def assert_spm_resampling_close(from_img, our_resampled, spm_resampled):
""" Assert our resampling is close to SPM's, allowing for edge effects
"""
# To allow for differences in the way SPM and scipy.ndimage handle off-edge
# interpolation, mask out voxels off edge
to_img_shape = spm_resampled.shape
to_img_affine = spm_resampled.affine
to_vox_coords = np.indices(to_img_shape).transpose((1, 2, 3, 0))
# Coordinates of to_img mapped to from_img
to_to_from = npl.inv(from_img.affine).dot(to_img_affine)
resamp_coords = apply_affine(to_to_from, to_vox_coords)
# Places where SPM may not return default value but scipy.ndimage will (SPM
# does not return zeros <0.05 from image edges).
# See: https://github.com/nipy/nibabel/pull/255#issuecomment-186774173
outside_vol = np.any((resamp_coords < 0) |
(np.subtract(resamp_coords, from_img.shape) > -1),
axis=-1)
spm_res = np.where(outside_vol, np.nan, np.array(spm_resampled.dataobj))
assert_allclose_safely(our_resampled.dataobj, spm_res)
assert_almost_equal(our_resampled.affine, spm_resampled.affine, 5)
def assert_spm_resampling_close(from_img, our_resampled, spm_resampled):
""" Assert our resampling is close to SPM's, allowing for edge effects
"""
# To allow for differences in the way SPM and scipy.ndimage handle off-edge
# interpolation, mask out voxels off edge
to_img_shape = spm_resampled.shape
to_img_affine = spm_resampled.affine
to_vox_coords = np.indices(to_img_shape).transpose((1, 2, 3, 0))
# Coordinates of to_img mapped to from_img
to_to_from = npl.inv(from_img.affine).dot(to_img_affine)
resamp_coords = apply_affine(to_to_from, to_vox_coords)
# Places where SPM may not return default value but scipy.ndimage will (SPM
# does not return zeros <0.05 from image edges).
# See: https://github.com/nipy/nibabel/pull/255#issuecomment-186774173
outside_vol = np.any((resamp_coords < 0) |
(np.subtract(resamp_coords, from_img.shape) > -1),
axis=-1)
spm_res = np.where(outside_vol, np.nan, np.array(spm_resampled.dataobj))
assert_allclose_safely(our_resampled.dataobj, spm_res)
assert_almost_equal(our_resampled.affine, spm_resampled.affine, 5)