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MNE-Features software for extracting features from multivariate time series

Project description

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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

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mne-features-0.2.tar.gz (40.0 kB view hashes)

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