couple fxes

aramis-lab · Nov 6, 2024 · 1c9d3d5 · 1c9d3d5
1 parent 27ba48b
commit 1c9d3d5
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Showing 3 changed files with 22 additions and 19 deletions.
diff --git a/clinica/pipelines/pet/engine.py b/clinica/pipelines/pet/engine.py
@@ -25,8 +25,8 @@ def _check_pipeline_parameters(self) -> None:
 
     def _get_pet_scans_query(self) -> QueryPattern:
         """Return the query to retrieve PET scans."""
-        from clinica.utils.input_files import bids_pet_nii
+        from clinica.utils.input_files import get_pet_nifti
 
-        return bids_pet_nii(
+        return get_pet_nifti(
             self.parameters["acq_label"], self.parameters["reconstruction_method"]
         )
diff --git a/clinica/pipelines/statistics_volume/statistics_volume_pipeline.py b/clinica/pipelines/statistics_volume/statistics_volume_pipeline.py
@@ -1,6 +1,11 @@
 from typing import List
 
 from clinica.pipelines.engine import Pipeline
+from clinica.utils.input_files import (
+    QueryPattern,
+    QueryPatternName,
+    query_pattern_factory,
+)
 from clinica.utils.pet import SUVRReferenceRegion, Tracer
 
 
@@ -96,10 +101,6 @@ def _build_input_node(self):
         import nipype.pipeline.engine as npe
 
         from clinica.utils.exceptions import ClinicaException
-        from clinica.utils.input_files import (
-            pet_volume_normalized_suvr_pet,
-            t1_volume_template_tpm_in_mni,
-        )
         from clinica.utils.inputs import clinica_file_filter
         from clinica.utils.stream import cprint
         from clinica.utils.ux import print_begin_image, print_images_to_process
@@ -117,8 +118,10 @@ def _build_input_node(self):
                 )
 
             self.parameters["measure_label"] = self.parameters["acq_label"].value
-            information_dict = 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_dartel"],
                 suvr_reference_region=self.parameters["suvr_reference_region"],
                 use_brainmasked_image=True,
@@ -127,7 +130,9 @@ def _build_input_node(self):
             )
         elif self.parameters["orig_input_data_volume"] == "t1-volume":
             self.parameters["measure_label"] = "graymatter"
-            information_dict = t1_volume_template_tpm_in_mni(
+            pattern = query_pattern_factory(
+                QueryPatternName.T1_VOLUME_TEMPLATE_TPM_IN_MNI
+            )(
                 group_label=self.parameters["group_label_dartel"],
                 tissue_number=1,
                 modulation=True,
@@ -141,17 +146,16 @@ def _build_input_node(self):
                 )
             # If custom file are grabbed, information of fwhm is irrelevant and should not appear on final filenames
             self.parameters["full_width_at_half_maximum"] = None
-            information_dict = {
-                "pattern": self.parameters["custom_file"],
-                "description": "custom file provided by user",
-            }
+            pattern = QueryPattern(
+                self.parameters["custom_file"], "custom file provided by user", ""
+            )
         else:
             raise ValueError(
                 f"Input data {self.parameters['orig_input_data_volume']} unknown."
             )
 
         input_files, self.subjects, self.sessions = clinica_file_filter(
-            self.subjects, self.sessions, self.caps_directory, information_dict
+            self.subjects, self.sessions, self.caps_directory, pattern
         )
 
         read_parameters_node = npe.Node(

diff --git a/clinica/pipelines/statistics_volume_correction/statistics_volume_correction_pipeline.py b/clinica/pipelines/statistics_volume_correction/statistics_volume_correction_pipeline.py
@@ -43,15 +43,14 @@ def _build_input_node(self):
         import nipype.interfaces.utility as nutil
         import nipype.pipeline.engine as npe
 
+        from clinica.utils.input_files import QueryPattern
         from clinica.utils.inputs import clinica_group_reader
 
         t_map = clinica_group_reader(
             self.caps_directory,
-            {
-                "pattern": self.parameters["t_map"] + "*",
-                "description": "statistics t map",
-                "needed_pipeline": "statistics-volume",
-            },
+            QueryPattern(
+                self.parameters["t_map"] + "*", "statistics t map", "statistics-volume"
+            ),
         )
 
         read_parameters_node = npe.Node(