UMM

Code to run UMM for BCI ERP datasets.

Important Disclaimer

The source code for the core algorithm of Unsupervised Mean-difference Maximization (UMM) is protected by copyright of the Radboud University, the Netherlands, 2023, and a patent is pending for UMM-based applications. The authors encourage the use of this code for non-commercial, not-for-profit and academic purposes. However, the source code may only be copied, published, or used for other purposes under a license that is to be obtained from Radboud University.

To obtain the code (umm.py), please send an email with the subject umm.py request to either Jan or Michael that states your name, affiliation and the information, if you intend to use the software either for non-commercial / academic purposes or for commercial purposes.

Michael:

Jan:

Setup

⚠️ If you want to re-run the example notebook, you need to replace the mockup file umm_demo/classification/umm.py with the version of umm.py that you have obtained following the above description.

Create and activate a virtual environment using:

python3 -m venv venv
source venv/bin/activate

Then install the necessary requirements:

pip install -r requirements.txt
pip install -e .

If you have a system jupyter notebook installation, you need to register the virtual environment as a notebook kernel:

ipython kernel install --name "umm-venv" --user

Now you can open the examples notebook and you should be able to run it:

jupyter notebook examples/

Frequently asked questions

It says I am missing some umm.py file?

You need to download the file in an extra step, as indicated at the top of this readme.

It says some "zip" file is not a zip?

Unfortunately the dataset host sometimes stops transmission early and you are left with a corrupt .zip file. To fix this go to the ~/mne_data/ directory, and either delete everything (not recommended) or find the unfinished "zip file" impostor and delete it.