ENH: Enable setting the random seed for pet-linear

aramis-lab · May 28, 2023 · 431ea2a · 431ea2a
1 parent 9e105da
commit 431ea2a
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Showing 2 changed files with 10 additions and 3 deletions.
diff --git a/clinica/pipelines/pet_linear/pet_linear_cli.py b/clinica/pipelines/pet_linear/pet_linear_cli.py
@@ -15,17 +15,18 @@
 @cli_param.argument.acq_label
 @cli_param.argument.suvr_reference_region
 @cli_param.option_group.pipeline_specific_options
-@cli_param.option_group.option(
+@cli_param.option.option(
     "-ui",
     "--uncropped_image",
     is_flag=True,
     help="Do not crop the image with template (cropped image are suggested for using with DL models)",
 )
-@cli_param.option_group.option(
+@cli_param.option.option(
     "--save_pet_in_t1w_space",
     is_flag=True,
     help="Save the PET image in the T1w space computed in the intermediate step of the pipeline",
 )
+@cli_param.option.random_seed
 @cli_param.option_group.common_pipelines_options
 @cli_param.option.subjects_sessions_tsv
 @cli_param.option.working_directory
@@ -37,6 +38,7 @@ def cli(
     suvr_reference_region: str,
     uncropped_image: bool = False,
     save_pet_in_t1w_space: bool = False,
+    random_seed: Optional[int] = None,
     subjects_sessions_tsv: Optional[str] = None,
     working_directory: Optional[str] = None,
     n_procs: Optional[int] = None,
@@ -64,6 +66,7 @@ def cli(
         "suvr_reference_region": suvr_reference_region,
         "uncropped_image": uncropped_image,
         "save_PETinT1w": save_pet_in_t1w_space,
+        "random_seed": random_seed,
     }
 
     pipeline = PETLinear(

diff --git a/clinica/pipelines/pet_linear/pet_linear_pipeline.py b/clinica/pipelines/pet_linear/pet_linear_pipeline.py
@@ -329,6 +329,9 @@ def build_core_nodes(self):
         ants_applytransform_nonlinear_node.inputs.dimension = 3
         ants_applytransform_nonlinear_node.inputs.reference_image = self.ref_template
 
+        if random_seed := self.parameters.get("random_seed", None):
+            ants_registration_nonlinear_node.inputs.random_seed = random_seed
+
         normalize_intensity_node = npe.Node(
             name="intensityNormalization",
             interface=nutil.Function(
@@ -380,7 +383,8 @@ def build_core_nodes(self):
                 (concatenate_node, ants_applytransform_node, [("transforms_list", "transforms")]),
                 # STEP 3
                 (self.input_node, ants_registration_nonlinear_node, [("t1w", "moving_image")]),
-                (ants_registration_nonlinear_node, ants_applytransform_nonlinear_node, [("reverse_forward_transforms", "transforms")]),
+                (ants_registration_nonlinear_node, ants_applytransform_nonlinear_node,
+                 [("reverse_forward_transforms", "transforms")]),
                 (ants_applytransform_node, ants_applytransform_nonlinear_node, [("output_image", "input_image")]),
                 (ants_applytransform_node, normalize_intensity_node, [("output_image", "input_img")]),
                 (ants_applytransform_nonlinear_node, normalize_intensity_node, [("output_image", "norm_img")]),