pyprep

PyPREP

For documentation, see the:

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

Installation

pyprep runs on Python version 3.10 or higher.

We recommend to run pyprep in a dedicated virtual environment (for example using conda).

For installing the stable version of pyprep, call:

python -m pip install --upgrade pyprep

or if you use conda:

conda install --channel conda-forge pyprep

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

python -m 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.

Logging

pyprep logs through the standard logging module and configures nothing when it is imported, so it is quiet by default but never silent: warnings and errors reach stderr without any setup. Call pyprep.setup_logging("info") to see what the pipeline decided, or pyprep.set_log_level("info") if your application already routes logging somewhere of its own.

See the Logging section of the API documentation for the details.

Contributing

The development of pyprep is taking place on GitHub.

For more information, please see CONTRIBUTING.md.

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

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

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