Load T1w-to-standard transform to same space as volumetric BOLD scan (#…

…926)

xcp_d/tests/data/test_ds001419_cifti_outputs.txt

@@ -47,8 +47,8 @@ xcp_d/space-fsLR_atlas-HCP_den-91k_dseg.dlabel.nii
 xcp_d/sub-01
 xcp_d/sub-01.html
 xcp_d/sub-01/anat
-xcp_d/sub-01/anat/sub-01_space-MNI152NLin6Asym_desc-preproc_T1w.nii.gz
-xcp_d/sub-01/anat/sub-01_space-MNI152NLin6Asym_dseg.nii.gz
+xcp_d/sub-01/anat/sub-01_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii.gz
+xcp_d/sub-01/anat/sub-01_space-MNI152NLin2009cAsym_dseg.nii.gz
 xcp_d/sub-01/func
 xcp_d/sub-01/func/sub-01_task-imagery_desc-dcan_qc.hdf5
 xcp_d/sub-01/func/sub-01_task-imagery_desc-filtered_motion.tsv

xcp_d/tests/test_utils_bids.py

@@ -14,6 +14,11 @@ def test_collect_participants(datasets):
     This also covers BIDSError and BIDSWarning.
     """
     bids_dir = datasets["ds001419"]
+
+    # Pass in non-BIDS folder to get BIDSError.
+    with pytest.raises(xbids.BIDSError, match="Could not find participants"):
+        xbids.collect_participants(os.path.dirname(bids_dir), participant_label="fail")
+
     with pytest.raises(xbids.BIDSError, match="Could not find participants"):
         xbids.collect_participants(bids_dir, participant_label="fail")
 
@@ -30,7 +35,7 @@ def test_collect_participants(datasets):
     assert found_labels == ["01"]
 
 
-def test_collect_data_pnc(datasets):
+def test_collect_data_ds001419(datasets):
     """Test the collect_data function."""
     bids_dir = datasets["ds001419"]
 
@@ -69,8 +74,8 @@ def test_collect_data_pnc(datasets):
     assert "space-fsLR" in subj_data["bold"][0]
     assert "space-" not in subj_data["t1w"]
     assert os.path.basename(subj_data["t1w"]) == "sub-01_desc-preproc_T1w.nii.gz"
-    assert "to-MNI152NLin6Asym" in subj_data["anat_to_template_xfm"]
-    assert "from-MNI152NLin6Asym" in subj_data["template_to_anat_xfm"]
+    assert "to-MNI152NLin2009cAsym" in subj_data["anat_to_template_xfm"]
+    assert "from-MNI152NLin2009cAsym" in subj_data["template_to_anat_xfm"]
 
 
 def test_collect_data_nibabies(datasets):

xcp_d/tests/test_utils_utils.py

@@ -155,18 +155,18 @@ def test_denoise_with_nilearn(ds001419_data, tmp_path_factory):
 
 def test_list_to_str():
     """Test the list_to_str function."""
-    lst = ["a"]
-    string = utils.list_to_str(lst)
+    string = utils.list_to_str(["a"])
     assert string == "a"
 
-    lst = ["a", "b"]
-    string = utils.list_to_str(lst)
+    string = utils.list_to_str(["a", "b"])
     assert string == "a and b"
 
-    lst = ["a", "b", "c"]
-    string = utils.list_to_str(lst)
+    string = utils.list_to_str(["a", "b", "c"])
     assert string == "a, b, and c"
 
+    with pytest.raises(ValueError, match="Zero-length list provided."):
+        utils.list_to_str([])
+
 
 def test_get_bold2std_and_t1w_xfms(ds001419_data):
     """Test get_bold2std_and_t1w_xfms."""
@@ -331,7 +331,7 @@ def test_get_std2bold_xfms(ds001419_data):
     """
     bold_file_nlin2009c = ds001419_data["nifti_file"]
 
-    # MNI152NLin2009cAsym --> MNI152NLin6Asym
+    # MNI152NLin6Asym --> MNI152NLin2009cAsym
     xforms_to_mni = utils.get_std2bold_xfms(bold_file_nlin2009c)
     assert len(xforms_to_mni) == 1
 
@@ -343,15 +343,15 @@ def test_get_std2bold_xfms(ds001419_data):
     xforms_to_mni = utils.get_std2bold_xfms(bold_file_nlin6asym)
     assert len(xforms_to_mni) == 1
 
-    # MNIInfant --> MNI152NLin6Asym
+    # MNI152NLin6Asym --> MNIInfant
     bold_file_infant = bold_file_nlin2009c.replace(
         "space-MNI152NLin2009cAsym_",
         "space-MNIInfant_cohort-1_",
     )
     xforms_to_mni = utils.get_std2bold_xfms(bold_file_infant)
     assert len(xforms_to_mni) == 2
 
-    # tofail --> MNI152NLin6Asym
+    # MNI152NLin6Asym --> tofail
     bold_file_tofail = bold_file_nlin2009c.replace("space-MNI152NLin2009cAsym_", "space-tofail_")
     with pytest.raises(ValueError, match="Space 'tofail'"):
         utils.get_std2bold_xfms(bold_file_tofail)

xcp_d/utils/bids.py

@@ -32,8 +32,8 @@
     "nibabies": {
         "cifti": ["fsLR"],
         "nifti": [
-            "MNIInfant",
             "MNI152NLin6Asym",
+            "MNIInfant",
             "MNI152NLin2009cAsym",
         ],
     },
@@ -279,18 +279,34 @@ def collect_data(
     if cifti:
         # Select the appropriate volumetric space for the CIFTI template.
         # This space will be used in the executive summary and T1w/T2w workflows.
-        temp_query = queries["anat_to_template_xfm"].copy()
-        volumetric_space = ASSOCIATED_TEMPLATES[space]
+        allowed_spaces = INPUT_TYPE_ALLOWED_SPACES.get(
+            input_type,
+            DEFAULT_ALLOWED_SPACES,
+        )["nifti"]
+
+        temp_bold_query = queries["bold"].copy()
+        temp_bold_query.pop("den", None)
+        temp_bold_query["extension"] = ".nii.gz"
+
+        temp_xfm_query = queries["anat_to_template_xfm"].copy()
 
-        temp_query["to"] = volumetric_space
-        transform_files = layout.get(**temp_query)
-        if not transform_files:
+        for volspace in allowed_spaces:
+            temp_bold_query["space"] = volspace
+            bold_data = layout.get(**temp_bold_query)
+            temp_xfm_query["to"] = volspace
+            transform_files = layout.get(**temp_xfm_query)
+
+            if bold_data and transform_files:
+                # will leave the best available space in the query
+                break
+
+        if not bold_data or not transform_files:
             raise FileNotFoundError(
-                f"No nifti transforms found to allowed space ({volumetric_space})"
+                f"No BOLD NIfTI or transforms found to allowed space ({volspace})"
             )
 
-        queries["anat_to_template_xfm"]["to"] = volumetric_space
-        queries["template_to_anat_xfm"]["from"] = volumetric_space
+        queries["anat_to_template_xfm"]["to"] = volspace
+        queries["template_to_anat_xfm"]["from"] = volspace
     else:
         # use the BOLD file's space if the BOLD file is a nifti.
         queries["anat_to_template_xfm"]["to"] = queries["bold"]["space"]
@@ -542,19 +558,20 @@ def collect_morphometry_data(layout, participant_label):
 
 
 @fill_doc
-def collect_run_data(layout, input_type, bold_file, cifti, primary_anat):
+def collect_run_data(layout, bold_file, cifti, primary_anat, target_space):
     """Collect data associated with a given BOLD file.
 
     Parameters
     ----------
     %(layout)s
-    %(input_type)s
     bold_file : :obj:`str`
         Path to the BOLD file.
     %(cifti)s
         Whether to collect files associated with a CIFTI image (True) or a NIFTI (False).
     primary_anat : {"T1w", "T2w"}
         The anatomical modality to use for the anat-to-native transform.
+    target_space
+        Used to find NIfTIs in the appropriate space if ``cifti`` is ``True``.
 
     Returns
     -------
@@ -598,24 +615,29 @@ def collect_run_data(layout, input_type, bold_file, cifti, primary_anat):
             suffix="xfm",
         )
     else:
-        allowed_nifti_spaces = INPUT_TYPE_ALLOWED_SPACES.get(
-            input_type,
-            DEFAULT_ALLOWED_SPACES,
-        )["nifti"]
+        # Split cohort out of the space for MNIInfant templates.
+        cohort = None
+        if "+" in target_space:
+            target_space, cohort = target_space.split("+")
+
         run_data["boldref"] = layout.get_nearest(
             bids_file.path,
             strict=False,
-            space=allowed_nifti_spaces,
+            space=target_space,
+            cohort=cohort,
             suffix="boldref",
             extension=[".nii", ".nii.gz"],
+            invalid_filters="allow",
         )
         run_data["nifti_file"] = layout.get_nearest(
             bids_file.path,
             strict=False,
-            space=allowed_nifti_spaces,
+            space=target_space,
+            cohort=cohort,
             desc="preproc",
             suffix="bold",
             extension=[".nii", ".nii.gz"],
+            invalid_filters="allow",
         )
 
     LOGGER.log(

xcp_d/workflows/anatomical.py

@@ -30,6 +30,7 @@
 )
 from xcp_d.utils.bids import get_freesurfer_dir, get_freesurfer_sphere
 from xcp_d.utils.doc import fill_doc
+from xcp_d.utils.utils import list_to_str
 from xcp_d.workflows.execsummary import (
     init_brainsprite_figures_wf,
     init_execsummary_anatomical_plots_wf,
@@ -204,6 +205,13 @@ def init_postprocess_anat_wf(
             workflow.connect([(inputnode, ds_t2w_std, [("t2w", "in_file")])])
 
     else:
+        out = (
+            ["T1w"] if t1w_available else [] + ["T2w"] if t2w_available else [] + ["segmentation"]
+        )
+        workflow.__desc__ = f"""\
+Native-space {list_to_str(out)} images were transformed to {target_space} space at 1 mm3
+resolution.
+"""
         warp_anat_dseg_to_template = pe.Node(
             ApplyTransforms(
                 num_threads=2,

xcp_d/workflows/base.py

@@ -669,11 +669,11 @@ def init_subject_wf(
 
         for j_run, bold_file in enumerate(task_files):
             run_data = collect_run_data(
-                layout,
-                input_type,
-                bold_file,
+                layout=layout,
+                bold_file=bold_file,
                 cifti=cifti,
                 primary_anat=primary_anat,
+                target_space=target_space,
             )
 
             post_scrubbing_duration = flag_bad_run(