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MNE : Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
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drammock MRG, FIX: apply transform before plotting sensors in 3D (#7142)
* apply transform before plotting sensors

* touch tutorial to trigger rendering

* add units to axis labels

* update what's new [ci skip]

* use FIFF constant
Latest commit 8ba88e2 Dec 15, 2019
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.circleci MAINT: Use action instead [ci skip] Dec 12, 2019
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doc MRG, FIX: apply transform before plotting sensors in 3D (#7142) Dec 15, 2019
examples MRG, BUG: Fix M/EEG topomap plotting (#7066) Dec 11, 2019
logo MAINT: Update logo code (#6328) May 16, 2019
tutorials MRG, FIX: apply transform before plotting sensors in 3D (#7142) Dec 15, 2019
.coveragerc MRG, ENH: Speed up clustering using numba (#6658) Aug 16, 2019
.mailmap umlauts Oct 5, 2019
.travis.yml ENH: Add mne sys_info command (#7105) Dec 2, 2019
LICENSE.txt MAINT: Move conftest (#6309) May 14, 2019
Makefile MRG, STY: Enable E241,E305 (#7017) Nov 4, 2019
README.rst MRG, DOC: Restore I/O content via new "tutorials" (#6809) Sep 24, 2019
azure-pipelines.yml MAINT: Unpin [ci skip] (#7132) Dec 10, 2019
codecov.yml FIX: Tweak May 13, 2016
ignore_words.txt DOC: Spelling (#7106) Dec 2, 2019
requirements.txt MRG, STY: Many style fixes (#6977) Oct 25, 2019
setup.cfg MAINT: Fix a few install issues (#7076) Nov 18, 2019


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MNE-Python software is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, and statistics.


MNE documentation for MNE-Python is available online.

Installing MNE-Python

To install the latest stable version of MNE-Python, you can use pip in a terminal:

pip install -U mne

Note that MNE-Python 0.17 was the last release to support Python 2. MNE-Python 0.18 only works under Python 3, and MNE-Python 0.19 requires Python 3.5 or higher.

For more complete instructions and more advanced installation methods (e.g. for the latest development version), see the installation guide.

Get the latest code

To install the latest version of the code using pip open a terminal and type:

pip install -U

To get the latest code using git, open a terminal and type:

git clone git://

Alternatively, you can also download a zip file of the latest development version.


The minimum required dependencies to run MNE-Python are:

  • Python >= 3.5
  • NumPy >= 1.12.1
  • SciPy >= 0.18.1

For full functionality, some functions require:

  • Matplotlib >= 2.0.2
  • Mayavi >= 4.6
  • PySurfer >= 0.8
  • Scikit-learn >= 0.18.2
  • Numba >= 0.40
  • NiBabel >= 2.1.0
  • Pandas >= 0.19.2
  • Picard >= 0.3
  • CuPy >= 4.0 (for NVIDIA CUDA acceleration)
  • DIPY >= 0.10.1
  • PyVista >= 0.20.1

Contributing to MNE-Python

Please see the documentation on the MNE-Python homepage:

Mailing list


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) 2011-2019, 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.

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