Skip to main content

MNE-Features software for extracting features from multivariate time series

Project description

Travis Codecov

This repository provides code for feature extraction with M/EEG data. The documentation of the MNE-Features module is available at: documentation.

Installation

To install the package, the simplest way is to use pip to get the latest release:

$ pip install mne-features

or to get the latest version of the code:

$ pip install git+https://github.com/mne-tools/mne-features.git#egg=mne_features

Dependencies

These are the dependencies to use MNE-Features:

  • numpy (>=1.17)

  • matplotlib (>=1.5)

  • scipy (>=1.0)

  • numba (>=0.46.0)

  • llvmlite (>=0.30)

  • scikit-learn (>=0.21)

  • mne (>=0.18.2)

  • PyWavelets (>=0.5.2)

  • pandas (>=0.25)

Cite

If you use this code in your project, please cite:

Jean-Baptiste SCHIRATTI, Jean-Eudes LE DOUGET, Michel LE VAN QUYEN, Slim ESSID, Alexandre GRAMFORT,
"An ensemble learning approach to detect epileptic seizures from long intracranial EEG recordings"
Proc. IEEE ICASSP Conf. 2018

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mne-features-0.1.tar.gz (34.9 kB view hashes)

Uploaded Source

Built Distribution

mne_features-0.1-py3-none-any.whl (25.1 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page