pyEntropy (pyEntrp)

Quick start
Usage
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

Usage

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:

Fork the repository and submit pull requests with your improvements, bug fixes, or new features.
Report any issues or bugs you encounter on the issue tracker.
Help improve the documentation by submitting documentation improvements or corrections.
Participate in discussions and share your ideas.

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!