diff --git a/SOMPY.egg-info/PKG-INFO b/SOMPY.egg-info/PKG-INFO deleted file mode 100644 index 59a7e68..0000000 --- a/SOMPY.egg-info/PKG-INFO +++ /dev/null @@ -1,10 +0,0 @@ -Metadata-Version: 1.0 -Name: SOMPY -Version: 1.0 -Summary: Self Organizing Maps Package -Home-page: UNKNOWN -Author: Vahid Moosavi and Sebastian Packmann -Author-email: UNKNOWN -License: UNKNOWN -Description: UNKNOWN -Platform: UNKNOWN diff --git a/SOMPY.egg-info/SOURCES.txt b/SOMPY.egg-info/SOURCES.txt deleted file mode 100644 index eefc78e..0000000 --- a/SOMPY.egg-info/SOURCES.txt +++ /dev/null @@ -1,20 +0,0 @@ -setup.py -SOMPY.egg-info/PKG-INFO -SOMPY.egg-info/SOURCES.txt -SOMPY.egg-info/dependency_links.txt -SOMPY.egg-info/requires.txt -SOMPY.egg-info/top_level.txt -sompy/__init__.py -sompy/codebook.py -sompy/decorators.py -sompy/neighborhood.py -sompy/normalization.py -sompy/sompy.py -sompy/visualization/__init__.py -sompy/visualization/bmuhits.py -sompy/visualization/dotmap.py -sompy/visualization/histogram.py -sompy/visualization/hitmap.py -sompy/visualization/mapview.py -sompy/visualization/umatrix.py -sompy/visualization/view.py \ No newline at end of file diff --git a/SOMPY.egg-info/dependency_links.txt b/SOMPY.egg-info/dependency_links.txt deleted file mode 100644 index 8b13789..0000000 --- a/SOMPY.egg-info/dependency_links.txt +++ /dev/null @@ -1 +0,0 @@ - diff --git a/SOMPY.egg-info/requires.txt b/SOMPY.egg-info/requires.txt deleted file mode 100644 index 5f16760..0000000 --- a/SOMPY.egg-info/requires.txt +++ /dev/null @@ -1,4 +0,0 @@ -numexpr >= 2.5 -numpy >= 1.7 -scikit-learn >= 0.16 -scipy >= 0.9 diff --git a/SOMPY.egg-info/top_level.txt b/SOMPY.egg-info/top_level.txt deleted file mode 100644 index c41ef42..0000000 --- a/SOMPY.egg-info/top_level.txt +++ /dev/null @@ -1 +0,0 @@ -sompy diff --git a/build/lib.linux-x86_64-2.7/sompy/__init__.py b/build/lib.linux-x86_64-2.7/sompy/__init__.py deleted file mode 100644 index 3b1e899..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/__init__.py +++ /dev/null @@ -1,31 +0,0 @@ - -from logging.config import dictConfig -import matplotlib - -#matplotlib.use('Agg') # Use whatever backend is available - -dictConfig({ - "version": 1, - "disable_existing_loggers": False, - "root": { - "level": "NOTSET", - "handlers": ["console"] - }, - "handlers": { - "console": { - "level": "DEBUG", - "class": "logging.StreamHandler", - "formatter": "basic" - } - }, - "formatters": { - "basic": { - "format": '%(message)s' - } - } -}) - - - -from .sompy import SOMFactory -from .visualization import * diff --git a/build/lib.linux-x86_64-2.7/sompy/codebook.py b/build/lib.linux-x86_64-2.7/sompy/codebook.py deleted file mode 100644 index b5e16c4..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/codebook.py +++ /dev/null @@ -1,173 +0,0 @@ -import numpy as np - -from sklearn.decomposition import PCA -#from sklearn.decomposition import RandomizedPCA# (randomizedpca is deprecated) -from .decorators import timeit - - -class InvalidNodeIndexError(Exception): - pass - - -class InvalidMapsizeError(Exception): - pass - - -class Codebook(object): - - def __init__(self, mapsize, lattice='rect'): - self.lattice = lattice - - if 2 == len(mapsize): - _size = [1, np.max(mapsize)] if 1 == np.min(mapsize) else mapsize - - elif 1 == len(mapsize): - _size = [1, mapsize[0]] - print('input was considered as the numbers of nodes') - print('map size is [{dlen},{dlen}]'.format(dlen=int(mapsize[0]/2))) - else: - raise InvalidMapsizeError( - "Mapsize is expected to be a 2 element list or a single int") - - self.mapsize = _size - self.nnodes = mapsize[0]*mapsize[1] - self.matrix = np.asarray(self.mapsize) - self.initialized = False - - @timeit() - def random_initialization(self, data): - """ - :param data: data to use for the initialization - :returns: initialized matrix with same dimension as input data - """ - mn = np.tile(np.min(data, axis=0), (self.nnodes, 1)) - mx = np.tile(np.max(data, axis=0), (self.nnodes, 1)) - self.matrix = mn + (mx-mn)*(np.random.rand(self.nnodes, data.shape[1])) - self.initialized = True - - @timeit() - def pca_linear_initialization(self, data): - """ - We initialize the map, just by using the first two first eigen vals and - eigenvectors - Further, we create a linear combination of them in the new map by - giving values from -1 to 1 in each - - X = UsigmaWT - XTX = Wsigma^2WT - T = XW = Usigma - - // Transformed by W EigenVector, can be calculated by multiplication - // PC matrix by eigenval too - // Further, we can get lower ranks by using just few of the eigen - // vevtors - - T(2) = U(2)sigma(2) = XW(2) ---> 2 is the number of selected - eigenvectors - - (*) Note that 'X' is the covariance matrix of original data - - :param data: data to use for the initialization - :returns: initialized matrix with same dimension as input data - """ - cols = self.mapsize[1] - coord = None - pca_components = None - - if np.min(self.mapsize) > 1: - coord = np.zeros((self.nnodes, 2)) - pca_components = 2 - - for i in range(0, self.nnodes): - coord[i, 0] = int(i / cols) # x - coord[i, 1] = int(i % cols) # y - - elif np.min(self.mapsize) == 1: - coord = np.zeros((self.nnodes, 1)) - pca_components = 1 - - for i in range(0, self.nnodes): - coord[i, 0] = int(i % cols) # y - - mx = np.max(coord, axis=0) - mn = np.min(coord, axis=0) - coord = (coord - mn)/(mx-mn) - coord = (coord - .5)*2 - me = np.mean(data, 0) - data = (data - me) - tmp_matrix = np.tile(me, (self.nnodes, 1)) - - # Randomized PCA is scalable - #pca = RandomizedPCA(n_components=pca_components) # RandomizedPCA is deprecated. - pca = PCA(n_components=pca_components, svd_solver='randomized') - - pca.fit(data) - eigvec = pca.components_ - eigval = pca.explained_variance_ - norms = np.sqrt(np.einsum('ij,ij->i', eigvec, eigvec)) - eigvec = ((eigvec.T/norms)*eigval).T - - for j in range(self.nnodes): - for i in range(eigvec.shape[0]): - tmp_matrix[j, :] = tmp_matrix[j, :] + coord[j, i]*eigvec[i, :] - - self.matrix = np.around(tmp_matrix, decimals=6) - self.initialized = True - - def grid_dist(self, node_ind): - """ - Calculates grid distance based on the lattice type. - - :param node_ind: number between 0 and number of nodes-1. Depending on - the map size, starting from top left - :returns: matrix representing the distance matrix - """ - if self.lattice == 'rect': - return self._rect_dist(node_ind) - - elif self.lattice == 'hexa': - return self._hexa_dist(node_ind) - - def _hexa_dist(self, node_ind): - raise NotImplementedError() - - def _rect_dist(self, node_ind): - """ - Calculates the distance of the specified node to the other nodes in the - matrix, generating a distance matrix - - Ej. The distance matrix for the node_ind=5, that corresponds to - the_coord (1,1) - array([[2, 1, 2, 5], - [1, 0, 1, 4], - [2, 1, 2, 5], - [5, 4, 5, 8]]) - - :param node_ind: number between 0 and number of nodes-1. Depending on - the map size, starting from top left - :returns: matrix representing the distance matrix - """ - rows = self.mapsize[0] - cols = self.mapsize[1] - dist = None - - # bmu should be an integer between 0 to no_nodes - if 0 <= node_ind <= (rows*cols): - node_col = int(node_ind % cols) - node_row = int(node_ind / cols) - else: - raise InvalidNodeIndexError( - "Node index '%s' is invalid" % node_ind) - - if rows > 0 and cols > 0: - r = np.arange(0, rows, 1)[:, np.newaxis] - c = np.arange(0, cols, 1) - dist2 = (r-node_row)**2 + (c-node_col)**2 - - dist = dist2.ravel() - else: - raise InvalidMapsizeError( - "One or both of the map dimensions are invalid. " - "Cols '%s', Rows '%s'".format(cols=cols, rows=rows)) - - return dist diff --git a/build/lib.linux-x86_64-2.7/sompy/decorators.py b/build/lib.linux-x86_64-2.7/sompy/decorators.py deleted file mode 100644 index a3ae0fc..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/decorators.py +++ /dev/null @@ -1,21 +0,0 @@ -import logging -from functools import wraps -from time import time - - -def timeit(log_level=logging.INFO, alternative_title=None): - def wrap(f): - @wraps(f) # keeps the f.__name__ outside the wrapper - def wrapped_f(*args, **kwargs): - t0 = time() - result = f(*args, **kwargs) - ts = round(time() - t0, 3) - - title = alternative_title or f.__name__ - logging.getLogger().log( - log_level, " %s took: %f seconds" % (title, ts)) - - return result - - return wrapped_f - return wrap diff --git a/build/lib.linux-x86_64-2.7/sompy/neighborhood.py b/build/lib.linux-x86_64-2.7/sompy/neighborhood.py deleted file mode 100644 index a4d2c9c..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/neighborhood.py +++ /dev/null @@ -1,48 +0,0 @@ -import numpy as np -import inspect -import sys - -small = .000000000001 - - -class NeighborhoodFactory(object): - - @staticmethod - def build(neighborhood_func): - for name, obj in inspect.getmembers(sys.modules[__name__]): - if inspect.isclass(obj): - if hasattr(obj, 'name') and neighborhood_func == obj.name: - return obj() - else: - raise Exception( - "Unsupported neighborhood function '%s'" % neighborhood_func) - - -class GaussianNeighborhood(object): - - name = 'gaussian' - - @staticmethod - def calculate(distance_matrix, radius, dim): - return np.exp(-1.0*distance_matrix/(2.0*radius**2)).reshape(dim, dim) - - def __call__(self, *args, **kwargs): - return self.calculate(*args) - - -class BubbleNeighborhood(object): - - name = 'bubble' - - @staticmethod - def calculate(distance_matrix, radius, dim): - def l(a, b): - c = np.zeros(b.shape) - c[a-b >= 0] = 1 - return c - - return l(radius, - np.sqrt(distance_matrix.flatten())).reshape(dim, dim) + small - - def __call__(self, *args, **kwargs): - return self.calculate(*args) diff --git a/build/lib.linux-x86_64-2.7/sompy/normalization.py b/build/lib.linux-x86_64-2.7/sompy/normalization.py deleted file mode 100644 index b641b94..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/normalization.py +++ /dev/null @@ -1,74 +0,0 @@ -import numpy as np -import sys -import inspect - - -class NormalizatorFactory(object): - - @staticmethod - def build(type_name): - for name, obj in inspect.getmembers(sys.modules[__name__]): - if inspect.isclass(obj): - if hasattr(obj, 'name') and type_name == obj.name: - return obj() - else: - raise Exception("Unknown normalization type '%s'" % type_name) - - -class Normalizator(object): - - def normalize(self, data): - raise NotImplementedError() - - def normalize_by(self, raw_data, data): - raise NotImplementedError() - - def denormalize_by(self, raw_data, data): - raise NotImplementedError() - - -class VarianceNormalizator(Normalizator): - - name = 'var' - - def _mean_and_standard_dev(self, data): - return np.mean(data, axis=0), np.std(data, axis=0) - - def normalize(self, data): - me, st = self._mean_and_standard_dev(data) - st[st == 0] = 1 # prevent: when sd = 0, normalized result = NaN - return (data-me)/st - - def normalize_by(self, raw_data, data): - me, st = self._mean_and_standard_dev(raw_data) - st[st == 0] = 1 # prevent: when sd = 0, normalized result = NaN - return (data-me)/st - - def denormalize_by(self, data_by, n_vect): - me, st = self._mean_and_standard_dev(data_by) - return n_vect * st + me - - -class RangeNormalizator(Normalizator): - - name = 'range' - - -class LogNormalizator(Normalizator): - - name = 'log' - - -class LogisticNormalizator(Normalizator): - - name = 'logistic' - - -class HistDNormalizator(Normalizator): - - name = 'histd' - - -class HistCNormalizator(Normalizator): - - name = 'histc' diff --git a/build/lib.linux-x86_64-2.7/sompy/sompy.py b/build/lib.linux-x86_64-2.7/sompy/sompy.py deleted file mode 100644 index 3dc9514..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/sompy.py +++ /dev/null @@ -1,703 +0,0 @@ -# -*- coding: utf-8 -*- - -# Author: Vahid Moosavi (sevamoo@gmail.com) -# Chair For Computer Aided Architectural Design, ETH Zurich -# Future Cities Lab -# www.vahidmoosavi.com - -# Contributor: Sebastian Packmann (sebastian.packmann@gmail.com) - - -import tempfile -import os -import itertools -import logging - -import numpy as np - -from time import time -from multiprocessing.dummy import Pool -from multiprocessing import cpu_count -from scipy.sparse import csr_matrix -from sklearn import neighbors -from sklearn.externals.joblib import Parallel, delayed, load, dump - -from .decorators import timeit -from .codebook import Codebook -from .neighborhood import NeighborhoodFactory -from .normalization import NormalizatorFactory - -#lbugnon -import sompy,ipdb -# - -class ComponentNamesError(Exception): - pass - - -class LabelsError(Exception): - pass - - -class SOMFactory(object): - - @staticmethod - def build(data, - mapsize=None, - mask=None, - mapshape='planar', - lattice='rect', - normalization='var', - initialization='pca', - neighborhood='gaussian', - training='batch', - name='sompy', - component_names=None): - """ - :param data: data to be clustered, represented as a matrix of n rows, - as inputs and m cols as input features - :param neighborhood: neighborhood object calculator. Options are: - - gaussian - - bubble - - manhattan (not implemented yet) - - cut_gaussian (not implemented yet) - - epanechicov (not implemented yet) - - :param normalization: normalizer object calculator. Options are: - - var - - :param mapsize: tuple/list defining the dimensions of the som. - If single number is provided is considered as the number of nodes. - :param mask: mask - :param mapshape: shape of the som. Options are: - - planar - - toroid (not implemented yet) - - cylinder (not implemented yet) - - :param lattice: type of lattice. Options are: - - rect - - hexa (not implemented yet) - - :param initialization: method to be used for initialization of the som. - Options are: - - pca - - random - - :param name: name used to identify the som - :param training: Training mode (seq, batch) - """ - if normalization: - normalizer = NormalizatorFactory.build(normalization) - else: - normalizer = None - neighborhood_calculator = NeighborhoodFactory.build(neighborhood) - return SOM(data, neighborhood_calculator, normalizer, mapsize, mask, - mapshape, lattice, initialization, training, name, component_names) - - -class SOM(object): - - def __init__(self, - data, - neighborhood, - normalizer=None, - mapsize=None, - mask=None, - mapshape='planar', - lattice='rect', - initialization='pca', - training='batch', - name='sompy', - component_names=None): - """ - Self Organizing Map - - :param data: data to be clustered, represented as a matrix of n rows, - as inputs and m cols as input features - :param neighborhood: neighborhood object calculator. - :param normalizer: normalizer object calculator. - :param mapsize: tuple/list defining the dimensions of the som. If - single number is provided is considered as the number of nodes. - :param mask: mask - :param mapshape: shape of the som. - :param lattice: type of lattice. - :param initialization: method to be used for initialization of the som. - :param name: name used to identify the som - :param training: Training mode (seq, batch) - """ - self._data = normalizer.normalize(data) if normalizer else data - self._normalizer = normalizer - self._dim = data.shape[1] - self._dlen = data.shape[0] - self._dlabel = None - self._bmu = None - - self.name = name - self.data_raw = data - self.neighborhood = neighborhood - self.mapshape = mapshape - self.initialization = initialization - self.mask = mask or np.ones([1, self._dim]) - mapsize = self.calculate_map_size(lattice) if not mapsize else mapsize - self.codebook = Codebook(mapsize, lattice) - self.training = training - self._component_names = self.build_component_names() if component_names is None else [component_names] - self._distance_matrix = self.calculate_map_dist() - - @property - def component_names(self): - return self._component_names - - @component_names.setter - def component_names(self, compnames): - if self._dim == len(compnames): - self._component_names = np.asarray(compnames)[np.newaxis, :] - else: - raise ComponentNamesError('Component names should have the same ' - 'size as the data dimension/features') - - def build_component_names(self): - cc = ['Variable-' + str(i+1) for i in range(0, self._dim)] - return np.asarray(cc)[np.newaxis, :] - - @property - def data_labels(self): - return self._dlabel - - @data_labels.setter - def data_labels(self, labels): - """ - Set labels of the training data, it should be in the format of a list - of strings - """ - if labels.shape == (1, self._dlen): - label = labels.T - elif labels.shape == (self._dlen, 1): - label = labels - elif labels.shape == (self._dlen,): - label = labels[:, np.newaxis] - else: - raise LabelsError('wrong label format') - - self._dlabel = label - - def build_data_labels(self): - cc = ['dlabel-' + str(i) for i in range(0, self._dlen)] - return np.asarray(cc)[:, np.newaxis] - - def calculate_map_dist(self): - """ - Calculates the grid distance, which will be used during the training - steps. It supports only planar grids for the moment - """ - nnodes = self.codebook.nnodes - - distance_matrix = np.zeros((nnodes, nnodes)) - for i in range(nnodes): - distance_matrix[i] = self.codebook.grid_dist(i).reshape(1, nnodes) - return distance_matrix - - @timeit() - def train(self, - n_job=1, - shared_memory=False, - verbose='info', - train_rough_len=None, - train_rough_radiusin=None, - train_rough_radiusfin=None, - train_finetune_len=None, - train_finetune_radiusin=None, - train_finetune_radiusfin=None, - train_len_factor=1, - maxtrainlen=np.Inf): - """ - Trains the som - - :param n_job: number of jobs to use to parallelize the traning - :param shared_memory: flag to active shared memory - :param verbose: verbosity, could be 'debug', 'info' or None - :param train_len_factor: Factor that multiply default training lenghts (similar to "training" parameter in the matlab version). (lbugnon) - """ - logging.root.setLevel( - getattr(logging, verbose.upper()) if verbose else logging.ERROR) - - logging.info(" Training...") - logging.debug(( - "--------------------------------------------------------------\n" - " details: \n" - " > data len is {data_len} and data dimension is {data_dim}\n" - " > map size is {mpsz0},{mpsz1}\n" - " > array size in log10 scale is {array_size}\n" - " > number of jobs in parallel: {n_job}\n" - " -------------------------------------------------------------\n") - .format(data_len=self._dlen, - data_dim=self._dim, - mpsz0=self.codebook.mapsize[0], - mpsz1=self.codebook.mapsize[1], - array_size=np.log10( - self._dlen * self.codebook.nnodes * self._dim), - n_job=n_job)) - - if self.initialization == 'random': - self.codebook.random_initialization(self._data) - - elif self.initialization == 'pca': - self.codebook.pca_linear_initialization(self._data) - - self.rough_train(njob=n_job, shared_memory=shared_memory, trainlen=train_rough_len, - radiusin=train_rough_radiusin, radiusfin=train_rough_radiusfin,trainlen_factor=train_len_factor,maxtrainlen=maxtrainlen) - self.finetune_train(njob=n_job, shared_memory=shared_memory, trainlen=train_finetune_len, - radiusin=train_finetune_radiusin, radiusfin=train_finetune_radiusfin,trainlen_factor=train_len_factor,maxtrainlen=maxtrainlen) - logging.debug( - " --------------------------------------------------------------") - logging.info(" Final quantization error: %f" % np.mean(self._bmu[1])) - - def _calculate_ms_and_mpd(self): - mn = np.min(self.codebook.mapsize) - max_s = max(self.codebook.mapsize[0], self.codebook.mapsize[1]) - - if mn == 1: - mpd = float(self.codebook.nnodes*10)/float(self._dlen) - else: - mpd = float(self.codebook.nnodes)/float(self._dlen) - ms = max_s/2.0 if mn == 1 else max_s - - return ms, mpd - - def rough_train(self, njob=1, shared_memory=False, trainlen=None, radiusin=None, radiusfin=None,trainlen_factor=1,maxtrainlen=np.Inf): - logging.info(" Rough training...") - - ms, mpd = self._calculate_ms_and_mpd() - #lbugnon: add maxtrainlen - trainlen = min(int(np.ceil(30*mpd)),maxtrainlen) if not trainlen else trainlen - print("maxtrainlen %d",maxtrainlen) - #lbugnon: add trainlen_factor - trainlen=int(trainlen*trainlen_factor) - - if self.initialization == 'random': - radiusin = max(1, np.ceil(ms/3.)) if not radiusin else radiusin - radiusfin = max(1, radiusin/6.) if not radiusfin else radiusfin - - elif self.initialization == 'pca': - radiusin = max(1, np.ceil(ms/8.)) if not radiusin else radiusin - radiusfin = max(1, radiusin/4.) if not radiusfin else radiusfin - - self._batchtrain(trainlen, radiusin, radiusfin, njob, shared_memory) - - def finetune_train(self, njob=1, shared_memory=False, trainlen=None, radiusin=None, radiusfin=None,trainlen_factor=1,maxtrainlen=np.Inf): - logging.info(" Finetune training...") - - ms, mpd = self._calculate_ms_and_mpd() - - #lbugnon: add maxtrainlen - if self.initialization == 'random': - trainlen = min(int(np.ceil(50*mpd)),maxtrainlen) if not trainlen else trainlen - radiusin = max(1, ms/12.) if not radiusin else radiusin # from radius fin in rough training - radiusfin = max(1, radiusin/25.) if not radiusfin else radiusfin - - elif self.initialization == 'pca': - trainlen = min(int(np.ceil(40*mpd)),maxtrainlen) if not trainlen else trainlen - radiusin = max(1, np.ceil(ms/8.)/4) if not radiusin else radiusin - radiusfin = 1 if not radiusfin else radiusfin # max(1, ms/128) - - print("maxtrainlen %d",maxtrainlen) - - #lbugnon: add trainlen_factor - trainlen=int(trainlen_factor*trainlen) - - - self._batchtrain(trainlen, radiusin, radiusfin, njob, shared_memory) - - def _batchtrain(self, trainlen, radiusin, radiusfin, njob=1, - shared_memory=False): - radius = np.linspace(radiusin, radiusfin, trainlen) - - if shared_memory: - data = self._data - data_folder = tempfile.mkdtemp() - data_name = os.path.join(data_folder, 'data') - dump(data, data_name) - data = load(data_name, mmap_mode='r') - - else: - data = self._data - - bmu = None - - # X2 is part of euclidean distance (x-y)^2 = x^2 +y^2 - 2xy that we use - # for each data row in bmu finding. - # Since it is a fixed value we can skip it during bmu finding for each - # data point, but later we need it calculate quantification error - fixed_euclidean_x2 = np.einsum('ij,ij->i', data, data) - - logging.info(" radius_ini: %f , radius_final: %f, trainlen: %d\n" % - (radiusin, radiusfin, trainlen)) - - for i in range(trainlen): - t1 = time() - neighborhood = self.neighborhood.calculate( - self._distance_matrix, radius[i], self.codebook.nnodes) - bmu = self.find_bmu(data, njb=njob) - self.codebook.matrix = self.update_codebook_voronoi(data, bmu, - neighborhood) - - #lbugnon: ojo! aca el bmy[1] a veces da negativo, y despues de eso se rompe...hay algo raro ahi - qerror = (i + 1, round(time() - t1, 3), - np.mean(np.sqrt(bmu[1] + fixed_euclidean_x2))) #lbugnon: ojo aca me tiró un warning, revisar (commit sinc: 965666d3d4d93bcf48e8cef6ea2c41a018c1cb83 ) - #lbugnon - #ipdb.set_trace() - # - logging.info( - " epoch: %d ---> elapsed time: %f, quantization error: %f\n" % - qerror) - - bmu[1] = np.sqrt(bmu[1] + fixed_euclidean_x2) - self._bmu = bmu - - @timeit(logging.DEBUG) - def find_bmu(self, input_matrix, njb=1, nth=1): - """ - Finds the best matching unit (bmu) for each input data from the input - matrix. It does all at once parallelizing the calculation instead of - going through each input and running it against the codebook. - - :param input_matrix: numpy matrix representing inputs as rows and - features/dimension as cols - :param njb: number of jobs to parallelize the search - :returns: the best matching unit for each input - """ - dlen = input_matrix.shape[0] - y2 = np.einsum('ij,ij->i', self.codebook.matrix, self.codebook.matrix) - if njb == -1: - njb = cpu_count() - - pool = Pool(njb) - chunk_bmu_finder = _chunk_based_bmu_find - - def row_chunk(part): - return part * dlen // njb - - def col_chunk(part): - return min((part+1)*dlen // njb, dlen) - - chunks = [input_matrix[row_chunk(i):col_chunk(i)] for i in range(njb)] - b = pool.map(lambda chk: chunk_bmu_finder(chk, self.codebook.matrix, y2, nth=nth), chunks) - pool.close() - pool.join() - bmu = np.asarray(list(itertools.chain(*b))).T - del b - return bmu - - @timeit(logging.DEBUG) - def update_codebook_voronoi(self, training_data, bmu, neighborhood): - """ - Updates the weights of each node in the codebook that belongs to the - bmu's neighborhood. - - First finds the Voronoi set of each node. It needs to calculate a - smaller matrix. - Super fast comparing to classic batch training algorithm, it is based - on the implemented algorithm in som toolbox for Matlab by Helsinky - University. - - :param training_data: input matrix with input vectors as rows and - vector features as cols - :param bmu: best matching unit for each input data. Has shape of - (2, dlen) where first row has bmu indexes - :param neighborhood: matrix representing the neighborhood of each bmu - - :returns: An updated codebook that incorporates the learnings from the - input data - """ - row = bmu[0].astype(int) - col = np.arange(self._dlen) - val = np.tile(1, self._dlen) - P = csr_matrix((val, (row, col)), shape=(self.codebook.nnodes, - self._dlen)) - S = P.dot(training_data) - - # neighborhood has nnodes*nnodes and S has nnodes*dim - # ---> Nominator has nnodes*dim - nom = neighborhood.T.dot(S) - nV = P.sum(axis=1).reshape(1, self.codebook.nnodes) - denom = nV.dot(neighborhood.T).reshape(self.codebook.nnodes, 1) - new_codebook = np.divide(nom, denom) - - return np.around(new_codebook, decimals=6) - - def project_data(self, data): - """ - Projects a data set to a trained SOM. It is based on nearest - neighborhood search module of scikitlearn, but it is not that fast. - """ - clf = neighbors.KNeighborsClassifier(n_neighbors=1) - labels = np.arange(0, self.codebook.matrix.shape[0]) - clf.fit(self.codebook.matrix, labels) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - data = self._normalizer.normalize_by(self.data_raw, data) - - return clf.predict(data) - - def predict_by(self, data, target, k=5, wt='distance'): - # here it is assumed that target is the last column in the codebook - # and data has dim-1 columns - dim = self.codebook.matrix.shape[1] - ind = np.arange(0, dim) - indX = ind[ind != target] - x = self.codebook.matrix[:, indX] - y = self.codebook.matrix[:, target] - n_neighbors = k - clf = neighbors.KNeighborsRegressor(n_neighbors, weights=wt) - clf.fit(x, y) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - dimdata = data.shape[1] - - if dimdata == dim: - data[:, target] = 0 - data = self._normalizer.normalize_by(self.data_raw, data) - data = data[:, indX] - - elif dimdata == dim-1: - data = self._normalizer.normalize_by(self.data_raw[:, indX], data) - - predicted_values = clf.predict(data) - predicted_values = self._normalizer.denormalize_by( - self.data_raw[:, target], predicted_values) - return predicted_values - - def predict(self, x_test, k=5, wt='distance'): - """ - Similar to SKlearn we assume that we have X_tr, Y_tr and X_test. Here - it is assumed that target is the last column in the codebook and data - has dim-1 columns - - :param x_test: input vector - :param k: number of neighbors to use - :param wt: method to use for the weights - (more detail in KNeighborsRegressor docs) - :returns: predicted values for the input data - """ - target = self.data_raw.shape[1]-1 - x_train = self.codebook.matrix[:, :target] - y_train = self.codebook.matrix[:, target] - clf = neighbors.KNeighborsRegressor(k, weights=wt) - clf.fit(x_train, y_train) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - x_test = self._normalizer.normalize_by( - self.data_raw[:, :target], x_test) - predicted_values = clf.predict(x_test) - - return self._normalizer.denormalize_by( - self.data_raw[:, target], predicted_values) - - def find_k_nodes(self, data, k=5): - from sklearn.neighbors import NearestNeighbors - # we find the k most similar nodes to the input vector - neighbor = NearestNeighbors(n_neighbors=k) - neighbor.fit(self.codebook.matrix) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - return neighbor.kneighbors( - self._normalizer.normalize_by(self.data_raw, data)) - - def bmu_ind_to_xy(self, bmu_ind): - """ - Translates a best matching unit index to the corresponding - matrix x,y coordinates. - - :param bmu_ind: node index of the best matching unit - (number of node from top left node) - :returns: corresponding (x,y) coordinate - """ - rows = self.codebook.mapsize[0] - cols = self.codebook.mapsize[1] - - # bmu should be an integer between 0 to no_nodes - out = np.zeros((bmu_ind.shape[0], 3)) - out[:, 2] = bmu_ind - out[:, 0] = rows-1-bmu_ind / cols - out[:, 0] = bmu_ind / cols - out[:, 1] = bmu_ind % cols - - return out.astype(int) - - def cluster(self, n_clusters=8): - import sklearn.cluster as clust - cl_labels = clust.KMeans(n_clusters=n_clusters).fit_predict( - self._normalizer.denormalize_by(self.data_raw, - self.codebook.matrix)) - self.cluster_labels = cl_labels - return cl_labels - - def predict_probability(self, data, target, k=5): - """ - Predicts probability of the input data to be target - - :param data: data to predict, it is assumed that 'target' is the last - column in the codebook, so data hould have dim-1 columns - :param target: target to predict probability - :param k: k parameter on KNeighborsRegressor - :returns: probability of data been target - """ - dim = self.codebook.matrix.shape[1] - ind = np.arange(0, dim) - indx = ind[ind != target] - x = self.codebook.matrix[:, indx] - y = self.codebook.matrix[:, target] - - clf = neighbors.KNeighborsRegressor(k, weights='distance') - clf.fit(x, y) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - dimdata = data.shape[1] - - if dimdata == dim: - data[:, target] = 0 - data = self._normalizer.normalize_by(self.data_raw, data) - data = data[:, indx] - - elif dimdata == dim-1: - data = self._normalizer.normalize_by(self.data_raw[:, indx], data) - - weights, ind = clf.kneighbors(data, n_neighbors=k, - return_distance=True) - weights = 1./weights - sum_ = np.sum(weights, axis=1) - weights = weights/sum_[:, np.newaxis] - labels = np.sign(self.codebook.matrix[ind, target]) - labels[labels >= 0] = 1 - - # for positives - pos_prob = labels.copy() - pos_prob[pos_prob < 0] = 0 - pos_prob *= weights - pos_prob = np.sum(pos_prob, axis=1)[:, np.newaxis] - - # for negatives - neg_prob = labels.copy() - neg_prob[neg_prob > 0] = 0 - neg_prob = neg_prob * weights * -1 - neg_prob = np.sum(neg_prob, axis=1)[:, np.newaxis] - - return np.concatenate((pos_prob, neg_prob), axis=1) - - def node_activation(self, data, target=None, wt='distance'): - weights, ind = None, None - - if not target: - clf = neighbors.KNeighborsClassifier( - n_neighbors=self.codebook.nnodes) - labels = np.arange(0, self.codebook.matrix.shape[0]) - clf.fit(self.codebook.matrix, labels) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - data = self._normalizer.normalize_by(self.data_raw, data) - weights, ind = clf.kneighbors(data) - - # Softmax function - weights = 1./weights - - return weights, ind - - def calculate_topographic_error(self): - bmus1 = self.find_bmu(self.data_raw, njb=1, nth=1) - bmus2 = self.find_bmu(self.data_raw, njb=1, nth=2) - bmus_gap = np.abs((self.bmu_ind_to_xy(np.array(bmus1[0]))[:, 0:2] - self.bmu_ind_to_xy(np.array(bmus2[0]))[:, 0:2]).sum(axis=1)) - return np.mean(bmus_gap != 1) - - def calculate_map_size(self, lattice): - """ - Calculates the optimal map size given a dataset using eigenvalues and eigenvectors. Matlab ported - :lattice: 'rect' or 'hex' - :return: map sizes - """ - D = self.data_raw.copy() - dlen = D.shape[0] - dim = D.shape[1] - munits = np.ceil(5 * (dlen ** 0.5)) - A = np.ndarray(shape=[dim, dim]) + np.Inf - - for i in range(dim): - D[:, i] = D[:, i] - np.mean(D[np.isfinite(D[:, i]), i]) - - for i in range(dim): - for j in range(dim): - c = D[:, i] * D[:, j] - c = c[np.isfinite(c)] - A[i, j] = sum(c) / len(c) - A[j, i] = A[i, j] - - VS = np.linalg.eig(A) - eigval = sorted(np.linalg.eig(A)[0]) - if eigval[-1] == 0 or eigval[-2] * munits < eigval[-1]: - ratio = 1 - else: - ratio = np.sqrt(eigval[-1] / eigval[-2]) - - if lattice == "rect": - size1 = min(munits, round(np.sqrt(munits / ratio))) - else: - size1 = min(munits, round(np.sqrt(munits / ratio*np.sqrt(0.75)))) - - size2 = round(munits / size1) - - return [int(size1), int(size2)] - - -# Since joblib.delayed uses Pickle, this method needs to be a top level -# method in order to be pickled -# Joblib is working on adding support for cloudpickle or dill which will allow -# class methods to be pickled -# when that that comes out we can move this to SOM class -def _chunk_based_bmu_find(input_matrix, codebook, y2, nth=1): - """ - Finds the corresponding bmus to the input matrix. - - :param input_matrix: a matrix of input data, representing input vector as - rows, and vectors features/dimention as cols - when parallelizing the search, the input_matrix can be - a sub matrix from the bigger matrix - :param codebook: matrix of weights to be used for the bmu search - :param y2: - """ - dlen = input_matrix.shape[0] - nnodes = codebook.shape[0] - bmu = np.empty((dlen, 2)) - - # It seems that small batches for large dlen is really faster: - # that is because of ddata in loops and n_jobs. for large data it slows - # down due to memory needs in parallel - blen = min(50, dlen) - i0 = 0 - - while i0+1 <= dlen: - low = i0 - high = min(dlen, i0+blen) - i0 = i0+blen - ddata = input_matrix[low:high+1] - d = np.dot(codebook, ddata.T) - d *= -2 - d += y2.reshape(nnodes, 1) - bmu[low:high+1, 0] = np.argpartition(d, nth, axis=0)[nth-1] - bmu[low:high+1, 1] = np.partition(d, nth, axis=0)[nth-1] - del ddata - - return bmu - - - diff --git a/build/lib.linux-x86_64-2.7/sompy/visualization/__init__.py b/build/lib.linux-x86_64-2.7/sompy/visualization/__init__.py deleted file mode 100644 index 3d7dfea..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/visualization/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from . import dotmap, histogram, hitmap, mapview, umatrix diff --git a/build/lib.linux-x86_64-2.7/sompy/visualization/bmuhits.py b/build/lib.linux-x86_64-2.7/sompy/visualization/bmuhits.py deleted file mode 100644 index d54328d..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/visualization/bmuhits.py +++ /dev/null @@ -1,54 +0,0 @@ -from collections import Counter - -import matplotlib -import numpy as np -from matplotlib import pyplot as plt - -from .mapview import MapView - - -class BmuHitsView(MapView): - def _set_labels(self, cents, ax, labels, onlyzeros, fontsize): - for i, txt in enumerate(labels): - if onlyzeros == True: - if txt > 0: - txt = "" - ax.annotate(txt, (cents[i, 1] + 0.5, cents[-(i+1), 0] + 0.5), va="center", ha="center", size=fontsize) - - def show(self, som, anotate=True, onlyzeros=False, labelsize=7, cmap="jet", logaritmic = False): - (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, - axis_num) = self._calculate_figure_params(som, 1, 1) - - self.prepare() - ax = plt.gca() - counts = Counter(som._bmu[0]) - counts = [counts.get(x, 0) for x in range(som.codebook.mapsize[0] * som.codebook.mapsize[1])] - mp = np.array(counts).reshape(som.codebook.mapsize[0], - som.codebook.mapsize[1]) - - if not logaritmic: - norm = matplotlib.colors.Normalize( - vmin=0, - vmax=np.max(mp.flatten()), - clip=True) - else: - norm = matplotlib.colors.LogNorm( - vmin=1, - vmax=np.max(mp.flatten())) - - msz = som.codebook.mapsize - - cents = som.bmu_ind_to_xy(np.arange(0, msz[0] * msz[1])) - - if anotate: - self._set_labels(cents, ax, counts, onlyzeros, labelsize) - - - pl = plt.pcolor(mp[::-1], norm=norm, cmap=cmap) - - plt.axis([0, som.codebook.mapsize[1], 0, som.codebook.mapsize[0]]) - ax.set_yticklabels([]) - ax.set_xticklabels([]) - plt.colorbar(pl) - - plt.show() diff --git a/build/lib.linux-x86_64-2.7/sompy/visualization/dotmap.py b/build/lib.linux-x86_64-2.7/sompy/visualization/dotmap.py deleted file mode 100644 index 7ba10ff..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/visualization/dotmap.py +++ /dev/null @@ -1,68 +0,0 @@ -from .view import MatplotView -from matplotlib import pyplot as plt -import numpy as np - - -class DotMapView(MatplotView): - - def init_figure(self, dim, cols): - no_row_in_plot = dim/cols + 1 - no_col_in_plot = dim if no_row_in_plot <= 1 else cols - h = .1 - w = .1 - self.width = no_col_in_plot*2.5*(1+w) - self.height = no_row_in_plot*2.5*(1+h) - self.prepare() - - def plot(self, data, coords, msz0, msz1, colormap, dlen, dim, rows, cols): - for i in range(dim): - plt.subplot(rows, cols, i+1) - - # This uses the colors uniquely for each record, while in normal - # views, it is based on the values within each dimensions. This is - # important when we are dealing with time series. Where we don't - # want to normalize colors within each time period, rather we like - # to see the patterns of each data records in time. - mn = np.min(data[:, :], axis=1) - mx = np.max(data[:, :], axis=1) - - for j in range(dlen): - plt.scatter(coords[j, 1], - msz0-1-coords[j, 0], - c=data[j, i], - vmax=mx[j], vmin=mn[j], - s=90, - marker='.', - edgecolor='None', - cmap=colormap, - alpha=1) - - eps = .0075 - plt.xlim(0-eps, msz1-1+eps) - plt.ylim(0-eps, msz0-1+eps) - plt.xticks([]) - plt.yticks([]) - - def show(self, som, which_dim='all', colormap=None, cols=None): - plt.cm.get_cmap(colormap) if colormap else plt.cm.get_cmap('RdYlBu_r') - - data = som.data_raw - msz0, msz1 = som.codebook.mapsize - coords = som.bmu_ind_to_xy(som.project_data(data))[:, :2] - cols = cols if cols else 8 # 8 is arbitrary - rows = data.shape[1]/cols+1 - - if which_dim == 'all': - dim = data.shape[0] - self.init_figure(dim, cols) - self.plot(data, coords, msz0, msz1, colormap, data.shape[0], - data.shape[1], rows, cols) - - else: - dim = 1 if type(which_dim) is int else len(which_dim) - self.init_figure(dim, cols) - self.plot(data, coords, msz0, msz1, colormap, data.shape[0], - len(which_dim), rows, cols) - - plt.tight_layout() - plt.subplots_adjust(hspace=.16, wspace=.05) diff --git a/build/lib.linux-x86_64-2.7/sompy/visualization/histogram.py b/build/lib.linux-x86_64-2.7/sompy/visualization/histogram.py deleted file mode 100644 index cc71996..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/visualization/histogram.py +++ /dev/null @@ -1,59 +0,0 @@ -from .view import MatplotView -from matplotlib import pyplot as plt -from matplotlib import cm -from matplotlib.colors import LogNorm -import numpy as np - - -class Hist2d(MatplotView): - - def _fill_hist(self, x, y, mapsize, data_coords, what='train'): - x = np.arange(.5, mapsize[1]+.5, 1) - y = np.arange(.5, mapsize[0]+.5, 1) - X, Y = np.meshgrid(x, y) - - if what == 'train': - a = plt.hist2d(x, y, bins=(mapsize[1], mapsize[0]), alpha=.0, - cmap=cm.jet) - area = a[0].T * 12 - plt.scatter(data_coords[:, 1], mapsize[0] - .5 - data_coords[:, 0], - s=area.flatten(), alpha=.9, c='None', marker='o', - cmap='jet', linewidths=3, edgecolor='r') - - else: - a = plt.hist2d(x, y, bins=(mapsize[1], mapsize[0]), alpha=.0, - cmap=cm.jet, norm=LogNorm()) - area = a[0].T*50 - plt.scatter(data_coords[:, 1] + .5, - mapsize[0] - .5 - data_coords[:, 0], - s=area, alpha=0.9, c='None', marker='o', cmap='jet', - linewidths=3, edgecolor='r') - plt.scatter(data_coords[:, 1]+.5, mapsize[0]-.5-data_coords[:, 0], - s=area, alpha=0.2, c='b', marker='o', cmap='jet', - linewidths=3, edgecolor='r') - - plt.xlim(0, mapsize[1]) - plt.ylim(0, mapsize[0]) - - def show(self, som, data=None): - # First Step: show the hitmap of all the training data - coord = som.bmu_ind_to_xy(som.project_data(som.data_raw)) - - self.prepare() - - ax = self._fig.add_subplot(111) - ax.xaxis.set_ticks([i for i in range(0, som.codebook.mapsize[1])]) - ax.yaxis.set_ticks([i for i in range(0, som.codebook.mapsize[0])]) - ax.xaxis.set_ticklabels([]) - ax.yaxis.set_ticklabels([]) - ax.grid(True, linestyle='-', linewidth=.5) - - self._fill_hist(coord[:, 1], coord[:, 0], som.codebook.mapsize, - som.bmu_ind_to_xy(np.arange(som.codebook.nnodes))) - - if data: - coord_d = som.bmu_ind_to_xy(som.project_data(data)) - self._fill_hist(coord[:, 1], coord[:, 0], som.codebook.mapsize, - coord_d, 'data') - - plt.show() diff --git a/build/lib.linux-x86_64-2.7/sompy/visualization/hitmap.py b/build/lib.linux-x86_64-2.7/sompy/visualization/hitmap.py deleted file mode 100644 index c0dd482..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/visualization/hitmap.py +++ /dev/null @@ -1,37 +0,0 @@ -from .view import MatplotView -from matplotlib import pyplot as plt -import numpy as np - - -class HitMapView(MatplotView): - - def _set_labels(self, cents, ax, labels): - for i, txt in enumerate(labels): - ax.annotate(txt, (cents[i, 1], cents[i, 0]), size=10, va="center") - - def show(self, som, data=None): - - try: - codebook = getattr(som, 'cluster_labels') - except: - codebook = som.cluster() - - # codebook = getattr(som, 'cluster_labels', som.cluster()) - msz = som.codebook.mapsize - - self.prepare() - ax = self._fig.add_subplot(111) - - if data: - proj = som.project_data(data) - cents = som.bmu_ind_to_xy(proj) - self._set_labels(cents, ax, codebook[proj]) - - else: - cents = som.bmu_ind_to_xy(np.arange(0, msz[0]*msz[1])) - self._set_labels(cents, ax, codebook) - - plt.imshow(codebook.reshape(msz[0], msz[1])[::], alpha=.5) - plt.show() - - return cents diff --git a/build/lib.linux-x86_64-2.7/sompy/visualization/mapview.py b/build/lib.linux-x86_64-2.7/sompy/visualization/mapview.py deleted file mode 100644 index f1258af..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/visualization/mapview.py +++ /dev/null @@ -1,187 +0,0 @@ -import matplotlib -from .view import MatplotView -from matplotlib import pyplot as plt -import numpy as np -import ipdb - - -class MapView(MatplotView): - - def _calculate_figure_params(self, som, which_dim, col_sz): - - # add this to avoid error when normalization is not used - if som._normalizer: - codebook = som._normalizer.denormalize_by(som.data_raw, som.codebook.matrix) - else: - codebook = som.codebook.matrix - - indtoshow, sV, sH = None, None, None - - if which_dim == 'all': - dim = som._dim - row_sz = np.ceil(float(dim) / col_sz) - msz_row, msz_col = som.codebook.mapsize - ratio_hitmap = msz_row / float(msz_col) - ratio_fig = row_sz / float(col_sz) - indtoshow = np.arange(0, dim).T - sH, sV = 16, 16*ratio_fig*ratio_hitmap - - elif type(which_dim) == int: - dim = 1 - msz_row, msz_col = som.codebook.mapsize - ratio_hitmap = msz_row / float(msz_col) - indtoshow = np.zeros(1) - indtoshow[0] = int(which_dim) - sH, sV = 16, 16 * ratio_hitmap - - elif type(which_dim) == list: - max_dim = codebook.shape[1] - dim = len(which_dim) - row_sz = np.ceil(float(dim) / col_sz) - msz_row, msz_col = som.codebook.mapsize - ratio_hitmap = msz_row / float(msz_col) - ratio_fig = row_sz / float(col_sz) - indtoshow = np.asarray(which_dim).T - sH, sV = 16, 16*ratio_fig*ratio_hitmap - - no_row_in_plot = dim / col_sz + 1 # 6 is arbitrarily selected - if no_row_in_plot <= 1: - no_col_in_plot = dim - else: - no_col_in_plot = col_sz - - axis_num = 0 - - width = sH - height = sV - - return (width, height, indtoshow, no_row_in_plot, no_col_in_plot, - axis_num) - - -class View2D(MapView): - - def show(self, som, what='codebook', which_dim='all', cmap=None, - col_sz=None, desnormalize=False): - (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, - axis_num) = self._calculate_figure_params(som, which_dim, col_sz) - self.prepare() - - if not desnormalize: - codebook = som.codebook.matrix - else: - codebook = som._normalizer.denormalize_by(som.data_raw, som.codebook.matrix) - - if which_dim == 'all': - names = som._component_names[0] - elif type(which_dim) == int: - names = [som._component_names[0][which_dim]] - elif type(which_dim) == list: - names = som._component_names[0][which_dim] - - - while axis_num < len(indtoshow): - axis_num += 1 - ax = plt.subplot(no_row_in_plot, no_col_in_plot, axis_num) - ind = int(indtoshow[axis_num-1]) - - min_color_scale = np.mean(codebook[:, ind].flatten()) - 1 * np.std(codebook[:, ind].flatten()) - max_color_scale = np.mean(codebook[:, ind].flatten()) + 1 * np.std(codebook[:, ind].flatten()) - min_color_scale = min_color_scale if min_color_scale >= min(codebook[:, ind].flatten()) else \ - min(codebook[:, ind].flatten()) - max_color_scale = max_color_scale if max_color_scale <= max(codebook[:, ind].flatten()) else \ - max(codebook[:, ind].flatten()) - norm = matplotlib.colors.Normalize(vmin=min_color_scale, vmax=max_color_scale, clip=True) - - mp = codebook[:, ind].reshape(som.codebook.mapsize[0], - som.codebook.mapsize[1]) - pl = plt.pcolor(mp[::-1], norm=norm) - plt.axis([0, som.codebook.mapsize[1], 0, som.codebook.mapsize[0]]) - plt.title(names[axis_num - 1]) - ax.set_yticklabels([]) - ax.set_xticklabels([]) - plt.colorbar(pl) - - #plt.show() - - -class View2DPacked(MapView): - - def _set_axis(self, ax, msz0, msz1): - plt.axis([0, msz0, 0, msz1]) - plt.axis('off') - ax.axis('off') - - def show(self, som, what='codebook', which_dim='all', cmap=None, - col_sz=None): - if col_sz is None: - col_sz = 6 - (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, - axis_num) = self._calculate_figure_params(som, which_dim, col_sz) - codebook = som.codebook.matrix - - cmap = cmap or plt.cm.get_cmap('RdYlBu_r') - msz0, msz1 = som.codebook.mapsize - compname = som.component_names - if what == 'codebook': - h = .1 - w = .1 - self.width = no_col_in_plot*2.5*(1+w) - self.height = no_row_in_plot*2.5*(1+h) - self.prepare() - - while axis_num < len(indtoshow): - axis_num += 1 - ax = self._fig.add_subplot(no_row_in_plot, no_col_in_plot, - axis_num) - ax.axis('off') - ind = int(indtoshow[axis_num-1]) - mp = codebook[:, ind].reshape(msz0, msz1) - plt.imshow(mp[::-1], norm=None, cmap=cmap) - self._set_axis(ax, msz0, msz1) - - if self.show_text is True: - plt.title(compname[0][ind]) - font = {'size': self.text_size} - plt.rc('font', **font) - if what == 'cluster': - try: - codebook = getattr(som, 'cluster_labels') - except: - codebook = som.cluster() - - h = .2 - w = .001 - self.width = msz0/2 - self.height = msz1/2 - self.prepare() - - ax = self._fig.add_subplot(1, 1, 1) - mp = codebook[:].reshape(msz0, msz1) - plt.imshow(mp[::-1], cmap=cmap) - - self._set_axis(ax, msz0, msz1) - - plt.subplots_adjust(hspace=h, wspace=w) - - plt.show() - - -class View1D(MapView): - - def show(self, som, what='codebook', which_dim='all', cmap=None, - col_sz=None): - (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, - axis_num) = self._calculate_figure_params(som, which_dim, col_sz) - self.prepare() - - codebook = som.codebook.matrix - - while axis_num < len(indtoshow): - axis_num += 1 - plt.subplot(no_row_in_plot, no_col_in_plot, axis_num) - ind = int(indtoshow[axis_num-1]) - mp = codebook[:, ind] - plt.plot(mp, '-k', linewidth=0.8) - - #plt.show() diff --git a/build/lib.linux-x86_64-2.7/sompy/visualization/umatrix.py b/build/lib.linux-x86_64-2.7/sompy/visualization/umatrix.py deleted file mode 100644 index afa8ae8..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/visualization/umatrix.py +++ /dev/null @@ -1,95 +0,0 @@ -from .view import MatplotView -from matplotlib import pyplot as plt -from pylab import imshow, contour -from math import sqrt -import numpy as np -import scipy - - -class UMatrixView(MatplotView): - - def build_u_matrix(self, som, distance=1, row_normalized=False): - UD2 = som.calculate_map_dist() - Umatrix = np.zeros((som.codebook.nnodes, 1)) - codebook = som.codebook.matrix - if row_normalized: - vector = som._normalizer.normalize_by(codebook.T, codebook.T, - method='var').T - else: - vector = codebook - - for i in range(som.codebook.nnodes): - codebook_i = vector[i][np.newaxis, :] - neighborbor_ind = UD2[i][0:] <= distance - neighborbor_codebooks = vector[neighborbor_ind] - Umatrix[i] = scipy.spatial.distance_matrix( - codebook_i, neighborbor_codebooks).mean() - - return Umatrix.reshape(som.codebook.mapsize) - - def show(self, som, distance2=1, row_normalized=False, show_data=True, - contooor=True, blob=False, labels=False): - umat = self.build_u_matrix(som, distance=distance2, - row_normalized=row_normalized) - msz = som.codebook.mapsize - proj = som.project_data(som.data_raw) - coord = som.bmu_ind_to_xy(proj) - - fig, ax = plt.subplots(1, 1) - imshow(umat, cmap=plt.cm.get_cmap('RdYlBu_r'), alpha=1) - - if contooor: - mn = np.min(umat.flatten()) - mx = np.max(umat.flatten()) - std = np.std(umat.flatten()) - md = np.median(umat.flatten()) - mx = md + 0*std - contour(umat, np.linspace(mn, mx, 15), linewidths=0.7, - cmap=plt.cm.get_cmap('Blues')) - - if show_data: - plt.scatter(coord[:, 1], coord[:, 0], s=2, alpha=1., c='Gray', - marker='o', cmap='jet', linewidths=3, edgecolor='Gray') - plt.axis('off') - - if labels: - if labels is True: - labels = som.build_data_labels() - for label, x, y in zip(labels, coord[:, 1], coord[:, 0]): - plt.annotate(str(label), xy=(x, y), - horizontalalignment='center', - verticalalignment='center') - - ratio = float(msz[0])/(msz[0]+msz[1]) - fig.set_size_inches((1-ratio)*15, ratio*15) - plt.tight_layout() - plt.subplots_adjust(hspace=.00, wspace=.000) - sel_points = list() - - if blob: - from skimage.color import rgb2gray - from skimage.feature import blob_log - - image = 1 / umat - rgb2gray(image) - - # 'Laplacian of Gaussian' - blobs = blob_log(image, max_sigma=5, num_sigma=4, threshold=.152) - blobs[:, 2] = blobs[:, 2] * sqrt(2) - imshow(umat, cmap=plt.cm.get_cmap('RdYlBu_r'), alpha=1) - sel_points = list() - - for blob in blobs: - row, col, r = blob - c = plt.Circle((col, row), r, color='red', linewidth=2, - fill=False) - ax.add_patch(c) - dist = scipy.spatial.distance_matrix( - coord[:, :2], np.array([row, col])[np.newaxis, :]) - sel_point = dist <= r - plt.plot(coord[:, 1][sel_point[:, 0]], - coord[:, 0][sel_point[:, 0]], '.r') - sel_points.append(sel_point[:, 0]) - - plt.show() - return sel_points, umat diff --git a/build/lib.linux-x86_64-2.7/sompy/visualization/view.py b/build/lib.linux-x86_64-2.7/sompy/visualization/view.py deleted file mode 100644 index c618a23..0000000 --- a/build/lib.linux-x86_64-2.7/sompy/visualization/view.py +++ /dev/null @@ -1,54 +0,0 @@ -from matplotlib import pyplot as plt - - -class View(object): - def __init__(self, width, height, title, show_axis=True, packed=True, - text_size=2.8, show_text=True, col_size=6, *args, **kwargs): - self.width = width - self.height = height - self.title = title - self.show_axis = show_axis - self.packed = packed - self.text_size = text_size - self.show_text = show_text - self.col_size = col_size - - def prepare(self, *args, **kwargs): - raise NotImplementedError() - - def save(self, filename): - raise NotImplementedError() - - def show(self, *args, **kwrags): - raise NotImplementedError() - - -class MatplotView(View): - - def __init__(self, width, height, title, show_axis=True, packed=True, - text_size=2.8, show_text=True, col_size=6, *args, **kwargs): - super(MatplotView, self).__init__(width, height, title, show_axis, - packed, text_size, show_text, - col_size, *args, **kwargs) - self._fig = None - - def __del__(self): - self._close_fig() - - def _close_fig(self): - if self._fig: - plt.close(self._fig) - - def prepare(self, *args, **kwargs): - self._close_fig() - self._fig = plt.figure(figsize=(self.width, self.height)) - plt.title(self.title) - plt.axis('off') - plt.rc('font', **{'size': self.text_size}) - - def save(self, filename, transparent=False, bbox_inches='tight', dpi=400): - self._fig.savefig(filename, transparent=transparent, dpi=dpi, - bbox_inches=bbox_inches) - - def show(self, *args, **kwrags): - raise NotImplementedError() diff --git a/build/lib/sompy/__init__.py b/build/lib/sompy/__init__.py deleted file mode 100644 index 3b1e899..0000000 --- a/build/lib/sompy/__init__.py +++ /dev/null @@ -1,31 +0,0 @@ - -from logging.config import dictConfig -import matplotlib - -#matplotlib.use('Agg') # Use whatever backend is available - -dictConfig({ - "version": 1, - "disable_existing_loggers": False, - "root": { - "level": "NOTSET", - "handlers": ["console"] - }, - "handlers": { - "console": { - "level": "DEBUG", - "class": "logging.StreamHandler", - "formatter": "basic" - } - }, - "formatters": { - "basic": { - "format": '%(message)s' - } - } -}) - - - -from .sompy import SOMFactory -from .visualization import * diff --git a/build/lib/sompy/codebook.py b/build/lib/sompy/codebook.py deleted file mode 100644 index b5e16c4..0000000 --- a/build/lib/sompy/codebook.py +++ /dev/null @@ -1,173 +0,0 @@ -import numpy as np - -from sklearn.decomposition import PCA -#from sklearn.decomposition import RandomizedPCA# (randomizedpca is deprecated) -from .decorators import timeit - - -class InvalidNodeIndexError(Exception): - pass - - -class InvalidMapsizeError(Exception): - pass - - -class Codebook(object): - - def __init__(self, mapsize, lattice='rect'): - self.lattice = lattice - - if 2 == len(mapsize): - _size = [1, np.max(mapsize)] if 1 == np.min(mapsize) else mapsize - - elif 1 == len(mapsize): - _size = [1, mapsize[0]] - print('input was considered as the numbers of nodes') - print('map size is [{dlen},{dlen}]'.format(dlen=int(mapsize[0]/2))) - else: - raise InvalidMapsizeError( - "Mapsize is expected to be a 2 element list or a single int") - - self.mapsize = _size - self.nnodes = mapsize[0]*mapsize[1] - self.matrix = np.asarray(self.mapsize) - self.initialized = False - - @timeit() - def random_initialization(self, data): - """ - :param data: data to use for the initialization - :returns: initialized matrix with same dimension as input data - """ - mn = np.tile(np.min(data, axis=0), (self.nnodes, 1)) - mx = np.tile(np.max(data, axis=0), (self.nnodes, 1)) - self.matrix = mn + (mx-mn)*(np.random.rand(self.nnodes, data.shape[1])) - self.initialized = True - - @timeit() - def pca_linear_initialization(self, data): - """ - We initialize the map, just by using the first two first eigen vals and - eigenvectors - Further, we create a linear combination of them in the new map by - giving values from -1 to 1 in each - - X = UsigmaWT - XTX = Wsigma^2WT - T = XW = Usigma - - // Transformed by W EigenVector, can be calculated by multiplication - // PC matrix by eigenval too - // Further, we can get lower ranks by using just few of the eigen - // vevtors - - T(2) = U(2)sigma(2) = XW(2) ---> 2 is the number of selected - eigenvectors - - (*) Note that 'X' is the covariance matrix of original data - - :param data: data to use for the initialization - :returns: initialized matrix with same dimension as input data - """ - cols = self.mapsize[1] - coord = None - pca_components = None - - if np.min(self.mapsize) > 1: - coord = np.zeros((self.nnodes, 2)) - pca_components = 2 - - for i in range(0, self.nnodes): - coord[i, 0] = int(i / cols) # x - coord[i, 1] = int(i % cols) # y - - elif np.min(self.mapsize) == 1: - coord = np.zeros((self.nnodes, 1)) - pca_components = 1 - - for i in range(0, self.nnodes): - coord[i, 0] = int(i % cols) # y - - mx = np.max(coord, axis=0) - mn = np.min(coord, axis=0) - coord = (coord - mn)/(mx-mn) - coord = (coord - .5)*2 - me = np.mean(data, 0) - data = (data - me) - tmp_matrix = np.tile(me, (self.nnodes, 1)) - - # Randomized PCA is scalable - #pca = RandomizedPCA(n_components=pca_components) # RandomizedPCA is deprecated. - pca = PCA(n_components=pca_components, svd_solver='randomized') - - pca.fit(data) - eigvec = pca.components_ - eigval = pca.explained_variance_ - norms = np.sqrt(np.einsum('ij,ij->i', eigvec, eigvec)) - eigvec = ((eigvec.T/norms)*eigval).T - - for j in range(self.nnodes): - for i in range(eigvec.shape[0]): - tmp_matrix[j, :] = tmp_matrix[j, :] + coord[j, i]*eigvec[i, :] - - self.matrix = np.around(tmp_matrix, decimals=6) - self.initialized = True - - def grid_dist(self, node_ind): - """ - Calculates grid distance based on the lattice type. - - :param node_ind: number between 0 and number of nodes-1. Depending on - the map size, starting from top left - :returns: matrix representing the distance matrix - """ - if self.lattice == 'rect': - return self._rect_dist(node_ind) - - elif self.lattice == 'hexa': - return self._hexa_dist(node_ind) - - def _hexa_dist(self, node_ind): - raise NotImplementedError() - - def _rect_dist(self, node_ind): - """ - Calculates the distance of the specified node to the other nodes in the - matrix, generating a distance matrix - - Ej. The distance matrix for the node_ind=5, that corresponds to - the_coord (1,1) - array([[2, 1, 2, 5], - [1, 0, 1, 4], - [2, 1, 2, 5], - [5, 4, 5, 8]]) - - :param node_ind: number between 0 and number of nodes-1. Depending on - the map size, starting from top left - :returns: matrix representing the distance matrix - """ - rows = self.mapsize[0] - cols = self.mapsize[1] - dist = None - - # bmu should be an integer between 0 to no_nodes - if 0 <= node_ind <= (rows*cols): - node_col = int(node_ind % cols) - node_row = int(node_ind / cols) - else: - raise InvalidNodeIndexError( - "Node index '%s' is invalid" % node_ind) - - if rows > 0 and cols > 0: - r = np.arange(0, rows, 1)[:, np.newaxis] - c = np.arange(0, cols, 1) - dist2 = (r-node_row)**2 + (c-node_col)**2 - - dist = dist2.ravel() - else: - raise InvalidMapsizeError( - "One or both of the map dimensions are invalid. " - "Cols '%s', Rows '%s'".format(cols=cols, rows=rows)) - - return dist diff --git a/build/lib/sompy/decorators.py b/build/lib/sompy/decorators.py deleted file mode 100644 index a3ae0fc..0000000 --- a/build/lib/sompy/decorators.py +++ /dev/null @@ -1,21 +0,0 @@ -import logging -from functools import wraps -from time import time - - -def timeit(log_level=logging.INFO, alternative_title=None): - def wrap(f): - @wraps(f) # keeps the f.__name__ outside the wrapper - def wrapped_f(*args, **kwargs): - t0 = time() - result = f(*args, **kwargs) - ts = round(time() - t0, 3) - - title = alternative_title or f.__name__ - logging.getLogger().log( - log_level, " %s took: %f seconds" % (title, ts)) - - return result - - return wrapped_f - return wrap diff --git a/build/lib/sompy/neighborhood.py b/build/lib/sompy/neighborhood.py deleted file mode 100644 index a4d2c9c..0000000 --- a/build/lib/sompy/neighborhood.py +++ /dev/null @@ -1,48 +0,0 @@ -import numpy as np -import inspect -import sys - -small = .000000000001 - - -class NeighborhoodFactory(object): - - @staticmethod - def build(neighborhood_func): - for name, obj in inspect.getmembers(sys.modules[__name__]): - if inspect.isclass(obj): - if hasattr(obj, 'name') and neighborhood_func == obj.name: - return obj() - else: - raise Exception( - "Unsupported neighborhood function '%s'" % neighborhood_func) - - -class GaussianNeighborhood(object): - - name = 'gaussian' - - @staticmethod - def calculate(distance_matrix, radius, dim): - return np.exp(-1.0*distance_matrix/(2.0*radius**2)).reshape(dim, dim) - - def __call__(self, *args, **kwargs): - return self.calculate(*args) - - -class BubbleNeighborhood(object): - - name = 'bubble' - - @staticmethod - def calculate(distance_matrix, radius, dim): - def l(a, b): - c = np.zeros(b.shape) - c[a-b >= 0] = 1 - return c - - return l(radius, - np.sqrt(distance_matrix.flatten())).reshape(dim, dim) + small - - def __call__(self, *args, **kwargs): - return self.calculate(*args) diff --git a/build/lib/sompy/normalization.py b/build/lib/sompy/normalization.py deleted file mode 100644 index b641b94..0000000 --- a/build/lib/sompy/normalization.py +++ /dev/null @@ -1,74 +0,0 @@ -import numpy as np -import sys -import inspect - - -class NormalizatorFactory(object): - - @staticmethod - def build(type_name): - for name, obj in inspect.getmembers(sys.modules[__name__]): - if inspect.isclass(obj): - if hasattr(obj, 'name') and type_name == obj.name: - return obj() - else: - raise Exception("Unknown normalization type '%s'" % type_name) - - -class Normalizator(object): - - def normalize(self, data): - raise NotImplementedError() - - def normalize_by(self, raw_data, data): - raise NotImplementedError() - - def denormalize_by(self, raw_data, data): - raise NotImplementedError() - - -class VarianceNormalizator(Normalizator): - - name = 'var' - - def _mean_and_standard_dev(self, data): - return np.mean(data, axis=0), np.std(data, axis=0) - - def normalize(self, data): - me, st = self._mean_and_standard_dev(data) - st[st == 0] = 1 # prevent: when sd = 0, normalized result = NaN - return (data-me)/st - - def normalize_by(self, raw_data, data): - me, st = self._mean_and_standard_dev(raw_data) - st[st == 0] = 1 # prevent: when sd = 0, normalized result = NaN - return (data-me)/st - - def denormalize_by(self, data_by, n_vect): - me, st = self._mean_and_standard_dev(data_by) - return n_vect * st + me - - -class RangeNormalizator(Normalizator): - - name = 'range' - - -class LogNormalizator(Normalizator): - - name = 'log' - - -class LogisticNormalizator(Normalizator): - - name = 'logistic' - - -class HistDNormalizator(Normalizator): - - name = 'histd' - - -class HistCNormalizator(Normalizator): - - name = 'histc' diff --git a/build/lib/sompy/sompy.py b/build/lib/sompy/sompy.py deleted file mode 100644 index 58818c8..0000000 --- a/build/lib/sompy/sompy.py +++ /dev/null @@ -1,708 +0,0 @@ -# -*- coding: utf-8 -*- - -# Author: Vahid Moosavi (sevamoo@gmail.com) -# Chair For Computer Aided Architectural Design, ETH Zurich -# Future Cities Lab -# www.vahidmoosavi.com - -# Contributor: Sebastian Packmann (sebastian.packmann@gmail.com) - - -import tempfile -import os -import itertools -import logging - -import numpy as np - -from time import time -from multiprocessing.dummy import Pool -from multiprocessing import cpu_count -from scipy.sparse import csr_matrix -from sklearn import neighbors -from sklearn.externals.joblib import Parallel, delayed, load, dump -import sys - -from .decorators import timeit -from .codebook import Codebook -from .neighborhood import NeighborhoodFactory -from .normalization import NormalizatorFactory - -#lbugnon -import sompy,ipdb -# - -class ComponentNamesError(Exception): - pass - - -class LabelsError(Exception): - pass - - -class SOMFactory(object): - - @staticmethod - def build(data, - mapsize=None, - mask=None, - mapshape='planar', - lattice='rect', - normalization='var', - initialization='pca', - neighborhood='gaussian', - training='batch', - name='sompy', - component_names=None): - """ - :param data: data to be clustered, represented as a matrix of n rows, - as inputs and m cols as input features - :param neighborhood: neighborhood object calculator. Options are: - - gaussian - - bubble - - manhattan (not implemented yet) - - cut_gaussian (not implemented yet) - - epanechicov (not implemented yet) - - :param normalization: normalizer object calculator. Options are: - - var - - :param mapsize: tuple/list defining the dimensions of the som. - If single number is provided is considered as the number of nodes. - :param mask: mask - :param mapshape: shape of the som. Options are: - - planar - - toroid (not implemented yet) - - cylinder (not implemented yet) - - :param lattice: type of lattice. Options are: - - rect - - hexa (not implemented yet) - - :param initialization: method to be used for initialization of the som. - Options are: - - pca - - random - - :param name: name used to identify the som - :param training: Training mode (seq, batch) - """ - if normalization: - normalizer = NormalizatorFactory.build(normalization) - else: - normalizer = None - neighborhood_calculator = NeighborhoodFactory.build(neighborhood) - return SOM(data, neighborhood_calculator, normalizer, mapsize, mask, - mapshape, lattice, initialization, training, name, component_names) - - -class SOM(object): - - def __init__(self, - data, - neighborhood, - normalizer=None, - mapsize=None, - mask=None, - mapshape='planar', - lattice='rect', - initialization='pca', - training='batch', - name='sompy', - component_names=None): - """ - Self Organizing Map - - :param data: data to be clustered, represented as a matrix of n rows, - as inputs and m cols as input features - :param neighborhood: neighborhood object calculator. - :param normalizer: normalizer object calculator. - :param mapsize: tuple/list defining the dimensions of the som. If - single number is provided is considered as the number of nodes. - :param mask: mask - :param mapshape: shape of the som. - :param lattice: type of lattice. - :param initialization: method to be used for initialization of the som. - :param name: name used to identify the som - :param training: Training mode (seq, batch) - """ - self._data = normalizer.normalize(data) if normalizer else data - self._normalizer = normalizer - self._dim = data.shape[1] - self._dlen = data.shape[0] - self._dlabel = None - self._bmu = None - - self.name = name - self.data_raw = data - self.neighborhood = neighborhood - self.mapshape = mapshape - self.initialization = initialization - self.mask = mask or np.ones([1, self._dim]) - mapsize = self.calculate_map_size(lattice) if not mapsize else mapsize - self.codebook = Codebook(mapsize, lattice) - self.training = training - self._component_names = self.build_component_names() if component_names is None else [component_names] - self._distance_matrix = self.calculate_map_dist() - - @property - def component_names(self): - return self._component_names - - @component_names.setter - def component_names(self, compnames): - if self._dim == len(compnames): - self._component_names = np.asarray(compnames)[np.newaxis, :] - else: - raise ComponentNamesError('Component names should have the same ' - 'size as the data dimension/features') - - def build_component_names(self): - cc = ['Variable-' + str(i+1) for i in range(0, self._dim)] - return np.asarray(cc)[np.newaxis, :] - - @property - def data_labels(self): - return self._dlabel - - @data_labels.setter - def data_labels(self, labels): - """ - Set labels of the training data, it should be in the format of a list - of strings - """ - if labels.shape == (1, self._dlen): - label = labels.T - elif labels.shape == (self._dlen, 1): - label = labels - elif labels.shape == (self._dlen,): - label = labels[:, np.newaxis] - else: - raise LabelsError('wrong label format') - - self._dlabel = label - - def build_data_labels(self): - cc = ['dlabel-' + str(i) for i in range(0, self._dlen)] - return np.asarray(cc)[:, np.newaxis] - - def calculate_map_dist(self): - """ - Calculates the grid distance, which will be used during the training - steps. It supports only planar grids for the moment - """ - nnodes = self.codebook.nnodes - - distance_matrix = np.zeros((nnodes, nnodes)) - for i in range(nnodes): - distance_matrix[i] = self.codebook.grid_dist(i).reshape(1, nnodes) - return distance_matrix - - @timeit() - def train(self, - n_job=1, - shared_memory=False, - verbose='info', - train_rough_len=None, - train_rough_radiusin=None, - train_rough_radiusfin=None, - train_finetune_len=None, - train_finetune_radiusin=None, - train_finetune_radiusfin=None, - train_len_factor=1, - maxtrainlen=np.Inf): - """ - Trains the som - - :param n_job: number of jobs to use to parallelize the traning - :param shared_memory: flag to active shared memory - :param verbose: verbosity, could be 'debug', 'info' or None - :param train_len_factor: Factor that multiply default training lenghts (similar to "training" parameter in the matlab version). (lbugnon) - """ - logging.root.setLevel( - getattr(logging, verbose.upper()) if verbose else logging.ERROR) - - logging.info(" Training...") - logging.debug(( - "--------------------------------------------------------------\n" - " details: \n" - " > data len is {data_len} and data dimension is {data_dim}\n" - " > map size is {mpsz0},{mpsz1}\n" - " > array size in log10 scale is {array_size}\n" - " > number of jobs in parallel: {n_job}\n" - " -------------------------------------------------------------\n") - .format(data_len=self._dlen, - data_dim=self._dim, - mpsz0=self.codebook.mapsize[0], - mpsz1=self.codebook.mapsize[1], - array_size=np.log10( - self._dlen * self.codebook.nnodes * self._dim), - n_job=n_job)) - - if self.initialization == 'random': - self.codebook.random_initialization(self._data) - - elif self.initialization == 'pca': - self.codebook.pca_linear_initialization(self._data) - - self.rough_train(njob=n_job, shared_memory=shared_memory, trainlen=train_rough_len, - radiusin=train_rough_radiusin, radiusfin=train_rough_radiusfin,trainlen_factor=train_len_factor,maxtrainlen=maxtrainlen) - self.finetune_train(njob=n_job, shared_memory=shared_memory, trainlen=train_finetune_len, - radiusin=train_finetune_radiusin, radiusfin=train_finetune_radiusfin,trainlen_factor=train_len_factor,maxtrainlen=maxtrainlen) - logging.debug( - " --------------------------------------------------------------") - logging.info(" Final quantization error: %f" % np.mean(self._bmu[1])) - - def _calculate_ms_and_mpd(self): - mn = np.min(self.codebook.mapsize) - max_s = max(self.codebook.mapsize[0], self.codebook.mapsize[1]) - - if mn == 1: - mpd = float(self.codebook.nnodes*10)/float(self._dlen) - else: - mpd = float(self.codebook.nnodes)/float(self._dlen) - ms = max_s/2.0 if mn == 1 else max_s - - return ms, mpd - - def rough_train(self, njob=1, shared_memory=False, trainlen=None, radiusin=None, radiusfin=None,trainlen_factor=1,maxtrainlen=np.Inf): - logging.info(" Rough training...") - - ms, mpd = self._calculate_ms_and_mpd() - #lbugnon: add maxtrainlen - trainlen = min(int(np.ceil(30*mpd)),maxtrainlen) if not trainlen else trainlen - print("maxtrainlen %d",maxtrainlen) - #lbugnon: add trainlen_factor - trainlen=int(trainlen*trainlen_factor) - - if self.initialization == 'random': - radiusin = max(1, np.ceil(ms/3.)) if not radiusin else radiusin - radiusfin = max(1, radiusin/6.) if not radiusfin else radiusfin - - elif self.initialization == 'pca': - radiusin = max(1, np.ceil(ms/8.)) if not radiusin else radiusin - radiusfin = max(1, radiusin/4.) if not radiusfin else radiusfin - - self._batchtrain(trainlen, radiusin, radiusfin, njob, shared_memory) - - def finetune_train(self, njob=1, shared_memory=False, trainlen=None, radiusin=None, radiusfin=None,trainlen_factor=1,maxtrainlen=np.Inf): - logging.info(" Finetune training...") - - ms, mpd = self._calculate_ms_and_mpd() - - #lbugnon: add maxtrainlen - if self.initialization == 'random': - trainlen = min(int(np.ceil(50*mpd)),maxtrainlen) if not trainlen else trainlen - radiusin = max(1, ms/12.) if not radiusin else radiusin # from radius fin in rough training - radiusfin = max(1, radiusin/25.) if not radiusfin else radiusfin - - elif self.initialization == 'pca': - trainlen = min(int(np.ceil(40*mpd)),maxtrainlen) if not trainlen else trainlen - radiusin = max(1, np.ceil(ms/8.)/4) if not radiusin else radiusin - radiusfin = 1 if not radiusfin else radiusfin # max(1, ms/128) - - print("maxtrainlen %d",maxtrainlen) - - #lbugnon: add trainlen_factor - trainlen=int(trainlen_factor*trainlen) - - - self._batchtrain(trainlen, radiusin, radiusfin, njob, shared_memory) - - def _batchtrain(self, trainlen, radiusin, radiusfin, njob=1, - shared_memory=False): - radius = np.linspace(radiusin, radiusfin, trainlen) - - if shared_memory: - data = self._data - data_folder = tempfile.mkdtemp() - data_name = os.path.join(data_folder, 'data') - dump(data, data_name) - data = load(data_name, mmap_mode='r') - - else: - data = self._data - - bmu = None - - # X2 is part of euclidean distance (x-y)^2 = x^2 +y^2 - 2xy that we use - # for each data row in bmu finding. - # Since it is a fixed value we can skip it during bmu finding for each - # data point, but later we need it calculate quantification error - fixed_euclidean_x2 = np.einsum('ij,ij->i', data, data) - - logging.info(" radius_ini: %f , radius_final: %f, trainlen: %d\n" % - (radiusin, radiusfin, trainlen)) - - for i in range(trainlen): - t1 = time() - neighborhood = self.neighborhood.calculate( - self._distance_matrix, radius[i], self.codebook.nnodes) - bmu = self.find_bmu(data, njb=njob) - self.codebook.matrix = self.update_codebook_voronoi(data, bmu, - neighborhood) - - #lbugnon: ojo! aca el bmy[1] a veces da negativo, y despues de eso se rompe...hay algo raro ahi - qerror = (i + 1, round(time() - t1, 3), - np.mean(np.sqrt(bmu[1] + fixed_euclidean_x2))) #lbugnon: ojo aca me tiró un warning, revisar (commit sinc: 965666d3d4d93bcf48e8cef6ea2c41a018c1cb83 ) - #lbugnon - #ipdb.set_trace() - # - logging.info( - " epoch: %d ---> elapsed time: %f, quantization error: %f\n" % - qerror) - if np.any(np.isnan(qerror)): - logging.info("nan quantization error, exit train\n") - - #sys.exit("quantization error=nan, exit train") - - bmu[1] = np.sqrt(bmu[1] + fixed_euclidean_x2) - self._bmu = bmu - - @timeit(logging.DEBUG) - def find_bmu(self, input_matrix, njb=1, nth=1): - """ - Finds the best matching unit (bmu) for each input data from the input - matrix. It does all at once parallelizing the calculation instead of - going through each input and running it against the codebook. - - :param input_matrix: numpy matrix representing inputs as rows and - features/dimension as cols - :param njb: number of jobs to parallelize the search - :returns: the best matching unit for each input - """ - dlen = input_matrix.shape[0] - y2 = np.einsum('ij,ij->i', self.codebook.matrix, self.codebook.matrix) - if njb == -1: - njb = cpu_count() - - pool = Pool(njb) - chunk_bmu_finder = _chunk_based_bmu_find - - def row_chunk(part): - return part * dlen // njb - - def col_chunk(part): - return min((part+1)*dlen // njb, dlen) - - chunks = [input_matrix[row_chunk(i):col_chunk(i)] for i in range(njb)] - b = pool.map(lambda chk: chunk_bmu_finder(chk, self.codebook.matrix, y2, nth=nth), chunks) - pool.close() - pool.join() - bmu = np.asarray(list(itertools.chain(*b))).T - del b - return bmu - - @timeit(logging.DEBUG) - def update_codebook_voronoi(self, training_data, bmu, neighborhood): - """ - Updates the weights of each node in the codebook that belongs to the - bmu's neighborhood. - - First finds the Voronoi set of each node. It needs to calculate a - smaller matrix. - Super fast comparing to classic batch training algorithm, it is based - on the implemented algorithm in som toolbox for Matlab by Helsinky - University. - - :param training_data: input matrix with input vectors as rows and - vector features as cols - :param bmu: best matching unit for each input data. Has shape of - (2, dlen) where first row has bmu indexes - :param neighborhood: matrix representing the neighborhood of each bmu - - :returns: An updated codebook that incorporates the learnings from the - input data - """ - row = bmu[0].astype(int) - col = np.arange(self._dlen) - val = np.tile(1, self._dlen) - P = csr_matrix((val, (row, col)), shape=(self.codebook.nnodes, - self._dlen)) - S = P.dot(training_data) - - # neighborhood has nnodes*nnodes and S has nnodes*dim - # ---> Nominator has nnodes*dim - nom = neighborhood.T.dot(S) - nV = P.sum(axis=1).reshape(1, self.codebook.nnodes) - denom = nV.dot(neighborhood.T).reshape(self.codebook.nnodes, 1) - new_codebook = np.divide(nom, denom) - - return np.around(new_codebook, decimals=6) - - def project_data(self, data): - """ - Projects a data set to a trained SOM. It is based on nearest - neighborhood search module of scikitlearn, but it is not that fast. - """ - clf = neighbors.KNeighborsClassifier(n_neighbors=1) - labels = np.arange(0, self.codebook.matrix.shape[0]) - clf.fit(self.codebook.matrix, labels) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - data = self._normalizer.normalize_by(self.data_raw, data) - - return clf.predict(data) - - def predict_by(self, data, target, k=5, wt='distance'): - # here it is assumed that target is the last column in the codebook - # and data has dim-1 columns - dim = self.codebook.matrix.shape[1] - ind = np.arange(0, dim) - indX = ind[ind != target] - x = self.codebook.matrix[:, indX] - y = self.codebook.matrix[:, target] - n_neighbors = k - clf = neighbors.KNeighborsRegressor(n_neighbors, weights=wt) - clf.fit(x, y) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - dimdata = data.shape[1] - - if dimdata == dim: - data[:, target] = 0 - data = self._normalizer.normalize_by(self.data_raw, data) - data = data[:, indX] - - elif dimdata == dim-1: - data = self._normalizer.normalize_by(self.data_raw[:, indX], data) - - predicted_values = clf.predict(data) - predicted_values = self._normalizer.denormalize_by( - self.data_raw[:, target], predicted_values) - return predicted_values - - def predict(self, x_test, k=5, wt='distance'): - """ - Similar to SKlearn we assume that we have X_tr, Y_tr and X_test. Here - it is assumed that target is the last column in the codebook and data - has dim-1 columns - - :param x_test: input vector - :param k: number of neighbors to use - :param wt: method to use for the weights - (more detail in KNeighborsRegressor docs) - :returns: predicted values for the input data - """ - target = self.data_raw.shape[1]-1 - x_train = self.codebook.matrix[:, :target] - y_train = self.codebook.matrix[:, target] - clf = neighbors.KNeighborsRegressor(k, weights=wt) - clf.fit(x_train, y_train) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - x_test = self._normalizer.normalize_by( - self.data_raw[:, :target], x_test) - predicted_values = clf.predict(x_test) - - return self._normalizer.denormalize_by( - self.data_raw[:, target], predicted_values) - - def find_k_nodes(self, data, k=5): - from sklearn.neighbors import NearestNeighbors - # we find the k most similar nodes to the input vector - neighbor = NearestNeighbors(n_neighbors=k) - neighbor.fit(self.codebook.matrix) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - return neighbor.kneighbors( - self._normalizer.normalize_by(self.data_raw, data)) - - def bmu_ind_to_xy(self, bmu_ind): - """ - Translates a best matching unit index to the corresponding - matrix x,y coordinates. - - :param bmu_ind: node index of the best matching unit - (number of node from top left node) - :returns: corresponding (x,y) coordinate - """ - rows = self.codebook.mapsize[0] - cols = self.codebook.mapsize[1] - - # bmu should be an integer between 0 to no_nodes - out = np.zeros((bmu_ind.shape[0], 3)) - out[:, 2] = bmu_ind - out[:, 0] = rows-1-bmu_ind / cols - out[:, 0] = bmu_ind / cols - out[:, 1] = bmu_ind % cols - - return out.astype(int) - - def cluster(self, n_clusters=8): - import sklearn.cluster as clust - cl_labels = clust.KMeans(n_clusters=n_clusters).fit_predict( - self._normalizer.denormalize_by(self.data_raw, - self.codebook.matrix)) - self.cluster_labels = cl_labels - return cl_labels - - def predict_probability(self, data, target, k=5): - """ - Predicts probability of the input data to be target - - :param data: data to predict, it is assumed that 'target' is the last - column in the codebook, so data hould have dim-1 columns - :param target: target to predict probability - :param k: k parameter on KNeighborsRegressor - :returns: probability of data been target - """ - dim = self.codebook.matrix.shape[1] - ind = np.arange(0, dim) - indx = ind[ind != target] - x = self.codebook.matrix[:, indx] - y = self.codebook.matrix[:, target] - - clf = neighbors.KNeighborsRegressor(k, weights='distance') - clf.fit(x, y) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - dimdata = data.shape[1] - - if dimdata == dim: - data[:, target] = 0 - data = self._normalizer.normalize_by(self.data_raw, data) - data = data[:, indx] - - elif dimdata == dim-1: - data = self._normalizer.normalize_by(self.data_raw[:, indx], data) - - weights, ind = clf.kneighbors(data, n_neighbors=k, - return_distance=True) - weights = 1./weights - sum_ = np.sum(weights, axis=1) - weights = weights/sum_[:, np.newaxis] - labels = np.sign(self.codebook.matrix[ind, target]) - labels[labels >= 0] = 1 - - # for positives - pos_prob = labels.copy() - pos_prob[pos_prob < 0] = 0 - pos_prob *= weights - pos_prob = np.sum(pos_prob, axis=1)[:, np.newaxis] - - # for negatives - neg_prob = labels.copy() - neg_prob[neg_prob > 0] = 0 - neg_prob = neg_prob * weights * -1 - neg_prob = np.sum(neg_prob, axis=1)[:, np.newaxis] - - return np.concatenate((pos_prob, neg_prob), axis=1) - - def node_activation(self, data, target=None, wt='distance'): - weights, ind = None, None - - if not target: - clf = neighbors.KNeighborsClassifier( - n_neighbors=self.codebook.nnodes) - labels = np.arange(0, self.codebook.matrix.shape[0]) - clf.fit(self.codebook.matrix, labels) - - # The codebook values are all normalized - # we can normalize the input data based on mean and std of - # original data - data = self._normalizer.normalize_by(self.data_raw, data) - weights, ind = clf.kneighbors(data) - - # Softmax function - weights = 1./weights - - return weights, ind - - def calculate_topographic_error(self): - bmus1 = self.find_bmu(self.data_raw, njb=1, nth=1) - bmus2 = self.find_bmu(self.data_raw, njb=1, nth=2) - bmus_gap = np.abs((self.bmu_ind_to_xy(np.array(bmus1[0]))[:, 0:2] - self.bmu_ind_to_xy(np.array(bmus2[0]))[:, 0:2]).sum(axis=1)) - return np.mean(bmus_gap != 1) - - def calculate_map_size(self, lattice): - """ - Calculates the optimal map size given a dataset using eigenvalues and eigenvectors. Matlab ported - :lattice: 'rect' or 'hex' - :return: map sizes - """ - D = self.data_raw.copy() - dlen = D.shape[0] - dim = D.shape[1] - munits = np.ceil(5 * (dlen ** 0.5)) - A = np.ndarray(shape=[dim, dim]) + np.Inf - - for i in range(dim): - D[:, i] = D[:, i] - np.mean(D[np.isfinite(D[:, i]), i]) - - for i in range(dim): - for j in range(dim): - c = D[:, i] * D[:, j] - c = c[np.isfinite(c)] - A[i, j] = sum(c) / len(c) - A[j, i] = A[i, j] - - VS = np.linalg.eig(A) - eigval = sorted(np.linalg.eig(A)[0]) - if eigval[-1] == 0 or eigval[-2] * munits < eigval[-1]: - ratio = 1 - else: - ratio = np.sqrt(eigval[-1] / eigval[-2]) - - if lattice == "rect": - size1 = min(munits, round(np.sqrt(munits / ratio))) - else: - size1 = min(munits, round(np.sqrt(munits / ratio*np.sqrt(0.75)))) - - size2 = round(munits / size1) - - return [int(size1), int(size2)] - - -# Since joblib.delayed uses Pickle, this method needs to be a top level -# method in order to be pickled -# Joblib is working on adding support for cloudpickle or dill which will allow -# class methods to be pickled -# when that that comes out we can move this to SOM class -def _chunk_based_bmu_find(input_matrix, codebook, y2, nth=1): - """ - Finds the corresponding bmus to the input matrix. - - :param input_matrix: a matrix of input data, representing input vector as - rows, and vectors features/dimention as cols - when parallelizing the search, the input_matrix can be - a sub matrix from the bigger matrix - :param codebook: matrix of weights to be used for the bmu search - :param y2: - """ - dlen = input_matrix.shape[0] - nnodes = codebook.shape[0] - bmu = np.empty((dlen, 2)) - - # It seems that small batches for large dlen is really faster: - # that is because of ddata in loops and n_jobs. for large data it slows - # down due to memory needs in parallel - blen = min(50, dlen) - i0 = 0 - - while i0+1 <= dlen: - low = i0 - high = min(dlen, i0+blen) - i0 = i0+blen - ddata = input_matrix[low:high+1] - d = np.dot(codebook, ddata.T) - d *= -2 - d += y2.reshape(nnodes, 1) - bmu[low:high+1, 0] = np.argpartition(d, nth, axis=0)[nth-1] - bmu[low:high+1, 1] = np.partition(d, nth, axis=0)[nth-1] - del ddata - - return bmu - - - diff --git a/build/lib/sompy/visualization/__init__.py b/build/lib/sompy/visualization/__init__.py deleted file mode 100644 index 3d7dfea..0000000 --- a/build/lib/sompy/visualization/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from . import dotmap, histogram, hitmap, mapview, umatrix diff --git a/build/lib/sompy/visualization/bmuhits.py b/build/lib/sompy/visualization/bmuhits.py deleted file mode 100644 index d54328d..0000000 --- a/build/lib/sompy/visualization/bmuhits.py +++ /dev/null @@ -1,54 +0,0 @@ -from collections import Counter - -import matplotlib -import numpy as np -from matplotlib import pyplot as plt - -from .mapview import MapView - - -class BmuHitsView(MapView): - def _set_labels(self, cents, ax, labels, onlyzeros, fontsize): - for i, txt in enumerate(labels): - if onlyzeros == True: - if txt > 0: - txt = "" - ax.annotate(txt, (cents[i, 1] + 0.5, cents[-(i+1), 0] + 0.5), va="center", ha="center", size=fontsize) - - def show(self, som, anotate=True, onlyzeros=False, labelsize=7, cmap="jet", logaritmic = False): - (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, - axis_num) = self._calculate_figure_params(som, 1, 1) - - self.prepare() - ax = plt.gca() - counts = Counter(som._bmu[0]) - counts = [counts.get(x, 0) for x in range(som.codebook.mapsize[0] * som.codebook.mapsize[1])] - mp = np.array(counts).reshape(som.codebook.mapsize[0], - som.codebook.mapsize[1]) - - if not logaritmic: - norm = matplotlib.colors.Normalize( - vmin=0, - vmax=np.max(mp.flatten()), - clip=True) - else: - norm = matplotlib.colors.LogNorm( - vmin=1, - vmax=np.max(mp.flatten())) - - msz = som.codebook.mapsize - - cents = som.bmu_ind_to_xy(np.arange(0, msz[0] * msz[1])) - - if anotate: - self._set_labels(cents, ax, counts, onlyzeros, labelsize) - - - pl = plt.pcolor(mp[::-1], norm=norm, cmap=cmap) - - plt.axis([0, som.codebook.mapsize[1], 0, som.codebook.mapsize[0]]) - ax.set_yticklabels([]) - ax.set_xticklabels([]) - plt.colorbar(pl) - - plt.show() diff --git a/build/lib/sompy/visualization/dotmap.py b/build/lib/sompy/visualization/dotmap.py deleted file mode 100644 index 7ba10ff..0000000 --- a/build/lib/sompy/visualization/dotmap.py +++ /dev/null @@ -1,68 +0,0 @@ -from .view import MatplotView -from matplotlib import pyplot as plt -import numpy as np - - -class DotMapView(MatplotView): - - def init_figure(self, dim, cols): - no_row_in_plot = dim/cols + 1 - no_col_in_plot = dim if no_row_in_plot <= 1 else cols - h = .1 - w = .1 - self.width = no_col_in_plot*2.5*(1+w) - self.height = no_row_in_plot*2.5*(1+h) - self.prepare() - - def plot(self, data, coords, msz0, msz1, colormap, dlen, dim, rows, cols): - for i in range(dim): - plt.subplot(rows, cols, i+1) - - # This uses the colors uniquely for each record, while in normal - # views, it is based on the values within each dimensions. This is - # important when we are dealing with time series. Where we don't - # want to normalize colors within each time period, rather we like - # to see the patterns of each data records in time. - mn = np.min(data[:, :], axis=1) - mx = np.max(data[:, :], axis=1) - - for j in range(dlen): - plt.scatter(coords[j, 1], - msz0-1-coords[j, 0], - c=data[j, i], - vmax=mx[j], vmin=mn[j], - s=90, - marker='.', - edgecolor='None', - cmap=colormap, - alpha=1) - - eps = .0075 - plt.xlim(0-eps, msz1-1+eps) - plt.ylim(0-eps, msz0-1+eps) - plt.xticks([]) - plt.yticks([]) - - def show(self, som, which_dim='all', colormap=None, cols=None): - plt.cm.get_cmap(colormap) if colormap else plt.cm.get_cmap('RdYlBu_r') - - data = som.data_raw - msz0, msz1 = som.codebook.mapsize - coords = som.bmu_ind_to_xy(som.project_data(data))[:, :2] - cols = cols if cols else 8 # 8 is arbitrary - rows = data.shape[1]/cols+1 - - if which_dim == 'all': - dim = data.shape[0] - self.init_figure(dim, cols) - self.plot(data, coords, msz0, msz1, colormap, data.shape[0], - data.shape[1], rows, cols) - - else: - dim = 1 if type(which_dim) is int else len(which_dim) - self.init_figure(dim, cols) - self.plot(data, coords, msz0, msz1, colormap, data.shape[0], - len(which_dim), rows, cols) - - plt.tight_layout() - plt.subplots_adjust(hspace=.16, wspace=.05) diff --git a/build/lib/sompy/visualization/histogram.py b/build/lib/sompy/visualization/histogram.py deleted file mode 100644 index cc71996..0000000 --- a/build/lib/sompy/visualization/histogram.py +++ /dev/null @@ -1,59 +0,0 @@ -from .view import MatplotView -from matplotlib import pyplot as plt -from matplotlib import cm -from matplotlib.colors import LogNorm -import numpy as np - - -class Hist2d(MatplotView): - - def _fill_hist(self, x, y, mapsize, data_coords, what='train'): - x = np.arange(.5, mapsize[1]+.5, 1) - y = np.arange(.5, mapsize[0]+.5, 1) - X, Y = np.meshgrid(x, y) - - if what == 'train': - a = plt.hist2d(x, y, bins=(mapsize[1], mapsize[0]), alpha=.0, - cmap=cm.jet) - area = a[0].T * 12 - plt.scatter(data_coords[:, 1], mapsize[0] - .5 - data_coords[:, 0], - s=area.flatten(), alpha=.9, c='None', marker='o', - cmap='jet', linewidths=3, edgecolor='r') - - else: - a = plt.hist2d(x, y, bins=(mapsize[1], mapsize[0]), alpha=.0, - cmap=cm.jet, norm=LogNorm()) - area = a[0].T*50 - plt.scatter(data_coords[:, 1] + .5, - mapsize[0] - .5 - data_coords[:, 0], - s=area, alpha=0.9, c='None', marker='o', cmap='jet', - linewidths=3, edgecolor='r') - plt.scatter(data_coords[:, 1]+.5, mapsize[0]-.5-data_coords[:, 0], - s=area, alpha=0.2, c='b', marker='o', cmap='jet', - linewidths=3, edgecolor='r') - - plt.xlim(0, mapsize[1]) - plt.ylim(0, mapsize[0]) - - def show(self, som, data=None): - # First Step: show the hitmap of all the training data - coord = som.bmu_ind_to_xy(som.project_data(som.data_raw)) - - self.prepare() - - ax = self._fig.add_subplot(111) - ax.xaxis.set_ticks([i for i in range(0, som.codebook.mapsize[1])]) - ax.yaxis.set_ticks([i for i in range(0, som.codebook.mapsize[0])]) - ax.xaxis.set_ticklabels([]) - ax.yaxis.set_ticklabels([]) - ax.grid(True, linestyle='-', linewidth=.5) - - self._fill_hist(coord[:, 1], coord[:, 0], som.codebook.mapsize, - som.bmu_ind_to_xy(np.arange(som.codebook.nnodes))) - - if data: - coord_d = som.bmu_ind_to_xy(som.project_data(data)) - self._fill_hist(coord[:, 1], coord[:, 0], som.codebook.mapsize, - coord_d, 'data') - - plt.show() diff --git a/build/lib/sompy/visualization/hitmap.py b/build/lib/sompy/visualization/hitmap.py deleted file mode 100644 index c0dd482..0000000 --- a/build/lib/sompy/visualization/hitmap.py +++ /dev/null @@ -1,37 +0,0 @@ -from .view import MatplotView -from matplotlib import pyplot as plt -import numpy as np - - -class HitMapView(MatplotView): - - def _set_labels(self, cents, ax, labels): - for i, txt in enumerate(labels): - ax.annotate(txt, (cents[i, 1], cents[i, 0]), size=10, va="center") - - def show(self, som, data=None): - - try: - codebook = getattr(som, 'cluster_labels') - except: - codebook = som.cluster() - - # codebook = getattr(som, 'cluster_labels', som.cluster()) - msz = som.codebook.mapsize - - self.prepare() - ax = self._fig.add_subplot(111) - - if data: - proj = som.project_data(data) - cents = som.bmu_ind_to_xy(proj) - self._set_labels(cents, ax, codebook[proj]) - - else: - cents = som.bmu_ind_to_xy(np.arange(0, msz[0]*msz[1])) - self._set_labels(cents, ax, codebook) - - plt.imshow(codebook.reshape(msz[0], msz[1])[::], alpha=.5) - plt.show() - - return cents diff --git a/build/lib/sompy/visualization/mapview.py b/build/lib/sompy/visualization/mapview.py deleted file mode 100644 index f1258af..0000000 --- a/build/lib/sompy/visualization/mapview.py +++ /dev/null @@ -1,187 +0,0 @@ -import matplotlib -from .view import MatplotView -from matplotlib import pyplot as plt -import numpy as np -import ipdb - - -class MapView(MatplotView): - - def _calculate_figure_params(self, som, which_dim, col_sz): - - # add this to avoid error when normalization is not used - if som._normalizer: - codebook = som._normalizer.denormalize_by(som.data_raw, som.codebook.matrix) - else: - codebook = som.codebook.matrix - - indtoshow, sV, sH = None, None, None - - if which_dim == 'all': - dim = som._dim - row_sz = np.ceil(float(dim) / col_sz) - msz_row, msz_col = som.codebook.mapsize - ratio_hitmap = msz_row / float(msz_col) - ratio_fig = row_sz / float(col_sz) - indtoshow = np.arange(0, dim).T - sH, sV = 16, 16*ratio_fig*ratio_hitmap - - elif type(which_dim) == int: - dim = 1 - msz_row, msz_col = som.codebook.mapsize - ratio_hitmap = msz_row / float(msz_col) - indtoshow = np.zeros(1) - indtoshow[0] = int(which_dim) - sH, sV = 16, 16 * ratio_hitmap - - elif type(which_dim) == list: - max_dim = codebook.shape[1] - dim = len(which_dim) - row_sz = np.ceil(float(dim) / col_sz) - msz_row, msz_col = som.codebook.mapsize - ratio_hitmap = msz_row / float(msz_col) - ratio_fig = row_sz / float(col_sz) - indtoshow = np.asarray(which_dim).T - sH, sV = 16, 16*ratio_fig*ratio_hitmap - - no_row_in_plot = dim / col_sz + 1 # 6 is arbitrarily selected - if no_row_in_plot <= 1: - no_col_in_plot = dim - else: - no_col_in_plot = col_sz - - axis_num = 0 - - width = sH - height = sV - - return (width, height, indtoshow, no_row_in_plot, no_col_in_plot, - axis_num) - - -class View2D(MapView): - - def show(self, som, what='codebook', which_dim='all', cmap=None, - col_sz=None, desnormalize=False): - (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, - axis_num) = self._calculate_figure_params(som, which_dim, col_sz) - self.prepare() - - if not desnormalize: - codebook = som.codebook.matrix - else: - codebook = som._normalizer.denormalize_by(som.data_raw, som.codebook.matrix) - - if which_dim == 'all': - names = som._component_names[0] - elif type(which_dim) == int: - names = [som._component_names[0][which_dim]] - elif type(which_dim) == list: - names = som._component_names[0][which_dim] - - - while axis_num < len(indtoshow): - axis_num += 1 - ax = plt.subplot(no_row_in_plot, no_col_in_plot, axis_num) - ind = int(indtoshow[axis_num-1]) - - min_color_scale = np.mean(codebook[:, ind].flatten()) - 1 * np.std(codebook[:, ind].flatten()) - max_color_scale = np.mean(codebook[:, ind].flatten()) + 1 * np.std(codebook[:, ind].flatten()) - min_color_scale = min_color_scale if min_color_scale >= min(codebook[:, ind].flatten()) else \ - min(codebook[:, ind].flatten()) - max_color_scale = max_color_scale if max_color_scale <= max(codebook[:, ind].flatten()) else \ - max(codebook[:, ind].flatten()) - norm = matplotlib.colors.Normalize(vmin=min_color_scale, vmax=max_color_scale, clip=True) - - mp = codebook[:, ind].reshape(som.codebook.mapsize[0], - som.codebook.mapsize[1]) - pl = plt.pcolor(mp[::-1], norm=norm) - plt.axis([0, som.codebook.mapsize[1], 0, som.codebook.mapsize[0]]) - plt.title(names[axis_num - 1]) - ax.set_yticklabels([]) - ax.set_xticklabels([]) - plt.colorbar(pl) - - #plt.show() - - -class View2DPacked(MapView): - - def _set_axis(self, ax, msz0, msz1): - plt.axis([0, msz0, 0, msz1]) - plt.axis('off') - ax.axis('off') - - def show(self, som, what='codebook', which_dim='all', cmap=None, - col_sz=None): - if col_sz is None: - col_sz = 6 - (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, - axis_num) = self._calculate_figure_params(som, which_dim, col_sz) - codebook = som.codebook.matrix - - cmap = cmap or plt.cm.get_cmap('RdYlBu_r') - msz0, msz1 = som.codebook.mapsize - compname = som.component_names - if what == 'codebook': - h = .1 - w = .1 - self.width = no_col_in_plot*2.5*(1+w) - self.height = no_row_in_plot*2.5*(1+h) - self.prepare() - - while axis_num < len(indtoshow): - axis_num += 1 - ax = self._fig.add_subplot(no_row_in_plot, no_col_in_plot, - axis_num) - ax.axis('off') - ind = int(indtoshow[axis_num-1]) - mp = codebook[:, ind].reshape(msz0, msz1) - plt.imshow(mp[::-1], norm=None, cmap=cmap) - self._set_axis(ax, msz0, msz1) - - if self.show_text is True: - plt.title(compname[0][ind]) - font = {'size': self.text_size} - plt.rc('font', **font) - if what == 'cluster': - try: - codebook = getattr(som, 'cluster_labels') - except: - codebook = som.cluster() - - h = .2 - w = .001 - self.width = msz0/2 - self.height = msz1/2 - self.prepare() - - ax = self._fig.add_subplot(1, 1, 1) - mp = codebook[:].reshape(msz0, msz1) - plt.imshow(mp[::-1], cmap=cmap) - - self._set_axis(ax, msz0, msz1) - - plt.subplots_adjust(hspace=h, wspace=w) - - plt.show() - - -class View1D(MapView): - - def show(self, som, what='codebook', which_dim='all', cmap=None, - col_sz=None): - (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, - axis_num) = self._calculate_figure_params(som, which_dim, col_sz) - self.prepare() - - codebook = som.codebook.matrix - - while axis_num < len(indtoshow): - axis_num += 1 - plt.subplot(no_row_in_plot, no_col_in_plot, axis_num) - ind = int(indtoshow[axis_num-1]) - mp = codebook[:, ind] - plt.plot(mp, '-k', linewidth=0.8) - - #plt.show() diff --git a/build/lib/sompy/visualization/umatrix.py b/build/lib/sompy/visualization/umatrix.py deleted file mode 100644 index afa8ae8..0000000 --- a/build/lib/sompy/visualization/umatrix.py +++ /dev/null @@ -1,95 +0,0 @@ -from .view import MatplotView -from matplotlib import pyplot as plt -from pylab import imshow, contour -from math import sqrt -import numpy as np -import scipy - - -class UMatrixView(MatplotView): - - def build_u_matrix(self, som, distance=1, row_normalized=False): - UD2 = som.calculate_map_dist() - Umatrix = np.zeros((som.codebook.nnodes, 1)) - codebook = som.codebook.matrix - if row_normalized: - vector = som._normalizer.normalize_by(codebook.T, codebook.T, - method='var').T - else: - vector = codebook - - for i in range(som.codebook.nnodes): - codebook_i = vector[i][np.newaxis, :] - neighborbor_ind = UD2[i][0:] <= distance - neighborbor_codebooks = vector[neighborbor_ind] - Umatrix[i] = scipy.spatial.distance_matrix( - codebook_i, neighborbor_codebooks).mean() - - return Umatrix.reshape(som.codebook.mapsize) - - def show(self, som, distance2=1, row_normalized=False, show_data=True, - contooor=True, blob=False, labels=False): - umat = self.build_u_matrix(som, distance=distance2, - row_normalized=row_normalized) - msz = som.codebook.mapsize - proj = som.project_data(som.data_raw) - coord = som.bmu_ind_to_xy(proj) - - fig, ax = plt.subplots(1, 1) - imshow(umat, cmap=plt.cm.get_cmap('RdYlBu_r'), alpha=1) - - if contooor: - mn = np.min(umat.flatten()) - mx = np.max(umat.flatten()) - std = np.std(umat.flatten()) - md = np.median(umat.flatten()) - mx = md + 0*std - contour(umat, np.linspace(mn, mx, 15), linewidths=0.7, - cmap=plt.cm.get_cmap('Blues')) - - if show_data: - plt.scatter(coord[:, 1], coord[:, 0], s=2, alpha=1., c='Gray', - marker='o', cmap='jet', linewidths=3, edgecolor='Gray') - plt.axis('off') - - if labels: - if labels is True: - labels = som.build_data_labels() - for label, x, y in zip(labels, coord[:, 1], coord[:, 0]): - plt.annotate(str(label), xy=(x, y), - horizontalalignment='center', - verticalalignment='center') - - ratio = float(msz[0])/(msz[0]+msz[1]) - fig.set_size_inches((1-ratio)*15, ratio*15) - plt.tight_layout() - plt.subplots_adjust(hspace=.00, wspace=.000) - sel_points = list() - - if blob: - from skimage.color import rgb2gray - from skimage.feature import blob_log - - image = 1 / umat - rgb2gray(image) - - # 'Laplacian of Gaussian' - blobs = blob_log(image, max_sigma=5, num_sigma=4, threshold=.152) - blobs[:, 2] = blobs[:, 2] * sqrt(2) - imshow(umat, cmap=plt.cm.get_cmap('RdYlBu_r'), alpha=1) - sel_points = list() - - for blob in blobs: - row, col, r = blob - c = plt.Circle((col, row), r, color='red', linewidth=2, - fill=False) - ax.add_patch(c) - dist = scipy.spatial.distance_matrix( - coord[:, :2], np.array([row, col])[np.newaxis, :]) - sel_point = dist <= r - plt.plot(coord[:, 1][sel_point[:, 0]], - coord[:, 0][sel_point[:, 0]], '.r') - sel_points.append(sel_point[:, 0]) - - plt.show() - return sel_points, umat diff --git a/build/lib/sompy/visualization/view.py b/build/lib/sompy/visualization/view.py deleted file mode 100644 index c618a23..0000000 --- a/build/lib/sompy/visualization/view.py +++ /dev/null @@ -1,54 +0,0 @@ -from matplotlib import pyplot as plt - - -class View(object): - def __init__(self, width, height, title, show_axis=True, packed=True, - text_size=2.8, show_text=True, col_size=6, *args, **kwargs): - self.width = width - self.height = height - self.title = title - self.show_axis = show_axis - self.packed = packed - self.text_size = text_size - self.show_text = show_text - self.col_size = col_size - - def prepare(self, *args, **kwargs): - raise NotImplementedError() - - def save(self, filename): - raise NotImplementedError() - - def show(self, *args, **kwrags): - raise NotImplementedError() - - -class MatplotView(View): - - def __init__(self, width, height, title, show_axis=True, packed=True, - text_size=2.8, show_text=True, col_size=6, *args, **kwargs): - super(MatplotView, self).__init__(width, height, title, show_axis, - packed, text_size, show_text, - col_size, *args, **kwargs) - self._fig = None - - def __del__(self): - self._close_fig() - - def _close_fig(self): - if self._fig: - plt.close(self._fig) - - def prepare(self, *args, **kwargs): - self._close_fig() - self._fig = plt.figure(figsize=(self.width, self.height)) - plt.title(self.title) - plt.axis('off') - plt.rc('font', **{'size': self.text_size}) - - def save(self, filename, transparent=False, bbox_inches='tight', dpi=400): - self._fig.savefig(filename, transparent=transparent, dpi=dpi, - bbox_inches=bbox_inches) - - def show(self, *args, **kwrags): - raise NotImplementedError() diff --git a/dist/SOMPY-1.0-py2.7.egg b/dist/SOMPY-1.0-py2.7.egg deleted file mode 100644 index 335c6cb..0000000 Binary files a/dist/SOMPY-1.0-py2.7.egg and /dev/null differ diff --git a/dist/SOMPY-1.0-py3.5.egg b/dist/SOMPY-1.0-py3.5.egg deleted file mode 100644 index e2f95eb..0000000 Binary files a/dist/SOMPY-1.0-py3.5.egg and /dev/null differ diff --git a/sompy/codebook.py b/sompy/codebook.py index b5e16c4..1195347 100644 --- a/sompy/codebook.py +++ b/sompy/codebook.py @@ -1,4 +1,5 @@ import numpy as np +import scipy as sp from sklearn.decomposition import PCA #from sklearn.decomposition import RandomizedPCA# (randomizedpca is deprecated) @@ -12,6 +13,16 @@ class InvalidNodeIndexError(Exception): class InvalidMapsizeError(Exception): pass +def generate_hex_lattice(n_rows, n_columns): + x_coord = [] + y_coord = [] + for i in range(n_rows): + for j in range(n_columns): + x_coord.append(i*1.5) + y_coord.append(np.sqrt(2/3)*(2*j+(1+i)%2)) + coordinates = np.column_stack([x_coord, y_coord]) + return coordinates + class Codebook(object): @@ -34,6 +45,12 @@ def __init__(self, mapsize, lattice='rect'): self.matrix = np.asarray(self.mapsize) self.initialized = False + if lattice == "hexa": + n_rows, n_columns = mapsize + coordinates = generate_hex_lattice(n_rows, n_columns) + self.lattice_distances = (sp.spatial.distance_matrix(coordinates, coordinates) + .reshape(n_rows * n_columns, n_rows, n_columns)) + @timeit() def random_initialization(self, data): """ @@ -129,7 +146,7 @@ def grid_dist(self, node_ind): return self._hexa_dist(node_ind) def _hexa_dist(self, node_ind): - raise NotImplementedError() + return self.lattice_distances[node_ind] def _rect_dist(self, node_ind): """ diff --git a/sompy/examples/.ipynb_checkpoints/California Housing-checkpoint.ipynb b/sompy/examples/.ipynb_checkpoints/California Housing-checkpoint.ipynb deleted file mode 100644 index ee62259..0000000 --- a/sompy/examples/.ipynb_checkpoints/California Housing-checkpoint.ipynb +++ /dev/null @@ -1,306 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "# Self Organizing Maps example - California Housing" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this document, the SOMPY lib is going to be used in order to provide an example of usage of the Self Organising Maps algorithm. The data to be used will be the California Housing dataset, included in the SciKit Learn library and included below" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "import numpy as np\n", - "from matplotlib import pyplot as plt\n", - "from sompy.sompy import SOMFactory\n", - "from sklearn.datasets import fetch_california_housing" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data Loading" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "First of all the data is loaded into the local environment as a numpy array. " - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "California housing dataset.\n", - "\n", - "The original database is available from StatLib\n", - "\n", - " http://lib.stat.cmu.edu/\n", - "\n", - "The data contains 20,640 observations on 9 variables.\n", - "\n", - "This dataset contains the average house value as target variable\n", - "and the following input variables (features): average income,\n", - "housing average age, average rooms, average bedrooms, population,\n", - "average occupation, latitude, and longitude in that order.\n", - "\n", - "References\n", - "----------\n", - "\n", - "Pace, R. Kelley and Ronald Barry, Sparse Spatial Autoregressions,\n", - "Statistics and Probability Letters, 33 (1997) 291-297.\n", - "\n", - "\n", - "FEATURES: MedInc, HouseAge, AveRooms, AveBedrms, Population, AveOccup, Latitude, Longitude, HouseValue\n" - ] - } - ], - "source": [ - "data = fetch_california_housing()\n", - "descr = data.DESCR\n", - "names = fetch_california_housing().feature_names+[\"HouseValue\"]\n", - "\n", - "data = np.column_stack([data.data, data.target])\n", - "print descr\n", - "print \"FEATURES: \", \", \".join(names)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## SOM Training" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The SOM training consists in 2 phases: the rough and the finetune one. The parameters that can be configured in the training step are:\n", - "\n", - "- The size of each individual grid\n", - "- The rough and finetune iterations\n", - "- The rough and finetune initial and final radiuses\n", - "- The initialization mechanism (random/pca)\n", - "\n", - "For the current example, only the rough/finetune iterations and the initialization mechanism parameters have been chosen. The other ones have not been specified so that the algorithm will choose them authomatically. \n", - "\n", - "For quantifying the error of the approximation, 2 metrics should be computed: \n", - "\n", - "- **The quantization error**: average distance between each data vector and its BMU.\n", - "- **The topographic error**: the proportion of all data vectors for which first and second BMUs are not adjacent units.\n", - "\n", - "A rule of thumb is to generate several models with different parameters and choose the one which, having a topographic error very near to zero, has the lowest quantization error. It is important to hold the topographic error very low in order to make the components smooth and easy to understand. " - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "#msz = calculate_msz(data)\n", - "sm = SOMFactory().build(data, normalization = 'var', initialization='random', component_names=names)\n", - "sm.train(n_job=1, verbose=False, train_rough_len=2, train_finetune_len=5)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Topographic error = 0.0891957364341; Quantization error = 0.843054042711\n" - ] - } - ], - "source": [ - "topographic_error = sm.calculate_topographic_error()\n", - "quantization_error = np.mean(sm._bmu[1])\n", - "print \"Topographic error = %s; Quantization error = %s\" % (topographic_error, quantization_error)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Visualization" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Components map" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false, - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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KQ/cw7as+a0sQ7E52xOJePGukhAmOvtGuf3jNti/P2qcc+n0z7aFTbPmVuwce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\nAIC2ItEEAAAAALTV/w/QH2prfCLxTgAAAABJRU5ErkJggg==\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from sompy.visualization.mapview import View2D\n", - "view2D = View2D(10,10,\"rand data\",text_size=10)\n", - "view2D.show(sm, col_sz=4, which_dim=\"all\", desnormalize=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Hits map" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false, - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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LI+fvSpibuReoyFaiRAlV4gD5rmD0MscB9eqinI0HczPmx3oLQ61zZ8p5YU9j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Tvyyiuv0KBBA/r168elS5eM2SSmTp2Kt7c37u7udOjQga1btwKQlJREjx498PDwwNPTkzfe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\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57+XzdPjwYfbs2YOfnx9nz54lMTERpVLJ/fv3mTVrFk2bNi00XP11hISEsH//frZu3cq2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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from sompy.visualization.bmuhits import BmuHitsView\n", - "\n", - "vhts = BmuHitsView(4,4,\"Hits Map\",text_size=12)\n", - "vhts.show(sm, anotate=True, onlyzeros=False, labelsize=12, cmap=\"Greys\", logaritmic=False)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### K-Means clustering" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "image/png": 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Cp+sZynQ9LxRAlfQRkqd00sfJIHktFkPtTl6jIONHl20JVG22yvYxCRllw8yYnEkJn/g8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2ybt4x2NPbeFeiEwh77vqldDh+J+fZD/xH6AAB6wj2ixtcBigmA6sBn9Oiz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xnynX8I2LwV7twZ4OTrYZeqsSVZxjgJBjWqZroe1earsH3uaWyfvA32vIPFTqd5GtazG9tj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\nEEIIIYQQQgghG8j/DxtZCKXuZolOAAAAAElFTkSuQmCC\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from sompy.visualization.hitmap import HitMapView\n", - "sm.cluster(4)\n", - "hits = HitMapView(20,20,\"Clustering\",text_size=12)\n", - "a=hits.show(sm)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Conclusions" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "From the visualizations above we can extract different conclusions like,\n", - "- The houses which have, on average, more bedrooms are generally on lower average income areas.\n", - "- The highest occupations occours only in cities where the population is high.\n", - "- The latitude and longitude of the samples have a strong negative correlation. It can be because California is diagonally oriented with respect to the coordinates system.\n", - "- The most demanded houses (AveOccup) are placed on the 37~38 latitude and -121.6~-121 longitude; i.e. near San-Francisco area\n", - "- Old houses are more likely to have less rooms and bedrooms on average.\n", - "- Low average income areas usually have less rooms and bedrooms than high average ones\n", - "- The house value seems to be related with the average income of the area where it sits.\n", - "\n", - "It is important to remark that there are areas on the map where the density of instances is lower than others. It is represented by the hit map and it should be taken in consideration when interpreting the components map.\n", - "\n", - "The clustering map can be used to help to find out the different behaviors represented in the components map." - ] - } - ], - "metadata": { - "anaconda-cloud": {}, - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.5.3" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/sompy/examples/AirFlights_hexagonal_grid.ipynb b/sompy/examples/AirFlights_hexagonal_grid.ipynb new file mode 100644 index 0000000..d652307 --- /dev/null +++ b/sompy/examples/AirFlights_hexagonal_grid.ipynb @@ -0,0 +1,692 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Study of airflight delay causes with Self Organizing Maps - Example of hexagonal lattice" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook is intended to be a brief guide on how to use Self Organizing Maps with the **SOMPY** library in Python. We are going to use hexagonal lattice in this example in order to understand the main causes of airflight cancellations\n", + "\n", + "##### Data description\n", + "________________________\n", + "\n", + "The U.S. Department of Transportation's (DOT) Bureau of Transportation Statistics (BTS) tracks the on-time performance of domestic flights operated by large air carriers. Summary information on the number of on-time, delayed, canceled and diverted flights appears in DOT's monthly Air Travel Consumer Report, published about 30 days after the month's end, as well as in summary tables posted on this website. BTS began collecting details on the causes of flight delays in June 2003. Summary statistics and raw data are made available to the public at the time the Air Travel Consumer Report is released.\n", + "\n", + "This version of the dataset was compiled from the Statistical Computing Statistical Graphics 2009 Data Expo and is also available [here](http://stat-computing.org/dataexpo/2009/the-data.html), [here](https://www.transtats.bts.gov/Fields.asp?Table_ID=236) and [here](https://www.kaggle.com/giovamata/airlinedelaycauses)\n", + "\n", + "**Fields description**\n", + "__________________________\n", + "1.\t**Year**:\t2008\n", + "2.\t**Month**:\t1-12\n", + "3.\t**DayofMonth**:\t1-31\n", + "4.\t**DayOfWeek**:\t1 (Monday) - 7 (Sunday)\n", + "5.\t**DepTime**:\tactual departure time (local, hhmm)\n", + "6.\t**CRSDepTime**:\tscheduled departure time (local, hhmm)\n", + "7.\t**ArrTime**:\tactual arrival time (local, hhmm)\n", + "8.\t**CRSArrTime**:\tscheduled arrival time (local, hhmm)\n", + "9.\t**UniqueCarrier**:\tunique carrier code\n", + "10.\t**FlightNum**:\tflight number\n", + "11.\t**TailNum**:\tplane tail number\n", + "12.\t**ActualElapsedTime**:\tin minutes\n", + "13.\t**CRSElapsedTime**:\tin minutes\n", + "14.\t**AirTime**:\tin minutes\n", + "15.\t**ArrDelay**:\tarrival delay, in minutes\n", + "16.\t**DepDelay**:\tdeparture delay, in minutes\n", + "17.\t**Origin**:\torigin IATA airport code\n", + "18.\t**Dest**:\tdestination IATA airport code\n", + "19.\t**Distance**:\tin miles\n", + "20.\t**TaxiIn**:\ttaxi in time, in minutes\n", + "21.\t**TaxiOut**:\ttaxi out time in minutes\n", + "22.\t**Cancelled**:\twas the flight cancelled?\n", + "23.\t**CancellationCode**:\treason for cancellation (A = carrier, B = weather, C = NAS, D = security)\n", + "24.\t**Diverted**:\t1 = yes, 0 = no\n", + "25.\t**CarrierDelay**:\tin minutes\n", + "26.\t**WeatherDelay**:\tin minutes\n", + "27.\t**NASDelay**:\tNational Air System delay in minutes\n", + "28.\t**SecurityDelay**\tin minutes\n", + "29.\t**LateAircraftDelay**\tin minutes" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "backend module://ipykernel.pylab.backend_inline version unknown\n" + ] + } + ], + "source": [ + "%matplotlib inline\n", + "import math\n", + "import glob\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pandas as pd\n", + "import urllib3\n", + "from sklearn.externals import joblib\n", + "import random\n", + "import matplotlib\n", + "from sompy.sompy import SOMFactory\n", + "from sompy.visualization.plot_tools import plot_hex_map\n", + "import logging\n" + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "!kaggle datasets download -d giovamata/airlinedelaycauses\n", + "!unzip airlinedelaycauses.zip" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data Processing" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv(\"./DelayedFlights.csv\")\n", + "\n", + "df = df[[\"Month\",\"DayofMonth\", \"DayOfWeek\",\"DepTime\", \"AirTime\",\n", + " \"Distance\", \"SecurityDelay\",\"WeatherDelay\", \"NASDelay\", \"CarrierDelay\",\n", + " \"ArrDelay\", \"DepDelay\", \"LateAircraftDelay\", \"Cancelled\"]]\n", + "clustering_vars = [\"Month\", \"DayofMonth\", \"DepTime\", \"AirTime\", \n", + " \"LateAircraftDelay\", \"DepDelay\", \"ArrDelay\", \"CarrierDelay\"]\n", + "df = df.fillna(0)\n", + "data = df[clustering_vars].values\n", + "names = clustering_vars" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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MonthDayofMonthDayOfWeekDepTimeAirTimeDistanceSecurityDelayWeatherDelayNASDelayCarrierDelayArrDelayDepDelayLateAircraftDelayCancelled
count1.936758e+061.936758e+061.936758e+061.936758e+061.936758e+061.936758e+061.936758e+061.936758e+061.936758e+061.936758e+061.936758e+061.936758e+061.936758e+061.936758e+06
mean6.111106e+001.575347e+013.984827e+001.518534e+031.078083e+027.656862e+025.805836e-022.385512e+009.675607e+001.235367e+014.201714e+014.318518e+011.629374e+013.268348e-04
std3.482546e+008.776272e+001.995966e+004.504853e+026.886184e+015.744797e+021.623934e+001.734036e+012.808958e+013.613493e+015.672935e+015.340250e+013.585904e+011.807562e-02
min1.000000e+001.000000e+001.000000e+001.000000e+000.000000e+001.100000e+010.000000e+000.000000e+000.000000e+000.000000e+00-1.090000e+026.000000e+000.000000e+000.000000e+00
25%3.000000e+008.000000e+002.000000e+001.203000e+035.800000e+013.380000e+020.000000e+000.000000e+000.000000e+000.000000e+009.000000e+001.200000e+010.000000e+000.000000e+00
50%6.000000e+001.600000e+014.000000e+001.545000e+039.000000e+016.060000e+020.000000e+000.000000e+000.000000e+000.000000e+002.400000e+012.400000e+010.000000e+000.000000e+00
75%9.000000e+002.300000e+016.000000e+001.900000e+031.370000e+029.980000e+020.000000e+000.000000e+006.000000e+001.000000e+015.500000e+015.300000e+011.800000e+010.000000e+00
max1.200000e+013.100000e+017.000000e+002.400000e+031.091000e+034.962000e+033.920000e+021.352000e+031.357000e+032.436000e+032.461000e+032.467000e+031.316000e+031.000000e+00
\n", + "
" + ], + "text/plain": [ + " Month DayofMonth DayOfWeek DepTime AirTime \\\n", + "count 1.936758e+06 1.936758e+06 1.936758e+06 1.936758e+06 1.936758e+06 \n", + "mean 6.111106e+00 1.575347e+01 3.984827e+00 1.518534e+03 1.078083e+02 \n", + "std 3.482546e+00 8.776272e+00 1.995966e+00 4.504853e+02 6.886184e+01 \n", + "min 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 0.000000e+00 \n", + "25% 3.000000e+00 8.000000e+00 2.000000e+00 1.203000e+03 5.800000e+01 \n", + "50% 6.000000e+00 1.600000e+01 4.000000e+00 1.545000e+03 9.000000e+01 \n", + "75% 9.000000e+00 2.300000e+01 6.000000e+00 1.900000e+03 1.370000e+02 \n", + "max 1.200000e+01 3.100000e+01 7.000000e+00 2.400000e+03 1.091000e+03 \n", + "\n", + " Distance SecurityDelay WeatherDelay NASDelay CarrierDelay \\\n", + "count 1.936758e+06 1.936758e+06 1.936758e+06 1.936758e+06 1.936758e+06 \n", + "mean 7.656862e+02 5.805836e-02 2.385512e+00 9.675607e+00 1.235367e+01 \n", + "std 5.744797e+02 1.623934e+00 1.734036e+01 2.808958e+01 3.613493e+01 \n", + "min 1.100000e+01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n", + "25% 3.380000e+02 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n", + "50% 6.060000e+02 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 \n", + "75% 9.980000e+02 0.000000e+00 0.000000e+00 6.000000e+00 1.000000e+01 \n", + "max 4.962000e+03 3.920000e+02 1.352000e+03 1.357000e+03 2.436000e+03 \n", + "\n", + " ArrDelay DepDelay LateAircraftDelay Cancelled \n", + "count 1.936758e+06 1.936758e+06 1.936758e+06 1.936758e+06 \n", + "mean 4.201714e+01 4.318518e+01 1.629374e+01 3.268348e-04 \n", + "std 5.672935e+01 5.340250e+01 3.585904e+01 1.807562e-02 \n", + "min -1.090000e+02 6.000000e+00 0.000000e+00 0.000000e+00 \n", + "25% 9.000000e+00 1.200000e+01 0.000000e+00 0.000000e+00 \n", + "50% 2.400000e+01 2.400000e+01 0.000000e+00 0.000000e+00 \n", + "75% 5.500000e+01 5.300000e+01 1.800000e+01 0.000000e+00 \n", + "max 2.461000e+03 2.467000e+03 1.316000e+03 1.000000e+00 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model Training " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As the data is relatively high, the model takes some time to train. We didn't finetune the hyperparameters of the algorithm and this is a potential improvement topic." + ] + }, + { + "cell_type": "raw", + "metadata": {}, + "source": [ + "%%time\n", + "# Train the model with different parameters. The more, the better. Each iteration is stored in disk for further study\n", + "for i in range(1000):\n", + " sm = SOMFactory().build(data, mapsize=[random.choice(list(range(15, 25))), \n", + " random.choice(list(range(10, 15)))],\n", + " normalization = 'var', initialization='random', component_names=names, lattice=\"hexa\")\n", + " sm.train(n_job=4, verbose=False, train_rough_len=30, train_finetune_len=100)\n", + " joblib.dump(sm, \"model_{}.joblib\".format(i))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "# Study the models trained and plot the errors obtained in order to select the best one\n", + "models_pool = glob.glob(\"./model*\")\n", + "errors=[]\n", + "for model_filepath in models_pool:\n", + " sm = joblib.load(model_filepath)\n", + " topographic_error = sm.calculate_topographic_error()\n", + " quantization_error = sm.calculate_quantization_error()\n", + " errors.append((topographic_error, quantization_error))\n", + "e_top, e_q = zip(*errors)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Y3izpQmDc9npgtaQTgAeBO2lpgqIIEtsnOsib1ommniZG9oz6aKGI6A/tahYTe20fNsV7tZp8bF8NXD0p7Z0tr/+gzWe/Ajynzvfsr0419TQxsiejhSJGTz+uajDtaCjbl5cvv2D7Pa0/wBe7U7zu6NTEsCZG9mS0UMRo6ddVDeoMnf1AzbSB1ammniZm5HZrlm9E9Id+XdWgXZ/Fc4HnAXMn9VscTtEHMTQ62dTTREdxOp8jptePTTb7o1/7KdvVLA4GHkcRUA5r+bkHeHXzReueNPV0zlXX7+D5F3+JRed/judf/KWeV51juPVrk83+6NeFH6etWdj+KvBVSX9t+/tdLFPX9XqewbDINq3RbcO4V0cnl9PppDqT8u4r97N4BnDIRGLdlWcHRT829Qxa9XoY/+NGf+vXJpv90a8Pr3WCxSeBTwP/CzibYi7EziYLFYP5lD6M/3Gjvw3r0PJ+fHitMxrqibY/Cjxo+6u2X0+X5j+Msn4dEdFOv7a1xvBKf2P31AkWD5Z//lDSyZKWUazzFA0axKf0/MeNbsvQ8u6p0wz13nIRwXMp5lccDryl0VLFQFav+7WtNYZbPzbZDKM6weLGcle8u4EXAUj6hUZLFX07IqJK/uNGDKc6zVDflfQpSY9tSbt62tzREaleR0Q/qVOzuBm4BrhG0mts38bUGxtFh+UpPSL6RZ1gYdsflHQj8M+S3kbNVWcjImI41AkWArD9dUkvoZhz8T8bLVVERPSVOsHiFRMvbP9Q0ospFhiMITHdTPFBm0EeEc2p3CkPOH1id7xJvlZ1ckknAX9OsUrtX9m+eNL7ZwPnAA8B9wKrbN9SvvdLwOUUQ3UfBo6z/bM6FxX1TTdTfPz7P+EfNu0YqBnkMVryMNNdje2UJ2kWsAY4EdgObJS0fiIYlK60/eEy/ynApcBJkg4EPgGcaftGSU/kkcmB0UHTzRT/1Ddu5yF7r/Ss81RPbmTNGsTlcAZdu1VnW3fK+3rre5KeX+Pcy4GtE3toS1oHrAD2BAvb97TkP5RHgtBLgZts31jm++8a3xf7YLoZ4ZMDRVX+eERuZM3LopXd1+ROefOA21uOt5dpjyLpHEm3AZcAby6TnwZY0gZJ35L0xzW+L/bBdDPCZ03d9NjXM8j7xSCu6zVoBnE5nEE3bbCQ9FxJ51LulNfy827q7ZQ31d1mr8dV22tsPwV4G3BBmXwg8ALgteWfrypHYk0u4ypJ45LGd+7MQrj7Yrr1nE4/fn7WedpHuZE1L4tWdl+TO+VtB+a3HB8J3NEm/zpgZctnv2r7x7bvo5gx/qzJH7C91vaY7bG5c+fWKFJMNt1M8feuXDpSM8g7ucNfbmTNy6KV3SdP0za9J4P05H3ZKa/spP4v4CXADmAjcIbtzS15Ftu+tXz9SuBdtsckPQH4IkWt4gHgX4HLbH9uuu8bGxvz+Pj4TIsZsVcfAxQ3nn0Njp0+X0wtgwg6Q9Im22NV+erMs3iMpLXAwtb8VTvl2d4taTWwgaLZ6grbmyVdCIzbXg+slnQCxUinOyk2VsL2nZIupQgwBq5uFygi9kenO0uz+m53ZDmc7qpTs7gR+DCwiWI+BAC2NzVbtJnpdc0iTzmDa9H5n5tyLLiA7158creLE9FVnaxZ7Lb9oQ6UaWhlqORgG8S9QyK6rc7Q2X+W9CZJvyjpf0z8NF6yATIsQyU72ck7SNJZGlGtTs3irPLP81rSDBzV+eIMpmEYKjnKtaP0MURUqwwWthd1oyCDbJCaMabrWxn1GbHpLI2ZGrV+yjo1CyQdAywBDplIs/03TRVq0AzKFqjtag/DUDuK6JZRrIlX9llIehfF8h4foNiD+xLglIbLNVAGZQvUdrWHTCSLqG9Y+ilnok7N4tXAM4Hrbf+2pJ8H/qrZYg2eQWjGaFd7uOw3jh2I2lFEPxjFmnid0VC7bD8M7JZ0OPAj0rk9kNrVHgaldhTRD0axJl6nZjEuaQ7wEYqJefcC32y0VNGIqr6VQagdRfSDQemn7KQ6o6HeVL78sKR/BQ63fVOzxYomZIhoRGf08v9Sr0Zh1Vnu44VTpduu3Fa1m3q93EdERNOaWKSyk8t9tE7GO4RiB7xNQNuFBCMiorN6OR+qTjPUK1uPJc2nGD4bHTRqE3wiYuZ6OQqr1qS8SbYDx3S6IKNsmCb4JOhFNKeXq0VUBgtJH+CR7VAPAI4FbmyyUMNgJjfNYVlqY5iCXkQ/6uUorFpDZ1te7wY+ZfvrDZVnKMz0pjksE3yGJej1SmplUaWXo7DqBIu/A55avt5i+/66J5d0EvDnFDvl/ZXtiye9fzZwDsWmSvcCq2zfImkh8B1gYu78dbbPrvu9vTbTm+YgLUTYzrAEvV5IrSzq6tV8qGlncEs6SNKfAbcDHwM+DmyTdH75/rJ2J5Y0C1gDvJxiEcLTJS2ZlO1K20ttH0vRaX5py3u32T62/BmYQAEzv2kOy34KozirtVNGca2hGCztlvt4P/A4YKHtZ9teBjwdOErSh4DPVpx7ObDV9jbbDwDrgBWtGWzf03J4KEy5u+XAmelNc1iW2hiWoNcLqZVFv2vXDPUKYLFbZu3ZvkfSG4EfU9QY2plHUSuZsB04fnImSecAbwUO5tFzNxZJuh64B7jA9jUV39c39qUTahiW2sgM8X03LE2RMbzaBYuHPcX0btsPSdpp+7qKc2uKtKnOtwZYI+kM4AKKnfl+CCyw/d+Sng1cJekZk2oiSFoFrAJYsGBBRXG6Z5RvmsMQ9HphFNcaisHSLljcIuk3J29yJOl1FJ3PVbYD81uOjwTuaJN/HfAhgLIT/f7y9SZJtwFP49Ejs7C9FlgLxXIfNcrUNblpxkyM8gNGDIZ2weIc4LOSXk+xvIeB44DZwKtqnHsjsFjSImAHcBpwRmsGSYtt31oengzcWqbPBX5S1mKOAhYD22pfVcQAygNG9LNpg4XtHcDxkl4MPIOiWenztr9Y58S2d0taDWygGDp7he3Nki4Exm2vB1ZLOgF4ELiTogkK4IXAhZJ2UwyrPdv2T/btEiMiYn9Vrjo7KLLqbETEzNVddbbOTnkRETHiEiwiIqJSgkVERFRKsIiIiEoJFhERUSnBIiIiKiVYREREpQSLiIiolGARERGVEiwiIqJSgkVERFRKsIiIiEoJFhERUSnBIiIiKrXb/Cj6xFXX78gOahHRUwkWfe6q63c8am/mHXft4u2fvRkgASMiuqbRZihJJ0naImmrpPOneP9sSTdLukHStZKWTHp/gaR7Jf1Rk+XsZ+/bsGVPoJiw68GHeN+GLT0qUUSMosaChaRZwBrg5cAS4PTJwQC40vZS28cClwCXTnr/MuDzTZVxENxx164ZpUdENKHJmsVyYKvtbbYfANYBK1oz2L6n5fBQYM8er5JWAtuAzQ2Wse89ac7sGaVHRDShyWAxD7i95Xh7mfYoks6RdBtFzeLNZdqhwNuA97T7AkmrJI1LGt+5c2fHCt5PznvZ0cw+aNaj0mYfNIvzXnZ0j0oUEaOoyWChKdK8V4K9xvZTKILDBWXye4DLbN/b7gtsr7U9Znts7ty5+13gfrRy2TwuOnUp8+bMRsC8ObO56NSl6dyOiK5qcjTUdmB+y/GRwB1t8q8DPlS+Ph54taRLgDnAw5J+ZvsvGylpn1u5bF6CQ0T0VJPBYiOwWNIiYAdwGnBGawZJi23fWh6eDNwKYPuXW/K8G7h3VANFREQ/aCxY2N4taTWwAZgFXGF7s6QLgXHb64HVkk4AHgTuBM5qqjwREbHvZO/VjTCQxsbGPD4+3utiREQMFEmbbI9V5cvaUBERUSnBIiIiKiVYREREpQSLiIiolGARERGVEiwiIqJSgkVERFRKsIiIiEoJFhERUSnBIiIiKiVYREREpQSLiIiolGARERGVEiwiIqJSgkVERFRqNFhIOknSFklbJZ0/xftnS7pZ0g2SrpW0pExfXqbdIOlGSa9qspwREdFeY8FC0ixgDfByYAlw+kQwaHGl7aW2jwUuAS4t078NjJXpJwGXS2pyC9iIiGijyZrFcmCr7W22HwDWAStaM9i+p+XwUMBl+n22d5fph0ykR0REbzT5tD4PuL3leDtw/ORMks4B3gocDLy4Jf144ArgycCZLcEjIiK6rMmahaZI26uGYHuN7acAbwMuaEn/hu1nAMcBb5d0yF5fIK2SNC5pfOfOnR0sekREtGoyWGwH5rccHwnc0Sb/OmDl5ETb3wF+ChwzxXtrbY/ZHps7d+5+FjciIqbTZLDYCCyWtEjSwcBpwPrWDJIWtxyeDNxapi+a6NCW9GTgaOB7DZY1IiLaaKzPwvZuSauBDcAs4ArbmyVdCIzbXg+slnQC8CBwJ3BW+fEXAOdLehB4GHiT7R83VdaIiGhP9nAMNBobG/P4+HivixERMVAkbbI9VpUvM7gjIqJSgkVERFRKsIiIiEoJFhERUSnBIiIiKiVYREREpQSLiIiolGARERGVEiwiIqJSgkVERFRKsIiIiEoJFhERUWloFhKUtBP4fs3sRwCjuortqF77qF435Npz7e092XblhkBDEyxmQtJ4nVUWh9GoXvuoXjfk2nPtnZFmqIiIqJRgERERlUY1WKztdQF6aFSvfVSvG3Lto6qj1z6SfRYRETEzo1qziIiIGRjaYCHpJElbJG2VdP4U7z9G0qfL978haWH3S9mMGtf+Vkm3SLpJ0hclPbkX5WxC1bW35Hu1JEsampEyda5d0mvK3/1mSVd2u4xNqfFvfoGkL0u6vvx3/4pelLPTJF0h6UeSvj3N+5L0F+Xfy02SnrXPX2Z76H6AWcBtwFHAwcCNwJJJed4EfLh8fRrw6V6Xu4vX/iLgseXrN47StZf5DgO+BlwHjPW63F38vS8GrgeeUB7/XK/L3cVrXwu8sXy9BPher8vdoWt/IfAs4NvTvP8K4POAgOcA39jX7xrWmsVyYKvtbbYfANYBKyblWQF8vHz998BLJKmLZWxK5bXb/rLt+8rD64Aju1zGptT5vQP8CXAJ8LNuFq5hda79DcAa23cC2P5Rl8vYlDrXbuDw8vXjgTu6WL7G2P4a8JM2WVYAf+PCdcAcSb+4L981rMFiHnB7y/H2Mm3KPLZ3A3cDT+xK6ZpV59pb/Q7Fk8cwqLx2ScuA+bb/pZsF64I6v/enAU+T9HVJ10k6qWula1ada3838DpJ24Grgd/vTtF6bqb3g2kd2JHi9J+pagiTh33VyTOIal+XpNcBY8CvNFqi7ml77ZIOAC4DfqtbBeqiOr/3Aymaon6VojZ5jaRjbN/VcNmaVufaTwf+2vb7JT0X+Nvy2h9uvng91bH73LDWLLYD81uOj2TvaueePJIOpKiatqvODYo6146kE4D/DZxi+/4ula1pVdd+GHAM8BVJ36Now10/JJ3cdf/N/5PtB21/F9hCETwGXZ1r/x3gMwC2/xM4hGLtpGFX635Qx7AGi43AYkmLJB1M0YG9flKe9cBZ5etXA19y2SM04CqvvWyKuZwiUAxLuzVUXLvtu20fYXuh7YUU/TWn2B7vTXE7qs6/+asoBjcg6QiKZqltXS1lM+pc+w+AlwBIejpFsNjZ1VL2xnrgN8tRUc8B7rb9w3050VA2Q9neLWk1sIFipMQVtjdLuhAYt70e+ChFVXQrRY3itN6VuHNqXvv7gMcBf1f26f/A9ik9K3SH1Lz2oVTz2jcAL5V0C/AQcJ7t/+5dqTuj5rWfC3xE0lsommF+axgeDiV9iqJZ8YiyP+ZdwEEAtj9M0T/zCmArcB/w2/v8XUPw9xUREQ0b1maoiIjooASLiIiolGARERGVEiwiIqJSgkVERFQayqGzMdwkPRH4Ynn4CxTDQCfGzC8v1wfqS+UE0B/bnjPFe+cAd9n+ZPdLFtFehs7GQJP0buBe23/ag+8+sFxXbEafYZpg0QRJs2w/1Pr9dcq8L9cWwy3NUDFUJP2xpG+XP79fpj213L/hbyXdLOkzkmaX750o6YYy/SPlDGAknVLuj3CNpA9IuqpMf6+kyyX9O/AxSU8p81wvaZOk48t8J5T7J1xV7h+xpnVVY0kXS7pR0n9K+rmWc/9h+fppkr5U5vmWpthvRdJZkr5Zlv+Dkg6QdKCku8oHvpchAAAC+0lEQVRzfRNYLmm7pHdI+jrwKknPUrGHy02S/kHS48vzXSvp/0j6GrC6qd9RDKYEixgakpYDr6VYsvq5wJsk/VL59hKK5bmXUixN/nuSHgtcAfxamf5YYFWZ/kHgpRT7BfzCpK9aBrzS9pnAD4ETbS8rv/svWvIdD/whsBR4Oo8sm/144Ku2nwn8J/D6KS7nU8BlZZ7nAY9alkXSMcCrgOfZPpaiSXliFYLHA9+yvbxcBwngp7afb/vvgE8A59r+JYr1od7RcurDbb/Q9p9NUaYYYQkWMUx+GfgH2/fZ/n8UayG9oHzvu+V6/lDcLF9AcQO/1fZtZfrfUASHJcAW298vl4T41KTv+SfbE3thPAb4qIqdytaVn51wne3vlc1A61rKssv2xLLwm4CFrSeX9ATgCNv/DGD7Zy37j0w4ATgOGJd0A8XKwU8p33sA+MdJ+T9dnvuJwCG2ry3TP15e84R1REwhHdwxTNptXjW5c85t8ldtgvXTltfnUuwX8DqKNXnurfhOKG7mEx5i6v+HVZ2JolgD6R2PSiz6RHZNse7RT1s+185PK96PEZWaRQyTr1G0yc+W9DiKZp9ryvcWSTqufH06cC1wC8VqpUeV6a8DvgpsBo6WNL/sZ/iNNt/5eOCH5c35LB59M36Oir2fZwGvKb+zUrmT3Y8lvRJA0iFl01irLwCvKVePRdITJS2oce4fA7skPa9MOpPimiPaSrCIoWH7mxRNRhsplh//kO2by7c3A2+QdBNwKLC2bNr5HeCzkm4G7gc+UqavprghX0Ox/v/d03ztXwK/K+k64MnlOSb8B/B+4Gbgv9h72ex2XgucW5b3WmDupGu9GXgP8IUyz78BP1/z3GcCl5WfWwK8dwblihGVobMx9CQ9Ffj7siO47mceZ/vesmZxOXCz7Q/M4PMnAKttr5x5iSP6T2oWEVN7Y9lxfAswG/hIj8sT0VOpWURERKXULCIiolKCRUREVEqwiIiISgkWERFRKcEiIiIqJVhERESl/w+wG94CO8HJzAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(e_top, e_q)\n", + "plt.xlabel(\"Topographic error\")\n", + "plt.ylabel(\"Quantization error\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " find_bmu took: 11.261000 seconds\n", + " find_bmu took: 13.157000 seconds\n", + " find_bmu took: 12.016000 seconds\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Topographic error = 0.024276135686544215\n", + " Quantization error = 0.36751687454158743\n" + ] + } + ], + "source": [ + "# Manually select the model with better features. In this case, the #3 model has been selected because\n", + "# quantization error is distributed across 34-40u and the topographic error varies much more,\n", + "# so the model with lower topographic error has been selected. It is very important to keep the topographic\n", + "# error as low as possible to assure a correct prototyping.\n", + "selected_model = 3\n", + "sm = joblib.load(models_pool[selected_model])\n", + "\n", + "topographic_error = sm.calculate_topographic_error()\n", + "quantization_error = sm.calculate_quantization_error()\n", + "print (\"Topographic error = %s\\n Quantization error = %s\" % (topographic_error, quantization_error))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Results " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Components plane " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The components map shows the values of the variables for each prototype and allows us to extract conclusions consisting of non-linear patterns between variables. We have represented 2 types of components maps.\n", + "- The **prototypes visualization**: it shows the patterns learned by the neural network which are used to determine de winning neuron of each training instance\n", + "- The **real visualization** with exogeneous variables: it shows the real average value of the components of each lattice element. This visualization should be used with 2 purposes: (i) compare it with the prototypes visualization to assess how good is the prototypes modeling and (ii) to add other exogeneous variables (those which have not been used to build the self organizing map) in order to study their relation with the endogeneous variables.\n", + "\n", + "If the quantization error is not very high and a proper visual assessment has been done assuring that the prototupes and real visualizations look very alike, the prototypes visualization can be used as a final product, since it is much visual appealing." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Prototypes component plane" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=8.4 to DejaVu Sans 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sompy.visualization.mapview import View2D\n", + "view2D = View2D(10,10,\"\", text_size=7)\n", + "view2D.show(sm, col_sz=5, which_dim=\"all\", denormalize=True)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Real values component plane" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=12.0 to DejaVu Sans ('C:\\\\Users\\\\Ivan Valles Perez\\\\AppData\\\\Local\\\\Continuum\\\\anaconda3\\\\lib\\\\site-packages\\\\matplotlib\\\\mpl-data\\\\fonts\\\\ttf\\\\DejaVuSans.ttf') with score of 0.050000\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Addition of some exogeneous variables to the map\n", + "exogeneous_vars = [c for c in df.columns if not c in clustering_vars+[\"Cancelled\", \"bmus\"]] \n", + "df[\"bmus\"] = sm.project_data(data)\n", + "df = df[clustering_vars + exogeneous_vars + [\"Cancelled\"] + [\"bmus\"]]\n", + "\n", + "empirical_codebook=df.groupby(\"bmus\").mean().values\n", + "matplotlib.rcParams.update({'font.size': 10})\n", + "plot_hex_map(empirical_codebook.reshape(sm.codebook.mapsize + [empirical_codebook.shape[-1]]), \n", + " titles=df.columns[:-1], shape=[4, 5], colormap=None)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Hits-map " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This visualization is very important because it shows how the instances are spreaded across the hexagonal lattice. The more instances lay into a cell, the more instances it is representing and hence the more we have to take it into acount" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sompy.visualization.bmuhits import BmuHitsView\n", + "#sm.codebook.lattice=\"rect\"\n", + "vhts = BmuHitsView(12,12,\"Hits Map\",text_size=7)\n", + "vhts.show(sm, anotate=True, onlyzeros=False, labelsize=7, cmap=\"autumn\", logaritmic=False)\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Clustering " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This visualization helps us to focus on the groups which share similar characteristics" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sompy.visualization.hitmap import HitMapView\n", + "sm.cluster(4)\n", + "\n", + "hits = HitMapView(12, 12,\"Clustering\",text_size=10, cmap=plt.cm.jet)\n", + "a=hits.show(sm, anotate=True, onlyzeros=False, labelsize=7, cmap=\"Pastel1\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Conclusions " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Looking at the components map and comparing each component with the cancellation component, a set of conclusions can be extracted. The main ones are summarized below\n", + "- The flight cancellations highly depend on the month. Late year flights are much more likely to suffer cancellations than early year flights\n", + "- The flight cancellations occur much more often in short flights than in longer flights\n", + "- The delays occuring on the previous flights, departures, arrivals, because of security reasons and because of the National Air Systems are not typically drivers for the flight cancellations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Apart from these ones, secondary conclusions can be extracted by comparing all the components together. A couple of examples is summarized below\n", + "- The majority of the delays occur in the afternoon\n", + "- The short time flights are the most prone to suffer delays" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
Iván Vallés Pérez - 14/10/2018
" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/sompy/examples/California Housing.ipynb b/sompy/examples/California Housing.ipynb deleted file mode 100644 index e4cadc3..0000000 --- a/sompy/examples/California Housing.ipynb +++ /dev/null @@ -1,307 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "# Self Organizing Maps example - California Housing" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this document, the SOMPY lib is going to be used in order to provide an example of usage of the Self Organising Maps algorithm. The data to be used will be the California Housing dataset, included in the SciKit Learn library and included below" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "import numpy as np\n", - "from matplotlib import pyplot as plt\n", - "from sompy.sompy import SOMFactory\n", - "from sklearn.datasets import fetch_california_housing" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data Loading" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "First of all the data is loaded into the local environment as a numpy array. " - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "downloading Cal. housing from http://www.dcc.fc.up.pt/~ltorgo/Regression/cal_housing.tgz to /home/leandro/scikit_learn_data\n", - "California housing dataset.\n", - "\n", - "The original database is available from StatLib\n", - "\n", - " http://lib.stat.cmu.edu/\n", - "\n", - "The data contains 20,640 observations on 9 variables.\n", - "\n", - "This dataset contains the average house value as target variable\n", - "and the following input variables (features): average income,\n", - "housing average age, average rooms, average bedrooms, population,\n", - "average occupation, latitude, and longitude in that order.\n", - "\n", - "References\n", - "----------\n", - "\n", - "Pace, R. Kelley and Ronald Barry, Sparse Spatial Autoregressions,\n", - "Statistics and Probability Letters, 33 (1997) 291-297.\n", - "\n", - "\n", - "FEATURES: MedInc, HouseAge, AveRooms, AveBedrms, Population, AveOccup, Latitude, Longitude, HouseValue\n" - ] - } - ], - "source": [ - "data = fetch_california_housing()\n", - "descr = data.DESCR\n", - "names = fetch_california_housing().feature_names+[\"HouseValue\"]\n", - "\n", - "data = np.column_stack([data.data, data.target])\n", - "print(descr)\n", - "print( \"FEATURES: \", \", \".join(names))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## SOM Training" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The SOM training consists in 2 phases: the rough and the finetune one. The parameters that can be configured in the training step are:\n", - "\n", - "- The size of each individual grid\n", - "- The rough and finetune iterations\n", - "- The rough and finetune initial and final radiuses\n", - "- The initialization mechanism (random/pca)\n", - "\n", - "For the current example, only the rough/finetune iterations and the initialization mechanism parameters have been chosen. The other ones have not been specified so that the algorithm will choose them authomatically. \n", - "\n", - "For quantifying the error of the approximation, 2 metrics should be computed: \n", - "\n", - "- **The quantization error**: average distance between each data vector and its BMU.\n", - "- **The topographic error**: the proportion of all data vectors for which first and second BMUs are not adjacent units.\n", - "\n", - "A rule of thumb is to generate several models with different parameters and choose the one which, having a topographic error very near to zero, has the lowest quantization error. It is important to hold the topographic error very low in order to make the components smooth and easy to understand. " - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "#msz = calculate_msz(data)\n", - "sm = SOMFactory().build(data, normalization = 'var', initialization='random', component_names=names)\n", - "sm.train(n_job=1, verbose=False, train_rough_len=2, train_finetune_len=5)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Topographic error = 0.00595930232558; Quantization error = 0.848287157651\n" - ] - } - ], - "source": [ - "topographic_error = sm.calculate_topographic_error()\n", - "quantization_error = np.mean(sm._bmu[1])\n", - "print (\"Topographic error = %s; Quantization error = %s\" % (topographic_error, quantization_error))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Visualization" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Components map" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false, - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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g9YxNJY9pm/Lbbe2ArYsF6m4lr6/pxICwvQ5D1jjO9oSsbtjvn+NClmztVcny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6DucvcVZnYqcAHQ1N0TIUROB/pQd39RB1rSWN+3gW8D5HdpCw8hu/sI2ZR/3P16M7sLeDywamLZ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\nXS5ruO58SfdJWivp0jbvoZmZmZlZV/CZUyu/1qf1j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/v1iPhn2QkBAAAAw4aVU+Qt1Hx/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\ncCSnAAAAAICBIzkFAAAAAAzc/wG86578IwPZWAAAAABJRU5ErkJggg==\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from sompy.visualization.mapview import View2D\n", - "view2D = View2D(10,10,\"rand data\",text_size=10)\n", - "view2D.show(sm, col_sz=4, which_dim=\"all\", desnormalize=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Hits map" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false, - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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8eZNvv/2WBw8eYG5uTuPGjZk4caJWGYZqE4bcP5TU9jZv3kxoaChJSUlYWVnh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\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LIBv4AXgADDI3s1Q7UmvXrkWr1VKzZk2Lbzs/P5+xY8diZ2fH/PnzAXBycqJp06aUKVOG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\nEEIIIYQQwkT/DzqFPP8uFwT4AAAAAElFTkSuQmCC\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from sompy.visualization.bmuhits import BmuHitsView\n", - "\n", - "vhts = BmuHitsView(4,4,\"Hits Map\",text_size=12)\n", - "vhts.show(sm, anotate=True, onlyzeros=False, labelsize=12, cmap=\"Greys\", logaritmic=False)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### K-Means clustering" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "image/png": 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k3kc1zc1F+ZMdPV/f8/1PfHX3vtElf/3tocWpmyZL0WecYVoZOzXasPueJza3r1m+8/Lb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\n45GLSQyaX4zjbLfZGXOIexN1mAtKgRE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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from sompy.visualization.hitmap import HitMapView\n", - "sm.cluster(4)\n", - "hits = HitMapView(20,20,\"Clustering\",text_size=12)\n", - "a=hits.show(sm)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Conclusions" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "From the visualizations above we can extract different conclusions like,\n", - "- The houses which have, on average, more bedrooms are generally on lower average income areas.\n", - "- The highest occupations occours only in cities where the population is high.\n", - "- The latitude and longitude of the samples have a strong negative correlation. It can be because California is diagonally oriented with respect to the coordinates system.\n", - "- The most demanded houses (AveOccup) are placed on the 37~38 latitude and -121.6~-121 longitude; i.e. near San-Francisco area\n", - "- Old houses are more likely to have less rooms and bedrooms on average.\n", - "- Low average income areas usually have less rooms and bedrooms than high average ones\n", - "- The house value seems to be related with the average income of the area where it sits.\n", - "\n", - "It is important to remark that there are areas on the map where the density of instances is lower than others. It is represented by the hit map and it should be taken in consideration when interpreting the components map.\n", - "\n", - "The clustering map can be used to help to find out the different behaviors represented in the components map." - ] - } - ], - "metadata": { - "anaconda-cloud": {}, - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.5.3" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/sompy/examples/california_housing_rectangular_grid.ipynb b/sompy/examples/california_housing_rectangular_grid.ipynb new file mode 100644 index 0000000..f15aeac --- /dev/null +++ b/sompy/examples/california_housing_rectangular_grid.ipynb @@ -0,0 +1,310 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "# Self Organizing Maps example - California Housing" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this document, the SOMPY lib is going to be used in order to provide an example of usage of the Self Organising Maps algorithm. The data to be used will be the California Housing dataset, included in the SciKit Learn library and included below" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "backend module://ipykernel.pylab.backend_inline version unknown\n" + ] + } + ], + "source": [ + "%matplotlib inline\n", + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "from sompy.sompy import SOMFactory\n", + "from sklearn.datasets import fetch_california_housing" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data Loading" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First of all the data is loaded into the local environment as a numpy array. " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "California housing dataset.\n", + "\n", + "The original database is available from StatLib\n", + "\n", + " http://lib.stat.cmu.edu/datasets/\n", + "\n", + "The data contains 20,640 observations on 9 variables.\n", + "\n", + "This dataset contains the average house value as target variable\n", + "and the following input variables (features): average income,\n", + "housing average age, average rooms, average bedrooms, population,\n", + "average occupation, latitude, and longitude in that order.\n", + "\n", + "References\n", + "----------\n", + "\n", + "Pace, R. Kelley and Ronald Barry, Sparse Spatial Autoregressions,\n", + "Statistics and Probability Letters, 33 (1997) 291-297.\n", + "\n", + "\n", + "FEATURES: MedInc, HouseAge, AveRooms, AveBedrms, Population, AveOccup, Latitude, Longitude, HouseValue\n" + ] + } + ], + "source": [ + "data = fetch_california_housing()\n", + "descr = data.DESCR\n", + "names = fetch_california_housing().feature_names+[\"HouseValue\"]\n", + "\n", + "data = np.column_stack([data.data, data.target])\n", + "print(descr)\n", + "print( \"FEATURES: \", \", \".join(names))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## SOM Training" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The SOM training consists in 2 phases: the rough and the finetune one. The parameters that can be configured in the training step are:\n", + "\n", + "- The size of each individual grid\n", + "- The rough and finetune iterations\n", + "- The rough and finetune initial and final radiuses\n", + "- The initialization mechanism (random/pca)\n", + "\n", + "For the current example, only the rough/finetune iterations and the initialization mechanism parameters have been chosen. The other ones have not been specified so that the algorithm will choose them authomatically. \n", + "\n", + "For quantifying the error of the approximation, 2 metrics should be computed: \n", + "\n", + "- **The quantization error**: average distance between each data vector and its BMU.\n", + "- **The topographic error**: the proportion of all data vectors for which first and second BMUs are not adjacent units.\n", + "\n", + "A rule of thumb is to generate several models with different parameters and choose the one which, having a topographic error very near to zero, has the lowest quantization error. It is important to hold the topographic error very low in order to make the components smooth and easy to understand. " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "#msz = calculate_msz(data)\n", + "sm = SOMFactory().build(data, normalization = 'var', initialization='random', component_names=names)\n", + "sm.train(n_job=1, verbose=False, train_rough_len=2, train_finetune_len=5)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Topographic error = 0.0013565891472868217; Quantization error = 0.8164994471732518\n" + ] + } + ], + "source": [ + "topographic_error = sm.calculate_topographic_error()\n", + "quantization_error = np.mean(sm._bmu[1])\n", + "print (\"Topographic error = %s; Quantization error = %s\" % (topographic_error, quantization_error))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visualization" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Components map" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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6ejoiIyOxdOlSrFmz5rrqYZi2pLW1GR0dbfc53bNnDzZt2gRFUaDVavHRRx+hsLAQXbp0QXx8PGbOnImqqioAwNNPP22fgThixAjce++9Hl3vc+fOYcKECYiMjERGRgaGDRt2XTemGN9EEUIIbzeCYRimPWCz2ZCSkoJ//vOfuP32273dHIZhGIZhGL+Cn5wyDMO4wdatW1FZWQmTyYRFixZBCGFPt88wDMMwDMM4Dw9OGYZh3GDPnj3o1q0b4uPj8dFHH2HDhg3st8YwDMMwDHMd8LRehmEYhmEYhmEYxuvwk1OGYRiGYRiGYRjG6/DglGEYhmEYhmEYhvE6OlcKh8YEISo51CFmEfT41mJT+w1pFRtREgjRNpLxcI2JjIe5YdzrLzQIeltV2eh32S43quNmK+35FKyzkPGOQVVkvMQYo4qJasmhQzcbimTyuCwerBhRUVFBf3kVI28Pw8VL1mbLxCflYMuWLS3W1R4wKEEIRljLBb2AEmQg40LiTaZY6P0qGunzhUttkZxDfOUtBxEZSsbDU+rIeFVjsCqmLae3q8YsEamsLRp6WxmCTKzR60AbFgZ9TKxjUHbedGFXSbpi6S1oQe1WWdcqi2vpBmo0ah0pspO9pHKbTaJRKi6rmlzJ5sqrQ67sAwBQQuhjvXfYJdcq8gBFpeEtatQZfQKBo1GDNhQh+kjnCtskB5KsH3Hl0lVWhye6KKnOXT0BeGKZkhMUVd7V/lmyPuZI9fVrr47lrtXtIVijNC4NTqOSQzF17c8dYpVmerBUbopQxSL1tEdnZngpGf9Z6AkyPiBI31wz2wUnzLVk/KPavmR8Q+lNqtjZi1Fk2e4SEf5/aflk/PGjE1Sxxq0JZFmtxIZV20ifVLRmurzl+3foL66h4pIV+7amNFtm0F0tX0C3F4IRhoHKz1su6AV0nbuScWs0PZjWVlSTcUvRGecXKun4NAZ6oGwzNThfdytiHqz2VwaAQc99Tca3lfRUxSL+j9Z/8Ll6l9piCaPPt1W1Hzj1e09otKGhAUOHDoXJZILFYsGECROwYMECTJs2DZ9//jmioprWdeXKlcjKylL9ftWqVfjrX/8KAPjjH/+IqVOnOtX21kAfE4vUhx51iEnuz0JHdAOyQahVfX+i2bgtSH1Otunp87Qw0HFNJN3wsDD1jWW9jr64sljpFWpopI+7xnoi3kDfiIGVvjhVLHRc06CO64yuXZhr+9I3efcPcq5P8yS33NXyIMsZfQKB04+G6CPxs87E+cFG3KUwSYRroR8AQOPCZMVG+uJIyOqWQQzQFMkNYRgk19ay8q4MFnWyZdJ9MaibolbJnSJJO0QwvT5lufGq2P7f/x9ddyvDGqVxaXDKML6HgFXylJlhGF/AfY0GBQVh586dCA8Ph9lsxpAhQzB69GgAwPPPP48JE9Q30K5w6dIlLFiwAAUFBVAUBf3798eYMWMQE6OeEcIwgQf3oQzj2wSeRvmdU8avEQAssDb7YRjGe3hCo4qiIDw8HABgNpthNpulU7OvZevWrcjNzUVsbCxiYmKQm5vbbqY+MYy7OKNP7kcZxnsEokZ5cMr4NQICVtH8h2EY7+EpjVqtVmRlZSExMRG5ubkYOHAgAODJJ59EZmYm5s2bB5NJPZ20tLQUqamp9v9TUlJQWkq/SsIwgYYz+uR+lGG8RyBqlAenjN9jg2j2wzCMd2lJo+Xl5cjOzrZ/li1bpqpDq9WisLAQJSUl2L9/Pw4fPozFixfj+++/x9dff41Lly7h2WefVf2OSnLl7FNXhgkEWtIn96MM410CTaP8zinj1wgAZlmqS4ZhvI4zGk1I6ICCggKn6ouOjkZOTlNWwscffxxA0zup999/P1544QVV+ZSUFOzatcv+f0lJCXJycpxtPsO0a7gPZRjfJhA1yk9OGb9GAAE11YFh/A1PaLS8vByVlZUAAKPRiO3bt6Nnz544e/Zs0zKEwIYNG9CnTx/Vb0eOHIlt27bh8uXLuHz5MrZt24aRI0d6dB0Zxl9xRp/cjzKM9whEjbr05LSqMVhlWVDfQKeBNlaq89drgugXdk90oG1JiuLiyPiFqO9UsREhtPWKXvHPh8PfmxPJ+GflPch4ydlYVUyppNNon/qxMxl/4MsHyXjUD+qDPthCC8EcSk+Xs0jiErcAuGIWFFj3k/wDXVqqKmbsRuvZpqePjdBGOmU+ZQNjk3mfSjLc+YpljAz9Nvop4taut5LxRsI1JlRPn29tQfQ5UWmky2sa3VeYuzWcPXsWU6dOhdVqhc1mw8SJE3HXXXdh+PDhKC8vhxACWVlZWLp0KQCgoKAAS5cuxfLlyxEbG4s//elPGDBgAADgqaeeQmys+nzZVigWIOjyNTFJLgu9C64/VskhbQ2SxIPVurMaaC1aQ+jzvVWhz9SUG68hiNazzGJGI/FFpfxSpZdlEisZjYmOU7YxisS5wybZrv2TSmSt8Vm4D71OZK8HuGIZAwBWtQaELDsrZWnTHJQNjFbmLeqB1x1kgySJbzm0kjjpZyypW7K9rZG01WXDz+jxgi8TaBr1z5Ebw/wXIQQa29kdI4ZpT3hCo5mZmThw4IAqvnPnTrJ8dnY2li9fbv9/+vTpmD59ulttYJj2CPehDOPbBKJGeXDK+DUCgXdHiWH8CdYow/gurE+G8W0CUaM8OGX8HAVWcOZNhvFdWKMM47uwPhnGtwk8jfLglPFrBACzCCzRMow/wRplGN+F9ckwvk0gapQHp4xfI4CAu6PEMP4Ea5RhfBfWJ8P4NoGo0RYHp8uWLbMboluqXEgdyDBthC3A7ihdy9UaNcPk5dYwjBrW6E8atRqpXLYM4z1Ynz/ps9Fq9HJrGEZNoGm0xcHprFmzMGvWLABAUGoqqr53TMGvr6E3WNw5dcwcRqedL03rQMbLO4WT8R87qG0Afog7RpbNCaXjfQ10ium2Zq+JzlP/r/IBZPxoaUcyrrmottcIrqD3TVgZnfUr8gf6pKytV7exoSO9/cxh9CFlIqwuANoCAwCi6bAKGxQ0gkiVHkBcrdFIxXmLDG20eisr0ZIdIkk9L8LUllEAUJcWoYrVdqSPDX09fTwGh9DnC8pKBjIrmXZG/Lf0DcJLvUJVMWsQrX+hldhrmCWWHkbJDQ+Jlca1sEYdNRoWn4qQCsdjXmolU6dOgyFxWJHub5k9jCVEHTerD6Omso10HWYrrWkLYQPREEafQ2yhZjKuk1hMaPTqbWKR2OhozXS7tYRlDABoiNOIIslEYgmnd4TMAsdXYX066jMquCNtWWIjYrIMqq7avRAoiqTPpaxhmmuLxoVBDWFp02zdFLJ1l9nrmCR9N3XNoZGsu4GO1yfT16mDOx+h6/FRAlGjLpoxMYzvYRNKsx+GYbwLa5RhfJeW9MkaZRjv4gmNTp8+HYmJiejTpw/5/fPPP4+srCxkZWWhT58+0Gq1uHTpkqdXxSl4cMr4NVfm4jf3YRjGe7BGGcZ3cUafrFGG8R6e0ui0adOwZcsW6fdPPPEECgsLUVhYiMWLF2PYsGGIjXV+Np4n4YRIjF8joMAs+DBmGF+FNcowvgvrk2F8G09pdOjQoSgqKnKq7Nq1azFp0iS3l3m98BmJ8Xv4ri7D+DasUYbxXVifDOPbtKVG6+vrsWXLFrz22mtttsxr4cEp49cIocAqeHY6w/gqrFGG8V1Ynwzj2zir0fLycmRnZ9v/vzrRlyt89NFHuPXWW702pRfgwSnj5wgA5gDLYsYw/gRrlGF8F9Ynw/g2zmo0ISEBBQUFbi9v3bp1Xp3SC7g4ONU2AmHFjo+WQy/QaaPDStX2Aw0JtPeATWJTUY8wMv6tOVkVq26k6z4bR5uSnAo7RcaHhZSrYjEaSX59F7loU/vbbavJJkoC355XryMAiAp6PUPPqx/5h5fS6b8jimjLGP3ZKjIOnVoU2hiJj4Qki7iVdhyBNdTdlOt81/dqFEVRWa1okmirpvo+SepYPH0ClG1iIUlTb3HBqSn4ssSSwUhbTAQyipXWi9ak3oY2nWtWMkojbWul1Et8/5y0kmGNOqJYgaBKx/2oNdMa0NZLrB0IZPvVppdpVL1PNFH0flIIaxhAboGjWNXnEbPkVN8oc+MIlqyPRd1GxSqzR6Lr1srcKySWNCSS7JjHKxPI+LlOtapYRy1tl9e2sD4dEACo86xw4VpFZpviisWM5LpYNrlTSNons6QhkbXPIhE61f/L1l2RtFyyniSSdRR6+rrFFEUvs6w+0vll+gRtp9Gqqip8/vnnWLNmTZssTwY/OWX8GgHAxkmnGcZnYY0yjO/C+mQY38ZTGp00aRJ27dqFiooKpKSkYMGCBTCbm+7gzZ49GwDw4YcfYsSIEQgLox8OthU8OGX8GgEFjYKnJDGMr8IaZRjfhfXJML6NpzS6du3aFstMmzYN06ZNc3tZ7sKDU8bvsbU43UEyb4xhmDbBXY02NDRg6NChMJlMsFgsmDBhAhYsWIApU6agoKAAer0et9xyC9544w3o9XrV77VaLfr27QsA6Ny5MzZt2nS9q8Iw7Y6W9QlwP8ow3iPQNMqDU8avaTInbkm0Lb+3lZ6ejoiICGi1Wuh0OtVL5UIIPPzww8jPz0doaChWrlyJfv36XX/DGSZA8IRGg4KCsHPnToSHh8NsNmPIkCEYPXo0pkyZYn83ZvLkyVi+fDkefPBB1e9DQkJQWFh4nWvAMO0X5/QJONOPMgzjeQJRozw4ZfyaJnPilqY7OCfYzz77DPHx8eR3mzdvxokTJ3DixAns27cPDz74IPbt2+diaxkm8PCERhVFQXh4U/IYs9kMs9kMRVFw55132svccsstKCkpcbe5DBNQOKdPoD1d+DKMPxGIGuW34Bm/RgjAKjTNfjzBxo0bcd9990FRFAwaNAiVlZU4e/asR+pmmPaMMxq94s925bNs2TJVPVarFVlZWUhMTERubi4GDhxo/85sNuPtt9/GqFGjyDY0NDQgOzsbgwYNwoYNG1ptXRnG33BGn5zNl2G8RyBq1DUrGZNA1GlHu4Gw09VkWaVKnTZd0xhHlrUG0VYtio3e2A0Nap+KUybaLqO6gfYwORGVSMa/CT+niv088juy7E0GtTUMAJgk6a53GVNVsd0VXcmyNefoFPOh5+htEvWDepkRp2rIsppStV0OANgq6X2piVan3dZ0iCDL6hroOe+GKpkVgbuCUmCTJldvwhljYkVRMGLECCiKgt/+9req70tLS5Ga+tP+S0lJQWlpKZKS1HYsXkWngybR0crA1JU+1i/1UMu/rpPknQXJbtLREoChUh0LPU/XHXqO9m9QLtLWRjYi3b02nNaLsNJ3Em1GiT2Kj6CLo8+VFkk6fo1FvW1lNj8yyxHprUqduxNsWtaoM/5sWq0WhYWFqKysxNixY3H48GH06dMHADBnzhwMHToUt912G/nbH3/8EcnJyfjhhx8wfPhw9O3bF926dbu+1XETxSagu8YiRttAH6daExEXEo1Kjg3ZcaBtUO9XxUbva43kPG2to+vWq7t/NJjpO/+NEhsYi0nypIAor62n26dtkOhF7XQHANARpwVF4q5hk1gpnT0bQ8afih2hii1L+YqupE1pWZ/O8ve//x3Lly+Hoijo27cv3nrrLQQHS3zk2gMye5TWrIew9gMARTY4oeqW2b1YaDsxWT9K2SkpsnWRxWX9i404z8nsfCTnRJll1MkS9TXRjjR6u/48xBeeRnpOo/4CT+tl/BoBoFE0fxg7c+G7e/duJCcn48KFC8jNzUXPnj0xdOjQn5ZDnPykJ2GGYew4o1FXiI6ORk5ODrZs2YI+ffpgwYIFKC8vxxtvvCH9TXJyk290165dkZOTgwMHDnhtcMowvoSn9FlaWoolS5bgyJEjCAkJwcSJE7Fu3TqfyPzJMP6Mp/tQf6B9PQdmAg4BBTbR/McZrly8JiYmYuzYsdi/f7/D9ykpKSguLrb/X1JSYv8NwzByPKHR8vJyVFY2PY43Go3Yvn07evbsieXLl2Pr1q1Yu3YtNJKnAZcvX4bJ1PSorKKiArt370avXr08t4IM48c4o09n+1GLxQKj0QiLxYL6+nruIxnGA3hSo/4CD04Zv8cKTbOflqirq0NNTY39723bttkxUMu4AAAgAElEQVSnC15hzJgxWL16NYQQ2Lt3L6KionxvSi/D+CjuavTs2bO4/fbbkZmZiQEDBiA3Nxd33XUXZs+ejfPnz2Pw4MHIysrCwoULAQAFBQWYOXMmAODo0aPIzs7GTTfdhNtvvx1/+MMfeHDKMFfRkj6d0WinTp3w+OOPo3PnzkhKSkJUVBRGjFBPZWYYxnU8oVF/IrCeEzPtDuezmMk5f/48xo4dC6Dpzu/kyZMxatQoLF26FAAwe/Zs3HnnncjPz0f37t0RGhqKt956y+22M0wg4AmNZmZm4sCBA6q4RfKOVHZ2NpYvXw4A+NnPfoZDhw65tXyGaa84q8+WcjdcvnwZGzduxOnTpxEdHY1f//rXWLNmDe65555WaTfDBAqe6EP9DR6cMn6NgLPmxHK6du2KgwcPquKzZ8+2/60oCl5//XW3lsMwgYgnNMowTOvgrD5byt2wfft2dOnSBQkJTQn5xo0bh6+++ooHpwzjJoHYh/LglPF7rAGWxYxh/A3WKMP4Lp7QZ+fOnbF3717U19cjJCQEO3bscHjSyjDM9RNofahLg1PFIhBc7piDXWb3IOrVOdl1BgNZNsxA3xHQmOlc7Vqzuryxka67vIa2ZLgQEk3GC8M6qWJfxtNZHfvE0D6XMbp6Mn68Vm13Q6W0BoDgMnrXhJfQKbMjflDn7ldO0Yb0lip6n8mwnVdbfRgiaSuZcD29L3VGPd2WUFpwkoThKoRQYJbYHwQiwmyGpaTUIabrGCspTehLK7GpsEnsKCSOLGHn1PVEfU/4SwDQnPiRjMuOU22E+thTOiQQJQGE0OcFXQ3dcNv5C+qYh2xnNCFqCyxNdBRdOIrWly2YntqjIWa3KlQqfgCaRom6JAmFhGQbOgtr9BoUwBrsuK21sn1CWSTITo4aen8rVonNAmFTo6+V6Nwkax8dtgWpjyWdkT52jY30cWcOd/5JgZZ2o5LGKcsYANDXqVdII3OSkGRrt5TQetmh7aGK3Wul+8Wnkj8h4zfoacssd/CUPgcOHIgJEyagX79+0Ol0uPnmm1WWbH6BAtquxUxoQGbrJENm4eKJzP+yuikrKUnfAMKmTVqHrB6rpA6tJC6zqaGQbG/FQtcdfJF+7SPopNre6A9x48iyf+m5kYyPCpH41LQCgdiHBtbaMu0OAQSc/xPD+BOsUYbxXTypzwULFmDBggUeqYthmCYCsQ/lwSnj5yiwBthcfIbxL1ijDOO7sD4ZxrcJPI3y4JTxawQQcFnMGMafYI0yjO/C+mQY3yYQNcqDU8avuWJOzDCMb8IaZRjfhfXJML5NIGo0sJ4TM+0SGzTNfhiG8S6sUYbxXVrSJ2uUYbyLJzQ6ffp0JCYmok+fPtIyu3btQlZWFnr37o1hw4Z5chVcgp+cMn6NEIDZxh0nw/gqrFGG8V1Ynwzj23hKo9OmTcPcuXNx3333kd9XVlZizpw52LJlCzp37owLF9TuBW2FS4NTa5AG1V1DHWLh+o5kWcP3hI1JVTVdVktvdJkVAoQ6DbRipesIuiSxqZGUt+nUqd3PxYQSJYEfE2kbGG2EmYxbG9Vzxg2StPOh58kwQsrp1Niay2qbDkt1DV2JJ7hUSYYNEtsJq4FOgS+olO1wwUoGSsCZE7uKKDhExmOSbiGi9ClBayLDCC+j08CHn1AfH9bDx8iyLiSSBwAooWpLlsZOtDVUQzx9PGostIVL0MUYVUx/XqKj2jo6HkRbYFnjI1UxUxTdPksIrQtLsMTuhQjrjLSKFMoSAZDaGQide/pijTpiNSioS3LUmSWE3j6hZ9V9IGUBAwBCZvcggdolmka6bl0dfcxo6um+TujVx6/GotYtACg2+lg3RUqOR6I4ZaUEABq6edBKXCC0RHnZdYjMjib4omQ/KOrrlt2W7mTROfV5ZPyRtO1kfFgw3R8D6nPOtbA+r0GjgQhVn8MVI7FfrRKvIletYVwpLysruY6GQsUlva6W1qIisXARFrXwhMQaRpE5r8jsa6i2SK4XZRYz+hr6BBB5Wn2dczkoniz7uGkCGT94434yPj/2JBl3B09pdOjQoSgqKpJ+/84772DcuHHo3LkzACBRMsZpC/iMxPg9VijNfhiG8S6sUYbxXVrSJ2uUYbxLW2j0+PHjuHz5MnJyctC/f3+sXr3aAy2/PnhaL+PXCCiwSO68MwzjfVijDOO7sD4ZxrdxVqPl5eXIzs62/z9r1izMmjXL6eVYLBZ888032LFjB4xGIwYPHoxBgwbhxhtvvK52uwMPThm/J9DMiRnG32CNMozvwvpkGN/GGY0mJCSgoKDgupeRkpKC+Ph4hIWFISwsDEOHDsXBgwe9Mjjlab2MXyMEYBVKsx+GYbwHa5RhfBdn9MkaZRjv0VYa/eUvf4kvv/wSFosF9fX12LdvHzIyMjywBq7DT04Zv4anJDGMb+MJjTY0NGDo0KEwmUywWCyYMGECFixYgNOnTyMvLw+XLl1Cv3798Pbbb8NgUCeZWrx4MVasWAGtVoslS5Zg5MiRbrWHYdoL3IcyjG/jKY1OmjQJu3btQkVFBVJSUrBgwQKYzU1Jo2bPno2MjAyMGjUKmZmZ0Gg0mDlzZrO2M60JD04Zv4enJDGMb+OuRoOCgrBz506Eh4fDbDZjyJAhGD16NF566SXMmzcPeXl5mD17NlasWIEHH3zQ4bdHjhzBunXr8N1336GsrAx33HEHjh8/Dq0kMyXDBBrchzKMb+MJja5du7bFMk888QSeeOIJt5flLi0OTpctW4Zly5YBAMyNdTCHOm4gmVWDIUqdwlycpf1RlBrakkFnoJsXQlgbaKxqCxgA0FjoFNOGy3Rea8WqLm+Ko60hapPp9pmi6DiV1j60gm5f6Hk6BXbQeYl9BWFroUisBYSL3h2aIHUKfMTQVhzG1AgyfiFLsq3i6PWPPe5c2wQAW4BPOXLQKCSeLwShu0+oYlpjN7KstoH2atAXXyTjljPFTrfDZcLU1k4NcbT+a1LpNxestKShM6rrDqqkLTD0dfSxaw6jj8e6JHXcQrtUQZFYY8jsK/TEaUGRZOjXG+htoq2XtUVWER2+Fk9oVFEUhIc32VGZzWaYzWYoioKdO3finXfeAQBMnToVf/7zn1WD040bNyIvLw9BQUHo0qULunfvjv3792Pw4MFutckVrtaopaEO1mu6zcZwep8YItQbWWqxJrMCcsFiRla3poHujzS1kgOSIFhi9wAbrS9dA91n2IiwzEpGZjEhQyGKu2rRo5FYZujUbm+wXqJFVBQSR8Y/iriZjJdFFElaI7leuAruQx312Witp+2zgiktSs6NDc73w00VubD9XTweIYg2WiXtlulF0j5FpxYjZS8DNGMxQy+RRk+fE4RGYhnZQC+TsmS0EPsXAOrM9LXu0ks5ZPyrG9TXUJlRpWTZJn5s5rsmAlGjLb5zOmvWLBQUFKCgoAC64LC2aBPDOI9omu7Q3Ke9c7VG9ZCMuhjGW3hIo1arFVlZWUhMTERubi66deuG6Oho6P57gZSSkoLSUvVFQGlpKVJTU+3/y8q1Jg79aAj3o4wP4YQ+23s/erU+DTrJHUOG8RYBqFGe1sv4NQI8JYlhfBlnNOpMCnytVovCwkJUVlZi7NixOHr0qKoehbjDL4inAVQ5hglEuA9lGN8mEDXKg1PG7wm06Q4M42+0pFFXUuBHR0cjJycHe/fuRWVlJSwWC3Q6HUpKSpCcnKwqn5KSguLin6aZy8oxTKDCfSjD+DaBplG2kmH8GgHAYtM0+2EYxnt4QqPl5eWorKwEABiNRmzfvh0ZGRm4/fbbsX79egDAqlWr8Mtf/lL12zFjxmDdunUwmUw4ffo0Tpw4gVtuucWj68gw/ooz+uR+lGG8RyBqlJ+cMn6NgBJwd5QYxp/whEbPnj2LqVOnwmq1wmazYeLEibjrrrvQq1cv5OXl4Y9//CNuvvlmzJgxAwCwadMmFBQUYOHChejduzcmTpyIXr16QafT4fXXX+dMvQzzX7gPZRjfJhA1yoNTxu/x1Fx8q9WK7OxsdOrUCR9//LHDdytXrsQTTzyBTp06AQDmzp2LmTNnemS5DNPecVejmZmZOHDggCretWtX7N+/XxUfM2YMxowZY///ySefxJNPPulWGximvRJo77MxjL8RaBp1aXCqCEBnckwuce3/drTqR8xKkMy/gb6LLUsPDSLdvaGSTl9tqJCkUi+lbW1EnTo1flhcDFk26FIHMt4YRaek1tWp22goq6Lbcb6cjFtrasg4hfa/1gvXokTQcYTTWSQtcery1Wl0+v+yXDp192s5b5HxESFEfn0At66JJePXIgQ8Np3hlVdeQUZGBqqrq8nvf/Ob3+C1117zyLJ8Aetl9bEX/P1ZurCxgQxbLtJWMq2KQa0vazB9DJii6SpMCRI/JR1xPrNIOgWtxAYphdb0bR3OqGJVZlpHxy4lkvFL59UWXQCgu6DeJjY9vU10DfT5SV9J72OlWnIOpd0uVHhSo+0Bxaa2BNI10MeSQlihyaxNbAa6H7XpJRYzWnVc00hbTGgaJZcKkr4bJrX1jKaOttcwVNJ1ULZuAL3+WrPEGkOCVWKnZA5Tt8UqSd5qDaK367U2QVcQ1GpKLp+Eja77rJHW/0FNKhkHvpfEr1oW61MNZalCJVGTWJtILVkkNiseQWrVRPkjycpKdCS7Fie2iSKblSKrWwZhUwNJ3YpkfTSNknFBpdrviTZBBAy19DItZ+h9X/yfrqpYUbA6doUg/FP63RUCUaOBtbZMu8QmlGY/zlBSUoJPPvmEn4YyTCvgCY0yDNM6tKRP1ijDeJdA0ygPThm/5spc/OY+V2wqrnyumG1fzSOPPILnnnsOGtkdQgDvv/8+MjMzMWHCBIfsnwzDyHFGowzDeAdn9MkaZRjvEYga5XdOGb/HKpq/x9KSTcXHH3+MxMRE9O/fH7t27SLL3H333Zg0aRKCgoKwdOlSTJ06FTt37nSn2QwTMLSkUYZhvAfrk2F8m0DTaGCtLdPuEML9KYO7d+/Gpk2bkJ6ejry8POzcuRP33HOPQ5m4uDgE/fed6QceeADffPNNq6wPw7Q3PKFRhmFaB2f0yRplGO8RiBrlwSnj9wihNPtpicWLF6OkpARFRUVYt24dhg8fjjVr1jiUOXv2p0RBmzZtQkZGhsfXg2HaK+5qlGGY1qMlfbJGGca7BJpGeVov4+cosLZSFrOnnnoK2dnZGDNmDJYsWYJNmzZBp9MhNjYWK1eubJVlMkz7o/U0yjCMu7A+Gca3CTyNumYlYwP0dddYydS6kBo7mk6Dbouic7WbEiTxaHVqZ30dnaY6qIxun+XSZTJOYSuj7TV0kvTVujBJ7nnCuqM1rThkljGNNyaT8dpU2urHGK++I1Pdk96un4/4OxnvrJMl6nbv/ogAPDqdIScnBzk5OQCAhQsX2uOLFy/G4sWLPbactkSW2l3bgbArkdlUGNUWS95CGJw/ZqwS9yp9PG2bkhittmqKD6GtVG6OppNiPRqr9uMEgHBNMN0YgpWxtJXMu2HZZPxkiLp8nULb1ARdpo+HkDJJmn6ze/YHntaov6NYgOBLjlZG+lra2khfrbZkkWEJo3VB9ZcAbYWibZTYuhG2MwBgkJwvtHVqqwaZfYUisYHRGeltQlnMKBaJNZQEJYS2U6IsqWySdbdI5GylZQcbYTEj9PQ20erobVJrpn1qzhqj6IU6AevzGmwCCmVB4ooTitROxQMWMxLNuVRetr9l7aZsdGRxV9snrZsYjMnKWumdoxCWVgCgI/avVmJ1FXxB0i9a6GUKoo0iSLJdAVySfnPV7xF4Gg2soTjT/hBN1zzNfRiG8SKsUYbxXZzQJ2uUYbyIhzQ6ffp0JCYmok+fPuT3u3btQlRUFLKyspCVleXwgKat4Wm9jF8j0HIWM74DwzDegzXKML6LM/oEWKMM4y08pdFp06Zh7ty5uO+++6RlbrvtNnz88ceuNbAV4PMN4+cEVgYzhvE/WKMM47t4xkPx2LFj9icuWVlZiIyMxMsvv9wG7WeY9o5nNDp06FDExsa2QXvdh5+cMn4PTzliGN+GNcowvosn9NmjRw8UFhYCAKxWKzp16oSxY8e6XzHDMG3Wh+7Zswc33XQTkpOT8cILL6B3795ts+Br4MEp49cIAdgCLIsZw/gTrFGG8V1aQ587duxAt27dkJaW5tF6GSYQcVaj5eXlyM7+KWnirFmzMGvWLKeX069fP5w5cwbh4eHIz8/Hr371K5w4ceK62uwuPDhl/B6eFsgwvg1rlGF8F0/rc926dZg0aZJH62SYQMYZjSYkJKCgoOC6lxEZ+ZOjyp133ok5c+agoqIC8fHx113n9cK3sxm/h7MMMoxvwxplGN/FmUygV57KXPksW7aMrKuxsRGbNm3Cr3/96zZeC4Zpv7RFRu1z585B/Lei/fv3w2azIS4uzv2KrwMXfU4FdA3XePtItog1XG0CJgy0109DPO3dVdeBbp6FsBENuUjfVQgNov3MPIHl7LlWq9sTiIQYMl6dTps/Vneht2FDstoT6p5b9pBl5X6mrYOAwlMGryY0BErvvo4xyeahrME0DYQ/IQClupaupL7ehca5hiaU9gsWevV5xCY5k9mC6PNTYiTtXTo4sUgVGxZxlCz7i1DaKxVw3s9Uxt3hp8n4qRja/7SO8D8srqc3ijGOPieGxdLtDq6W+DY7iSc0WlxcjPvuuw/nzp2DRqPBrFmz8PDDD+M3v/kNjh07BgCorKxEdHS0/b23q0lPT0dERAS0Wi10Op1bd5fdRWO2IazEUTeKSeLpSfjxiWB6vwotfV63hMh8OtVxq6S7VKwSnz5B9906oq/XSPxMZd6PMv9Tyl9QMbvmc6rR0eujsRBtkTywkD3IEDKLS2Lb2mQ+p3QVqDXR+1i48eTTWX06+1Rm8+bN6NevHzp06HDdbfIqQkAx0v2gCpnvpmykICQaoMpLRxuSfaWVxCm/UI3sIJXoSOIj6hKu+JnKkLVDtq0anV8fRebDbJMsU+JNq+iI87O+maGWEw8lPXWdO2nSJOzatQsVFRVISUnBggULYDY3ecHOnj0b69evx//93/9Bp9MhJCQE69atgyLbb60MT+tl/B5+8MIwvo27GtXpdHjxxRfRr18/1NTUoH///sjNzcW7775rL/PYY48hKipKWsdnn33mlelJDOPreLIPXbt2LU/pZRgP4wmNrl27ttnv586di7lz53pgSe7Dg1PGvxHu3TVmGKaV8YBGk5KSkJSUBACIiIhARkYGSktL0atXr6ZFCIF//etf2Llzp9vNZZiAwoN9aH19PT799FO88cYbHqmPYRgE5HUuD04Zv0fYAku0DONvtKRRV7IMFhUV4cCBAxg4cKA99uWXX6JDhw644YYbyN8oioIRI0ZAURT89re/dSmDIcO0dzzVh4aGhuLixYseqYthmJ8ItOtcHpwyfg8nVGEY36YljTr7PlttbS3Gjx+Pl19+2SGzYEtTCXfv3o3k5GRcuHABubm56NmzJ4YOHep0+xmmPcN9KMP4NoGmUR6cMn6NQOBNd2AYf8JTGjWbzRg/fjymTJmCcePG2eMWiwUffPABvvnmG+lvk5OTAQCJiYkYO3Ys9u/fz4NThgH3oQzj6wSiRjnNKePfiKbpDs19GIbxIh7QqBACM2bMQEZGBh599FGH77Zv346ePXsiJSWF/G1dXR1qamrsf2/btg19+vRxf70Ypj3ghD65H2UYLxKAGnXRSgbQ1jumZraG0FWY4tQp5hui6bGwKZreqGaJK4lCZIc21NBlhZfSILc12gj1xjImh5Nl6xPpbWLqSKfG7tLlvCr2l8TDLrSulQmw6Q7NYQnX4Pxgx2NBX0dvoJAKtZCCy2mNyqwNWhNNSAgZNxPnHHMYfUxbI8xkvFt0BRmnbGPkljGtR5wmjIwPjfiejFdb1Nuq2khbw9SlRJPxygbaFiTSIPE5O0uHSdzU6O7du/H222+jb9++yMrKAgAsWrQId955J9atW6ea0ltWVoaZM2ciPz8f58+fx9ixYwE0PWWdPHkyRo0a5V6D3EBptEBbcs3xJ7E2Qah6v9oMdJ9r09EakMUFJXWpPYqk7iD6fGF1YX9rZDY6EgsHKi6zgZD2/zL7GsJKRkN3i9C46K5h06nrFgbJOip0+xollj5ai5uWedyH/oQQUpsQFZLjyGUoGxhXr10pCxOAPrfI2k13l3ILF0qjMl1IrWRcEJLM1kU259UqsZKhyku2iZAdC7Lzk6GVxBRgGuVpvYyfowTcdAeG8S/c1+iQIUPs5uDXsnLlSlUsOTkZ+fn5AICuXbvi4MGDbi2fYdov3IcyjG8TeBrlwSnj34jAy2LGMH4Fa5RhfBfWJ8P4NgGoUR6cMv5PgE13YBi/gzXKML4L65NhfJsA0ygPTpl2QGDdUWIY/4M1yjC+C+uTYXybwNIoD04Z/8fFxBQMw7QxrFGG8V1Ynwzj2wSYRlscnC5btgzLli0DADQ21rV6gxjGJQSAAHtR/Fqu1qjFyBplfAzWqGM/ajN6uTUMcxWsT0d9WlmfjI8RgBptcXA6a9YszJo1CwAQGd4JunrHXNPGSNruoTpNnb7amEgvwxwhSxlPlw+6pE67LSurOJsS3N9JS1aF6jtKbH5i6SqC4umT8q0JP1x3s9oCWRZxV7FarcjOzkanTp3w8ccfO3xnMplw33334ZtvvkFcXBzeffddpKene2bBbnK1RoPSU1DZ1/GY11+ijwNLsDquaZTYznhqI7tCcBAZNoerbRNMUXQVITG0DUyPMLU9EgDcqKcsZmhLJm+QHVRNxhuiv1PFaq20NczuRtp2olIfSsaNCfTxE/4JGSbxxuHjS1yt0ShNHGwXLzt8r4ml7X1soep92BhN68IaTF+8yPpGbaM6piGsVADId6AkrhBeMppGiWWMxbVHAkKn7v9l9jqymXA2A23JQlnmSK1kJLYblNWdrC2Klt5+Gg0d10rj9DZ09uqH9XmVPg0daFsRaiO5qAtoaOsl6NU6FwaJPZCkClndgojLrotl9k2wyDymXNgmMlsXGVQ9EksbIatbFqe2lavWPbJ9qaGE7v7AMtA0KjvMGcZ/sCnNf5zklVdeQUZGBvndihUrEBMTg5MnT2LevHmYP3++p1rPMO0fD2mUYZhWoCV9skYZxrsEmEZ5cMr4PYpo/uMMJSUl+OSTTzBz5kzy+40bN2Lq1KkAgAkTJmDHjh1S30WGYRzxhEYZhmkdWtIna5RhvEugaZQHp4x/I1r+lJeXIzs72/658m7J1TzyyCN47rnnoJFM1SgtLUVqaioAQKfTISoqChcvXmyVVWKYdoUTGmUYxks4o0/WKMN4jwDUKA9OGT+n5akOCQkJKCgosH+uvFtyhY8//hiJiYno37+/dCnUU1LFA+8RMEz7J7CmIzGMf+GEPlmjDONFPKPR6dOnIzExEX369Gm23Ndffw2tVov169d7agVchgenjP/j5t2k3bt3Y9OmTUhPT0deXh527tyJe+65x6FMSkoKiouLAQAWiwVVVVWIjZVklmIYxpEAuuPLMH5HgD2VYRi/wwManTZtGrZs2dJsGavVivnz52PkyJFuNtg9eHDK+D9uCnbx4sUoKSlBUVER1q1bh+HDh2PNmjUOZcaMGYNVq1YBANavX4/hw4fzk1OGcRa+8GUY34UHpwzj23hAo0OHDm3xocqrr76K8ePHIzFRYq/SRrRoJXM1ik1AU++Yf15oaCsZcxgRk1jGiBA63bOmlk73rq1Xx4IqJXY0l2jrBV9H0UrWvVMSGTcmR6hiDbH04MkcR6cRvyGefofy55FqmwqfQQBKK005euqpp5CdnY0xY8ZgxowZuPfee9G9e3fExsZi3bp1rbJMdwkJbkRWzzMOse8v0CeZeov6mAm5RB93tMpbmZBgMtwYrW6jhXZBgV7rmk1FpU1t03HOWkuWjdHQlh5BisQCwAOYBL0+ERq1DVSXEFrPRTF051QqWWZDFG1J47TBTitq1B8RQsBmcrQ4kt0lFnr1sS50EssYiWuCzuj8yEIrsZLSGenjTl9L9yXaWrXPiqaB8K4BpDYLthBaR1Yibgmhz1s2g+S4ky2TroauQrK9ZdY9rgzw9Dq68vAgExmP0NNx2jDrGlif148sKaLMkkVmP0Idj4RlEkCfE5qNE3Vr6MOFtIBqqkQSpyxpJHYv0m0itZ5RlxcSCxxhlvg6ydpC2L0oBrqfk9rAUJYxzZV3hzbSaGlpKT788EPs3LkTX3/9dasvrzlcGpwyjE/iwbu6OTk5yMnJAQAsXLjQHg8ODsZ7773nuQUxTCDBT14YxndhfTKMb+OERq8k/7zC1f69zvDII4/g2WefhVbycKwt4Wm9DMMwjE9TXFyM22+/HRkZGejduzdeeeUVAMCf//xndOrUCVlZWcjKykJ+fj75+y1btqBHjx7o3r07nnnmmbZsOsMwDMO0Oi0l/2yJgoIC5OXlIT09HevXr8ecOXOwYcOGVmpt8/CTU8bv4SlJDOPbuKtRnU6HF198Ef369UNNTQ369++P3NxcAMC8efPw+OOPS39rtVrx0EMP4dNPP0VKSgoGDBiAMWPGoFevXm61iWHaC9yHMoxv0xYaPX36tP3vadOm4a677sKvfvWrVl8uBQ9OGf+GkzUwjG/jAY0mJSUhKanpffuIiAhkZGSgtFT2lqwj+/fvR/fu3dG1a1cAQF5eHjZu3MiDU4YBuA9lGF/HQxqdNGkSdu3ahYqKCqSkpGDBggUw//d93dmzZ7u/AA/Cg1PG/+GOlWF8Gw9qtKioCAcOHMDAgQOxe/duvPbaa1i9ejWys7Px4osvIiYmxqF8aWkpUlNT7f+npKRg3759nmsQw/g73IcyjG/jAY2uXbvW6bIrV650f4FuwO+cMn6PYmv+wzCMd2lJo1cSOVz5LFu2jImjASMAACAASURBVKyntrYW48ePx8svv4zIyEg8+OCDOHXqFAoLC5GUlITHHntM9RtBZINkGyiG+YmW9Mn9KMN4l0DTqGtPToVQpYPWWCSp5+vUMUMVPRa2GukLBX0dHQ++pI6FlhD+MgAsZ8+RcW+gCVEbcmhiY4iSgIiLIuONMbSpR30HdXr9hni6HeEJxM4BcHv8cTKeE+zjt1V9vHltSbTOiLsTDzrEgrW9ybL7qrqqYg0ltH1DdJjEq6WqyrUGuoAIpa1aKIIq6Xj9qUgy/i76kfFzqery6cG0JUuoJB9/Bz29TTrr1CcujUIfvJVWWudllnQyftSYrIoduJxClr1UT+/LkCDa6iNIT6fvd4kWNHolkUNzmM1mjB8/HlOmTMG4ceMAAB06dLB//8ADD+Cuu+5S/S4lJQXFxcX2/0tKSpCcrN5ebYri3H1hpVG97XU1tG2CYpbZqUgsKYiwRmIlo6+TWcbQGrjWcg4AYJLYPejodisG+vLEEqoub4qRlJWcQiSyg4Zqouw+hiQuJIkuBdVEDd2QyJAGMt4pjD63ROnVVlKAk1YyAPeh1yKzN7kW2U0uWbZTrQvPg5xtQ0sQTRSS9gktrXPpzTwNUY9NJi7JulslnkwyqxayDolNpaRuRajrltnRyGwdFa0L1jOe2JcBplF+csr4NYpo+cMwjPfwhEaFEJgxYwYyMjLw6KOP2uNnz561//3hhx+iT58+qt8OGDAAJ06cwOnTp9HY2Ih169ZhzJgxHlk3hvF3nNEn96MM4z0CUaP8zinj/3CmQYbxbdzU6O7du/H222+jb9++yMrKAgAsWrQIa9euRWFhIRRFQXp6Ot544w0AQFlZGWbOnIn8/HzodDq89tprGDlyJKxWK6ZPn47evenZBAwTkHAfyjC+TYBplAenjN/T3u4YMUx7w12NDhkyhHx39M477yTLJycnO3ie3nnnndKyDBPocB/KML5NoGmUB6eM/xNgomUYv4M1yjC+C+uTYXybANMov3PK+DcisDKYMYzfwRplGN/FCX06q9HKykpMmDABPXv2REZGBvbs2dO6bWeYQMCDGvUX+Mkp4/8E2B0lhvE7WKMM47t4SJ8PP/wwRo0ahfXr16OxsRH19bSLAsMwLhJgfajLg1PF4jg819XSqZrDLqjTLxtq6Bd6hY6OK5IM06Hl6nTX2ks1ZFkPmCBI0aWlknFzZ9rDpSFcvbmFll53axD9UNscSpc3xqvjjfH02vdLpO117or4lowDYZK4bxBoc/GbI0xjwsCQ0w6xsgjaruhQTEdVzBRDWxjZOsbSCyw7S8ddQBcXR8atwfTpKeiy+sSgr6NvG0adpvViOkxbzGzv1l8VEzfS1ktxkXQ8Ioi2gegYoj5HRUssIKotwWS8rJ5ud1G5ehuK07RuSbsMANH9y8l477gSMn6IroaENfoTikYDTcg1+1di1aAhrFoMRnoHCh3dZ9jCaD8VawihL4kNhMYosZiw0Lqj2qLYJJcbNroOykZHhqxflMhI+pRBSzjjKJJtYqVdt2CVOEzYQtQLDQ6n7ZuSw6rJeEY43XdHaOlzTvPmTD/hCX1WV1fjiy++wMqVKwEABoMBBoNkY/g0astEALRGpVYykkmJlPWKBJm2pBfGMrsSPbFMyXWn1O5FVrdN0hYKV72lKd25uL0VITk/EXUrMjsa2bpLLWaItkjOca4QaH0oT+tl/B/RwodhGO/CGmUY36UlfTqh0R9++AEJCQm4//77cfPNN2PmzJmoq6Nv4DEM4yIe0Kg/wYNTxr8JMO8nhvE7WKMM47s46aFYXl6O7Oxs+2fZsmUO1VgsFvznP//Bgw8+iAMHDiAsLAzPPPOMl1aKYdoR7HPKMH5IOxMlw7Q7WKMM47s4oc+EhAQUFMgnCqekpCAlJQUDBw4EAEyYMIEHpwzjKQKsD+Unp4xfoyCwMpgxjL/BGmUY38UZfTqj0Y4dOyI1NRXHjh0DAOzYsQO9evVq3cYzTADgKY36E/zklPF/AuyOEsP4HaxRhvFdPKTPV199FVOmTEFjYyO6du2Kt956yzMVM0ygE2B9KA9OGf+mHc61Z5h2BWuUYXwXD+ozKyur2am/DMNcBwHYh7o2OLXagBrH7Gv6S3Sq8FAqKMtSraHTQ9skFjMaM7GXDHRed01ICF23kbZwoMorXWnLmOoetEVHdWc6xbSJcsyQZammM8xDSLahhVjNoBg6vXxW1I9kvKfety1jpLSz6QzuEKJo0FvvqL4TIcVk2fiIHqpYWRRtJVOfGk7GwytSyLioVWdpVOJoO5rGJNoexRpM68hwWX1ca0sv0u2opi2mwiUp8+NSOqhi5YNoa6iLXWm9XAihRX3CoD5QNTG00HUGOkV/Yw19vjWUqOORZ8iisEncHUQ/Oj4u7hsyfggu2ESwRpvHIrFNMRLncCt9bCgSuwKtUXJej1Nr2magNSf0tF6sBtqrheq7ZZYsmgaJHYXM7sKFizQhucKRVUH1r4pNcn0is4yRySJEvZ5hIYR3DYBQncRixnCZjuvpOCDx0rkW1mfLUJYirtqjSK51SasR6joXcssT6Jy3qREGiTBcXR+qLTLrFWlj6PKCsoGRbD9FYusiZNsKxDlHYjsDRbKtJOdhWCnrHg+8QRlgGuV3Thm/J5AymDGMP8IaZRjfJdAygTKMv+EJjU6fPh2JiYno06cP+f3GjRuRmZmJrKwsZGdn49///reH18J5eHDK+D9uej81NDTglltuwU033YTevXvj6aefVpVZuXIlEhISkJWVhaysLCxfvtyTa8Aw7ZsA8mdjGL8jwDwUGcbv8IBGp02bhi1btki///nPf46DBw+isLAQb775JmbOnOmBhl8f/M4p498I97OUBQUFYefOnQgPD4fZbMaQIUMwevRoDBo0yKHcb37zG7z22mvuLYxhAg0PaJRhmFaC9ckwvo2HNDp06FAUFRVJvw8P/+lVj7q6OiiuTvP2IDw4ZfwfN+/qKopiF6XZbIbZbPaqKBmm3cFPXhjGd2F9Moxv44RGy8vLkZ2dbf9/1qxZmDVrlkuL+fDDD/H//t//w4ULF/DJJ5+42kqPwdN6Gb/HE+/KWK1WZGVlITExEbm5uXYj8at5//33kZmZiQkTJqC4mE4yxDCMGnc1WlxcjNtvvx0ZGRno3bs3XnnlFQDAE088gZ49eyIzMxNjx45FZWUl+fv09HT07dvX/i4NwzA/we+cMoxv44xGExISUFBQYP+4OjAFgLFjx+L777/Hhg0b8Kc//akV1sQ5eHDK+DcCTVnMmvlcuZt05bNs2TJVNVqtFoWFhSgpKcH+/ftx+PBhh+/vvvtuFBUV4dtvv8Udd9yBqVOntvaaMUz7wAmNtoROp8OLL76Io0ePYu/evXj99ddx5MgR5Obm4vDhw/j2229x4403YvHixdI6PvvsMxQWFrLVBcNcjTP65Gm/DOM9vKDRoUOH4tSpU6ioqPBsxU7S4rTeZcuW2S/mG821sJ6/4PC9VpIG2mBVW1IISbpn6OgxsiWczsluCVHX05BCW2Bo4yVp9CXTNutj1JY0NSn0ZqqlHWZg7URbuKQmXVLHwuk7/WdqaJua0nN0XBjVbQyW3O6M1aptPvwV5b+f5rhyN8kZoqOjkZOTgy1btjhkNIuL+8kH6IEHHsD8+fOvo7Wtw9UaLb+oTm9+g6Gc/F2nsCpV7ExcAlm2OlVi1dSYRDeKOPTqO9A6MkXTe1BfS1cdf1GtL0tpGV3YVarU2yT+RBFZNOaWXmS8rhNt32AOVZ/nGuJoq6uGBFq7eotkWxGOOZS9FAA00M44SAmmz1u9JccP0EkSd8QZjbZEUlISkpKajrWIiAhkZGSgtLQUI0aMsJcZNGgQ1q9f7+aSWgeHftRmhGg0O3wvKMsYAArRvwqphQF9dSKzWVCs6r7RGkxr1BYk6aOD6D1rpeKSPldrklhmSKxnKB1ZJI4pNpljhuRCTmY9Q2GVWTJpJY8ZKbcQC71vKhtp8Z4x0eLVK5JjAhJPuqvwhD79nWv16TaSY1dqP6JQ+pLVIdG5mbajoiymhFVSt1l2bpHEqet/mZWMxOpKhkJtE5kVD7n9moHqRyXnJ0ViOydDULZgVvcU1lYaPXnyJLp16wZFUfCf//wHjY2NDte+bUmLW33WrFn2R8R6BLVFmxjGNdzMYFZeXm6fDmg0GrF9+3b07NnToczZs2ftf2/atAkZGRmeabsHuFqjCXHOe50xTJvRgkadmd1whaKiIhw4cEA19f7NN9/E6NGjyd8oioIRI0agf//+zdbdWjj0o4qT3pMM01YEeLbeq/Vp0Eju6jGMN/GARidNmoTBgwfj2LFjSElJwYoVK7B06VIsXboUQNOra3369EFWVhYeeughvPvuu17Lv8IJkRi/x90sZmfPnsXUqVNhtVphs9kwceJE3HXXXXjqqaeQnZ2NMWPGYMmSJdi0aRN0Oh1iY2OxcuVKj7SdYQKBljTq7OyG2tpajB8/Hi+//DIiIyPt8b/97W/Q6XSYMmUK+bvdu3cjOTkZFy5cQG5uLnr27ImhQ4e6tA4M017hbL0M49t4QqNr165t9vv58+f7zKxAHpwy/o+bd3UzMzNx4MABVXzhwoX2vxcvXtzs+2wMwzSDB568mM1mjB8/HlOmTMG4cePs8VWrVuHjjz/Gjh07pHd5k5OTAQCJiYkYO3Ys9u/fz4NThrlCO38yyjB+T4BplBMiMf4NZxlkGN/GAxoVQmDGjBnIyMjAo48+ao9v2bIFzz77LDZt2oTQ0FDyt3V1daipqbH/vW3bNof3yRkmoHFCn9yPMowXCUCN8pNTxu/hKUkM49u4q9Hdu3fj7bffttvBAMCiRYvwu9/9DiaTCbm5uQCakiItXboUZWVlmDlzJvLz83H+/HmMHTsWAGCxWDB58mSMGjXKvQYxTDuC+1CG8W0CTaM8OGX8n3Z2x4hh2h1uanTIkCEQRBbIO++8kyyfnJyM/Px8AEDXrl1x8OBB9xrAMO0Z7kMZxrcJMI26PDi9No29tfwiWU6rJ6qOpG1dbJL09dZgOvOoKUYdt4RIUtob6HzvZonDDGWzYEk2kWVTCGsYAPhZwmkyPiVmryrW10BnhvvRQnhDAHgi9Fdk/Jszal8bUz1t/7Hrcg8yfk9kERkPUXw7S3N7m87gaTpKrA1SQy6rYtEd6OOuphttYWQNpo8x6kRqkmQkt4bStwQNF+m3DiJ/VGc7bc27bLZG2o5B+XchGY/unELXE6+2uzLF0/qvvIE+bxlppx+Y4tUbvC6C3q6RnarJ+IzU3WQ8XRdBL9QFWKNXIQQgbOoYBfEOrcwaRmqnoKPLC626bmswXUdjBB2nbF0A2sbIJjlVSE0SJGErkexYZiUje9pgoCUADeXGIWse7f4DUU3/wKZXb4BqLT0V/YyGPh5sgq77fEgkGQe+k8QdYX1ejSK1FXEamZ4lNjBwJcm+rA6Z3QvRfylGyQJdtcCh4lIrGRcPMuq8pZP09Fr6PKQE0f2oYlJvE9ICBnDZAke6rdwk0DTKT04Z/+aKOTHDML4Ja5RhfBfWJ8P4NgGoUR6cMn6NgsC7o8Qw/z979x4XVZ3/D/x1ZgYBuQjIRRCVFIoRRRK8tWjexvtSiGlmm7cia93arDbLrbSr7q7f1b7d1rIkt6QyL63r/Vauv8rFxELLMEO5qSCggFzmcn5/8HVyPO8PzDiDzHDez8eDx0Pfc+ZcZs57zvmc8zmftyfhHGXMfXF+Mube1Jij3Dhlnk9lScuYx+EcZcx9cX4y5t5UlqPcOGWeTQYkR59lYIzdOJyjjLkvzk/G3JsKc5Qbp8zjtdTdQV0pzZj74RxlzH3ZVWu49VeDMSagthzlxinzfO0pIxlrjzhHGXNfnJ+MuTeV5ajTjVPZZKRfMCmHU5YFQ+CbBaVkTIJh6hs6KeMNIfRqGP0F8U70cM++XWoVsVsjzpLT3hb8MxmfFphHxrtoBStD6C4o3zAgqICMHy2JUsRMZfQw9V+d6EXGH/caRsbf7PoNGXcXLRUnVllO2y2cqKfQM5guj/RDN7oORE0Heh/TNChz1OInGGLdm/4CG2V6mdXEuoQm3ExOaz72E73MViRfpMvxUL9mWn96qHuzoOxGQyj9GXaMqlHE+oWfJ6edGPodGb/bX1layFU4R38laTSQvK8pz9VB8IVTx0xRaQNBJRlo7K9TIQvmYe5Al9agSsYAgIko1SaaVlRixtJBUE7FWxmXBaVXdDX0tktV9DK9apXzIcvLANAa6WUaO9KflWRWxutB53+VICGMJnp7yn0FtfHsLSVjx0igaspRspQMVSLF0TIjohI1GgdK14iWKSiFcm35R5dypKupqMSMqAyMhvhhIMoxNcUFTRmd/dsu+gZcVmLGSWrLUb5zyjybrL5RzBjzKJyjjLkvzk/G3JsKc5Qbp8zzqSxpGfM4nKOMuS/OT8bcm8pylBunzKNJUN8oZox5Es5RxtwX5ydj7k2NOSp6SoUxjyHJzf8xxtoW5yhj7qul/OQcZaxtuSJH58yZg/DwcPTp04d8/cMPP0RiYiISExNx22234ejRoy7eCvtx45R5NtmOP8ZY2+EcZcx92ZOfnKOMtR0X5eisWbOwfft24es33XQTvvjiC3z33Xd49tlnkZmZ6fy6Xyfu1ss8ntSKg9ExxpzHOcqY++L8ZMy9uSJHhw0bhoKCAuHrt912m/XfgwcPRlFRkfMLvU5855R5PO6OxJh7czZHCwsLMWLECOj1eiQkJGDlypUAgIqKChgMBsTFxcFgMKCyki6Hk5WVhbi4OMTFxSErK8uVm8aYx+NuvYy5txudo6tXr8b48eNdO1MHtN6dU6I2kCSoF6Qx0gV8NCbBp00UJDIKynw1htLL9AtV1jMFgFsjixWxYUF0rcThHfPJuCP1TB3lJbh8YjYrrzN0qKCvPVgu0bXV9gXEkfE3/ZSfycNBbXdFxYYMcf0sBgCoFdTjCtJeVsQifJS1TwHgfAC9TxfX0vuSRSJ+WgT1TDv4NZJxcwd6X680+yin9Q4lpw2MCSLjPmeV2w4A0mViXXSCPPKla66ZBXXbLB2UNQovJCi3BQCq9fTvVmSPC2T89i4nFbExgd+T0w73ucH54oIc1el0WL58Ofr374/q6mokJyfDYDBgzZo1GDVqFBYuXIilS5di6dKlWLZsmc17KyoqsGTJEuTk5ECSJCQnJyMtLQ3BwcFOrdN102igEeSTAnHMdLRuoaSh90dNnbJGucZI748isqCEqtnbvhgAWAT7o8VXsJ1exPQmQZVC0RmbTE+vJdLfp4peD02D4Lylk6Buu69ymWYfej2MVI1HALUWevq6y/TvsKD8uy0XHkNjYmIQEBAArVYLnU6HnJwcl8z3hrO3zqmjNUSpusUAXS/UkdqnonkAQKMyz11W+1RUt9WRWUBQu5Qi+kxE8dbsESDKGeozEX3vdi+rmeVdpaysDCkpKdb/Z2ZmXlfX3H379mH16tX4z3/+4/B7XYW79TKPZ09xYsZY23E2RyMjIxEZGQkACAgIgF6vR3FxMTZv3oz9+/cDAGbOnInhw4crGqc7duyAwWBASEjTqbrBYMD27dsxffp051aKsXbClcfQffv2ITSUvljIGLs+9uRoWFiY0xeEvvvuO9x///3Ytm0bOnfu7NS8nMGNU+bRJHCXI8bcmatztKCgAEeOHMGgQYNw7tw5a6M1MjIS58+fV0xfXFyMbt26Wf8fHR2N4mJlbxDG1IiPoYy5txuVo2fOnMHkyZOxdu1a3Hzzza2/wGZw45R5Nll2uktSfX09hg0bhoaGBphMJkyZMgVLliyxmaahoQH33XcfDh8+jM6dO+Pjjz9GTEyMU8tlTBXsyFF7uyPV1NQgIyMDK1asQGBgoJ2LVy5bckF3NMbaBTuPofbkqCRJGDNmDCRJwoMPPtimo30y1m644DwXAKZPn479+/ejvLwc0dHRWLJkCYzGpm7f8+bNwwsvvIALFy7g4YcfBoA27ZrPjVPm8ZztkuTt7Y29e/fC398fRqMRqampGD9+PAYPHmydZvXq1QgODsbJkyeRnZ2Np556Ch9//LGTa86YOrSUo/Z0RzIajcjIyMCMGTMwefJkAEBERARKS0sRGRmJ0tJShIeHK94XHR1t7foLAEVFRRg+fLijm8BYu+WqLoMHDx5EVFQUzp8/D4PBgPj4eAwbNsxFa8mYermi6/26deuaff3dd9/Fu+++6/yCXIBH62Uez9kRzCRJgr9/0wAlRqMRRqNRcWdl8+bNmDlzJgBgypQp2LNnD3lHhjGm5GyOyrKMuXPnQq/XY8GCBdZ4WlqadfTdrKws3HHHHYr3jh07Fjt37kRlZSUqKyuxc+dOjB071mXbxpinc9VIoFFRUQCA8PBwpKen49ChQ6241oyph9pG1ObGKfNsMppGqWvuzw5msxlJSUkIDw+HwWDAoEGDbF6/+rk1nU6HTp064cIFeuRUxthVXJCjBw8exNq1a7F3714kJSUhKSkJW7duxcKFC7Fr1y7ExcVh165dWLhwIQAgJycH999/PwAgJCQEzz77LAYMGIABAwbgueeesw6OxJjq2ZOfduRobW0tqqurrf/euXMn+vTp08orz5gKuChHPUmrdeuV6+oVMam2gZxWKxhmWedLxzVG5WpbqOHlAfiG1JHxQV1Pk3FD8HFFrK83PXhGjM6xYfcdUWmhS10UN9LlD0zVyqHk/avoeZsFI3fXlHUk4/sq4hWx3j70Z3LDy1Sg5e4O9jwro9VqkZubi6qqKqSnpyMvL8/mwOrJz60Faeg07+FVroid8+lETlvsQ5dkOecdQMaNjcrrXl4+yiHtAaBH5woy3sW3mow39lBuzy+96cbG6bP09nQooZ9X9KIWKapGIbi0J9ofTUR6afrSpXtGd/uFjA8IoOMGP2W5qxgd/d20BWe7JKWmpgp7KuzZs0cRS0lJsemeNGfOHMyZM8e5lXAVjQR4X/N7XU8fG6njqNxIl16CJNghjXRZIslXefzS1tM12UTfn6AiC5kzGkFZB1lU7sFs/++r1CAol9MoKjEjCBMneLpawednpvdHjVG0Lsq4jj7MQxaU/zEb6YO3rHOgHAfBFV0Gz507h/T0dACAyWTCPffcg3Hjxjk/Y3dBlpIRfHCCcmLC0itUKRTRtIK4LNPrQpWNkQW/CQ6XqSLO3alYs0Q/DNS6iBpgJsE8BOUrqXmLPj8h0ffjpTw/kXTON7XUVpWCnzllnq+F7rWODK8dFBSE4cOHY/v27TaN0+joaBQWFiI6OhomkwkXL17kuy+M2Yu7wDPmvlyQnz179sTRo0ddsDKMMQWVHUO5Wy/zeM72wy8rK0NVVdNt5rq6OuzevRvx8bZ3i69+tm39+vUYOXKkx9w5ZaytqelZGcY8jdqeZ2PM06gtR/nOKfNokkx3xXJEaWkpZs6cCbPZDIvFgqlTp2LSpEl47rnnkJKSgrS0NMydOxe/+93vEBsbi5CQEGRnZ7toCxhr31yRo4yx1sH5yZh7U2OOcuOUeT4n++InJibiyJEjivgLL7xg/bePjw8+/fRT5xbEmFqp7HkZxjwK5ydj7k1lOcqNU+bxJJX1xWfM03COMua+OD8Zc29qy9EWG6erVq3CqlWrAABG0CMKMtZm5PY3hLajrs7RsguOjbbHWKvjHLXJ0UYzPYI8Y22C89M2Py2cn8zNqDBHW2ycXl12I1Cyf3RSmRjCWRIN62xx7H61TIxUbfan55EYcY6Mjwz6gYzHdyhVxIyCmhGHBMPXayV6O83EfApNnclpv7ucSMa/KOlFxv0KlF9lx/P0Z9IQSK+3VyU9BHj+hVBFbKd/X3Jao6wsxQMAQRr6B79WVpbAcVR7exDcUVfnaEo/ZXmIQI0v+b5RvsqGrJ+G/v7qLXSpgrM1dLmSCyblPhboryyLAQC3BheR8d8E5JPxMK2y/Ep1F7qs048xUWT80MWbyHh+ZZgi1mBybGh8rYbeIVNClb8t94b9P3La+A50HaiuWlF5GPcpG0PhHP01Rzt1iFCcaMiNdJklS53yd1MWnKRoiBIGzXLgZMcimDV1LAbo6hCaWnpabR09sJyllp45Vb5GK7huLirVohO0P7wuKz8TTb1jF/w0RsH3Y1LGtaJSN4LPSneZnl4jOLWyF+fnNflJceQ81dG7XNTgiqKSLKKyKa7gaDkVspaU6EdBUAJH9Lk60oYQ7f+i0jiOfJeigS8F34/kRZwrXVs67DqoLUe5Wy/zfCrr7sCYx+EcZcx9cX4y5t5UlqPcOGWeTRYXQ2eMuQHOUcbcF+cnY+5NhTnKjVPm+dSVs4x5Hs5RxtwX5ydj7k1lOcqNU+bx1DaKGWOehnOUMffF+cmYe1NbjnLjlHk2GYDKujsw5lE4RxlzX5yfjLk3FeYoN06ZR5Mgq+6KEmOehHOUMffF+cmYe1NjjrZa41TSEbP28SantfjR8cZAevUagpQx73B6zPghwafIeK8O58l4tUVZkiK/kR5a/NjlrmS8oJYuD1NW56eI1TTQ217fQJfuqD/bkYxHnlIOjd3xbCM5rWSih7WuD6FLzFyqUi7zcEA3ctryRn8yXm2kS30U1waScWCvIE5QWdK2psHedM51DvqGjF8wKvdpADiijVbEovyVJWAAIMnvDBkf4E3naBcttY/RY8mneP9Ixod2/ImM/9g5UhGrMNHbaAadL0Fa+rfodwHlZJzm3qVhHMY5+itZBhqv+W0WlUiQlPuYpoOghIHg+Cr50ccM2V/5m2zyo+dt9hGUgaBTABJRGUdDV8txuEQCVTZFVEpGVNZF20jHvS4pZ65ppL8b2UtQMkOwPdR6a+hDNCRBBQwtXY0LHWrphdpdYYbz0xb1eRAxWVB6RbIIEkOEOl8WljCh5y0RvxUAIBPzkQRlXUTlUUTlq6jfJ1HJGNH2SBrBV0HjkwAAIABJREFUZ0Ut08Gyk+JSMsp5iz4/UWUcIeq7pGKOckGOzpkzB1u2bEF4eDjy8vIUr//444+YPXs2vv32W7z88st44oknnF7m9XIwgxhzM1e6OzT3xxhrO5yjjLkve/KTc5SxtuOiHJ01axa2b98ufD0kJASvvfZamzZKr+Buvczjqa27A2Oextkcpa74Tps2DSdOnAAAVFVVISgoCLm5uYr3xsTEICAgAFqtFjqdDjk5OU6tC2PtDR9DGXNvrsjRYcOGoaCgQPh6eHg4wsPD8e9//9vpZTmLG6fM8/GBlTH35mSOzpo1C/Pnz8d9991njX388cfWfz/++OPo1KmT8P379u1DaGioU+vAWLvFx1DG3JvKcpQbp8yzybLjzyEwxm4cF+Roc1d8ZVnGJ598gr17HXhOnTHWhI+hjLk3O3O0rKwMKSkp1v9nZmYiMzOzNdes1XDjlHk+Pq4y5t5ayFFnDqoHDhxAREQE4uLiyNclScKYMWMgSRIefPBBjz1YM9Zq+BjKmHuzI0fDwsLazWMr3DhlHo+fl2HMvbWUo84cVNetW4fp06cLXz948CCioqJw/vx5GAwGxMfHY9iwYde1LMbaIz6GMube1JajrVdKxl9ZfsHiR5cTaQyih8CviaTHcK7toRweenR3umTMCP8fyLhWcBni27oYReybiz3JaU9epJ9hKr9Il1NprFaWcJEa6AGTNUZ62G2/Ynr6gJPVipi2soacVjITtXgA1If40vELyvU+5RVGTlvsQz/3dbma/u6lKrpkDl2MhyADMPNl39YW50Xv0/PD9pHxHb4JiliPDmXktGl+yn0XADSgl+mIYA1dRiOYrqaEII2yrE21hf6Z7Kihh6nvpXN+vduVVsxRk8mEDRs24PDhw8JpoqKiADQN9pCeno5Dhw65X+NUUGpA40uUgegg2Hl96d9YOYAuhWTsrIw3BNHHXBN9iBaWgaHKxmhFZVNEu4Zg3lQZGG0DPTFVvgUQl5jRGImcFpwUUiU6gGY+E5PyBV0dPa3oM/G+RL/QoYreULp41zX4GKpEfedUSRZh+RFBXFQ2hdqXRKVkRAQlXKhSLbJgvSVR2RTBTi0sSWPnejS9IJiHA/MWzsMV83Z0mdS+IyppYy8X5ej06dOxf/9+lJeXIzo6GkuWLIHR2PRjPW/ePJw9exYpKSm4dOkSNBoNVqxYgePHjyMwUFTysfXwnVPm4WTVPSjOmGdpvRzdvXs34uPjER2trKsLALW1tbBYLAgICEBtbS127tyJ5557rlXWhTHPxMdQxtyba3J03bp1zb7epUsXFBUVOb0cV+A6p8zzyXLzf4yxtuVkjk6fPh1DhgzBiRMnEB0djdWrVwMAsrOzFV16S0pKMGHCBADAuXPnkJqain79+mHgwIGYOHEixo0b5/rtY8yTtZSffBxlrG2pLEf5zinzbNwliTH35oIcFV3xXbNmjSIWFRWFrVu3AgB69uyJo0ePOrVsxto1PoYy5t5UmKPcOGUeTgZkdSUtY56Fc5Qx98X5yZh7U1+Ocrde5vmc7OpQWFiIESNGQK/XIyEhAStXrlRMs3//fnTq1AlJSUlISkrCCy+80Bpbwlj7pKLuSIx5HJV1GWTM46gsR/nOKfNsLujuoNPpsHz5cvTv3x/V1dVITk6GwWBA7969baYbOnQotmzZ4tSyGFMdFXZJYsxjcH4y5t5UmKNON04lHV0KBH7KEg6WjvS0jQH0+NV1EfSs4+KLFbGnuuwkpxWVdchtrKfjNd0VsaPno8hpL1XSQ/RLF+mP1btaeaOaGnIfAHR0FRh0Pka/Qfo+XxEzNdDb6GWkR7YMCKS30+yj3J66GrrsTKMXHe9IVwtBh4t03CFOXjGKjIxEZGQkACAgIAB6vR7FxcWKxilTiveicyA+uMCBubhPB44YXYAiZpTpMg1eEr2vM0I7u6rrFK0GCLTdz6RGQZ0VE1GCwEtw2BaUkjF3EpQIC1WWpKkPpssjmAW7ukaw2toGKiYo3yKosiAqpyKZlfMRHUdFZV1EZKLEhOwlqK8hql5BrB8AdKhRbpDXZUH5D9E8qugPXHeRPtZDcHqmwPlpS1T2xN7pHC1hQn3+FkECUL8JAGRHypWISt3Igv3R0URyhJbOL4kqryX67ROV9BF9D0biB0OUA8Lv0oFluiK/VJaj7nNWyNh1cW1Xh4KCAhw5cgSDBg1SvPbVV1+hX79+GD9+PI4dO+aqDWCsnVNXdyTGPIsd+ck5ylgbUl+Ocrde5tlktFjguKysDCkpKdb/Z2ZmIjMzUzFdTU0NMjIysGLFCkXR4f79++P06dPw9/fH1q1bceeddyI/X3m3mjF2DTtylDHWRjg/GXNvKsxRbpwyz9fCFaOwsDDk5OQ0O43RaERGRgZmzJiByZMnK16/urE6YcIEPPzwwygvL0doaOj1rTNjatLOruoy1q64MD/NZjNSUlLQtWtXHqOBMVdR2TGUu/UyDycDlhb+WpqDLGPu3LnQ6/VYsGABOc3Zs2ch/9+Pw6FDh2CxWNC5c2eXbglj7ZPzOcoYay125KcDObpy5Uro9fpWXF/G1Ma1OeoJ+M4p82yygwMBEA4ePIi1a9eib9++SEpKAgC88sorOHPmDABg3rx5WL9+Pd566y3odDr4+voiOzsbkuhBecbYr1yQo4yxVuLC/CwqKsK///1vLFq0CP/zP//jknkypnoqPIZy45R5Pie7O6SmplrviorMnz8f8+fPd2o5jKmWyrokMeZR7MhPe8Zu+OMf/4i//OUvqK4WDM/PGLs+KjuGOt041XYKJOOyj3IMc4s3PWS02Ye+A2UMoL+MkeEnFDFRyRgRo0yvy7k6ZSmJ2lp6iH5RyZgOVXRvaao8jI4Ych8AfCrobe/4cwUZF5WNoVjOldPLDAsi4/4+ys9Wd5neRsHHCq8aenu8L9JXgy7TsyEWKIuHXGfMBbwkvobnFM5RW1oNLJ1sS61J9fQ+JjUQZYwEPTZEJU8sPnS8MUA5H5OyAlzTPAQlSYQlXIivW0NXZIK2kT42iErJOMIiSF2taN5UqQ9RDxnBuaKmkT6maUzEQgVd8TRGegW11fRxXrpUS6+MPUMi2JmfLY3dsGXLFoSHhyM5ORn79++3Y8FuSiMBHYgdnrpzJSjrIiTcl4j9QHSnTBQX7Esy8d1KgjIo1LQAxA8AkusiKr3kYHkdqpSMoOyMsKyLK0r3iDhaRsgZKjyG8lkX83hq6+7AmKfhHGXMfbkiPw8ePIjPP/8cW7duRX19PS5duoR7770X//znP12whoypm9qOoTwgEvNw6qr9xJjn4RxlzH25pobiq6++iqKiIhQUFCA7OxsjR47khiljLsF1ThnzLDLa3ShljLUrnKOMuS/OT8bcmwpzlBunzKPJUF93B8Y8CecoY+6rNfJz+PDhGD58uEvnyZhaqfEYyo1T5tlkGZDV9aA4Yx6Fc5Qx98X5yZh7U2GOcuOUeTxZZd0dGPM0nKOMuS/OT8bcm9pytMXG6apVq7Bq1SoAQKP3ZVT2+eWaKa79fzMuCeLH6XCIIP4Z8Yz9Z6BL2jiqrOxzhIWF2cSCXTJnx4hu4JcpK9006e/Y/MvKyhTbCfkHemLiK5YEX7toEG3R9ohKxhQUFAhesXXb2IEoL/+52WlCQ+0ZT99zXZ2jeSeAgZNckwvuitx32yF3307OUftdnaMN5gpckP9lO4G34I2iuCNEx93vlCFfFywOoPdd0XX/trgfIKiAA/sLsjUhc7TxetbITh0EcUH62JOj9uQn0L5z1CY/UYWyoH1tvEatz92PL67gCdvIOUqTZNn+IZ5SUlKarXPVHqhhGwH1bKfaqOF7VcM2AurZTrVRw/eqhm0E1LOdaqKW71QN26mGbWyvuJQMY4wxxhhjjLE2x41TxhhjjDHGGGNtTrt48eLFjrwhOTm5lVbFfahhGwH1bKfaqOF7VcM2AurZTrVRw/eqhm0E1LOdaqKW71QN26mGbWyPHHrmlDHGGGOMMcYYaw3crZcxxhhjjDHGWJvjxiljjDHGGGOMsTbHjVPGGGOMMcYYY22OG6eMMcYYY4wxxtocN04ZY4wxxhhjjLU5bpwyxhhjjDHGGGtz3DhljDHGGGOMMdbmuHHKGGOMMcYYY6zNceOUMcYYY4wxxlib48YpY4wxxhhjjLE2x41TxhhjjDHGGGNtjhunjDHGGGOMMcbaHDdOGWOMMcYYY4y1OW6cMsYYY4wxxhhrc9w4ZYwxxhhjjDHW5rhxyhhjjDHGGGOszXHjtJXs378f0dHR1/3+efPm4cUXX3ThGjHGGGPuy9/fH6dOnXLZ/CRJwsmTJ102P8aY0vjx45GVleWy+Q0fPhzvvvuuy+bHPI9qGqcxMTHw9fWFv78/IiIiMHv2bNTU1LT1agEA1qxZg9TUVJvY22+/jWeffbaN1oixtjV8+HAEBwejoaHBJfNraGjA008/je7du8PX1xdxcXH461//ClmWXTJ/xtQsJiYGu3fvdug91AloTU0NevbsCQCYNWsW/vznP7tsHRlTi+vJR2ds27YNM2fOBECfzzLmKNU0TgHgX//6F2pqavDtt9/iv//9L1566aW2XiXG2DUKCgpw4MABSJKEzz//3CXzvOuuu7Bnzx5s3boV1dXVWLt2LVatWoVHH33UJfNnjDHGGGPOU1Xj9IquXbti/PjxyMvLQ0lJCdLS0hASEoLY2Fi888471ukWL16MKVOmYNq0aQgICED//v1x9OhR6+vXdhlq7krv0qVL0atXLwQEBKB3797YuHEjAOCHH37AvHnz8NVXX8Hf3x9BQUHkvN555x3ExsYiJCQEaWlpKCkpsVmPt99+G3FxcQgODsbvf/97viPEPNYHH3yAwYMHY9asWdauQl9//TW6dOkCs9lsnW7jxo1ITEwEAFgsFmuOde7cGVOnTkVFRQUAYM+ePdi5cyc+++wz9OnTBzqdDoMHD8Y///lPvPHGG9YcrqiowOzZsxEVFYXg4GDceeed1mVt3rwZSUlJCAwMRK9evbB9+3YAyivUixcvxr333gugqZEtSRJWrVqFqKgoREZGYvny5a34yTHmPiorKzFp0iSEhYUhODgYkyZNQlFREQBg0aJFOHDgAObPnw9/f3/Mnz8fwK/H1FWrVuHDDz/EX/7yF/j7++O3v/2tzetXXHuc/Otf/4rIyEhERUXhvffes1mfhoYGPPHEE+jevTsiIiIwb9481NXVtfbHwJjbuN7zSLPZjMcffxyhoaG46aab8Prrr0OSJJhMJgC/9oIQnc9e20vi2ruru3btQnx8PDp16oT58+crzl/fe+896PV6BAcHY+zYsTh9+nSrfUbMPaiycVpYWIitW7fi1ltvxfTp0xEdHY2SkhKsX78ezzzzDPbs2WOddvPmzbjrrrtQUVGBe+65B3feeSeMRqPDy+zVqxcOHDiAixcv4vnnn8e9996L0tJS6PV6vP322xgyZAhqampQVVWleO/evXvx9NNP45NPPkFpaSl69OiBu+++22aaLVu24L///S+OHj2KTz75BDt27HD8g2HMDXzwwQeYMWMGZsyYgR07duDcuXMYPHgw/Pz8sHfvXut0H330Ee655x4AwGuvvYZNmzbhiy++QElJifXgCjQd+AYNGoRu3brZLGfQoEGIjo625vvvfvc7XL58GceOHcP58+fx2GOPAQAOHTqE++67D3/9619RVVWFL7/8EjExMXZvz759+5Cfn4+dO3di6dKlN7S7FWNtxWKxYPbs2Th9+jTOnDkDX19fayP05ZdfxtChQ/H666+jpqYGr7/+us17MzMzMWPGDPzpT39CTU0N/vWvf7W4vO3bt+Nvf/sbdu3ahfz8fEWePfXUU/jpp5+Qm5uLkydPori4GC+88ILrNpgxN+bMeeQ777yDbdu2ITc3F99++y02bdpELsOe89lrlZeXIyMjAy+99BLKy8vRq1cvHDx40Pr6pk2b8Morr2DDhg0oKyvD0KFDMX36dCc+CeYJVNU4vfPOOxEUFITU1FTcfvvtyMzMxH/+8x8sW7YMPj4+SEpKwv3334+1a9da35OcnIwpU6bAy8sLCxYsQH19Pb7++muHl33XXXchKioKGo0G06ZNQ1xcHA4dOmTXez/88EPMmTMH/fv3h7e3N1599VV89dVXKCgosE6zcOFCBAUFoXv37hgxYgRyc3MdXkfG2tp//vMfnD59GlOnTkVycjJ69eqFjz76CAAwffp0rFu3DgBQXV2NrVu3Wg9S//jHP/Dyyy8jOjoa3t7eWLx4MdavXw+TyYTy8nJERkaSy4uMjER5eTlKS0uxbds2vP322wgODoaXlxduv/12AMDq1asxZ84cGAwGaDQadO3aFfHx8XZv0/PPPw8/Pz/07dsXs2fPtm4DY+1Z586dkZGRgY4dOyIgIACLFi3CF1980WrL++STTzB79mz06dMHfn5+WLx4sfU1WZbxzjvv4O9//ztCQkIQEBCAZ555BtnZ2a22Poy5E2fOIz/55BM8+uijiI6ORnBwMBYuXOiy9dq6dSt69+5tPc/+4x//iC5dulhf/8c//oGnn34aer0eOp0OzzzzDHJzc/nuaTunqsbppk2bUFVVhdOnT+PNN99ESUmJ9UB1RY8ePVBcXGz9/9V3WzQajfUuq6M++OADJCUlISgoCEFBQcjLy0N5ebld7y0pKUGPHj2s//f390fnzp1t1vPqZO7YsaPbDPbEmCOysrIwZswYhIaGAgDuuecea9fee+65Bxs2bEBDQwM2bNiA/v37W/Pi9OnTSE9Pt+aXXq+HVqvFuXPnEBoaitLSUnJ5paWlCA0NRWFhIUJCQhAcHKyYprCwEL169brubbr6N6RHjx7X9fvBmKe5fPkyHnzwQfTo0QOBgYEYNmwYqqqqbLrmu1JJSYki164oKyvD5cuXkZycbP2NGDduHMrKylplXRhzN86cR16bW9f2QnJ2va6enyRJNv8/ffo0Hn30UWvehoSEQJZlm/Vm7Y+urVegLUVFRaGiogLV1dXWBuqZM2fQtWtX6zSFhYXWf1ssFhQVFSEqKgpAU/JevnzZ+vrZs2fJ8jGnT5/GAw88gD179mDIkCHQarVISkqy9quXJKnF9bz6KlFtbS0uXLhgs56Mebq6ujp88sknMJvN1oNkQ0MDqqqqcPToUfTr1w89evTAtm3bbLr0Ak0Hy/feew+/+c1vFPMdPXo0VqxYgcLCQpuD3qFDh1BYWIiRI0fC398fFRUVqKqqsj4nc/W8f/75Z3Kd/fz8FL8B1yosLLTeaT1z5oz194Ox9mz58uU4ceIEvvnmG3Tp0gW5ubm49dZb7T7uUa83d8yNjIy0OV6fOXPG+u/Q0FD4+vri2LFjfNxkquTMeWRkZKT1eXHA9rz4WlTeNnecvDZvZVm2+X+3bt2waNEizJgxo8X1ZO2Hqu6cXqtbt2647bbb8PTTT6O+vh7fffcdVq9ebZMEhw8fxoYNG2AymbBixQp4e3tj8ODBAICkpCR89NFHMJvN2L59u7DLUm1tLSRJQlhYGADg/fffR15envX1iIgIFBUVobGxkXz/Pffcg/fffx+5ubloaGjAM888g0GDBjn03Btj7m7Tpk3QarU4fvw4cnNzkZubix9++AFDhw7FBx98AKApF1577TV8+eWXuOuuu6zvnTdvHhYtWmQ9+JaVlWHz5s0Amhqno0aNQkZGBo4dOwaz2Yyvv/4aM2bMwEMPPYS4uDhERkZi/PjxePjhh1FZWQmj0Ygvv/wSADB37ly8//772LNnDywWC4qLi/Hjjz8CaPoNyM7OhtFoRE5ODtavX6/YrhdffNH6LOv777+PadOmternyFhbMBqNqK+vt/5VVlbC19cXQUFBqKiowJIlS2ymj4iIaLamKfV6c8fcqVOnYs2aNTh+/DguX75sszyNRoMHHngAjz32GM6fPw8AKC4u5rEZWLt1bT5OnTr1us8jp06dipUrV6K4uBhVVVVYtmyZcFrqfDYpKQkbNmzA5cuXcfLkSaxevdr62sSJE3Hs2DHrefZrr71m03idN28eXn31VRw7dgwAcPHiRXz66afX8YkwT6LqxikArFu3DgUFBYiKikJ6ejqWLFkCg8Fgff2OO+7Axx9/jODgYKxduxYbNmyAl5cXAGDlypX417/+haCgIHz44Yc2o3terXfv3nj88ccxZMgQRERE4Pvvv7e5wzNy5EgkJCSgS5cu1u6MVxs1ahRefPFFZGRkIDIyEj///DM/K8PanaysLMyePRvdu3dHly5drH/z58/Hhx9+CJPJhOnTp2P//v0YOXKkTa48+uijSEtLw5gxYxAQEIDBgwfjm2++sb7+2WefYcSIERg3bhz8/f1x7733Yu7cufjf//1f6zRr166Fl5cX4uPjER4ejhUrVgAABg4ciPfffx+PPfYYOnXqhNtvv93aCH7xxRfx888/Izg4GM8//7zN3dwrbr/9dsTGxmLUqFF44oknMGbMmNb6CBlrMxMmTICvr6/1r6qqCnV1dQgNDcXgwYMxbtw4m+kfffRRrF+/HsHBwXjkkUcU85s7dy6OHz+OoKAg67G1uWPu+PHj8cc//hEjR45EbGwsRo4caTO/ZcuWITY2FoMHD0ZgYCBGjx6NEydOtMInwVjbuzYfDxw4cN3nkQ888ADGjBmDxMRE3HrrrZgwYQJ0Oh20Wq1iWup89rHHHkOHDh0QERGBmTNn2twACg0NxaeffoqFCxeic+fOyM/Ptzk/Tk9Px1NPPYW7774bgYGB6NOnD7Zt2+bkp8PcnSRzzRGhxYsX4+TJk/jnP//Z1qvCGPMwBQUFuOmmm2A0GqHTqfoJCsYYY+3Etm3bMG/ePB6UiLUa1d85ZYwxxhhjjCnV1dVh69atMJlMKC4uxpIlS5Cent7Wq8XaMW6cMsYYY4wxxhRkWcbzzz+P4OBg3HrrrdDr9VwjmLUq7tbLGGOMMcYYY6zN8Z1Txhhjbq2wsBAjRoyAXq9HQkICVq5cCQB48sknER8fj8TERKSnp6Oqqop8f0xMDPr27YukpCSkpKTcyFVnjDHGmAP4ziljjDG3VlpaitLSUvTv3x/V1dVITk7Gpk2bUFRUhJEjR0Kn0+Gpp54CALLMQUxMDHJycsjR0BljjDHmPhwaQjI0RIuYbl6ttS431CULXQD8gslfERO13rt3uEjGdSq4IZ2fp/ycAEC2WFwy/w6dNSgvL29xurEj/HChwtzsNKGRw7F9+3aXrJe766Dxga824PpnwJeqWo9OOex+aFw1OWmwpvl92hn5xwPJuGwWLFNw/fJG5mhkZCQiIyMBAAEBAdDr9SguLrYpyzN48GCyzqy76aD1ha/W9jswBXYgp+0YflkRi9DR+4xGkLwy6GMd9Y2YZOU+2jQtfUwT/VxYZOX05Y30MUNTSi8TNcptdxU5sCMZb+ys3KKwjjXktFrQxzqdRMddkdOiz/uyIEfLSgJazFF78hNQz3E0OESDrtHKU+PTDSGKmFQqOIWubr19tzVJvj5k3NKN3qe7e1coYr6Sa85/z5uVv4nnLnUip9XVCWbiwPmMJEgBi+ArttA/2ZC9lAvV6MTnxX5VjZyjBIcapzHdvHBoR/fWWpcbak8dfUD84PxvFLFGwd75Zo8tZDxYQx/42pMJNys/JwAw19AHckdVxvxi13TlFWZ8syO62WkGT2r5BLq98NUG4LagjOt+vywLfkQtgl/5tuh4IREn2+7UAYRaPwBS52BFbNbGfeS0d/nTF75cYWLSaDJurqC7xEKwT1TEnLRrea7O0YKCAhw5cgSDBg2yib/33nuYNm0a+R5JkjBmzBhIkoQHH3wQmZmZdi/P1Xy1gbity3SbWJmBPq6mPHxEEXssfA85rbdE54BR0DitJo5rF8x+5LRVFvqYZpTpY+Nl4sxtdQF9zOj4Kn3CqfniWzLuEMGJsnFIfzJ+5j7lCeADSf8hp+2kpc+Iw3SXyHiGH31RwREWQYP4SKOJjD80ueWeAvbkJ9ByjtbX12PYsGFoaGiAyWTClClTsGTJEuzZswdPPvkkLBYL/P39sWbNGsTGxire/+qrr2L16tXQarV47bXXMHbs2BbXqTV0jdbhs38rP7cHf1LWsNa8Qn++2n2HXb5eN4Lmlt5kvOFvtWR8ZdzHiljfDr4uWZf/rVL+Jq7YNZ6ctvNRwTFX1CYkfio7VNMT13Wm2wq1gpRpiDYqYn4h4osVvi/S7YiruSpHPQkX32MeToZZ1KBijLmBlnO0rKzM5lnQzMxMsgFZU1ODjIwMrFixAoGBv959fPnll6HT6WyKu1/t4MGDiIqKwvnz52EwGBAfH49hw4Zd5/Yw1p645hjq7e2NvXv3wt/fH0ajEampqRg/fjweeughbN68GXq9Hm+++SZeeuklrFmzxua9x48fR3Z2No4dO4aSkhKMHj0aP/30E7RawV11xlRFfee53DhlHk0GYOG+qIy5LXtyNCwsDDk5Oc1OYzQakZGRgRkzZmDy5MnWeFZWFrZs2YI9e/ZAEty1joqKAgCEh4cjPT0dhw4d4sYpY3DdMVSSJPj7N3XdNhqNMBqNkCQJkiTh0qWmu8kXL1605uLVNm/ejLvvvhve3t646aabEBsbi0OHDmHIkCFOrxdjnk6N57ncOGUeTYYMo9x6z+cxxpzjihyVZRlz586FXq/HggULrPHt27dj2bJl+OKLL9CxI931tLa2FhaLBQEBAaitrcXOnTvx3HPPObU+jLUXrjyGms1mJCcn4+TJk/j973+PQYMG4d1338WECRPg6+uLwMBAfP3114r3FRcXY/Dgwdb/R0dHo7i42CXrxJinU+N5bvsfuYe1exbIzf4xxtqWszl68OBBrF27Fnv37kVSUhKSkpKwdetWzJ8/H9XV1TAYDEhKSsK8efMAACUlJZgwYQIA4Ny5c0hNTUW/fv1sp9m8AAAgAElEQVQwcOBATJw4EePGjWvV7WXMk7SUnxbI1q73V/5WrVqlmI9Wq0Vubi6Kiopw6NAh5OXl4e9//zu2bt2KoqIizJ492+bi0hVU0QhRLwjG1MieHG1P+M4p82gyAHM7S0rG2hNX5Ghqaip5AnulAXqtqKgobN26FQDQs2dPHD161KnlM9Ze2Zuf9nS9vyIoKAjDhw/Htm3bcPToUevgZdOmTSMvDEVHR6OwsND6/6KiIrL7L2NqpMbzXL5zyjyaDMAoW5r9Y4y1Hc5RxtyXPflpT46WlZWhqqppxO+6ujrs3r0ber0eFy9exE8//QQA2LVrF/R6veK9aWlpyM7ORkNDA3755Rfk5+dj4MCBLt1OxjyVq3LUk7T7O6fFZnr49v3V9IP2uee6KmLVlfSzTHPMd5Lxv8VsIOO9dHSdt9ZyyUIPde8t0V/757X0sOjLX5yuiHWq+er6V8zF2ldKtgKNoHsU0W1KkulpZQtdqgCiuraaG3zdS9QFrC1KzIiWWa0ss7TymbvJSe967R9Or0af1x4i493rvifjkmhkTME+4QjO0auYzZAv2pYb8amkP6ELDfYfM0SfcT1Rc7QprjwOGEHvA1TdUgAwC/YNquZq35BSctovh0eQ8R41feh5l15QBgX533BzJBn/5S56+tcHZytiEzvWk9O2hZ+M9DH9/fIRgnf8aNd8XZGfpaWlmDlzJsxmMywWC6ZOnYpJkybhnXfeQUZGBjQaDYKDg/Hee+8BAD7//HPk5OTghRdeQEJCAqZOnYrevXtDp9PhjTfeaLORer0lDXp5Kc/5egefVcSOBnch5+Gn8yLjsklZZsSdaIrOkfHS/3cLGX83WDmo3Jgg+vgSpKHLqXx1OY6Mv/nlKEWs6xf0sdX/NF3CUHNRUMKllogLfkM0A+gyX5e70PuntqPyO06MKKHXA0C+8BVbajuG8p1T5tFkyDC38NeSwsJCjBgxAnq9HgkJCVi5ciUAYPHixejatavNM25XvPrqq4iNjcUtt9yCHTt2WOPbt2/HLbfcgtjYWCxdutT1G8yYh3FFjjLGWoc9+WlPjiYmJuLIkSP47rvvkJeXZx10LD09Hd9//z2OHj2K/fv3o2fPngCa7pa+8MIL1vcvWrQIP//8M06cOIHx4+l6loypkaty1JO0+zunrH2TZcDoZE7qdDosX74c/fv3R3V1NZKTk2EwGAAAjz32GJ544gmb6UU12QDg97//PXbt2oXo6GgMGDAAaWlp6N2bLmzNmBq4IkcZY62D85Mx96bGHOXGKfNwEsxwrtthZGQkIiObun8FBARAr9c3O4y9qCYbAMTGxlqvDN99993YvHkzN06Zyjmfo4yx1sL5yZh7U1+Ocrde5tFkABa5+T9HFBQU4MiRI9bRBV9//XUkJiZizpw5qKysBNBUk61bt27W91ypySaKM6Zmrs5Rxpjr2JOfnKOMtR015ig3TplHkwE0QtPsnz312QCgpqYGGRkZWLFiBQIDA/HQQw/h559/Rm5uLiIjI/H44483LVNQk41rtTGmZE+OMsbahj35yTnKWNtRY4622K131apV1pP5sgvmVl8hxhxlaWE0UXvqsxmNRmRkZGDGjBmYPHkyACAi4tdRJB944AFMmjQJQPM12dqiVtvVOdpocZ+RJRm7oqUcbe9sclTmHGXuhfPz1/ws5/Nc5obUlqMtNk4zMzORmZkJAEjp59PqK3S9RCVj1l1MIuNfnI8l49WFgYpYx2L6ikT+iV5kfEzU42Tcp6tyuOuenYlh8QH09KfjYR3o7QzRKed92eJNTrv+zK1kXP6YLiUTuvsXRUxQWMRh2oAAp97fVJzYuaSVZRlz586FXq/HggULrPHS0lLrs6gbN25Enz5NpQ3S0tJwzz33YMGCBSgpKbHWZJNlGfn5+fjll1/QtWtXZGdn46OPPnJq3exxdY528gpXlo4R3b2lhuo3Cb5ZR0uyiErMUFqz7Exr3rl28DORGxoVsU7/7zQ57ZAn55HxC7+lh8YP3OuniPXYosxbALCIvmNRySFBeRF7uSJHPZ1NjmpDIZttT4AlB/pkeUmO7XdUyRgAqCWOD0bBtCJawbr4aJQlT4Z2OkFO65umzAsA2No7gYybi2OUQcFHEnhzJRn/IOFjMj7UfU9xAAAbL9HH7h37+pPxYDtKyXB+Ks9zNcRdqECd8qKSxat9fW6mC/R5503rK8j4/soURexfcYLzS2/6nMC3kC670/1b5XGq4y8XyWmlc/R6m8rKybgj/E51IuOVsSFkPDy0ShH7e7ctwvlPQss3MNSYozwgEvNoMiQYZedOng8ePIi1a9eib9++SEpqupjxyiuvYN26dcjNzYUkSYiJicE//tFUe7K5mmyvv/46xo4dC7PZjDlz5iAhgT7BYkwtXJGjjLHWwfnJmHtTY45y45R5NFdcUUpNTSWfF50wYYLwPYsWLcKiRYvI9zT3PsbURo1XfRnzFJyfjLk3NeYoN06Zh5NgltvXg+CMtS+co4y5L85Pxtyb+nJUXVvL2h0ZgBHaZv8YY22Hc5Qx92VPfnKOMtZ2bkSOfvrpp0hISIBGo7EZQPTChQsYMWIE/P39MX/+fJv3rFu3Dn379kViYiLGjRuH8nLlM7779+9Hp06dkJSUhKSkJLzwwgt2rQ/fOWUeTZbVd0WJMU/COcqY++L8ZMy93Ygc7dOnDzZs2IAHH3zQJu7j44MXX3wReXl5yMvLs8ZNJhMeffRRHD9+HKGhofjTn/6E119/HYsXL1bMe+jQodiyRTwoFIV/kZjHs0Bq9o8x1raczdHCwkKMGDECer0eCQkJWLlyJQCgoqICBoMBcXFxMBgMqKykR2fNyspCXFwc4uLikJWV5dJtY8zTtZSffBxlrG21do7q9Xrccsstirifnx9SU1Ph42M7lLksy5BlGbW1tZBlGZcuXXJp6USPvHNqlJVDTO+9fBM57TdVdLz0Aj08tHeFsr3uW0avh1cdPX59x3P0TmI8qSxTcypQGQOAHzrHkHEpgq6R1zlIWUrGZKGvPVw8Tg+B3aOIHtIfZmXdL42vL71+3nT5GikkiIxbAjrSy8R3grgtGRIaHSx/0O5dW5pFVKqlNcusOEJUdka03o6WtaE4su2uKqNDzEe+RJeGCv73D2Q8ZDvddUduVOausGSMqGyJqJSMA2VOKK7IUZ1Oh+XLl6N///6orq5GcnIyDAYD1qxZg1GjRmHhwoVYunQpli5dimXLltm8t6KiAkuWLEFOTg4kSUJycjLS0tIQHBzs1Do5sTHQhIfZhC51pz+f4QFnFTEfwb5bK/ia6i30vB3pBuajMZJxs6D2np+mQRHrrqPLUSR2LibjdwR/S8ZP9QtXxET716iOdPmaOC9/Mu7u1p4YSMa77aZzXXlWoMTHUFtGWHDWrPzkvi6LUcR8y+m8kE103FPJJ06R8a7Eb1FNAX1O2xhA72M+VfS+61tcq4hJFZfIaV1RMkZEuqz8LWvOpMg8RSxc69zvjTvmqJeXF9566y307dsXfn5+iIuLwxtvvEFO+9VXX6Ffv36IiorC3/72N7uqWPCdU+bRZAAWaJr9Y4y1HVfkaGRkJPr3b6rlGBAQAL1ej+LiYmzevBkzZ84EAMycORObNm1SvHfHjh0wGAwICQlBcHAwDAYDtm/f7tJtZMxT2ZOffBxlrO3Ym6NlZWVISUmx/q1atcpmPqNHj0afPn0Uf5s3b3Z4nYxGI9566y0cOXIEJSUlSExMxKuvvqqYrn///jh9+jSOHj2KP/zhD7jzzjvtmr97NcUZuw6iq/eMMffgyhwtKCjAkSNHMGjQIJw7dw6RkZEAmhqw58+fV0xfXFyMbt26Wf8fHR2N4mL6bh1jasTHUMbcmz05GhYWZjOY0bV2797tsvXJzc0FAPTq1QsAMHXqVCxdulQxXeBVvUMnTJiAhx9+GOXl5QgNDW12/tw4ZR6tqThxS7uxC7qBMsauiz05WlZ2HikpKdb/Z2ZmIjMzUzFdTU0NMjIysGLFCpuDXrPLJ7pTS+7SpZ2xNmbfMbRpyubU19dj2LBhaGhogMlkwpQpU7BkyRIMHToU1dVNjy+cP38eAwcOJHs4aLVa9O3bFwDQvXt3fP755w5vC2Ptkaty1JW6du2K48ePo6ysDGFhYdi1axf0er1iurNnzyIiIgKSJOHQoUOwWCzo3Llzi/PnxinzaE3FiVvqcqR8ZpYxdmPYk6MtXfEFmroRZWRkYMaMGZg8eTIAICIiAqWlpYiMjERpaSnCw5XPI0ZHR2P//v3W/xcVFWH48OGObgZj7ZJ9x1CgpeOot7c39u7dC39/fxiNRqSmpmL8+PE4cOCAdZqMjAzccccd5Pt9fX2td2MYY79yVY42Z+PGjfjDH/6AsrIyTJw4EUlJSdixYwcAICYmBpcuXUJjYyM2bdqEnTt3onfv3nj++ecxbNgweHl5oUePHlizZg0A4O233wYAzJs3D+vXr8dbb70FnU4HX19fZGdn23VxmBunzKPJkLhLEmNuzBU5Kssy5s6dC71ejwULFljjaWlpyMrKwsKFC5GVlUWe+I4dOxbPPPOMdSTfnTt3ks/GMKZGrjqGSpIEf/+mgV+MRiOMRqPNSWh1dTX27t2L999/3+llMaYmN+I8Nz09Henp6eRrBQUFZHzevHmYN28eGb9i/vz5ivqo9uCn3JlHk2XAKOua/WOMtR1X5OjBgwexdu1a7N2711rMe+vWrVi4cCF27dqFuLg47Nq1CwsXLgQA5OTk4P777wcAhISE4Nlnn8WAAQMwYMAAPPfccwgJoUcsZ0xt7MlPo6xrcbAVADCbzUhKSkJ4eDgMBgMGDRpkfW3jxo0YNWqUsDt+fX09UlJSMHjwYLLbL2NqZW+OticeuTU765TDMn91qRc57c+VdN9mc7kPGfcjyuR5X6RLQ+jqBXEv+gqHV50y7lMhKDtTRsfry+gSLheC6e2h+BfS89bWCkpPELfgNf5+9LSd6AOPKSyAjJs7CnZBulwhgWuw2ZBgfykZV5RkEXHBvGWj/cPxS46WyxFN7wgHSsYAgExNL/qciPJNTfNwwXfmaMkYWbCddnM+R1NTU8lnRwFgz549ilhKSgreffdd6//nzJmDOXPmOLUOrmLu6IVL/bvYxC72p8t4DfT7WRHzluh9t16m9xmtJNpPlSEvSXAMENAIrm97Scp1CSLKywBApJY+BiRo6O35jbdyMCsvSXQq45klY2osdMk48wn6OOr7YyE9n5Yf7YK9+WlP13utVovc3FxUVVUhPT0deXl56NOnDwBg3bp11gtGlDNnziAqKgqnTp3CyJEj0bdvX+tgKzdSmakjVlUOUK5fnrKG481lVeQ82tuDRBaiVBkA6IqVA9CJMs7UiT5HlUz075OmVvl7YT7feiVjRMyd6S1qpKsjYlIAVQZRcL5sN/Wd5/KdU+bRZABmWdPsH2Os7XCOMua+7MlPR3M0KCgIw4cPt5ZsunDhAg4dOoSJEycK3xMV1dT469mzJ4YPH44jR45c9zYx1p60Ro66u/a1NUx1mkYx0zb715LCwkKMGDECer0eCQkJWLlyJQDgySefRHx8PBITE5Geno6qqqarpAUFBfD19bV2L7y6f/3hw4fRt29fxMbG4pFHHhHe7WFMLVyRo4yx1mFPftqTo2VlZdZjZF1dHXbv3o34+HgAwKeffopJkybBx4e+e1ZZWYmGhqY7ZeXl5Th48CB69+7toi1kzLO5Kkc9CTdOmcczQ9PsX0t0Oh2WL1+OH374AV9//TXeeOMNHD9+HAaDAXl5efjuu+9w88032wyi0qtXL+Tm5iI3N9c6MhkAPPTQQ1i1ahXy8/ORn59vvXLMmJo5m6OMsdbTUn7ak6OlpaUYMWIEEhMTMWDAABgMBkyaNAkAkJ2djenTp9tMf/Vz4T/88ANSUlLQr18/jBgxAgsXLuTGKWNXcUWOehKPfOaUsStkABYnuzNERkYiMjISABAQEAC9Xo/i4mKMGTPGOs3gwYOxfv36ZudTWlqKS5cuYciQIQCA++67D5s2bcL48eOdWj/GPJkrcpQx1jpclZ+JiYnCrrhXl3K64urnwm+77TZ8//33Tq8DY+2RGo+h3DhlHu1Kd4fmXBll8IrMzExkZmaS0xYUFODIkSM2owwCwHvvvYdp06ZZ///LL7/g1ltvRWBgIF566SUMHToUxcXFiI6Otk4THR2N4mLl4B2MqYk9OcoYaxucn4y5NzXmKDdOmccztzCKmT2jDAJATU0NMjIysGLFCpvh7l9++WXodDrMmDEDQNOd1jNnzqBz5844fPgw7rzzThw7dox8vtSeYsOMtXct5ShjrO1wfjLm3tSWo27dOD0oKNXydU2sIpZ/KYyc9mJVRzLuXUHfIveuUjYwvGrpgcE1JnqwG8lE70S6y8qYtkFQMkLQqGkIpr+yy+HKqypmb3JS+JYLhu5usL90h7AUh6gxJhoXyMkqFbIsuaS7g9FoREZGBmbMmIHJkydb41lZWdiyZQv27NljbWh6e3vD27vpw01OTkavXr3w008/ITo6GkVFRdb3FhUVWUcgZIJSKgBgFpW6sH/nkAXlNaCl48KfeWq/Fqy3LCj3IuTI4FiOloyhysM4fGFEVALHuUG9XJWj7YXZG7jUw/b32i+4hpzW4sBzRJ009JV1M+iyJF6iEjOEeovguIMOds9DxEui11tUpkYjyvV2ZF89XYfXv4gMw1J2gX7BjlIynJ+26i1eOFEToYhriVKAZj96/9f40iX/LHV1zq2cmzFVKGv+6XzpQa90Rvp4KYmOr+eUZWNkkwPnqA7SBtBlmqqj6TZEYyi9PfFezpaNUVJjjrp145SxlsiA090dZFnG3LlzodfrsWDBAmt8+/btWLZsGb744gt07PjrD1RZWRlCQkKg1Wpx6tQp5Ofno2fPnggJCUFAQAC+/vprDBo0CB988AH+8Ic/OLVujHk6V+QoY6x1cH4y5t7UmKPcOGUeTnK6vtPBgwexdu1a9O3bF0lJSQCAV155BY888ggaGhpgMBgANA2K9Pbbb+PLL7/Ec889B51OB61Wi7fffhshIU1Xut966y3MmjULdXV1GD9+PA+GxJgLcpQx1lo4Pxlzb+rLUW6cMo/WNIqZc33xU1NTyedFJ0yYQE6fkZGBjIwM8rWUlBTk5eU5tT6MtSeuyFHGWOvg/GTMvakxR7lxyjyaGkcxY8yTcI4y5r44Pxlzb2rMUW6cMo/nyKAhjLEbj3OUMffF+cmYe1NbjnLjlHk0WQbMKuvuwJgn4RxlzH1xfjLm3tSYo27ROD1jqibjJxqVJWMA4GRtuCJWXBlETiuV0/VUfAQjr3vVKJ89lLX0TmHyouOSoPKCtkY59LTuUgM9D5Og3ItRUB9GUg7fbfKl18/7Ej1v0TLh5aWMicqCCOIawTDispdzV4NkSDBZ1NXdoVmyDDReM9y6oJwKycmyIc0SlVIRlIwRlWqhSptIWnofcKhkDEDvv46UgHF0+lb8vCXRNgpQz10DgOTkQZFz1FaHajOivrhoEztr6kRO+0HYbYpYz26fk9P21NGfcYRgPwiQGhWxesE+cBF0Llos9LypmnyNgiv/Rpmet7dEHHdU4sjlHmS84znB93CZqFNnJ85PWz07VOPDmP2K+DMTKhSxf5//DTmPrpe6kXFt8XkybqlWngM7XKqsLRDHbrmaLoslLBlzmS6vY66quv71ug5yXHcyXtdZcG7hT5foag1qzFG3aJwy5gy1FSdmzNNwjjLmvjg/GXNvastRdXViZu3OlVHMmvtjjLUdV+TonDlzEB4ejj59+lhj06ZNQ1JSEpKSkhATE2MtA3WtmJgYa5molJQUV20WY+2CPfnJx1HG2s6NyNFPP/0UCQkJ0Gg0yMnJscYvXLiAESNGwN/fH/Pnz7d5z8cff4zExEQkJCTgT3/6k3Der776KmJjY3HLLbdgx44ddq0P3zllHk6CSWWjmDHmWZzP0VmzZmH+/Pm47777rLGPP/7Y+u/HH38cnTrRXWMBYN++fQgNDXVqHRhrn/gYyph7a/0c7dOnDzZs2IAHH3zQJu7j44MXX3wReXl5NmUSL1y4gCeffBKHDx9GWFgYZs6ciT179mDUqFE27z9+/Diys7Nx7NgxlJSUYPTo0fjpp5+gFTyKdQXfOWUe7cqD4s39McbajitydNiwYQgJCRHMX8Ynn3yC6dOnu3rVGWv37MlPPo4y1nZuRI7q9Xrccsstirifnx9SU1Ph42M7rs2pU6dw8803IywsDAAwevRofPbZZ4r3b968GXfffTe8vb1x0003ITY2FocOHWpxfbhxyjyeRdY0+8cYa1st5WhZWRlSUlKsf6tWrbJ73gcOHEBERATi4uLI1yVJwpgxY5CcnOzQfBlTi5byk4+jjLUtd8vR2NhY/PjjjygoKIDJZMKmTZtQWFiomK64uBjduv06QFh0dDSKi4tbnD9362UeTYYEEx84GXNb9uRoWFiYzXMujli3bl2zd00PHjyIqKgonD9/HgaDAfHx8Rg2bNh1LYux9sZVx9D6+noMGzYMDQ0NMJlMmDJlCpYsWYKhQ4ei+v9Goz1//jwGDhyITZs2Kd6flZWFl156CQDw5z//GTNnznR6nRhrD+zN0SsXea/IzMxEZmam9f+jR4/G2bNnFe97+eWXcccddzi0TsHBwXjrrbcwbdo0aDQa3HbbbTh16pRy3YkR4CWp5bu8LTZOV61aZb3aXHahdYa2PmUKJOM/1XUh42eqlWVj6i/4ktP6ldAfQsfz9LDWunpl3ORD7xQNnQQ7i+Bz9yFKz2gb6OHyNbXKYf4BQDLRQ/1rG5TrLZnpFdHWO/g96ojdxCKYh6Bsgagcj7OuPCiuZlfnaKOlHvK1w7sLSgRJkgMnJHb8mLQ4vaPzcISgHA0E+4YsKoXk0DJbseyOiMb+z1C0jcISM6Lvp4VnQ1pcD7RejppMJmzYsAGHDx8WThMVFQUACA8PR3p6Og4dOnTDG6c2OXr5IizfHrNdx/Ndyff96Ku8G/y/U0YRUwIzQr8i4z10dKm2Dg7ko5dE70sdNfRxykicSIn2gRrZRMb97Vy39ujYpSgy7l1Jf1bOcFV+ent7Y+/evfD394fRaERqairGjx+PAwcOWKfJyMggT4IrKiqwZMkS5OTkQJIkJCcnIy0tDcHBwU6vlz3sOc99Jfw7ReznKWHktKdqbibjIcfo81RdJVEK6BJdksVSdZGOO1FOyJXMF+n109TTZRMtDTeuJMsVVOk5UwBdplEWtJIkUc3IVmBvjrZ0kXf37t0uXCvgt7/9LX77298CaMoh6jnS6OhomzuqRUVF1mNyc1o8O83MzEROTg5ycnIQJqj3w1hbcqeuDm3h6hztQNS7ZayttVaO7t69G/Hx8YiOjiZfr62ttd61qa2txc6dO21G/L1Rrs5RLwhqVTPWRlzRZVCSJPj7N11SMBqNMBqNNndIqqursXfvXtx5552K9+7YsQMGgwEhISEIDg6GwWDA9u3bXbeBLeDzXObu3K1bL9DUEwIAKisr8eabb+L+++9XTJOWlobs7Gw0NDTgl19+QX5+PgYOHNjivNv/mTtr12S5qbtDc38tKSwsxIgRI6DX65GQkICVK1cCaLqaazAYEBcXB4PBgMrKyv9bpoxHHnkEsbGxSExMxLfffmudV1ZWFuLi4hAXF4esrKzW2WjGPIgrcnT69OkYMmQITpw4gejoaKxevRoAkJ2drejSW1JSggkTJgAAzp07h9TUVPTr1w8DBw7ExIkTMW7cONdvJGMeyp78NNn5XLjZbEZSUhLCw8NhMBgwaNAg62sbN27EqFGjEBio7Cl3vc+lMaYG9uaoMzZu3Ijo6Gh89dVXmDhxIsaOHWt9LSYmBgsWLMCaNWsQHR2N48ePAwAeffRR9O7dG7/5zW+wcOFC3HxzU4+Bzz//HM899xwAICEhAVOnTkXv3r0xbtw4vPHGGy2O1AvwM6esHXC2S5JOp8Py5cvRv39/VFdXIzk5GQaDAWvWrMGoUaOwcOFCLF26FEuXLsWyZcuwbds25OfnIz8/H9988w0eeughfPPNN23eNYkxd+Vsjq5bt46Mr1mzRhGLiorC1q1bAQA9e/bE0aNHnVo2Y+2dK7oMAoBWq0Vubi6qqqqQnp6OvLw8a0+FdevWkXdWgOt/Lo0xtWjtx9fS09ORnp5OvlZQUEDGRcfltLQ0pKWlWf+/aNEiLFq0yKH14TunzKPZU5y4JZGRkejfvz8AICAgAHq9HsXFxdi8ebN1UIaZM2daB3HYvHkz7rvvPkiShMGD/z97dx8XVZn3D/xzZsABREBQCBzLBCtFEQWfylw3JfIhkixXa28t2kjL7NejvvIh3dbV2u2uu1tX47YH7d7VsnyqVcKHrNZXyo0rbmIpmqYgKgikyNMwc35/uE7iuS6YcWZkZs7n/XrNS/zOmTPXmZnvnLnOuc71HYzq6mqUlZW1+dAkIm/kjhwlIs9wJD+dzdGIiAgMHz7cvv87d+4c8vPzMWbMGOHy13pdGpEeeCJHvR07p+TTVChoshlavDnj+PHj2LdvHwYNGoQzZ84gNjYWwKUO7OXx9bIhSByaRKTl7hwlIvdxJD8dydHy8nJUV1cDAOrq6uzXgwPA2rVrMXbsWE2txMvS09ORl5eHqqoqVFVVIS8vr9mwQiI9c1eO+hL/2hrSJRuUFm+O1lCsqanB+PHj8dZbbwmvi7lMNgSJQ5OIxFrLUSJqO63lpyM5WlZWhl//+tdISkrCgAEDkJaWhrFjxwIQXxteUFBgH+YbGRmJuXPnYsCAARgwYADmzZuHyMhI928okY9yR476El5zSr5NbX0sviPXylgsFowfPx4PP/ww7r//fgBATEwMysrKEBsbi7KyMkRHRwOQD0Eym83YuXNns/jw4cOvbeIyrOsAACAASURBVLuI/IUDOUpEbcRN+ZmUlIR9+/YJ77tyv3hZamoqVqxYYf9/VlYWsrKyXG4Hkd/R4T70unZOG1SLMP5DQzdh/OhFcQ2ps1UdNDHTafGmhJ4S1yIKqpDUCxO8//UdxTNL1YmbB6u4lBUsodr1qAbxMJegKuemM1es2u00SmqiGhqdrPEYIGiLTVI/MridMG4NFtdztQVKTt5fdKhlUAGXhzOoqorHHnsMPXv2xHPPPWePZ2RkYOXKlZg1axZWrlxpr8+WkZGBJUuWYOLEidizZw/Cw8MRGxuL9PR0vPzyy/ZZffPy8rBo0SKX2uY0RVu/VFP39FpI62tKPqeis8iSuqCqrN6qpI6YInhKRdY+Z2q5yrirnqnNifVIt8fxHZSz9UxFtd8AuLz97shRf9dUIh7+f+NG7c7kq5Bk4bIHb48RxkfecEgYTwo+oYlFGMW1Etsr4nqmBkmOyuqiitRLPl81NnH9w1DJPtMXHW8S16D9v8PdhPGex8qFcVeqnzI/r91H3bcL44mjbhDGG0PFI7JCy7R5bqoKFy4bWCPOc+MFcb4oVdrPmK2ySrisJ2ultkU9UxnRvk6xir+zDOJuC4yB4uVF31uufmfpMUd55pR8mgrXLwTftWsXPvzwQ/Tp0wfJyZd++P3xj3/ErFmzMGHCBLz77ru48cYbsXbtWgDA6NGjsXnzZiQkJCAkJATvv/8+gOZDkwBwaBIR3JOjROQZzE8i76bHHGXnlHye6mLSDh06VHi9KABs3649MqooCpYuXSpcnkOTiLRczVEi8hzmJ5F301uOsnNKPk1V4XLxYSLyHOYokfdifhJ5Nz3mKDun5PP0dkSJyNcwR4m8F/OTyLvpLUfZOSUfp7+x+ES+hTlK5L2Yn0TeTX85ys4p+TQVgFVns5gR+RLmKJH3Yn4SeTc95uh17ZyaFHE5kQqLtjQMAJz4OUIYt5Vrp2UOOid+znY1kumhm8Txpvbal6QpRHzEolE80zeawqzCuNUkmr5a/IFTjeLXSro9gvIwBotsWXH7VFnpCVF5GEk5CkukuI5OY7iklEyA5GhQpTisobqv0ofeiErMXF2Gxq1kZVCM4udUJHHhsrLPrrNtEZGVwLFJymW0wQdSuP2ybXT2tXIVc/SaNR06oomZd4j3lyWIFcb/2lNcvuL/Ym7SxLqHinekcUHi0hOdA8SlUMIFJWnCDHXCZRshLl8RJClfEyqM+qZPzovLAnX6h3h/2XT8J/c3gvnpdk/1/EoY//PP6cJ4Y0ftbyxjnbgsn7FBHA+sCRHGQyq0P1SDKqKFywZUimv4icrRAIB6UZu7NkEMANQmSU2WNqBatb+BjRfF3zeA+HU1R4m/Ez1ChznKM6fk82yi4rRX0NdgCCLvwxwl8l6t5SfAHCVqS3rLUXZOyaepUFod7sAPOVHbYY4SeS9H8hNgjhK1FT3mqL4GMZNfUtWWb0TUtlzN0aysLERHR6N379722Pz589GlSxckJycjOTkZmzdvFj42NzcXt956KxISErB48WJ3bRKR32gtP7kfJWpbestRdk7J56mq0uKNiNqWqzn6yCOPIDc3VxN/9tlnUVhYiMLCQowePVpzv9VqxVNPPYUtW7bg4MGDWL16NQ4ePOiWbSLyF63lJ/ejRG1LbznqT2eBSYdUVX+zmBH5Enfk6LBhw3D8+HGnH5efn4+EhAR0794dADBx4kRs3LgRvXr1cqk9RP6C+1Ai76bHHNXX1pJf0tNQByJf5KkcXbJkCZKSkpCVlYWqKu3siaWlpejatav9/2azGaWlpdf+hER+SG9DBol8jadzdO3atUhMTITBYEBBQYE9fu7cOfz6179GaGgopk+f3uwxH330EZKSkpCYmIiXXnpJuN7jx48jODjYfvnN1KlTHWqPV5w5DTKIp5g+X6ctGQMAATXaPrVBMgu0NVB8qrshQjxVuyVUu25Le/G6bSbJpyFIUqZGsLilg7a8DADYqsTtVkQrgbiUjGIVt0OVlZgIEn8cbILlbUHidtd1Ek9zLivHYxOvxin+NpzBNQpgaP56KF5+xE0xSj4EspInghIzshI4onI5LbIJ8kvyra9I8kg0TT0A5w4FOlPqRka2t5KVwPFgiZnWcrS8vBypqan2/2dnZyM7O7vFx0ybNg1z586FoiiYO3cunn/+ebz33ntXPa/2NZC9b76i3dEzwnhEV21pGAA4FyTegR1s0JaeORkuLt/WIahBGA8JlJR7EcQj2olLTNwcLC5f0y/kuDCeYqrQxG4w+maBmY2lScJ45IEaYdxTfUR37EPr6+sxbNgwNDQ0oKmpCQ888AAWLFgAVVUxZ84crF27FkajEdOmTcOMGTM0jzcajejTpw8A4MYbb8SmTZtcblNbGRB8TBg3m8Wf9RK1kzbYJHlPbOK4oV78/X3xvHb/GlAjLvnX7oI4HlwRKYyHnK7XxALPSMrOnBPXB7T9fF68vGw/6gaqYD9vqG8SLiv7/d8jTPs9BAA2D2Wpp3/n9u7dG+vWrcMTTzzRLB4UFIRXX30VBw4cwIEDB+zxc+fO4cUXX8TevXvRuXNnTJkyBdu3b8eIESM0646Pj0dhYaFT7fGKzinRtVKhwMbOKZHXciRHO3fu3OxorSNiYmLsfz/++OMYO3asZhmz2YyTJ0/a/19SUoK4uDinnofIn7lrH2oymbBjxw6EhobCYrFg6NChGDVqFL7//nucPHkSP/zwAwwGA86ePSt8fHBwsNM/YIn04Hr8zu3Zs6cw3r59ewwdOhRHjjSvuf3jjz/illtuQefOnQEAI0eOxKeffirsnF4L7z6lQtQa1fXJVkQzgf7mN7+xD0Po1q0bkpMvFUtvaYjC3r170adPHyQkJGDGjBnCszZEuuOGHBUpKyuz/71+/fpm+XvZgAEDUFxcjGPHjqGxsRFr1qxBRkbGNW8Kkd9xID8dyVFFURAaeukMtsVigcVigaIoWLZsGebNmwfDv0dmREdHe3RziPyOm3LUnRISEvDDDz/g+PHjaGpqwoYNG5odCL7SsWPH0K9fP/zqV7/CN99849D6eeaUfJ+LfcBHHnkE06dPx+TJk+2xjz76yP73888/j/DwcPv/ZUMUpk2bhpycHAwePBijR49Gbm4uRo0a5VrjiPyBizk6adIk7Ny5ExUVFTCbzViwYAF27tyJwsJCKIqCbt264Z133gEAnDp1Cr/73e+wefNmBAQEYMmSJUhPT4fVakVWVhYSExPdsEFEfsRNx1GtVitSUlJw5MgRPPXUUxg0aBCOHj2Kjz76COvXr0fnzp3x9ttvo0ePHprH1tfXIzU1FQEBAZg1axbGjRvnnkYR+QMHcrS1y2NGjhyJ06dPax63cOFC3HfffU41p2PHjli2bBl+85vfwGAw4Pbbb8ePP/6oWS42NhYnTpxAVFQU9u7di3HjxqGoqAhhYWEtrp+dU/J5Nsk1GI5qaSZQVVXx8ccfY8eOHS2uo6ysDOfPn8eQIUMAAJMnT8aGDRvYOSWC6zm6evVqTeyxxx4TLhsXF9es5uno0aOFZWaI6BJH8tOR68KNRiMKCwtRXV2NzMxMHDhwAA0NDQgKCkJBQQHWrVuHrKws4dmTEydOIC4uDj/++CPuuusu9OnTB/Hx8a5vHJEfcCRHW7s8Ztu2be5sEu69917ce++9AICcnBwYBfOHmEwmmEwmAEBKSgri4+Nx+PDhZt8lIuyckk9T4dkLxb/55hvExMQ0O9J7eYhCWFgY/vCHP+DOO+9EaWkpzGazfRnOCkp0iadzlIiunaP56cx14RERERg+fDhyc3NhNpsxfvx4AEBmZiYeffRR4WMuXwvevXt3DB8+HPv27WPnlAjeuw89e/YsoqOjUVVVhb/85S/4+OOPNcuUl5cjMjISRqMRP/74I4qLi+2l3VrCa07Jt6kAVKXF2+UjvpdvOTk5Dq9+9erVmDRpkv3/l4co7Nu3D//5n/+Jhx56COfPn/fLWUGJ3MKBHCWiNuJIfjqQo+Xl5aiurgYA1NXVYdu2bbjtttswbtw4+8ijr776CrfccovmsVVVVWhouDQjdEVFBXbt2sVaxESXuSlHW7J+/XqYzWZ8++23GDNmDNLT0+33devWDc899xw++OADmM1mHDx4EADwzDPPoFevXrjjjjswa9Yse25v2rQJ8+bNAwB8/fXXSEpKQt++ffHAAw9g+fLliIwUz/58Ja84c5pg0o6BBgCjQVzywCp4D2ziyjCwtJe8YZKOQ1OwNm4VV0eBIpvpuk7c5zdYHC+BE1AnHmBurBc/qcGifa1sAZJSF0GSYxJOXHdiCRV/dGSvtzVIUkpG8gl05oPZWrWQa5kJFACampqwbt067N271x6TDVEwm80oKSmxL9ems4JeXRJEkbyxglJD0tIrohIrlx7gRMMknCgZA0hKz0jyWXH2+Jtge5yd0l62ixCux02TZqmC8jCK7HV1tsSMGzhb0YfkbJXaeq4AEH4oShhvCu4gjF8UlGqr6Sje2f0cIn4DlUBZWSLtZ8woWTY/WFwCZ1eE+Oj6HVHa65rGholneU1uJy5H1xbO2+o0sdIS8XvWs6JcGBcXu3CdO/KzrKwMU6ZMgdVqhc1mw4QJEzB27FgMHToUDz/8MN58802EhoZixYoVAICCggIsX74cK1aswPfff48nnngCBoMBNpsNs2bN8unOaaRRXHppVOxBYfwf7bRniC80moTLNljEv45q6iXL12l/HDc0iNdxUVKO5rzkN227qhBNLLRUXI4m/Ij4eyjwuPizbhOUnrHVaXPomgg+8EqjuKRlo+TSyMh2F4XxC6o2S1u+utIxnt6HZmZmIjMzU3if7LI30eU2AJCRkWGfeHD8+PH2kRPO8IrOKdG189wsZZeP/F45XFc2RCEyMhIdOnTA7t27MWjQIKxatQpPP/20R9pF5Fuu/0yCROQo9+RnUlIS9u3bp4lHRETg73//uyaemppq76jefvvt+O6771xuA5F/0t8+lMN6yfeprdxaMWnSJAwZMgSHDh2C2WzGu+++CwBYs2ZNsyG9QMtDFJYtW4bf/e53SEhIQHx8PCdDIrrMxRwlIg9qLT+Zo0RtS2c5yjOn5NtUQPXATKAA8MEHH2hiLQ1RSE1NxYEDB1xqC5HfcUOOEpGHMD+JvJsOc5SdU/ID+kpaIt/DHCXyXsxPIu+mrxxl55R8n58NZyDyO8xRIu/F/CTybjrL0VY7pzk5OfbSG+XnnJu1ksjjVAA6G+5wtStztFEwIyRRm2KONstRC8QzeRK1CeYnf+eSd9NhjrbaOc3OzkZ2djYAILWvZ6Zl7xJQLYx37SiO/9BJO311faO4loxqFL+hshIuqmCKKIN4hmkEXhCvO6BWUOoCgFHQbwiuEB8OafezeNJ4Y52kMaJSGoHit9cWICnRYRW3RRGUHJFVJ5GNPLCJXxJpKRlnuKkah8+6MkfD28UAV5dacaYUiidLxkifUzJHuqxOrOjDJ8lzKSdq0CqKOF9UaRJ4ph0e58H3mDn6S46GKa3XeGuJrJyC8Ydjwnh0Taww3hCrLXBQFyPej9Z2kpQOk9RIEJZfk3zU64PFvysOdQgVxk9Ed9TESrpqYwAwsdNuYfwOk3g/Gqh4bjDZSdH+tVEyJ6WT5atcxfz8JT9T+ppgEZQDEWmC+H2KlJTxejh8rzCeGaad5fiiKs7FSqv29y8AfFffVRgvqtGWtDtVGy5c9ud6cRmYWsnv64u12vI15bHikjb1keJ2dwoWfz8FHRU8Z9kZ4bLuKDGjnhOX6DJYJO2TdAwsHsolveUoh/WS79NZ0hL5HOYokfdifhJ5N53lKDun5PMUnQ13IPI1zFEi78X8JPJuestRdk7Jt/lhfSciv8IcJfJezE8i76bDHGXnlHycAqj6OqJE5FuYo0Tei/lJ5N30l6OSq/GJfIitlRsRtS0XczQrKwvR0dHo3bu3Pfbiiy/itttuQ1JSEjIzM1FdLZ5Ar1u3bujTpw+Sk5ORmprq8qYQ+Z3W8pP7UaK2pbMcZeeUfJ/ayo2I2paLOfrII48gNze3WSwtLQ0HDhzAv/71L9xyyy1YtGiR9PFffvklCgsLUVBQcM2bQOS3WstP7keJ2pbOctQrhvVW28TTV0cH1QjjJZ1qNbEaiKeptrYTT4EdXC5uS9A57TtsFMQAoClIfJrd1k4cNzZo1xNcIZ6KPOCieJpqpUG8vGrS1mpRDeJ2yMrryBgEs6oba8XtMDaKa8Y0id9iaXkBh6nQ3XCHVjlYnkRVBYfaZPOVy8q9uIPsOZvE0/mrouVFNaAAKFeX1bmGtghfJ8myLVEk5QX8nhtydNiwYTh+/Hiz2N13323/e/Dgwfjkk09ceg5fZ60R7y/xQ7EwHPiT9kvZFNpeuGxEe3HcFi6JB2v3u9b24p8bF28Q1Z0Baszi3K21aEvM7DLcLFzWoIhz92LH/cJ4YjvtD4Mgyfep1clfg/WqtsRGh9gLwmXVcHEZHY/gPrQZK1TUqJJag1cJlJzfCTeIyyN1dMs+QLxfTAsWl5JCR228yqb9DQ0A/2zoIIx/XXObePkqbfmaYyZxqawLEH+mFZs4/6PUTppYUL24RrQ7SslYJSNvIo6Iv0NON4jraFkEuVSnuljbWoc5qtNfS+RPFFvLNyJqW57O0ffeew+jRo0SP7ei4O6770ZKSgpycnJcfzIiP9NafnI/StS29JajXnHmlIiI9Ku8vLzZ9aDZ2dnIzs526LELFy5EQEAAHn74YeH9u3btQlxcHM6ePYu0tDTcdtttGDZsmFvaTURERO7FM6fk8xS15VtrRJOtzJ8/H126dEFycjKSk5OxefNm+32LFi1CQkICbr31VnzxxRf2eG5uLm699VYkJCRg8eLFbt1GIl/WWo527twZBQUF9pujHdOVK1fi888/x1//+lcokuGXcXFxAIDo6GhkZmYiPz/fbdtF5A9ay09H9qP19fUYOHAg+vbti8TERLzyyisALl2GMXv2bNxyyy3o2bMn3n77beHjV65ciR49eqBHjx5YuXKlOzePyOe5I0d9CTun5NtUADal5VsrRJOtAMCzzz6LwsJCFBYWYvTo0QCAgwcPYs2aNSgqKkJubi6efPJJWK1WWK1WPPXUU9iyZQsOHjyI1atX4+DBg+7eWiLf44YcFcnNzcVrr72GTZs2ISREPOfAxYsXceHCBfvfeXl5zQ5CEemeI/npQI6aTCbs2LED+/fvR2FhIXJzc7F792588MEHOHnyJH744Qd8//33mDhxouaxlZWVWLBgAfbs2YP8/HwsWLAAVVVVHthYIh/kphxtydq1a5GYmAiDwdBs4sCtW7ciJSUFffr0QUpKCnbs2GG/b+/evejTpw8SEhIwY8YM4XwgqqpixowZSEhIQFJSEv75z3861B52Tsn3uTiD2bBhwxAZKb6I/2obN27ExIkTYTKZcPPNNyMhIQH5+fnIz89HQkICunfvjnbt2mHixInYuHHjtW4RkX9xMUcnTZqEIUOG4NChQzCbzXj33Xcxffp0XLhwAWlpaUhOTsbUqVMBAKdOnbIfTDpz5gyGDh2Kvn37YuDAgRgzZgzuuecej2wikc9yw0ygiqIgNPTSpDcWiwUWiwWKomDZsmWYN28eDP+eDCg6Olrz2C+++AJpaWmIjIxEx44dkZaWJjxgTKRbHp6tt3fv3li3bp3mkpdOnTrhs88+w3fffYeVK1fiP/7jP+z3TZs2DTk5OSguLkZxcbEwZ7ds2WK/PycnB9OmTXOoPbzmlHyep4YzLFmyBKtWrUJqaireeOMNdOzYEaWlpRg8eLB9GbPZjNLSUgBA165dm8X37NnjmYYR+RhXc3T16tWa2GOPPSZcNi4uzj4Mv3v37ti/XzwzKxFd4q59qNVqRUpKCo4cOYKnnnoKgwYNwtGjR/HRRx9h/fr16Ny5M95++2306NGj2eNKS0s1+8/L+1Ui8vyw3Z49ewrj/fr1s/+dmJiI+vp6NDQ0oLKyEufPn8eQIUMAAJMnT8aGDRs0ExNu3LgRkydPhqIoGDx4MKqrq1FWVobY2NgW23NdO6dHm8RT3R9tvNWp9XRsr50G29Iknna+sUFycvisePmgKm2JFFOVuKyLbGbnphDJyypYPqBOXJJFRlQyBgBsJu1zNrUXL2s1iV8TY6N4ui+DRRs3SkraGOvF61A6iNuiOLf5Yq3MUnYtk61MmzYNc+fOhaIomDt3Lp5//nm89957wmELiqLAJii1IrsGzuOufl5npq+XlYxxsmyKo+VsWqLK2iJ6ra3ibVQDxO2WlZgRlo2xuWmvIHpNZO+Ns6V7RO+Puz5/7ih/4GczCfoDUfkFaUmG8gqXn09W1CnS3EUYD+oTJ26KQVumpkYyrDs/8CZh3CYpPVUZri27c0OAuMREiCIuN9Le4FgZEgAYdZP40o+vew8Rxjv8y+FVO8eB/HRkP2o0GlFYWIjq6mpkZmbiwIEDaGhoQFBQEAoKCrBu3TpkZWXhm2++afY42X61rdgcPA1lkbxwVkn5MYPiHYMVOxrE+TIiWPyDLNkkvk7/o8CfNbGNtr7CZY/WikvGXOwiLrsTWKNd3nQ2QrgsTpWJ424Q/s/TwviXP/UQxh/t9A9NrJMq7kM4xQv2oZ9++in69esHk8mE0tJSmM1m+32yA0qyA09e1TklcjdHLgS/PNmKM2JiYux/P/744xg7diyAS4l18uRJ+30lJSX2CVdkcSI988fJGoj8haP56cx+NCIiAsOHD0dubi7MZjPGjx8PAMjMzMSjjz6qWd5sNmPnzp32/5eUlGD48OEOPReRv3M0R1s7gDRy5EicPq3tbC9cuBD33Xdfi+suKirCzJkzkZeXB8DxA0rXeuCJnVPyfR4oTnzlsIP169fbJ1HJyMjAQw89hOeeew6nTp1CcXExBg4cCFVVUVxcjGPHjqFLly5Ys2YN/va3v7m9XUQ+SWcFxIl8ihvys7y8HIGBgYiIiEBdXR22bduGmTNnYty4cdixYweysrLw1Vdf4ZZbbtE8Nj09HS+//LJ9EqS8vDwsWrTI5TYR+Q0HcrS1A0jbtm27pqcuKSlBZmYmVq1ahfj4eACXDiiVlJQ0W0Z0QqalEzotYeeUfJ6rxYcnTZqEnTt3oqKiAmazGQsWLMDOnTtRWFgIRVHQrVs3vPPOOwAujbmfMGECevXqhYCAACxduhTGfw8RXbJkCdLT02G1WpGVlYXExERXN43IL/hbgXAif+KO/CwrK8OUKVNgtVphs9kwYcIEjB07FkOHDsXDDz+MN998E6GhoVixYgUAoKCgAMuXL8eKFSsQGRmJuXPnYsCAAQCAefPmOTxJIZEetNU+tLq6GmPGjMGiRYtwxx132OOxsbHo0KEDdu/ejUGDBmHVqlV4+umnNY/PyMjAkiVLMHHiROzZswfh4eGtDukF2Dklf3AdJ1sBgNmzZ2P27Nma+OjRo+2zhBLRFTisl8h7uSE/k5KSsG/fPk08IiICf//73zXx1NRUe0cVuFRvPCsry/WGEPkjD+9D169fj6effhrl5eUYM2YMkpOT8cUXX2DJkiU4cuQIXn31Vbz66qsALo1siI6OxrJly/DII4+grq4Oo0aNsk+GtHz5cgDA1KlTMXr0aGzevBkJCQkICQnB+++/71B72Dkl38br2Yi8G3OUyHsxP4m823XI0czMTGRmZmric+bMwZw5c4SPSU1NxYEDBzTxy2XdgEvXly5dutTp9rBzSr6PQwaJvBtzlMh7MT+JvJvOctRjndNii7ZszN6GroIlgeK6GGH8vEU8xXSAYPC1KbBJuGyj5CJiY4MwjMCL2qm0jefFCyuS8hoBFyXlXtpp46pR3D7RsgBgC9ROow8ATSHaKcobJeVbrOIZvRFYKykxUy+IS7bd2CiOB16ULC95H5w5SMSjvldQABiu+kzZxJ8xUTkV1Sr5BrS6o+aPhGTmNkVSwkQVtEVWdkZpEn8viNYBwD1lU2TrcKY0gqTUjfR9cGbd7thGJzFHSaapRFzPMrhWWzIOADojQROzBon3i+fUMGF8Z512HQBQ2jlcE7s96kfhsgmmM8L4DQHa8hoAECIoMTM49Ihw2Y9HDBDGw4t6CeM4fEwcdxDz8xcKgEC49h3ZoIr3O4GKb54PijK0F8bv7/CDJvazVVymprJOHK+oE78mddHanG6IFrejnUncV7A11Avjzmj68bgw3v6L24Xxd28cpomNi9rrcjv0lqPeUXSJiIiIiIiIdM03D+MQXaZyJlAir8YcJfJezE8i76bDHGXnlHyfzoY7EPkc5iiR92J+Enk3neUoO6fk+3SWtEQ+hzlK5L2Yn0TeTWc5ys4p+TQF+hvuQORLmKNE3ov5SeTd9Jij7JySb2ONNiLvxhwl8l7MTyLvpsMcdapzqkKF5aopso82iWuBFArKxhTVdhEue/xilDBeViOeBt4qKA9jaRKXXjA0ikssBNSL32nFIjg8IZnTWIV43aqsrIPoKSXLNgWLt8ciKQ/TFKxdj7WdrH3i5tkknwarSfsC2AIkJXACJa93rfiwj6FJ/D7UiZsiprOkbdXVnylZ6RBR3OjkBN6SEi5uKVciW7coZySljaQlY2Q5KlheVHIHgPPbKGqjMyVgWnpO2WvlLZij5CRrZZUwHlKgLZvSOSheuGxVraT0WrA4/n2YtlTFuZ7i8hX3moVhBCriMiJWwe+FIINFuOzdfYqE8R2TkoXxqO/EcXx/UBy/GvPTToGCQEX7PWtworiFRRXvd2ySYpXOrNub3GAM1cQmhP9TuOzpGG2ZJgDYcqGnMG5pr83R2hvEeRt0Q2dh3PbTSWHcHWI2ictA7Q7R5mJeP/E2AkAnfOLYE+osR30zI4iuoNhavhFR23I1R7OyshAdHY3evXvbY5WVlUhLS0OPHj2QlpaGqipxZ2blypXo0aMHevTogZUrm51mbAAAIABJREFUV7prk4j8Rmv5yf0oUdvSW46yc0q+T23lRkRty8UcfeSRR5Cbm9sstnjxYowYMQLFxcUYMWIEFi9erHlcZWUlFixYgD179iA/Px8LFiyQdmKJdKu1/OR+lKht6SxH2Tkl36azhCXyOW7I0WHDhiEyMrJZbOPGjZgyZQoAYMqUKdiwYYPmcV988QXS0tIQGRmJjh07Ii0tTdPJJdI1R/KT+1GitqPDHGXnlHyeJ4YMvvjii7jtttuQlJSEzMxMVFdXAwCOHz+O4OBgJCcnIzk5GVOnTrU/Zu/evejTpw8SEhIwY8YMqJLrIIn0xhPDkc6cOYPY2FgAQGxsLM6ePatZprS0FF27/jL/gdlsRmlp6bU9IZGf0tuQQSJfo7ccZeeUfJ6itnxrjWjIYFpaGg4cOIB//etfuOWWW7Bo0SL7ffHx8SgsLERhYSGWL19uj0+bNg05OTkoLi5GcXExz9AQ/VtrOVpeXo7U1FT7LScnxy3PKzpApDg7CRWRn2stP/U2UyiRt9FbjrJzSr7PA0MG7777bgQEXJq+ePDgwSgpKWlxHWVlZTh//jyGDBkCRVEwefJk4TBDIl1qJUc7d+6MgoIC+y07O7vVVcbExKCsrAzApfyLjo7WLGM2m3Hy5C8zNpaUlCAuLs4NG0TkR9wwZLC+vh4DBw5E3759kZiYiFdeeQXApYO/N998s320UWFhofDxRqPRvkxGRoY7torIf3BYb3M5OTn2o9nl5yRlGYjayPU4mvTee+9h1KhR9v8fO3YM/fr1w69+9St88803AC4NHzSbf6ktcD2HD16Zo41Wp4rwEHmcp3I0IyPDPvvuypUrcd9992mWSU9PR15eHqqqqlBVVYW8vDykp6e7sjnX5MoctUBcfo2oLTiSn47kqMlkwo4dO7B//34UFhYiNzcXu3fvBgD86U9/so82Sk4Wl70JDg62L7Np0yZ3bmKrrszPCv7OJS/jrhz1Ja3WOc3OzrYfxU7oE4Lcuua1R0stHYWPK66L0cRk9Ux/+lm8jp8vBAvjqk07LMtmEdciDKyXDeESv5NNIYKXxOBE3VIAqmR51Shot6CGKAA0dhDHLSGSdYueU9I+g1V8h+zDLa5zKl5WtI0AYKwXD4g3Nrgho1pZxeUhg5dd+ZluzcKFCxEQEICHH34YwKVr206cOIGoqCjs3bsX48aNQ1FRUZsOH7xye8JNNwBX12gzSF6gAO2bqMjqhUJcu88pbqrpKWqj6mydT9n1wE7UUPVobVFn65k6c32zs+12R81aF9N80qRJ2LlzJyoqKmA2m7FgwQLMmjULEyZMwLvvvosbb7wRa9euBQAUFBRg+fLlWLFiBSIjIzF37lwMGDAAADBv3jzNKInr4cocDVOu//P7k6byCk2swy7xd4upSltvHQDqo9oJ442h2vVUWMQ1FP/Z4UZhPNxYK4xbnRiolhgqPrB58Vfidh/odYMwHjjfwSd0w25YURSEhl6qe2mxWGCxWHxmCP2V+dm/r0lYd9SkiGtsigQqktrYOhAfoK19CgDZnb8Sxk/Vi+uf7q3oronVRotf15Ae2v4GAASWnBLGpfXPndB0RjvHAQDEvavN/9ge4u8KADjnaIr4WeezNRzWSz6vtaNJ1zJkELh0Nubzzz/HX//6V/tO1mQyISrq0kGWlJQUxMfH4/DhwzCbzc2G/nL4INEvXD3iu3r1apSVlcFisaCkpASPPfYYoqKisH37dhQXF2P79u32TmdqaipWrFhhf2xWVhaOHDmCI0eO4NFHH/XUJhL5LHedlbFarUhOTkZ0dDTS0tIwaNAgAMDs2bORlJSEZ599Fg0N4pED9fX1SE1NxeDBg3lJDNFVPH3mdO3atUhMTITBYEBBQYE9vnXrVqSkpKBPnz5ISUnBjh077Pc5Mgnozp07ER4ebh+y//vf/96h9rBzSr7P1srtGuTm5uK1117Dpk2bEBISYo+Xl5fD+u+jbj/++COKi4vRvXt3xMbGokOHDti9ezdUVcWqVauEwwyJdMkDOUpEbtJaftocm7TMaDSisLAQJSUlyM/Px4EDB7Bo0SL88MMP+L//+z9UVlbitddeEzbhxIkTKCgowN/+9jf8v//3/3D06FFPbS2R73EgR13Ru3dvrFu3DsOGDWsW79SpEz777DN89913WLlyJf7jP/7Dfp+jk4Deeeed9iH78+bNc6g9rQ7rJfJqbjhiJBoyuGjRIjQ0NCAtLQ3ApUmRli9fjq+//hrz5s1DQEAAjEYjli9fbj9js2zZMjzyyCOoq6vDqFGjml2nSqRbfng9DJHfcDA/L49AckRERASGDx+O3NxcvPDCCwAujTp69NFH8ec//1n4mMsjjbp3747hw4dj3759iI+Pd2wbiPzZddiH9uzZUxjv16+f/e/ExETU19ejoaEBlZWV9klAAdgnAXXX7152Tsn3uZi0q1ev1sQee+wx4bLjx4/H+PHjhfelpqbiwIEDrjWGyB+xc0rkvdyQn+Xl5QgMDERERATq6uqwbds2zJw5E2VlZYiNjYWqqtiwYUOzeuKXVVVVISQkBCaTCRUVFdi1axdeeukl1xtF5C+8YB/66aefol+/fjCZTE5NAvrtt9+ib9++iIuLw5///GckJia2+lzsnJLP87fiw0T+hjlK5L3ckZ9lZWWYMmUKrFYrbDYbJkyYgLFjx+Kuu+5CeXk5VFVFcnKyvTb4lROXff/993jiiSdgMBhgs9kwa9Ys9OrVy/VGEfkJR3K0tck/R44cidOnT2set3DhwlYvQysqKsLMmTORl5cHwPEa4v3798dPP/2E0NBQbN68GePGjUNxcXGr28LOKfk8Dhkk8m7MUSLv5Y78TEpKwr59+zTxKydQudKVE5fdfvvt+O6771xvBJGfcsfQ+23btl3Tc5eUlCAzMxOrVq2yD7V3dBLQsLBfKryMHj0aTz75JCoqKtCpU6cWn9OpzunP1hD8vbJvs1hVY4hw2bLaDprYuQvthcvWXQgSP2GNeNpoRVBKRvbGKZIZoy2CKeMBoDZG+5IYLeKXyWBx7hvdFqh9zibJpjcFOTcFe0C9ti0B9eJlDY2SciGST4Noen1VMlO6wSKOB0iO+hiaXDxk64fFh12jAqqDr6lomn+jJOes4nWqzlyF70z5lpbiTpTAcUvpFWfJyvE4U8KlyQ2le2Qkr6siKxnj6rT7zFHysKaz5cJ4QPXPwnjYTeISM5YbwjSxphBxSbvi28Q/rvqGiUtphBgaNbFARZznHQzinfcdEUeE8dSwn4TxvwqjV2F+NqMAMMC1EjiiUjR6lxgo7is830U8ic7s+kxN7LhNXAGh3XlxiaXoKHHZLtn3hTtYa2q0wX0H5Q/o78BK2zBHq6urMWbMGCxatAh33HGHPX7lJKCDBg3CqlWr8PTTT2sef/r0acTExEBRFOTn58Nms9krXrSEGUQ+TcGl4Q4t3Yio7TBHibyXI/nJHCVqO9cjR9evXw+z2Yxvv/0WY8aMQXp6OgBgyZIlOHLkCF599VV7OZizZy/VeF22bBl+97vfISEhAfHx8fbJkJYvX24fvv/JJ5+gd+/e6Nu3L2bMmIE1a9Y4VP+Yw3rJ9/GoL5F3Y44SeS/mJ5F383COZmZmIjNTe7Z6zpw5mDNnjvAxsklAp06dav97+vTpmD59utPtYeeUfJ50SCcReQXmKJH3Yn4SeTe95Sg7p+Tb1NaHM+grpYm8DHOUyHs5kJ//XoyI2oIOc5SdU/J9/pSRRP6IOUrkvZifRN5NZznKzin5vNam2NZZThN5HeYokfdypEwFc5So7egtR53qnF60tMOe0zc2i9XVi6dwbqzRxpUL4qcLqBVPGmyQVFMQlTGxBYjfFpu4eWgIl6zboJ1FSjAD/KW4VTzjlCqZiErUliaTpB2SUi0BdZK2XBAsW+vc9F0Wk/h9sDpR1sbYIH4fDE3iuCKJO8zB4Q66cvW1CTbJa+yOaxicKdUim6FNUr7GKc6u24PbLi0ZIyrH42jZn9YoTky8LllUdbVkjAxzlNqIrVG887YdOSaMB+JmbbC3uJSMKcBz5Z5kJWbaGxqE8aBASQ03R37iMT+bUaAgUOF5m+tlsEn8Wj9+4z80sTcbRgiXbSzuLIyrDZIf775GhznKDCTf50+Hi4j8EXOUyHsxP4m8m85ylHVOyacpuDTcoaUbEbUdd+TooUOH7DXWkpOTERYWhrfeeqvZMjt37kR4eLh9md///vee2SAiP+JIfnI/StR29JijPHNKPk+RDVslIq/gao7eeuutKCwsBABYrVZ06dJFWJPtzjvvxOeff+7ScxHpDfehRN5NbznKM6fk21QHbq3IyspCdHQ0evfubY9VVlYiLS0NPXr0QFpaGqqqqi49napixowZSEhIQFJSEv75z3/aH7Ny5Ur06NEDPXr0wMqVK922iUQ+zQ05eqXt27cjPj4eN910k3vbSaRHjuSnvn4XE3kXHeYoO6fk8xRby7fWPPLII8jNzW0WW7x4MUaMGIHi4mKMGDECixcvBgBs2bIFxcXFKC4uRk5ODqZNmwbgUmd2wYIF2LNnD/Lz87FgwQJ7h5ZI71zN0SutWbMGkyZNEt737bffom/fvhg1ahSKiorc0HIi/9dafuptMhYib6O3HGXnlHyeqwk7bNgwREZGNott3LgRU6ZMAQBMmTIFGzZssMcnT54MRVEwePBgVFdXo6ysDF988QXS0tIQGRmJjh07Ii0tTdPhJdKr1nK0vLwcqamp9ltOTo5wPY2Njdi0aRMefPBBzX39+/fHTz/9hP379+Ppp5/GuHHjPL1ZRH5Bbz98iXyN3nLUqWtOrQ1GXPgxolnMUC/u3wZdFDxZrXi9shdVVgamKUQbk5VeUY3ic91qgONlYGQXGquSrn1TkDhu6aCNWSWlZGSviUE2Y7yg3apRvI02ybtulbzewnY0il8UoyQuLRnjakkPtfV1XP7he1l2djays7NbfMyZM2cQGxsLAIiNjcXZs2cBAKWlpejatat9ObPZjNLSUmn8ulOhLR0je31EJU+axCUMVCfjIoq7yrqIysYISkC1shJx2JPXdQjKxqhuej7FIHgvZeVlpKWFPLR3cyBHO3fujIKCglZXtWXLFvTv3x8xMTGa+8LCwux/jx49Gk8++SQqKirQqVMnp5tMfk72WRd8J9aJq1SgZ9jPwngHY70wHiTYeRvhXM6J1gEAQYqsZIZjpWTcUlqLWtWgit+/WkE83CD+IWnQyTmlLgHakWdhQeLculAt/vxafxbnqM/RYY7q41NOfq21Gcwu//C9fGutY9oSVfAFoSiKNE5E7ptlcPXq1dIhvadPn7bnYX5+Pmw2G6KiotzRfCK/5o6ZQOvr6zFw4ED07dsXiYmJeOWVVwBcumzm5ptvts+ifXlis6txzgYiOc7WS+RDFHhmOENMTAzKysoQGxuLsrIyREdHA7h0RvTkyZP25UpKShAXFwez2YydO3c2iw8fPtz9DSPyMe7K0draWmzduhXvvPOOPbZ8+XIAwNSpU/HJJ59g2bJlCAgIQHBwMNasWcMDREStcFd+mkwm7NixA6GhobBYLBg6dChGjRoFAPjTn/6EBx54QPrYy3M2FBQUQFEUpKSkICMjAx07dnS9YUQ+zlO/c70Zz5ySb1PV1m/XICMjw370duXKlbjvvvvs8VWrVkFVVezevRvh4eGIjY1Feno68vLyUFVVhaqqKuTl5SE9Pd1tm0nks9yUoyEhITh37hzCw8PtsalTp2Lq1KkAgOnTp6OoqAj79+/H7t27cfvtt3tkc4j8iiP56UCOKoqC0NBQAIDFYoHFYnH44BDnbCBqgZty1Jewc0o+z9WhDpMmTcKQIUNw6NAhmM1mvPvuu5g1axa2bt2KHj16YOvWrZg1axaAS9eyde/eHQkJCXj88cfxl7/8BQAQGRmJuXPnYsCAARgwYADmzZunmWSJSK/0NByJyNe4a8ig1WpFcnIyoqOjkZaWhkGDBgEAZs+ejaSkJDz77LNoaGjQPM5r5mwg8lIc1kvkY1wd7rB69WphfPv27drnUhQsXbpUuHxWVhaysrJcawyRH9LbkCQiX+JIfjoysaDRaERhYSGqq6uRmZmJAwcOYNGiRbjhhhvQ2NiI7OxsvPbaa5g3b16zx3HOBqKW6W0fyjOn5Nsuz07b0o2I2g5zlMh7OZKfNtWpiQUjIiIwfPhw5ObmIjY2FoqiwGQy4dFHH0V+fr5medlcDkQEh3PUFWvXrkViYiIMBkOzmfO3bt2KlJQU9OnTBykpKdixY4f9vtmzZ6Nr16724fwyixYtQkJCAm699VZ88cUXDrXHqTOnxgagw5Hm/VmjZAZzY4PgSJhs9vZAcbwxTHzkzCqYYVuxipc1SNoXICh1AwDtzgtiNeKG2yTlaJpMjrfbGiz+QBkaJGVgJK9VU5Colox4WVkVDVlc9F4G1ohXHlAvfq0USeKogW44PsLfts1dfRRadi2C1ap9qCAGAKpFUsNItrzo/ZZ9eYpK2qCF0jMGwWdGdlTR2RIzziwvqSWlSF5vVVDaRVgCpiWy8jDOkJTRkJa1cUeJGeYoeRNJHjV2idDE6ruLf0TEh1YI4+FGcc08UbkXo5Nj8QIVx0t3OcUN+VleXo7AwEBERESgrq4O27Ztw8yZM+0TC6qqig0bNqB3796ax6anp+Pll19GVdWl8iF5eXlYtGiR643yMg2q+P2rVbX7UYtV/DnqZBTUUoTvlpg5ba0Rxo82dtfEjpWJy4L1OHhBGPerk40e3of27t0b69atwxNPPNEs3qlTJ3z22WeIi4vDgQMHkJ6ebh9yf++992L69Ono0aOHdL0HDx7EmjVrUFRUhFOnTmHkyJE4fPgwjLLfd//GYb3k82QdXyLyDsxRIu/ljvwsKyvDlClTYLVaYbPZMGHCBIwdOxZ33XUXysvLoaoqkpOT7TNsFxQUYPny5VixYkWzORsAcM4Goqt4eh/as2dPYbxfv372vxMTE1FfX4+GhgaYTCYMHjy41fVu3LgREydOhMlkws0334yEhATk5+djyJAhLT6OnVPyef52ITiRv2GOEnkvd+RnUlIS9u3bp4lfOQzwSqmpqVixYoX9/5yzgUjOG/ahn376Kfr16weTyeTwY0pLS5t1Yh2d7IydU/JtKjhkkMibMUeJvBfzk8i7OZijrU1aNnLkSJw+fVrzuIULF9rLJcoUFRVh5syZyMvLc7jZwLVPdsbOKfk0BYBi5Z6VyFsxR4m8F/OTyLs5mqOXJy2T2bZt2zU9f0lJCTIzM7Fq1SrEx8c79dhrnezMN6+gJrqCoqot3oiobTFHibxXa/nJHCVqW22Vo9XV1RgzZgwWLVqEO+64w+nHZ2RkYM2aNWhoaMCxY8dQXFyMgQMHtvo4dk7Jt6kO3Iio7TBHibyXI/nJHCVqO9chR9evXw+z2Yxvv/0WY8aMQXp6OgBgyZIlOHLkCF599VUkJycjOTkZZ8+eBQC89NJLMJvNqK2thdlsxvz58wEAmzZtstcyTkxMxIQJE9CrVy/cc889WLp0aasz9QIODOvNyclBTk4OAMBacxGhZc0nZ5adahZdvCupvABLiKQkg7hKhfBNMDaIFw0UzzCNdj+L40FV2idtd0HcEJtRUkomSFzvpbGjYB3txO0wSGaMl5XjEb22stdbtg5nygLJSsYYGiVlKmSvlUnSyCpxWLBm3c8EemWONtrqHC8lI4pbZR8wSXkUJ8qPCGbLByCvbORUJSQHvuyarcMNJVlU555SXDJH9WCheWfzwtkSM46vmDl6RY5aINlZ0XUTEC0uSXG6V7Am1q2LePKOG9pVC+PtDeL3N8igLcdl9IpiF8zPK/Oz/Jzsh6fjLJKSMfWSnWCtTbsfkFU1s0lKzIQo4h1SsKL9PRqoXP8r+mps9cJ4qVX8I3j/xa6aWFCRNj8BQDlUfO0N8wmez9HMzExkZmZq4nPmzMGcOXOEj3n99dfx+uuva+IZGRnIyMiw/3/27NmYPXu2U+1p9Rdadna2vehyoKm9Uysnui5UteWbn7syR9sZxF/eRG2KOfrLfhSOz3RIdF20lp9+nqNX5mfnKGePOhJdBzrLUU6IRL5NlZ8JJiIvwBwl8l7MTyLvpsMcZeeUfJ/OhyQReT3mKJH3Yn4SeTed5SgnRCKf5+oMZocOHbJf6J2cnIywsDC89dZbmD9/Prp06WKPb9682f6YRYsWISEhAbfeeiu++OILT24ekc/jTKBE3ouz9RJ5N73lKM+cku9zMSlvvfVWFBYWAgCsViu6dOmCzMxMvP/++3j22WfxwgsvNFv+4MGDWLNmDYqKinDq1CmMHDkShw8fdmgGMiJdcsOOs1u3bujQoQOMRiMCAgI09dxUVcUzzzyDzZs3IyQkBB988AH69+/v8vMS+T0/+2FL5Hd0lqPsnJJPU1TVrQXEt2/fjvj4eNx0003SZTZu3IiJEyfCZDLh5ptvRkJCAvLz8zFkyBC3tYPIX7gzR7/88kt06iSeaXXLli0oLi5GcXEx9uzZg2nTpmHPnj1ueV4if+XufSgRuZcec9SpzqliUzUlRGTlSlTBPNiyqgmyKZINTeIHGAUzUgtmaQcABFWJ122qFl9dHFijneo7oFY8LbgtQNy+4Erxi9IYJjizJnlRZGV0nInLytEYGyXlfyQffqNFGzcIYpdWIt4eW6A4bm3nhpHlbjyitGbNGkyaNMn+/yVLlmDVqlVITU3FG2+8gY4dO6K0tBSDBw+2L2M2m1FaKi43cP25OGubqNwJIL/ewYnyI4pBdkW/G844S7fZyVItRsc/j7JcVEV1tAAoojPr0hI9Ts5+4IYccKYskPMr9/yOdePGjZg8eTIURcHgwYNRXV2NsrIyxMbGevy5yTsJcw4AOoYLwxcExyQHhJcLl+0cIK5T18FYJ4wHQvuFYXRylhOjpwqO6uysjKfVqOK6fPVO7Kcskt+GFyTruCjZIQUp2h+CQZJSaiGSEjPBiuszjAdKSt3Idjun67U52uGkeGFrTc01t8tn6CxHec0p+b5WptcuLy9Hamqq/Xa5ntnVGhsbsWnTJjz44IMAgGnTpuHo0aMoLCxEbGwsnn/++X8/naDjJemUExHckqOKouDuu+9GSkqK8P7S0lJ07fpLbTzvOmhE5MV0VqaCyOfoLEc5rJd8myo/43tZ586dNdeniWzZsgX9+/dHTEwMANj/BYDHH38cY8eOBXDpR+/Jkyft95WUlCAuLu5aWk/k/9yUo7t27UJcXBzOnj2LtLQ03HbbbRg2bNgvT8ODRkTOcyA/AfDXIlFb0WGO8swp+T43HU1avXp1syG9ZWVl9r/Xr1+P3r17AwAyMjKwZs0aNDQ04NixYyguLsbAgQPdtz1E/sYNOXr5AFB0dDQyMzORn5/f7H4eNCK6Rjo7K0Pkc3SWo+ycko9zT8LW1tZi69atuP/+++2xl156CX369EFSUhK+/PJLvPnmmwCAxMRETJgwAb169cI999yDpUuXcqZeIinXc/TixYu4cOGC/e+8vDz7waLLMjIysGrVKqiqit27dyM8PJzXmxK1yoH8dCBH6+vrMXDgQPTt2xeJiYl45ZVXmt3/9NNPIzQ0VPjY48ePIzg42F62berUqW7ZMiL/4J4c9SV+dBKYdEkF4IZZzEJCQnDu3LlmsQ8//FC6/OzZszF79myXn5fI77khR8+cOYPMzEwAQFNTEx566CHcc889WL58OQBg6tSpGD16NDZv3oyEhASEhITg/fffd7XlRP7PTftQk8mEHTt2IDQ0FBaLBUOHDsWoUaMwePBgFBQUoLq6usXHx8fH20u6EdEV3JSjvoSdU/J5/lZ8mMjfuJqj3bt3x/79+zXxK8+wKIqCpUuXuvQ8RHrkjn2ooij2M6MWiwUWiwWKosBqteLFF1/E3/72N6xfv97l5yHSI739znW6c3p16RirpESIrZ0TpWQkr3lArfgOxapdUUC9eFnTz7KSMeI6K4YGwXTc0lI3wjCM9eLnbHdBO/RTlYwGlb1WxgZxPLBO20bZa2JsFLfPICkxIxouICoVBACqrGSMSTyCvCnYDROW6CxpneZMeRjZaykrGWOV1FMRcnLos7QtgrhsG2UT4jjTFOk6ZHW0JG1x5qWSceazLslRWTsUWU5f73YTuYkhOFgYr+8qLiXT7tafNbGBYT8Kl+0eeFa8DklJD6ugXIhVVotPwtnSMw5zU35arVakpKTgyJEjeOqppzBo0CD813/9FzIyMlodYn/s2DH069cPYWFh+MMf/oA777zTLW3ypPM2cdmgWsmXpuzdE371St4T0ecIcO7EmqwkkVVWqsgNP9NMSqAwHqSIX8PKBm3uBpdLfnTrgc72oTxzSr5NVQGrh3bYROQ65iiR93IwPy+Xe7osOzsb2dnZzZYxGo0oLCxEdXU1MjMz8fXXX2Pt2rXYuXNni+uOjY3FiRMnEBUVhb1792LcuHEoKipCWFjYNW0SkV/R4T6UnVPyfTo7okTkc5ijRN7Lgfx0tCQbAERERGD48OH48ssvceTIESQkJAC4NPFgQkICjhw50mx5k8kEk8kEAEhJSUF8fDwOHz7crDNMpGs624dytl7yfTqawYzIJzFHibyXG2YCLS8vt096VFdXh23btiElJQWnT5/G8ePHcfz4cYSEhGg6ppcfa/33JSI//vgjiouL0b17d/duI5Ev09lsveyckm9TVcBqbflGRG2HOUrkvRzJTwdytKysDL/+9a+RlJSEAQMGIC0tDWPHjpUuv2nTJsybNw8A8PXXXyMpKQl9+/bFAw88gOXLlyMyMtJtm0jk09yUoy1Zu3YtEhMTYTAYmo2Q2Lp1K1JSUtCnTx+kpKRgx44d9vtmz56Nrl27SktEAddeJorDesn3+dkRIyK/wxwl8l5uyM+kpCTs27evxWVqamrsf2e34RwQAAAgAElEQVRkZCAjIwMAMH78eIwfP97lNhD5LQ/vQ3v37o1169bhiSeeaBbv1KkTPvvsM8TFxeHAgQNIT09HaWkpAODee+/F9OnT0aNHjxbXfS1lotg5Jd+mQjqbMhF5AeYokfdifhJ5t+uQoz179hTG+/XrZ/87MTER9fX1aGhogMlkwuDBgz3WHuc7py68PrJZ0A0WSRmYBsefzCgpg2KsFZ/qNjRJSmMI5vRWBWVxWmJoErelXY32OVWDZGS15CnbnRe32ySIKxZJyRjZnOOyiiOC8jDWIHG7GzuI45b2kunPg8TP2U4cFpOVEdEjFdrhHZIjbqIyMKrktXSuZIyTZKVXJPVeRG1UjM6VqVElz6mIrnSQ5aivfu4U2XeOrIyAG3aKvvpakU9TojsJ42f7i/cwo2/+pyZ2e7C4lEykQZwX9ZLv20qbtpTGRdWpPZ2UrDSIw5ifdioAm+DHUK2tURuTlIypl9QClPUvRKVkZJXAZPtz2fKBws+GpH2ufo6uwXmbSRg/djZKE+t20eLp5ngvL8jRTz/9FP369bNPXuaoaykTxTOn5OP870JwIv/CHCXyXsxPIu/m+KRkLZV7GjlyJE6fPq153MKFC3Hfffe1uO6ioiLMnDkTeXl5TrT72stEsXNKvk2FVxxRIiIJ5iiR92J+Enk3B3O0tXJP27Ztu6anLykpQWZmJlatWoX4+HinHnutZaLYOSXfxx0rkXdjjhJ5L+YnkXdroxytrq7GmDFjsGjRItxxxx1OP768vByRkZEwGo1OlYliKRnyceqlCzlauhFRG2KOEnkvB/KTOUrUhjyfo+vXr4fZbMa3336LMWPGID09HQCwZMkSHDlyBK+++qq9HMzZs2cBAC+99BLMZjNqa2thNpsxf/58AO4pE8Uzp+TbVPnkNs7o1q0bOnToAKPRiICAABQUFKCyshK/+c1vcPz4cXTr1g0ff/wxOnbsCFVV8cwzz2Dz5s0ICQnBBx98gP79+7thY4j8kJtylIg8gPlJ5N2uQ45mZmYiMzNTE58zZw7mzJkjfMzrr7+O119/XRN3R5konjkl32e1tXxz0JdffonCwkL7mP3FixdjxIgRKC4uxogRI7B48WIAwJYtW1BcXIzi4mLk5ORg2rRpHtksIr/hphwlIg9oLT+Zo0RtS2c56tyZU1VQ9kUyfbWw+oDkrLNRUkpGVgpFVJLGICubIomrsm65UXuHanSulIxsOwNqRaVkJOuWzMxlqhZPXR5Qp40rspIxstIigm2XxS2h4mUbOoq3xxIqbkqTq6VkVNVjY/E3btyInTt3AgCmTJmC4cOH47XXXsPGjRsxefJkKIqCwYMHo7q6GmVlZYiNjfVIO5yjar6kpEfcROVhvOkLTjrvviDWFrNNyp5T9ho600bZss4M3ZHWInCO4up63JCjJ0+exOTJk3H69GkYDAZkZ2fjmWeeabbMzp07cd999+Hmm28GANx///32oUVeRVGgBDQvK6I26bhEgjtIyiM1xYQL4xdvFO9Huwed1cQ6S6pUhSqScgq2BmE4UPDDxSipr2eV/ECRxY2KC6W+PLgP9UVNsOGstVYTtwp+2El+usIie/8kP5jbCfbRsq9d50rGAO0U7QO86azUqaaOwnhTpfbHoSLJLb+nwxzlsF7yfW7omCiKgrvvvhuKouCJJ55AdnY2zpw5Y+9wxsbG2sfZl5aWomvXrvbHms1mlJaWeknnlMgLuZijAQEBeOONN9C/f39cuHABKSkpSEtLQ69evZotd+edd+Lzzz936bmIdIelZIi8m85ylJ1T8nEqVNEZwCu0VvsJAHbt2oW4uDicPXsWaWlpuO222+TPKPiSUARHJ4kIcCRHWxMbG2s/+NOhQwf07NkTpaWlms4pETnL9fwkIk/SX46yc0q+TUWrQx1bq/0EAHFxcQCA6OhoZGZmIj8/HzExMfbhumVlZYiOjgZw6UzpyZMn7Y8tKSmxP56IruJAjjrj+PHj2LdvHwYNGqS579tvv0Xfvn0RFxeHP//5z0hMTHTb8xL5JTfnJxG5mQ5z1JuGnhNdG9XW8q0VFy9exIULF+x/5+XloXfv3sjIyMDKlSsBACtXrsR9990H4NJMZKtWrYKqqti9ezfCw8M5pJeoJa3k6OXRDZdvOTk5wtXU1NRg/PjxeOuttxAWFtbsvv79++Onn37C/v378fTTT2PcuHHXY8uIfF9r+1DO5kvUtnSWozxzSj5NVV0f7nDmzBn7FNpNTU146KGHcM8992DAgAGYMGEC3n33Xdx4441Yu3YtAGD06NHYvHkzEhISEBISgvfff9/l7SDyV47kqCOjGywWC8aPH4+HH34Y999/v+b+Kzuro0ePxpNPPomKigp06tTp2hpOpAPu2IcSkefoMUfZOSWfp7o43KF79+7Yv3+/Jh4VFYXt27dr4oqiYOnSpS49J5GeuJqjqqriscceQ8+ePfHcc88Jlzl9+jRiYmKgKAry8/Nhs9kQFRXl0vMS6YGr+UlEnqW3HG21c5qTk2MfYmVpqEBN+cceb1RbKi8vR+fOnT2z8krXV9Hk+ioAOLmdFwSxM+JFA8VhaVzm+PHjDi13e/pAVFQcbXEZfz9zcmWONhgvoPymls9A+TqP5qgX8fbtvJ45umvXLnz44Yfo06cPkpOTAQB//OMfceLECQDA1KlT8cknn2DZsmUICAhAcHAw1qxZ4zUTlV2Zo43tLqKy9+E2bpFnec1nt0H8uev0rnjx9wTx9yC/ZMNrtlPCkRx1JD8B/96PXpmfhw4ZkHGf/88h4T2fXXGnqxPWaGJVslX0F4e9ZxvlmKNiiiqaelQiNTW11aFXvk4P2wjoZzv1Rg/vqx62EdDPduqNHt5XPWwjoJ/t1BO9vKd62E49bKO/4oRIRERERERE1ObYOSUiIiIiIqI2Z5w/f/58Zx6QkpLioaZ4Dz1sI6Cf7dQbPbyvethGQD/bqTd6eF/1sI2AfrZTT/TynuphO/Wwjf7IqWtOiYiIiIiIiDyBw3qJiIiIiIiozbFzSkRERERERG2OnVMiIiIiIiJqc+ycEhERERERUZtj55SIiIiIiIjaHDunRERERERE1ObYOSUiIiIiIqI2x84pERERERERtTl2TomIiIiIiKjNsXNKREREREREbY6dUyIiIiIiImpz7JwSERERERFRm2PnlIiIiIiIiNocO6dERERERETU5tg5JSIiIiIiojbHzikRERERERG1OXZOiYiIiIiIqM2xc+oj5s+fj9/+9rdt3QwiIiIiIiKP8NvOabdu3bBt27ZmsQ8++ABDhw697m0pLS1FQEAAjh49qrkvMzMTL7zwwnVvExERERERkTfx286pN+nSpQtGjBiBDz/8sFm8srISmzdvxpQpU9qoZURERERERN5Bt53T77//HsOHD0dERAQSExOxadMm+33Dhw/HihUr7P+/8oyrqqp49tlnER0djfDwcCQlJeHAgQMAgIaGBrzwwgu48cYbERMTg6lTp6Kurg4AMGXKFE3ndM2aNUhMTESfPn0AAM888wy6du2KsLAwpKSk4JtvvhG2fefOnTCbzc1iV54pttlsWLx4MeLj4xEVFYUJEyagsrLSlZeLiIiIiIjIo3TZObVYLLj33ntx99134+zZs/jv//5vPPzwwzh06FCrj83Ly8PXX3+Nw4cPo7q6Gh999BGioqIAADNnzsThw4dRWFiII0eOoLS0FL///e8BXBq+W1FRgX/84x/2dX344YeYPHmy/f8DBgxAYWEhKisr8dBDD+HBBx9EfX2909v39ttvY8OGDfjqq69w6tQpdOzYEU899ZTT6yEiIiIiIrpe/LpzOm7cOERERNhvTz75JABg9+7dqKmpwaxZs9CuXTvcddddGDt2LFavXt3qOgMDA3HhwgX88MMPUFUVPXv2RGxsLFRVxf/8z//gzTffRGRkJDp06ICXX34Za9asAQAEBwfjwQcfxKpVqwAAxcXF2Lt3Lx566CH7un/7298iKioKAQEBeP7559HQ0OBQh/lq77zzDhYuXAiz2QyTyYT58+fjk08+QVNTk9PrIiIiIiIiuh78unO6YcMGVFdX229/+ctfAACnTp1C165dYTD8svk33XQTSktLW13nXXfdhenTp+Opp55CTEwMsrOzcf78eZSXl6O2thYpKSn2zvA999yD8vJy+2OnTJmCjz/+GPX19fjwww9xzz33IDo62n7/G2+8gZ49eyI8PBwRERH4+eefUVFR4fR2//TTT8jMzLS3o2fPnjAajThz5ozT6yIiIiIiIroe/LpzKhMXF4eTJ0/CZrPZYydOnECXLl0AAO3bt0dtba39vtOnTzd7/IwZM7B3714UFRXh8OHD+NOf/oROnTohODgYRUVF9s7wzz//jJqaGvvj7rzzTkRFRWHjxo343//932ZDer/55hu89tpr+Pjjj1FVVYXq6mqEh4dDVVVN+69un9VqbdYJ7tq1K7b8//buNbaq8873+G95b99v2GAndkxDGJJgbtkHOwMiCTNoam7nlAY8OhOCTgaRZB+GRlM1UtQXo0YKZ8R0WkWTSL1IVlDV0gik0zMdJm1w6AvgTK0U1yok02QupA03N4BtLr7b+7LOi5w6cdd/e3uzTezH/n6kLeH/eva67O0X/Pw8a/2PHRsXzIeHh8euDwAAAABmmjkZTtesWaPi4mJ94xvfUCwW08mTJ/XGG2/oiSeekCRFIhH94z/+owYHB/XBBx/o4MGDY+/95S9/qdOnTysWi6m4uFgFBQUKhULKycnRs88+q6985Su6du2apI9byLz11lvjjv3UU0/pq1/9qm7evKkvfOELY/W+vj6Fw2FVVVUpHo9r//796u3tNc//gQce0PDwsH76058qFovpb//2bzUyMjK2fe/evfqbv/kbXbhwQZLU1dWlo0ePTs2HBwAAAAB3wJwMp3l5efrnf/5nHTt2TAsWLNC+ffv0gx/8QEuXLpUkfeUrX1FeXp7uuusu/eVf/qV27do19t7e3l49++yzqqio0L333qv58+eP9Sn9+7//ey1ZskRr165VWVmZPv/5zwfuGX3qqad08eJF/cVf/IXy8/PH6ps2bdKWLVv0wAMP6N5771VBQYEWLlxonn95ebm+853v6JlnntE999yj4uLicU/v/fKXv6xt27Zp48aNKi0t1dq1a3X69Okp+/wAAAAAYKp5vrVuFAAAAACAz9CcnDkFAAAAAMwshFMAAAAAwLQjnAIAAAAAph3hFAAAAAAw7cKZDA6VFSu3et74YorHKVllL9V+c5JmPRyy62XhoUDtrtBoir3PbD1J+yvoGik167Fhe3wo+JEoJ57ioCn+JJHiVMz95MTsL95PuW/72081vig5pO7ubnvjp2zaUKye64kJxyyo+VO1tram3RcAAACA6ZNROM2tnqd7v/E/x9V83w4diXgwdYTCdtgsLRo269XF/WZ9Y9W/BWpfrjhvjp3pXu+rNOvf/u0Gs37tPxaY9XnvBz/voi47tMUL7UQ4tMD+Lgu7gt9b8Uf2HwPixfav1FBlyKzHSuxjhk6/btb/UM/1hNrf+tyEY/74v6UPuQAAAACmV0bhFJhpfPmK+ammiAEAAAC4gnAKp/mSkqnWlgMAAABwBuEUzkvKXi4OAAAAwB2EUzjt42W9hFMAAADAdYRTOM2XlGBZLwAAAOA8wimcxz2nAAAAgPsyCqd+LEcjV4vG1bx4ilYgw8F6PN8OET3zcs16PGG3PHm38J5Ara3wt+bYRwpSNNKcBiN+LFA7dWupOfZqV5lZL+q0r6fgenBpa26f3UqmoNtuA1NyySwrZzS4n3hJiu8s3/59SNVDNVXdbjwT5EuK+YRTAAAAwHXMnMJpvnyW9QIAAACzAOEUbvOlBNkUAAAAcB7hFE7z5SkmeykxAAAAAHcQTuE0X1KSmVMAAADAeYRTOC/BzCkAAADgPMIpnPbx03pnzhOZAQAAANyetOG0paVFLS0tkiT/5oCKz49v8hEesd+X2x9cazlaZoeIgbo8s96fF2yPIknniyoDtdb8VebYK4kLZn1V3kdm/f7ckkAt5sfNsf93ON+s/++ePzbrJz68P1Dzf1tsji37nVlW8Uf2Z5J/M3iOuTftLyd0o9/eeW+fXS8sCJT8ugXmUK80w793ZDnp6YuZUwAAAGA2SJskotGootGoJKnw7oV3/ISATPjylBAzpwAAAIDrWNYLp7GsFwAAAJgd+F89HOcp4edM+Ern0qVL2rBhg+rr67V8+XK9+uqrgTHf/OY3FYlEFIlEtGLFCoVCIV2/fl2StGjRIq1cuVKRSESNjY1TfoUAAADAXMDMKZzmS0pm+TeWcDisl19+WatXr1ZfX58aGhrU1NSkZcuWjY154YUX9MILL0iS3njjDf3DP/yDKis/uff5xIkTWrDAvg8XAAAAQHqEUzjN9z2N+qH0AydQU1OjmpoaSVJpaanq6+vV2dk5Lpx+2uHDh7Vz586sjgkAAABgPJb1wnlJeRO+urq61NjYOPb6/dOnLefPn9eZM2e0Zs0ac/vg4KBaW1vV3Nw8VvM8Txs3blRDQ8OE+wYAAACQWkYzp6GYVNo5vkVMXm/CHjscbHkyUJtrjh2utFuBjMbs7Nw/Emzh8u/9d5tjB5N2m5q+okKzfjPZGahdjAdb10jSkat2gOl4/z6zXnIu+HGXfBRsuSNJ+bfszzXcb9dzbw0Hajk9vebYZFePXR8cNOuh8nKjFmy5I0m5RfavVLzQ/o6T4ezawHzcSmbiv7FUVVWpo6Mj7b76+/vV3NysV155RWVlZeaYN954Q4888si4Jb1tbW2qra3VtWvX1NTUpKVLl2r9+vUZXQcAAAAw1zFzCqf58hTzwxO+JiMWi6m5uVm7du3Sjh07Uo47cuRIYElvbW2tJKm6ulrbt29Xe3v77V8QAAAAMEcRTuG8hO9N+ErH9309/fTTqq+v1/PPP59y3K1bt3Tq1Cl98YtfHKsNDAyor69v7N/Hjx/XihUrsr8oAAAAYI7hgUhwmi8v7bLedNra2nTo0KGxdjCSdODAAV28eFGStHfvXknSj3/8Y23cuFHFxcVj77169aq2b98uSYrH43ryySe1efPmrM4HAAAAmIsIp3CaL01i6a59n+7vPfroo/J9+97fT9u9e7d27949rrZ48WK98847ad8LAAAAYGKEUzjN1+SW7gIAAACY2QincF6SW6cBAAAA52UUTnOGkyr7z/5xtdCNfnOsXxBsG5MonGeOzb9pn8Zohd165npecaA2Erf3MRi397Eg1z7veaGBQO3fhu4xx35wfb5ZD98M2fWhYC0nZi8nzRm16+GBUXv81RuBWvx3V8yx8oNtfiaSuHUreB63Ss2xuYX2560Uk5u5A3awND4qk+97ivn25w0AAADAHcycwmm+pITPzCkAAADgOsIpnJft03oBAAAATD/CKZzmi2W9AAAAwGxAOIXTfElJlvUCAAAAziOcwnGeEqmetgQAAADAGYRTOM2XWNYLAAAAzAIZhVNvZFQ5H1waV0v0B1uvSFKovCxQK8yzD5fItduSKEXoGOovCtR6S/PNscMjKVrJ5NvnneMF26z8ZrDKHDswaB8zPGTP5IWHrZrdMiY0FLfrvcZOJCW7uoPFDFvGZGTAbvaSMxD8biQpL5aw6znZt5JhWS8AAADgPmZO4TxayQAAAADuI5zCaTytFwAAAJgdCKdw2sdP6+WBSAAAAIDrCKdwXkIs6wUAAABcRziF03x5irOsFwAAAHAeU05wmu9LCd+b8JXOpUuXtGHDBtXX12v58uV69dVXA2NOnjyp8vJyRSIRRSIR7d+/f2xba2urHnzwQS1ZskRf//rXp/T6AAAAgLmCmVM4L9t7TsPhsF5++WWtXr1afX19amhoUFNTk5YtWzZu3GOPPaaf/OQn42qJREJf+tKX9LOf/Ux1dXV6+OGHtW3btsB7AQAAAEwss3AaCsmbVz6ulJOw+1fGe3qCb0/Rd7M0btfDg3b/06Ge4GkPVaboiTpQbNbfTi4y6xfmVwT3MWr3So0P5Jn13FGzrNyB4HXm3bAH595I0emzt98sJ0dTHPQO8VMczxu1fx+SxXZP2GR+il9Buw1t8Dym4Gm9NTU1qqmpkSSVlpaqvr5enZ2dkwqY7e3tWrJkiRYvXixJeuKJJ3T06FHCKQAAAJAhlvXCab9/Wu9Er0ycP39eZ86c0Zo1awLb3n77bT300EPasmWL3nvvPUlSZ2enFi5cODamrq5OnZ2dWV0TAAAAMBexrBeO85T0J/4bS1dXlxobG8d+jkajikajgXH9/f1qbm7WK6+8orKysnHbVq9erQsXLqikpERvvvmmHn/8cZ07d06+7wfPyKO1DQAAAJApwimc5vtSLE04raqqUkdHx4RjYrGYmpubtWvXLu3YsSOw/dNhdevWrdq3b5+6u7tVV1enS5cujW27fPmyamtrM7wKAAAAACzrhfOSfs6Er3R839fTTz+t+vp6Pf/88+aYK1eujM2Stre3K5lMav78+Xr44Yd17tw5ffjhhxodHdWRI0e0bdu2Kb0+AAAAYC5g5hRO85X5faV/qK2tTYcOHdLKlSsViUQkSQcOHNDFixclSXv37tWPfvQjffe731U4HFZhYaGOHDkiz/MUDof1rW99S5s2bVIikdCePXu0fPnyrK8LAAAAmGvShtOWlha1tLRIkkYTg3f8hIBM+JLik5gdncijjz5q3jv6ac8995yee+45c9vWrVu1devWrM4BAAAAmOvShtNPPzymvKhGfknBuO1estx6m9TXFyglrt8wh4aSdjAoGo6Z9fwbwfYwhZV2q5KBXvsSB3rtFjOX5xcFasm8FK1uBuxQlGt3e1F+b3A/uT12zxTveq9ZT/Zct3f+GfMKC8x67O4ys35tdaFZH55v77/snyZ/LpNZugsAAABgZmNZL9x2G+1iAAAAAMw8hFM4bSqW9QIAAACYfoRTOM2XmDkFAAAAZgHCKZxHOAUAAADcRziF03x5LOsFAAAAZgHCKdzmM3MKAAAAzAaZhVPPk58bGl/Kt1u4hObNC9QSt+z2KP7IiH246zftfQ8E+60WXQ+2gJGk/B67XvyR3QpluDL4kcRKQsZIfXzDo6GwO2GfS9dQoObdtPvOJLp67EPG7fY6d1KopCRQSyy62xx76fN2y5jdzT8z6ztKz5r1Xf9UO6lz455TAAAAYHZg5hRO8+UpnmRZLwAAAOA6wimc5zNzCgAAADiPcArnJUU4BQAAAFxHOIXTfF9KsKwXAAAAcB7hFI7zeCASAAAAMAsQTuE87jkFAAAA3JdROPVzPMVLx7eOCYXsNiuhUHCpZbgs2JJEkhSL28dL0WLGv2G0mOm5YY7N+ci+xKIiu+VJUaHRYsaqSfLz7H17IynavdwMttJJpDjvaWkZU1pqb1h0T6DUHbHH/vkX/8Wsf7XygxRHTfE7MUkfL+slnAIAAACuY+YUzkv3QCSiKwAAADDz8SQZOM3Xx8t6J3qlc+nSJW3YsEH19fVavny5Xn311cCY119/XatWrdKqVau0bt06vfPOO2PbFi1apJUrVyoSiaixsXEqLw8AAACYM5g5heO8tMt60/0FJhwO6+WXX9bq1avV19enhoYGNTU1admyZWNj7rvvPp06dUoVFRU6duyYotGoTp8+Pbb9xIkTWrBgQTYXAgAAAMxphFM4L9sHItXU1KimpkaSVFpaqvr6enV2do4Lp+vWrRv799q1a3X58uWsjgkAAABgPJb1wmm+n/2y3k87f/68zpw5ozVr1qQcc/DgQW3ZsmXsZ8/ztHHjRjU0NKilpeW2rwUAAACYy5g5hfPSLevt6uoady9oNBpVNBoNjOvv71dzc7NeeeUVlZWVmfs6ceKEDh48qJ///Odjtba2NtXW1uratWtqamrS0qVLtX79+tu8GgAAAGBuyiicJvNyNFA3vq1KeChp73ggP1gbstuGhG8Nm3XverD1iiT5Q8HxyRF7H7K70Uj9/Sk2zH6h8nJ7Q91dZnnoc8Ggdn213f7nf1X/+rbP63almx2tqqpSR0fHhGNisZiam5u1a9cu7dixwxzz7rvv6plnntGxY8c0f/78sXptba0kqbq6Wtu3b1d7ezvhFAAAAMgQy3rhNF8TL+mdzLJe3/f19NNPq76+Xs8//7w55uLFi9qxY4cOHTqkBx54YKw+MDCgvr6+sX8fP35cK1asmJqLAwAAAOYQlvXCbb6UzPKBSG1tbTp06NBYOxhJOnDggC5evChJ2rt3r/bv36+enh7t27dP0sdP+O3o6NDVq1e1fft2SVI8HteTTz6pzZs3Z3U+AAAAwFxEOIX7/Oze/uijj8r3J97Ja6+9ptdeey1QX7x48biepwAAAABuD+EUzsu2lQwAAACA6Uc4hdN8Sck0T+sFAAAAMPMRTuE2XxIzpwAAAIDzMgqniVypv+YPg0DIHBuKBevhQXu/hd15Zr04ZIeOHKuVzNCQvfM5LDRvnln3760168M1xWa9d2Hw1+Sxh967/RObYmluFwUAAADgAGZO4ThPPst6AQAAAOcRTuE+Zk4BAAAA5xFO4Tafp/UCAAAAswHhFO4jnAIAAADOI5zCfSzrBQAAAJxHOIX7CKcAAACA89KG05aWFrW0tEiS4sMDipWN3x4vtpNBMjdYDw3lmGNHyu12NJ5fataLY4ngvkdGzLGJ/n6zPtvk5BnteD5XY44dXGR/rv019vfQ/7lgbWf1LyZ9bneUL57WCwAAAMwCdlr8lGg0qo6ODnV0dChUbPfBBKaVn+YFAAAAYMZjWS/cxwORAAAAAOcRTuE2X/KS030SAAAAALJFOIXjPGZOAQAAgFmAcAr3cV8pAAAA4Ly0D0QCZrxkmlcaly5d0oYNG1RfX6/ly5fr1VdfDYzxfV9//dd/rSVLlmjVqlX61dHaCTIAABFcSURBVK9+Nbbt+9//vu6//37df//9+v73vz8llwQAAADMNZnNnHpSomD8NFWi2P7fv1cSC9TiMTsLD/tGGxRJgzft1iZ5N4NPDc7rqzDHaq60kqm5K1AbvKfEHNtXZ3+uA7X2vuN1w4FaqRes/f8zSVG/Q3xlvaw3HA7r5Zdf1urVq9XX16eGhgY1NTVp2bJlY2OOHTumc+fO6dy5czp9+rT+6q/+SqdPn9b169f10ksvqaOjQ57nqaGhQdu2bVNFRYrfRwAAAAAmZk7hPM+f+JVOTU2NVq9eLUkqLS1VfX29Ojs7x405evSonnrqKXmep7Vr1+rmzZv66KOP9NZbb6mpqUmVlZWqqKhQU1OTWltb78RlAgAAALMa95zCfWkCaFdXlxobG8d+jkajikaj5tjz58/rzJkzWrNmzbh6Z2enFi5cOPZzXV2dOjs7U9YBAAAAZIZwCuelmx2tqqpSR0dH2v309/erublZr7zyisrKysZt8/3gQTzPS1kHAAAAkBmW9cJ9vjfxaxJisZiam5u1a9cu7dixI7C9rq5Oly5dGvv58uXLqq2tTVkHAAAAkBnCKdzmK+un9fq+r6efflr19fV6/vnnzTHbtm3TD37wA/m+r1/84hcqLy9XTU2NNm3apOPHj+vGjRu6ceOGjh8/rk2bNk3RxQEAAABzB8t64bzJPPRoIm1tbTp06JBWrlypSCQiSTpw4IAuXrwoSdq7d6+2bt2qN998U0uWLFFRUZG+973vSZIqKyv1ta99TQ8//LAk6cUXX1RlZWV2JwQAAADMQZmFU1/KGR2/TNKL2csm/WSwnpOfMMfGy+z6aLnd8iReEjztvLB9KV7I3oefsI9p78SeYM4pyDfryaGhye97iiQXlAdqAzX2ZzJYY+8j/jm7PczShVcCteKc0RRnUpCifgdlGU4fffRR897RT/M8T9/+9rfNbXv27NGePXuyOwkAAABgjmPmFE7zfMmbxNJdAAAAADMb4RTum+RDjwAAAADMXIRTuC/LZb0AAAAAph/hFM5jWS8AAADgPsIp3OZn/7ReAAAAANOPcAr3EU4BAAAA5xFO4TyW9QIAAADuyyicegkp//r4Wk7c7gE6msgL1BIlcXu/9i4UK7br8Xzj6aw5KXaSKeNkwvd9zhw6Wldh1pP5dm/V/Mu9gVri3/4zg5OTQvPmmfWRymB/0aEq+ym2ozUxs/5g3VWz/kTNLwO1SN409DMFAAAAMGsxcwr3sawXAAAAcB7hFG7zWdYLAAAAzAaEU7iPmVMAAADAeYRTOM0TrWQAAACA2YBwCrexrBcAAACYFQincB8zpwAAAIDzMgqnOTGpqGt8EogN2O1KQoPBeqw81xybKLDThW93ZFG8KNjuxS8Mtq6RpJzCQvuY/f1mPVReFjxedbk5dqDObqcyVJniM1m8IFCbd3epOTb/d7fMerzS7q/Tf0/wsx2qtj/X6pqbZn3H3WfM+v8o7TbrMwbhFAAAAHDeFDUHBaaPl5z4lc6ePXtUXV2tFStWmNu/+c1vKhKJKBKJaMWKFQqFQrp+/eOGv4sWLdLKlSsViUTU2Ng4lZcFAAAAzCmEU7jNn8Qrjd27d6u1tTXl9hdeeEFnz57V2bNn9Xd/93f6kz/5E1VWVo5tP3HihM6ePauOjo5srgQAAACY0wincJ7nT/xKZ/369ePC5kQOHz6snTt3ZnnGAAAAAP4Q4RTOy3ZZ72QNDg6qtbVVzc3Nnxzb87Rx40Y1NDSopaVl6g4GAAAAzDE8rRfuSzM72tXVNe5+0Gg0qmg0mvFh3njjDT3yyCPjZlnb2tpUW1ura9euqampSUuXLtX69esz3jcAAAAw16UNpy0tLWMzQvGRgTt+QkBGJnFfaVVV1ZTcD3rkyJHAkt7a2lpJUnV1tbZv36729nbCKQAAAHAb0obTT88ylZbXqbArPm57XoG9Mjh3MFgfHrZbrIzMs+upFh3Hio02NZV2y5i8gSqzHi4tsXdeHmztMlpht6kZKUtxPSluX4wXBWv9C/PNsXk3q+2dpAhioxXBmlc7aI7dtajdrD9b/pG98xnM0+TuK83WrVu3dOrUKf3whz8cqw0MDCiZTKq0tFQDAwM6fvy4XnzxxTt/MgAAAMAsxLJeOC/bcLpz506dPHlS3d3dqqur00svvaRYLCZJ2rt3ryTpxz/+sTZu3Kji4k/6zF69elXbt2+XJMXjcT355JPavHlzdicDAAAAzFGEU7gvy3B6+PDhtGN2796t3bt3j6stXrxY77zzTnYHBwAAACCJcArX+VP7RF4AAAAA04NwCvd9BvecAgAAALizCKdw3mfxQCQAAAAAdxbhFM5jWS8AAADgvozCqZfwlXdzZFzND9n9XkJDwV17yVxzbDI3VYsZ+zyG5wdrfSlashSHjcGSwgMxs54oCp73SIX9McXt7jWKlaWYyrtnKFBaWN1jDp2XP2zWe0ft6ywKB6/nz++ye3vuKr1un5+LJtHnFAAAAMDMx8wp3Ec4BQAAAJxHOIXTPLGsFwAAAJgNCKdwnuczdQoAAAC4jnAKt3HPKQAAADArEE7hvHTLesmuAAAAwMxHOIXz0vU5JZwCAAAAM19mrWTiSYWuD4yr+fn2LvycYJ8VL2GPTdVKZrTCnhIbzQvW44X2vmMleWY9/5bd1sY3TmW01D6/WIlZVqIibtaX11wN1LZU/9ocu67oA7MeySuwDzqXkT4BAAAA5zFzCrf5PK0XAAAAmA0Ip3Cap/TLegEAAADMfIRTuI9WMgAAAIDzCKdwG8t6AQAAgFkhZ7pPAMiWl5z4lc6ePXtUXV2tFStWmNtPnjyp8vJyRSIRRSIR7d+/f2xba2urHnzwQS1ZskRf//rXp+qSAAAAgDmHcAr3+WleaezevVutra0Tjnnsscd09uxZnT17Vi+++KIkKZFI6Etf+pKOHTum999/X4cPH9b777+f1aUAAAAAc1Vmy3rjcfnXuseVvIp55lB/fnGgNlpiZ+Hh+XaCKF3Ya9br5t0M1D6qLTPH3qiy63nX7EsPDwVrfsgcqtEK+7wLyofNek1R8HrKQ4Pm2LtDdjsa/AFf8pLZ3XO6fv16nT9/PuP3tbe3a8mSJVq8eLEk6YknntDRo0e1bNmyrM4HAAAAmIuYOYXzPH/i11R4++239dBDD2nLli167733JEmdnZ1auHDh2Ji6ujp1dnZOzQEBAACAOYYHIsF9aQJoV1eXGhsbx36ORqOKRqOT3v3q1at14cIFlZSU6M0339Tjjz+uc+fOyTeeEux53qT3CwAAAOAThFM4zfP9tMt6q6qq1NHRcdvHKCv7ZGn41q1btW/fPnV3d6uurk6XLl0a23b58mXV1tbe9nEAAACAuYxlvXDenV7We+XKlbFZ0vb2diWTSc2fP18PP/ywzp07pw8//FCjo6M6cuSItm3blv0BAQAAgDmImVO4L8sAunPnTp08eXJsNvSll15SLBaTJO3du1c/+tGP9N3vflfhcFiFhYU6cuSIPM9TOBzWt771LW3atEmJREJ79uzR8uXLp+CCAAAAgLmHcAq3+ZKXyC6dHj58eMLtzz33nJ577jlz29atW7V169asjg8AAAAgw3DqJxJK3Lo1fgelJebYeFGw/8pIhb3fZM2IWf+vi94z6/99Xnug1pMItq6RpDfvecis/+LaIrN+pas8UPMH7I/JD9uhKBRKmvUbo0WB2r8OLjRGSjHfPubm4t+a9btD9vcwJ0zRE3kBAAAATB9mTuG8qWoXAwAAAGD6EE7hvHRP6wUAAAAw8xFO4TZfLOsFAAAAZgHCKZzm6eNepwAAAADcRjiF87J9Wi8AAACA6Uc4hdtY1gsAAADMCmnDaUtLi1paWiRJMRktXwryzfeNlhmtZCrtYyxdeMWsH6h+N8VZFRi1hDnyzwp/Zda/U3DNrP+f8H8J1C5cnW+OTfbmmfWBa3Zbm7NDdYHaueIF5ti2gsVm/WhhxKyX5NrteCw1Bb1mfWF+j1lflt8ZqP1Zof15f/Z8iWW9AAAAgPPShtNoNKpoNCpJKvNSpEtgGvG0XgAAAMB9LOuF23zJS073SQAAAADIFuEU7mNZLwAAAOA8wimcx7JeAAAAwH2EU7iPmVMAAADAeYRTuM2XxD2nAAAAgPMyCqdejqecgsJxtWSp1dZFGinPCdRGF8TNsV+4K1XLmDtnU8m/m/V/KXwgULsgu5VMzlDwGiUpt8+zD3ol+HEPFNqfX2+hPRvYmZciiSWDx/TD9ti8slGzvqC836wvrwy2wEnObzfHNhXa3/Gd4smXlySdAgAAAK5j5hTuS7esN8XfCgAAAADMHPbUH+CK3y/rneiVxp49e1RdXa0VK1aY219//XWtWrVKq1at0rp16/TOO++MbVu0aJFWrlypSCSixsbGbK8GAAAAmLMIp3Cel0xO+Epn9+7dam1tTbn9vvvu06lTp/Tuu+/qa1/7mqLR6LjtJ06c0NmzZ9XR0ZH1tQAAAABzFct64Tg/66f1rl+/XufPn0+5fd26dWP/Xrt2rS5fvpzV8QAAAAAEMXMKt/n6OJxO9JpCBw8e1JYtW8Z+9jxPGzduVENDg1paWqb0WAAAAMBcwswpnOclJg6gXV1d4+4HjUajgaW5k3HixAkdPHhQP//5z8dqbW1tqq2t1bVr19TU1KSlS5dq/fr1Ge8bAAAAmOsyC6c5OcopKhpXihXnmUNHS4O1wsohc+zjJf+R4oAlmZxdRv4obO97fn6wnYpvtGmRpNCoXQ/bHVkUHg7W/JC9j2SKemjUnuzO6wsGtER+yBw7XJFr1q/UFJr1ocXB8X9UdM0c21T4gVm/o9LMjlZVVWV9P+i7776rZ555RseOHdP8+Z+0FqqtrZUkVVdXa/v27WpvbyecAgAAALeBZb1wmy8p6U/8ytLFixe1Y8cOHTp0SA888Ekf3IGBAfX19Y39+/jx4ymf+AsAAABgYizrheN8aRJP5J3Izp07dfLkSXV3d6uurk4vvfSSYrGYJGnv3r3av3+/enp6tG/fPklSOBxWR0eHrl69qu3bt0uS4vG4nnzySW3evDm7ywEAAADmKMIp3JflQ48OHz484fbXXntNr732WqC+ePHicT1PAQAAANw+winc9vtlvQAAAACcRjiF43wpmZjukwAAAACQJcIp3MbMKQAAADArEE7hvizvOQUAAAAw/TILp54n5Y3veZkotHcRKwvWFi/oMcfeHbpz/UwzVZ3XF6il7HNq9C2VJGMXkqT83mCIyhm1g1V42H4CbdFvbpp1r+dGsFg5zxw7uMiuXx+1+5/eLC8O1P6z+i5zbO+8fzXrZTl2D9XsZf+0XgAAAADTj5lTuM0X4RQAAACYBQincB/LegEAAADnEU7hOF9KMHMKAAAAuI5wCrf5ku8TTgEAAADXEU7hPlrJAAAAAM4jnMJtvi8lEtN9FgAAAACylGE49aRQaFwlUZBjjowXBmez7iuxW8nMJEU5o8Fiiom50Ihdzx2w35B/PW6MDdYkKfdKr1mPn/uNfVBDTv+AWS/It1vG5C60W8xoOBQodQ/b7X9+G7fb7kTy7F1PCR6IBAAAADiPmVM4z6eVDAAAAOA8winc5vO0XgAAAGA2IJzCfTytFwAAAHAe4RRO8yX5PK0XAAAAcB7hFG7zffk8rRcAAABwnuf7Ez/qtKWlRS0tLZKkX//611qxYsVncmLTpaurS1VVVdN9GnfcTL/O8+fPq7u7O+24zZs3px23YMECtba2TtWpAQAAALgD0obTT2tsbFRHR8edPJ9pNxeuUZo71wkAAADADXaTUgAAAAAAPkOEUwAAAADAtMsonEaj0Tt1HjPGXLhGae5cJwAAAAA3ZHTPKQAAAAAAdwLLegEAAAAA045wCgAAAACYdoRTAAAAAMC0I5wCAAAAAKYd4RQAAAAAMO3+Hz2vvhOytkh+AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sompy.visualization.mapview import View2D\n", + "view2D = View2D(10,10,\"rand data\",text_size=10)\n", + "view2D.show(sm, col_sz=4, which_dim=\"all\", denormalize=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Hits map" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sompy.visualization.bmuhits import BmuHitsView\n", + "\n", + "vhts = BmuHitsView(10,10,\"Hits Map\",text_size=7)\n", + "vhts.show(sm, anotate=True, onlyzeros=False, labelsize=12, cmap=\"Greys\", logaritmic=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### K-Means clustering" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\Ivan Valles Perez\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py:107: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance. In a future version, a new instance will always be created and returned. Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n", + " warnings.warn(message, mplDeprecation, stacklevel=1)\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sompy.visualization.hitmap import HitMapView\n", + "sm.cluster(4)\n", + "hits = HitMapView(10,10,\"Clustering\",text_size=7)\n", + "a=hits.show(sm, labelsize=12)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Conclusions" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "From the visualizations above we can extract different conclusions like,\n", + "- The houses which have, on average, more bedrooms are generally on lower average income areas.\n", + "- The highest occupations occours only in cities where the population is high.\n", + "- The latitude and longitude of the samples have a strong negative correlation. It can be because California is diagonally oriented with respect to the coordinates system.\n", + "- The most demanded houses (AveOccup) are placed on the 37~38 latitude and -121.6~-121 longitude; i.e. near San-Francisco area\n", + "- Old houses are more likely to have less rooms and bedrooms on average.\n", + "- Low average income areas usually have less rooms and bedrooms than high average ones\n", + "- The house value seems to be related with the average income of the area where it sits.\n", + "\n", + "It is important to remark that there are areas on the map where the density of instances is lower than others. It is represented by the hit map and it should be taken in consideration when interpreting the components map.\n", + "\n", + "The clustering map can be used to help to find out the different behaviors represented in the components map." + ] + } + ], + "metadata": { + "anaconda-cloud": {}, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.5" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/sompy/normalization.py b/sompy/normalization.py index b641b94..cf833ca 100644 --- a/sompy/normalization.py +++ b/sompy/normalization.py @@ -3,7 +3,7 @@ import inspect -class NormalizatorFactory(object): +class NormalizerFactory(object): @staticmethod def build(type_name): @@ -15,7 +15,7 @@ def build(type_name): raise Exception("Unknown normalization type '%s'" % type_name) -class Normalizator(object): +class Normalizer(object): def normalize(self, data): raise NotImplementedError() @@ -27,7 +27,7 @@ def denormalize_by(self, raw_data, data): raise NotImplementedError() -class VarianceNormalizator(Normalizator): +class VarianceNormalizer(Normalizer): name = 'var' @@ -49,26 +49,26 @@ def denormalize_by(self, data_by, n_vect): return n_vect * st + me -class RangeNormalizator(Normalizator): +class RangeNormalizer(Normalizer): name = 'range' -class LogNormalizator(Normalizator): +class LogNormalizer(Normalizer): name = 'log' -class LogisticNormalizator(Normalizator): +class LogisticNormalizer(Normalizer): name = 'logistic' -class HistDNormalizator(Normalizator): +class HistDNormalizer(Normalizer): name = 'histd' -class HistCNormalizator(Normalizator): +class HistCNormalizer(Normalizer): name = 'histc' diff --git a/sompy/sompy.py b/sompy/sompy.py index 9cbd15e..5a32675 100644 --- a/sompy/sompy.py +++ b/sompy/sompy.py @@ -26,12 +26,8 @@ from .decorators import timeit from .codebook import Codebook from .neighborhood import NeighborhoodFactory -from .normalization import NormalizatorFactory +from .normalization import NormalizerFactory -#lbugnon -#import ipdb -import sompy -# class ComponentNamesError(Exception): pass @@ -78,7 +74,7 @@ def build(data, :param lattice: type of lattice. Options are: - rect - - hexa (not implemented yet) + - hexa :param initialization: method to be used for initialization of the som. Options are: @@ -89,7 +85,7 @@ def build(data, :param training: Training mode (seq, batch) """ if normalization: - normalizer = NormalizatorFactory.build(normalization) + normalizer = NormalizerFactory.build(normalization) else: normalizer = None neighborhood_calculator = NeighborhoodFactory.build(neighborhood) @@ -623,8 +619,20 @@ def node_activation(self, data, target=None, wt='distance'): def calculate_topographic_error(self): bmus1 = self.find_bmu(self.data_raw, njb=1, nth=1) bmus2 = self.find_bmu(self.data_raw, njb=1, nth=2) - bmus_gap = np.abs((self.bmu_ind_to_xy(np.array(bmus1[0]))[:, 0:2] - self.bmu_ind_to_xy(np.array(bmus2[0]))[:, 0:2]).sum(axis=1)) - return np.mean(bmus_gap != 1) + topographic_error = None + if self.codebook.lattice=="rect": + bmus_gap = np.abs((self.bmu_ind_to_xy(np.array(bmus1[0]))[:, 0:2] - self.bmu_ind_to_xy(np.array(bmus2[0]))[:, 0:2]).sum(axis=1)) + topographic_error = np.mean(bmus_gap != 1) + elif self.codebook.lattice=="hexa": + dist_matrix_1 = self.codebook.lattice_distances[bmus1[0].astype(int)].reshape(len(bmus1[0]), -1) + topographic_error = (np.array( + [distances[bmu2] for bmu2, distances in zip(bmus2[0].astype(int), dist_matrix_1)]) > 2).mean() + return(topographic_error) + + def calculate_quantization_error(self): + neuron_values = self.codebook.matrix[self.find_bmu(self._data)[0].astype(int)] + quantization_error = np.mean(np.abs(neuron_values - self._data)) + return quantization_error def calculate_map_size(self, lattice): """ diff --git a/sompy/visualization/bmuhits.py b/sompy/visualization/bmuhits.py index d54328d..d382fc6 100644 --- a/sompy/visualization/bmuhits.py +++ b/sompy/visualization/bmuhits.py @@ -6,21 +6,27 @@ from .mapview import MapView +from sompy.visualization.plot_tools import plot_hex_map + + class BmuHitsView(MapView): - def _set_labels(self, cents, ax, labels, onlyzeros, fontsize): + def _set_labels(self, cents, ax, labels, onlyzeros, fontsize, hex=False): for i, txt in enumerate(labels): if onlyzeros == True: if txt > 0: txt = "" - ax.annotate(txt, (cents[i, 1] + 0.5, cents[-(i+1), 0] + 0.5), va="center", ha="center", size=fontsize) + c = cents[i] if hex else (cents[i, 1] + 0.5, cents[-(i + 1), 0] + 0.5) + ax.annotate(txt, c, va="center", ha="center", size=fontsize) def show(self, som, anotate=True, onlyzeros=False, labelsize=7, cmap="jet", logaritmic = False): + org_w = self.width + org_h = self.height (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, axis_num) = self._calculate_figure_params(som, 1, 1) + self.width /= (self.width/org_w) if self.width > self.height else (self.height/org_h) + self.height /= (self.width / org_w) if self.width > self.height else (self.height / org_h) - self.prepare() - ax = plt.gca() counts = Counter(som._bmu[0]) counts = [counts.get(x, 0) for x in range(som.codebook.mapsize[0] * som.codebook.mapsize[1])] mp = np.array(counts).reshape(som.codebook.mapsize[0], @@ -39,16 +45,25 @@ def show(self, som, anotate=True, onlyzeros=False, labelsize=7, cmap="jet", loga msz = som.codebook.mapsize cents = som.bmu_ind_to_xy(np.arange(0, msz[0] * msz[1])) + self.prepare() - if anotate: - self._set_labels(cents, ax, counts, onlyzeros, labelsize) + if som.codebook.lattice == "rect": + ax = plt.gca() + if anotate: + self._set_labels(cents, ax, counts, onlyzeros, labelsize) - pl = plt.pcolor(mp[::-1], norm=norm, cmap=cmap) + pl = plt.pcolor(mp[::-1], norm=norm, cmap=cmap) - plt.axis([0, som.codebook.mapsize[1], 0, som.codebook.mapsize[0]]) - ax.set_yticklabels([]) - ax.set_xticklabels([]) - plt.colorbar(pl) + plt.axis([0, som.codebook.mapsize[1], 0, som.codebook.mapsize[0]]) + ax.set_yticklabels([]) + ax.set_xticklabels([]) + plt.colorbar(pl) - plt.show() + #plt.show() + elif som.codebook.lattice == "hexa": + ax, cents = plot_hex_map(mp[::-1], colormap=cmap, fig=self._fig) + if anotate: + self._set_labels(cents, ax, reversed(counts), onlyzeros, labelsize, hex=True) + #plt.show() + #return ax, cents diff --git a/sompy/visualization/hitmap.py b/sompy/visualization/hitmap.py index c0dd482..6227ff3 100644 --- a/sompy/visualization/hitmap.py +++ b/sompy/visualization/hitmap.py @@ -1,37 +1,57 @@ from .view import MatplotView +from sompy.visualization.plot_tools import plot_hex_map from matplotlib import pyplot as plt import numpy as np +from .mapview import MapView -class HitMapView(MatplotView): - def _set_labels(self, cents, ax, labels): - for i, txt in enumerate(labels): - ax.annotate(txt, (cents[i, 1], cents[i, 0]), size=10, va="center") - def show(self, som, data=None): +class HitMapView(MapView): + def _set_labels(self, cents, ax, labels, onlyzeros, fontsize, hex=False): + for i, txt in enumerate(labels): + if onlyzeros == True: + if txt > 0: + txt = "" + c = cents[i] if hex else (cents[i, 1] + 0.5, cents[-(i + 1), 0] + 0.5) + ax.annotate(txt, c, va="center", ha="center", size=fontsize) + + def show(self, som, data=None, anotate=True, onlyzeros=False, labelsize=7, cmap="jet"): + org_w = self.width + org_h = self.height + (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, + axis_num) = self._calculate_figure_params(som, 1, 1) + self.width /= (self.width / org_w) if self.width > self.height else (self.height / org_h) + self.height /= (self.width / org_w) if self.width > self.height else (self.height / org_h) try: - codebook = getattr(som, 'cluster_labels') + clusters = getattr(som, 'cluster_labels') except: - codebook = som.cluster() + clusters = som.cluster() # codebook = getattr(som, 'cluster_labels', som.cluster()) msz = som.codebook.mapsize self.prepare() - ax = self._fig.add_subplot(111) - - if data: - proj = som.project_data(data) - cents = som.bmu_ind_to_xy(proj) - self._set_labels(cents, ax, codebook[proj]) - - else: - cents = som.bmu_ind_to_xy(np.arange(0, msz[0]*msz[1])) - self._set_labels(cents, ax, codebook) - - plt.imshow(codebook.reshape(msz[0], msz[1])[::], alpha=.5) - plt.show() - - return cents + if som.codebook.lattice == "rect": + ax = self._fig.add_subplot(111) + + if data: + proj = som.project_data(data) + cents = som.bmu_ind_to_xy(proj) + if anotate: + # TODO: Fix position of the labels + self._set_labels(cents, ax, clusters[proj], onlyzeros, labelsize, hex=False) + + else: + cents = som.bmu_ind_to_xy(np.arange(0, msz[0]*msz[1])) + if anotate: + # TODO: Fix position of the labels + self._set_labels(cents, ax, clusters, onlyzeros, labelsize, hex=False) + + plt.imshow(clusters.reshape(msz[0], msz[1])[::], alpha=.5) + + elif som.codebook.lattice == "hexa": + ax, cents = plot_hex_map(np.flip(clusters.reshape(msz[0], msz[1])[::], axis=1), fig=self._fig, colormap=cmap, colorbar=False) + if anotate: + self._set_labels(cents, ax, clusters, onlyzeros, labelsize, hex=True) \ No newline at end of file diff --git a/sompy/visualization/mapview.py b/sompy/visualization/mapview.py index b46acb2..1dd5485 100644 --- a/sompy/visualization/mapview.py +++ b/sompy/visualization/mapview.py @@ -1,8 +1,10 @@ +from matplotlib import colors import matplotlib + +from sompy.visualization.plot_tools import plot_hex_map from .view import MatplotView from matplotlib import pyplot as plt import numpy as np -#import ipdb class MapView(MatplotView): @@ -62,12 +64,12 @@ def _calculate_figure_params(self, som, which_dim, col_sz): class View2D(MapView): def show(self, som, what='codebook', which_dim='all', cmap=None, - col_sz=None, desnormalize=False): + col_sz=None, denormalize=False): (self.width, self.height, indtoshow, no_row_in_plot, no_col_in_plot, axis_num) = self._calculate_figure_params(som, which_dim, col_sz) self.prepare() - if not desnormalize: + if not denormalize: codebook = som.codebook.matrix else: codebook = som._normalizer.denormalize_by(som.data_raw, som.codebook.matrix) @@ -79,30 +81,32 @@ def show(self, som, what='codebook', which_dim='all', cmap=None, elif type(which_dim) == list: names = som._component_names[0][which_dim] + if som.codebook.lattice=="rect": + while axis_num < len(indtoshow): + axis_num += 1 + ax = plt.subplot(no_row_in_plot, no_col_in_plot, axis_num) + ind = int(indtoshow[axis_num-1]) - while axis_num < len(indtoshow): - axis_num += 1 - ax = plt.subplot(no_row_in_plot, no_col_in_plot, axis_num) - ind = int(indtoshow[axis_num-1]) + min_color_scale = np.mean(codebook[:, ind].flatten()) - 1 * np.std(codebook[:, ind].flatten()) + max_color_scale = np.mean(codebook[:, ind].flatten()) + 1 * np.std(codebook[:, ind].flatten()) + min_color_scale = min_color_scale if min_color_scale >= min(codebook[:, ind].flatten()) else \ + min(codebook[:, ind].flatten()) + max_color_scale = max_color_scale if max_color_scale <= max(codebook[:, ind].flatten()) else \ + max(codebook[:, ind].flatten()) + norm = matplotlib.colors.Normalize(vmin=min_color_scale, vmax=max_color_scale, clip=True) - min_color_scale = np.mean(codebook[:, ind].flatten()) - 1 * np.std(codebook[:, ind].flatten()) - max_color_scale = np.mean(codebook[:, ind].flatten()) + 1 * np.std(codebook[:, ind].flatten()) - min_color_scale = min_color_scale if min_color_scale >= min(codebook[:, ind].flatten()) else \ - min(codebook[:, ind].flatten()) - max_color_scale = max_color_scale if max_color_scale <= max(codebook[:, ind].flatten()) else \ - max(codebook[:, ind].flatten()) - norm = matplotlib.colors.Normalize(vmin=min_color_scale, vmax=max_color_scale, clip=True) - - mp = codebook[:, ind].reshape(som.codebook.mapsize[0], - som.codebook.mapsize[1]) - pl = plt.pcolor(mp[::-1], norm=norm) - plt.axis([0, som.codebook.mapsize[1], 0, som.codebook.mapsize[0]]) - plt.title(names[axis_num - 1]) - ax.set_yticklabels([]) - ax.set_xticklabels([]) - plt.colorbar(pl) + mp = codebook[:, ind].reshape(som.codebook.mapsize[0], + som.codebook.mapsize[1]) + pl = plt.pcolor(mp[::-1], norm=norm) + plt.axis([0, som.codebook.mapsize[1], 0, som.codebook.mapsize[0]]) + plt.title(names[axis_num - 1]) + ax.set_yticklabels([]) + ax.set_xticklabels([]) + plt.colorbar(pl) + elif som.codebook.lattice=="hexa": + plot_hex_map(codebook.reshape(som.codebook.mapsize + [som.codebook.matrix.shape[-1]]), titles=names, + shape=[no_row_in_plot, no_col_in_plot], colormap=cmap, fig=self._fig) - #plt.show() class View2DPacked(MapView): @@ -185,3 +189,5 @@ def show(self, som, what='codebook', which_dim='all', cmap=None, plt.plot(mp, '-k', linewidth=0.8) #plt.show() + + diff --git a/sompy/visualization/plot_tools.py b/sompy/visualization/plot_tools.py new file mode 100644 index 0000000..b610a7d --- /dev/null +++ b/sompy/visualization/plot_tools.py @@ -0,0 +1,82 @@ +import math + +import numpy as np +from matplotlib import cm, pyplot as plt +from matplotlib.collections import RegularPolyCollection +from mpl_toolkits.axes_grid1 import make_axes_locatable + + +def plot_hex_map(d_matrix, titles=[], colormap=cm.gray, shape=[1, 1], comp_width=5, hex_shrink=1.0, fig=None, + colorbar=True): + """ + Plot hexagon map where each neuron is represented by a hexagon. The hexagon + color is given by the distance between the neurons (D-Matrix) + + Args: + - grid: Grid dictionary (keys: centers, x, y ), + - d_matrix: array contaning the distances between each neuron + - w: width of the map in inches + - title: map title + + Returns the Matplotlib SubAxis instance + """ + + d_matrix = np.flip(d_matrix, axis=0) + + def create_grid_coordinates(x, y): + coordinates = [x for row in -1 * np.array(list(range(x))) for x in + list(zip(np.arange(((row) % 2) * 0.5, y + ((row) % 2) * 0.5), [0.8660254 * (row)] * y))] + return (np.array(list(reversed(coordinates))), x, y) + + if d_matrix.ndim < 3: + d_matrix = np.expand_dims(d_matrix, 2) + + if len(titles) != d_matrix.shape[2]: + titles = [""] * d_matrix.shape[2] + + n_centers, x, y = create_grid_coordinates(*d_matrix.shape[:2]) + + # Size of figure in inches + if fig is None: + xinch, yinch = comp_width * shape[1], comp_width * (x / y) * shape[0] + fig = plt.figure(figsize=(xinch, yinch), dpi=72.) + + for comp, title in zip(range(d_matrix.shape[2]), titles): + ax = fig.add_subplot(shape[0], shape[1], comp + 1, aspect='equal') + + # Get pixel size between two data points + xpoints = n_centers[:, 0] + ypoints = n_centers[:, 1] + ax.scatter(xpoints, ypoints, s=0.0, marker='s') + ax.axis([min(xpoints) - 1., max(xpoints) + 1., + min(ypoints) - 1., max(ypoints) + 1.]) + xy_pixels = ax.transData.transform(np.vstack([xpoints, ypoints]).T) + xpix, ypix = xy_pixels.T + + # discover radius and hexagon + apothem = hex_shrink * (xpix[1] - xpix[0]) / math.sqrt(3) + area_inner_circle = math.pi * (apothem ** 2) + dm = d_matrix[:, :, comp].reshape(np.multiply(*d_matrix.shape[:2])) + collection_bg = RegularPolyCollection( + numsides=6, # a hexagon + rotation=0, + sizes=(area_inner_circle,), + array=dm, + cmap=colormap, + offsets=n_centers, + transOffset=ax.transData, + ) + ax.add_collection(collection_bg, autolim=True) + + ax.axis('off') + ax.autoscale_view() + ax.set_title(title)#, fontdict={"fontsize": 3 * comp_width}) + divider = make_axes_locatable(ax) + cax = divider.append_axes("right", size="5%", pad=0.05) + cbar = plt.colorbar(collection_bg, cax=cax) + if not colorbar: + cbar.remove() + + #cbar.ax.tick_params(labelsize=3 * comp_width) + + return ax, list(reversed(n_centers)) \ No newline at end of file diff --git a/sompy/visualization/view.py b/sompy/visualization/view.py index c618a23..7763506 100644 --- a/sompy/visualization/view.py +++ b/sompy/visualization/view.py @@ -42,6 +42,7 @@ def _close_fig(self): def prepare(self, *args, **kwargs): self._close_fig() self._fig = plt.figure(figsize=(self.width, self.height)) + self._fig.patch.set_facecolor('white') plt.title(self.title) plt.axis('off') plt.rc('font', **{'size': self.text_size})