Commiting again same thing

nipype/interfaces/camino/dti.py

@@ -66,56 +66,56 @@ def _gen_outfilename(self):
  return name + '_DT.Bdouble'
 
 class DTMetricInputSpec(CommandLineInputSpec):
- eigen_data = File(exists=True, argstr='-inputfile %s', mandatory=True, 
+ eigen_data = File(exists=True, argstr='-inputfile %s', mandatory=True,
  desc='voxel-order data filename')
 
  metric = traits.Enum('fa','md','rd','l1', 'l2', 'l3', 'tr', 'ra', '2dfa','cl','cp','cs',
  argstr='-stat %s', mandatory=True,
  desc=('Specifies the metric to compute. Possible choices are: '
  '"fa", "md", "rd", "l1", "l2", "l3", "tr", "ra", "2dfa", "cl", "cp" or "cs".'))
 
- inputdatatype = traits.Enum('double', 'float', 'long', 'int', 'short', 'char', 
+ inputdatatype = traits.Enum('double', 'float', 'long', 'int', 'short', 'char',
  argstr='-inputdatatype %s', usedefault=True,
  desc=('Specifies the data type of the input data. '
  'The data type can be any of the following strings: '
  '"char", "short", "int", "long", "float" or "double".'
  'Default is double data type'))
 
- outputdatatype = traits.Enum('double', 'float', 'long', 'int', 'short', 'char', 
+ outputdatatype = traits.Enum('double', 'float', 'long', 'int', 'short', 'char',
  argstr='-outputdatatype %s', usedefault=True,
  desc=('Specifies the data type of the output data. '
  'The data type can be any of the following strings: '
  '"char", "short", "int", "long", "float" or "double".'
  'Default is double data type'))
- 
+
  data_header = File(argstr='-header %s', exists=True,
  desc=('A Nifti .nii or .nii.gz file containing the header information. '
  'Usually this will be the header of the raw data file from which '
  'the diffusion tensors were reconstructed.'))
- 
+
  outputfile = File(argstr='-outputfile %s', genfile=True,
  desc=('Output name. Output will be a .nii.gz file if data_header is provided and'
  'in voxel order with outputdatatype datatype (default: double) otherwise.'))
- 
+
 class DTMetricOutputSpec(TraitedSpec):
  metric_stats = File(exists=True, desc='Diffusion Tensor statistics of the chosen metric')
 
 class DTMetric(CommandLine):
  """
  Computes tensor metric statistics based on the eigenvalues l1 >= l2 >= l3
  typically obtained from ComputeEigensystem.
- 
+
  The full list of statistics is:
- 
+
  <cl> = (l1 - l2) / l1 , a measure of linearity
  <cp> = (l2 - l3) / l1 , a measure of planarity
  <cs> = l3 / l1 , a measure of isotropy
- with: cl + cp + cs = 1 
- 
+ with: cl + cp + cs = 1
+
  <l1> = first eigenvalue
  <l2> = second eigenvalue
  <l3> = third eigenvalue
- 
+
  <tr> = l1 + l2 + l3
  <md> = tr / 3
  <rd> = (l2 + l3) / 2
@@ -129,7 +129,7 @@ class DTMetric(CommandLine):
  Example
  -------
  Compute the CP planar metric as float data type.
- 
+
  >>> import nipype.interfaces.camino as cam
  >>> dtmetric = cam.DTMetric()
  >>> dtmetric.inputs.eigen_data = 'dteig.Bdouble'
@@ -793,14 +793,14 @@ class ComputeEigensystemInputSpec(StdOutCommandLineInputSpec):
 
  maxcomponents = traits.Int(argstr='-maxcomponents %d', desc='The maximum number of tensor components in a voxel of the input data.')
 
- inputdatatype = traits.Enum('double', 'float', 'long', 'int', 'short', 'char', 
+ inputdatatype = traits.Enum('double', 'float', 'long', 'int', 'short', 'char',
  argstr='-inputdatatype %s', usedefault=True,
  desc=('Specifies the data type of the input data. '
  'The data type can be any of the following strings: '
  '"char", "short", "int", "long", "float" or "double".'
  'Default is double data type'))
 
- outputdatatype = traits.Enum('double', 'float', 'long', 'int', 'short', 'char', 
+ outputdatatype = traits.Enum('double', 'float', 'long', 'int', 'short', 'char',
  argstr='-outputdatatype %s', usedefault=True,
  desc=('Specifies the data type of the output data. '
  'The data type can be any of the following strings: '