Git Product home page Git Product logo

mne-python's Introduction

The homepage of MNE with user documentation is located on:

http://martinos.org/mne

Getting the latest code

To get the latest code using git, simply type:

git clone git://github.com/mne-tools/mne-python.git

If you don't have git installed, you can download a zip or tarball of the latest code: http://github.com/mne-tools/mne-python/archives/master

Installing

As any Python packages, to install MNE-Python, simply do:

python setup.py install

in the source code directory.

You can also install the latest release with easy_install:

easy_install -U mne

or with pip:

pip install mne --upgrade

Workflow to contribute

To contribute to MNE-Python, first create an account on github. Once this is done, fork the mne-python repository to have you own repository, clone it using 'git clone' on the computers where you want to work. Make your changes in your clone, push them to your github account, test them on several computer, and when you are happy with them, send a pull request to the main repository.

Dependencies

The required dependencies to build the software are python >= 2.5, NumPy >= 1.4, SciPy >= 0.7.

To run the tests you will also need nose >= 0.10. and the MNE sample dataset (will be downloaded automatically when you run an example ... but be patient)

Mailing list

http://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis

Running the test suite

To run the test suite, you need nosetests and the coverage modules. Run the test suite using:

nosetests

from the root of the project.

Making a release and uploading it to PyPI

This command is only run by project manager, to make a release, and upload in to PyPI:

python setup.py sdist bdist_egg register upload

Licensing

MNE-Python is BSD-licenced (3 clause):

This software is OSI Certified Open Source Software. OSI Certified is a certification mark of the Open Source Initiative.

Copyright (c) 2011, authors of MNE-Python All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

  • Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
  • Neither the names of MNE-Python authors nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission.

This software is provided by the copyright holders and contributors "as is" and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. In no event shall the copyright owner or contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage.

mne-python's People

Contributors

agramfort avatar ellenlau avatar emilyruzich avatar mluessi avatar mshamalainen avatar yarikoptic avatar

Stargazers

 avatar  avatar

Watchers

 avatar  avatar  avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.