Merge branch 'master' into tst/martin

* master:
  Fixed file extension
  Fixed test files import.
  fixed possible values for -datatype parameter of tracks2prob interface. Previous values were in error. correct values obtained from: http://www.brain.org.au/software/mrtrix/general/formats.html#datatypes
  autogenerated tests
  added dummy files for testing new mrtrix interfaces
  updated CHANGES log
  Updated new mrtrix interfaces to new out_file format
  Added GenerateDirections, FindShPeaks, Directions2Amplitude interfaces wrapping gendir, find_SH_peaks and dir2amp mrtrix commands.
  tst: auto test generation for FUGUE
  fix: warp/unwarp arg parsing for use w/o an in_file
  fix: typo in fugue parameter
  add: pycharm .idea/ directory to .gitignore

Author: satra

.gitignore

@@ -12,3 +12,4 @@
 .project
 .settings
 .pydevproject
+.idea/

CHANGES

@@ -8,7 +8,6 @@ Next release
 * ENH: Added support for Simple Linux Utility Resource Management (SLURM)
 * ENH: AFNI interfaces refactor, prefix, suffix are replaced by "flexible_%s_templates"
 * ENH: DataGrabber and SelectFiles use human (or natural) sort now
-
 * ENH: Several new interfaces related to Camino were added:
         - camino.SFPICOCalibData
         - camino.Conmat
@@ -17,6 +16,10 @@ Next release
         - camino.SFPeaks
         One outdated interface no longer part of Camino was removed:
         - camino.Conmap
+* ENH: Three new mrtrix interfaces were added:
+        - mrtrix.GenerateDirections
+        - mrtrix.FindShPeaks
+        - mrtrix.Directions2Amplitude
 
 * FIX: Several fixes related to Camino interfaces:
         - ProcStreamlines would ignore many arguments silently (target, waypoint, exclusion ROIS, etc.)

nipype/interfaces/fsl/preprocess.py

@@ -1197,7 +1197,7 @@ class FUGUEInputSpec(FSLCommandInputSpec):
                                desc='apply Fourier (sinusoidal) fitting of order N')
     pava = traits.Bool(argstr='--pava',
                        desc='apply monotonic enforcement via PAVA')
-    despike_theshold = traits.Float(argstr='--despikethreshold=%s',
+    despike_threshold = traits.Float(argstr='--despikethreshold=%s',
                                     desc='specify the threshold for de-spiking (default=3.0)')
     unwarp_direction = traits.Enum('x', 'y', 'z', 'x-', 'y-', 'z-',
                                    argstr='--unwarpdir=%s',
@@ -1287,13 +1287,13 @@ def _parse_inputs(self, skip=None):
                 self.inputs.shift_out_file = self._gen_fname(
                     self.inputs.in_file, suffix='_vsm')
 
-        if self.inputs.forward_warping or not isdefined(self.inputs.in_file):
-            skip += ['unwarped_file']
+        if not isdefined(self.inputs.in_file):
+            skip += ['unwarped_file', 'warped_file']
+        elif self.inputs.forward_warping:
             if not isdefined(self.inputs.warped_file):
                 self.inputs.warped_file = self._gen_fname(
                     self.inputs.in_file, suffix='_warped')
-        if not self.inputs.forward_warping or not isdefined(self.inputs.in_file):
-            skip += ['warped_file']
+        elif not self.inputs.forward_warping:
             if not isdefined(self.inputs.unwarped_file):
                 self.inputs.unwarped_file = self._gen_fname(
                     self.inputs.in_file, suffix='_unwarped')

nipype/interfaces/fsl/tests/test_auto_FUGUE.py

@@ -61,13 +61,13 @@ def test_FUGUE_inputs():
     nohash=True,
     ),
     output_type=dict(),
-    despike_theshold=dict(argstr='--despikethreshold=%s',
-    ),
     icorr=dict(requires=['shift_in_file'],
     argstr='--icorr',
     ),
     fmap_in_file=dict(argstr='--loadfmap=%s',
     ),
+    despike_threshold=dict(argstr='--despikethreshold=%s',
+    ),
     unwarp_direction=dict(argstr='--unwarpdir=%s',
     ),
     fmap_out_file=dict(hash_files=False,

nipype/interfaces/mrtrix/__init__.py

@@ -5,10 +5,10 @@
                        SphericallyDeconvolutedStreamlineTrack,
                        ProbabilisticSphericallyDeconvolutedStreamlineTrack)
 from .tensors import (FSL2MRTrix, ConstrainedSphericalDeconvolution,
-                      DWI2SphericalHarmonicsImage, EstimateResponseForSH)
+                      DWI2SphericalHarmonicsImage, EstimateResponseForSH,
+                      GenerateDirections, FindShPeaks, Directions2Amplitude)
 from .preprocess import (MRConvert, MRMultiply, MRTrixViewer, MRTrixInfo,
                          GenerateWhiteMatterMask, DWI2Tensor,
                          Tensor2ApparentDiffusion, Tensor2FractionalAnisotropy,
                          Tensor2Vector, MedianFilter3D, Erode, Threshold)
-from .convert import MRTrix2TrackVis
-
+from .convert import MRTrix2TrackVis

nipype/interfaces/mrtrix/preprocess.py

@@ -11,7 +11,7 @@
 
 from nipype.interfaces.base import CommandLineInputSpec, CommandLine, traits, TraitedSpec, File, InputMultiPath, isdefined
 from nipype.utils.filemanip import split_filename
-import os, os.path as op
+import os.path as op
 
 class MRConvertInputSpec(CommandLineInputSpec):
     in_file = File(exists=True, argstr='%s', mandatory=True, position=-2,
@@ -65,7 +65,11 @@ class MRConvert(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['converted'] = op.abspath(self._gen_outfilename())
+        outputs['converted'] = self.inputs.out_filename
+        if not isdefined(outputs['converted']):
+            outputs['converted'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['converted'] = op.abspath(outputs['converted'])
         return outputs
 
     def _gen_filename(self, name):
@@ -169,7 +173,11 @@ class Tensor2Vector(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['vector'] = op.abspath(self._gen_outfilename())
+        outputs['vector'] = self.inputs.out_filename
+        if not isdefined(outputs['vector']):
+            outputs['vector'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['vector'] = op.abspath(outputs['vector'])
         return outputs
 
     def _gen_filename(self, name):
@@ -210,7 +218,11 @@ class Tensor2FractionalAnisotropy(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['FA'] = op.abspath(self._gen_outfilename())
+        outputs['FA'] = self.inputs.out_filename
+        if not isdefined(outputs['FA']):
+            outputs['FA'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['FA'] = op.abspath(outputs['FA'])
         return outputs
 
     def _gen_filename(self, name):
@@ -251,7 +263,11 @@ class Tensor2ApparentDiffusion(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['ADC'] = op.abspath(self._gen_outfilename())
+        outputs['ADC'] = self.inputs.out_filename
+        if not isdefined(outputs['ADC']):
+            outputs['ADC'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['ADC'] = op.abspath(outputs['ADC'])
         return outputs
 
     def _gen_filename(self, name):
@@ -293,7 +309,11 @@ class MRMultiply(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['out_file'] = op.abspath(self._gen_outfilename())
+        outputs['out_file'] = self.inputs.out_filename
+        if not isdefined(outputs['out_file']):
+            outputs['out_file'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['out_file'] = op.abspath(outputs['out_file'])
         return outputs
 
     def _gen_filename(self, name):
@@ -435,7 +455,11 @@ class Erode(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['out_file'] = op.abspath(self._gen_outfilename())
+        outputs['out_file'] = self.inputs.out_filename
+        if not isdefined(outputs['out_file']):
+            outputs['out_file'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['out_file'] = op.abspath(outputs['out_file'])
         return outputs
 
     def _gen_filename(self, name):
@@ -485,7 +509,11 @@ class Threshold(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['out_file'] = op.abspath(self._gen_outfilename())
+        outputs['out_file'] = self.inputs.out_filename
+        if not isdefined(outputs['out_file']):
+            outputs['out_file'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['out_file'] = op.abspath(outputs['out_file'])
         return outputs
 
     def _gen_filename(self, name):
@@ -526,7 +554,11 @@ class MedianFilter3D(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['out_file'] = op.abspath(self._gen_outfilename())
+        outputs['out_file'] = self.inputs.out_filename
+        if not isdefined(outputs['out_file']):
+            outputs['out_file'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['out_file'] = op.abspath(outputs['out_file'])
         return outputs
 
     def _gen_filename(self, name):
@@ -576,7 +608,11 @@ class MRTransform(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['out_file'] = op.abspath(self._gen_outfilename())
+        outputs['out_file'] = self.inputs.out_filename
+        if not isdefined(outputs['out_file']):
+            outputs['out_file'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['out_file'] = op.abspath(outputs['out_file'])
         return outputs
 
     def _gen_filename(self, name):

nipype/interfaces/mrtrix/tensors.py

@@ -73,7 +73,11 @@ class DWI2SphericalHarmonicsImage(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['spherical_harmonics_image'] = op.abspath(self._gen_outfilename())
+        outputs['spherical_harmonics_image'] = self.inputs.out_filename
+        if not isdefined(outputs['spherical_harmonics_image']):
+            outputs['spherical_harmonics_image'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['spherical_harmonics_image'] = op.abspath(outputs['spherical_harmonics_image'])
         return outputs
 
     def _gen_filename(self, name):
@@ -148,7 +152,11 @@ class ConstrainedSphericalDeconvolution(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['spherical_harmonics_image'] = op.abspath(self._gen_outfilename())
+        outputs['spherical_harmonics_image'] = self.inputs.out_filename
+        if not isdefined(outputs['spherical_harmonics_image']):
+            outputs['spherical_harmonics_image'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['spherical_harmonics_image'] = op.abspath(outputs['spherical_harmonics_image'])
         return outputs
 
     def _gen_filename(self, name):
@@ -194,7 +202,11 @@ class EstimateResponseForSH(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['response'] = op.abspath(self._gen_outfilename())
+        outputs['response'] = self.inputs.out_filename
+        if not isdefined(outputs['response']):
+            outputs['response'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['response'] = op.abspath(outputs['response'])
         return outputs
 
     def _gen_filename(self, name):
@@ -282,3 +294,109 @@ def _gen_outfilename(self):
         _, bvec , _ = split_filename(self.inputs.bvec_file)
         _, bval , _ = split_filename(self.inputs.bval_file)
         return bvec + '_' + bval + '.txt'
+
+
+class GenerateDirectionsInputSpec(CommandLineInputSpec):
+    num_dirs = traits.Int(mandatory=True, argstr='%s', position=-2 , desc='the number of directions to generate.')
+
+    power = traits.Float(argstr='-power %s', desc='specify exponent to use for repulsion power law.')
+    niter = traits.Int(argstr='-niter %s', desc='specify the maximum number of iterations to perform.')
+    display_info = traits.Bool(argstr='-info', desc='Display information messages.')
+    quiet_display = traits.Bool(argstr='-quiet', desc='do not display information messages or progress status.')
+    display_debug = traits.Bool(argstr='-debug', desc='Display debugging messages.')
+    out_file = File("directions.txt", argstr='%s', hash_files=False,
+                     position= -1, desc='the text file to write the directions to, as [ az el ] pairs.', usedefault=True)
+
+class GenerateDirectionsOutputSpec(TraitedSpec):
+    out_file = File(exists=True, desc='directions file')
+
+class GenerateDirections(CommandLine):
+    """
+    generate a set of directions evenly distributed over a hemisphere.
+
+    Example
+    -------
+
+    >>> import nipype.interfaces.mrtrix as mrt
+    >>> gendir = mrt.GenerateDirections()
+    >>> gendir.inputs.num_dirs = 300
+    >>> gendir.run()                                          # doctest: +SKIP
+    """
+
+    _cmd = 'gendir'
+    input_spec=GenerateDirectionsInputSpec
+    output_spec=GenerateDirectionsOutputSpec
+
+    
+class FindShPeaksInputSpec(CommandLineInputSpec):
+    in_file = File(exists=True, argstr='%s', mandatory=True, position=-3, desc='the input image of SH coefficients.')
+    directions_file = File(exists=True, argstr='%s', mandatory=True, position=-2, desc='the set of directions to use as seeds for the peak finding')    
+    peaks_image = File(exists=True, argstr='-peaks %s', desc='the program will try to find the peaks that most closely match those in the image provided')
+    num_peaks = traits.Int(argstr='-num %s', desc='the number of peaks to extract (default is 3)')
+    peak_directions = traits.List(traits.Float, argstr='-direction %s', sep=' ', minlen=2, maxlen=2,
+                                  desc='phi theta.  the direction of a peak to estimate. The algorithm will attempt to find the same number of peaks as have been specified using this option ' \
+                                  ' phi: the azimuthal angle of the direction (in degrees). theta: the elevation angle of the direction (in degrees, from the vertical z-axis)')
+    peak_threshold = traits.Float(argstr='-threshold %s', desc='only peak amplitudes greater than the threshold will be considered')
+    display_info = traits.Bool(argstr='-info', desc='Display information messages.')
+    quiet_display = traits.Bool(argstr='-quiet', desc='do not display information messages or progress status.')
+    display_debug = traits.Bool(argstr='-debug', desc='Display debugging messages.')
+    out_file = File(name_template="%s_peak_dirs.mif", keep_extension=False, argstr='%s', hash_files=False, position= -1,
+                    desc='the output image. Each volume corresponds to the x, y & z component of each peak direction vector in turn', name_source=["in_file"])
+    
+class FindShPeaksOutputSpec(TraitedSpec):
+    out_file = File(exists=True, desc='Peak directions image')
+
+class FindShPeaks(CommandLine):
+    """
+    identify the orientations of the N largest peaks of a SH profile
+
+    Example
+    -------
+
+    >>> import nipype.interfaces.mrtrix as mrt
+    >>> shpeaks = mrt.FindShPeaks()
+    >>> shpeaks.inputs.in_file = 'csd.mif'
+    >>> shpeaks.inputs.directions_file = 'dirs.txt'
+    >>> shpeaks.inputs.num_peaks = 2
+    >>> shpeaks.run()                                          # doctest: +SKIP
+    """
+
+    _cmd = 'find_SH_peaks'
+    input_spec=FindShPeaksInputSpec
+    output_spec=FindShPeaksOutputSpec
+
+
+
+class Directions2AmplitudeInputSpec(CommandLineInputSpec):
+    in_file = File(exists=True, argstr='%s', mandatory=True, position=-2, desc='the input directions image. Each volume corresponds to the x, y & z component of each direction vector in turn.')    
+    peaks_image = File(exists=True, argstr='-peaks %s', desc='the program will try to find the peaks that most closely match those in the image provided')
+    num_peaks = traits.Int(argstr='-num %s', desc='the number of peaks to extract (default is 3)')
+    peak_directions = traits.List(traits.Float, argstr='-direction %s', sep=' ', minlen=2, maxlen=2,
+                                  desc='phi theta.  the direction of a peak to estimate. The algorithm will attempt to find the same number of peaks as have been specified using this option ' \
+                                  ' phi: the azimuthal angle of the direction (in degrees). theta: the elevation angle of the direction (in degrees, from the vertical z-axis)')
+    display_info = traits.Bool(argstr='-info', desc='Display information messages.')
+    quiet_display = traits.Bool(argstr='-quiet', desc='do not display information messages or progress status.')
+    display_debug = traits.Bool(argstr='-debug', desc='Display debugging messages.')
+    out_file = File(name_template="%s_amplitudes.mif", keep_extension=False, argstr='%s', hash_files=False, position= -1,
+                    desc='the output amplitudes image', name_source=["in_file"])
+    
+class Directions2AmplitudeOutputSpec(TraitedSpec):
+    out_file = File(exists=True, desc='amplitudes image')
+
+class Directions2Amplitude(CommandLine):
+    """
+    convert directions image to amplitudes
+
+    Example
+    -------
+
+    >>> import nipype.interfaces.mrtrix as mrt
+    >>> amplitudes = mrt.Directions2Amplitude()
+    >>> amplitudes.inputs.in_file = 'peak_directions.mif'
+    >>> amplitudes.run()                                          # doctest: +SKIP
+    """
+
+    _cmd = 'dir2amp'
+    input_spec=Directions2AmplitudeInputSpec
+    output_spec=Directions2AmplitudeOutputSpec
+