fix unit tests and add some more

clinica/utils/input_files.py

@@ -177,6 +177,7 @@ def query_factory(name: Union[str, QueryName], *args, **kwargs) -> Query:
 
 
 def get_dwi_file(filetype: Union[str, DWIFileType]) -> Query:
+    """Return the query to get DWI files (nii, json, bvec, bval)."""
     filetype = DWIFileType(filetype)
     return Query(
         f"dwi/sub-*_ses-*_dwi.{filetype.value}*", f"DWI {filetype.value} files.", ""

test/unittests/utils/test_input_files.py

@@ -3,7 +3,7 @@
 import pytest
 
 from clinica.pipelines.dwi.dti.utils import DTIBasedMeasure
-from clinica.utils.input_files import query_factory
+from clinica.utils.input_files import Query, query_factory
 from clinica.utils.pet import ReconstructionMethod, Tracer
 
 
@@ -44,13 +44,49 @@ def toy_func_3(x, y=2, z=3):
 @pytest.mark.parametrize(
     "query_name,expected_pattern,expected_description,expected_pipelines",
     [
-        ("T1W", "sub-*_ses-*_t1w.nii*", "T1w MRI", ()),
-        ("T2W", "sub-*_ses-*_flair.nii*", "FLAIR T2w MRI", ()),
+        ("T1W", "sub-*_ses-*_t1w.nii*", "T1w MRI", ""),
+        ("T2W", "sub-*_ses-*_flair.nii*", "FLAIR T2w MRI", ""),
         (
             "T1_FS_WM",
             "t1/freesurfer_cross_sectional/sub-*_ses-*/mri/wm.seg.mgz",
             "segmentation of white matter (mri/wm.seg.mgz).",
-            ("t1-freesurfer",),
+            "t1-freesurfer",
+        ),
+        (
+            "T1_FS_BRAIN",
+            "t1/freesurfer_cross_sectional/sub-*_ses-*/mri/brain.mgz",
+            "extracted brain from T1w MRI (mri/brain.mgz).",
+            "t1-freesurfer",
+        ),
+        (
+            "T1_FS_ORIG_NU",
+            "t1/freesurfer_cross_sectional/sub-*_ses-*/mri/orig_nu.mgz",
+            (
+                "intensity normalized volume generated after correction for"
+                " non-uniformity in FreeSurfer (mri/orig_nu.mgz)."
+            ),
+            "t1-freesurfer",
+        ),
+        (
+            "T1_FS_LONG_ORIG_NU",
+            "t1/long-*/freesurfer_longitudinal/sub-*_ses-*.long.sub-*_*/mri/orig_nu.mgz",
+            (
+                "intensity normalized volume generated after correction for non-uniformity "
+                "in FreeSurfer (orig_nu.mgz) in longitudinal"
+            ),
+            "t1-freesurfer and t1-freesurfer longitudinal",
+        ),
+        (
+            "T1W_TO_MNI_TRANSFORM",
+            "*space-MNI152NLin2009cSym_res-1x1x1_affine.mat",
+            "Transformation matrix from T1W image to MNI space using t1-linear pipeline",
+            "t1-linear",
+        ),
+        (
+            "DWI_PREPROC_BRAINMASK",
+            "dwi/preprocessing/sub-*_ses-*_space-*_brainmask.nii*",
+            "b0 brainmask",
+            "dwi-preprocessing-using-t1 or dwi-preprocessing-using-fieldmap",
         ),
     ],
 )
@@ -64,27 +100,99 @@ def test_query_factory(
     assert query.needed_pipeline == expected_pipelines
 
 
+@pytest.mark.parametrize(
+    "filetype,expected_pattern,expected_description,expected_pipelines",
+    [
+        ("nii", "dwi/sub-*_ses-*_dwi.nii*", "DWI nii files.", ""),
+        ("json", "dwi/sub-*_ses-*_dwi.json*", "DWI json files.", ""),
+        ("bvec", "dwi/sub-*_ses-*_dwi.bvec*", "DWI bvec files.", ""),
+        ("bval", "dwi/sub-*_ses-*_dwi.bval*", "DWI bval files.", ""),
+    ],
+)
+def test_get_dwi_file(
+    filetype: str,
+    expected_pattern: str,
+    expected_description: str,
+    expected_pipelines: str,
+):
+    from clinica.utils.input_files import get_dwi_file
+
+    query = get_dwi_file(filetype)
+
+    assert query.pattern == expected_pattern
+    assert query.description == expected_description
+    assert query.needed_pipeline == expected_pipelines
+
+
+@pytest.mark.parametrize(
+    "filetype,expected_pattern,expected_description,expected_pipelines",
+    [
+        (
+            "nii",
+            "dwi/preprocessing/sub-*_ses-*_space-*_desc-preproc_dwi.nii*",
+            "preprocessed nii files",
+            "dwi-preprocessing-using-t1 or dwi-preprocessing-using-fieldmap",
+        ),
+        (
+            "json",
+            "dwi/preprocessing/sub-*_ses-*_space-*_desc-preproc_dwi.json*",
+            "preprocessed json files",
+            "dwi-preprocessing-using-t1 or dwi-preprocessing-using-fieldmap",
+        ),
+        (
+            "bvec",
+            "dwi/preprocessing/sub-*_ses-*_space-*_desc-preproc_dwi.bvec*",
+            "preprocessed bvec files",
+            "dwi-preprocessing-using-t1 or dwi-preprocessing-using-fieldmap",
+        ),
+        (
+            "bval",
+            "dwi/preprocessing/sub-*_ses-*_space-*_desc-preproc_dwi.bval*",
+            "preprocessed bval files",
+            "dwi-preprocessing-using-t1 or dwi-preprocessing-using-fieldmap",
+        ),
+    ],
+)
+def test_get_dwi_preprocessed_file(
+    filetype: str,
+    expected_pattern: str,
+    expected_description: str,
+    expected_pipelines: str,
+):
+    from clinica.utils.input_files import get_dwi_preprocessed_file
+
+    query = get_dwi_preprocessed_file(filetype)
+
+    assert query.pattern == expected_pattern
+    assert query.description == expected_description
+    assert query.needed_pipeline == expected_pipelines
+
+
 def test_bids_pet_nii_empty():
     from clinica.utils.input_files import bids_pet_nii
 
-    assert bids_pet_nii() == {
-        "pattern": Path("pet") / "*_pet.nii*",
-        "description": "PET data",
-    }
+    query = bids_pet_nii()
+
+    assert query.pattern == str(Path("pet") / "*_pet.nii*")
+    assert query.description == "PET data"
 
 
 @pytest.fixture
-def expected_bids_pet_query(tracer, reconstruction):
-    return {
-        "pattern": Path("pet")
-        / f"*_trc-{tracer.value}_rec-{reconstruction.value}_pet.nii*",
-        "description": f"PET data with {tracer.value} tracer and reconstruction method {reconstruction.value}",
-    }
+def expected_bids_pet_query(
+    tracer: Tracer, reconstruction: ReconstructionMethod
+) -> Query:
+    return Query(
+        str(Path("pet") / f"*_trc-{tracer.value}_rec-{reconstruction.value}_pet.nii*"),
+        f"PET data with {tracer.value} tracer and reconstruction method {reconstruction.value}",
+        "",
+    )
 
 
 @pytest.mark.parametrize("tracer", Tracer)
 @pytest.mark.parametrize("reconstruction", ReconstructionMethod)
-def test_bids_pet_nii(tracer, reconstruction, expected_bids_pet_query):
+def test_bids_pet_nii(
+    tracer: Tracer, reconstruction: ReconstructionMethod, expected_bids_pet_query: Query
+):
     from clinica.utils.input_files import bids_pet_nii
 
     assert bids_pet_nii(tracer, reconstruction) == expected_bids_pet_query
@@ -96,11 +204,14 @@ def test_dwi_dti_query(dti_measure, space):
     from clinica.utils.input_files import dwi_dti
 
     space = space or "*"
-    assert dwi_dti(dti_measure, space=space) == {
-        "pattern": f"dwi/dti_based_processing/*/*_space-{space}_{dti_measure.value}.nii.gz",
-        "description": f"DTI-based {dti_measure.value} in space {space}.",
-        "needed_pipeline": "dwi_dti",
-    }
+    query = dwi_dti(dti_measure, space=space)
+
+    assert (
+        query.pattern
+        == f"dwi/dti_based_processing/*/*_space-{space}_{dti_measure.value}.nii.gz"
+    )
+    assert query.description == f"DTI-based {dti_measure.value} in space {space}."
+    assert query.needed_pipeline == "dwi_dti"
 
 
 def test_dwi_dti_query_error():