Merge remote-tracking branch 'upstream/master' into fix/antsct

* upstream/master:
  Update auto-generated files after make specs
  Added Limbo
  Added MIA description
  Update CHANGES

Author: satra

CHANGES

@@ -10,6 +10,7 @@ Next release
 * ENH: Resting state fMRI example with NiPy realignment and no SPM (https://github.com/nipy/nipype/pull/992)
 * FIX: Corrected Freesurfer SegStats _list_outputs to avoid error if summary_file is 
 	   undefined (issue #994)(https://https://github.com/nipy/nipype/pull/996)
+* FIX: OpenfMRI support and FSL 5.0.7 changes (https://github.com/nipy/nipype/pull/1006)
 
 Release 0.10.0 (October 10, 2014)
 ============

doc/devel/software_using_nipype.rst

@@ -28,6 +28,11 @@ Forward
 
 `Forward <http://cyclotronresearchcentre.github.io/forward/>`_ is set of tools simplifying the preparation of accurate electromagnetic head models for EEG forward modeling. It uses Nipype Workflows and Interfaces.
 
+Limbo
+-----
+
+`Limbo <https://github.com/Gilles86/in_limbo>`_ is a toolbox for finding brain regions that are neither significantly active nor inactive, but rather “in limbo”. It was build using custom Nipype Interfaces and Workflows.
+
 Lyman
 -----
 
@@ -38,6 +43,11 @@ Medimsight
 
 `Medimsight <https://www.medimsight.com>`_ is a commercial service medical imaging cloud platform. It uses Nipype to interface with various neuroimaging software.
 
+MIA
+---
+
+`MIA <http://mia.sourceforge.net>`_ MIA is a a toolkit for gray scale medical image analysis. It provides Nipype interfaces for easy integration with other software.
+
 Mindboggle
 ----------
 

examples/fmri_ants_openfmri.py

@@ -378,7 +378,7 @@ def analyze_openfmri_dataset(data_dir, subject=None, model_id=None,
                          name='datasource')
     datasource.inputs.base_directory = data_dir
     datasource.inputs.template = '*'
-    
+
     if has_contrast:
         datasource.inputs.field_template = {'anat': '%s/anatomy/highres001.nii.gz',
                                             'bold': '%s/BOLD/task%03d_r*/bold.nii.gz',

examples/rsfmri_vol_surface_preprocessing_nipy.py

@@ -945,7 +945,7 @@ def create_resting_workflow(args, name=None):
     if args.dicom_file:
         TR, slice_times, slice_thickness = get_info(args.dicom_file)
         slice_times = (np.array(slice_times)/1000.).tolist()
-        
+
     if name is None:
         name = 'resting_' + args.subject_id
     kwargs = dict(files=[os.path.abspath(filename) for filename in args.files],

nipype/algorithms/tests/test_auto_Overlap.py

@@ -0,0 +1,46 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from nipype.testing import assert_equal
+from nipype.algorithms.misc import Overlap
+
+def test_Overlap_inputs():
+    input_map = dict(bg_overlap=dict(mandatory=True,
+    usedefault=True,
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    mask_volume=dict(),
+    out_file=dict(usedefault=True,
+    ),
+    vol_units=dict(mandatory=True,
+    usedefault=True,
+    ),
+    volume1=dict(mandatory=True,
+    ),
+    volume2=dict(mandatory=True,
+    ),
+    weighting=dict(usedefault=True,
+    ),
+    )
+    inputs = Overlap.input_spec()
+
+    for key, metadata in input_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(inputs.traits()[key], metakey), value
+
+def test_Overlap_outputs():
+    output_map = dict(dice=dict(),
+    diff_file=dict(),
+    jaccard=dict(),
+    labels=dict(),
+    roi_di=dict(),
+    roi_ji=dict(),
+    roi_voldiff=dict(),
+    volume_difference=dict(),
+    )
+    outputs = Overlap.output_spec()
+
+    for key, metadata in output_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(outputs.traits()[key], metakey), value
+

nipype/interfaces/ants/segmentation.py

@@ -268,7 +268,7 @@ class N4BiasFieldCorrection(ANTSCommand):
 
     Examples
     --------
-	
+
 	>>> import copy
     >>> from nipype.interfaces.ants import N4BiasFieldCorrection
     >>> n4 = N4BiasFieldCorrection()
@@ -327,14 +327,14 @@ def _format_arg(self, name, trait_spec, value):
             output = self._gen_filename('output_image')
             newval = '[ %s, %s ]' % (output, bias_image)
             return trait_spec.argstr % newval
-            
+
         if name == 'bspline_fitting_distance':
             if isdefined(self.inputs.bspline_order):
                 newval = '[ %g, %d ]' % (value, self.inputs.bspline_order)
             else:
                 newval = '[ %g ]' % value
             return trait_spec.argstr % newval
-            
+
         if ((name == 'n_iterations') and
            (isdefined(self.inputs.convergence_threshold))):
             newval = '[ %s, %g ]' % ('x'.join([str(elt) for elt in value]),

nipype/interfaces/ants/tests/test_auto_ConvertScalarImageToRGB.py

@@ -0,0 +1,77 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from nipype.testing import assert_equal
+from nipype.interfaces.ants.visualization import ConvertScalarImageToRGB
+
+def test_ConvertScalarImageToRGB_inputs():
+    input_map = dict(args=dict(argstr='%s',
+    ),
+    colormap=dict(argstr='%s',
+    mandatory=True,
+    position=4,
+    usedefault=True,
+    ),
+    custom_color_map_file=dict(argstr='%s',
+    position=5,
+    usedefault=True,
+    ),
+    dimension=dict(argstr='%d',
+    mandatory=True,
+    position=0,
+    usedefault=True,
+    ),
+    environ=dict(nohash=True,
+    usedefault=True,
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    input_image=dict(argstr='%s',
+    mandatory=True,
+    position=1,
+    ),
+    mask_image=dict(argstr='%s',
+    position=3,
+    usedefault=True,
+    ),
+    maximum_RGB_output=dict(argstr='%d',
+    position=9,
+    usedefault=True,
+    ),
+    maximum_input=dict(argstr='%d',
+    mandatory=True,
+    position=7,
+    ),
+    minimum_RGB_output=dict(argstr='%d',
+    position=8,
+    usedefault=True,
+    ),
+    minimum_input=dict(argstr='%d',
+    mandatory=True,
+    position=6,
+    ),
+    num_threads=dict(nohash=True,
+    usedefault=True,
+    ),
+    output_image=dict(argstr='%s',
+    position=2,
+    usedefault=True,
+    ),
+    terminal_output=dict(mandatory=True,
+    nohash=True,
+    ),
+    )
+    inputs = ConvertScalarImageToRGB.input_spec()
+
+    for key, metadata in input_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(inputs.traits()[key], metakey), value
+
+def test_ConvertScalarImageToRGB_outputs():
+    output_map = dict(output_image=dict(),
+    )
+    outputs = ConvertScalarImageToRGB.output_spec()
+
+    for key, metadata in output_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(outputs.traits()[key], metakey), value
+

nipype/interfaces/ants/tests/test_auto_CreateTiledMosaic.py

@@ -0,0 +1,60 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from nipype.testing import assert_equal
+from nipype.interfaces.ants.visualization import CreateTiledMosaic
+
+def test_CreateTiledMosaic_inputs():
+    input_map = dict(alpha_value=dict(argstr='-a %.2f',
+    ),
+    args=dict(argstr='%s',
+    ),
+    direction=dict(argstr='-d %d',
+    ),
+    environ=dict(nohash=True,
+    usedefault=True,
+    ),
+    flip_slice=dict(argstr='-f %s',
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    input_image=dict(argstr='-i %s',
+    mandatory=True,
+    ),
+    mask_image=dict(argstr='-x %s',
+    ),
+    num_threads=dict(nohash=True,
+    usedefault=True,
+    ),
+    output_image=dict(argstr='-o %s',
+    usedefault=True,
+    ),
+    pad_or_crop=dict(argstr='-p %s',
+    ),
+    permute_axes=dict(argstr='-g',
+    ),
+    rgb_image=dict(argstr='-r %s',
+    mandatory=True,
+    ),
+    slices=dict(argstr='-s %s',
+    ),
+    terminal_output=dict(mandatory=True,
+    nohash=True,
+    ),
+    tile_geometry=dict(argstr='-t %s',
+    ),
+    )
+    inputs = CreateTiledMosaic.input_spec()
+
+    for key, metadata in input_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(inputs.traits()[key], metakey), value
+
+def test_CreateTiledMosaic_outputs():
+    output_map = dict(output_image=dict(),
+    )
+    outputs = CreateTiledMosaic.output_spec()
+
+    for key, metadata in output_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(outputs.traits()[key], metakey), value
+

nipype/interfaces/ants/visualization.py

@@ -30,7 +30,7 @@ class ConvertScalarImageToRGBInputSpec(ANTSCommandInputSpec):
                 'blue, copper, jet, hsv, spring, summer, '
                 'autumn, winter, hot, cool, overunder, custom '
                 ), mandatory = True, position = 4)
-    custom_color_map_file=traits.Str('none', argstr='%s', usedefault=True, 
+    custom_color_map_file=traits.Str('none', argstr='%s', usedefault=True,
             desc = 'custom color map file', position = 5)
     minimum_input = traits.Int(argstr='%d', desc='minimum input',
             mandatory = True, position = 6)
@@ -54,7 +54,7 @@ class ConvertScalarImageToRGB(ANTSCommand):
     >>> converter.inputs.input_image = 'T1.nii.gz'
     >>> converter.inputs.colormap = 'jet'
     >>> converter.inputs.minimum_input = 0
-    >>> converter.inputs.maximum_input = 6 
+    >>> converter.inputs.maximum_input = 6
     >>> converter.cmdline
     'ConvertScalarImageToRGB 3 T1.nii.gz rgb.nii.gz none jet none 0 6 0 255'
     """
@@ -67,9 +67,9 @@ def _format_arg(self, opt, spec, val):
 
     def _list_outputs(self):
         outputs = self._outputs().get()
-        outputs['output_image'] = os.path.join(os.getcwd(), 
+        outputs['output_image'] = os.path.join(os.getcwd(),
                 self.inputs.output_image)
-        return outputs 
+        return outputs
 
 
 class CreateTiledMosaicInputSpec(ANTSCommandInputSpec):
@@ -78,7 +78,7 @@ class CreateTiledMosaicInputSpec(ANTSCommandInputSpec):
             mandatory = True)
     rgb_image= File(argstr='-r %s', exists = True,
             desc = ('An optional Rgb image can be added as an overlay.'
-            'It must have the same image' 
+            'It must have the same image'
             'geometry as the input grayscale image.'),
             mandatory = True)
     mask_image = File(argstr = '-x %s', exists = True,
@@ -88,24 +88,24 @@ class CreateTiledMosaicInputSpec(ANTSCommandInputSpec):
             'using the specified alpha parameter.'))
     output_image = traits.Str('output.png', argstr = '-o %s',
             desc = 'The output consists of the tiled mosaic image.',
-            usedefault = True) 
+            usedefault = True)
     tile_geometry = traits.Str(argstr = '-t %s',desc = (
           'The tile geometry specifies the number of rows and columns'
-          'in the output image. For example, if the user specifies "5x10", ' 
+          'in the output image. For example, if the user specifies "5x10", '
           'then 5 rows by 10 columns of slices are rendered. If R < 0 and C > '
           '0 (or vice versa), the negative value is selected'
-          'based on direction.')) 
+          'based on direction.'))
     direction = traits.Int(argstr = '-d %d', desc = ('Specifies the direction of '
           'the slices. If no direction is specified, the '
-          'direction with the coarsest spacing is chosen.')) 
-    pad_or_crop = traits.Str(argstr='-p %s', 
+          'direction with the coarsest spacing is chosen.'))
+    pad_or_crop = traits.Str(argstr='-p %s',
         desc = 'argument passed to -p flag:'
           '[padVoxelWidth,<constantValue=0>]'
           '[lowerPadding[0]xlowerPadding[1],upperPadding[0]xupperPadding[1],'
           'constantValue]'
           'The user can specify whether to pad or crop a specified '
           'voxel-width boundary of each individual slice. For this '
-          'program, cropping is simply padding with negative voxel-widths.' 
+          'program, cropping is simply padding with negative voxel-widths.'
           'If one pads (+), the user can also specify a constant pad '
           'value (default = 0). If a mask is specified, the user can use '
           'the mask to define the region, by using the keyword "mask"'
@@ -118,21 +118,21 @@ class CreateTiledMosaicInputSpec(ANTSCommandInputSpec):
         desc = ('flipXxflipY'))
     permute_axes = traits.Bool(argstr = '-g', desc = 'doPermute'
         )
-    
+
 
 class CreateTiledMosaicOutputSpec(TraitedSpec):
     output_image= File(exists=True, desc='image file')
 
 class CreateTiledMosaic(ANTSCommand):
     """The program CreateTiledMosaic in conjunction with ConvertScalarImageToRGB
-    provides useful functionality for common image analysis tasks. The basic 
-    usage of CreateTiledMosaic is to tile a 3-D image volume slice-wise into 
+    provides useful functionality for common image analysis tasks. The basic
+    usage of CreateTiledMosaic is to tile a 3-D image volume slice-wise into
     a 2-D image.
 
     Examples
     --------
 
-    >>> from nipype.interfaces.ants.visualization import CreateTiledMosaic 
+    >>> from nipype.interfaces.ants.visualization import CreateTiledMosaic
     >>> mosaic_slicer = CreateTiledMosaic()
     >>> mosaic_slicer.inputs.input_image = 'T1.nii.gz'
     >>> mosaic_slicer.inputs.rgb_image = 'rgb.nii.gz'
@@ -141,17 +141,17 @@ class CreateTiledMosaic(ANTSCommand):
     >>> mosaic_slicer.inputs.alpha_value = 0.5
     >>> mosaic_slicer.inputs.direction = 2
     >>> mosaic_slicer.inputs.pad_or_crop = '[ -15x -50 , -15x -30 ,0]'
-    >>> mosaic_slicer.inputs.slices = '[2 ,100 ,160]' 
+    >>> mosaic_slicer.inputs.slices = '[2 ,100 ,160]'
     >>> mosaic_slicer.cmdline
     'CreateTiledMosaic -a 0.50 -d 2 -i T1.nii.gz -x mask.nii.gz -o output.png -p [ -15x -50 , -15x -30 ,0] -r rgb.nii.gz -s [2 ,100 ,160]'
     """
 
     _cmd = 'CreateTiledMosaic'
     input_spec = CreateTiledMosaicInputSpec
     output_spec = CreateTiledMosaicOutputSpec
-    
+
     def _list_outputs(self):
         outputs = self._outputs().get()
-        outputs['output_image'] = os.path.join(os.getcwd(), 
+        outputs['output_image'] = os.path.join(os.getcwd(),
                 self.inputs.output_image)
         return outputs

nipype/interfaces/spm/tests/test_auto_Normalize.py

@@ -13,7 +13,8 @@ def test_Normalize_inputs():
     ignore_exception=dict(nohash=True,
     usedefault=True,
     ),
-    jobtype=dict(),
+    jobtype=dict(usedefault=True,
+    ),
     matlab_cmd=dict(),
     mfile=dict(usedefault=True,
     ),