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PyPREP: A Python implementation of the Preprocessing Pipeline (PREP) for EEG data

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PyPREP

For documentation, see the:

pyprep is a Python implementation of the Preprocessing Pipeline (PREP) for EEG data, working with MNE-Python.

Installation

pyprep requires Python version 3.9 or higher to run properly. We recommend to run pyprep in a dedicated virtual environment (for example using conda).

For installing the stable version of pyprep, call:

pip install pyprep

or, as an alternative to pip, call:

conda install -c conda-forge pyprep

For installing the latest (development) version of pyprep, call:

pip install --upgrade https://github.com/sappelhoff/pyprep/archive/refs/heads/main.zip

Both the stable and the latest installation will additionally install all required dependencies automatically. The dependencies are defined in the pyproject.toml file under the dependencies and project.optional-dependencies sections.

Contributions

We are actively looking for contributors!

Please chime in with your ideas on how to improve this software by opening a GitHub issue, or submitting a pull request.

See also our CONTRIBUTING.md file for help with submitting a pull request.

Potential contributors should install pyprep in the following way:

  1. First they should fork pyprep to their own GitHub account.
  2. Then they should run the following commands, adequately replacing <gh-username> with their GitHub username.
git clone https://github.com/<gh-username>/pyprep
cd pyprep
git fetch --tags --prune --prune-tags
pip install -e ".[dev]"
pre-commit install

Citing

If you use this software in academic work, please cite it using the Zenodo entry. Please also consider citing the original publication on PREP (see "References" below). Metadata is encoded in the CITATION.cff file.

References

  1. Bigdely-Shamlo, N., Mullen, T., Kothe, C., Su, K.-M., & Robbins, K. A. (2015). The PREP pipeline: standardized preprocessing for large-scale EEG analysis. Frontiers in Neuroinformatics, 9, 16. doi: 10.3389/fninf.2015.00016