ordpy: A Python package for data analysis with permutation entropy and ordinal network methods

Abstract

Since Bandt and Pompe's seminal work, permutation entropy has been used in several applications and is now an essential tool for time series analysis. Beyond becoming a popular and successful technique, permutation entropy inspired a framework for mapping time series into symbolic sequences that triggered the development of many other tools, including an approach for creating networks from time series known as ordinal networks. Despite the increasing popularity, the computational development of these methods is fragmented, and there were still no efforts focusing on creating a unified software package. Here we present ordpy, a simple and open-source Python module that implements permutation entropy and several of the principal methods related to Bandt and Pompe's framework to analyze time series and two-dimensional data. In particular, ordpy implements permutation entropy, Tsallis and Rényi permutation entropies, complexity-entropy plane, complexity-entropy curves, missing ordinal patterns, ordinal networks, and missing ordinal transitions for one-dimensional (time series) and two-dimensional (images) data as well as their multiscale generalizations. We review some theoretical aspects of these tools and illustrate the use of ordpy by replicating several literature results.

arXiv comment23 two-column pages, 10 figures; accepted for publication in Chaos

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• Clustering free-falling paper motion with complexity and entropy
• Exploring the Interplay of Intrinsic Fluctuation and Complexity in Intracellular Calcium Dynamics
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• Cryptocurrency Time Series on the Binary Complexity-Entropy Plane: Ranking Efficiency from the Perspective of Complex Systems
• A hybrid dynamical-stochastic model of maximum temperature time series of Imphal, Northeast India incorporating nonlinear feedback and noise diagnostics
• Complexity-entropy analysis of solar photospheric turbulence: Hinode images of magnetic and Poynting fluxes
• Investigating the diversity and stylization of contemporary user generated visual arts in the complexity entropy plane
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