A Python library for computing entropy measures for time series analysis.

entropy, multiscale, permutation, python, sample
pip install pyentrp==0.9.0


pyEntropy (pyEntrp)

py39 status py310 status py311 status py312 status

  1. Quick start
  2. Usage
  3. Contributors and participation

pyEntropy is a lightweight library built on top of NumPy that provides functions for computing various types of entropy for time series analysis.

The library currently supports the following types of entropy computation:

  • Shannon Entropy shannon_entropy
  • Sample Entropy sample_entropy
  • Multiscale Entropy multiscale_entropy
  • Composite Multiscale Entropy composite_multiscale_entropy
  • Permutation Entropy permutation_entropy
  • Multiscale Permutation Entropy multiscale_permutation_entropy
  • Weighted Permutation Entropy weighted_permutation_entropy

Quick start

Install pyEntropy using pip:

pip install pyentrp

Install pyEntropy using poetry:

poetry add pyentrp


from pyentrp import entropy as ent
import numpy as np

ts = [1, 4, 5, 1, 7, 3, 1, 2, 5, 8, 9, 7, 3, 7, 9, 5, 4, 3]
std_ts = np.std(ts)
sample_entropy = ent.sample_entropy(ts, 4, 0.2 * std_ts)

Contributors and participation

pyEntropy is an open-source project, and contributions are highly encouraged. If you would like to contribute, you can:

The following contributors have made significant contributions to pyEntropy:

Contributions are very welcome, documentation improvements/corrections, bug reports, even feature requests :)

If you find pyEntropy useful, please consider giving it a star.

Your support is greatly appreciated!