This is the repository for the minischool on MOABB, the Mother of All BC Benchmarks.
There is several possibilities. If you already have a working Python 3 environnement, you could use pip:
pip install MOABB
If you do not have a Python environment, we recommand installing Ananconda. We have USB key with the
There are two option, the first on is creating a specific environment. You need to download this environment.yml file on this page and run the following command:
conda env create -f environment.yml
The other option is to use poetry, as explained on the MOABB website.
Check your installation with notebooks/0_Minischool_Verify_Installation
This first notebook demonstrate how to use MOABB, with a simple example on a famous motor imagery dataset. See notebooks/1_Minischool_Discovering_MOABB.ipynb
This interlude is meant to demonstrate some simple code to use Riemannian geometry with PyRiemann. See notebooks/1bis_Minischool_Pyriemann
This notebook illustrate advanced possibilities of MOABB with an example benchmark on P300 dataset. See notebooks/2_Minischool_P300_Benchmarks