01d18e835815feedeac2fbeff8025cdd94128eaa,pynets/fmri/clustools.py,NilParcellate,create_clean_mask,#NilParcellate#,411

Before Change

        // Load clustering mask
        self._clust_mask_img = nib.load(self.clust_mask)
        self._mask_data = np.asarray(self._clust_mask_img.dataobj).astype("bool").astype("uint8")

        // Ensure mask does not inclue voxels outside of the brain
        self._masked_fmri_vol = np.asarray(self._func_img.dataobj)[:, :, :, 0]
        self._masked_fmri_vol = self._masked_fmri_vol.astype("bool")
        self._mask_data[~self._masked_fmri_vol] = 0
        del self._masked_fmri_vol
        self._clust_mask_corr = "%s%s%s%s" % (self._dir_path, "/", mask_name, ".nii")
        self._clust_mask_corr_img = nib.Nifti1Image(self._mask_data, affine=self._clust_mask_img.affine,
                                                    header=self._clust_mask_img.header)
        nib.save(self._clust_mask_corr_img, self._clust_mask_corr)
        self._clust_mask_img.uncache()
        del self._mask_data
        gc.collect()

        return self.atlas

After Change

                                                        threshold=1, connected=False)
        nib.save(self._clust_mask_corr_img, "%s%s%s%s" % (self._dir_path, "/", mask_name, ".nii"))

        func_vol_img.uncache()
        clust_mask_res_img.uncache()
        gc.collect()

        return self.atlas

Instances