Installing MNE-Python¶

Installing Python¶

MNE-Python runs within Python, and depends on several other Python packages. MNE-Python 0.18 only supports Python version 3.5 or higher. We strongly recommend the Anaconda distribution of Python, which comes with more than 250 scientific packages pre-bundled, and includes the conda command line tool for installing new packages and managing different package sets (“environments”) for different projects. Follow the installation instructions for Anaconda; when you are done, you should see a similar output if you type the following command in a terminal:

$conda --version && python --version conda 4.6.2 Python 3.6.7 :: Anaconda, Inc.  If you get an error message, consult the Anaconda documentation and search for Anaconda install tips (Stack Overflow results are often helpful). Installing MNE-Python and its dependencies¶ Once you have Anaconda installed, the easiest way to install MNE-Python is to use the provided environment file to install MNE-Python and its dependencies into a new conda environment: $ curl --remote-name https://raw.githubusercontent.com/mne-tools/mne-python/master/environment.yml
$conda env create -f environment.yml$ conda activate mne


(You can also use a web browser to download the required environment file if you do not have curl.) These commands will create a new environment called mne and then activate it.

Make sure you activate the environment (conda activate mne) each time you open a terminal, or put the activation command in your .bashrc or .profile so that it happens automatically.

macOS

If you are on macOS, you need to manually update PyQt5. This step is not needed on Linux, and even breaks things on Windows.

$pip install --upgrade "pyqt5>=5.10"  Testing MNE-Python installation¶ To make sure MNE-Python installed correctly, type the following command in a terminal: $ python -c 'import mne; mne.sys_info()'


This should display some system information along with the versions of MNE-Python and its dependencies. Typical output looks like this:

Platform:      Linux-4.18.0-13-generic-x86_64-with-debian-buster-sid
Python:        3.6.8 |Anaconda, Inc.| (default, Dec 30 2018, 01:22:34)  [GCC 7.3.0]
Executable:    /home/travis/miniconda/envs/test/bin/python
CPU:           x86_64: 48 cores
Memory:        62.7 GB

mne:           0.17.0
numpy:         1.15.4 {blas=mkl_rt, lapack=mkl_rt}
scipy:         1.2.0
matplotlib:    3.0.2 {backend=Qt5Agg}

sklearn:       0.20.2
nibabel:       2.3.3
mayavi:        4.7.0.dev0 {qt_api=pyqt5, PyQt5=5.10.1}
pandas:        0.24.0
dipy:          0.15.0


Troubleshooting MNE-Python installation¶

If something went wrong during installation and you can’t figure it out yourself, check out the Advanced setup of MNE-Python page to see if your problem is discussed there. If not, the MNE mailing list and MNE gitter channel are good resources for troubleshooting installation problems.