From 6750f1562b4fdb62e99d90243ff58c1c0b52c700 Mon Sep 17 00:00:00 2001 From: steve Date: Sat, 21 Dec 2019 06:11:03 +0100 Subject: [PATCH 1/2] removed all useso f numpy_mmap --- examples/dmri_camino_dti.py | 8 ++----- examples/dmri_connectivity.py | 9 +++----- examples/fmri_ants_openfmri.py | 1 - examples/fmri_fsl.py | 3 +-- examples/fmri_spm_auditory.py | 3 +-- examples/fmri_spm_face.py | 3 +-- examples/rsfmri_vol_surface_preprocessing.py | 21 +++++++------------ .../rsfmri_vol_surface_preprocessing_nipy.py | 13 ++++++------ nipype/algorithms/confounds.py | 9 ++++---- nipype/algorithms/icc.py | 3 +-- nipype/algorithms/misc.py | 9 ++++---- nipype/algorithms/modelgen.py | 7 +++---- nipype/algorithms/rapidart.py | 7 +++---- nipype/algorithms/tests/test_misc.py | 5 ++--- .../algorithms/tests/test_normalize_tpms.py | 1 - nipype/algorithms/tests/test_splitmerge.py | 1 - nipype/interfaces/dcmstack.py | 3 +-- nipype/interfaces/dipy/preprocess.py | 5 ++--- .../interfaces/freesurfer/tests/test_model.py | 1 - nipype/interfaces/fsl/epi.py | 3 +-- nipype/interfaces/mrtrix/convert.py | 6 ++---- nipype/interfaces/spm/base.py | 6 +++--- nipype/utils/__init__.py | 1 - nipype/utils/config.py | 1 - 24 files changed, 48 insertions(+), 81 deletions(-) diff --git a/examples/dmri_camino_dti.py b/examples/dmri_camino_dti.py index eaf9b4ff95..9dc52f7d90 100755 --- a/examples/dmri_camino_dti.py +++ b/examples/dmri_camino_dti.py @@ -35,10 +35,9 @@ def get_vox_dims(volume): import nibabel as nb - from nipype.utils import NUMPY_MMAP if isinstance(volume, list): volume = volume[0] - nii = nb.load(volume, mmap=NUMPY_MMAP) + nii = nb.load(volume) hdr = nii.header voxdims = hdr.get_zooms() return [float(voxdims[0]), float(voxdims[1]), float(voxdims[2])] @@ -46,10 +45,8 @@ def get_vox_dims(volume): def get_data_dims(volume): import nibabel as nb - from nipype.utils import NUMPY_MMAP if isinstance(volume, list): volume = volume[0] - nii = nb.load(volume, mmap=NUMPY_MMAP) hdr = nii.header datadims = hdr.get_data_shape() return [int(datadims[0]), int(datadims[1]), int(datadims[2])] @@ -57,8 +54,7 @@ def get_data_dims(volume): def get_affine(volume): import nibabel as nb - from nipype.utils import NUMPY_MMAP - nii = nb.load(volume, mmap=NUMPY_MMAP) + nii = nb.load(volume) return nii.affine diff --git a/examples/dmri_connectivity.py b/examples/dmri_connectivity.py index fc5b51c362..e50bc25815 100755 --- a/examples/dmri_connectivity.py +++ b/examples/dmri_connectivity.py @@ -73,10 +73,9 @@ def get_vox_dims(volume): import nibabel as nb - from nipype.utils import NUMPY_MMAP if isinstance(volume, list): volume = volume[0] - nii = nb.load(volume, mmap=NUMPY_MMAP) + nii = nb.load(volume) hdr = nii.header voxdims = hdr.get_zooms() return [float(voxdims[0]), float(voxdims[1]), float(voxdims[2])] @@ -84,10 +83,9 @@ def get_vox_dims(volume): def get_data_dims(volume): import nibabel as nb - from nipype.utils import NUMPY_MMAP if isinstance(volume, list): volume = volume[0] - nii = nb.load(volume, mmap=NUMPY_MMAP) + nii = nb.load(volume) hdr = nii.header datadims = hdr.get_data_shape() return [int(datadims[0]), int(datadims[1]), int(datadims[2])] @@ -95,8 +93,7 @@ def get_data_dims(volume): def get_affine(volume): import nibabel as nb - from nipype.utils import NUMPY_MMAP - nii = nb.load(volume, mmap=NUMPY_MMAP) + nii = nb.load(volume) return nii.affine diff --git a/examples/fmri_ants_openfmri.py b/examples/fmri_ants_openfmri.py index 35684cf595..73aa2d66b7 100755 --- a/examples/fmri_ants_openfmri.py +++ b/examples/fmri_ants_openfmri.py @@ -41,7 +41,6 @@ from nipype.workflows.fmri.fsl import (create_featreg_preproc, create_modelfit_workflow, create_fixed_effects_flow) -from nipype.utils import NUMPY_MMAP config.enable_provenance() version = 0 diff --git a/examples/fmri_fsl.py b/examples/fmri_fsl.py index 9d4ab71423..13ce9fa8da 100755 --- a/examples/fmri_fsl.py +++ b/examples/fmri_fsl.py @@ -101,11 +101,10 @@ def pickfirst(files): def getmiddlevolume(func): from nibabel import load - from nipype.utils import NUMPY_MMAP funcfile = func if isinstance(func, list): funcfile = func[0] - _, _, _, timepoints = load(funcfile, mmap=NUMPY_MMAP).shape + _, _, _, timepoints = load(funcfile).shape return int(timepoints / 2) - 1 diff --git a/examples/fmri_spm_auditory.py b/examples/fmri_spm_auditory.py index e4c690421a..29a59726a0 100755 --- a/examples/fmri_spm_auditory.py +++ b/examples/fmri_spm_auditory.py @@ -107,10 +107,9 @@ def get_vox_dims(volume): import nibabel as nb - from nipype.utils import NUMPY_MMAP if isinstance(volume, list): volume = volume[0] - nii = nb.load(volume, mmap=NUMPY_MMAP) + nii = nb.load(volume) hdr = nii.header voxdims = hdr.get_zooms() return [float(voxdims[0]), float(voxdims[1]), float(voxdims[2])] diff --git a/examples/fmri_spm_face.py b/examples/fmri_spm_face.py index 5644398d54..a60b1d32c7 100755 --- a/examples/fmri_spm_face.py +++ b/examples/fmri_spm_face.py @@ -101,10 +101,9 @@ def get_vox_dims(volume): import nibabel as nb - from nipype.utils import NUMPY_MMAP if isinstance(volume, list): volume = volume[0] - nii = nb.load(volume, mmap=NUMPY_MMAP) + nii = nb.load(volume) hdr = nii.header voxdims = hdr.get_zooms() return [float(voxdims[0]), float(voxdims[1]), float(voxdims[2])] diff --git a/examples/rsfmri_vol_surface_preprocessing.py b/examples/rsfmri_vol_surface_preprocessing.py index 20b150b149..43e9d3d089 100644 --- a/examples/rsfmri_vol_surface_preprocessing.py +++ b/examples/rsfmri_vol_surface_preprocessing.py @@ -117,10 +117,9 @@ def median(in_files): """ import numpy as np import nibabel as nb - from nipype.utils import NUMPY_MMAP average = None for idx, filename in enumerate(filename_to_list(in_files)): - img = nb.load(filename, mmap=NUMPY_MMAP) + img = nb.load(filename) data = np.median(img.get_data(), axis=3) if average is None: average = data @@ -146,12 +145,11 @@ def bandpass_filter(files, lowpass_freq, highpass_freq, fs): from nipype.utils.filemanip import split_filename, list_to_filename import numpy as np import nibabel as nb - from nipype.utils import NUMPY_MMAP out_files = [] for filename in filename_to_list(files): path, name, ext = split_filename(filename) out_file = os.path.join(os.getcwd(), name + '_bp' + ext) - img = nb.load(filename, mmap=NUMPY_MMAP) + img = nb.load(filename) timepoints = img.shape[-1] F = np.zeros((timepoints)) lowidx = int(timepoints / 2) + 1 @@ -264,12 +262,11 @@ def extract_noise_components(realigned_file, from scipy.linalg.decomp_svd import svd import numpy as np import nibabel as nb - from nipype.utils import NUMPY_MMAP import os - imgseries = nb.load(realigned_file, mmap=NUMPY_MMAP) + imgseries = nb.load(realigned_file) components = None for filename in filename_to_list(mask_file): - mask = nb.load(filename, mmap=NUMPY_MMAP).get_data() + mask = nb.load(filename).get_data() if len(np.nonzero(mask > 0)[0]) == 0: continue voxel_timecourses = imgseries.get_data()[mask > 0] @@ -334,11 +331,10 @@ def extract_subrois(timeseries_file, label_file, indices): """ from nipype.utils.filemanip import split_filename import nibabel as nb - from nipype.utils import NUMPY_MMAP import os - img = nb.load(timeseries_file, mmap=NUMPY_MMAP) + img = nb.load(timeseries_file) data = img.get_data() - roiimg = nb.load(label_file, mmap=NUMPY_MMAP) + roiimg = nb.load(label_file) rois = roiimg.get_data() prefix = split_filename(timeseries_file)[1] out_ts_file = os.path.join(os.getcwd(), '%s_subcortical_ts.txt' % prefix) @@ -359,9 +355,8 @@ def combine_hemi(left, right): """ import os import numpy as np - from nipype.utils import NUMPY_MMAP - lh_data = nb.load(left, mmap=NUMPY_MMAP).get_data() - rh_data = nb.load(right, mmap=NUMPY_MMAP).get_data() + lh_data = nb.load(left).get_data() + rh_data = nb.load(right).get_data() indices = np.vstack((1000000 + np.arange(0, lh_data.shape[0])[:, None], 2000000 + np.arange(0, rh_data.shape[0])[:, None])) diff --git a/examples/rsfmri_vol_surface_preprocessing_nipy.py b/examples/rsfmri_vol_surface_preprocessing_nipy.py index d3d9887cc6..2397a136e0 100644 --- a/examples/rsfmri_vol_surface_preprocessing_nipy.py +++ b/examples/rsfmri_vol_surface_preprocessing_nipy.py @@ -76,7 +76,6 @@ import numpy as np import scipy as sp import nibabel as nb -from nipype.utils.config import NUMPY_MMAP """ A list of modules and functions to import inside of nodes @@ -129,7 +128,7 @@ def median(in_files): """ average = None for idx, filename in enumerate(filename_to_list(in_files)): - img = nb.load(filename, mmap=NUMPY_MMAP) + img = nb.load(filename) data = np.median(img.get_data(), axis=3) if average is None: average = data @@ -156,7 +155,7 @@ def bandpass_filter(files, lowpass_freq, highpass_freq, fs): for filename in filename_to_list(files): path, name, ext = split_filename(filename) out_file = os.path.join(os.getcwd(), name + '_bp' + ext) - img = nb.load(filename, mmap=NUMPY_MMAP) + img = nb.load(filename) timepoints = img.shape[-1] F = np.zeros((timepoints)) lowidx = int(timepoints / 2) + 1 @@ -282,9 +281,9 @@ def extract_subrois(timeseries_file, label_file, indices): The first four columns are: freesurfer index, i, j, k positions in the label file """ - img = nb.load(timeseries_file, mmap=NUMPY_MMAP) + img = nb.load(timeseries_file) data = img.get_data() - roiimg = nb.load(label_file, mmap=NUMPY_MMAP) + roiimg = nb.load(label_file) rois = roiimg.get_data() prefix = split_filename(timeseries_file)[1] out_ts_file = os.path.join(os.getcwd(), '%s_subcortical_ts.txt' % prefix) @@ -303,8 +302,8 @@ def extract_subrois(timeseries_file, label_file, indices): def combine_hemi(left, right): """Combine left and right hemisphere time series into a single text file """ - lh_data = nb.load(left, mmap=NUMPY_MMAP).get_data() - rh_data = nb.load(right, mmap=NUMPY_MMAP).get_data() + lh_data = nb.load(left).get_data() + rh_data = nb.load(right).get_data() indices = np.vstack((1000000 + np.arange(0, lh_data.shape[0])[:, None], 2000000 + np.arange(0, rh_data.shape[0])[:, None])) diff --git a/nipype/algorithms/confounds.py b/nipype/algorithms/confounds.py index 3bbf4632f4..7c1dd4edae 100644 --- a/nipype/algorithms/confounds.py +++ b/nipype/algorithms/confounds.py @@ -26,7 +26,6 @@ OutputMultiPath, SimpleInterface, ) -from ..utils import NUMPY_MMAP from ..utils.misc import normalize_mc_params IFLOGGER = logging.getLogger("nipype.interface") @@ -599,7 +598,7 @@ def _run_interface(self, runtime): else 0 ) - imgseries = nb.load(self.inputs.realigned_file, mmap=NUMPY_MMAP) + imgseries = nb.load(self.inputs.realigned_file) if len(imgseries.shape) != 4: raise ValueError( @@ -917,7 +916,7 @@ class TSNR(BaseInterface): output_spec = TSNROutputSpec def _run_interface(self, runtime): - img = nb.load(self.inputs.in_file[0], mmap=NUMPY_MMAP) + img = nb.load(self.inputs.in_file[0]) header = img.header.copy() vollist = [nb.load(filename) for filename in self.inputs.in_file] data = np.concatenate( @@ -1263,7 +1262,7 @@ def combine_mask_files(mask_files, mask_method=None, mask_index=None): ) ) if mask_index < len(mask_files): - mask = nb.load(mask_files[mask_index], mmap=NUMPY_MMAP) + mask = nb.load(mask_files[mask_index]) return [mask] raise ValueError( ("mask_index {0} must be less than number of mask " "files {1}").format( @@ -1273,7 +1272,7 @@ def combine_mask_files(mask_files, mask_method=None, mask_index=None): masks = [] if mask_method == "none": for filename in mask_files: - masks.append(nb.load(filename, mmap=NUMPY_MMAP)) + masks.append(nb.load(filename)) return masks if mask_method == "union": diff --git a/nipype/algorithms/icc.py b/nipype/algorithms/icc.py index cd73caa0ca..568f71fa7e 100644 --- a/nipype/algorithms/icc.py +++ b/nipype/algorithms/icc.py @@ -11,7 +11,6 @@ traits, File, ) -from ..utils import NUMPY_MMAP class ICCInputSpec(BaseInterfaceInputSpec): @@ -46,7 +45,7 @@ def _run_interface(self, runtime): session_datas = [ [ - nb.load(fname, mmap=NUMPY_MMAP).get_fdata()[maskdata].reshape(-1, 1) + nb.load(fname).get_fdata()[maskdata].reshape(-1, 1) for fname in sessions ] for sessions in self.inputs.subjects_sessions diff --git a/nipype/algorithms/misc.py b/nipype/algorithms/misc.py index b472039075..bbb150ff4f 100644 --- a/nipype/algorithms/misc.py +++ b/nipype/algorithms/misc.py @@ -28,7 +28,6 @@ Undefined, ) from ..utils.filemanip import fname_presuffix, split_filename, ensure_list -from ..utils import NUMPY_MMAP from . import confounds @@ -210,7 +209,7 @@ def _gen_output_filename(self, name): def _run_interface(self, runtime): for fname in self.inputs.volumes: - img = nb.load(fname, mmap=NUMPY_MMAP) + img = nb.load(fname) affine = img.affine affine = np.dot(self.inputs.transformation_matrix, affine) @@ -1320,7 +1319,7 @@ def split_rois(in_file, mask=None, roishape=None): if roishape is None: roishape = (10, 10, 1) - im = nb.load(in_file, mmap=NUMPY_MMAP) + im = nb.load(in_file) imshape = im.shape dshape = imshape[:3] nvols = imshape[-1] @@ -1411,7 +1410,7 @@ def merge_rois(in_files, in_idxs, in_ref, dtype=None, out_file=None): except: pass - ref = nb.load(in_ref, mmap=NUMPY_MMAP) + ref = nb.load(in_ref) aff = ref.affine hdr = ref.header.copy() rsh = ref.shape @@ -1469,7 +1468,7 @@ def merge_rois(in_files, in_idxs, in_ref, dtype=None, out_file=None): data[idata] = cdata[0:nels] nb.Nifti1Image(data.reshape(rsh[:3]), aff, hdr).to_filename(fname) - imgs = [nb.load(im, mmap=NUMPY_MMAP) for im in nii] + imgs = [nb.load(im) for im in nii] allim = nb.concat_images(imgs) allim.to_filename(out_file) diff --git a/nipype/algorithms/modelgen.py b/nipype/algorithms/modelgen.py index 2457fe8d2f..e41b76637a 100644 --- a/nipype/algorithms/modelgen.py +++ b/nipype/algorithms/modelgen.py @@ -17,7 +17,6 @@ from nibabel import load import numpy as np -from ..utils import NUMPY_MMAP from ..interfaces.base import ( BaseInterface, TraitedSpec, @@ -474,7 +473,7 @@ def _generate_standard_design( for i, out in enumerate(outliers): numscans = 0 for f in ensure_list(sessinfo[i]["scans"]): - shape = load(f, mmap=NUMPY_MMAP).shape + shape = load(f).shape if len(shape) == 3 or shape[3] == 1: iflogger.warning( "You are using 3D instead of 4D " @@ -604,7 +603,7 @@ def _concatenate_info(self, infolist): if isinstance(f, list): numscans = len(f) elif isinstance(f, (str, bytes)): - img = load(f, mmap=NUMPY_MMAP) + img = load(f) numscans = img.shape[3] else: raise Exception("Functional input not specified correctly") @@ -984,7 +983,7 @@ def _generate_clustered_design(self, infolist): infoout[i].onsets = None infoout[i].durations = None if info.conditions: - img = load(self.inputs.functional_runs[i], mmap=NUMPY_MMAP) + img = load(self.inputs.functional_runs[i]) nscans = img.shape[3] reg, regnames = self._cond_to_regress(info, nscans) if hasattr(infoout[i], "regressors") and infoout[i].regressors: diff --git a/nipype/algorithms/rapidart.py b/nipype/algorithms/rapidart.py index a13d412481..b3cdbc8a23 100644 --- a/nipype/algorithms/rapidart.py +++ b/nipype/algorithms/rapidart.py @@ -18,7 +18,6 @@ from nibabel import load, funcs, Nifti1Image import numpy as np -from ..utils import NUMPY_MMAP from ..interfaces.base import ( BaseInterface, traits, @@ -485,12 +484,12 @@ def _detect_outliers_core(self, imgfile, motionfile, runidx, cwd=None): # read in functional image if isinstance(imgfile, (str, bytes)): - nim = load(imgfile, mmap=NUMPY_MMAP) + nim = load(imgfile) elif isinstance(imgfile, list): if len(imgfile) == 1: - nim = load(imgfile[0], mmap=NUMPY_MMAP) + nim = load(imgfile[0]) else: - images = [load(f, mmap=NUMPY_MMAP) for f in imgfile] + images = [load(f) for f in imgfile] nim = funcs.concat_images(images) # compute global intensity signal diff --git a/nipype/algorithms/tests/test_misc.py b/nipype/algorithms/tests/test_misc.py index 40aab24b2a..755527da49 100644 --- a/nipype/algorithms/tests/test_misc.py +++ b/nipype/algorithms/tests/test_misc.py @@ -9,7 +9,6 @@ from nipype.algorithms import misc from nipype.utils.filemanip import fname_presuffix from nipype.testing.fixtures import create_analyze_pair_file_in_directory -from nipype.utils import NUMPY_MMAP from nipype.testing import example_data @@ -32,7 +31,7 @@ def test_CreateNifti(create_analyze_pair_file_in_directory): result = create_nifti.run() assert os.path.exists(result.outputs.nifti_file) - assert nb.load(result.outputs.nifti_file, mmap=NUMPY_MMAP) + assert nb.load(result.outputs.nifti_file) def test_CalculateMedian(create_analyze_pair_file_in_directory): @@ -46,4 +45,4 @@ def test_CalculateMedian(create_analyze_pair_file_in_directory): eg = mean.run() assert os.path.exists(eg.outputs.median_files) - assert nb.load(eg.outputs.median_files, mmap=NUMPY_MMAP) + assert nb.load(eg.outputs.median_files) diff --git a/nipype/algorithms/tests/test_normalize_tpms.py b/nipype/algorithms/tests/test_normalize_tpms.py index c9b206361d..9541d5d882 100644 --- a/nipype/algorithms/tests/test_normalize_tpms.py +++ b/nipype/algorithms/tests/test_normalize_tpms.py @@ -13,7 +13,6 @@ import nipype.testing as nit from nipype.algorithms.misc import normalize_tpms -from nipype.utils import NUMPY_MMAP def test_normalize_tpms(tmpdir): diff --git a/nipype/algorithms/tests/test_splitmerge.py b/nipype/algorithms/tests/test_splitmerge.py index 5b06484e2c..3060ef0611 100644 --- a/nipype/algorithms/tests/test_splitmerge.py +++ b/nipype/algorithms/tests/test_splitmerge.py @@ -2,7 +2,6 @@ # -*- coding: utf-8 -*- from nipype.testing import example_data -from nipype.utils import NUMPY_MMAP def test_split_and_merge(tmpdir): diff --git a/nipype/interfaces/dcmstack.py b/nipype/interfaces/dcmstack.py index d7223468c8..716a148143 100644 --- a/nipype/interfaces/dcmstack.py +++ b/nipype/interfaces/dcmstack.py @@ -22,7 +22,6 @@ isdefined, Undefined, ) -from ..utils import NUMPY_MMAP have_dcmstack = True try: @@ -369,7 +368,7 @@ class MergeNifti(NiftiGeneratorBase): output_spec = MergeNiftiOutputSpec def _run_interface(self, runtime): - niis = [nb.load(fn, mmap=NUMPY_MMAP) for fn in self.inputs.in_files] + niis = [nb.load(fn) for fn in self.inputs.in_files] nws = [NiftiWrapper(nii, make_empty=True) for nii in niis] if self.inputs.sort_order: sort_order = self.inputs.sort_order diff --git a/nipype/interfaces/dipy/preprocess.py b/nipype/interfaces/dipy/preprocess.py index 3e89d1b88a..7e3c67b977 100644 --- a/nipype/interfaces/dipy/preprocess.py +++ b/nipype/interfaces/dipy/preprocess.py @@ -5,7 +5,6 @@ import numpy as np from distutils.version import LooseVersion -from ...utils import NUMPY_MMAP from ... import logging from ..base import traits, TraitedSpec, File, isdefined @@ -222,7 +221,7 @@ def resample_proxy(in_file, order=3, new_zooms=None, out_file=None): fext = fext2 + fext out_file = op.abspath("./%s_reslice%s" % (fname, fext)) - img = nb.load(in_file, mmap=NUMPY_MMAP) + img = nb.load(in_file) hdr = img.header.copy() data = img.get_fdata(dtype=np.float32) affine = img.affine @@ -262,7 +261,7 @@ def nlmeans_proxy(in_file, settings, snr=None, smask=None, nmask=None, out_file= fext = fext2 + fext out_file = op.abspath("./%s_denoise%s" % (fname, fext)) - img = nb.load(in_file, mmap=NUMPY_MMAP) + img = nb.load(in_file) hdr = img.header data = img.get_fdata() aff = img.affine diff --git a/nipype/interfaces/freesurfer/tests/test_model.py b/nipype/interfaces/freesurfer/tests/test_model.py index 8d30ebb5dc..73a2d1f5c6 100644 --- a/nipype/interfaces/freesurfer/tests/test_model.py +++ b/nipype/interfaces/freesurfer/tests/test_model.py @@ -8,7 +8,6 @@ import pytest -from nipype.utils import NUMPY_MMAP from nipype.interfaces.freesurfer import model, no_freesurfer import nipype.pipeline.engine as pe diff --git a/nipype/interfaces/fsl/epi.py b/nipype/interfaces/fsl/epi.py index eeab08371e..c5bb6f6ce1 100644 --- a/nipype/interfaces/fsl/epi.py +++ b/nipype/interfaces/fsl/epi.py @@ -11,7 +11,6 @@ import warnings from ...utils.filemanip import split_filename, fname_presuffix -from ...utils import NUMPY_MMAP from ..base import traits, TraitedSpec, InputMultiPath, File, isdefined from .base import FSLCommand, FSLCommandInputSpec, Info @@ -118,7 +117,7 @@ def _run_interface(self, runtime): if runtime.returncode == 0: out_file = self.inputs.out_fieldmap - im = nb.load(out_file, mmap=NUMPY_MMAP) + im = nb.load(out_file) dumb_img = nb.Nifti1Image(np.zeros(im.shape), im.affine, im.header) out_nii = nb.funcs.concat_images((im, dumb_img)) nb.save(out_nii, out_file) diff --git a/nipype/interfaces/mrtrix/convert.py b/nipype/interfaces/mrtrix/convert.py index b2314271c4..41b593d9a6 100644 --- a/nipype/interfaces/mrtrix/convert.py +++ b/nipype/interfaces/mrtrix/convert.py @@ -19,11 +19,10 @@ def get_vox_dims(volume): import nibabel as nb - from nipype.utils import NUMPY_MMAP if isinstance(volume, list): volume = volume[0] - nii = nb.load(volume, mmap=NUMPY_MMAP) + nii = nb.load(volume) hdr = nii.header voxdims = hdr.get_zooms() return [float(voxdims[0]), float(voxdims[1]), float(voxdims[2])] @@ -31,11 +30,10 @@ def get_vox_dims(volume): def get_data_dims(volume): import nibabel as nb - from nipype.utils import NUMPY_MMAP if isinstance(volume, list): volume = volume[0] - nii = nb.load(volume, mmap=NUMPY_MMAP) + nii = nb.load(volume) hdr = nii.header datadims = hdr.get_data_shape() return [int(datadims[0]), int(datadims[1]), int(datadims[2])] diff --git a/nipype/interfaces/spm/base.py b/nipype/interfaces/spm/base.py index a70e0ab166..f168ce3329 100644 --- a/nipype/interfaces/spm/base.py +++ b/nipype/interfaces/spm/base.py @@ -24,7 +24,7 @@ # Local imports from ... import logging -from ...utils import spm_docs as sd, NUMPY_MMAP +from ...utils import spm_docs as sd from ..base import ( BaseInterface, traits, @@ -50,7 +50,7 @@ def func_is_3d(in_file): if isinstance(in_file, list): return func_is_3d(in_file[0]) else: - img = load(in_file, mmap=NUMPY_MMAP) + img = load(in_file) shape = img.shape if len(shape) == 3 or (len(shape) == 4 and shape[3] == 1): return True @@ -78,7 +78,7 @@ def scans_for_fname(fname): for sno, f in enumerate(fname): scans[sno] = "%s,1" % f return scans - img = load(fname, mmap=NUMPY_MMAP) + img = load(fname) if len(img.shape) == 3: return np.array(("%s,1" % fname,), dtype=object) else: diff --git a/nipype/utils/__init__.py b/nipype/utils/__init__.py index 6508602eb8..a8ee27f54d 100644 --- a/nipype/utils/__init__.py +++ b/nipype/utils/__init__.py @@ -1,5 +1,4 @@ # -*- coding: utf-8 -*- -from .config import NUMPY_MMAP from .onetime import OneTimeProperty, setattr_on_read from .tmpdirs import TemporaryDirectory, InTemporaryDirectory diff --git a/nipype/utils/config.py b/nipype/utils/config.py index 999ee76307..10df588487 100644 --- a/nipype/utils/config.py +++ b/nipype/utils/config.py @@ -28,7 +28,6 @@ "filemanip_level": ("logging.utils_level", "1.0"), } -NUMPY_MMAP = LooseVersion(np.__version__) >= LooseVersion("1.12.0") DEFAULT_CONFIG_TPL = """\ [logging] From e4b18c6a14dd96e97f0c920acae95b9309ff5535 Mon Sep 17 00:00:00 2001 From: steve Date: Sat, 21 Dec 2019 23:56:49 +0100 Subject: [PATCH 2/2] corrected wrong deletion of line --- examples/dmri_camino_dti.py | 1 + 1 file changed, 1 insertion(+) diff --git a/examples/dmri_camino_dti.py b/examples/dmri_camino_dti.py index 9dc52f7d90..7928fd7cfa 100755 --- a/examples/dmri_camino_dti.py +++ b/examples/dmri_camino_dti.py @@ -47,6 +47,7 @@ def get_data_dims(volume): import nibabel as nb if isinstance(volume, list): volume = volume[0] + nii = nb.load(volume) hdr = nii.header datadims = hdr.get_data_shape() return [int(datadims[0]), int(datadims[1]), int(datadims[2])]