Supporting code for the article "The WQN algorithm for EEG artifact removal in the absence of scale invariance" by Matteo Dora, Stéphane Jaffard, David Holcman.
The code was written for Python 3.11 (but can probably run on previous versions without modification). The dependencies can be installed with pip
:
pip install -r requirements.txt
All figures and results in the article can be reproduced by running the scripts in the root folder, which are numbered based on their appearance in the manuscript.
The generated output files will be placed in the ./output
folder.
For example, to reproduce Figure 1, run:
python 10_multifractal_analysis.py
This will generate the file fig_scale_invariance.pdf
in the ./output
folder, which corresponds to Figure 1 in the article.
Note: Not all data required to run the scripts are included in this repository. Each dataset in the data
folder has a readme.md
file with instructions on how to download.
Once data is downloaded, run the script 00_preprocess_data.py
to convert the data to the format used by the other scripts.
If you need help running the code don't hesitate to contact the author at matteo.dora@ieee.org.