Select masks from subjects in the analysis

bclenet · Jun 13, 2024 · 38ba3bb · 38ba3bb
1 parent 74b432c
commit 38ba3bb
Showing 1 changed file with 16 additions and 1 deletion.
diff --git a/narps_open/pipelines/team_4TQ6.py b/narps_open/pipelines/team_4TQ6.py
@@ -429,6 +429,19 @@ def get_group_level_analysis_sub_workflow(self, method):
         )
         group_level.connect(select_files, 'cope', get_copes, 'input_str')
 
+        # Function Node elements_in_string
+        #   Get masks for these subjects
+        # Note : using a MapNode with elements_in_string requires using clean_list to remove
+        #   None values from the out_list
+        get_masks = MapNode(Function(
+            function = elements_in_string,
+            input_names = ['input_str', 'elements'],
+            output_names = ['out_list']
+            ),
+            name = 'get_masks', iterfield = 'input_str'
+        )
+        group_level.connect(select_files, 'masks', get_masks, 'input_str')
+
         # Function Node elements_in_string
         #   Get variance of the estimated copes (varcope) for these subjects
         # Note : using a MapNode with elements_in_string requires using clean_list to remove
@@ -455,7 +468,7 @@ def get_group_level_analysis_sub_workflow(self, method):
         # Merge Node - Merge masks for further intersection
         merge_masks = Node(Merge(), name = 'merge_masks')
         merge_masks.inputs.dimension = 't'
-        group_level.connect(select_files, 'masks', merge_masks, 'in_files')
+        group_level.connect(get_masks, ('out_list', clean_list), merge_masks, 'in_files')
 
         # MultiImageMaths Node - Create a group mask by
         #   computing the intersection of all subject masks.
@@ -517,6 +530,7 @@ def get_group_level_analysis_sub_workflow(self, method):
             get_group_subjects.inputs.list_2 = self.subject_list
             group_level.connect(get_group_subjects, 'out_list', get_copes, 'elements')
             group_level.connect(get_group_subjects, 'out_list', get_varcopes, 'elements')
+            group_level.connect(get_group_subjects, 'out_list', get_masks, 'elements')
 
             # Function Node get_one_sample_t_test_regressors
             #   Get regressors in the equalRange and equalIndifference method case
@@ -537,6 +551,7 @@ def get_group_level_analysis_sub_workflow(self, method):
             #   Indeed the SelectFiles node asks for all (*) subjects available
             get_copes.inputs.elements = self.subject_list
             get_varcopes.inputs.elements = self.subject_list
+            get_masks.inputs.elements = self.subject_list
 
             # Setup a two sample t-test
             specify_model.inputs.contrasts = [