_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
python-antropy 0.1.9
Propagated dependencies: python-numba@0.61.0 python-numpy@1.26.4 python-scikit-learn@1.7.0 python-scipy@1.12.0
Channel: guix-science
Location: guix-science/packages/electrophysiology.scm (guix-science packages electrophysiology)
Home page: https://raphaelvallat.com/antropy
Licenses: Modified BSD
Build system: pyproject
Synopsis: Entropy and complexity of (EEG) time-series in Python
Description:

AntroPy is a Python package providing several time-efficient algorithms for computing the complexity of time-series. It can be used for example to extract features from EEG signals.

Total results: 1