Merge pull request #1960 from satra/fix/autotest

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

@@ -19,10 +19,8 @@
                     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,
@@ -32,5 +30,6 @@
                     SpatialFilter, UnaryMaths, BinaryMaths, MultiImageMaths,
                     MaxnImage, MinImage, MedianImage, PercentileImage,
                     AR1Image)
-
 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()