Merge branch 'master' of github.com:nipy/nipype

Author: Tristan Glatard

.travis.yml

@@ -26,9 +26,9 @@ install:
   - source activate testenv
   - if [ ${TRAVIS_PYTHON_VERSION:0:1} == "2" ]; then pip install ordereddict; fi
   - conda install --yes numpy scipy nose traits networkx dateutil
-  - pip install nibabel --use-mirrors
-  - pip install python-coveralls --use-mirrors
-  - pip install nose-cov --use-mirrors
+  - pip install nibabel
+  - pip install python-coveralls
+  - pip install nose-cov
   - pip install https://github.com/RDFLib/rdflib/archive/master.zip
   - pip install https://github.com/trungdong/prov/archive/rdf.zip
   - python setup.py install

nipype/interfaces/fsl/__init__.py

@@ -16,7 +16,8 @@
                     ImageStats, FilterRegressor, Overlay, Slicer,
                     PlotTimeSeries, PlotMotionParams, ConvertXFM,
                     SwapDimensions, PowerSpectrum, Reorient2Std,
-                    Complex, InvWarp, WarpUtils, ConvertWarp, WarpPoints, WarpPointsToStd)
+                    Complex, InvWarp, WarpUtils, ConvertWarp, WarpPoints, 
+                    WarpPointsToStd, RobustFOV)
 
 from .epi import (PrepareFieldmap, TOPUP, ApplyTOPUP, Eddy, EPIDeWarp,
                   SigLoss, EddyCorrect, EpiReg)

nipype/interfaces/fsl/tests/test_auto_RobustFOV.py

@@ -0,0 +1,41 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from nipype.testing import assert_equal
+from nipype.interfaces.fsl.utils import RobustFOV
+
+def test_RobustFOV_inputs():
+    input_map = dict(args=dict(argstr='%s',
+    ),
+    environ=dict(nohash=True,
+    usedefault=True,
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    in_file=dict(argstr='-i %s',
+    mandatory=True,
+    position=0,
+    ),
+    out_roi=dict(argstr='-r %s',
+    hash_files=False,
+    name_source=['in_file'],
+    name_template='%s_ROI',
+    ),
+    output_type=dict(),
+    terminal_output=dict(nohash=True,
+    ),
+    )
+    inputs = RobustFOV.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_RobustFOV_outputs():
+    output_map = dict(out_roi=dict(),
+    )
+    outputs = RobustFOV.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/fsl/utils.py

@@ -31,6 +31,24 @@
 warn = warnings.warn
 warnings.filterwarnings('always', category=UserWarning)
 
+class RobustFOVInputSpec(FSLCommandInputSpec):
+    in_file = File(exists=True,
+                   desc='input filename',
+                   argstr='-i %s', position=0, mandatory=True)
+    out_roi = File(desc="ROI volume output name", argstr="-r %s",
+                   name_source=['in_file'], hash_files=False, 
+                   name_template='%s_ROI')
+    
+    
+class RobustFOVOutputSpec(TraitedSpec):
+    out_roi = File(exists=True, desc="ROI volume output name")
+
+
+class RobustFOV(FSLCommand):
+    _cmd = 'robustfov'
+    input_spec = RobustFOVInputSpec
+    output_spec = RobustFOVOutputSpec
+    
 
 class ImageMeantsInputSpec(FSLCommandInputSpec):
     in_file = File(exists=True,

nipype/interfaces/semtools/__init__.py

@@ -0,0 +1,10 @@
+from diffusion import *
+from featurecreator import GenerateCsfClippedFromClassifiedImage
+from segmentation import *
+from filtering import *
+from brains import *
+from testing import *
+from utilities import *
+from legacy import *
+from registration import *
+from converters import DWISimpleCompare, DWICompare

nipype/interfaces/semtools/brains/__init__.py

@@ -0,0 +1,3 @@
+from segmentation import SimilarityIndex, BRAINSTalairach, BRAINSTalairachMask
+from utilities import HistogramMatchingFilter
+from classify import BRAINSPosteriorToContinuousClass

nipype/interfaces/semtools/brains/classify.py

@@ -0,0 +1,48 @@
+# -*- coding: utf8 -*-
+"""Autogenerated file - DO NOT EDIT
+If you spot a bug, please report it on the mailing list and/or change the generator."""
+
+from nipype.interfaces.base import CommandLine, CommandLineInputSpec, SEMLikeCommandLine, TraitedSpec, File, Directory, traits, isdefined, InputMultiPath, OutputMultiPath
+import os
+
+
+class BRAINSPosteriorToContinuousClassInputSpec(CommandLineInputSpec):
+    inputWhiteVolume = File(desc="White Matter Posterior Volume", exists=True, argstr="--inputWhiteVolume %s")
+    inputBasalGmVolume = File(desc="Basal Grey Matter Posterior Volume", exists=True, argstr="--inputBasalGmVolume %s")
+    inputSurfaceGmVolume = File(desc="Surface Grey Matter Posterior Volume", exists=True, argstr="--inputSurfaceGmVolume %s")
+    inputCsfVolume = File(desc="CSF Posterior Volume", exists=True, argstr="--inputCsfVolume %s")
+    inputVbVolume = File(desc="Venous Blood Posterior Volume", exists=True, argstr="--inputVbVolume %s")
+    inputCrblGmVolume = File(desc="Cerebellum Grey Matter Posterior Volume", exists=True, argstr="--inputCrblGmVolume %s")
+    inputCrblWmVolume = File(desc="Cerebellum White Matter Posterior Volume", exists=True, argstr="--inputCrblWmVolume %s")
+    outputVolume = traits.Either(traits.Bool, File(), hash_files=False, desc="Output Continuous Tissue Classified Image", argstr="--outputVolume %s")
+
+
+class BRAINSPosteriorToContinuousClassOutputSpec(TraitedSpec):
+    outputVolume = File(desc="Output Continuous Tissue Classified Image", exists=True)
+
+
+class BRAINSPosteriorToContinuousClass(SEMLikeCommandLine):
+
+    """title: Tissue Classification
+
+category: BRAINS.Classify
+
+description: This program will generate an 8-bit continuous tissue classified image based on BRAINSABC posterior images.
+
+version: 3.0
+
+documentation-url: http://www.nitrc.org/plugins/mwiki/index.php/brains:BRAINSClassify
+
+license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
+
+contributor: Vincent A. Magnotta
+
+acknowledgements: Funding for this work was provided by NIH/NINDS award NS050568
+
+"""
+
+    input_spec = BRAINSPosteriorToContinuousClassInputSpec
+    output_spec = BRAINSPosteriorToContinuousClassOutputSpec
+    _cmd = " BRAINSPosteriorToContinuousClass "
+    _outputs_filenames = {'outputVolume': 'outputVolume'}
+    _redirect_x = False

nipype/interfaces/semtools/brains/segmentation.py

@@ -0,0 +1,126 @@
+# -*- coding: utf8 -*-
+"""Autogenerated file - DO NOT EDIT
+If you spot a bug, please report it on the mailing list and/or change the generator."""
+
+from nipype.interfaces.base import CommandLine, CommandLineInputSpec, SEMLikeCommandLine, TraitedSpec, File, Directory, traits, isdefined, InputMultiPath, OutputMultiPath
+import os
+
+
+class SimilarityIndexInputSpec(CommandLineInputSpec):
+    outputCSVFilename = File(desc="output CSV Filename", exists=True, argstr="--outputCSVFilename %s")
+    ANNContinuousVolume = File(desc="ANN Continuous volume to be compared to the manual volume", exists=True, argstr="--ANNContinuousVolume %s")
+    inputManualVolume = File(desc="input manual(reference) volume", exists=True, argstr="--inputManualVolume %s")
+    thresholdInterval = traits.Float(desc="Threshold interval to compute similarity index between zero and one", argstr="--thresholdInterval %f")
+
+
+class SimilarityIndexOutputSpec(TraitedSpec):
+    pass
+
+
+class SimilarityIndex(SEMLikeCommandLine):
+
+    """title: BRAINSCut:SimilarityIndexComputation
+
+category: BRAINS.Segmentation
+
+description: Automatic analysis of BRAINSCut Output
+
+version: 1.0
+
+license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
+
+contributor: Eunyoung Regin Kim
+
+"""
+
+    input_spec = SimilarityIndexInputSpec
+    output_spec = SimilarityIndexOutputSpec
+    _cmd = " SimilarityIndex "
+    _outputs_filenames = {}
+    _redirect_x = False
+
+
+class BRAINSTalairachInputSpec(CommandLineInputSpec):
+    AC = InputMultiPath(traits.Float, desc="Location of AC Point ", sep=",", argstr="--AC %s")
+    ACisIndex = traits.Bool(desc="AC Point is Index", argstr="--ACisIndex ")
+    PC = InputMultiPath(traits.Float, desc="Location of PC Point ", sep=",", argstr="--PC %s")
+    PCisIndex = traits.Bool(desc="PC Point is Index", argstr="--PCisIndex ")
+    SLA = InputMultiPath(traits.Float, desc="Location of SLA Point ", sep=",", argstr="--SLA %s")
+    SLAisIndex = traits.Bool(desc="SLA Point is Index", argstr="--SLAisIndex ")
+    IRP = InputMultiPath(traits.Float, desc="Location of IRP Point ", sep=",", argstr="--IRP %s")
+    IRPisIndex = traits.Bool(desc="IRP Point is Index", argstr="--IRPisIndex ")
+    inputVolume = File(desc="Input image used to define physical space of images", exists=True, argstr="--inputVolume %s")
+    outputBox = traits.Either(traits.Bool, File(), hash_files=False, desc="Name of the resulting Talairach Bounding Box file", argstr="--outputBox %s")
+    outputGrid = traits.Either(traits.Bool, File(), hash_files=False, desc="Name of the resulting Talairach Grid file", argstr="--outputGrid %s")
+
+
+class BRAINSTalairachOutputSpec(TraitedSpec):
+    outputBox = File(desc="Name of the resulting Talairach Bounding Box file", exists=True)
+    outputGrid = File(desc="Name of the resulting Talairach Grid file", exists=True)
+
+
+class BRAINSTalairach(SEMLikeCommandLine):
+
+    """title: BRAINS Talairach
+
+category: BRAINS.Segmentation
+
+description: This program creates a VTK structured grid defining the Talairach coordinate system based on four points: AC, PC, IRP, and SLA. The resulting structred grid can be written as either a classic VTK file or the new VTK XML file format. Two representations of the resulting grid can be written. The first is a bounding box representation that also contains the location of the AC and PC points. The second representation is the full Talairach grid representation that includes the additional rows of boxes added to the inferior allowing full coverage of the cerebellum.
+
+version: 0.1
+
+documentation-url: http://www.nitrc.org/plugins/mwiki/index.php/brains:BRAINSTalairach
+
+license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
+
+contributor: Steven Dunn and Vincent Magnotta
+
+acknowledgements: Funding for this work was provided by NIH/NINDS award NS050568
+
+"""
+
+    input_spec = BRAINSTalairachInputSpec
+    output_spec = BRAINSTalairachOutputSpec
+    _cmd = " BRAINSTalairach "
+    _outputs_filenames = {'outputGrid': 'outputGrid', 'outputBox': 'outputBox'}
+    _redirect_x = False
+
+
+class BRAINSTalairachMaskInputSpec(CommandLineInputSpec):
+    inputVolume = File(desc="Input image used to define physical space of resulting mask", exists=True, argstr="--inputVolume %s")
+    talairachParameters = File(desc="Name of the Talairach parameter file.", exists=True, argstr="--talairachParameters %s")
+    talairachBox = File(desc="Name of the Talairach box file.", exists=True, argstr="--talairachBox %s")
+    hemisphereMode = traits.Enum("left", "right", "both", desc="Mode for box creation: left, right, both", argstr="--hemisphereMode %s")
+    expand = traits.Bool(desc="Expand exterior box to include surface CSF", argstr="--expand ")
+    outputVolume = traits.Either(traits.Bool, File(), hash_files=False, desc="Output filename for the resulting binary image", argstr="--outputVolume %s")
+
+
+class BRAINSTalairachMaskOutputSpec(TraitedSpec):
+    outputVolume = File(desc="Output filename for the resulting binary image", exists=True)
+
+
+class BRAINSTalairachMask(SEMLikeCommandLine):
+
+    """title: Talairach Mask
+
+category: BRAINS.Segmentation
+
+description: This program creates a binary image representing the specified Talairach region. The input is an example image to define the physical space for the resulting image, the Talairach grid representation in VTK format, and the file containing the Talairach box definitions to be generated. These can be combined in BRAINS to create a label map using the procedure Brains::WorkupUtils::CreateLabelMapFromBinaryImages.
+
+version: 0.1
+
+documentation-url: http://www.nitrc.org/plugins/mwiki/index.php/brains:BRAINSTalairachMask
+
+license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt
+
+contributor: Steven Dunn and Vincent Magnotta
+
+acknowledgements: Funding for this work was provided by NIH/NINDS award NS050568
+
+"""
+
+    input_spec = BRAINSTalairachMaskInputSpec
+    output_spec = BRAINSTalairachMaskOutputSpec
+    _cmd = " BRAINSTalairachMask "
+    _outputs_filenames = {'outputVolume': 'outputVolume.nii'}
+    _redirect_x = False

nipype/interfaces/semtools/brains/utilities.py

@@ -0,0 +1,44 @@
+# -*- coding: utf8 -*-
+"""Autogenerated file - DO NOT EDIT
+If you spot a bug, please report it on the mailing list and/or change the generator."""
+
+from nipype.interfaces.base import CommandLine, CommandLineInputSpec, SEMLikeCommandLine, TraitedSpec, File, Directory, traits, isdefined, InputMultiPath, OutputMultiPath
+import os
+
+
+class HistogramMatchingFilterInputSpec(CommandLineInputSpec):
+    inputVolume = File(desc="The Input image to be computed for statistics", exists=True, argstr="--inputVolume %s")
+    referenceVolume = File(desc="The Input image to be computed for statistics", exists=True, argstr="--referenceVolume %s")
+    outputVolume = traits.Either(traits.Bool, File(), hash_files=False, desc="Output Image File Name", argstr="--outputVolume %s")
+    referenceBinaryVolume = File(desc="referenceBinaryVolume", exists=True, argstr="--referenceBinaryVolume %s")
+    inputBinaryVolume = File(desc="inputBinaryVolume", exists=True, argstr="--inputBinaryVolume %s")
+    numberOfMatchPoints = traits.Int(desc=" number of histogram matching points", argstr="--numberOfMatchPoints %d")
+    numberOfHistogramBins = traits.Int(desc=" number of histogram bin", argstr="--numberOfHistogramBins %d")
+    writeHistogram = traits.Str(desc=" decide if histogram data would be written with prefixe of the file name", argstr="--writeHistogram %s")
+    histogramAlgorithm = traits.Enum("OtsuHistogramMatching", desc=" histogram algrithm selection", argstr="--histogramAlgorithm %s")
+    verbose = traits.Bool(desc=" verbose mode running for debbuging", argstr="--verbose ")
+
+
+class HistogramMatchingFilterOutputSpec(TraitedSpec):
+    outputVolume = File(desc="Output Image File Name", exists=True)
+
+
+class HistogramMatchingFilter(SEMLikeCommandLine):
+
+    """title: Write Out Image Intensities
+
+category: BRAINS.Utilities
+
+description: For Analysis
+
+version: 0.1
+
+contributor: University of Iowa Department of Psychiatry, http:://www.psychiatry.uiowa.edu
+
+"""
+
+    input_spec = HistogramMatchingFilterInputSpec
+    output_spec = HistogramMatchingFilterOutputSpec
+    _cmd = " HistogramMatchingFilter "
+    _outputs_filenames = {'outputVolume': 'outputVolume.nii'}
+    _redirect_x = False