FIX: PEP8 - E303 too many blank lines (2)

Author: miykael

build_docs.py

@@ -72,7 +72,6 @@ class APIDocs(TempInstall):
         ('None', None, 'this command has no options'),
         ]
 
-
     def run(self):
         # First build the project and install it to a temporary location.
         TempInstall.run(self)
@@ -158,7 +157,6 @@ def zip_docs(self):
                                  os.path.join(relative, 'html_docs', f))
             zf.close()
 
-
         def finalize_options(self):
             """ Override the default for the documentation build
                 directory.

doc/sphinxext/numpy_ext/docscrape.py

@@ -192,7 +192,6 @@ def _parse_param_list(self, content):
 
         return params
 
-
     _name_rgx = re.compile(r"^\s*(:(?P<role>\w+):`(?P<name>[a-zA-Z0-9_.-]+)`|"
                            r" (?P<name2>[a-zA-Z0-9_.-]+))\s*", re.X)
 

doc/sphinxext/numpy_ext/docscrape_sphinx.py

@@ -5,7 +5,6 @@
 from nipype.external.six import string_types
 
 
-
 class SphinxDocString(NumpyDocString):
     def __init__(self, docstring, config={}):
         self.use_plots = config.get('use_plots', False)

examples/dmri_dtk_dti.py

@@ -159,7 +159,6 @@
                       ])
 
 
-
 """
 Setup for Tracktography
 -----------------------

examples/dmri_dtk_odf.py

@@ -160,7 +160,6 @@
                       ])
 
 
-
 """
 Setup for Tracktography
 -----------------------

examples/dmri_fsl_dti.py

@@ -172,7 +172,6 @@
                       ])
 
 
-
 """
 Setup for Tracktography
 -----------------------

examples/fmri_fsl.py

@@ -29,7 +29,6 @@
 import nipype.algorithms.rapidart as ra      # artifact detection
 
 
-
 """
 Preliminaries
 -------------

examples/fmri_openfmri.py

@@ -350,7 +350,6 @@ def split_files(in_files, splits):
     wf.connect(registration, 'outputspec.transformed_files',
                splitfunc, 'in_files')
 
-
     """
     Connect to a datasink
     """

examples/fmri_spm_auditory.py

@@ -87,7 +87,6 @@
 coregister.inputs.jobtype = 'estimate'
 
 
-
 segment = pe.Node(interface=spm.Segment(), name="segment")
 
 """Uncomment the following line for faster execution
@@ -201,7 +200,6 @@ def get_vox_dims(volume):
 """
 
 
-
 l1pipeline = pe.Workflow(name='firstlevel')
 l1pipeline.connect([(preproc, l1analysis, [('realign.realignment_parameters',
                                             'modelspec.realignment_parameters')])])
@@ -221,7 +219,6 @@ def makelist(item):
                                                 'modelspec.functional_runs')])])
 
 
-
 """
 Data specific components
 ------------------------

examples/fmri_spm_face.py

@@ -80,7 +80,6 @@
 coregister.inputs.jobtype = 'estimate'
 
 
-
 segment = pe.Node(interface=spm.Segment(), name="segment")
 segment.inputs.save_bias_corrected = True
 

examples/frontiers_paper/smoothing_comparison.py

@@ -54,7 +54,6 @@
                       'inputnode.mask_file')
 
 
-
 recon_all = pe.Node(interface=fs.ReconAll(), name="recon_all")
 
 surfregister = pe.Node(interface=fs.BBRegister(), name='surfregister')

examples/rsfmri_vol_surface_preprocessing.py

@@ -634,7 +634,6 @@ def create_workflow(files,
     registration.inputs.inputspec.subjects_dir = subjects_dir
     registration.inputs.inputspec.target_image = target_file
 
-
     """Use :class:`nipype.algorithms.rapidart` to determine which of the
     images in the functional series are outliers based on deviations in
     intensity or movement.
@@ -648,7 +647,6 @@ def create_workflow(files,
     art.inputs.mask_type = 'spm_global'
     art.inputs.parameter_source = 'SPM'
 
-
     """Here we are connecting all the nodes together. Notice that we add the merge node only if you choose
     to use 4D. Also `get_vox_dims` function is passed along the input volume of normalise to set the optimal
     voxel sizes.
@@ -698,7 +696,6 @@ def merge_files(in1, in2):
     wf.connect(art, 'norm_files', createfilter1, 'comp_norm')
     wf.connect(art, 'outlier_files', createfilter1, 'outliers')
 
-
     filter1 = MapNode(fsl.GLM(out_f_name='F_mcart.nii',
                               out_pf_name='pF_mcart.nii',
                               demean=True),
@@ -710,7 +707,6 @@ def merge_files(in1, in2):
                filter1, 'out_res_name')
     wf.connect(createfilter1, 'out_files', filter1, 'design')
 
-
     createfilter2 = MapNode(Function(input_names=['realigned_file', 'mask_file',
                                                   'num_components',
                                                   'extra_regressors'],
@@ -726,7 +722,6 @@ def merge_files(in1, in2):
     wf.connect(registration, ('outputspec.segmentation_files', selectindex, [0, 2]),
                createfilter2, 'mask_file')
 
-
     filter2 = MapNode(fsl.GLM(out_f_name='F.nii',
                               out_pf_name='pF.nii',
                               demean=True),

examples/rsfmri_vol_surface_preprocessing_nipy.py

@@ -508,7 +508,6 @@ def create_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
     """
@@ -517,7 +516,6 @@ def create_reg_workflow(name='registration'):
     register.connect(convert2itk, 'itk_transform', merge, 'in2')
     register.connect(reg, 'composite_transform', merge, 'in1')
 
-
     """
     Transform the mean image. First to anatomical and then to target
     """
@@ -535,7 +533,6 @@ def create_reg_workflow(name='registration'):
     register.connect(inputnode, 'mean_image', warpmean, 'input_image')
     register.connect(merge, 'out', warpmean, 'transforms')
 
-
     """
     Assign all the output files
     """
@@ -596,7 +593,6 @@ def create_workflow(files,
     realign.inputs.slice_info = 2
     realign.plugin_args = {'sbatch_args': '-c%d' % 4}
 
-
     # Comute TSNR on realigned data regressing polynomials upto order 2
     tsnr = MapNode(TSNR(regress_poly=2), iterfield=['in_file'], name='tsnr')
     wf.connect(realign, "out_file", tsnr, "in_file")
@@ -640,7 +636,6 @@ def create_workflow(files,
     art.inputs.mask_type = 'spm_global'
     art.inputs.parameter_source = 'NiPy'
 
-
     """Here we are connecting all the nodes together. Notice that we add the merge node only if you choose
     to use 4D. Also `get_vox_dims` function is passed along the input volume of normalise to set the optimal
     voxel sizes.
@@ -689,7 +684,6 @@ def merge_files(in1, in2):
     wf.connect(art, 'norm_files', createfilter1, 'comp_norm')
     wf.connect(art, 'outlier_files', createfilter1, 'outliers')
 
-
     filter1 = MapNode(fsl.GLM(out_f_name='F_mcart.nii.gz',
                               out_pf_name='pF_mcart.nii.gz',
                               demean=True),
@@ -701,7 +695,6 @@ def merge_files(in1, in2):
                filter1, 'out_res_name')
     wf.connect(createfilter1, 'out_files', filter1, 'design')
 
-
     createfilter2 = MapNode(Function(input_names=['realigned_file', 'mask_file',
                                                   'num_components',
                                                   'extra_regressors'],
@@ -717,7 +710,6 @@ def merge_files(in1, in2):
     wf.connect(registration, ('outputspec.segmentation_files', selectindex, [0, 2]),
                createfilter2, 'mask_file')
 
-
     filter2 = MapNode(fsl.GLM(out_f_name='F.nii.gz',
                               out_pf_name='pF.nii.gz',
                               demean=True),

nipype/algorithms/metrics.py

@@ -412,7 +412,6 @@ def _run_interface(self, runtime):
         img_ref = np.array([nb.load(fname).get_data() for fname in self.inputs.in_ref])
         img_tst = np.array([nb.load(fname).get_data() for fname in self.inputs.in_tst])
 
-
         msk = np.sum(img_ref, axis=0)
         msk[msk > 0] = 1.0
         tst_msk = np.sum(img_tst, axis=0)
@@ -447,7 +446,6 @@ def _run_interface(self, runtime):
         setattr(self, '_jaccard',  np.sum(weights * self._jaccards))
         setattr(self, '_dice', np.sum(weights * self._dices))
 
-
         diff = np.zeros(diff_im[0].shape)
 
         for w, ch in zip(weights, diff_im):
@@ -457,7 +455,6 @@ def _run_interface(self, runtime):
         nb.save(nb.Nifti1Image(diff, nb.load(self.inputs.in_ref[0]).get_affine(),
                                nb.load(self.inputs.in_ref[0]).get_header()), self.inputs.out_file)
 
-
         return runtime
 
     def _list_outputs(self):
@@ -631,7 +628,6 @@ def __init__(self, **inputs):
             self._have_nipy = False
         super(Similarity, self).__init__(**inputs)
 
-
     def _run_interface(self, runtime):
         if not self._have_nipy:
             raise RuntimeError('nipy is not installed')

nipype/algorithms/misc.py

@@ -1278,7 +1278,6 @@ def normalize_tpms(in_files, in_mask=None, out_files=[]):
 
     msk = np.ma.masked_equal(msk, 0)
 
-
     for i, out_file in enumerate(out_files):
         data = np.ma.masked_equal(img_data[i], 0)
         probmap = data / weights

nipype/algorithms/tests/test_errormap.py

@@ -26,7 +26,6 @@ def test_errormap():
 	nib.save(img2, os.path.join(tempdir, 'alan.nii.gz'))
 	nib.save(maskimg, os.path.join(tempdir, 'mask.nii.gz'))
 
-
 	# Default metric
 	errmap = ErrorMap()
 	errmap.inputs.in_tst = os.path.join(tempdir, 'von.nii.gz')

nipype/external/cloghandler.py

@@ -65,7 +65,6 @@
     codecs = None
 
 
-
 # Question/TODO: Should we have a fallback mode if we can't load portalocker /
 # we should still be better off than with the standard RotattingFileHandler
 # class, right? We do some rename checking... that should prevent some file

nipype/external/portalocker.py

@@ -124,7 +124,6 @@ def unlock(file):
         fcntl.flock(file.fileno(), fcntl.LOCK_UN)
 
 
-
 if __name__ == '__main__':
     from time import time, strftime, localtime
     import sys

nipype/external/provcopy.py

@@ -319,7 +319,6 @@ def json_representation(self):
                 #  Assuming it is a valid identifier
                 return {'$': str(self._value), 'type': self._datatype.get_uri()}
 
-
     def rdf_representation(self):
         if self._langtag:
             # a langtag can only goes with string

nipype/external/six.py

@@ -655,7 +655,6 @@ def assertRegex(self, *args, **kwargs):
 if PY3:
     exec_ = getattr(moves.builtins, "exec")
 
-
     def reraise(tp, value, tb=None):
         if value is None:
             value = tp()
@@ -676,7 +675,6 @@ def exec_(_code_, _globs_=None, _locs_=None):
             _locs_ = _globs_
         exec("""exec _code_ in _globs_, _locs_""")
 
-
     exec_("""def reraise(tp, value, tb=None):
     raise tp, value, tb
 """)

nipype/fixes/numpy/testing/noseclasses.py

@@ -93,7 +93,6 @@ def _find(self, tests, obj, name, module, source_lines, globs, seen):
                     self._find(tests, val, valname1, module, source_lines,
                                globs, seen)
 
-
         # Look for tests in a class's contained objects.
         if isclass(obj) and self._recurse:
             # print 'RECURSE into class:',obj  # dbg

nipype/interfaces/afni/base.py

@@ -111,7 +111,6 @@ class AFNICommand(CommandLine):
     input_spec = AFNICommandInputSpec
     _outputtype = None
 
-
     def __init__(self, **inputs):
         super(AFNICommand, self).__init__(**inputs)
         self.inputs.on_trait_change(self._output_update, 'outputtype')

nipype/interfaces/afni/preprocess.py

@@ -1407,7 +1407,6 @@ class TCorr1DInputSpec(AFNICommandInputSpec):
                         position=1)
 
 
-
 class TCorr1DOutputSpec(TraitedSpec):
     out_file = File(desc='output file containing correlations',
                     exists=True)

nipype/interfaces/ants/registration.py

@@ -670,7 +670,6 @@ def _formatWinsorizeImageIntensities(self):
         self._quantilesDone = True
         return '--winsorize-image-intensities [ %s, %s ]' % (self.inputs.winsorize_lower_quantile, self.inputs.winsorize_upper_quantile)
 
-
     def _format_arg(self, opt, spec, val):
         if opt == 'fixed_image_mask':
             if isdefined(self.inputs.moving_image_mask):

nipype/interfaces/ants/resampling.py

@@ -382,7 +382,6 @@ class ApplyTransformsToPoints(ANTSCommand):
     input_spec = ApplyTransformsToPointsInputSpec
     output_spec = ApplyTransformsToPointsOutputSpec
 
-
     def _getTransformFileNames(self):
         retval = []
         for ii in range(len(self.inputs.transforms)):

nipype/interfaces/camino/calib.py

@@ -131,7 +131,6 @@ def _gen_outfilename(self):
         return name + '_PICOCalib.Bfloat'
 
 
-
 class SFLUTGenInputSpec(StdOutCommandLineInputSpec):
     in_file = File(exists=True, argstr='-inputfile %s', mandatory=True,
                    desc='Voxel-order data of the spherical functions peaks.')

nipype/interfaces/camino/odf.py

@@ -92,7 +92,6 @@ def _gen_outfilename(self):
         return name + '_qmat.Bdouble'
 
 
-
 class LinReconInputSpec(StdOutCommandLineInputSpec):
     in_file = File(exists=True, argstr='%s', mandatory=True, position=1,
                    desc='voxel-order data filename')

nipype/interfaces/dynamic_slicer.py

@@ -21,8 +21,6 @@ class SlicerCommandLine(CommandLine):
     input_spec = SlicerCommandLineInputSpec
     output_spec = DynamicTraitedSpec
 
-
-
     def _grab_xml(self, module):
         cmd = CommandLine(command="Slicer3", args="--launch %s --xml" %module)
         ret = cmd.run()
@@ -66,7 +64,6 @@ def __init__(self, module, **inputs):
                 else:
                     traitsParams["argstr"] = "--" + name + " "
 
-
                 argsDict = {'file': '%s', 'integer': "%d", 'double': "%f", 'float': "%f", 'image': "%s", 'transform': "%s", 'boolean': '', 'string-enumeration': '%s', 'string': "%s"}
 
                 if param.nodeName.endswith('-vector'):
@@ -117,7 +114,6 @@ def __init__(self, module, **inputs):
             _ = getattr(self.inputs, name)
         # self._outputs().trait_set(trait_change_notify=False, **undefined_output_traits)
 
-
     def _gen_filename(self, name):
         if name in self._outputs_filenames:
             return os.path.join(os.getcwd(), self._outputs_filenames[name])