TEST: Add smoke tests for main anatomical workflows

smriprep/workflows/tests/test_anatomical.py

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+from pathlib import Path
+
+import nibabel as nb
+import numpy as np
+import pytest
+
+from niworkflows.utils.spaces import SpatialReferences, Reference
+from niworkflows.utils.testing import generate_bids_skeleton
+
+from ..anatomical import init_anat_preproc_wf, init_anat_fit_wf
+
+BASE_LAYOUT = {
+    "01": {
+        "anat": [{"suffix": "T1w"}, {"suffix": "T2w"}],
+        "func": [
+            {
+                "task": "rest",
+                "run": i,
+                "suffix": "bold",
+                "metadata": {"PhaseEncodingDirection": "j", "TotalReadoutTime": 0.6},
+            }
+            for i in range(1, 3)
+        ],
+        "fmap": [
+            {"suffix": "phasediff", "metadata": {"EchoTime1": 0.005, "EchoTime2": 0.007}},
+            {"suffix": "magnitude1", "metadata": {"EchoTime": 0.005}},
+            {
+                "suffix": "epi",
+                "direction": "PA",
+                "metadata": {"PhaseEncodingDirection": "j", "TotalReadoutTime": 0.6},
+            },
+            {
+                "suffix": "epi",
+                "direction": "AP",
+                "metadata": {"PhaseEncodingDirection": "j-", "TotalReadoutTime": 0.6},
+            },
+        ],
+    },
+}
+
+
+@pytest.fixture(scope="module")
+def bids_root(tmp_path_factory):
+    base = tmp_path_factory.mktemp("base")
+    bids_dir = base / "bids"
+    generate_bids_skeleton(bids_dir, BASE_LAYOUT)
+    yield bids_dir
+
+
+@pytest.mark.parametrize("freesurfer", [True, False])
+@pytest.mark.parametrize("cifti_output", [False, "91k"])
+def test_init_anat_preproc_wf(
+    bids_root: Path,
+    tmp_path: Path,
+    freesurfer: bool,
+    cifti_output: bool,
+):
+    output_dir = tmp_path / 'output'
+    output_dir.mkdir()
+
+    init_anat_preproc_wf(
+        bids_root=str(bids_root),
+        output_dir=str(output_dir),
+        freesurfer=freesurfer,
+        hires=False,
+        longitudinal=False,
+        msm_sulc=False,
+        t1w=[str(bids_root / "sub-01" / "anat" / "sub-01_T1w.nii.gz")],
+        t2w=[str(bids_root / "sub-01" / "anat" / "sub-01_T2w.nii.gz")],
+        skull_strip_mode=False,
+        skull_strip_template=Reference("OASIS30ANTs"),
+        spaces=SpatialReferences(
+            spaces=["MNI152NLin2009cAsym", "fsaverage5"],
+            checkpoint=True,
+        ),
+        precomputed={},
+        omp_nthreads=1,
+        cifti_output=cifti_output,
+    )
+
+
+@pytest.mark.parametrize("msm_sulc", [True, False])
+@pytest.mark.parametrize("skull_strip_mode", ['skip', 'force'])
+def test_anat_fit_wf(
+    bids_root: Path,
+    tmp_path: Path,
+    msm_sulc: bool,
+    skull_strip_mode: str,
+):
+    output_dir = tmp_path / 'output'
+    output_dir.mkdir()
+
+    init_anat_fit_wf(
+        bids_root=str(bids_root),
+        output_dir=str(output_dir),
+        freesurfer=True,
+        hires=False,
+        longitudinal=False,
+        msm_sulc=msm_sulc,
+        t1w=[str(bids_root / "sub-01" / "anat" / "sub-01_T1w.nii.gz")],
+        t2w=[str(bids_root / "sub-01" / "anat" / "sub-01_T2w.nii.gz")],
+        skull_strip_mode=skull_strip_mode,
+        skull_strip_template=Reference("OASIS30ANTs"),
+        spaces=SpatialReferences(
+            spaces=["MNI152NLin2009cAsym", "fsaverage5"],
+            checkpoint=True,
+        ),
+        precomputed={},
+        omp_nthreads=1,
+    )
+
+
+@pytest.mark.parametrize("t1w_preproc", [False, True])
+@pytest.mark.parametrize("t2w_preproc", [False, True])
+@pytest.mark.parametrize("t1w_mask", [False, True])
+@pytest.mark.parametrize("t1w_dseg", [False, True])
+@pytest.mark.parametrize("t1w_tpms", [False, True])
+def test_anat_fit_precomputes(
+    bids_root: Path,
+    tmp_path: Path,
+    t1w_preproc: bool,
+    t2w_preproc: bool,
+    t1w_mask: bool,
+    t1w_dseg: bool,
+    t1w_tpms: bool,
+):
+    output_dir = tmp_path / 'output'
+    output_dir.mkdir()
+
+    empty_img = nb.Nifti1Image(np.zeros((1, 1, 1)), np.eye(4))
+    precomputed = {}
+    if t1w_preproc:
+        precomputed["t1w_preproc"] = str(tmp_path / "t1w_preproc.nii.gz")
+    if t2w_preproc:
+        precomputed["t2w_preproc"] = str(tmp_path / "t2w_preproc.nii.gz")
+    if t1w_mask:
+        precomputed["t1w_mask"] = str(tmp_path / "t1w_mask.nii.gz")
+    if t1w_dseg:
+        precomputed["t1w_dseg"] = str(tmp_path / "t1w_dseg.nii.gz")
+    if t1w_tpms:
+        precomputed["t1w_tpms"] = str(tmp_path / "t1w_tpms.nii.gz")
+
+    for path in precomputed.values():
+        empty_img.to_filename(path)
+
+    init_anat_fit_wf(
+        bids_root=str(bids_root),
+        output_dir=str(output_dir),
+        freesurfer=False,
+        hires=False,
+        longitudinal=False,
+        msm_sulc=True,
+        t1w=[str(bids_root / "sub-01" / "anat" / "sub-01_T1w.nii.gz")],
+        t2w=[str(bids_root / "sub-01" / "anat" / "sub-01_T2w.nii.gz")],
+        skull_strip_mode=False,
+        skull_strip_template=Reference("OASIS30ANTs"),
+        spaces=SpatialReferences(
+            spaces=["MNI152NLin2009cAsym", "fsaverage5"],
+            checkpoint=True,
+        ),
+        precomputed=precomputed,
+        omp_nthreads=1,
+    )