FIX: PEP8 - E222 multiple spaces after operator

Author: miykael

examples/smri_ants_registration.py

@@ -58,7 +58,7 @@
 """
 
 reg = Registration()
-reg.inputs.fixed_image =  input_images[0]
+reg.inputs.fixed_image = input_images[0]
 reg.inputs.moving_image = input_images[1]
 reg.inputs.output_transform_prefix = 'thisTransform'
 reg.inputs.output_warped_image = 'INTERNAL_WARPED.nii.gz'

nipype/algorithms/metrics.py

@@ -401,7 +401,7 @@ class FuzzyOverlap(BaseInterface):
     >>> res = overlap.run() # doctest: +SKIP
     """
 
-    input_spec =  FuzzyOverlapInputSpec
+    input_spec = FuzzyOverlapInputSpec
     output_spec = FuzzyOverlapOutputSpec
 
     def _run_interface(self, runtime):
@@ -466,8 +466,8 @@ def _list_outputs(self):
             outputs[method] = getattr(self, '_' + method)
         #outputs['volume_difference'] = self._volume
         outputs['diff_file'] = os.path.abspath(self.inputs.out_file)
-        outputs['class_fji'] =  np.array(self._jaccards).astype(float).tolist();
-        outputs['class_fdi']=  self._dices.astype(float).tolist();
+        outputs['class_fji'] = np.array(self._jaccards).astype(float).tolist();
+        outputs['class_fdi']= self._dices.astype(float).tolist();
         return outputs
 
 

nipype/algorithms/misc.py

@@ -100,7 +100,7 @@ def _get_brodmann_area(self):
         for lab in labels:
             newdata[origdata == lab] = 1
         if self.inputs.hemi == 'right':
-            newdata[int(floor(float(origdata.shape[0]) /  2)):, :, :] = 0
+            newdata[int(floor(float(origdata.shape[0]) / 2)):, :, :] = 0
         elif self.inputs.hemi == 'left':
             newdata[:int(ceil(float(origdata.shape[0]) / 2)), :, :] = 0
 

nipype/algorithms/tests/test_normalize_tpms.py

@@ -29,7 +29,7 @@ def test_normalize_tpms():
 
     for i in range(3):
         mapname = example_data('tpm_%02d.nii.gz' % i)
-        filename =  os.path.join(tempdir, 'modtpm_%02d.nii.gz' % i)
+        filename = os.path.join(tempdir, 'modtpm_%02d.nii.gz' % i)
         out_files.append(os.path.join(tempdir, 'normtpm_%02d.nii.gz' % i))
 
         im = nb.load(mapname)

nipype/interfaces/afni/preprocess.py

@@ -1534,7 +1534,7 @@ class ROIStatsInputSpec(CommandLineInputSpec):
 
 
 class ROIStatsOutputSpec(TraitedSpec):
-    stats =  File(desc='output tab separated values file', exists=True)
+    stats = File(desc='output tab separated values file', exists=True)
 
 
 class ROIStats(CommandLine):

nipype/interfaces/dcmstack.py

@@ -185,7 +185,7 @@ def _run_interface(self, runtime):
         for key, stack in stacks.items():
             nw = NiftiWrapper(stack.to_nifti(embed_meta=True))
             const_meta = nw.meta_ext.get_class_dict(('global', 'const'))
-            out_path =  self._get_out_path(const_meta)
+            out_path = self._get_out_path(const_meta)
             if not self.inputs.embed_meta:
                 nw.remove_extension()
             nb.save(nw.nii_img, out_path)

nipype/interfaces/fsl/tests/test_maths.py

@@ -74,9 +74,9 @@ def test_maths_base(fsl_output_type=None):
 
     # Now test that we can set the various data types
     dtypes = ["float","char","int","short","double","input"]
-    int_cmdline =  "fslmaths -dt %s a.nii " + os.path.join(testdir, out_file)
-    out_cmdline =  "fslmaths a.nii " + os.path.join(testdir, out_file) + " -odt %s"
-    duo_cmdline =  "fslmaths -dt %s a.nii " + os.path.join(testdir, out_file) + " -odt %s"
+    int_cmdline = "fslmaths -dt %s a.nii " + os.path.join(testdir, out_file)
+    out_cmdline = "fslmaths a.nii " + os.path.join(testdir, out_file) + " -odt %s"
+    duo_cmdline = "fslmaths -dt %s a.nii " + os.path.join(testdir, out_file) + " -odt %s"
     for dtype in dtypes:
         foo = fsl.MathsCommand(in_file="a.nii", internal_datatype=dtype)
         yield assert_equal, foo.cmdline, int_cmdline%dtype
@@ -116,7 +116,7 @@ def test_changedt(fsl_output_type=None):
 
     # Now test that we can set the various data types
     dtypes = ["float","char","int","short","double","input"]
-    cmdline =  "fslmaths a.nii b.nii -odt %s"
+    cmdline = "fslmaths a.nii b.nii -odt %s"
     for dtype in dtypes:
         foo = fsl.MathsCommand(in_file="a.nii",out_file="b.nii",output_datatype=dtype)
         yield assert_equal, foo.cmdline, cmdline%dtype

nipype/interfaces/nipy/model.py

@@ -137,7 +137,7 @@ def _run_interface(self, runtime):
 
 
         if conditions:
-            paradigm =  BlockParadigm(con_id=conditions, onset=onsets, duration=duration)
+            paradigm = BlockParadigm(con_id=conditions, onset=onsets, duration=duration)
         else:
             paradigm = None
         design_matrix, self._reg_names = dm.dmtx_light(frametimes, paradigm, drift_model=drift_model, hfcut=hpf,

nipype/utils/matlabtools.py

@@ -56,7 +56,7 @@ def mlab_tempfile(dir=None):
         f = tempfile.NamedTemporaryFile(suffix='.m',prefix='tmp_matlab_',
                                         dir=dir)
         # Check the file name for matlab compilance
-        fname =  os.path.splitext(os.path.basename(f.name))[0]
+        fname = os.path.splitext(os.path.basename(f.name))[0]
         if valid_name.match(fname):
             break
         # Close the temp file we just made if its name is not valid; the

nipype/workflows/smri/ants/antsRegistrationBuildTemplate.py

@@ -189,17 +189,17 @@ def antsRegistrationTemplateBuildSingleIterationWF(iterationPhasePrefix=''):
     BeginANTS=pe.MapNode(interface=Registration(), name = 'BeginANTS', iterfield=['moving_image'])
     BeginANTS.inputs.dimension = 3
     BeginANTS.inputs.output_transform_prefix = str(iterationPhasePrefix)+'_tfm'
-    BeginANTS.inputs.transforms =               ["Affine",          "SyN"]
-    BeginANTS.inputs.transform_parameters =     [[0.9],             [0.25,3.0,0.0]]
-    BeginANTS.inputs.metric =                   ['Mattes',          'CC']
-    BeginANTS.inputs.metric_weight =            [1.0,               1.0]
+    BeginANTS.inputs.transforms = ["Affine",          "SyN"]
+    BeginANTS.inputs.transform_parameters = [[0.9],             [0.25,3.0,0.0]]
+    BeginANTS.inputs.metric = ['Mattes',          'CC']
+    BeginANTS.inputs.metric_weight = [1.0,               1.0]
     BeginANTS.inputs.radius_or_number_of_bins = [32,                5]
     BeginANTS.inputs.number_of_iterations = [[1000, 1000, 1000], [50, 35, 15]]
-    BeginANTS.inputs.use_histogram_matching =   [True,               True]
+    BeginANTS.inputs.use_histogram_matching = [True,               True]
     BeginANTS.inputs.use_estimate_learning_rate_once = [False,       False]
-    BeginANTS.inputs.shrink_factors =           [[3,2,1],            [3,2,1]]
-    BeginANTS.inputs.smoothing_sigmas =         [[3,2,0],            [3,2,0]]
-    BeginANTS.inputs.sigma_units =         ["vox"]*2
+    BeginANTS.inputs.shrink_factors = [[3,2,1],            [3,2,1]]
+    BeginANTS.inputs.smoothing_sigmas = [[3,2,0],            [3,2,0]]
+    BeginANTS.inputs.sigma_units = ["vox"]*2
 
     GetMovingImagesNode = pe.Node(interface=util.Function(function=GetMovingImages,
                                                           input_names=['ListOfImagesDictionaries','registrationImageTypes','interpolationMapping'],