Merge pull request #2011 from satra/rel/0.13.0

Rel/0.13.0

Author: satra

CHANGES

@@ -1,4 +1,4 @@
-Upcoming Release
+0.13.0 (May 11, 2017)
 =====================
 
 * ENH: Multi-stage recon-all directives (https://github.com/nipy/nipype/pull/1991)
@@ -63,7 +63,7 @@ Upcoming Release
 
 
 0.13.0-rc1 (January 4, 2017)
-===============================
+============================
 
 * FIX: Compatibility with traits 4.6 (https://github.com/nipy/nipype/pull/1770)
 * FIX: Multiproc deadlock (https://github.com/nipy/nipype/pull/1756)

doc/conf.py

@@ -73,7 +73,7 @@
 
 # General information about the project.
 project = u'nipype'
-copyright = u'2009-16, Neuroimaging in Python team'
+copyright = u'2009-17, Neuroimaging in Python team'
 
 # The version info for the project you're documenting, acts as replacement for
 # |version| and |release|, also used in various other places throughout the
@@ -82,7 +82,7 @@
 # The short X.Y version.
 version = nipype.__version__
 # The full version, including alpha/beta/rc tags.
-release = "0.12.0"
+release = "0.13.0"
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

doc/documentation.rst

@@ -9,7 +9,7 @@ Documentation
    :Release: |version|
    :Date: |today|
 
-Previous versions:  `0.12.0 <http://nipype.readthedocs.io/en/0.12.0/>`_ `0.11.0 <http://nipy.org/nipype/0.11.0>`_
+Previous versions:  `0.12.1 <http://nipype.readthedocs.io/en/0.12.1/>`_ `0.11.0 <http://nipy.org/nipype/0.11.0>`_
 
 
 .. container:: doc2

doc/quickstart.rst

@@ -19,6 +19,16 @@ Michael Notter's Nipype tutorial. `Available here`__
 
 __ https://miykael.github.io/nipype_tutorial/
 
+How should I ask questions or report bugs?
+==========================================
+
+* If you find a bug or a suggestion for improvement report it here: `GitHub Issues <https://github.com/nipy/nipype/issues>`_
+* If you have a conceptual or clarification question ask it here: `Neurostars <https://neurostars.org/>`_
+* If you want to hangout with developers, you can use either::
+
+    `Gitter <https://gitter.im/nipy/nipype>`_
+    `Slack <https://brainhack.slack.com/messages/C1FR76RAL>`_
+
 Nipype workshop materials
 =========================
 

doc/users/install.rst

@@ -1,19 +1,18 @@
 .. _install:
 
-======================
- Download and install
-======================
+====================
+Download and install
+====================
 
 This page covers the necessary steps to install Nipype.
 
-Nipype for users
-----------------
-
 Using docker
 ~~~~~~~~~~~~
 
 You can follow the `Nipype tutorial <https://miykael.github.io/nipype_tutorial/>`_
 
+or use this docker container: `docker pull nipype/nipype`
+
 Using conda
 ~~~~~~~~~~~
 
@@ -75,7 +74,7 @@ path to compile the traits package.
 From source
 ~~~~~~~~~~~
 
-The current release is found here: `<https://github.com/nipy/nipype/releases/latest>`_.
+The most recent release is found here: `<https://github.com/nipy/nipype/releases/latest>`_.
 
 The development version: [`zip <http://github.com/nipy/nipype/zipball/master>`__ `tar.gz
 <http://github.com/nipy/nipype/tarball/master>`__]
@@ -100,69 +99,19 @@ the tests::
     python -c "import nipype; print(nipype.__version__)"
     python -c "import nipype; nipype.test()"
 
-Installation for developers
----------------------------
-
-Developers should start `here <../devel/testing_nipype.html>`_.
-
-Recommended Software
---------------------
-
-Strong Recommendations
-~~~~~~~~~~~~~~~~~~~~~~
-
-IPython_
-  Interactive python environment.
-
-Matplotlib_
-  Plotting library
-
-Sphinx_ 1.1
-  Required for building the documentation
-
-`Graphviz <http://www.graphviz.org/>`_
-  Required for building the documentation.
-
 Interface Dependencies
 ~~~~~~~~~~~~~~~~~~~~~~
 
-You might not need some of the following packages, depending on what exactly you
-want to use nipype for. If you do need any of them, install nipype's wrapper package
-(``nipype.interfaces``), then install the programs separately onto your computer, just
-like you would install any other app.
+Nipype provides wrappers around many neuroimaging tools and contains some
+algorithms. These tools will need to be installed for Nipype to run. You can
+create containers with different versions of these tools installed using
+`Neurodocker <https://github.com/kaczmarj/neurodocker>`_
 
-FSL_
-  4.1.0 or later
-
-matlab_
-  2008a or later
-
-SPM_
-  SPM5 or later
-
-FreeSurfer_
-  FreeSurfer v4.0.0 or later
-
-AFNI_
-  2009_12_31_1431 or later
-
-Slicer_
-  3.6 or later
-
-Nipy_
-  0.4 or later
-
-Nitime_
-  (optional)
-
-ANTS_
-
-MRtrix_ and MRtrix3_
-
-Camino_
+Installation for developers
+---------------------------
 
-Camino2Trackvis_
+Developers should start `here <../devel/testing_nipype.html>`_.
 
-ConnectomeViewer_
+Developers can also use this docker container: `docker pull nipype/nipype:master`
 
 .. include:: ../links_names.txt

nipype/algorithms/confounds.py

@@ -308,14 +308,14 @@ class CompCorInputSpec(BaseInterfaceInputSpec):
     mask_files = InputMultiPath(File(exists=True),
                                 desc=('One or more mask files that determines '
                                       'ROI (3D). When more that one file is '
-                                      'provided `merge_method` or ' 
+                                      'provided `merge_method` or '
                                       '`merge_index` must be provided'))
     merge_method = traits.Enum('union', 'intersect', 'none', xor=['mask_index'],
                                requires=['mask_files'],
                                desc=('Merge method if multiple masks are '
-                                     'present - `union` uses voxels included in' 
+                                     'present - `union` uses voxels included in'
                                      ' at least one input mask, `intersect` '
-                                     'uses only voxels present in all input ' 
+                                     'uses only voxels present in all input '
                                      'masks, `none` performs CompCor on '
                                      'each mask individually'))
     mask_index = traits.Range(low=0, xor=['merge_method'],
@@ -330,8 +330,8 @@ class CompCorInputSpec(BaseInterfaceInputSpec):
                                          'pre-component extraction'))
     regress_poly_degree = traits.Range(low=1, default=1, usedefault=True,
                                        desc='the degree polynomial to use')
-    header_prefix = traits.Str(desc=('the desired header for the output tsv ' 
-                                     'file (one column). If undefined, will ' 
+    header_prefix = traits.Str(desc=('the desired header for the output tsv '
+                                     'file (one column). If undefined, will '
                                      'default to "CompCor"'))
 
 
@@ -851,8 +851,8 @@ def combine_mask_files(mask_files, mask_method=None, mask_index=None):
             if len(mask_files) == 1:
                 mask_index = 0
             else:
-                raise ValueError(('When more than one mask file is provided, ' 
-                                  'one of merge_method or mask_index must be ' 
+                raise ValueError(('When more than one mask file is provided, '
+                                  'one of merge_method or mask_index must be '
                                   'set'))
         if mask_index < len(mask_files):
             mask = nb.load(mask_files[mask_index], mmap=NUMPY_MMAP)

nipype/info.py

@@ -9,7 +9,7 @@
 # full release.  '.dev' as a version_extra string means this is a development
 # version
 # Remove -dev for release
-__version__ = '0.13.0-dev'
+__version__ = '0.13.0'
 
 
 def get_nipype_gitversion():

nipype/interfaces/fsl/ICA_AROMA.py

@@ -1,8 +1,8 @@
 # -*- coding: utf-8 -*-
 # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
 # vi: set ft=python sts=4 ts=4 sw=4 et:
-"""This commandline module provides classes for interfacing with the 
-`ICA-AROMA.py<https://github.com/rhr-pruim/ICA-AROMA>`_ command line tool. 
+"""This commandline module provides classes for interfacing with the
+`ICA-AROMA.py<https://github.com/rhr-pruim/ICA-AROMA>`_ command line tool.
     Change directory to provide relative paths for doctests
     >>> import os
     >>> filepath = os.path.dirname(os.path.realpath(__file__))
@@ -23,18 +23,18 @@
 
 class ICA_AROMAInputSpec(CommandLineInputSpec):
     feat_dir = Directory(exists=True, mandatory=True,
-                         argstr='-feat %s', 
+                         argstr='-feat %s',
                          xor=['in_file', 'mat_file', 'fnirt_warp_file', 'motion_parameters'],
                          desc='If a feat directory exists and temporal filtering '
                          'has not been run yet, ICA_AROMA can use the files in '
                          'this directory.')
-    in_file = File(exists=True, mandatory=True, 
-                   argstr='-i %s', xor=['feat_dir'], 
+    in_file = File(exists=True, mandatory=True,
+                   argstr='-i %s', xor=['feat_dir'],
                    desc='volume to be denoised')
     out_dir = Directory('out', mandatory=True,
-                        argstr='-o %s',  
+                        argstr='-o %s',
                         desc='output directory')
-    mask = File(exists=True, argstr='-m %s', xor=['feat_dir'], 
+    mask = File(exists=True, argstr='-m %s', xor=['feat_dir'],
                 desc='path/name volume mask')
     dim = traits.Int(argstr='-dim %d',
                      desc='Dimensionality reduction when running '
@@ -65,31 +65,31 @@ class ICA_AROMAInputSpec(CommandLineInputSpec):
                                '-both: both aggressive and non-aggressive denoising (two outputs)')
 
 class ICA_AROMAOutputSpec(TraitedSpec):
-    aggr_denoised_file = File(exists=True, 
+    aggr_denoised_file = File(exists=True,
                               desc='if generated: aggressively denoised volume')
     nonaggr_denoised_file = File(exists=True,
                                  desc='if generated: non aggressively denoised volume' )
-    out_dir = Directory(exists=True, 
+    out_dir = Directory(exists=True,
                         desc='directory contains (in addition to the denoised files): '
                         'melodic.ica + classified_motion_components + '
                         'classification_overview + feature_scores + melodic_ic_mni)')
-   
+
 class ICA_AROMA(CommandLine):
     """
     Interface for the ICA_AROMA.py script.
-    
-    ICA-AROMA (i.e. 'ICA-based Automatic Removal Of Motion Artifacts') concerns 
+
+    ICA-AROMA (i.e. 'ICA-based Automatic Removal Of Motion Artifacts') concerns
     a data-driven method to identify and remove motion-related independent
     components from fMRI data. To that end it exploits a small, but robust
     set of theoretically motivated features, preventing the need for classifier
-    re-training and therefore providing direct and easy applicability. 
+    re-training and therefore providing direct and easy applicability.
 
     See link for further documentation: https://github.com/rhr-pruim/ICA-AROMA
 
     Example
     -------
 
-    >>> from nipype.interfaces.fsl import ICA_AROMA 
+    >>> from nipype.interfaces.fsl import ICA_AROMA
     >>> from nipype.testing import example_data
     >>> AROMA_obj = ICA_AROMA.ICA_AROMA()
     >>> AROMA_obj.inputs.in_file = 'functional.nii'
@@ -114,5 +114,5 @@ def _list_outputs(self):
             outputs['aggr_denoised_file'] = os.path.join(out_dir, 'denoised_func_data_aggr.nii.gz')
         if self.inputs.denoise_type in ('nonaggr', 'both'):
             outputs['nonaggr_denoised_file'] = os.path.join(out_dir, 'denoised_func_data_nonaggr.nii.gz')
-        
+
         return outputs

nipype/interfaces/fsl/tests/test_auto_MELODIC.py

@@ -43,6 +43,14 @@ def test_MELODIC_inputs():
     ),
     maxit=dict(argstr='--maxit=%d',
     ),
+    migp=dict(argstr='--migp',
+    ),
+    migpN=dict(argstr='--migpN %d',
+    ),
+    migp_factor=dict(argstr='--migp_factor %d',
+    ),
+    migp_shuffle=dict(argstr='--migp_shuffle',
+    ),
     mix=dict(argstr='--mix=%s',
     ),
     mm_thresh=dict(argstr='--mmthresh=%f',

nipype/interfaces/niftyreg/tests/test_regutils.py

@@ -283,7 +283,7 @@ def test_reg_average():
                         os.path.join(os.getcwd(), 'avg_out.nii.gz'),
                         ref_file, trans1_file, one_file, trans2_file, two_file,
                         trans3_file, three_file))
-    
+
     assert argv.decode('utf-8') == expected_argv
 
     # Test Reg Average: demean3