Alexandre Gramfort
156 lines
5.1 KiB
ReStructuredText
156 lines
5.1 KiB
ReStructuredText
.. -*- mode: rst -*-
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|Travis|_ |Appveyor|_ |Circle|_ |Codecov|_ |Zenodo|_
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|MNE|_
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.. |Travis| image:: https://api.travis-ci.org/mne-tools/mne-python.png?branch=master
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.. _Travis: https://travis-ci.org/mne-tools/mne-python
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.. |Appveyor| image:: https://ci.appveyor.com/api/projects/status/jg8ncqql9wayo8mg/branch/master?svg=true
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.. _Appveyor: https://ci.appveyor.com/project/mne-tools/mne-python/branch/master
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.. |Circle| image:: https://circleci.com/gh/mne-tools/mne-python.svg?style=svg
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.. _Circle: https://circleci.com/gh/mne-tools/mne-python
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.. |Codecov| image:: https://codecov.io/gh/mne-tools/mne-python/branch/master/graph/badge.svg
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.. _Codecov: https://codecov.io/gh/mne-tools/mne-python
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.. |Zenodo| image:: https://zenodo.org/badge/5822/mne-tools/mne-python.svg
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.. _Zenodo: https://zenodo.org/badge/latestdoi/5822/mne-tools/mne-python
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.. |MNE| image:: https://martinos.org/mne/stable/_static/mne_logo.png
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.. _MNE: https://martinos.org/mne
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MNE-Python
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==========
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`MNE-Python software`_ is an open-source Python package for exploring,
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visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG,
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ECoG, and more. It includes modules for data input/output, preprocessing,
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visualization, source estimation, time-frequency analysis, connectivity analysis,
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machine learning, and statistics.
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Documentation
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^^^^^^^^^^^^^
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`MNE documentation`_ for MNE-Python is available online.
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Installing MNE-Python
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^^^^^^^^^^^^^^^^^^^^^
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To install the latest stable version of MNE-Python, you can use `pip <https://pip.pypa.io/en/stable/>`_ in a terminal:
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.. code-block:: bash
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pip install -U mne
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**Note** that MNE-Python 0.17 will be the last release to support Python 2. From MNE-Python 0.18, only Python 3 will be supported.
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For more complete instructions and more advanced installation methods (e.g. for
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the latest development version), see the `getting started page`_.
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Get the latest code
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^^^^^^^^^^^^^^^^^^^
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To install the latest version of the code using `pip <https://pip.pypa.io/en/stable/>`_ open a terminal and type:
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.. code-block:: bash
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pip install -U https://api.github.com/repos/mne-tools/mne-python/zipball/master
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To get the latest code using `git <https://git-scm.com/>`_, open a terminal and type:
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.. code-block:: bash
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git clone git://github.com/mne-tools/mne-python.git
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Alternatively, you can also download a
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`zip file of the latest development version <https://github.com/mne-tools/mne-python/archive/master.zip>`_.
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Dependencies
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^^^^^^^^^^^^
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The minimum required dependencies to run MNE-Python are:
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- Python >= 2.7
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- NumPy >= 1.8
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- SciPy >= 0.12
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For full functionality, some functions require:
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- Matplotlib >= 1.3
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- Mayavi >= 4.6
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- Scikit-learn >= 0.15 (>= 0.18 recommended)
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- NiBabel >= 2.1.0
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- Pandas >= 0.13
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- Picard >= 0.3
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To use `NVIDIA CUDA <https://developer.nvidia.com/cuda-zone>`_ for resampling
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and FFT FIR filtering, you will also need to install the NVIDIA CUDA SDK,
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pycuda, and scikit-cuda (see the `getting started page`_
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for more information).
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Contributing to MNE-Python
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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Please see the documentation on the MNE-Python homepage:
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https://martinos.org/mne/contributing.html
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Mailing list
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^^^^^^^^^^^^
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http://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
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Licensing
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^^^^^^^^^
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MNE-Python is **BSD-licenced** (3 clause):
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This software is OSI Certified Open Source Software.
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OSI Certified is a certification mark of the Open Source Initiative.
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Copyright (c) 2011-2017, authors of MNE-Python.
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice,
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this list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the names of MNE-Python authors nor the names of any
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contributors may be used to endorse or promote products derived from
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this software without specific prior written permission.
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**This software is provided by the copyright holders and contributors
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"as is" and any express or implied warranties, including, but not
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limited to, the implied warranties of merchantability and fitness for
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a particular purpose are disclaimed. In no event shall the copyright
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owner or contributors be liable for any direct, indirect, incidental,
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special, exemplary, or consequential damages (including, but not
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limited to, procurement of substitute goods or services; loss of use,
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data, or profits; or business interruption) however caused and on any
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theory of liability, whether in contract, strict liability, or tort
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(including negligence or otherwise) arising in any way out of the use
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of this software, even if advised of the possibility of such
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damage.**
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.. _MNE-Python software: https://martinos.org/mne
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.. _MNE documentation: http://martinos.org/mne/documentation.html
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.. _getting started page: https://martinos.org/mne/getting_started.html
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