• mne (>=0.23)

  • numpy (>=1.14)

  • scipy (>=1.5.0 for certain operations with EEGLAB data)

  • xarray (>=0.18)

  • joblib (>=1.0.0)

  • scikit-learn (>=0.24.2)

  • pandas (>=0.23.4, optional, for generating event statistics)

  • matplotlib (optional, for using the interactive data inspector)

We require that you use Python 3.7 or higher. You may choose to install mne-connectivity via pip, or conda.

Installation via Conda#

To install MNE-Connectivity using conda in a virtual environment, simply run the following at the root of the repository:

# with python>=3.8 at least
conda create -n mne
conda activate mne
conda install -c conda-forge mne-connectivity

Installation via Pip#

To install MNE-Connectivity including all dependencies required to use all features, simply run the following at the root of the repository:

python -m venv .venv
pip install -U mne-connectivity

If you want to install a snapshot of the current development version, run:

pip install --user -U

To check if everything worked fine, the following command should not give any error messages:

python -c 'import mne_connectivity'

MNE-Connectivity works best with the latest stable release of MNE-Python. To ensure MNE-Python is up-to-date, run:

pip install --user -U mne