74c014b048f6e4df6780bb767702a852b1beba1c,pynets/dmri/estimation.py,,create_anisopowermap,#Any#Any#Any#,60

Before Change

    print("Generating anisotropic power map to use for registrations...")
    nodif_B0_img = nib.load(B0_mask)

    dwi_data = np.asarray(img.dataobj)
    for b0 in sorted(list(np.where(gtab.b0s_mask==True)[0]), reverse=True):
        dwi_data = np.delete(dwi_data, b0, 3)

    anisomap = anisotropic_power(sf_to_sh(dwi_data, gtab_hemisphere, sh_order=2))
    anisomap[np.isnan(anisomap)] = 0
    masked_data = anisomap * np.asarray(nodif_B0_img.dataobj).astype("bool")
    anisopwr_path = "%s%s" % (os.path.dirname(B0_mask), "/aniso_power.nii.gz")
    img = nib.Nifti1Image(masked_data.astype(np.float32), aff)
    img.to_filename(anisopwr_path)
    nodif_B0_img.uncache()
    del anisomap

    return anisopwr_path, B0_mask, gtab_file, dwi_file

After Change

        print("Generating anisotropic power map to use for registrations...")
        nodif_B0_img = nib.load(B0_mask)

        dwi_data = np.asarray(img.dataobj)
        for b0 in sorted(list(np.where(gtab.b0s_mask==True)[0]), reverse=True):
            dwi_data = np.delete(dwi_data, b0, 3)

        anisomap = anisotropic_power(sf_to_sh(dwi_data, gtab_hemisphere, sh_order=2))
        anisomap[np.isnan(anisomap)] = 0
        masked_data = anisomap * np.asarray(nodif_B0_img.dataobj).astype("bool")
        img = nib.Nifti1Image(masked_data.astype(np.float32), aff)
        img.to_filename(anisopwr_path)
        nodif_B0_img.uncache()
        del anisomap

    return anisopwr_path, B0_mask, gtab_file, dwi_file

Instances