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Functions on top of NumPy for computing different types of entropy

Project description

pypi Build Status codecov py27 status py36 status image1 image2 image3

  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

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

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Files for pyentrp, version 0.7.1
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