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A Python implementation of the preprocessing pipeline (PREP) for EEG data.

Project description

Python tests codecov Documentation Status PyPI version

pyprep

For documentation, see the:

pyprep is a python implementation of the Preprocessing Pipeline (PREP) for EEG data, working with MNE-Python for EEG data processing and analysis. Also contains a function to detect outlier epochs inspired by the FASTER algorithm.

ALPHA SOFTWARE. This package is currently in its early stages of iteration. It may change both its internals or its user-facing API in the near future. Any feedback and ideas on how to improve either of these is more than welcome! Use this software at your own risk.

Installation

pyprep requires Python version 3.6 or higher to run properly. We recommend to run pyprep in a dedicated virtual environment (using e.g., conda).

For installing the stable version of pyprep, simply call pip install pyprep. This should install dependencies automatically, which are defined in the setup.cfg file in the options.install_requires section.

For installation of the development version use:

git clone https://github.com/sappelhoff/pyprep
cd pyprep
pip install -r requirements-dev.txt
pre-commit install
pip install -e .

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.

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
  2. Nolan, H., Whelan, R., & Reilly, R. B. (2010). FASTER: fully automated statistical thresholding for EEG artifact rejection. Journal of neuroscience methods, 192(1), 152-162. doi: 10.1016/j.jneumeth.2010.07.015

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