Merge branch 'master' into enh/versioning

* master: (106 commits)
  Doctest fix, better error reporting.
  fix: config updated before checking for deprecated options
  put back the n_procs docs
  Udated docs with n_procs for MultiProc
  DOC: Improve docstring for DataFinder, include example usage.
  fix: adding atlases
  fix: removing recommends
  fix: restore fsl
  fix: remove fsl for now
  fix: variable name
  fix: use neurodebian sources
  fix: add missing nibabel
  fix: install nibabel in python dir
  fix: remove easy_install suffix
  fix: testing sklearn travis fix
  BF: Fixes for last commit
  BF: Use ignore regexes instead of functions so they can pickle.
  ENH: Added DataFinder interface.
  added cmdline example
  pep8
  ...

Author: satra

.travis.yml

@@ -1,22 +1,21 @@
-# vim ft=yaml
-# travis-ci.org definition for nipy build
-#
-# We pretend to be erlang because we need can't use the python support in
-# travis-ci; it uses virtualenvs, they do not have numpy, scipy, matplotlib,
-# and it is impractical to build them
-language: erlang
-env:
-    - PYTHON=python PYSUF=''
-    # - PYTHON=python3 PYSUF=3 : python3-numpy not currently available
-install:
-    - sudo apt-get install $PYTHON-dev
-    - sudo apt-get install $PYTHON-numpy
-    - sudo apt-get install $PYTHON-scipy
-    - sudo apt-get install $PYTHON-networkx
-    - sudo apt-get install $PYTHON-traits
-    - sudo apt-get install $PYTHON-setuptools
-    - sudo easy_install$PYSUF nibabel # Latest pypi
-    - sudo apt-get install $PYTHON-nose
-script:
-    # Change into an innocuous directory and find tests from installation
-    - make test
+language: python
+python:
+    - "2.7"
+before_install:
+    - deactivate
+    - sudo apt-get update -qq
+    - sudo apt-get install lsb-release
+    - source /etc/lsb-release
+    - wget -O- http://neuro.debian.net/lists/${DISTRIB_CODENAME}.us-nh | sudo tee /etc/apt/sources.list.d/neurodebian.sources.list
+    - sudo apt-key adv --recv-keys --keyserver pgp.mit.edu 2649A5A9
+    - sudo apt-get update -qq
+    - sudo apt-get install -qq python-scipy python-nose
+    - sudo apt-get install -qq python-networkx python-traits python-setuptools
+    - sudo apt-get install -qq python-nibabel
+    - sudo apt-get install -qq --no-install-recommends fsl afni
+    - sudo apt-get install -qq fsl-atlases
+    - source /etc/fsl/fsl.sh
+    - virtualenv --system-site-packages ~/virtualenv/this
+    - source ~/virtualenv/this/bin/activate
+install: python setup.py build_ext --inplace
+script: make test

CHANGES

@@ -1,13 +1,15 @@
 Next release
 ============
 
-* ENH: New interfaces: ICC, Meshfix, ants.Register
+* ENH: Add basic support for LSF plugin.
+* ENH: New interfaces: ICC, Meshfix, ants.Register, C3dAffineTool, ants.JacobianDeterminant
 * ENH: New workflows: ants template building (both using 'ANTS' and the new 'antsRegistration')
 * ENH: New examples: how to use ANTS template building workflows (smri_ants_build_tmeplate), 
 	  how to set SGE specific options (smri_ants_build_template_new)
 * ENH: added no_flatten option to Merge
 * ENH: added versioning option and checking to traits
 * ENH: added deprecation metadata to traits
+* ENH: Slicer interfaces were updated to version 4.1
 
 Release 0.6.0 (Jun 30, 2012)
 ============================

doc/users/plugins.rst

@@ -9,8 +9,8 @@ available plugins allow local and distributed execution of workflows and
 debugging. Each available plugin is described below.
 
 Current plugins are available for Linear, Multiprocessing, IPython_ distributed
-processing platforms and for direct processing on SGE_, PBS_, and Condor_. We
-anticipate future plugins for the Soma_ workflow and LSF_.
+processing platforms and for direct processing on SGE_, PBS_, Condor_, and LSF_. We
+anticipate future plugins for the Soma_ workflow.
 
 .. note::
 
@@ -34,7 +34,7 @@ Optional arguments::
 .. note::
 
    Except for the status_callback, the remaining arguments only apply to the
-   distributed plugins: MultiProc/IPython(X)/SGE/PBS/Condor
+   distributed plugins: MultiProc/IPython(X)/SGE/PBS/Condor/LSF
 
 For example:
 
@@ -71,11 +71,17 @@ a local system.
 
 Optional arguments::
 
-  n_procs :  Number of processes to launch in parallel
+  n_procs :  Number of processes to launch in parallel, if not set number of 
+  processors/threads will be automatically detected
 
 To distribute processing on a multicore machine, simply call::
 
-  workflow.run(plugin='MultiProc', plugin_args={'n_procs' : 2})
+  workflow.run(plugin='MultiProc')
+
+This will use all available CPUs. If on the other hand you would like to restrict
+the number of used resources (to say 2 CPUs), you can call::
+
+  workflow.run(plugin='MultiProc', plugin_args={'n_procs' : 2}
 
 IPython
 -------
@@ -102,7 +108,7 @@ SGE/PBS
 In order to use nipype with SGE_ or PBS_ you simply need to call::
 
        workflow.run(plugin='SGE')
-       workflow.run(plugin='PBS)
+       workflow.run(plugin='PBS')
 
 Optional arguments::
 
@@ -130,6 +136,17 @@ particular node might use more resources than other nodes in a workflow.
 
      node.plugin_args = {'qsub_args': '-l nodes=1:ppn=3', 'overwrite': True}
 
+LSF
+---
+
+Submitting via LSF is almost identical to SGE above:
+
+       workflow.run(plugin='LSF')
+
+Optional arguments::
+
+  template: custom template file to use
+  bsub_args: any other command line args to be passed to bsub.
 
 Condor
 ------

examples/dmri_connectivity_advanced.py

@@ -56,12 +56,13 @@
 import nipype.interfaces.cmtk as cmtk
 import nipype.interfaces.dipy as dipy
 import inspect
-import os.path as op                      # system functions
+import os, os.path as op                      # system functions
 from nipype.workflows.dmri.fsl.dti import create_eddy_correct_pipeline
 from nipype.workflows.dmri.camino.connectivity_mapping import select_aparc_annot
 from nipype.utils.misc import package_check
 import warnings
 from nipype.workflows.dmri.connectivity.nx import create_networkx_pipeline, create_cmats_to_csv_pipeline
+from nipype.workflows.smri.freesurfer import create_tessellation_flow
 
 try:
     package_check('cmp')
@@ -82,6 +83,9 @@
 fs.FSCommand.set_default_subjects_dir(subjects_dir)
 fsl.FSLCommand.set_default_output_type('NIFTI')
 
+fs_dir = os.environ['FREESURFER_HOME']
+lookup_file = op.join(fs_dir,'FreeSurferColorLUT.txt')
+
 """
 This needs to point to the fdt folder you can find after extracting
 
@@ -328,7 +332,7 @@
 
 CFFConverter = pe.Node(interface=cmtk.CFFConverter(), name="CFFConverter")
 CFFConverter.inputs.script_files = op.abspath(inspect.getfile(inspect.currentframe()))
-giftiSurfaces = pe.Node(interface=util.Merge(8), name="GiftiSurfaces")
+giftiSurfaces = pe.Node(interface=util.Merge(9), name="GiftiSurfaces")
 giftiLabels = pe.Node(interface=util.Merge(2), name="GiftiLabels")
 niftiVolumes = pe.Node(interface=util.Merge(3), name="NiftiVolumes")
 fiberDataArrays = pe.Node(interface=util.Merge(4), name="FiberDataArrays")
@@ -344,6 +348,9 @@
 NxStatsCFFConverter = pe.Node(interface=cmtk.CFFConverter(), name="NxStatsCFFConverter")
 NxStatsCFFConverter.inputs.script_files = op.abspath(inspect.getfile(inspect.currentframe()))
 
+tessflow = create_tessellation_flow(name='tessflow', out_format='gii')
+tessflow.inputs.inputspec.lookup_file = lookup_file
+
 """
 Connecting the workflow
 =======================
@@ -371,6 +378,9 @@
 mapping.connect([(inputnode, FreeSurferSourceRH,[("subjects_dir","subjects_dir")])])
 mapping.connect([(inputnode, FreeSurferSourceRH,[("subject_id","subject_id")])])
 
+mapping.connect([(inputnode, tessflow,[("subjects_dir","inputspec.subjects_dir")])])
+mapping.connect([(inputnode, tessflow,[("subject_id","inputspec.subject_id")])])
+
 mapping.connect([(inputnode, parcellate,[("subjects_dir","subjects_dir")])])
 mapping.connect([(inputnode, parcellate,[("subject_id","subject_id")])])
 mapping.connect([(parcellate, mri_convert_ROI_scale500,[('roi_file','in_file')])])
@@ -516,6 +526,7 @@
 mapping.connect([(mris_convertRHinflated, giftiSurfaces,[("converted","in6")])])
 mapping.connect([(mris_convertLHsphere, giftiSurfaces,[("converted","in7")])])
 mapping.connect([(mris_convertRHsphere, giftiSurfaces,[("converted","in8")])])
+mapping.connect([(tessflow, giftiSurfaces,[("outputspec.meshes","in9")])])
 
 mapping.connect([(mris_convertLHlabels, giftiLabels,[("converted","in1")])])
 mapping.connect([(mris_convertRHlabels, giftiLabels,[("converted","in2")])])

examples/dmri_group_connectivity_mrtrix.py

@@ -140,12 +140,6 @@
 
     l1pipeline = create_group_connectivity_pipeline(group_list, group_id, data_dir, subjects_dir, output_dir, info)
 
-    # This is used to demonstrate the ease through which different parameters can be set for each group.
-    if group_id == 'parkinsons':
-        l1pipeline.inputs.connectivity.mapping.threshold_FA.absolute_threshold_value = 0.5
-    else:
-        l1pipeline.inputs.connectivity.mapping.threshold_FA.absolute_threshold_value = 0.7
-
     # Here with invert the b-vectors in the Y direction and set the maximum harmonic order of the
     # spherical deconvolution step
     l1pipeline.inputs.connectivity.mapping.fsl2mrtrix.invert_y = True

nipype/algorithms/misc.py

@@ -649,32 +649,33 @@ def _list_outputs(self):
         return outputs
 
 def merge_csvs(in_list):
-	for idx, in_file in enumerate(in_list):
-		try:
-			in_array = np.loadtxt(in_file, delimiter=',')
-		except ValueError, ex:
-			try:
-				in_array = np.loadtxt(in_file, delimiter=',', skiprows=1)
-			except ValueError, ex:
-				first = open(in_file, 'r')
-				header_line = first.readline()
-				header_list = header_line.split(',')
-				n_cols = len(header_list)
-				try:
-					in_array = np.loadtxt(in_file, delimiter=',', skiprows=1, usecols=range(1,n_cols))
-				except ValueError, ex:
-					in_array = np.loadtxt(in_file, delimiter=',', skiprows=1, usecols=range(1,n_cols-1))
-		if idx == 0:
-			out_array = in_array
-		else:
-			out_array = np.dstack((out_array, in_array))
-	out_array = np.squeeze(out_array)
-	iflogger.info('Final output array shape:')
-	iflogger.info(np.shape(out_array))
-	return out_array
+    for idx, in_file in enumerate(in_list):
+        try:
+            in_array = np.loadtxt(in_file, delimiter=',')
+        except ValueError, ex:
+            try:
+                in_array = np.loadtxt(in_file, delimiter=',', skiprows=1)
+            except ValueError, ex:
+                first = open(in_file, 'r')
+                header_line = first.readline()
+                header_list = header_line.split(',')
+                n_cols = len(header_list)
+                try:
+                    in_array = np.loadtxt(in_file, delimiter=',', skiprows=1, usecols=range(1,n_cols))
+                except ValueError, ex:
+                    in_array = np.loadtxt(in_file, delimiter=',', skiprows=1, usecols=range(1,n_cols-1))
+        if idx == 0:
+            out_array = in_array
+        else:
+            out_array = np.dstack((out_array, in_array))
+    out_array = np.squeeze(out_array)
+    iflogger.info('Final output array shape:')
+    iflogger.info(np.shape(out_array))
+    return out_array
 
 def remove_identical_paths(in_files):
     import os.path as op
+    from nipype.utils.filemanip import split_filename
     if len(in_files) > 1:
         out_names = list()
         commonprefix = op.commonprefix(in_files)
@@ -699,24 +700,27 @@ def maketypelist(rowheadings, shape, extraheadingBool, extraheading):
         for idx in range(1,(min(shape)+1)):
             typelist.append((str(idx), float))
     else:
-        typelist.append((str(1), float))
+        for idx in range(1,(shape[0]+1)):
+            typelist.append((str(idx), float))
     if extraheadingBool:
         typelist.append((extraheading, 'a40'))
     iflogger.info(typelist)
     return typelist
 
 def makefmtlist(output_array, typelist, rowheadingsBool, shape, extraheadingBool):
-    output = np.zeros(max(shape), typelist)
     fmtlist = []
     if rowheadingsBool:
         fmtlist.append('%s')
     if len(shape) > 1:
+        output = np.zeros(max(shape), typelist)
         for idx in range(1,min(shape)+1):
             output[str(idx)] = output_array[:,idx-1]
             fmtlist.append('%f')
     else:
-        output[str(1)] = output_array
-        fmtlist.append('%f')
+        output = np.zeros(1, typelist)
+        for idx in range(1,len(output_array)+1):
+            output[str(idx)] = output_array[idx-1]
+            fmtlist.append('%f')
     if extraheadingBool:
         fmtlist.append('%s')
     fmt = ','.join(fmtlist)
@@ -727,6 +731,7 @@ class MergeCSVFilesInputSpec(TraitedSpec):
     out_file = File('merged.csv', usedefault=True, desc='Output filename for merged CSV file')
     column_headings = traits.List(traits.Str, desc='List of column headings to save in merged CSV file (must be equal to number of input files). If left undefined, these will be pulled from the input filenames.')
     row_headings = traits.List(traits.Str, desc='List of row headings to save in merged CSV file (must be equal to number of rows in the input files).')
+    row_heading_title = traits.Str('label', usedefault=True, desc='Column heading for the row headings added')
     extra_column_heading = traits.Str(desc='New heading to add for the added field.')
     extra_field = traits.Str(desc='New field to add to each row. This is useful for saving the group or subject ID in the file.')
 
@@ -756,6 +761,7 @@ class MergeCSVFiles(BaseInterface):
 
     def _run_interface(self, runtime):
         extraheadingBool = False
+        extraheading = ''
         rowheadingsBool = False
         """
         This block defines the column headings.
@@ -775,14 +781,15 @@ def _run_interface(self, runtime):
                 extraheading = 'type'
                 iflogger.info('Extra column heading was not defined. Using "type"')
             headings.append(extraheading)
-            extraheadingBool = True
+            extraheadingBool = True            
 
         if len(self.inputs.in_files) == 1:
             iflogger.warn('Only one file input!')
 
         if isdefined(self.inputs.row_headings):
             iflogger.info('Row headings have been provided. Adding "labels" column header.')
-            csv_headings = '"labels","' + '","'.join(itertools.chain(headings)) + '"\n'
+            prefix = '"{p}","'.format(p=self.inputs.row_heading_title)
+            csv_headings = prefix + '","'.join(itertools.chain(headings)) + '"\n'
             rowheadingsBool = True
         else:
             iflogger.info('Row headings have not been provided.')
@@ -814,12 +821,16 @@ def _run_interface(self, runtime):
             for row_heading in row_heading_list:
                 row_heading_with_quotes = '"' + row_heading + '"'
                 row_heading_list_with_quotes.append(row_heading_with_quotes)
-            row_headings = np.array(row_heading_list_with_quotes)
+            row_headings = np.array(row_heading_list_with_quotes, dtype='|S40')
             output['heading'] = row_headings
 
         if isdefined(self.inputs.extra_field):
             extrafieldlist = []
-            for idx in range(0,max(shape)):
+            if len(shape) > 1:
+                mx = shape[0]
+            else:
+                mx = 1
+            for idx in range(0,mx):
                 extrafieldlist.append(self.inputs.extra_field)
             iflogger.info(len(extrafieldlist))
             output[extraheading] = extrafieldlist

nipype/algorithms/modelgen.py

@@ -278,7 +278,7 @@ def _generate_standard_design(self, infolist,
             sessinfo.insert(i, dict(cond=[]))
             if isdefined(self.inputs.high_pass_filter_cutoff):
                 sessinfo[i]['hpf'] = np.float(self.inputs.high_pass_filter_cutoff)
-            if hasattr(info, 'conditions') and info.conditions:
+            if hasattr(info, 'conditions') and info.conditions is not None:
                 for cid, cond in enumerate(info.conditions):
                     sessinfo[i]['cond'].insert(cid, dict())
                     sessinfo[i]['cond'][cid]['name']  = info.conditions[cid]

nipype/interfaces/ants/__init__.py

@@ -14,4 +14,4 @@
 from .segmentation import Atropos, N4BiasFieldCorrection
 
 # Utility Programs
-from .utils import AverageAffineTransform, AverageImages, MultiplyImages
+from .utils import AverageAffineTransform, AverageImages, MultiplyImages, JacobianDeterminant