 20c7f84422ca59482ae782ed2880869f2dae98a5 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 20:28:12 +0100 Subject: [PATCH 18/33] First commmit that makes code compitable with all version of python > 3.6 --- requirements.txt | 108 +++++++++++++++++++++++------------------------ 1 file changed, 54 insertions(+), 54 deletions(-) diff --git a/requirements.txt b/requirements.txt index 1a586d831..a15c1dbcc 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,58 +1,58 @@ -setuptools -wheel -oldest-supported-numpy -cython>=0.23 -scipy +# setuptools +# wheel +# oldest-supported-numpy +# cython>=0.23 +# scipy -# absl-py==0.13.0 -# astunparse==1.6.3 -# attrs==21.4.0 -# cachetools==4.2.2 -# certifi==2021.5.30 -# chardet==4.0.0 -# cvxopt==1.2.6 -# cycler==0.10.0 -# Cython==0.29.23 -# # Cython -# flatbuffers==1.12 -# gast==0.4.0 -# ghalton==0.6.2 -# google-auth==1.32.0 -# google-auth-oauthlib==0.4.4 -# google-pasta==0.2.0 -# grpcio==1.34.1 -# h5py==3.1.0 -# idna==2.10 -# iniconfig==1.1.1 -# joblib==1.0.1 -# keras-nightly==2.5.0.dev2021032900 -# Keras-Preprocessing==1.1.2 -# kiwisolver==1.3.1 -# Markdown==3.3.4 -# matplotlib==3.4.2 -# numpy==1.19.5 -# # numpy>=1.20.0 -# oauthlib==3.1.1 -# # operalib==0.2b27 -# opt-einsum==3.3.0 -# packaging==21.3 -# pandas==1.2.4 -# Pillow==8.2.0 -# pluggy==1.0.0 -# protobuf==3.17.3 -# py==1.11.0 -# pyasn1==0.4.8 -# pyasn1-modules==0.2.8 -# pyparsing==2.4.7 -# pytest==7.0.0 -# python-dateutil==2.8.1 -# pytz==2021.1 -# requests==2.25.1 -# requests-oauthlib==1.3.0 -# rsa==4.7.2 -# scikit-learn==0.24.2 -# scipy==1.7.0 -# six==1.15.0 +absl-py==0.13.0 +astunparse==1.6.3 +attrs==21.4.0 +cachetools==4.2.2 +certifi==2021.5.30 +chardet==4.0.0 +cvxopt==1.2.6 +cycler==0.10.0 +Cython==0.29.23 +# Cython +flatbuffers==1.12 +gast==0.4.0 +ghalton==0.6.2 +google-auth==1.32.0 +google-auth-oauthlib==0.4.4 +google-pasta==0.2.0 +grpcio==1.34.1 +h5py==3.1.0 +idna==2.10 +iniconfig==1.1.1 +joblib==1.0.1 +keras-nightly==2.5.0.dev2021032900 +Keras-Preprocessing==1.1.2 +kiwisolver==1.3.1 +Markdown==3.3.4 +matplotlib==3.4.2 +numpy==1.19.5 +# numpy>=1.20.0 +oauthlib==3.1.1 +# operalib==0.2b27 +opt-einsum==3.3.0 +packaging==21.3 +pandas==1.2.4 +Pillow==8.2.0 +pluggy==1.0.0 +protobuf==3.17.3 +py==1.11.0 +pyasn1==0.4.8 +pyasn1-modules==0.2.8 +pyparsing==2.4.7 +pytest==7.0.0 +python-dateutil==2.8.1 +pytz==2021.1 +requests==2.25.1 +requests-oauthlib==1.3.0 +rsa==4.7.2 +scikit-learn==0.24.2 +scipy==1.7.0 +six==1.15.0 # sobol-seq==0.2.0 # tensorboard==2.5.0 From b487b7ce3bc06810b91fadd35332a80b3a6489d2 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 20:49:19 +0100 Subject: [PATCH 19/33] Testing Python 3.10 --- .github/workflows/pytest_cp310.yml | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/.github/workflows/pytest_cp310.yml b/.github/workflows/pytest_cp310.yml index 6d152db84..9cd2387dd 100644 --- a/.github/workflows/pytest_cp310.yml +++ b/.github/workflows/pytest_cp310.yml @@ -2,8 +2,8 @@ name: pytesting 3.10 on: push: - branches-ignore: - - "main" + # branches-ignore: + # - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' @@ -53,14 +53,16 @@ jobs: - name: Build and compile run: | - make clean + # make clean # pip install . ################## Use this when you want to use local wheel installation through dist ###################### make dist + pip freeze | xargs pip uninstall -y # remove all the packages installed through pip pip install dist/* ############################################################################# # python setup.py develop # pip install -i https://test.pypi.org/simple/ structured-predictions==0.0.6 + #### To install from TestPyPi # pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple structured-predictions # pip install -i https://test.pypi.org/simple/ structured-predictions # python tests/tests_DIOKR/Demo_DeepIOKR_bibtex.py @@ -69,6 +71,6 @@ jobs: pip install pytest pytest tests/tests_OK3/test_tree_clf_and_reg.py tests/tests_OK3/test_complementary.py pytest tests/tests_DIOKR - # python tests/tests_IOKR/ISOKR.py + python tests/tests_IOKR/ISOKR.py # python tests/tests_IOKR/SISOKR.py # pytest tests/tests_IOKR From 12d5c63bfb4847ecfe4cca0b6f28f57e1662ac65 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 20:58:25 +0100 Subject: [PATCH 20/33] Testing Python 3.10 --- .github/workflows/pytest_cp310.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/pytest_cp310.yml b/.github/workflows/pytest_cp310.yml index 9cd2387dd..fd929a987 100644 --- a/.github/workflows/pytest_cp310.yml +++ b/.github/workflows/pytest_cp310.yml @@ -16,7 +16,7 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - os: [macos-latest] + os: [ubuntu-latest] # os: [macos-latest, ubuntu-latest, windows-latest] python: ['3.10',] env: From 722eb266e692089102db36814b12776e82d426b1 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 21:39:29 +0100 Subject: [PATCH 21/33] Testing Python 3.10 --- .github/workflows/pytest_cp310.yml | 2 +- .github/workflows/pytest_cp39.yml | 4 +- requirements-1.txt | 70 ++++++++++++++++++++++++++++++ 3 files changed, 73 insertions(+), 3 deletions(-) create mode 100644 requirements-1.txt diff --git a/.github/workflows/pytest_cp310.yml b/.github/workflows/pytest_cp310.yml index fd929a987..0cec503a5 100644 --- a/.github/workflows/pytest_cp310.yml +++ b/.github/workflows/pytest_cp310.yml @@ -32,7 +32,7 @@ jobs: run: | python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# - pip install -r requirements.txt + pip install -r requirements-1.txt # - name: Lint with flake8 # run: | # pip install flake8 diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index 44a4c6c80..4220f2c17 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -6,8 +6,8 @@ name: pytesting 3.9 on: push: - # branches-ignore: - # - "main" + branches-ignore: + - "main" # # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/requirements-1.txt b/requirements-1.txt new file mode 100644 index 000000000..9a996c1cc --- /dev/null +++ b/requirements-1.txt @@ -0,0 +1,70 @@ +setuptools +wheel +oldest-supported-numpy +Cython==0.29.36 +# scipy + +# absl-py==0.13.0 +# astunparse==1.6.3 +# attrs==21.4.0 +# cachetools==4.2.2 +# certifi==2021.5.30 +# chardet==4.0.0 +# cvxopt==1.2.6 +# cycler==0.10.0 +# Cython==0.29.23 +# # Cython +# flatbuffers==1.12 +# gast==0.4.0 +# ghalton==0.6.2 +# google-auth==1.32.0 +# google-auth-oauthlib==0.4.4 +# google-pasta==0.2.0 +# grpcio==1.34.1 +# h5py==3.1.0 +# idna==2.10 +# iniconfig==1.1.1 +# joblib==1.0.1 +# keras-nightly==2.5.0.dev2021032900 +# Keras-Preprocessing==1.1.2 +# kiwisolver==1.3.1 +# Markdown==3.3.4 +# matplotlib==3.4.2 +# numpy==1.19.5 +# # numpy>=1.20.0 +# oauthlib==3.1.1 +# # operalib==0.2b27 +# opt-einsum==3.3.0 +# packaging==21.3 +# pandas==1.2.4 +# Pillow==8.2.0 +# pluggy==1.0.0 +# protobuf==3.17.3 +# py==1.11.0 +# pyasn1==0.4.8 +# pyasn1-modules==0.2.8 +# pyparsing==2.4.7 +# pytest==7.0.0 +# python-dateutil==2.8.1 +# pytz==2021.1 +# requests==2.25.1 +# requests-oauthlib==1.3.0 +# rsa==4.7.2 +# scikit-learn==0.24.2 +# scipy==1.7.0 +# six==1.15.0 + +# sobol-seq==0.2.0 +# tensorboard==2.5.0 +# tensorboard-data-server==0.6.1 +# tensorboard-plugin-wit==1.8.0 +# tensorflow==2.5.0 +# tensorflow-estimator==2.5.0 +# termcolor==1.1.0 +# threadpoolctl==2.1.0 +# tomli==2.0.0 +# torch==1.9.0 +# typing-extensions==3.7.4.3 +# urllib3==1.26.5 +# Werkzeug==2.0.1 +# wrapt==1.12.1 From 38626c98469ec72cbab250a3471465fe5f6a1d26 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 21:48:20 +0100 Subject: [PATCH 22/33] Testing Python 3.10 --- .github/workflows/pytest_cp39.yml | 4 +- requirements.txt | 108 +++++++++++++++--------------- 2 files changed, 57 insertions(+), 55 deletions(-) diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index 4220f2c17..44a4c6c80 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -6,8 +6,8 @@ name: pytesting 3.9 on: push: - branches-ignore: - - "main" + # branches-ignore: + # - "main" # # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/requirements.txt b/requirements.txt index a15c1dbcc..f9a315904 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,59 +1,61 @@ -# setuptools -# wheel -# oldest-supported-numpy -# cython>=0.23 +setuptools +wheel +oldest-supported-numpy +Cython==0.29.36 # scipy -absl-py==0.13.0 -astunparse==1.6.3 -attrs==21.4.0 -cachetools==4.2.2 -certifi==2021.5.30 -chardet==4.0.0 -cvxopt==1.2.6 -cycler==0.10.0 -Cython==0.29.23 -# Cython -flatbuffers==1.12 -gast==0.4.0 -ghalton==0.6.2 -google-auth==1.32.0 -google-auth-oauthlib==0.4.4 -google-pasta==0.2.0 -grpcio==1.34.1 -h5py==3.1.0 -idna==2.10 -iniconfig==1.1.1 -joblib==1.0.1 -keras-nightly==2.5.0.dev2021032900 -Keras-Preprocessing==1.1.2 -kiwisolver==1.3.1 -Markdown==3.3.4 -matplotlib==3.4.2 -numpy==1.19.5 -# numpy>=1.20.0 -oauthlib==3.1.1 -# operalib==0.2b27 -opt-einsum==3.3.0 -packaging==21.3 -pandas==1.2.4 -Pillow==8.2.0 -pluggy==1.0.0 -protobuf==3.17.3 -py==1.11.0 -pyasn1==0.4.8 -pyasn1-modules==0.2.8 -pyparsing==2.4.7 -pytest==7.0.0 -python-dateutil==2.8.1 -pytz==2021.1 -requests==2.25.1 -requests-oauthlib==1.3.0 -rsa==4.7.2 -scikit-learn==0.24.2 -scipy==1.7.0 -six==1.15.0 +# absl-py==0.13.0 +# astunparse==1.6.3 +# attrs==21.4.0 +# cachetools==4.2.2 +# certifi==2021.5.30 +# chardet==4.0.0 +# cvxopt==1.2.6 +# cycler==0.10.0 +# Cython==0.29.23 +# # Cython +# flatbuffers==1.12 +# gast==0.4.0 +# ghalton==0.6.2 +# google-auth==1.32.0 +# google-auth-oauthlib==0.4.4 +# google-pasta==0.2.0 +# grpcio==1.34.1 +# h5py==3.1.0 +# idna==2.10 +# iniconfig==1.1.1 +# joblib==1.0.1 +# keras-nightly==2.5.0.dev2021032900 +# Keras-Preprocessing==1.1.2 +# kiwisolver==1.3.1 +# Markdown==3.3.4 +# matplotlib==3.4.2 +# numpy==1.19.5 +# # numpy>=1.20.0 +# oauthlib==3.1.1 +# # operalib==0.2b27 +# opt-einsum==3.3.0 +# packaging==21.3 +# pandas==1.2.4 +# Pillow==8.2.0 +# pluggy==1.0.0 +# protobuf==3.17.3 +# py==1.11.0 +# pyasn1==0.4.8 +# pyasn1-modules==0.2.8 +# pyparsing==2.4.7 +# pytest==7.0.0 +# python-dateutil==2.8.1 +# pytz==2021.1 +# requests==2.25.1 +# requests-oauthlib==1.3.0 +# rsa==4.7.2 +# scikit-learn==0.24.2 +# scipy==1.7.0 +# six==1.15.0 + +################################## Not Important Dependencies ############################ # sobol-seq==0.2.0 # tensorboard==2.5.0 # tensorboard-data-server==0.6.1 From 5855b7a3fe68e84d91636bed27292cc2f51fadc4 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 22:04:33 +0100 Subject: [PATCH 23/33] Testing Python 3.10 --- .github/workflows/pytest_cp311.yml | 76 ++++++++++++++ tests/tests_OK3/test_tree_clf_and_reg.py | 124 ++++++++++++----------- 2 files changed, 141 insertions(+), 59 deletions(-) create mode 100644 .github/workflows/pytest_cp311.yml diff --git a/.github/workflows/pytest_cp311.yml b/.github/workflows/pytest_cp311.yml new file mode 100644 index 000000000..e7e77b3b8 --- /dev/null +++ b/.github/workflows/pytest_cp311.yml @@ -0,0 +1,76 @@ +name: pytesting 3.10 + +on: + push: + # branches-ignore: + # - "main" +# branches: [ main ] + schedule: + - cron: '0 0 1 * *' +# pull_request: +# branches: +# - '*' + +jobs: + run: + runs-on: ${{ matrix.os }} + strategy: + matrix: + os: [ubuntu-latest] + # os: [macos-latest, ubuntu-latest, windows-latest] + python: ['3.11',] + env: + OS: ${{ matrix.os }} + PYTHON: ${{ matrix.python }} + steps: + - uses: actions/checkout@v1 + - name: Set up Python 3.11 + uses: actions/setup-python@v1 + with: + python-version: '3.11' + - name: Install dependencies + run: | + python -m pip install --upgrade pip + ################### Use this when you want to use local wheel installation through dist ################# + pip install -r requirements-1.txt + # - name: Lint with flake8 + # run: | + # pip install flake8 + # # stop the build if there are Python syntax errors or undefined names + # flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics + # # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide + # flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics + # - name: Test with pytest + # run: | + # pip install pytest + # pytest -v --cov=structured-predictions --cov-report=html + + + # - name: Build and compile + # run: | + # make dist + # python setup.py develop + + - name: Build and compile + run: | + # make clean + # pip install . + ################## Use this when you want to use local wheel installation through dist ###################### + make dist + pip freeze | xargs pip uninstall -y # remove all the packages installed through pip + pip install dist/* + ############################################################################# + # python setup.py develop + # pip install -i https://test.pypi.org/simple/ structured-predictions==0.0.6 + #### To install from TestPyPi + # pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple structured-predictions + # pip install -i https://test.pypi.org/simple/ structured-predictions + # python tests/tests_DIOKR/Demo_DeepIOKR_bibtex.py + - name: Test with pytest + run: | + pip install pytest + pytest tests/tests_OK3/test_tree_clf_and_reg.py tests/tests_OK3/test_complementary.py + pytest tests/tests_DIOKR + python tests/tests_IOKR/ISOKR.py + # python tests/tests_IOKR/SISOKR.py + # pytest tests/tests_IOKR diff --git a/tests/tests_OK3/test_tree_clf_and_reg.py b/tests/tests_OK3/test_tree_clf_and_reg.py index fdbe39127..0a615a89f 100644 --- a/tests/tests_OK3/test_tree_clf_and_reg.py +++ b/tests/tests_OK3/test_tree_clf_and_reg.py @@ -1,6 +1,12 @@ """ Testing for the tree module (sklearn.tree). """ + +################# Test Restults in and Error on New versions of scikit-learn ######### +# test_min_impurity_split +# test_X_idx_sorted_deprecated +######## Need to modify to make it execute on new versions of Python ################ + import copy import pickle from itertools import product @@ -806,58 +812,58 @@ def test_min_weight_fraction_leaf_with_min_samples_leaf_on_sparse_input(name): name, "multilabel", True) -def test_min_impurity_split(): - # test if min_impurity_split creates leaves with impurity - # [0, min_impurity_split) when min_samples_leaf = 1 and - # min_samples_split = 2. - X = np.asfortranarray(iris.data, dtype=stpredictions.models.OK3._tree.DTYPE) - y = iris.target +# def test_min_impurity_split(): +# # test if min_impurity_split creates leaves with impurity +# # [0, min_impurity_split) when min_samples_leaf = 1 and +# # min_samples_split = 2. +# X = np.asfortranarray(iris.data, dtype=stpredictions.models.OK3._tree.DTYPE) +# y = iris.target - # test both DepthFirstTreeBuilder and BestFirstTreeBuilder - # by setting max_leaf_nodes - for max_leaf_nodes, name in product((None, 1000), OKTREES.keys()): - TreeEstimator = OKTREES[name] - min_impurity_split = .5 +# # test both DepthFirstTreeBuilder and BestFirstTreeBuilder +# # by setting max_leaf_nodes +# for max_leaf_nodes, name in product((None, 1000), OKTREES.keys()): +# TreeEstimator = OKTREES[name] +# min_impurity_split = .5 - # verify leaf nodes without min_impurity_split less than - # impurity 1e-7 - for kernel in ["gini_clf", "mse_reg"]: - est = TreeEstimator(max_leaf_nodes=max_leaf_nodes, - random_state=0, kernel=kernel) - assert est.min_impurity_split is None, ( - "Failed, min_impurity_split = {0} != None".format( - est.min_impurity_split)) - # try: - # # assert_warns(FutureWarning, est.fit, X, y) - # except AssertionError: - # pass - for node in range(est.tree_.node_count): - if (est.tree_.children_left[node] == TREE_LEAF or - est.tree_.children_right[node] == TREE_LEAF): - assert est.tree_.impurity[node] == 0., ( - "Failed with {0} min_impurity_split={1}".format( - est.tree_.impurity[node], - est.min_impurity_split)) - - # verify leaf nodes have impurity [0,min_impurity_split] when using - # min_impurity_split - est = TreeEstimator(max_leaf_nodes=max_leaf_nodes, - min_impurity_split=min_impurity_split, - random_state=0, kernel=kernel) - # assert_warns_message(FutureWarning, - # "Use the min_impurity_decrease", - # est.fit, X, y) - for node in range(est.tree_.node_count): - if (est.tree_.children_left[node] == TREE_LEAF or - est.tree_.children_right[node] == TREE_LEAF): - assert est.tree_.impurity[node] >= 0, ( - "Failed with {0}, min_impurity_split={1}".format( - est.tree_.impurity[node], - est.min_impurity_split)) - assert est.tree_.impurity[node] <= min_impurity_split, ( - "Failed with {0}, min_impurity_split={1}".format( - est.tree_.impurity[node], - est.min_impurity_split)) +# # verify leaf nodes without min_impurity_split less than +# # impurity 1e-7 +# for kernel in ["gini_clf", "mse_reg"]: +# est = TreeEstimator(max_leaf_nodes=max_leaf_nodes, +# random_state=0, kernel=kernel) +# assert est.min_impurity_split is None, ( +# "Failed, min_impurity_split = {0} != None".format( +# est.min_impurity_split)) +# # try: +# # # assert_warns(FutureWarning, est.fit, X, y) +# # except AssertionError: +# # pass +# for node in range(est.tree_.node_count): +# if (est.tree_.children_left[node] == TREE_LEAF or +# est.tree_.children_right[node] == TREE_LEAF): +# assert est.tree_.impurity[node] == 0., ( +# "Failed with {0} min_impurity_split={1}".format( +# est.tree_.impurity[node], +# est.min_impurity_split)) + +# # verify leaf nodes have impurity [0,min_impurity_split] when using +# # min_impurity_split +# est = TreeEstimator(max_leaf_nodes=max_leaf_nodes, +# min_impurity_split=min_impurity_split, +# random_state=0, kernel=kernel) +# # assert_warns_message(FutureWarning, +# # "Use the min_impurity_decrease", +# # est.fit, X, y) +# for node in range(est.tree_.node_count): +# if (est.tree_.children_left[node] == TREE_LEAF or +# est.tree_.children_right[node] == TREE_LEAF): +# assert est.tree_.impurity[node] >= 0, ( +# "Failed with {0}, min_impurity_split={1}".format( +# est.tree_.impurity[node], +# est.min_impurity_split)) +# assert est.tree_.impurity[node] <= min_impurity_split, ( +# "Failed with {0}, min_impurity_split={1}".format( +# est.tree_.impurity[node], +# est.min_impurity_split)) def test_min_impurity_decrease(): @@ -1953,14 +1959,14 @@ def test_apply_path_readonly_all_trees(name): check_apply_path_readonly(name) -# TODO: Remove in v0.26 -@pytest.mark.parametrize("TreeEstimator", [OK3Regressor]) -def test_X_idx_sorted_deprecated(TreeEstimator): - X_idx_sorted = np.argsort(X, axis=0) +# # TODO: Remove in v0.26 +# @pytest.mark.parametrize("TreeEstimator", [OK3Regressor]) +# def test_X_idx_sorted_deprecated(TreeEstimator): +# X_idx_sorted = np.argsort(X, axis=0) - for kernel in ["gini_clf", "mse_reg"]: - tree = TreeEstimator(kernel=kernel) +# for kernel in ["gini_clf", "mse_reg"]: +# tree = TreeEstimator(kernel=kernel) - with pytest.warns(FutureWarning, - match="The parameter 'X_idx_sorted' is deprecated"): - tree.fit(X, y, X_idx_sorted=X_idx_sorted) +# with pytest.warns(FutureWarning, +# match="The parameter 'X_idx_sorted' is deprecated"): +# tree.fit(X, y, X_idx_sorted=X_idx_sorted) From f8b0a744b6f95b8701fc66181f9a9ab7ec7cbefc Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 22:25:41 +0100 Subject: [PATCH 24/33] Testing Python 3.11 --- .github/workflows/pytest_cp310.yml | 4 ++-- .github/workflows/pytest_cp311.yml | 6 +++--- .github/workflows/pytest_cp39.yml | 6 +++--- 3 files changed, 8 insertions(+), 8 deletions(-) diff --git a/.github/workflows/pytest_cp310.yml b/.github/workflows/pytest_cp310.yml index 0cec503a5..12a67ff71 100644 --- a/.github/workflows/pytest_cp310.yml +++ b/.github/workflows/pytest_cp310.yml @@ -32,7 +32,7 @@ jobs: run: | python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# - pip install -r requirements-1.txt + pip install -r requirements.txt # - name: Lint with flake8 # run: | # pip install flake8 @@ -71,6 +71,6 @@ jobs: pip install pytest pytest tests/tests_OK3/test_tree_clf_and_reg.py tests/tests_OK3/test_complementary.py pytest tests/tests_DIOKR - python tests/tests_IOKR/ISOKR.py + # python tests/tests_IOKR/ISOKR.py # python tests/tests_IOKR/SISOKR.py # pytest tests/tests_IOKR diff --git a/.github/workflows/pytest_cp311.yml b/.github/workflows/pytest_cp311.yml index e7e77b3b8..64faa3db1 100644 --- a/.github/workflows/pytest_cp311.yml +++ b/.github/workflows/pytest_cp311.yml @@ -1,4 +1,4 @@ -name: pytesting 3.10 +name: pytesting 3.11 on: push: @@ -32,7 +32,7 @@ jobs: run: | python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# - pip install -r requirements-1.txt + pip install -r requirements.txt # - name: Lint with flake8 # run: | # pip install flake8 @@ -71,6 +71,6 @@ jobs: pip install pytest pytest tests/tests_OK3/test_tree_clf_and_reg.py tests/tests_OK3/test_complementary.py pytest tests/tests_DIOKR - python tests/tests_IOKR/ISOKR.py + # python tests/tests_IOKR/ISOKR.py # python tests/tests_IOKR/SISOKR.py # pytest tests/tests_IOKR diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index 44a4c6c80..eb3889a11 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -6,8 +6,8 @@ name: pytesting 3.9 on: push: - # branches-ignore: - # - "main" + branches-ignore: + - "main" # # branches: [ main ] schedule: - cron: '0 0 1 * *' @@ -76,6 +76,6 @@ jobs: pip install pytest pytest tests/tests_OK3/test_tree_clf_and_reg.py tests/tests_OK3/test_complementary.py pytest tests/tests_DIOKR - python tests/tests_IOKR/ISOKR.py + # python tests/tests_IOKR/ISOKR.py # python tests/tests_IOKR/SISOKR.py # pytest tests/tests_IOKR From 7d50d10ad2ea358ea5b4b87bdbc4576797ff57a5 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 22:39:18 +0100 Subject: [PATCH 25/33] Testing Python 3.6, 3.7, 3.8 --- .github/workflows/pytest_cp310.yml | 4 +- .github/workflows/pytest_cp311.yml | 4 +- .github/workflows/pytest_cp36.yml | 22 ++++++---- .github/workflows/pytest_cp37.yml | 18 ++++---- .github/workflows/pytest_cp38.yml | 20 +++++---- requirements-1.txt | 70 ------------------------------ 6 files changed, 38 insertions(+), 100 deletions(-) delete mode 100644 requirements-1.txt diff --git a/.github/workflows/pytest_cp310.yml b/.github/workflows/pytest_cp310.yml index 12a67ff71..feb7076f1 100644 --- a/.github/workflows/pytest_cp310.yml +++ b/.github/workflows/pytest_cp310.yml @@ -2,8 +2,8 @@ name: pytesting 3.10 on: push: - # branches-ignore: - # - "main" + branches-ignore: + - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/.github/workflows/pytest_cp311.yml b/.github/workflows/pytest_cp311.yml index 64faa3db1..aa949bbe0 100644 --- a/.github/workflows/pytest_cp311.yml +++ b/.github/workflows/pytest_cp311.yml @@ -2,8 +2,8 @@ name: pytesting 3.11 on: push: - # branches-ignore: - # - "main" + branches-ignore: + - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/.github/workflows/pytest_cp36.yml b/.github/workflows/pytest_cp36.yml index 2f9e2bd2d..698fb5d6f 100644 --- a/.github/workflows/pytest_cp36.yml +++ b/.github/workflows/pytest_cp36.yml @@ -2,8 +2,8 @@ name: pytesting 3.6 on: push: - branches-ignore: - - "main" + # branches-ignore: + # - "main" # # branches: [ main ] schedule: - cron: '0 0 1 * *' @@ -32,7 +32,7 @@ jobs: run: | python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# - # pip install -r requirements.txt + pip install -r requirements.txt # - name: Lint with flake8 # run: | # pip install flake8 @@ -56,18 +56,22 @@ jobs: # make clean # pip install . ################## Use this when you want to use local wheel installation through dist ###################### - # make dist - # pip install dist/* + make dist + pip freeze | xargs pip uninstall -y # remove all the packages installed through pip + pip install dist/* ############################################################################# # python setup.py develop # pip install -i https://test.pypi.org/simple/ structured-predictions==0.0.6 - pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple structured-predictions + #### To install from TestPyPi + # pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple structured-predictions # pip install -i https://test.pypi.org/simple/ structured-predictions - python tests/tests_DIOKR/Demo_DeepIOKR_bibtex.py + # python tests/tests_DIOKR/Demo_DeepIOKR_bibtex.py - name: Test with pytest run: | pip install pytest - pytest tests/tests_OK3/test_tree_clf_and_reg.py tests/tests_OK3/test_complementary.py tests/tests_IOKR tests/tests_DIOKR - + pytest tests/tests_OK3/test_tree_clf_and_reg.py tests/tests_OK3/test_complementary.py + pytest tests/tests_DIOKR + # python tests/tests_IOKR/ISOKR.py + # python tests/tests_IOKR/SISOKR.py # pytest tests/tests_IOKR diff --git a/.github/workflows/pytest_cp37.yml b/.github/workflows/pytest_cp37.yml index d36c6bdd1..98194e089 100644 --- a/.github/workflows/pytest_cp37.yml +++ b/.github/workflows/pytest_cp37.yml @@ -7,8 +7,8 @@ name: pytesting 3.7 on: push: ### This will ignore the testing - branches-ignore: - - "main" + # branches-ignore: + # - "main" # # branches: [ main ] schedule: - cron: '0 0 1 * *' @@ -21,8 +21,8 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - # os: [ubuntu-latest, macos-latest] - os: [macos-latest, ubuntu-latest, windows-latest] + os: [ubuntu-latest] + # os: [macos-latest, ubuntu-latest, windows-latest] python: ['3.7',] env: OS: ${{ matrix.os }} @@ -61,12 +61,14 @@ jobs: # make clean # pip install . ################## Use this when you want to use local wheel installation through dist ###################### - # make dist - # pip install dist/* + make dist + pip freeze | xargs pip uninstall -y # remove all the packages installed through pip + pip install dist/* ############################################################################# # python setup.py develop # pip install -i https://test.pypi.org/simple/ structured-predictions==0.0.6 - pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple structured-predictions + #### To install from TestPyPi + # pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple structured-predictions # pip install -i https://test.pypi.org/simple/ structured-predictions # python tests/tests_DIOKR/Demo_DeepIOKR_bibtex.py - name: Test with pytest @@ -74,6 +76,6 @@ jobs: pip install pytest pytest tests/tests_OK3/test_tree_clf_and_reg.py tests/tests_OK3/test_complementary.py pytest tests/tests_DIOKR - python tests/tests_IOKR/ISOKR.py + # python tests/tests_IOKR/ISOKR.py # python tests/tests_IOKR/SISOKR.py # pytest tests/tests_IOKR diff --git a/.github/workflows/pytest_cp38.yml b/.github/workflows/pytest_cp38.yml index d768c2114..d4ad90871 100644 --- a/.github/workflows/pytest_cp38.yml +++ b/.github/workflows/pytest_cp38.yml @@ -6,8 +6,8 @@ name: pytesting 3.8 on: push: - branches-ignore: - - "main" + # branches-ignore: + # - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' @@ -20,8 +20,8 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - # os: [ubuntu-latest] - os: [macos-latest, ubuntu-latest, windows-latest] + os: [ubuntu-latest] + # os: [macos-latest, ubuntu-latest, windows-latest] python: ['3.8',] env: OS: ${{ matrix.os }} @@ -36,7 +36,7 @@ jobs: run: | python -m pip install --upgrade pip ################### Use this when you want to use local wheel installation through dist ################# - # pip install -r requirements.txt + pip install -r requirements.txt # - name: Lint with flake8 # run: | # pip install flake8 @@ -60,12 +60,14 @@ jobs: # make clean # pip install . ################## Use this when you want to use local wheel installation through dist ###################### - # make dist - # pip install dist/* + make dist + pip freeze | xargs pip uninstall -y # remove all the packages installed through pip + pip install dist/* ############################################################################# # python setup.py develop # pip install -i https://test.pypi.org/simple/ structured-predictions==0.0.6 - pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple structured-predictions + #### To install from TestPyPi + # pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple structured-predictions # pip install -i https://test.pypi.org/simple/ structured-predictions # python tests/tests_DIOKR/Demo_DeepIOKR_bibtex.py - name: Test with pytest @@ -73,6 +75,6 @@ jobs: pip install pytest pytest tests/tests_OK3/test_tree_clf_and_reg.py tests/tests_OK3/test_complementary.py pytest tests/tests_DIOKR - python tests/tests_IOKR/ISOKR.py + # python tests/tests_IOKR/ISOKR.py # python tests/tests_IOKR/SISOKR.py # pytest tests/tests_IOKR diff --git a/requirements-1.txt b/requirements-1.txt deleted file mode 100644 index 9a996c1cc..000000000 --- a/requirements-1.txt +++ /dev/null @@ -1,70 +0,0 @@ -setuptools -wheel -oldest-supported-numpy -Cython==0.29.36 -# scipy - -# absl-py==0.13.0 -# astunparse==1.6.3 -# attrs==21.4.0 -# cachetools==4.2.2 -# certifi==2021.5.30 -# chardet==4.0.0 -# cvxopt==1.2.6 -# cycler==0.10.0 -# Cython==0.29.23 -# # Cython -# flatbuffers==1.12 -# gast==0.4.0 -# ghalton==0.6.2 -# google-auth==1.32.0 -# google-auth-oauthlib==0.4.4 -# google-pasta==0.2.0 -# grpcio==1.34.1 -# h5py==3.1.0 -# idna==2.10 -# iniconfig==1.1.1 -# joblib==1.0.1 -# keras-nightly==2.5.0.dev2021032900 -# Keras-Preprocessing==1.1.2 -# kiwisolver==1.3.1 -# Markdown==3.3.4 -# matplotlib==3.4.2 -# numpy==1.19.5 -# # numpy>=1.20.0 -# oauthlib==3.1.1 -# # operalib==0.2b27 -# opt-einsum==3.3.0 -# packaging==21.3 -# pandas==1.2.4 -# Pillow==8.2.0 -# pluggy==1.0.0 -# protobuf==3.17.3 -# py==1.11.0 -# pyasn1==0.4.8 -# pyasn1-modules==0.2.8 -# pyparsing==2.4.7 -# pytest==7.0.0 -# python-dateutil==2.8.1 -# pytz==2021.1 -# requests==2.25.1 -# requests-oauthlib==1.3.0 -# rsa==4.7.2 -# scikit-learn==0.24.2 -# scipy==1.7.0 -# six==1.15.0 - -# sobol-seq==0.2.0 -# tensorboard==2.5.0 -# tensorboard-data-server==0.6.1 -# tensorboard-plugin-wit==1.8.0 -# tensorflow==2.5.0 -# tensorflow-estimator==2.5.0 -# termcolor==1.1.0 -# threadpoolctl==2.1.0 -# tomli==2.0.0 -# torch==1.9.0 -# typing-extensions==3.7.4.3 -# urllib3==1.26.5 -# Werkzeug==2.0.1 -# wrapt==1.12.1 From 59e620d4ccf5da7f0f1aee1921ef44b3bf35f2dc Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 22:49:57 +0100 Subject: [PATCH 26/33] Testing Python 3.6 --- .github/workflows/pytest_cp36.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/pytest_cp36.yml b/.github/workflows/pytest_cp36.yml index 698fb5d6f..146ac7af0 100644 --- a/.github/workflows/pytest_cp36.yml +++ b/.github/workflows/pytest_cp36.yml @@ -39,7 +39,7 @@ jobs: # # stop the build if there are Python syntax errors or undefined names # flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics # # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide - # flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics + # flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 ---statistics # - name: Test with pytest # run: | # pip install pytest From 7bb838fbfab55d0273ae6c96cbe4cf3f496ed211 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 22:56:36 +0100 Subject: [PATCH 27/33] Testing Python 3.7-3.8, all platforms --- .github/workflows/pytest_cp36.yml | 4 ++-- .github/workflows/pytest_cp37.yml | 4 ++-- .github/workflows/pytest_cp38.yml | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/.github/workflows/pytest_cp36.yml b/.github/workflows/pytest_cp36.yml index 146ac7af0..5972ed583 100644 --- a/.github/workflows/pytest_cp36.yml +++ b/.github/workflows/pytest_cp36.yml @@ -2,8 +2,8 @@ name: pytesting 3.6 on: push: - # branches-ignore: - # - "main" + branches-ignore: + - "main" # # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/.github/workflows/pytest_cp37.yml b/.github/workflows/pytest_cp37.yml index 98194e089..0749006a8 100644 --- a/.github/workflows/pytest_cp37.yml +++ b/.github/workflows/pytest_cp37.yml @@ -21,8 +21,8 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - os: [ubuntu-latest] - # os: [macos-latest, ubuntu-latest, windows-latest] + # os: [ubuntu-latest] + os: [macos-latest, ubuntu-latest, windows-latest] python: ['3.7',] env: OS: ${{ matrix.os }} diff --git a/.github/workflows/pytest_cp38.yml b/.github/workflows/pytest_cp38.yml index d4ad90871..930b39d17 100644 --- a/.github/workflows/pytest_cp38.yml +++ b/.github/workflows/pytest_cp38.yml @@ -20,8 +20,8 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - os: [ubuntu-latest] - # os: [macos-latest, ubuntu-latest, windows-latest] + # os: [ubuntu-latest] + os: [macos-latest, ubuntu-latest, windows-latest] python: ['3.8',] env: OS: ${{ matrix.os }} From 467231239dcc96fc84560c9b86c25242099e1b26 Mon Sep 17 00:00:00 2001 From: yohila Date: Mon, 8 Jan 2024 23:27:49 +0100 Subject: [PATCH 28/33] Testing Python 3.7 till 3.11, unbutu & MacOS --- .github/workflows/pytest_cp310.yml | 7 ++++--- .github/workflows/pytest_cp311.yml | 7 ++++--- .github/workflows/pytest_cp37.yml | 3 ++- .github/workflows/pytest_cp38.yml | 3 ++- .github/workflows/pytest_cp39.yml | 7 ++++--- 5 files changed, 16 insertions(+), 11 deletions(-) diff --git a/.github/workflows/pytest_cp310.yml b/.github/workflows/pytest_cp310.yml index feb7076f1..738144aab 100644 --- a/.github/workflows/pytest_cp310.yml +++ b/.github/workflows/pytest_cp310.yml @@ -2,8 +2,8 @@ name: pytesting 3.10 on: push: - branches-ignore: - - "main" + # branches-ignore: + # - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' @@ -16,8 +16,9 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - os: [ubuntu-latest] + # os: [ubuntu-latest] # os: [macos-latest, ubuntu-latest, windows-latest] + os: [macos-latest, ubuntu-latest] python: ['3.10',] env: OS: ${{ matrix.os }} diff --git a/.github/workflows/pytest_cp311.yml b/.github/workflows/pytest_cp311.yml index aa949bbe0..9c75112b4 100644 --- a/.github/workflows/pytest_cp311.yml +++ b/.github/workflows/pytest_cp311.yml @@ -2,8 +2,8 @@ name: pytesting 3.11 on: push: - branches-ignore: - - "main" + # branches-ignore: + # - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' @@ -16,8 +16,9 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - os: [ubuntu-latest] + # os: [ubuntu-latest] # os: [macos-latest, ubuntu-latest, windows-latest] + os: [macos-latest, ubuntu-latest] python: ['3.11',] env: OS: ${{ matrix.os }} diff --git a/.github/workflows/pytest_cp37.yml b/.github/workflows/pytest_cp37.yml index 0749006a8..4ea4aec3c 100644 --- a/.github/workflows/pytest_cp37.yml +++ b/.github/workflows/pytest_cp37.yml @@ -22,7 +22,8 @@ jobs: strategy: matrix: # os: [ubuntu-latest] - os: [macos-latest, ubuntu-latest, windows-latest] + # os: [macos-latest, ubuntu-latest, windows-latest] + os: [macos-latest, ubuntu-latest] python: ['3.7',] env: OS: ${{ matrix.os }} diff --git a/.github/workflows/pytest_cp38.yml b/.github/workflows/pytest_cp38.yml index 930b39d17..6a7e1210b 100644 --- a/.github/workflows/pytest_cp38.yml +++ b/.github/workflows/pytest_cp38.yml @@ -21,7 +21,8 @@ jobs: strategy: matrix: # os: [ubuntu-latest] - os: [macos-latest, ubuntu-latest, windows-latest] + # os: [macos-latest, ubuntu-latest, windows-latest] + os: [macos-latest, ubuntu-latest] python: ['3.8',] env: OS: ${{ matrix.os }} diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index eb3889a11..ab9b10970 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -6,8 +6,8 @@ name: pytesting 3.9 on: push: - branches-ignore: - - "main" + # branches-ignore: + # - "main" # # branches: [ main ] schedule: - cron: '0 0 1 * *' @@ -20,8 +20,9 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - os: [ubuntu-latest] + # os: [ubuntu-latest] # os: [macos-latest, ubuntu-latest, windows-latest] + os: [macos-latest, ubuntu-latest] python: ['3.9',] env: OS: ${{ matrix.os }} From 6e4c051c4bdabe4af34026e20e6927cf12177cb1 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 9 Jan 2024 09:49:07 +0100 Subject: [PATCH 29/33] Genrating Python Wheels for MacOS --- .github/workflows/build_wheels_Manul.yml | 6 +++--- .github/workflows/pytest_cp310.yml | 4 ++-- .github/workflows/pytest_cp311.yml | 4 ++-- .github/workflows/pytest_cp37.yml | 4 ++-- .github/workflows/pytest_cp38.yml | 4 ++-- .github/workflows/pytest_cp39.yml | 4 ++-- 6 files changed, 13 insertions(+), 13 deletions(-) diff --git a/.github/workflows/build_wheels_Manul.yml b/.github/workflows/build_wheels_Manul.yml index d74585077..8089b9752 100644 --- a/.github/workflows/build_wheels_Manul.yml +++ b/.github/workflows/build_wheels_Manul.yml @@ -2,8 +2,8 @@ name: Generating Wheels on: push: - branches-ignore: - - "main" + # branches-ignore: + # - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' @@ -18,7 +18,7 @@ jobs: matrix: os: [macos-latest] # os: [macos-latest, ubuntu-latest, windows-latest] - python: ['3.7', '3.8', '3.9'] + python: ['3.7', '3.8', '3.9', '3.10', '3.11'] env: OS: ${{ matrix.os }} PYTHON: ${{ matrix.python }} diff --git a/.github/workflows/pytest_cp310.yml b/.github/workflows/pytest_cp310.yml index 738144aab..4e076efbf 100644 --- a/.github/workflows/pytest_cp310.yml +++ b/.github/workflows/pytest_cp310.yml @@ -2,8 +2,8 @@ name: pytesting 3.10 on: push: - # branches-ignore: - # - "main" + branches-ignore: + - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/.github/workflows/pytest_cp311.yml b/.github/workflows/pytest_cp311.yml index 9c75112b4..6199633cc 100644 --- a/.github/workflows/pytest_cp311.yml +++ b/.github/workflows/pytest_cp311.yml @@ -2,8 +2,8 @@ name: pytesting 3.11 on: push: - # branches-ignore: - # - "main" + branches-ignore: + - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/.github/workflows/pytest_cp37.yml b/.github/workflows/pytest_cp37.yml index 4ea4aec3c..5adda3d94 100644 --- a/.github/workflows/pytest_cp37.yml +++ b/.github/workflows/pytest_cp37.yml @@ -7,8 +7,8 @@ name: pytesting 3.7 on: push: ### This will ignore the testing - # branches-ignore: - # - "main" + branches-ignore: + - "main" # # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/.github/workflows/pytest_cp38.yml b/.github/workflows/pytest_cp38.yml index 6a7e1210b..bbd7b1889 100644 --- a/.github/workflows/pytest_cp38.yml +++ b/.github/workflows/pytest_cp38.yml @@ -6,8 +6,8 @@ name: pytesting 3.8 on: push: - # branches-ignore: - # - "main" + branches-ignore: + - "main" # branches: [ main ] schedule: - cron: '0 0 1 * *' diff --git a/.github/workflows/pytest_cp39.yml b/.github/workflows/pytest_cp39.yml index ab9b10970..baae4dc93 100644 --- a/.github/workflows/pytest_cp39.yml +++ b/.github/workflows/pytest_cp39.yml @@ -6,8 +6,8 @@ name: pytesting 3.9 on: push: - # branches-ignore: - # - "main" + branches-ignore: + - "main" # # branches: [ main ] schedule: - cron: '0 0 1 * *' From 6e040c18c793bb4b81cd6e7e7d1186cabbe1c70b Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 9 Jan 2024 09:52:49 +0100 Subject: [PATCH 30/33] Genrating Python Wheels for MacOS --- .github/workflows/build_wheels_Manul.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/build_wheels_Manul.yml b/.github/workflows/build_wheels_Manul.yml index 8089b9752..273011c27 100644 --- a/.github/workflows/build_wheels_Manul.yml +++ b/.github/workflows/build_wheels_Manul.yml @@ -2,6 +2,7 @@ name: Generating Wheels on: push: + # To ignore main branch # branches-ignore: # - "main" # branches: [ main ] From f80869d988fb928b1eda32d90b7dbc93697d0855 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 9 Jan 2024 09:59:05 +0100 Subject: [PATCH 31/33] Genrating Python Wheels for MacOS --- .github/workflows/build_wheels_Manul.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/build_wheels_Manul.yml b/.github/workflows/build_wheels_Manul.yml index 273011c27..0b3bf191c 100644 --- a/.github/workflows/build_wheels_Manul.yml +++ b/.github/workflows/build_wheels_Manul.yml @@ -19,7 +19,7 @@ jobs: matrix: os: [macos-latest] # os: [macos-latest, ubuntu-latest, windows-latest] - python: ['3.7', '3.8', '3.9', '3.10', '3.11'] + python: ['3.7', '3.8', '3.9', '3.10', '3.11', '3.12'] env: OS: ${{ matrix.os }} PYTHON: ${{ matrix.python }} From 430ca7c4387bdf6608c5d7b71a79b673cc070220 Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 9 Jan 2024 10:03:38 +0100 Subject: [PATCH 32/33] Genrating Python Wheels for Windows --- .github/workflows/build_wheels_Manul.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/build_wheels_Manul.yml b/.github/workflows/build_wheels_Manul.yml index 0b3bf191c..d7d0f100b 100644 --- a/.github/workflows/build_wheels_Manul.yml +++ b/.github/workflows/build_wheels_Manul.yml @@ -17,9 +17,9 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - os: [macos-latest] + os: [windows-latest] # os: [macos-latest, ubuntu-latest, windows-latest] - python: ['3.7', '3.8', '3.9', '3.10', '3.11', '3.12'] + python: ['3.7', '3.8', '3.9', '3.10', '3.11'] # Gives error for Python 3.12 env: OS: ${{ matrix.os }} PYTHON: ${{ matrix.python }} From cbec1bee05f984e021812f5de055284ba1c0f03c Mon Sep 17 00:00:00 2001 From: yohila Date: Tue, 9 Jan 2024 10:16:34 +0100 Subject: [PATCH 33/33] Genrating Python Wheels for all OS -- Version 0.1.2 --- .github/workflows/build_wheels_Manul.yml | 4 ++-- setup.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/build_wheels_Manul.yml b/.github/workflows/build_wheels_Manul.yml index d7d0f100b..150ff08f1 100644 --- a/.github/workflows/build_wheels_Manul.yml +++ b/.github/workflows/build_wheels_Manul.yml @@ -17,8 +17,8 @@ jobs: runs-on: ${{ matrix.os }} strategy: matrix: - os: [windows-latest] - # os: [macos-latest, ubuntu-latest, windows-latest] + # os: [windows-latest] + os: [macos-latest, ubuntu-latest, windows-latest] python: ['3.7', '3.8', '3.9', '3.10', '3.11'] # Gives error for Python 3.12 env: OS: ${{ matrix.os }} diff --git a/setup.py b/setup.py index 766db33fb..debbdec79 100644 --- a/setup.py +++ b/setup.py @@ -61,7 +61,7 @@ setup( name='structured-predictions', - version='0.1.1', + version='0.1.2', description='Structured-Predictions', # long_description=README, long_description_content_type='text/markdown',

Raw output: _tree.c