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ComplexityMeasures.jl: Scalable software to unify and accelerate entropy and complexity timeseries analysis
George Datseris1, Kristian Agasøster Haaga2,3,4
1Department of Mathematics and Statistics, University of Exeter, Exeter, United Kingdom.
Plos One
|June 13, 2025
Summary
ComplexityMeasures.jl is a new open-source software for nonlinear timeseries analysis, offering 1638 complexity measures. Its composable design ensures high performance and extensibility for researchers.
Area of Science:
- Nonlinear dynamics and time series analysis.
Background:
- The proliferation of entropy and complexity measures in nonlinear time series analysis poses challenges for software development and researcher decision-making.
- A unified, sustainable software solution is needed to manage and apply these diverse measures effectively.
Purpose of the Study:
- To introduce ComplexityMeasures.jl, an open-source software designed for nonlinear time series analysis.
- To provide researchers with a comprehensive, high-performance tool for accessing and utilizing a vast array of complexity measures.
- To demonstrate the software's design, performance, and extendability compared to existing alternatives.
Main Methods:
- Development of ComplexityMeasures.jl with a mathematically rigorous, composable design.
- Implementation of 1638 distinct complexity measures within the software.
- Comparative analysis of ComplexityMeasures.jl against alternative software solutions based on performance, measure count, reliability, and extendability.
Main Results:
- ComplexityMeasures.jl offers 1638 complexity measures with highly efficient code (2.3 lines/measure).
- The software demonstrates superior computational performance, reliability, and extendability compared to alternatives.
- It is integrated into the DynamicalSystems.jl library, promoting open-source development practices.
Conclusions:
- ComplexityMeasures.jl provides a sustainable and performant solution for nonlinear time series analysis.
- Its design facilitates informed measure selection and accelerates complexity-related research.
- The software fosters a collaborative community for ongoing development and contribution.
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