fix shells options, merge master

Author: oesteban

nipype/interfaces/mrtrix3/preprocess.py

@@ -46,7 +46,7 @@ class ResponseSDInputSpec(CommandLineInputSpec):
 
     # DW Shell selection options
 
-    shell = traits.List(traits.Float, sep=',', argstr='-shell %f',
+    shell = traits.List(traits.Float, sep=',', argstr='-shell %s',
                         desc='specify one or more dw gradient shells')
     in_mask = File(exists=True, argstr='-mask %s',
                    desc='provide initial mask image')

nipype/interfaces/mrtrix3/reconst.py

@@ -21,6 +21,7 @@
 from nipype.utils.filemanip import split_filename
 from nipype.interfaces.traits_extension import isdefined
 
+
 class FitTensorInputSpec(CommandLineInputSpec):
     in_file = File(exists=True, argstr='%s', mandatory=True, position=-2,
                    desc='input diffusion weighted images')
@@ -30,17 +31,16 @@ class FitTensorInputSpec(CommandLineInputSpec):
 
     # General options
     in_mask = File(exists=True, argstr='-mask %s',
-                   desc=('only perform computation within the specified binary '
-                         'brain mask image'))
+                   desc=('only perform computation within the specified '
+                         'binary brain mask image'))
     method = traits.Enum(
         'nonlinear', 'loglinear', 'sech', 'rician', argstr='-method %s',
         desc=('select method used to perform the fitting'))
     reg_term = traits.Float(
         5.e3, argstr='-regularisation %f',
-        desc=('specify the strength of the regularisation term on the magnitude '
-              'of the tensor elements (default = 5000). This only applies to the '
-              'non-linear methods'))
-
+        desc=('specify the strength of the regularisation term on the '
+              'magnitude of the tensor elements (default = 5000). This '
+              'only applies to the non-linear methods'))
 
     # DW gradient table import options
     grad_file = File(exists=True, argstr='-grad %s',
@@ -100,7 +100,8 @@ class EstimateFODInputSpec(CommandLineInputSpec):
               'function coefficients for a single fibre population'))
     out_file = File(
         'fods.mif', argstr='%s', mandatory=True, position=-1,
-        usedefault=True, desc='the output spherical harmonics coefficients image')
+        usedefault=True, desc=('the output spherical harmonics coefficients'
+                               ' image'))
 
     # DW gradient table import options
     grad_file = File(exists=True, argstr='-grad %s',
@@ -118,7 +119,7 @@ class EstimateFODInputSpec(CommandLineInputSpec):
               'false, 0 / 1 (default: true).'))
 
     # DW Shell selection options
-    shell = traits.List(traits.Float, sep=',', argstr='-shell %f',
+    shell = traits.List(traits.Float, sep=',', argstr='-shell %s',
                         desc='specify one or more dw gradient shells')
 
     # Spherical deconvolution options
@@ -217,4 +218,4 @@ class EstimateFOD(CommandLine):
     def _list_outputs(self):
         outputs = self.output_spec().get()
         outputs['out_file'] = op.abspath(self.inputs.out_file)
-        return outputs
+        return outputs

nipype/interfaces/mrtrix3/tests/test_auto_EstimateFOD.py

@@ -42,7 +42,7 @@ def test_EstimateFOD_inputs():
     ),
     sh_filter=dict(argstr='-filter %s',
     ),
-    shell=dict(argstr='-shell %f',
+    shell=dict(argstr='-shell %s',
     sep=',',
     ),
     terminal_output=dict(nohash=True,

nipype/interfaces/mrtrix3/tests/test_auto_ResponseSD.py

@@ -40,7 +40,7 @@ def test_ResponseSD_inputs():
     ),
     out_sf=dict(argstr='-sf %s',
     ),
-    shell=dict(argstr='-shell %f',
+    shell=dict(argstr='-shell %s',
     sep=',',
     ),
     terminal_output=dict(nohash=True,

nipype/interfaces/mrtrix3/utils.py

@@ -43,6 +43,7 @@ class BrainMaskInputSpec(CommandLineInputSpec):
               'BValueScaling entry. Valid choices are yes / no, true / '
               'false, 0 / 1 (default: true).'))
 
+
 class BrainMaskOutputSpec(TraitedSpec):
     out_file = File(exists=True, desc='the output response file')
 
@@ -74,7 +75,6 @@ def _list_outputs(self):
         return outputs
 
 
-
 class Mesh2PVEInputSpec(CommandLineInputSpec):
     in_file = File(exists=True, argstr='%s', mandatory=True, position=-3,
                    desc='input mesh')
@@ -184,10 +184,12 @@ class TensorMetricsInputSpec(CommandLineInputSpec):
         desc=('specify the desired eigenvalue/eigenvector(s). Note that '
               'several eigenvalues can be specified as a number sequence'))
     in_mask = File(exists=True, argstr='-mask %s',
-                   desc=('only perform computation within the specified binary '
-                         'brain mask image'))
+                   desc=('only perform computation within the specified binary'
+                         ' brain mask image'))
     modulate = traits.Enum('FA', 'none', 'eval', argstr='-modulate %s',
-                           desc='how to modulate the magnitude of the eigenvectors')
+                           desc=('how to modulate the magnitude of the'
+                                 ' eigenvectors'))
+
 
 class TensorMetricsOutputSpec(TraitedSpec):
     out_fa = File(desc='output FA file')
@@ -225,4 +227,4 @@ def _list_outputs(self):
             if isdefined(getattr(self.inputs, k)):
                 outputs[k] = op.abspath(getattr(self.inputs, k))
 
-        return outputs
+        return outputs