some fixes

aramis-lab · Nov 6, 2024 · eb5dba8 · eb5dba8
1 parent 1c9d3d5
commit eb5dba8
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Showing 4 changed files with 62 additions and 51 deletions.
diff --git a/clinica/pipelines/anatomical/freesurfer/longitudinal/correction/pipeline.py b/clinica/pipelines/anatomical/freesurfer/longitudinal/correction/pipeline.py
@@ -59,7 +59,11 @@ def _build_input_node(self):
             save_part_sess_long_ids_to_tsv,
         )
         from clinica.utils.exceptions import ClinicaException
-        from clinica.utils.input_files import T1_FS_DESTRIEUX, T1_FS_T_DESTRIEUX
+        from clinica.utils.input_files import (
+            Parcellation,
+            QueryPatternName,
+            query_pattern_factory,
+        )
         from clinica.utils.inputs import (
             clinica_file_reader,
             format_clinica_file_reader_errors,
@@ -119,19 +123,26 @@ def _build_input_node(self):
                 ) = extract_subject_session_longitudinal_ids_from_filename(
                     to_process_ids
                 )
-
+        pattern_segmentation = query_pattern_factory(
+            QueryPatternName.T1_FREESURFER_SEGMENTATION
+        )(Parcellation.DESTRIEUX)
         _, errors_destrieux = clinica_file_reader(
-            self.subjects, self.sessions, self.caps_directory, T1_FS_DESTRIEUX
+            self.subjects, self.sessions, self.caps_directory, pattern_segmentation
         )
+        pattern_template = query_pattern_factory(
+            QueryPatternName.T1_FREESURFER_TEMPLATE
+        )(Parcellation.DESTRIEUX)
         _, errors_t_destrieux = clinica_file_reader(
-            self.subjects, list_long_id, self.caps_directory, T1_FS_T_DESTRIEUX
+            self.subjects, list_long_id, self.caps_directory, pattern_template
         )
         all_errors = [errors_destrieux, errors_t_destrieux]
 
         if any(all_errors):
             message = "Clinica faced errors while trying to read files in your CAPS directory.\n"
-            for error, info in zip(all_errors, [T1_FS_DESTRIEUX, T1_FS_T_DESTRIEUX]):
-                message += format_clinica_file_reader_errors(error, info)
+            for error, pattern in zip(
+                all_errors, [pattern_segmentation, pattern_template]
+            ):
+                message += format_clinica_file_reader_errors(error, pattern)
             raise ClinicaException(message)
 
         save_part_sess_long_ids_to_tsv(

diff --git a/clinica/pipelines/anatomical/freesurfer/longitudinal/template/pipeline.py b/clinica/pipelines/anatomical/freesurfer/longitudinal/template/pipeline.py
@@ -2,6 +2,11 @@
 from typing import List
 
 from clinica.pipelines.engine import Pipeline
+from clinica.utils.input_files import (
+    Parcellation,
+    QueryPatternName,
+    query_pattern_factory,
+)
 
 
 class T1FreeSurferTemplate(Pipeline):
@@ -17,7 +22,6 @@ def get_processed_images(
     ) -> List[str]:
         import re
 
-        from clinica.utils.input_files import T1_FS_T_DESTRIEUX
         from clinica.utils.inputs import clinica_file_reader
         from clinica.utils.longitudinal import get_long_id
         from clinica.utils.participant import get_unique_subjects
@@ -28,11 +32,13 @@ def get_processed_images(
         list_long_id = [
             get_long_id(list_session_ids) for list_session_ids in list_list_session_ids
         ]
-
         image_ids: List[str] = []
         if caps_directory.is_dir():
+            pattern = query_pattern_factory(QueryPatternName.T1_FREESURFER_TEMPLATE)(
+                Parcellation.DESTRIEUX
+            )
             t1_freesurfer_files, _ = clinica_file_reader(
-                list_participant_id, list_long_id, caps_directory, T1_FS_T_DESTRIEUX
+                list_participant_id, list_long_id, caps_directory, pattern
             )
             image_ids = [
                 re.search(r"(sub-[a-zA-Z0-9]+)_(long-[a-zA-Z0-9]+)", file).group()
@@ -88,9 +94,7 @@ def _build_input_node(self):
         from clinica.pipelines.anatomical.freesurfer.longitudinal.utils import (
             save_part_sess_long_ids_to_tsv,
         )
-        from clinica.utils.exceptions import ClinicaCAPSError, ClinicaException
         from clinica.utils.filemanip import extract_subjects_sessions_from_filename
-        from clinica.utils.input_files import T1_FS_DESTRIEUX
         from clinica.utils.inputs import clinica_file_filter
         from clinica.utils.longitudinal import (
             get_long_id,
@@ -149,11 +153,12 @@ def _build_input_node(self):
                 self.subjects, self.sessions = extract_subjects_sessions_from_filename(
                     to_process_ids
                 )
-
+        pattern = query_pattern_factory(QueryPatternName.T1_FREESURFER_SEGMENTATION)(
+            Parcellation.DESTRIEUX
+        )
         _, self.subjects, self.sessions = clinica_file_filter(
-            self.subjects, self.sessions, self.caps_directory, T1_FS_DESTRIEUX
+            self.subjects, self.sessions, self.caps_directory, pattern
         )
-
         long_ids = get_participants_long_id(self.subjects, self.sessions)
         save_part_sess_long_ids_to_tsv(
             self.subjects, self.sessions, long_ids, self.base_dir / self.name

diff --git a/clinica/pipelines/machine_learning/input.py b/clinica/pipelines/machine_learning/input.py
@@ -150,7 +150,7 @@ def get_images(self):
         """
         Returns: a list of filenames
         """
-        from clinica.utils.input_files import pet_volume_normalized_suvr_pet
+        from clinica.utils.input_files import QueryPatternName, query_pattern_factory
         from clinica.utils.inputs import clinica_file_reader
 
         if self._images is not None:
@@ -183,8 +183,10 @@ def get_images(self):
                     raise Exception("File %s doesn't exists." % image)
 
         elif self._input_params["image_type"] == "PET":
-            caps_files_information = pet_volume_normalized_suvr_pet(
-                acq_label=self._input_params["acq_label"],
+            pattern = query_pattern_factory(
+                QueryPatternName.PET_VOLUME_NORMALIZED_SUVR
+            )(
+                tracer=self._input_params["acq_label"],
                 group_label=self._input_params["group_label"],
                 suvr_reference_region=self._input_params["suvr_reference_region"],
                 use_brainmasked_image=True,
@@ -195,7 +197,7 @@ def get_images(self):
                 self._subjects,
                 self._sessions,
                 self._input_params["caps_directory"],
-                caps_files_information,
+                pattern,
             )
         else:
             raise ValueError(

diff --git a/clinica/pipelines/machine_learning_spatial_svm/spatial_svm_pipeline.py b/clinica/pipelines/machine_learning_spatial_svm/spatial_svm_pipeline.py
@@ -1,6 +1,12 @@
+from pathlib import Path
 from typing import List
 
 from clinica.pipelines.engine import Pipeline
+from clinica.utils.input_files import (
+    QueryPattern,
+    QueryPatternName,
+    query_pattern_factory,
+)
 
 
 class SpatialSVM(Pipeline):
@@ -53,16 +59,10 @@ def get_output_fields(self) -> List[str]:
 
     def _build_input_node(self):
         """Build and connect an input node to the pipeline."""
-        import os
-
         import nipype.interfaces.utility as nutil
         import nipype.pipeline.engine as npe
 
         from clinica.utils.exceptions import ClinicaCAPSError, ClinicaException
-        from clinica.utils.input_files import (
-            pet_volume_normalized_suvr_pet,
-            t1_volume_final_group_template,
-        )
         from clinica.utils.inputs import (
             clinica_file_reader,
             clinica_group_reader,
@@ -86,19 +86,18 @@ def _build_input_node(self):
             ),
         )
         all_errors = []
-
         if self.parameters["orig_input_data_ml"] == "t1-volume":
-            caps_files_information = {
-                "pattern": os.path.join(
-                    "t1",
-                    "spm",
-                    "dartel",
-                    "group-" + self.parameters["group_label"],
-                    "*_T1w_segm-graymatter_space-Ixi549Space_modulated-on_probability.nii.gz",
+            pattern = QueryPattern(
+                str(
+                    Path("t1")
+                    / "spm"
+                    / "dartel"
+                    / f"group-{self.parameters['group_label']}"
+                    / "*_T1w_segm-graymatter_space-Ixi549Space_modulated-on_probability.nii.gz"
                 ),
-                "description": "graymatter tissue segmented in T1w MRI in Ixi549 space",
-                "needed_pipeline": "t1-volume-tissue-segmentation",
-            }
+                "graymatter tissue segmented in T1w MRI in Ixi549 space",
+                "t1-volume-tissue-segmentation",
+            )
         elif self.parameters["orig_input_data_ml"] == "pet-volume":
             if not (
                 self.parameters["acq_label"]
@@ -110,8 +109,11 @@ def _build_input_node(self):
                     f"- suvr_reference_region: {self.parameters['suvr_reference_region']}\n"
                     f"- use_pvc_data: {self.parameters['use_pvc_data']}\n"
                 )
-            caps_files_information = pet_volume_normalized_suvr_pet(
-                acq_label=self.parameters["acq_label"],
+            pattern = query_pattern_factory(
+                QueryPatternName.PET_VOLUME_NORMALIZED_SUVR
+            )(
+                tracer=self.parameters["acq_label"],
+                group_label=self.parameters["group_label"],
                 suvr_reference_region=self.parameters["suvr_reference_region"],
                 use_brainmasked_image=False,
                 use_pvc_data=self.parameters["use_pvc_data"],
@@ -121,27 +123,18 @@ def _build_input_node(self):
             raise ValueError(
                 f"Image type {self.parameters['orig_input_data_ml']} unknown."
             )
-
         input_image, caps_error = clinica_file_reader(
-            self.subjects,
-            self.sessions,
-            self.caps_directory,
-            caps_files_information,
+            self.subjects, self.sessions, self.caps_directory, pattern
         )
         if caps_error:
-            all_errors.append(
-                format_clinica_file_reader_errors(caps_error, caps_files_information)
-            )
-
+            all_errors.append(format_clinica_file_reader_errors(caps_error, pattern))
         try:
-            dartel_input = clinica_group_reader(
-                self.caps_directory,
-                t1_volume_final_group_template(self.parameters["group_label"]),
+            pattern = query_pattern_factory(QueryPatternName.T1_VOLUME_GROUP_TEMPLATE)(
+                self.parameters["group_label"]
             )
+            dartel_input = clinica_group_reader(self.caps_directory, pattern)
         except ClinicaException as e:
             all_errors.append(e)
-
-        # Raise all errors if some happened
         if any(all_errors):
             error_message = "Clinica faced errors while trying to read files in your CAPS directories.\n"
             for msg in all_errors: