Planar Visibility Graph Network Algorithm For Two Dimensional Timeseries

TL;DR

This paper introduces a fast method to convert 2D timeseries into planar graphs using the Planar Visibility Graph Network algorithm, enabling new complex network-based analysis of different types of series.

Contribution

The paper presents a novel, efficient algorithm for transforming 2D timeseries into planar graphs, facilitating complex network analysis of various series types.

Findings

Different series produce distinct network properties.

The method captures series characteristics through network measures.

It enables new perspectives in timeseries analysis.

Abstract

In this brief paper, a simple and fast computational method, the Planar Visibility Graph Networks Algorithm was proposed based on the famous Visibility Graph Algorithm, which can fulfill converting two dimensional timeseries into a planar graph. The constructed planar graph inherits several properties of the series in its structure. Thereby, periodic series, random series, and chaotic series convert into quite different networks with different average degree, characteristic path length, diameter, clustering coefficient, different degree distribution, and modularity, etc. By means of this new approach, with such different networks measures, one can characterize two dimensional timeseries from a new viewpoint of complex networks.