[](https://travis-ci.org/sappelhoff/pyprep) [](https://codecov.io/gh/sappelhoff/pyprep) [](http://pyprep.readthedocs.io/en/latest/?badge=latest) [](https://badge.fury.io/py/pyprep)
# pyprep
A python implementation of the Preprocessing Pipeline (PREP) for EEG data.
Working with [MNE-Python](https://www.martinos.org/mne/stable/index.html) for EEG data processing and analysis.
For a basic use example, see [the documentation.](http://pyprep.readthedocs.io/en/latest/examples.html)
Also contains a function to detect outlier epochs inspired by the FASTER algorithm.
# Installation
Probably easiest through:
pip install pyprep
For development version:
`bash git clone https://github.com/sappelhoff/pyprep #clone pyprep locally cd pyprep #go to pyprep directory pip install -r requirements.txt #install all dependencies pip install -e . #install pyprep ` # Reference 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)
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](https://doi.org/10.1016/j.jneumeth.2010.07.015)
Metadata
Release files for pyprep 0.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| pyprep-0.2.2.tar.gz | 11.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyprep-0.2.2-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 23.7 kB
Release files / pyprep-0.2.2.tar.gz
| Download URL | pyprep-0.2.2.tar.gz |
|---|---|
| Size | 11.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
e487e9ae79bd4e5d3f0332fc691c0aebc8c26474e404c328d082c1632515d840
|
|
BLAKE2b-256 checksum How to use checksums |
652cbeb13982246c31b48e55de660acfbb8e390310b3ceeb27097c38676ecf26
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / pyprep-0.2.2-py2.py3-none-any.whl
| Download URL | pyprep-0.2.2-py2.py3-none-any.whl |
|---|---|
| Size | 11.8 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
9a78e689ad86caef6e537a1f80b91220ba66127aac607e56d2c916a2db0f8d14
|
|
BLAKE2b-256 checksum How to use checksums |
98b619690eb3ebf3d3f4bf7690e939b570f9bf994d77296255860c10625e8584
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for pyprep 0.2.2
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.