Merge remote-tracking branch 'upstream/master'

Author: mick-d

nipype/interfaces/afni/preprocess.py

@@ -1450,10 +1450,13 @@ def _format_arg(self, name, trait_spec, value):
     def _filename_from_source(self, name):
         trait_spec = self.inputs.trait(name)
         retval = getattr(self.inputs, name)
-        if not isdefined(retval):
+        if not isdefined(retval) or "%s" in retval:
             if not trait_spec.name_source:
                 return retval
-            name_template = trait_spec.name_template
+            if isdefined(retval) and "%s" in retval:
+                name_template = retval
+            else:
+                name_template = trait_spec.name_template
             if not name_template:
                 name_template = "%s_generated"
             if isinstance(trait_spec.name_source, list):

nipype/interfaces/base.py

@@ -11,4 +11,5 @@
                     SegStats, Label2Vol, MS_LDA)
 from .utils import (SampleToSurface, SurfaceSmooth, SurfaceTransform,
                     SurfaceSnapshots,ApplyMask, MRIsConvert, MRITessellate,
-                    MRIMarchingCubes, SmoothTessellation, MakeAverageSubject)
+                    MRIMarchingCubes, SmoothTessellation, MakeAverageSubject,
+                    ExtractMainComponent)

nipype/interfaces/camino2trackvis/convert.py

@@ -28,6 +28,9 @@
                                     CommandLineInputSpec, isdefined)
 
 
+from ... import logging
+iflogger = logging.getLogger('interface')
+
 class ParseDICOMDirInputSpec(FSTraitedSpec):
     dicom_dir = Directory(exists=True, argstr='--d %s', mandatory=True,
                          desc='path to siemens dicom directory')
@@ -593,7 +596,8 @@ class ReconAllInputSpec(CommandLineInputSpec):
     directive = traits.Enum('all', 'autorecon1', 'autorecon2', 'autorecon2-cp',
                             'autorecon2-wm', 'autorecon2-inflate1', 'autorecon2-perhemi',
                             'autorecon3', 'localGI', 'qcache', argstr='-%s',
-                            desc='process directive', usedefault=True)
+                            desc='process directive', usedefault=True,
+                            position=0)
     hemi = traits.Enum('lh', 'rh', desc='hemisphere to process', argstr="-hemi %s")
     T1_files = InputMultiPath(File(exists=True), argstr='-i %s...',
                               desc='name of T1 file to process')
@@ -621,14 +625,97 @@ class ReconAll(CommandLine):
     >>> reconall.inputs.subjects_dir = '.'
     >>> reconall.inputs.T1_files = 'structural.nii'
     >>> reconall.cmdline
-    'recon-all -i structural.nii -all -subjid foo -sd .'
+    'recon-all -all -i structural.nii -subjid foo -sd .'
 
     """
 
     _cmd = 'recon-all'
     _additional_metadata = ['loc', 'altkey']
     input_spec = ReconAllInputSpec
     output_spec = ReconAllIOutputSpec
+    _can_resume = True
+
+
+    _steps = [
+        #autorecon1
+        ('motioncor', ['mri/rawavg.mgz', 'mri/orig.mgz']),
+        ('talairach', ['mri/transforms/talairach.auto.xfm',
+                       'mri/transforms/talairach.xfm']),
+        ('nuintensitycor', ['mri/nu.mgz']),
+        ('normalization', ['mri/T1.mgz']),
+        ('skullstrip',
+         ['mri/transforms/talairach_with_skull.lta',
+          'mri/brainmask.auto.mgz',
+          'mri/brainmask.mgz']),
+        #autorecon2
+        ('gcareg', ['mri/transforms/talairach.lta']),
+        ('canorm', ['mri/norm.mgz']),
+        ('careg', ['mri/transforms/talairach.m3z']),
+        ('careginv', ['mri/transforms/talairach.m3z.inv.x.mgz',
+                      'mri/transforms/talairach.m3z.inv.y.mgz',
+                      'mri/transforms/talairach.m3z.inv.z.mgz']),
+        ('rmneck', ['mri/nu_noneck.mgz']),
+        ('skull-lta', ['mri/transforms/talairach_with_skull_2.lta']),
+        ('calabel',
+         ['mri/aseg.auto_noCCseg.mgz', 'mri/aseg.auto.mgz', 'mri/aseg.mgz']),
+        ('normalization2', ['mri/brain.mgz']),
+        ('maskbfs', ['mri/brain.finalsurfs.mgz']),
+        ('segmentation', ['mri/wm.asegedit.mgz', 'mri/wm.mgz']),
+        ('fill', ['mri/filled.mgz']),
+        ('tessellate', ['surf/lh.orig.nofix', 'surf/rh.orig.nofix']),
+        ('smooth1', ['surf/lh.smoothwm.nofix', 'surf/rh.smoothwm.nofix']),
+        ('inflate1', ['surf/lh.inflated.nofix', 'surf/rh.inflated.nofix']),
+        ('qsphere', ['surf/lh.qsphere.nofix', 'surf/rh.qsphere.nofix']),
+        ('fix', ['surf/lh.orig', 'surf/rh.orig']),
+        ('white',
+         ['surf/lh.white',
+          'surf/rh.white',
+          'surf/lh.curv',
+          'surf/rh.curv',
+          'surf/lh.area',
+          'surf/rh.area',
+          'label/lh.cortex.label',
+          'label/rh.cortex.label']),
+        ('smooth2', ['surf/lh.smoothwm', 'surf/rh.smoothwm']),
+        ('inflate2',
+         ['surf/lh.inflated',
+          'surf/rh.inflated',
+          'surf/lh.sulc',
+          'surf/rh.sulc',
+          'surf/lh.inflated.H',
+          'surf/rh.inflated.H',
+          'surf/lh.inflated.K',
+          'surf/rh.inflated.K']),
+        #autorecon3
+        ('sphere', ['surf/lh.sphere', 'surf/rh.sphere']),
+        ('surfreg', ['surf/lh.sphere.reg', 'surf/rh.sphere.reg']),
+        ('jacobian_white', ['surf/lh.jacobian_white',
+                            'surf/rh.jacobian_white']),
+        ('avgcurv', ['surf/lh.avg_curv', 'surf/rh.avg_curv']),
+        ('cortparc', ['label/lh.aparc.annot', 'label/rh.aparc.annot']),
+        ('pial',
+         ['surf/lh.pial',
+          'surf/rh.pial',
+          'surf/lh.curv.pial',
+          'surf/rh.curv.pial',
+          'surf/lh.area.pial',
+          'surf/rh.area.pial',
+          'surf/lh.thickness',
+          'surf/rh.thickness']),
+        ('cortparc2', ['label/lh.aparc.a2009s.annot',
+                       'label/rh.aparc.a2009s.annot']),
+        ('parcstats2',
+         ['stats/lh.aparc.a2009s.stats',
+          'stats/rh.aparc.a2009s.stats',
+          'stats/aparc.annot.a2009s.ctab']),
+        ('cortribbon', ['mri/lh.ribbon.mgz', 'mri/rh.ribbon.mgz',
+                        'mri/ribbon.mgz']),
+        ('segstats', ['stats/aseg.stats']),
+        ('aparc2aseg', ['mri/aparc+aseg.mgz', 'mri/aparc.a2009s+aseg.mgz']),
+        ('wmparc', ['mri/wmparc.mgz', 'stats/wmparc.stats']),
+        ('balabels', ['BA.ctab', 'BA.thresh.ctab']),
+        ('label-exvivo-ec', ['label/lh.entorhinal_exvivo.label',
+                             'label/rh.entorhinal_exvivo.label'])]
 
     def _gen_subjects_dir(self):
         return os.getcwd()
@@ -660,6 +747,39 @@ def _list_outputs(self):
         outputs['subjects_dir'] = subjects_dir
         return outputs
 
+    @property
+    def cmdline(self):
+        subjects_dir = self.inputs.subjects_dir
+        if not isdefined(subjects_dir):
+            subjects_dir = self._gen_subjects_dir()
+        if not os.path.isdir(
+            os.path.join(subjects_dir,self.inputs.subject_id,'mri')):
+            return super(ReconAll, self).cmdline
+        self._check_mandatory_inputs()
+        skip = ['T1_files']
+        subjects_dir = self.inputs.subjects_dir
+        if not isdefined(subjects_dir):
+            subjects_dir = self._gen_subjects_dir()
+        flags = []
+        directive = 'all'
+        for idx, step in enumerate(self._steps):
+            step, outfiles = step
+            if all([os.path.exists(os.path.join(subjects_dir,self.inputs.subject_id,f)) for f  in outfiles]):
+                flags.append('-no%s'%step)
+                if idx > 4:
+                    directive = 'autorecon2'
+                elif idx > 23:
+                    directive = 'autorecon3'
+            else:
+                flags.append('-%s'%step)
+        self.inputs.args = ' '.join([self.inputs.args] + flags)
+        self.inputs.directive = directive
+        allargs = self._parse_inputs(skip=skip)
+        allargs.insert(0, self.cmd)
+        cmd = ' '.join(allargs)
+        iflogger.info('resume recon-all : %s'%cmd)
+        return cmd
+
 
 class BBRegisterInputSpec(FSTraitedSpec):
     subject_id = traits.Str(argstr='--s %s',

nipype/interfaces/freesurfer/__init__.py

@@ -16,7 +16,7 @@
 from nipype.utils.filemanip import fname_presuffix, split_filename
 
 from nipype.interfaces.freesurfer.base import FSCommand, FSTraitedSpec
-from nipype.interfaces.base import TraitedSpec, File, traits, OutputMultiPath, isdefined
+from nipype.interfaces.base import TraitedSpec, File, traits, OutputMultiPath, isdefined, CommandLine, CommandLineInputSpec
 
 filemap = dict(cor='cor', mgh='mgh', mgz='mgz', minc='mnc',
                afni='brik', brik='brik', bshort='bshort',
@@ -1026,3 +1026,30 @@ def _list_outputs(self):
         outputs = self.output_spec().get()
         outputs['average_subject_name'] = self.inputs.out_name
         return outputs
+
+class ExtractMainComponentInputSpec(CommandLineInputSpec):
+    in_file = File(exists=True, mandatory=True, argstr='%s', position=1,
+                   desc='input surface file')
+    out_file = File(name_template='%s.maincmp', name_source='in_file',
+                    argstr='%s', position=2,
+                    desc='surface containing main component')
+
+class ExtractMainComponentOutputSpec(TraitedSpec):
+    out_file = File(exists=True, desc='surface containing main component')
+
+class ExtractMainComponent(CommandLine):
+    """Extract the main component of a tesselated surface
+
+    Examples
+    --------
+
+    >>> from nipype.interfaces.freesurfer import ExtractMainComponent
+    >>> mcmp = ExtractMainComponent(in_file='lh.pial')
+    >>> mcmp.cmdline
+    'mris_extract_main_component lh.pial lh.maincmp'
+
+    """
+
+    _cmd='mris_extract_main_component'
+    input_spec=ExtractMainComponentInputSpec
+    output_spec=ExtractMainComponentOutputSpec

nipype/interfaces/freesurfer/preprocess.py

@@ -4,10 +4,11 @@
 <http://www.fmrib.ox.ac.uk/fsl/index.html>`_ command line tools.  This
 was written to work with FSL version 5.0.4.
 
-Examples
---------
-See the docstrings of the individual classes for examples.
-
+    Change directory to provide relative paths for doctests
+    >>> import os
+    >>> filepath = os.path.dirname( os.path.realpath( __file__ ) )
+    >>> datadir = os.path.realpath(os.path.join(filepath, '../../testing/data'))
+    >>> os.chdir(datadir)
 """
 
 import os

nipype/interfaces/freesurfer/utils.py

@@ -1663,9 +1663,10 @@ def _list_outputs(self):
 class GLMInputSpec(FSLCommandInputSpec):
     in_file = File(exists=True, argstr='-i %s', mandatory=True, position=1,
                    desc='input file name (text matrix or 3D/4D image file)')
-    out_file = File(argstr='-o %s', genfile=True, position=3,
+    out_file = File(name_template="%s_glm.txt", argstr='-o %s', position=3,
                     desc=('filename for GLM parameter estimates'
-                          + ' (GLM betas)'))
+                          + ' (GLM betas)'),
+                    name_source="in_file", keep_extension=True)
     design = File(exists=True, argstr='-d %s', mandatory=True, position=2,
                   desc=('file name of the GLM design matrix (text time'
                         + ' courses for temporal regression or an image'
@@ -1761,7 +1762,7 @@ class GLM(FSLCommand):
     >>> import nipype.interfaces.fsl as fsl
     >>> glm = fsl.GLM(in_file='functional.nii', design='maps.nii')
     >>> glm.cmdline
-    'fsl_glm -d maps.nii -i functional.nii -o functional_glm.txt'
+    'fsl_glm -i functional.nii -d maps.nii -o functional_glm.txt'
 
     """
     _cmd = 'fsl_glm'
@@ -1813,7 +1814,3 @@ def _list_outputs(self):
 
         return outputs
 
-    def _gen_filename(self, name):
-        if name in ['out_file']:
-            return self._gen_fname(self.inputs.in_file, suffix='_glm')
-        return None

nipype/interfaces/fsl/epi.py

@@ -12,6 +12,7 @@
 from nipype.interfaces.base import CommandLineInputSpec, CommandLine, traits, TraitedSpec, File
 from nipype.utils.filemanip import split_filename
 import os, os.path as op
+from nipype.interfaces.traits_extension import isdefined
 
 class Tracks2ProbInputSpec(CommandLineInputSpec):
     in_file = File(exists=True, argstr='%s', mandatory=True, position=-2,
@@ -54,7 +55,11 @@ class Tracks2Prob(CommandLine):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs['tract_image'] = op.abspath(self._gen_outfilename())
+        outputs['tract_image'] = self.inputs.out_filename
+        if not isdefined(outputs['tract_image']):
+            outputs['tract_image'] = op.abspath(self._gen_outfilename())
+        else:
+            outputs['tract_image'] = os.path.abspath(outputs['tract_image'])
         return outputs
 
     def _gen_filename(self, name):

nipype/interfaces/fsl/model.py

@@ -55,8 +55,9 @@ class SliceTimingInputSpec(SPMCommandInputSpec):
 
 
 class SliceTimingOutputSpec(TraitedSpec):
-    timecorrected_files = OutputMultiPath(File(exist=True,
-                                             desc='slice time corrected files'))
+    timecorrected_files = OutputMultiPath(traits.Either(traits.List(File(exists=True)),
+                                                        File(exists=True)),
+                                          desc='slice time corrected files')
 
 
 class SliceTiming(SPMCommand):
@@ -100,15 +101,11 @@ def _list_outputs(self):
 
         filelist = filename_to_list(self.inputs.in_files)
         for f in filelist:
-            run = []
             if isinstance(f, list):
-                for inner_f in filename_to_list(f):
-                    run.append(fname_presuffix(inner_f,
-                                               prefix=self.inputs.out_prefix))
+                run = [fname_presuffix(in_f, prefix=self.inputs.out_prefix) for in_f in f]
             else:
-                realigned_run = fname_presuffix(f,
-                                                prefix=self.inputs.out_prefix)
-            outputs['timecorrected_files'].append(realigned_run)
+                run = fname_presuffix(f, prefix=self.inputs.out_prefix)
+            outputs['timecorrected_files'].append(run)
         return outputs
 
 
@@ -152,9 +149,18 @@ class RealignInputSpec(SPMCommandInputSpec):
 
 class RealignOutputSpec(TraitedSpec):
     mean_image = File(exists=True, desc='Mean image file from the realignment')
+    modified_in_files = OutputMultiPath(traits.Either(traits.List(File(exists=True)),
+                                             File(exists=True)),
+                                        desc='Copies of all files passed to in_files.\
+                                              Headers will have been modified to align all\
+                                              images with the first, or optionally to first\
+                                              do that, extract a mean image, and re-align to\
+                                              that mean image.')
     realigned_files = OutputMultiPath(traits.Either(traits.List(File(exists=True)),
                                                     File(exists=True)),
-                                      desc='Realigned files')
+                                      desc='If jobtype is write or estwrite, these will be the\
+                                            resliced files. Otherwise, they will be copies of\
+                                            in_files that have had their headers rewritten.')
     realignment_parameters = OutputMultiPath(File(exists=True),
                     desc='Estimated translation and rotation parameters')
 
@@ -213,6 +219,10 @@ def _list_outputs(self):
                                                                      use_ext=False))
             if not isinstance(imgf, list) and func_is_3d(imgf):
                 break
+        if self.inputs.jobtype == "estimate":
+            outputs['realigned_files'] = self.inputs.in_files
+        if self.inputs.jobtype == "estimate" or self.inputs.jobtype == "estwrite":
+            outputs['modified_in_files'] = self.inputs.in_files
         if self.inputs.jobtype == "write" or self.inputs.jobtype == "estwrite":
             if isinstance(self.inputs.in_files[0], list):
                 first_image = self.inputs.in_files[0][0]
@@ -367,8 +377,11 @@ class NormalizeInputSpec(SPMCommandInputSpec):
     jobtype = traits.Enum('estwrite', 'est', 'write',
                           desc='one of: est, write, estwrite (opt, estwrite)',
                           usedefault=True)
-    apply_to_files = InputMultiPath(File(exists=True), field='subj.resample',
-                               desc='files to apply transformation to (opt)', copyfile=True)
+    apply_to_files = InputMultiPath(traits.Either(File(exists=True),
+                                                  traits.List(File(exists=True))),
+                                    field='subj.resample',
+                                    desc='files to apply transformation to (opt)',
+                                    copyfile=True)
     parameter_file = File(field='subj.matname', mandatory=True,
                           xor=['source', 'template'],
                           desc='normalization parameter file*_sn.mat', copyfile=False)
@@ -481,9 +494,13 @@ def _list_outputs(self):
         elif 'write' in self.inputs.jobtype:
             outputs['normalized_files'] = []
             if isdefined(self.inputs.apply_to_files):
-                for imgf in filename_to_list(self.inputs.apply_to_files):
-                    outputs['normalized_files'].append(fname_presuffix(imgf, prefix=self.inputs.out_prefix))
-
+                filelist = filename_to_list(self.inputs.apply_to_files)
+                for f in filelist:
+                    if isinstance(f, list):
+                        run = [fname_presuffix(in_f, prefix=self.inputs.out_prefix) for in_f in f]
+                    else:
+                        run = [fname_presuffix(f, prefix=self.inputs.out_prefix)]
+                    outputs['normalized_files'].extend(run)
             if isdefined(self.inputs.source):
                 outputs['normalized_source'] = []
                 for imgf in filename_to_list(self.inputs.source):