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Merge pull request #10 from FCP-INDI/new_interfaces
New interfaces update into sgiavasis/nipype
2 parents d674756 + a80756c commit cc9918c

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.travis.yml

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@@ -34,6 +34,7 @@ before_install:
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echo 'include_dirs = /usr/include:/usr/include/X11' >> $HOME/.numpy-site.cfg;
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fi
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install:
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- sudo apt-get install fusefat
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- conda update --yes conda
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- conda create -n testenv --yes pip python=$TRAVIS_PYTHON_VERSION
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- source activate testenv
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- pip install -r requirements.txt # finish remaining requirements
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- python setup.py install
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script:
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- python -W once:FSL:UserWarning:nipype `which nosetests` --with-doctest --with-cov --cover-package nipype --cov-config .coveragerc --logging-level=INFO
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- python -W once:FSL:UserWarning:nipype `which nosetests` --with-doctest --with-cov --cover-package nipype --cov-config .coveragerc --logging-level=DEBUG --verbosity=3
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after_success:
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- coveralls --config_file .coveragerc
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deploy:

CHANGES

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Next release
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============
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* FIX: job execution on systems/approaches where locale is undefined (https://github.com/nipy/nipype/pull/1401)
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* FIX: Clean up byte/unicode issues using subprocess (https://github.com/nipy/nipype/pull/1394)
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* FIX: Prevent crash when tvtk is loaded - ETS_TOOLKIT=null (https://github.com/nipy/nipype/pull/973)
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* ENH: New interfaces in dipy: RESTORE, EstimateResponseSH, CSD and StreamlineTractography
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(https://github.com/nipy/nipype/pull/1090)
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* ENH: Added interfaces of AFNI (https://github.com/nipy/nipype/pull/1360,
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https://github.com/nipy/nipype/pull/1361)
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https://github.com/nipy/nipype/pull/1361, https://github.com/nipy/nipype/pull/1382)
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* ENH: Provides a Nipype wrapper for antsJointFusion (https://github.com/nipy/nipype/pull/1351)
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* ENH: Added support for PETPVC (https://github.com/nipy/nipype/pull/1335)
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* ENH: Merge S3DataSink into DataSink, added AWS documentation (https://github.com/nipy/nipype/pull/1316)
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* API: Default model level for the bedpostx workflow has been set to "2" following FSL 5.0.9 lead
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* ENH: New interfaces for interacting with AWS S3: S3DataSink and S3DataGrabber (https://github.com/nipy/nipype/pull/1201)
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* ENH: Interfaces for MINC tools (https://github.com/nipy/nipype/pull/1304)
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* FIX: Use realpath to determine hard link source (https://github.com/nipy/nipype/pull/1388)
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* FIX: Correct linking/copying fallback behavior (https://github.com/nipy/nipype/pull/1391)
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Release 0.11.0 (September 15, 2015)
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============

README.rst

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:target: https://pypi.python.org/pypi/nipype/
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:alt: License
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.. image:: https://img.shields.io/badge/gitter-join%20chat%20%E2%86%92-brightgreen.svg?style=flat
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:target: http://gitter.im/nipy/nipype
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:alt: Chat
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Current neuroimaging software offer users an incredible opportunity to
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analyze data using a variety of different algorithms. However, this has
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resulted in a heterogeneous collection of specialized applications

circle.yml

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- bash <(wget -q -O- http://neuro.debian.net/_files/neurodebian-travis.sh)
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override:
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# Install apt packages
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- sudo apt-get install -y fsl-core fsl-atlases fsl-mni152-templates fsl-feeds afni swig python-vtk xvfb
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- sudo apt-get install -y fsl-core fsl-atlases fsl-mni152-templates fsl-feeds afni swig python-vtk xvfb fusefat
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- echo 'source /etc/fsl/fsl.sh' >> $HOME/.profile
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- echo 'source /etc/afni/afni.sh' >> $HOME/.profile
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- mkdir -p ~/examples/ && ln -sf /usr/share/fsl-feeds/ ~/examples/feeds
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- pip install -e git+https://github.com/enthought/etsproxy.git#egg=etsproxy
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- pip install -e git+https://github.com/enthought/ets.git#egg=ets
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- gem install fakes3
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- if [[ ! -d ~/examples/data ]]; then wget "http://tcpdiag.dl.sourceforge.net/project/nipy/nipype/nipype-0.2/nipype-tutorial.tar.bz2" && tar jxvf nipype-tutorial.tar.bz2 && mv nipype-tutorial/* ~/examples/; fi
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- if [[ ! -d ~/examples/data ]]; then wget "https://dl.dropbox.com/s/jzgq2nupxyz36bp/nipype-tutorial.tar.bz2" && tar jxvf nipype-tutorial.tar.bz2 && mv nipype-tutorial/* ~/examples/; fi
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- if [[ ! -d ~/examples/fsl_course_data ]]; then wget -c "http://fsl.fmrib.ox.ac.uk/fslcourse/fdt1.tar.gz" && wget -c "http://fsl.fmrib.ox.ac.uk/fslcourse/fdt2.tar.gz" && wget -c "http://fsl.fmrib.ox.ac.uk/fslcourse/tbss.tar.gz" && mkdir ~/examples/fsl_course_data && tar zxvf fdt1.tar.gz -C ~/examples/fsl_course_data && tar zxvf fdt2.tar.gz -C ~/examples/fsl_course_data && tar zxvf tbss.tar.gz -C ~/examples/fsl_course_data; fi
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- bash ~/nipype/tools/install_spm_mcr.sh
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- mkdir -p ~/.nipype && echo '[logging]' > ~/.nipype/nipype.cfg && echo 'workflow_level = DEBUG' >> ~/.nipype/nipype.cfg && echo 'interface_level = DEBUG' >> ~/.nipype/nipype.cfg && echo 'filemanip_level = DEBUG' >> ~/.nipype/nipype.cfg

doc/documentation.rst

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:Release: |version|
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:Date: |today|
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Previous versions: `0.10.0 <http://nipy.org/nipype/0.10.0>`_ `0.9.2 <http://nipy.org/nipype/0.9.2>`_
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Previous versions: `0.11.0 <http://nipy.org/nipype/0.11.0>`_ `0.10.0 <http://nipy.org/nipype/0.10.0>`_
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.. container:: doc2
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doc/links_names.txt

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.. _pylint: http://www.logilab.org/project/pylint
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.. _pyflakes: http://divmod.org/trac/wiki/DivmodPyflakes
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.. _virtualenv: http://pypi.python.org/pypi/virtualenv
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.. _git: http://git.or.cz/
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.. _git: https://git-scm.com/
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.. _flymake: http://flymake.sourceforge.net/
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.. _rope: http://rope.sourceforge.net/
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.. _pymacs: http://pymacs.progiciels-bpi.ca/pymacs.html
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.. _`python coverage tester`: http://nedbatchelder.com/code/modules/coverage.html
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.. Other python projects
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.. _numpy: http://www.scipy.org/NumPy
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.. _numpy: http://www.numpy.org/
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.. _scipy: http://www.scipy.org
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.. _ipython: http://ipython.scipy.org
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.. _`ipython manual`: http://ipython.scipy.org/doc/manual/html
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.. _matplotlib: http://matplotlib.sourceforge.net
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.. _ipython: https://ipython.org
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.. _`ipython manual`: https://ipython.readthedocs.org/en/stable/
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.. _matplotlib: http://matplotlib.org/
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.. _ETS: http://code.enthought.com/projects/tool-suite.php
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.. _`Enthought Tool Suite`: http://code.enthought.com/projects/tool-suite.php
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.. _python: http://www.python.org
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.. _mayavi: http://mayavi.sourceforge.net/
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.. _sympy: http://code.google.com/p/sympy/
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.. _networkx: http://networkx.lanl.gov/
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.. _pythonxy: http://www.pythonxy.com/
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.. _sympy: http://www.sympy.org/
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.. _networkx: https://networkx.github.io/
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.. _pythonxy: https://python-xy.github.io/
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.. _EPD: http://www.enthought.com/products/epd.php
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.. _Traits: http://code.enthought.com/projects/traits/
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.. _Anaconda: https://store.continuum.io/cshop/anaconda/
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.. _Anaconda: https://www.continuum.io/downloads
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.. _Canopy: https://www.enthought.com/products/canopy/
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.. Python imaging projects

doc/users/pipeline_tutorial.rst

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~~~~~~
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Download and extract the `Pipeline tutorial data (429MB).
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<http://sourceforge.net/projects/nipy/files/nipype/nipype-0.2/nipype-tutorial.tar.bz2/download>`_
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<https://dl.dropbox.com/s/jzgq2nupxyz36bp/nipype-tutorial.tar.bz2>`_
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(checksum: 56ed4b7e0aac5627d1724e9c10cd26a7)
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doc/users/plugins.rst

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In addition to overall workflow configuration, you can use node level
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configuration for OAR::
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node.plugin_args = {'oarsub_args': '-l "nodes=1/cores=3"'}
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node.plugin_args = {'overwrite': True, 'oarsub_args': '-l "nodes=1/cores=3"'}
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this would apply only to the node and is useful in situations, where a
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particular node might use more resources than other nodes in a workflow.
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You need to set the 'overwrite' flag to bypass the general settings-template you defined for the other nodes.
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``qsub`` emulation

examples/README

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A dataset for use with these scripts can be downloaded from the nipype
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website. At the time of writing, it's at:
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http://nipy.sourceforge.net/nipype/users/pipeline_tutorial.html
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http://nipy.org/nipype/users/pipeline_tutorial.html

nipype/interfaces/afni/__init__.py

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from .base import Info
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from .preprocess import (To3D, Refit, Resample, TStat, Automask, Volreg, Merge,
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ZCutUp, Calc, TShift, Warp, Detrend, Despike, Copy,
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Fourier, Allineate, Maskave, SkullStrip, TCat, Fim,
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BlurInMask, Autobox, TCorrMap, Bandpass, Retroicor,
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ZCutUp, Calc, TShift, Warp, Detrend, Despike, DegreeCentrality,
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LFCD, Copy, Fourier, Allineate, Maskave, SkullStrip, TCat,
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Fim, BlurInMask, Autobox, TCorrMap, Bandpass, Retroicor,
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TCorrelate, TCorr1D, BrickStat, ROIStats, AutoTcorrelate,
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AFNItoNIFTI, Eval, Means, Hist, FWHMx)
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AFNItoNIFTI, Eval, Means, Hist, FWHMx, OutlierCount,
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QualityIndex)
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from .svm import (SVMTest, SVMTrain)

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