install_mne_python.rst

Installing MNE-Python

There are many ways to install a Python interpreter and MNE. Here we show a simple well tested solution.

1. Get Python

We recommend the Anaconda distribution. Follow the installation instructions. When you are done, you should see a similar output if you type the following command in a terminal:

$ conda --version && python --version
conda 4.5.4
Python 3.6.5 :: Anaconda, Inc.

If you get an error message, consult the Anaconda documentation and search for Anaconda install tips (Stack Overflow results are often helpful).

Note

MNE-Python 0.17 will be the last release to support Python 2. From MNE-Python 0.18, only Python 3 will be supported.

2. Get MNE and its dependencies

From the command line, install the MNE dependencies to a dedicated mne Anaconda environment.

$ curl -O 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.

|apple| 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

3. Check that everything works

To make sure everything installed correctly, type the following command in a terminal:

$ python

This should open an interactive Python prompt, where you can type:

>>> import mne

If you get a new prompt with no error messages, you should be good to go!

|windows| Windows

If you are on Windows, you might have to use the IPython magic command %gui qt after importing MNE, Mayavi or PySurfer (see here):

In [1]: from mayavi import mlab
In [2]: %gui qt

The $ conda env create ... step sometimes emits warnings, but you can ensure all default dependencies are installed by listing their versions with:

>>> mne.sys_info()  # doctest:+SKIP
Platform:      Linux-4.4.0-112-generic-x86_64-with-debian-jessie-sid
Python:        3.6.6 |Anaconda, Inc.| (default, Jun 28 2018, 17:14:51)  [GCC 7.2.0]
Executable:    /home/travis/miniconda/envs/test/bin/python
CPU:           x86_64: 48 cores
Memory:        62.7 GB

mne:           0.16.2
numpy:         1.15.0 {blas=mkl_rt, lapack=mkl_rt}
scipy:         1.1.0
matplotlib:    2.2.2 {backend=Qt5Agg}

sklearn:       0.19.1
nibabel:       2.3.0
mayavi:        4.6.1 {qt_api=pyqt5}
cupy:          Not found
pandas:        0.23.4

For advanced topics like how to get :ref:`CUDA` support or if you are experiencing other issues, check out :ref:`advanced_setup`.