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Merge pull request #390 from effigies/test/smoketest-workflows
TEST: Add smoke tests for main anatomical workflows
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‎smriprep/workflows/anatomical.py

Lines changed: 2 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -794,7 +794,7 @@ def init_anat_fit_wf(
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if skull_strip_mode == "auto":
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run_skull_strip = all(_is_skull_stripped(img) for img in t1w)
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else:
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run_skull_strip = {"force": True, "skip": False}
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run_skull_strip = {"force": True, "skip": False}[skull_strip_mode]
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# Brain extraction
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if run_skull_strip:
@@ -1155,9 +1155,7 @@ def init_anat_fit_wf(
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(surface_recon_wf, coreg_xfms, [('outputnode.fsnative2t1w_xfm', 'in2')]),
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(coreg_xfms, t2wtot1w_xfm, [('out', 'in_xfms')]),
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(t2w_template_wf, t2w_resample, [('outputnode.anat_ref', 'input_image')]),
1158-
(brain_extraction_wf, t2w_resample, [
1159-
(('outputnode.bias_corrected', _pop), 'reference_image'),
1160-
]),
1158+
(t1w_buffer, t2w_resample, [('T1w_preproc', 'reference_image')]),
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(t2wtot1w_xfm, t2w_resample, [('out_xfm', 'transforms')]),
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(inputnode, ds_t2w_preproc, [('t2w', 'source_file')]),
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(t2w_resample, ds_t2w_preproc, [('output_image', 'in_file')]),

‎smriprep/workflows/tests/test_anatomical.py

Lines changed: 222 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,222 @@
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from pathlib import Path
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import nibabel as nb
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import numpy as np
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import pytest
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from niworkflows.utils.spaces import SpatialReferences, Reference
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from niworkflows.utils.testing import generate_bids_skeleton
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from ..anatomical import init_anat_preproc_wf, init_anat_fit_wf
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BASE_LAYOUT = {
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"01": {
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"anat": [
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{"run": 1, "suffix": "T1w"},
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{"run": 2, "suffix": "T1w"},
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{"suffix": "T2w"},
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],
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"func": [
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{
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"task": "rest",
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"run": i,
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"suffix": "bold",
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"metadata": {"PhaseEncodingDirection": "j", "TotalReadoutTime": 0.6},
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}
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for i in range(1, 3)
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],
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"fmap": [
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{"suffix": "phasediff", "metadata": {"EchoTime1": 0.005, "EchoTime2": 0.007}},
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{"suffix": "magnitude1", "metadata": {"EchoTime": 0.005}},
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{
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"suffix": "epi",
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"direction": "PA",
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"metadata": {"PhaseEncodingDirection": "j", "TotalReadoutTime": 0.6},
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},
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{
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"suffix": "epi",
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"direction": "AP",
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"metadata": {"PhaseEncodingDirection": "j-", "TotalReadoutTime": 0.6},
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},
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],
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},
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}
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@pytest.fixture(scope="module", autouse=True)
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def quiet_logger():
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import logging
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logger = logging.getLogger("nipype.workflow")
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old_level = logger.getEffectiveLevel()
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logger.setLevel(logging.ERROR)
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yield
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logger.setLevel(old_level)
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@pytest.fixture(scope="module")
58+
def bids_root(tmp_path_factory):
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base = tmp_path_factory.mktemp("base")
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bids_dir = base / "bids"
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generate_bids_skeleton(bids_dir, BASE_LAYOUT)
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yield bids_dir
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@pytest.mark.parametrize("freesurfer", [True, False])
66+
@pytest.mark.parametrize("cifti_output", [False, "91k"])
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def test_init_anat_preproc_wf(
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bids_root: Path,
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tmp_path: Path,
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freesurfer: bool,
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cifti_output: bool,
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):
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output_dir = tmp_path / 'output'
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output_dir.mkdir()
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init_anat_preproc_wf(
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bids_root=str(bids_root),
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output_dir=str(output_dir),
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freesurfer=freesurfer,
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hires=False,
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longitudinal=False,
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msm_sulc=False,
83+
t1w=[str(bids_root / "sub-01" / "anat" / "sub-01_T1w.nii.gz")],
84+
t2w=[str(bids_root / "sub-01" / "anat" / "sub-01_T2w.nii.gz")],
85+
skull_strip_mode='force',
86+
skull_strip_template=Reference("OASIS30ANTs"),
87+
spaces=SpatialReferences(
88+
spaces=["MNI152NLin2009cAsym", "fsaverage5"],
89+
checkpoint=True,
90+
),
91+
precomputed={},
92+
omp_nthreads=1,
93+
cifti_output=cifti_output,
94+
)
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97+
@pytest.mark.parametrize("msm_sulc", [True, False])
98+
@pytest.mark.parametrize("skull_strip_mode", ['skip', 'force'])
99+
def test_anat_fit_wf(
100+
bids_root: Path,
101+
tmp_path: Path,
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msm_sulc: bool,
103+
skull_strip_mode: str,
104+
):
105+
output_dir = tmp_path / 'output'
106+
output_dir.mkdir()
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108+
init_anat_fit_wf(
109+
bids_root=str(bids_root),
110+
output_dir=str(output_dir),
111+
freesurfer=True,
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hires=False,
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longitudinal=False,
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msm_sulc=msm_sulc,
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t1w=[str(bids_root / "sub-01" / "anat" / "sub-01_T1w.nii.gz")],
116+
t2w=[str(bids_root / "sub-01" / "anat" / "sub-01_T2w.nii.gz")],
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skull_strip_mode=skull_strip_mode,
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skull_strip_template=Reference("OASIS30ANTs"),
119+
spaces=SpatialReferences(
120+
spaces=["MNI152NLin2009cAsym", "fsaverage5"],
121+
checkpoint=True,
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),
123+
precomputed={},
124+
omp_nthreads=1,
125+
)
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127+
128+
@pytest.mark.parametrize("t1w", [1, 2])
129+
@pytest.mark.parametrize("t2w", [0, 1])
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@pytest.mark.parametrize("skull_strip_mode", ['skip', 'force'])
131+
@pytest.mark.parametrize("t1w_preproc", [False, True])
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@pytest.mark.parametrize("t2w_preproc", [False, True])
133+
@pytest.mark.parametrize("t1w_mask", [False, True])
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@pytest.mark.parametrize("t1w_dseg", [False, True])
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@pytest.mark.parametrize("t1w_tpms", [False, True])
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@pytest.mark.parametrize("xfms", [False, True])
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@pytest.mark.parametrize("sphere_reg_msm", [0, 1, 2])
138+
def test_anat_fit_precomputes(
139+
bids_root: Path,
140+
tmp_path: Path,
141+
t1w: int,
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t2w: int,
143+
skull_strip_mode: str,
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t1w_preproc: bool,
145+
t2w_preproc: bool,
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t1w_mask: bool,
147+
t1w_dseg: bool,
148+
t1w_tpms: bool,
149+
xfms: bool,
150+
sphere_reg_msm: int,
151+
):
152+
"""Test as many combinations of precomputed files and input
153+
configurations as possible."""
154+
output_dir = tmp_path / 'output'
155+
output_dir.mkdir()
156+
157+
# Construct inputs
158+
t1w_list = [
159+
str(bids_root / "sub-01" / "anat" / "sub-01_run-1_T1w.nii.gz"),
160+
str(bids_root / "sub-01" / "anat" / "sub-01_run-2_T1w.nii.gz"),
161+
][:t1w]
162+
t2w_list = [str(bids_root / "sub-01" / "anat" / "sub-01_T2w.nii.gz")][:t2w]
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164+
# Construct precomputed files
165+
empty_img = nb.Nifti1Image(np.zeros((1, 1, 1)), np.eye(4))
166+
precomputed = {}
167+
if t1w_preproc:
168+
precomputed["t1w_preproc"] = str(tmp_path / "t1w_preproc.nii.gz")
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if t2w_preproc:
170+
precomputed["t2w_preproc"] = str(tmp_path / "t2w_preproc.nii.gz")
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if t1w_mask:
172+
precomputed["t1w_mask"] = str(tmp_path / "t1w_mask.nii.gz")
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if t1w_dseg:
174+
precomputed["t1w_dseg"] = str(tmp_path / "t1w_dseg.nii.gz")
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if t1w_tpms:
176+
precomputed["t1w_tpms"] = str(tmp_path / "t1w_tpms.nii.gz")
177+
178+
for path in precomputed.values():
179+
empty_img.to_filename(path)
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precomputed["sphere_reg_msm"] = [
182+
str(tmp_path / f"sub-01_hemi-{hemi}_desc-msm_sphere.surf.gii")
183+
for hemi in ["L", "R"]
184+
][:sphere_reg_msm]
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for path in precomputed["sphere_reg_msm"]:
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Path(path).touch()
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if xfms:
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transforms = precomputed["transforms"] = {}
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transforms["MNI152NLin2009cAsym"] = {
191+
"forward": str(tmp_path / "MNI152NLin2009cAsym_forward_xfm.txt"),
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"reverse": str(tmp_path / "MNI152NLin2009cAsym_reverse_xfm.txt"),
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}
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transforms["fsnative"] = {
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"forward": str(tmp_path / "fsnative_forward_xfm.txt"),
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"reverse": str(tmp_path / "fsnative_reverse_xfm.txt"),
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}
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# Write dummy transforms
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for xfm in transforms.values():
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for path in xfm.values():
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Path(path).touch()
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# Create workflow
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init_anat_fit_wf(
206+
bids_root=str(bids_root),
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output_dir=str(output_dir),
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freesurfer=True,
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hires=False,
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longitudinal=False,
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msm_sulc=True,
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t1w=t1w_list,
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t2w=t2w_list,
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skull_strip_mode=skull_strip_mode,
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skull_strip_template=Reference("OASIS30ANTs"),
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spaces=SpatialReferences(
217+
spaces=["MNI152NLin2009cAsym", "fsaverage5"],
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checkpoint=True,
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),
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precomputed=precomputed,
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omp_nthreads=1,
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)

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