FIX: PEP8 - E262 inline comment should start with '# '

Author: miykael

examples/dmri_mrtrix_dti.py

@@ -22,7 +22,7 @@
 import nipype.interfaces.io as nio           # Data i/o
 import nipype.interfaces.utility as util     # utility
 import nipype.pipeline.engine as pe          # pypeline engine
-import nipype.interfaces.mrtrix as mrtrix   #<---- The important new part!
+import nipype.interfaces.mrtrix as mrtrix  # <---- The important new part!
 import nipype.interfaces.fsl as fsl
 import nipype.algorithms.misc as misc
 import os, os.path as op                     # system functions

nipype/external/cloghandler.py

@@ -319,7 +319,7 @@ def shouldRollover(self, record):
     def _shouldRollover(self):
         if self.maxBytes > 0:                   # are we rolling over?
             try:
-                self.stream.seek(0, 2)  #due to non-posix-compliant Windows feature
+                self.stream.seek(0, 2)  # due to non-posix-compliant Windows feature
             except IOError:
                 return True
             if self.stream.tell() >= self.maxBytes:

nipype/interfaces/spm/model.py

@@ -116,7 +116,7 @@ def _format_arg(self, opt, spec, val):
         """
         if opt in ['spm_mat_dir', 'mask_image']:
             return np.array([str(val)], dtype=object)
-        if opt in ['session_info']:  #, 'factor_info']:
+        if opt in ['session_info']:  # , 'factor_info']:
             if isinstance(val, dict):
                 return [val]
             else:
@@ -719,7 +719,7 @@ class FactorialDesignInputSpec(SPMCommandInputSpec):
                                            desc='threshold using a proportion of the global value')
     use_implicit_threshold = traits.Bool(field='masking.im',
                                          desc='use implicit mask NaNs or zeros to threshold')
-    explicit_mask_file = File(field='masking.em',  #requires cell
+    explicit_mask_file = File(field='masking.em',  # requires cell
                               desc='use an implicit mask file to threshold')
     global_calc_omit = traits.Bool(field='globalc.g_omit',
                                    xor=['global_calc_mean', 'global_calc_values'],