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nipreps · May 7, 2024 · d267a86 · d267a86
1 parent d3a3680
commit d267a86
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Showing 4 changed files with 32 additions and 29 deletions.
diff --git a/src/fmripost_aroma/interfaces/resampler.py b/src/fmripost_aroma/interfaces/resampler.py
@@ -10,29 +10,29 @@
 
 
 class _ResamplerInputSpec(BaseInterfaceInputSpec):
-    bold_file = File(exists=True, desc="BOLD file to resample.")
+    bold_file = File(exists=True, desc='BOLD file to resample.')
     derivs_path = traits.Directory(
         exists=True,
-        desc="Path to derivatives.",
+        desc='Path to derivatives.',
     )
     output_dir = traits.Directory(
         exists=True,
-        desc="Output directory.",
+        desc='Output directory.',
     )
     space = traits.Str(
-        "MNI152NLin6Asym",
+        'MNI152NLin6Asym',
         usedefault=True,
-        desc="Output space.",
+        desc='Output space.',
     )
     resolution = traits.Str(
-        "2",
+        '2',
         usedefault=True,
-        desc="Output resolution.",
+        desc='Output resolution.',
     )
 
 
 class _ResamplerOutputSpec(TraitedSpec):
-    output_file = File(exists=True, desc="Resampled BOLD file.")
+    output_file = File(exists=True, desc='Resampled BOLD file.')
 
 
 class Resampler(SimpleInterface):
@@ -57,6 +57,6 @@ def _run_interface(self, runtime):
             resolution=self.inputs.resolution,
         )
 
-        self._results["output_file"] = output_file
+        self._results['output_file'] = output_file
 
         return runtime
diff --git a/src/fmripost_aroma/utils/resampler.py b/src/fmripost_aroma/utils/resampler.py
@@ -1,3 +1,7 @@
+"""Resampler methods for fMRI data."""
+
+from __future__ import annotations
+
 import asyncio
 import os
 from functools import partial
@@ -19,7 +23,6 @@
 from templateflow import api as tf
 from typing_extensions import Annotated
 
-
 R = TypeVar('R')
 
 nipreps_cfg = niworkflows.data.load('nipreps.json')

diff --git a/src/fmripost_aroma/workflows/base.py b/src/fmripost_aroma/workflows/base.py
@@ -321,7 +321,7 @@ def init_single_subject_wf(subject_id: str):
 
     for bold_file in subject_data['bold']:
         ica_aroma_wf = init_ica_aroma_wf(bold_file=bold_file)
-        ica_aroma_wf.__desc__ = func_pre_desc + (ica_aroma_wf.__desc__ or "")
+        ica_aroma_wf.__desc__ = func_pre_desc + (ica_aroma_wf.__desc__ or '')
 
         functional_cache = {}
         if config.execution.derivatives:
@@ -344,8 +344,8 @@ def init_single_subject_wf(subject_id: str):
             )
             workflow.connect([
                 (resample_raw_wf, ica_aroma_wf, [
-                    ("outputnode.bold_std", "inputnode.bold_std"),
-                    ("outputnode.bold_mask_std", "inputnode.bold_mask_std"),
+                    ('outputnode.bold_std', 'inputnode.bold_std'),
+                    ('outputnode.bold_mask_std', 'inputnode.bold_mask_std'),
                 ]),
             ])  # fmt:skip
         else:
@@ -358,13 +358,13 @@ def init_single_subject_wf(subject_id: str):
                     entities=entities,
                 )
             )
-            ica_aroma_wf.inputs.inputnode.bold_std = functional_cache["bold_std"]
-            ica_aroma_wf.inputs.inputnode.bold_mask_std = functional_cache["bold_mask_std"]
+            ica_aroma_wf.inputs.inputnode.bold_std = functional_cache['bold_std']
+            ica_aroma_wf.inputs.inputnode.bold_mask_std = functional_cache['bold_mask_std']
             workflow.add_nodes([ica_aroma_wf])
 
-        ica_aroma_wf.inputs.inputnode.movpar_file = functional_cache["movpar_file"]
-        ica_aroma_wf.inputs.inputnode.skip_vols = functional_cache["skip_vols"]
-        ica_aroma_wf.inputs.inputnode.spatial_reference = functional_cache["spatial_reference"]
+        ica_aroma_wf.inputs.inputnode.movpar_file = functional_cache['movpar_file']
+        ica_aroma_wf.inputs.inputnode.skip_vols = functional_cache['skip_vols']
+        ica_aroma_wf.inputs.inputnode.spatial_reference = functional_cache['spatial_reference']
 
         # Now denoise the native-space BOLD data using ICA-AROMA
 

diff --git a/src/fmripost_aroma/workflows/resampling.py b/src/fmripost_aroma/workflows/resampling.py
@@ -11,21 +11,21 @@ def init_resample_raw_wf(bold_file, functional_cache):
 
     from fmripost_aroma.interfaces.resampler import Resampler
 
-    workflow = Workflow(name="resample_raw_wf")
+    workflow = Workflow(name='resample_raw_wf')
 
     inputnode = pe.Node(
-        niu.IdentityInterface(fields=["bold_file", "mask_file"]),
-        name="inputnode",
+        niu.IdentityInterface(fields=['bold_file', 'mask_file']),
+        name='inputnode',
     )
     inputnode.inputs.bold_file = bold_file
-    inputnode.inputs.mask_file = functional_cache["bold_mask"]
+    inputnode.inputs.mask_file = functional_cache['bold_mask']
 
     outputnode = pe.Node(
-        niu.IdentityInterface(fields=["bold_std", "bold_mask_std"]),
-        name="outputnode",
+        niu.IdentityInterface(fields=['bold_std', 'bold_mask_std']),
+        name='outputnode',
     )
 
-    stc_wf = init_bold_stc_wf(name="resample_stc_wf")
+    stc_wf = init_bold_stc_wf(name='resample_stc_wf')
     workflow.connect([
         (inputnode, stc_wf, [
             ('bold_file', 'inputnode.bold_file'),
@@ -34,17 +34,17 @@ def init_resample_raw_wf(bold_file, functional_cache):
     ])  # fmt:skip
 
     resample_bold = pe.Node(
-        Resampler(space="MNI152NLin6Asym", resolution="2"),
-        name="resample_bold",
+        Resampler(space='MNI152NLin6Asym', resolution='2'),
+        name='resample_bold',
     )
     workflow.connect([
         (stc_wf, resample_bold, [('outputnode.bold_file', 'bold_file')]),
         (resample_bold, outputnode, [('output_file', 'bold_std')]),
     ])  # fmt:skip
 
     resample_bold_mask = pe.Node(
-        Resampler(space="MNI152NLin6Asym", resolution="2"),
-        name="resample_bold_mask",
+        Resampler(space='MNI152NLin6Asym', resolution='2'),
+        name='resample_bold_mask',
     )
     workflow.connect([
         (inputnode, resample_bold_mask, [('mask_file', 'bold_file')]),