pyentrp 0.7.1

Functions on top of NumPy for computing different types of entropy

1. Quick start

2. Usage

3. Contributors and participation

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

• Nikolay Donets

• Jakob Dreyer

• Raphael Vallat

• Christopher Schölzel

• Sam Dotson

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