复杂性测量.jl:可扩展的软件,以统一和加速和复杂性时间序列分析
George Datseris1, Kristian Agasøster Haaga2,3,4
1Department of Mathematics and Statistics, University of Exeter, Exeter, United Kingdom.
PloS one
|June 13, 2025
概括
复杂度测量.jl是一个新的开源软件用于非线性时间序列分析,提供1638个复杂度测量. 它的可组合设计确保了研究人员的高性能和可扩展性.
科学领域:
- 非线性动力学和时间序列分析.
背景情况:
- 在非线性时间序列分析中,和复杂度指标的扩散给软件开发和研究人员的决策带来了挑战.
- 需要一个统一的,可持续的软件解决方案来有效地管理和应用这些多样化的措施.
研究的目的:
- 为非线性时间序列分析而设计的开源软件ComplexityMeasures.jl进行介绍.
- 为研究人员提供一个全面的,高性能工具,用于访问和利用各种各样的复杂度测量.
- 与现有的替代方案相比,展示软件的设计,性能和可扩展性.
主要方法:
- 开发复杂性测量.jl的数学严格,可组合的设计.
- 在软件中实现1638个不同的复杂度指标.
- 与基于性能,测量数量,可靠性和可扩展性的替代软件解决方案对比,对ComplexityMeasures.jl进行比较分析.
主要成果:
- 复杂度指标.jl提供1638个复杂度指标,具有高效的代码 (2.3行/指标).
- 与替代方案相比,该软件表现出卓越的计算性能,可靠性和可扩展性.
- 它集成到DynamicalSystems.jl库中,促进开源开发实践.
结论:
- 复杂性测量.jl为非线性时间序列分析提供了可持续且高性能的解决方案.
- 它的设计促进了明智的措施选择,并加速了与复杂性相关的研究.
- 该软件促进一个协作社区的持续发展和贡献.
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