Pyprep
PyPREP: A Python implementation of the Preprocessing Pipeline (PREP) for EEG data
Install / Use
/learn @sappelhoff/PyprepREADME
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PyPREP
For documentation, see the:
stable documentation <https://pyprep.readthedocs.io/en/stable/>_latest (development) documentation <https://pyprep.readthedocs.io/en/latest/>_
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pyprep is a Python implementation of the
Preprocessing Pipeline (PREP) <https://doi.org/10.3389/fninf.2015.00016>_
for EEG data, working with MNE-Python <https://mne.tools>_.
Installation
pyprep runs on Python version 3.10 or higher.
We recommend to run pyprep in a dedicated virtual environment
(for example using conda <https://docs.conda.io/en/latest/miniconda.html>_).
For installing the stable version of pyprep, call:
.. code-block:: Text
python -m pip install --upgrade pyprep
or if you use conda <https://docs.conda.io/en/latest/miniconda.html>_:
.. code-block:: Text
conda install --channel conda-forge pyprep
For installing the latest (development) version of pyprep, call:
.. code-block:: Text
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.
Contributing
The development of pyprep is taking place on
GitHub <https://github.com/sappelhoff/pyprep>_.
For more information, please see
CONTRIBUTING.md <https://github.com/sappelhoff/pyprep/blob/main/.github/CONTRIBUTING.md>_.
Citing
If you use this software in academic work, please cite it using the Zenodo entry <https://zenodo.org/badge/latestdoi/129240824>_.
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 <https://doi.org/10.3389/fninf.2015.00016>_
