-
Notifications
You must be signed in to change notification settings - Fork 82
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
1 parent
6d9c6da
commit 47fee8d
Showing
2 changed files
with
188 additions
and
165 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,188 @@ | ||
| from pathlib import Path | ||
| from typing import Optional, Tuple, Union | ||
| from unittest.mock import patch | ||
|
|
||
| import nibabel as nib | ||
| import numpy as np | ||
| import pytest | ||
| from numpy.testing import assert_array_equal | ||
|
|
||
| from clinica.pipelines.utils import ( | ||
| AntsRegistrationSynQuickTransformType, | ||
| AntsRegistrationTransformType, | ||
| ) | ||
|
|
||
|
|
||
| def n4biasfieldcorrection_mock( | ||
| input_image: Path, | ||
| bspline_fitting_distance: int, | ||
| save_bias: bool = False, | ||
| verbose: bool = False, | ||
| ): | ||
| """The mock simply returns the input image without any processing.""" | ||
| return nib.load(input_image) | ||
|
|
||
|
|
||
| def test_run_n4biasfieldcorrection_no_bias_saving(tmp_path): | ||
| from clinica.pipelines.utils import run_n4biasfieldcorrection | ||
|
|
||
| data = np.random.random((10, 10, 10)) | ||
| nib.save(nib.Nifti1Image(data, np.eye(4)), tmp_path / "test.nii.gz") | ||
| output_dir = tmp_path / "out" | ||
| output_dir.mkdir() | ||
|
|
||
| with patch("ants.image_write", wraps=nib.save) as image_write_mock: | ||
| with patch( | ||
| "clinica.pipelines.utils._call_n4_bias_field_correction", | ||
| wraps=n4biasfieldcorrection_mock, | ||
| ) as ants_bias_correction_mock: | ||
| bias_corrected_image = run_n4biasfieldcorrection( | ||
| tmp_path / "test.nii.gz", | ||
| bspline_fitting_distance=300, | ||
| output_prefix="sub-01_ses-M000", | ||
| output_dir=output_dir, | ||
| ) | ||
| image_write_mock.assert_called_once() | ||
| ants_bias_correction_mock.assert_called_once_with( | ||
| tmp_path / "test.nii.gz", | ||
| 300, | ||
| save_bias=False, | ||
| verbose=False, | ||
| ) | ||
| # Verify that the bias corrected image exists | ||
| # If all went well, it will be the same as the input image because of the mocks. | ||
| assert [f.name for f in output_dir.iterdir()] == [ | ||
| "sub-01_ses-M000_bias_corrected_image.nii.gz" | ||
| ] | ||
| assert bias_corrected_image.exists() | ||
| bias_corrected_nifti = nib.load(bias_corrected_image) | ||
| assert_array_equal(bias_corrected_nifti.affine, np.eye(4)) | ||
| assert_array_equal(bias_corrected_nifti.get_fdata(), data) | ||
|
|
||
|
|
||
| def test_run_n4biasfieldcorrection(tmp_path): | ||
| from clinica.pipelines.utils import run_n4biasfieldcorrection | ||
|
|
||
| data = np.random.random((10, 10, 10)) | ||
| nib.save(nib.Nifti1Image(data, np.eye(4)), tmp_path / "test.nii.gz") | ||
| output_dir = tmp_path / "out" | ||
| output_dir.mkdir() | ||
|
|
||
| with patch("ants.image_write", wraps=nib.save) as image_write_mock: | ||
| with patch( | ||
| "clinica.pipelines.utils._call_n4_bias_field_correction", | ||
| wraps=n4biasfieldcorrection_mock, | ||
| ) as ants_bias_correction_mock: | ||
| bias_corrected_image = run_n4biasfieldcorrection( | ||
| tmp_path / "test.nii.gz", | ||
| bspline_fitting_distance=300, | ||
| output_prefix="sub-01_ses-M000", | ||
| output_dir=output_dir, | ||
| save_bias=True, | ||
| verbose=True, | ||
| ) | ||
| image_write_mock.assert_called() | ||
| ants_bias_correction_mock.assert_called_with( | ||
| tmp_path / "test.nii.gz", | ||
| 300, | ||
| save_bias=True, | ||
| verbose=True, | ||
| ) | ||
| assert set([f.name for f in output_dir.iterdir()]) == { | ||
| "sub-01_ses-M000_bias_corrected_image.nii.gz", | ||
| "sub-01_ses-M000_bias_image.nii.gz", | ||
| } | ||
| assert bias_corrected_image.exists() | ||
| bias_corrected_nifti = nib.load(bias_corrected_image) | ||
| assert_array_equal(bias_corrected_nifti.affine, np.eye(4)) | ||
| assert_array_equal(bias_corrected_nifti.get_fdata(), data) | ||
|
|
||
|
|
||
| def generate_fake_fixed_and_moving_images(folder: Path): | ||
| data = np.random.random((10, 10, 10)) | ||
| nib.save(nib.Nifti1Image(data, np.eye(4)), folder / "fixed.nii.gz") | ||
| nib.save(nib.Nifti1Image(data, np.eye(4)), folder / "moving.nii.gz") | ||
|
|
||
|
|
||
| def test_run_ants_registration_synquick_error(tmp_path, mocker): | ||
| import re | ||
|
|
||
| from clinica.pipelines.utils import run_ants_registration_synquick | ||
|
|
||
| generate_fake_fixed_and_moving_images(tmp_path) | ||
| mocker.patch( | ||
| "clinica.pipelines.utils._call_ants_registration", | ||
| return_value={}, | ||
| ) | ||
| with pytest.raises( | ||
| RuntimeError, | ||
| match=re.escape( | ||
| "Something went wrong when calling antsRegistration with the following parameters :\n" | ||
| f"- fixed_image = {tmp_path / 'fixed.nii.gz'}\n" | ||
| f"- moving_image = {tmp_path / 'moving.nii.gz'}\n" | ||
| f"- random_seed = 0\n" | ||
| f"- type_of_transformation='antsRegistrationSyN[a]'\n" | ||
| ), | ||
| ): | ||
| run_ants_registration_synquick( | ||
| tmp_path / "fixed.nii.gz", | ||
| tmp_path / "moving.nii.gz", | ||
| random_seed=0, | ||
| transform_type=AntsRegistrationSynQuickTransformType.AFFINE, | ||
| ) | ||
|
|
||
|
|
||
| def ants_registration_mock( | ||
| fixed_image: Path, | ||
| moving_image: Path, | ||
| random_seed: int, | ||
| transform_type: Union[ | ||
| AntsRegistrationTransformType, AntsRegistrationSynQuickTransformType | ||
| ], | ||
| verbose: bool = False, | ||
| shrink_factors: Optional[Tuple[int, ...]] = None, | ||
| smoothing_sigmas: Optional[Tuple[int, ...]] = None, | ||
| number_of_iterations: Optional[Tuple[int, ...]] = None, | ||
| ) -> dict: | ||
| workdir = fixed_image.parent / "workdir" | ||
| workdir.mkdir() | ||
| mocked_transform = workdir / "transform.mat" | ||
| mocked_transform.touch() | ||
| return { | ||
| "warpedmovout": nib.load(fixed_image), | ||
| "fwdtransforms": ["fooo.txt", mocked_transform], | ||
| "invtransforms": [mocked_transform], | ||
| "foo": "bar", | ||
| } | ||
|
|
||
|
|
||
| def test_run_ants_registration_synquick(tmp_path): | ||
| from clinica.pipelines.utils import run_ants_registration_synquick | ||
|
|
||
| output_dir = tmp_path / "out" | ||
| output_dir.mkdir() | ||
| generate_fake_fixed_and_moving_images(tmp_path) | ||
|
|
||
| with patch( | ||
| "clinica.pipelines.utils._call_ants_registration", | ||
| wraps=ants_registration_mock, | ||
| ) as mock1: | ||
| with patch("ants.image_write", wraps=nib.save) as mock2: | ||
| run_ants_registration_synquick( | ||
| tmp_path / "fixed.nii.gz", | ||
| tmp_path / "moving.nii.gz", | ||
| random_seed=12, | ||
| transform_type=AntsRegistrationSynQuickTransformType.AFFINE, | ||
| output_dir=output_dir, | ||
| ) | ||
| mock1.assert_called_once_with( | ||
| tmp_path / "fixed.nii.gz", | ||
| tmp_path / "moving.nii.gz", | ||
| 12, | ||
| AntsRegistrationSynQuickTransformType.AFFINE, | ||
| verbose=False, | ||
| shrink_factors=None, | ||
| smoothing_sigmas=None, | ||
| number_of_iterations=None, | ||
| ) | ||
| mock2.assert_called_once() |