Skip to content

nipy/nipype

This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.

Folders and files

NameName
Last commit message
Last commit date

Latest commit

4f08c9a · Jan 4, 2017
Dec 5, 2016
Dec 29, 2016
Dec 9, 2016
Sep 13, 2016
Jan 4, 2017
Dec 15, 2016
Dec 16, 2016
Aug 19, 2016
Mar 14, 2012
Apr 27, 2016
Aug 17, 2015
Aug 11, 2016
Dec 16, 2016
Oct 21, 2016
Jun 24, 2016
Jul 20, 2016
Sep 11, 2011
May 5, 2016
Aug 9, 2015
Dec 9, 2016
Nov 25, 2016
Apr 19, 2016
Apr 7, 2016
Aug 24, 2016
Dec 17, 2016
Sep 19, 2016
Dec 18, 2016
Dec 18, 2016
Oct 7, 2016
Sep 16, 2016

Repository files navigation

NIPYPE: Neuroimaging in Python: Pipelines and Interfaces

https://travis-ci.org/nipy/nipype.png?branch=master https://circleci.com/gh/nipy/nipype/tree/master.svg?style=svg https://www.codacy.com/project/badge/182f27944c51474490b369d0a23e2f32 Latest Version Supported Python versions Development Status License Chat

Current neuroimaging software offer users an incredible opportunity to analyze data using a variety of different algorithms. However, this has resulted in a heterogeneous collection of specialized applications without transparent interoperability or a uniform operating interface.

Nipype, an open-source, community-developed initiative under the umbrella of NiPy, is a Python project that provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages (e.g., SPM, FSL, FreeSurfer, AFNI, Slicer, ANTS), eases the design of workflows within and between packages, and reduces the learning curve necessary to use different packages. Nipype is creating a collaborative platform for neuroimaging software development in a high-level language and addressing limitations of existing pipeline systems.

Nipype allows you to:

  • easily interact with tools from different software packages
  • combine processing steps from different software packages
  • develop new workflows faster by reusing common steps from old ones
  • process data faster by running it in parallel on many cores/machines
  • make your research easily reproducible
  • share your processing workflows with the community

Documentation

Please see the doc/README.txt document for information on our documentation.

Website

Information specific to Nipype is located here:

http://nipy.org/nipype

Support and Communication

If you have a problem or would like to ask a question about how to do something in Nipype please open an issue in this GitHub repository.

To participate in the Nipype development related discussions please use the following mailing list:

http://mail.python.org/mailman/listinfo/neuroimaging

Please add [nipype] to the subject line when posting on the mailing list.

Warning

As of Nov 23, 2016, NeuroStars is down. We used to have all previous Nipype questions available under the nipype label.

Nipype structure

Currently Nipype consists of the following files and directories:

INSTALL
NIPYPE prerequisites, installation, development, testing, and troubleshooting.
README
This document.
THANKS
NIPYPE developers and contributors. Please keep it up to date!!
LICENSE
NIPYPE license terms.
doc/
Sphinx/reST documentation

examples/

nipype/
Contains the source code.
setup.py
Script for building and installing NIPYPE.

License information

We use the 3-clause BSD license; the full license is in the file LICENSE in the nipype distribution.

There are interfaces to some GNU code but these are entirely optional.

All trademarks referenced herein are property of their respective holders.

Copyright (c) 2009-2015, NIPY Developers All rights reserved.