Functions on top of NumPy for computing different types of entropy
Project description
This is a small set of functions on top of NumPy that help to compute different types of entropy for time series analysis.
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
pip install 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)Requirements:
>numpy-1.7.0
Contributors and participation
Contributions are very welcome, documentation improvements/corrections, bug reports, even feature requests :)
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