[pre-commit.ci] auto fixes from pre-commit.com hooks

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Author: pre-commit-ci[bot]

CPAC/func_preproc/func_motion.py

@@ -88,17 +88,18 @@ def calc_motion_stats(wf, cfg, strat_pool, pipe_num, opt=None):
         "inputspec.motion_correct",
     )
 
-    try :
-        wf.connect(*strat_pool.get_data("space-bold_desc-brain_mask"),
+    try:
+        wf.connect(
+            *strat_pool.get_data("space-bold_desc-brain_mask"),
             gen_motion_stats,
             "inputspec.mask",
         )
-    except :
+    except:
         mask_bold = pe.Node(interface=afni.MaskTool(), name=f"mask_bold_{pipe_num}")
         mask_bold.inputs.outputtype = "NIFTI_GZ"
         node, out = strat_pool.get_data("desc-preproc_bold")
         wf.connect(node, out, mask_bold, "in_file")
-        wf.connect(mask_bold, "out_file", gen_motion_stats, "inputspec.mask") 
+        wf.connect(mask_bold, "out_file", gen_motion_stats, "inputspec.mask")
 
     wf.connect(
         *strat_pool.get_data("desc-movementParameters_motion"),

CPAC/func_preproc/func_preproc.py

@@ -1611,7 +1611,9 @@ def bold_mask_anatomical_resampled(wf, cfg, strat_pool, pipe_num, opt=None):
 
     Adapted from `DCAN Lab's BOLD mask method from the ABCD pipeline <https://github.com/DCAN-Labs/DCAN-HCP/blob/1d90814/fMRIVolume/scripts/OneStepResampling.sh#L121-L132>`_.
     """
-    anat_brain_to_func_res = anat_brain_to_bold_res(wf_name="anat_brain_to_bold_res", cfg=cfg, pipe_num=pipe_num)
+    anat_brain_to_func_res = anat_brain_to_bold_res(
+        wf_name="anat_brain_to_bold_res", cfg=cfg, pipe_num=pipe_num
+    )
 
     node, out = strat_pool.get_data("space-template_desc-preproc_T1w")
     wf.connect(
@@ -1836,12 +1838,17 @@ def bold_masking(wf, cfg, strat_pool, pipe_num, opt=None):
 
     return (wf, outputs)
 
+
 @nodeblock(
     name="template_space_bold_masking",
     switch=[
         ["functional_preproc", "run"],
         ["functional_preproc", "template_space_func_masking", "run"],
-        ["functional_preproc", "template_space_func_masking", "apply_func_mask_in_template_space"],
+        [
+            "functional_preproc",
+            "template_space_func_masking",
+            "apply_func_mask_in_template_space",
+        ],
     ],
     inputs=[("space-template_desc-preproc_bold", "space-template_desc-bold_mask")],
     outputs={
@@ -1862,13 +1869,16 @@ def bold_masking(wf, cfg, strat_pool, pipe_num, opt=None):
 def template_space_bold_masking(wf, cfg, strat_pool, pipe_num, opt=None):
     """Mask the bold in template space."""
     func_edge_detect = pe.Node(
-        interface=afni_utils.Calc(), name=f"template_space_func_extract_brain_{pipe_num}"
+        interface=afni_utils.Calc(),
+        name=f"template_space_func_extract_brain_{pipe_num}",
     )
 
     func_edge_detect.inputs.expr = "a*b"
     func_edge_detect.inputs.outputtype = "NIFTI_GZ"
 
-    node_head_bold, out_head_bold = strat_pool.get_data("space-template_desc-preproc_bold")
+    node_head_bold, out_head_bold = strat_pool.get_data(
+        "space-template_desc-preproc_bold"
+    )
     wf.connect(node_head_bold, out_head_bold, func_edge_detect, "in_file_a")
 
     node, out = strat_pool.get_data("space-template_desc-bold_mask")

CPAC/pipeline/cpac_pipeline.py

@@ -1512,13 +1512,15 @@ def build_workflow(subject_id, sub_dict, cfg, pipeline_name=None):
             warp_bold_mask_to_EPItemplate,
             warp_deriv_mask_to_EPItemplate,
         ]
-        
+
     # Template space functional masking
     if cfg.functional_preproc["template_space_func_masking"]["run"]:
         if not rpool.check_rpool("space-template_desc-bold_mask"):
-            pipeline_blocks += bold_mask_anatomical_resampled,
-        if cfg.functional_preproc["template_space_func_masking"]["apply_func_mask_in_template_space"]:
-            pipeline_blocks += template_space_bold_masking,
+            pipeline_blocks += (bold_mask_anatomical_resampled,)
+        if cfg.functional_preproc["template_space_func_masking"][
+            "apply_func_mask_in_template_space"
+        ]:
+            pipeline_blocks += (template_space_bold_masking,)
 
     # Template-space nuisance regression
     nuisance_template = (

CPAC/resources/configs/pipeline_config_abcd-options.yml

@@ -218,7 +218,7 @@ registration_workflows:
 
       # Choose coregistration degree of freedom
       dof: 12
-      
+
 
 
     func_registration_to_template:
@@ -331,7 +331,7 @@ nuisance_corrections:
 
     # switch to Off if nuisance regression is off and you don't want to write out the regressors
     create_regressors: Off
-    
+
     # Process and refine masks used to produce regressors and time series for
     # regression.
     regressor_masks:

CPAC/resources/configs/pipeline_config_abcd-prep.yml

@@ -233,4 +233,4 @@ functional_preproc:
       # Anatomical_Resampled: Resample anatomical brain mask in standard space to get BOLD brain mask in standard space. Adapted from DCAN Lab's BOLD mask method from the ABCD pipeline. ("Create fMRI resolution standard space files for T1w image, wmparc, and brain mask […] don't use FLIRT to do spline interpolation with -applyisoxfm for the 2mm and 1mm cases because it doesn't know the peculiarities of the MNI template FOVs")
     using: [Anatomical_Resampled]
 
-    apply_func_mask_in_template_space: On
+    apply_func_mask_in_template_space: On

CPAC/resources/configs/pipeline_config_blank.yml

@@ -1150,14 +1150,14 @@ functional_preproc:
 
       # Choose whether or not to dilate the anatomical mask if you choose 'Anatomical_Refined' as the functional masking option. It will dilate one voxel if enabled.
       anatomical_mask_dilation: Off
-  
+
   template_space_func_masking:
     run: Off
       # Anatomical_Resampled: Resample anatomical brain mask in standard space to get BOLD brain mask in standard space. Adapted from DCAN Lab's BOLD mask method from the ABCD pipeline. ("Create fMRI resolution standard space files for T1w image, wmparc, and brain mask […] don't use FLIRT to do spline interpolation with -applyisoxfm for the 2mm and 1mm cases because it doesn't know the peculiarities of the MNI template FOVs")
     using: [Anatomical_Resampled]
 
     apply_func_mask_in_template_space: Off
-    
+
   generate_func_mean:
 
     # Generate mean functional image