cleaned up interfaces

Author: satra

nipype/interfaces/afni/tests/test_auto_Autobox.py

@@ -20,6 +20,7 @@ def test_Autobox_inputs():
     ),
     out_file=dict(argstr='-prefix %s',
     name_source='in_file',
+    name_template='%s_autobox',
     ),
     outputtype=dict(),
     padding=dict(argstr='-npad %d',

nipype/interfaces/ants/tests/test_auto_Registration.py

@@ -104,6 +104,8 @@ def test_Registration_inputs():
     use_estimate_learning_rate_once=dict(),
     use_histogram_matching=dict(usedefault=True,
     ),
+    verbose=dict(argstr='-v',
+    ),
     winsorize_lower_quantile=dict(argstr='%s',
     usedefault=True,
     ),

nipype/interfaces/fsl/__init__.py

@@ -19,16 +19,15 @@
                     SwapDimensions, PowerSpectrum, Reorient2Std,
                     Complex, InvWarp, WarpUtils, ConvertWarp, WarpPoints,
                     WarpPointsToStd, RobustFOV, CopyGeom, MotionOutliers)
-
 from .epi import (PrepareFieldmap, TOPUP, ApplyTOPUP, Eddy, EPIDeWarp,
                   SigLoss, EddyCorrect, EpiReg)
-
 from .dti import (BEDPOSTX, XFibres, DTIFit,
                   ProbTrackX, ProbTrackX2,
                   VecReg, ProjThresh, FindTheBiggest, DistanceMap,
                   TractSkeleton, MakeDyadicVectors, BEDPOSTX5, XFibres5)
 from .maths import (ChangeDataType, Threshold, MeanImage, ApplyMask,
                     IsotropicSmooth, TemporalFilter, DilateImage, ErodeImage,
                     SpatialFilter, UnaryMaths, BinaryMaths, MultiImageMaths)
-
 from .possum import B0Calc
+from .fix import (AccuracyTester, Classifier, Cleaner, FeatureExtractor,
+                  Training, TrainingSetCreator)

nipype/interfaces/fsl/fix.py

@@ -255,8 +255,8 @@ class CleanerInputSpec(CommandLineInputSpec):
                                  desc='cleanup motion confounds, looks for design.fsf for highpass filter cut-off',
                                  position=2)
 
-    highpass = traits.Float(argstr='-m -h %f',
-                            desc='cleanup motion confounds', value=100, position=2)
+    highpass = traits.Float(100, argstr='-m -h %f', usedefault=True,
+                            desc='cleanup motion confounds', position=2)
 
     aggressive = traits.Bool(argstr='-A',
                              desc='Apply aggressive (full variance) cleanup, instead of the default less-aggressive (unique variance) cleanup.', position=3)

nipype/interfaces/fsl/tests/test_auto_RobustFOV.py

@@ -6,6 +6,8 @@
 def test_RobustFOV_inputs():
     input_map = dict(args=dict(argstr='%s',
     ),
+    brainsize=dict(argstr='-b %d',
+    ),
     environ=dict(nohash=True,
     usedefault=True,
     ),
@@ -21,6 +23,11 @@ def test_RobustFOV_inputs():
     name_source=['in_file'],
     name_template='%s_ROI',
     ),
+    out_transform=dict(argstr='-m %s',
+    hash_files=False,
+    name_source=['in_file'],
+    name_template='%s_to_ROI',
+    ),
     output_type=dict(),
     terminal_output=dict(nohash=True,
     ),
@@ -34,6 +41,7 @@ def test_RobustFOV_inputs():
 
 def test_RobustFOV_outputs():
     output_map = dict(out_roi=dict(),
+    out_transform=dict(),
     )
     outputs = RobustFOV.output_spec()
 

nipype/interfaces/fsl/utils.py

@@ -70,25 +70,28 @@ class RobustFOVInputSpec(FSLCommandInputSpec):
     out_roi = File(desc="ROI volume output name", argstr="-r %s",
                    name_source=['in_file'], hash_files=False,
                    name_template='%s_ROI')
-    brainsize = traits.Int(170, desc='size of brain in z-dimension (default 170mm/150mm)',
-                           argstr='-b %d', usedefault=False)
-    out_transform = File(desc="Transformation matrix in_file to out_roi output name", argstr="-m %s",
+    brainsize = traits.Int(desc=('size of brain in z-dimension (default '
+                                 '170mm/150mm)'),
+                           argstr='-b %d')
+    out_transform = File(desc=("Transformation matrix in_file to out_roi "  
+                               "output name"),
+                         argstr="-m %s",
                          name_source=['in_file'], hash_files=False,
-                         name_template='%s_to_ROI', usedefault=False, mandatatory=False)
+                         name_template='%s_to_ROI')
 
 
 class RobustFOVOutputSpec(TraitedSpec):
     out_roi = File(exists=True, desc="ROI volume output name")
-    out_transform = File(exists=True, desc="Transformation matrix in_file to out_roi output name")
+    out_transform = File(exists=True,
+                         desc=("Transformation matrix in_file to out_roi " 
+                               "output name"))
 
 
 class RobustFOV(FSLCommand):
-    """robustfov command has been introduced in FSL5. It automatically crops an
-    image removing lower head and neck.
-    Input of brainsize in optional (default 170mm/150mm)
-    Output of ROI and transformation matrix is optional.
-    Interface is stable 5.0.0 to 5.0.9
-    But default brainsize changed from 150mm to 170mm.
+    """Automatically crops an image removing lower head and neck.
+    
+    Interface is stable 5.0.0 to 5.0.9, but default brainsize changed from 
+    150mm to 170mm.
     """
 
     _cmd = 'robustfov'

nipype/interfaces/utility/tests/test_auto_Merge.py

@@ -11,6 +11,8 @@ def test_Merge_inputs():
     ),
     no_flatten=dict(usedefault=True,
     ),
+    ravel_inputs=dict(usedefault=True,
+    ),
     )
     inputs = Merge.input_spec()