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miykaelmiykael
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FIX: PEP8 - E225 missing whitespace around operator
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‎examples/dmri_dtk_dti.py

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -125,23 +125,23 @@
125125
"""
126126

127127
fslroi = pe.Node(interface=fsl.ExtractROI(),name='fslroi')
128-
fslroi.inputs.t_min=0
129-
fslroi.inputs.t_size=1
128+
fslroi.inputs.t_min = 0
129+
fslroi.inputs.t_size = 1
130130

131131
"""
132132
create a brain mask from the nodif_brain
133133
"""
134134

135135
bet = pe.Node(interface=fsl.BET(),name='bet')
136-
bet.inputs.mask=True
137-
bet.inputs.frac=0.34
136+
bet.inputs.mask = True
137+
bet.inputs.frac = 0.34
138138

139139
"""
140140
correct the diffusion weighted images for eddy_currents
141141
"""
142142

143143
eddycorrect = create_eddy_correct_pipeline('eddycorrect')
144-
eddycorrect.inputs.inputnode.ref_num=0
144+
eddycorrect.inputs.inputnode.ref_num = 0
145145

146146
"""
147147
compute the diffusion tensor in each voxel

‎examples/dmri_dtk_odf.py

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -125,23 +125,23 @@
125125
"""
126126

127127
fslroi = pe.Node(interface=fsl.ExtractROI(),name='fslroi')
128-
fslroi.inputs.t_min=0
129-
fslroi.inputs.t_size=1
128+
fslroi.inputs.t_min = 0
129+
fslroi.inputs.t_size = 1
130130

131131
"""
132132
create a brain mask from the nodif_brain
133133
"""
134134

135135
bet = pe.Node(interface=fsl.BET(),name='bet')
136-
bet.inputs.mask=True
137-
bet.inputs.frac=0.34
136+
bet.inputs.mask = True
137+
bet.inputs.frac = 0.34
138138

139139
"""
140140
correct the diffusion weighted images for eddy_currents
141141
"""
142142

143143
eddycorrect = create_eddy_correct_pipeline('eddycorrect')
144-
eddycorrect.inputs.inputnode.ref_num=0
144+
eddycorrect.inputs.inputnode.ref_num = 0
145145

146146

147147
hardi_mat = pe.Node(interface=dtk.HARDIMat(),name='hardi_mat')

‎examples/dmri_fsl_dti.py

Lines changed: 12 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -136,23 +136,23 @@
136136
"""
137137

138138
fslroi = pe.Node(interface=fsl.ExtractROI(),name='fslroi')
139-
fslroi.inputs.t_min=0
140-
fslroi.inputs.t_size=1
139+
fslroi.inputs.t_min = 0
140+
fslroi.inputs.t_size = 1
141141

142142
"""
143143
create a brain mask from the nodif_brain
144144
"""
145145

146146
bet = pe.Node(interface=fsl.BET(),name='bet')
147-
bet.inputs.mask=True
148-
bet.inputs.frac=0.34
147+
bet.inputs.mask = True
148+
bet.inputs.frac = 0.34
149149

150150
"""
151151
correct the diffusion weighted images for eddy_currents
152152
"""
153153

154154
eddycorrect = create_eddy_correct_pipeline('eddycorrect')
155-
eddycorrect.inputs.inputnode.ref_num=0
155+
eddycorrect.inputs.inputnode.ref_num = 0
156156

157157
"""
158158
compute the diffusion tensor in each voxel
@@ -201,14 +201,14 @@
201201
"""
202202

203203
probtrackx = pe.Node(interface=fsl.ProbTrackX(),name='probtrackx')
204-
probtrackx.inputs.mode='seedmask'
204+
probtrackx.inputs.mode = 'seedmask'
205205
probtrackx.inputs.c_thresh = 0.2
206-
probtrackx.inputs.n_steps=2000
207-
probtrackx.inputs.step_length=0.5
208-
probtrackx.inputs.n_samples=5000
209-
probtrackx.inputs.opd=True
210-
probtrackx.inputs.os2t=True
211-
probtrackx.inputs.loop_check=True
206+
probtrackx.inputs.n_steps = 2000
207+
probtrackx.inputs.step_length = 0.5
208+
probtrackx.inputs.n_samples = 5000
209+
probtrackx.inputs.opd = True
210+
probtrackx.inputs.os2t = True
211+
probtrackx.inputs.loop_check = True
212212

213213

214214
"""

‎examples/fmri_ants_openfmri.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -935,7 +935,7 @@ def split_files(in_files, splits):
935935

936936
def get_subs(subject_id, conds, run_id, model_id, task_id):
937937
subs = [('_subject_id_%s_' % subject_id, '')]
938-
subs.append(('_model_id_%d' % model_id, 'model%03d' %model_id))
938+
subs.append(('_model_id_%d' % model_id, 'model%03d' % model_id))
939939
subs.append(('task_id_%d/' % task_id, '/task%03d_' % task_id))
940940
subs.append(('bold_dtype_mcf_mask_smooth_mask_gms_tempfilt_mean_warp',
941941
'mean'))

‎examples/fmri_fsl.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -551,7 +551,7 @@ def num_copes(files):
551551
"""
552552

553553
smoothnode = firstlevel.get_node('preproc.smooth')
554-
assert(str(smoothnode)=='preproc.smooth')
554+
assert(str(smoothnode) == 'preproc.smooth')
555555
smoothnode.iterables = ('fwhm', [5.,10.])
556556

557557
hpcutoff = 120

‎examples/fmri_openfmri.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -357,7 +357,7 @@ def split_files(in_files, splits):
357357

358358
def get_subs(subject_id, conds, model_id, task_id):
359359
subs = [('_subject_id_%s_' % subject_id, '')]
360-
subs.append(('_model_id_%d' % model_id, 'model%03d' %model_id))
360+
subs.append(('_model_id_%d' % model_id, 'model%03d' % model_id))
361361
subs.append(('task_id_%d/' % task_id, '/task%03d_' % task_id))
362362
subs.append(('bold_dtype_mcf_mask_smooth_mask_gms_tempfilt_mean_warp',
363363
'mean'))

‎examples/fmri_spm.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -353,7 +353,7 @@ def getstripdir(subject_id):
353353
contrast_ids = list(range(1,len(contrasts)+1))
354354
l2source = pe.Node(nio.DataGrabber(infields=['fwhm', 'con']), name="l2source")
355355
# we use .*i* to capture both .img (SPM8) and .nii (SPM12)
356-
l2source.inputs.template=os.path.abspath('spm_tutorial/l1output/*/con*/*/_fwhm_%d/con_%04d.*i*')
356+
l2source.inputs.template = os.path.abspath('spm_tutorial/l1output/*/con*/*/_fwhm_%d/con_%04d.*i*')
357357
# iterate over all contrast images
358358
l2source.iterables = [('fwhm',fwhmlist),
359359
('con',contrast_ids)]

‎examples/fmri_spm_auditory.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -70,7 +70,7 @@
7070

7171
if merge_to_4d:
7272
merge = pe.Node(interface=fsl.Merge(), name="merge")
73-
merge.inputs.dimension="t"
73+
merge.inputs.dimension = "t"
7474

7575
"""Use :class:`nipype.interfaces.spm.Realign` for motion correction
7676
and register all images to the mean image.

‎examples/fmri_spm_dartel.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -169,8 +169,8 @@
169169

170170
overlaystats = pe.Node(interface=fsl.Overlay(), name="overlaystats")
171171
overlaystats.inputs.stat_thresh = (3,10)
172-
overlaystats.inputs.show_negative_stats=True
173-
overlaystats.inputs.auto_thresh_bg=True
172+
overlaystats.inputs.show_negative_stats = True
173+
overlaystats.inputs.auto_thresh_bg = True
174174

175175
"""Use :class:`nipype.interfaces.fsl.Slicer` to create images of the overlaid
176176
statistical volumes for a report of the first-level results.
@@ -485,7 +485,7 @@ def getstripdir(subject_id):
485485
contrast_ids = list(range(1,len(contrasts)+1))
486486
l2source = pe.Node(nio.DataGrabber(infields=['fwhm', 'con']), name="l2source")
487487
# we use .*i* to capture both .img (SPM8) and .nii (SPM12)
488-
l2source.inputs.template=os.path.abspath('spm_dartel_tutorial/l1output/*/con*/*/_fwhm_%d/con_%04d.*i*')
488+
l2source.inputs.template = os.path.abspath('spm_dartel_tutorial/l1output/*/con*/*/_fwhm_%d/con_%04d.*i*')
489489
# iterate over all contrast images
490490
l2source.iterables = [('fwhm',fwhmlist),
491491
('con',contrast_ids)]

‎examples/fmri_spm_nested.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -175,8 +175,8 @@
175175

176176
overlaystats = pe.Node(interface=fsl.Overlay(), name="overlaystats")
177177
overlaystats.inputs.stat_thresh = (3,10)
178-
overlaystats.inputs.show_negative_stats=True
179-
overlaystats.inputs.auto_thresh_bg=True
178+
overlaystats.inputs.show_negative_stats = True
179+
overlaystats.inputs.auto_thresh_bg = True
180180

181181
"""Use :class:`nipype.interfaces.fsl.Slicer` to create images of the overlaid
182182
statistical volumes for a report of the first-level results.
@@ -439,7 +439,7 @@ def getstripdir(subject_id):
439439
contrast_ids = list(range(1,len(contrasts)+1))
440440
l2source = pe.Node(nio.DataGrabber(infields=['fwhm', 'con']), name="l2source")
441441
# we use .*i* to capture both .img (SPM8) and .nii (SPM12)
442-
l2source.inputs.template=os.path.abspath('spm_tutorial2/l1output/*/con*/*/_fwhm_%d/con_%04d.*i*')
442+
l2source.inputs.template = os.path.abspath('spm_tutorial2/l1output/*/con*/*/_fwhm_%d/con_%04d.*i*')
443443
# iterate over all contrast images
444444
l2source.iterables = [('fwhm',fwhmlist),
445445
('con',contrast_ids)]

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