clean up white spaces

Author: chrisgorgo

examples/fmri_ants_openfmri.py

@@ -228,7 +228,6 @@ def create_reg_workflow(name='registration'):
     register.connect(stripper, 'out_file', reg, 'moving_image')
     register.connect(inputnode,'target_image_brain', reg,'fixed_image')
 
-
     """
     Concatenate the affine and ants transforms into a list
     """
@@ -239,7 +238,6 @@ def create_reg_workflow(name='registration'):
     register.connect(convert2itk, 'itk_transform', merge, 'in2')
     register.connect(reg, ('composite_transform', pickfirst), merge, 'in1')
 
-
     """
     Transform the mean image. First to anatomical and then to target
     """
@@ -271,7 +269,6 @@ def create_reg_workflow(name='registration'):
     register.connect(inputnode,'source_files', warpall, 'input_image')
     register.connect(merge, 'out', warpall, 'transforms')
 
-
     """
     Assign all the output files
     """
@@ -379,6 +376,7 @@ def create_fs_reg_workflow(name='registration'):
     """
     Apply inverse transform to aparc file
     """
+    
     aparcxfm = Node(freesurfer.ApplyVolTransform(inverse=True,
                                                  interp='nearest'),
                     name='aparc_inverse_transform')
@@ -439,7 +437,6 @@ def create_fs_reg_workflow(name='registration'):
     register.connect(stripper, 'out_file', reg, 'moving_image')
     register.connect(inputnode,'target_image', reg,'fixed_image')
 
-
     """
     Concatenate the affine and ants transforms into a list
     """
@@ -450,10 +447,10 @@ def create_fs_reg_workflow(name='registration'):
     register.connect(convert2itk, 'itk_transform', merge, 'in2')
     register.connect(reg, ('composite_transform', pickfirst), merge, 'in1')
 
-
     """
     Transform the mean image. First to anatomical and then to target
     """
+    
     warpmean = Node(ants.ApplyTransforms(), name='warpmean')
     warpmean.inputs.input_image_type = 0
     warpmean.inputs.interpolation = 'Linear'
@@ -492,7 +489,6 @@ def create_fs_reg_workflow(name='registration'):
     register.connect(inputnode,'source_files', warpall, 'input_image')
     register.connect(merge, 'out', warpall, 'transforms')
 
-
     """
     Assign all the output files
     """
@@ -659,6 +655,7 @@ def analyze_openfmri_dataset(data_dir, subject=None, model_id=None,
     """
     Return data components as anat, bold and behav
     """
+    
     contrast_file = os.path.join(data_dir, 'models', 'model%03d' % model_id,
                                  'task_contrasts.txt')
     has_contrast = os.path.exists(contrast_file)

examples/rsfmri_vol_surface_preprocessing_nipy.py

@@ -433,6 +433,7 @@ def create_reg_workflow(name='registration'):
     """
     Apply inverse transform to take segmentations to functional space
     """
+    
     applyxfm = MapNode(freesurfer.ApplyVolTransform(inverse=True,
                                                     interp='nearest'),
                        iterfield=['target_file'],
@@ -445,6 +446,7 @@ def create_reg_workflow(name='registration'):
     """
     Apply inverse transform to aparc file
     """
+    
     aparcxfm = Node(freesurfer.ApplyVolTransform(inverse=True,
                                                  interp='nearest'),
                     name='aparc_inverse_transform')
@@ -519,6 +521,7 @@ def create_reg_workflow(name='registration'):
     """
     Transform the mean image. First to anatomical and then to target
     """
+    
     warpmean = Node(ants.ApplyTransforms(), name='warpmean')
     warpmean.inputs.input_image_type = 3
     warpmean.inputs.interpolation = 'Linear'
@@ -608,6 +611,7 @@ def create_workflow(files,
 
     """Segment and Register
     """
+    
     registration = create_reg_workflow(name='registration')
     wf.connect(calc_median, 'median_file', registration, 'inputspec.mean_image')
     registration.inputs.inputspec.subject_id = subject_id
@@ -616,6 +620,7 @@ def create_workflow(files,
 
     """Quantify TSNR in each freesurfer ROI
     """
+    
     get_roi_tsnr = MapNode(fs.SegStats(default_color_table=True),
                            iterfield=['in_file'], name='get_aparc_tsnr')
     get_roi_tsnr.inputs.avgwf_txt_file = True
@@ -951,7 +956,6 @@ def get_names(files, suffix):
 Creates the full workflow including getting information from dicom files
 """
 
-
 def create_resting_workflow(args, name=None):
     TR = args.TR
     slice_times = args.slice_times