The homepage of MNE with user documentation is located on:
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
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
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.
The required dependencies to build the software are python >= 2.6, NumPy >= 1.4, SciPy >= 0.7.2 and matplotlib >= 0.98.4.
Some isolated functions (e.g. filtering with firwin2 require Scipy >= 0.9).
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)
http://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
To run the test suite, you need nosetests and the coverage modules. Run the test suite using:
nosetests
from the root of the project.
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
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.