Entropy for Python
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
sample_entropy
multiscale_entropy
composite_multiscale_entropy
permutation_entropy
multiscale_permutation_entropy
weighted_permutation_entropy
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)
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!