pynamicalsys: A Python toolkit for the analysis of dynamical systems
Since Lorenz’s seminal work on a simplified weather model, the numerical analysis of nonlinear dynamical systems has become one of the main subjects of research in physics. Despite of that, there remains a need for accessible, efficient, and easy-to-use computational tools to study such systems. In...
Saved in:
| Published in: | Chaos, solitons and fractals Vol. 201; p. 117269 |
|---|---|
| Main Authors: | , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01.12.2025
|
| Subjects: | |
| ISSN: | 0960-0779 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Since Lorenz’s seminal work on a simplified weather model, the numerical analysis of nonlinear dynamical systems has become one of the main subjects of research in physics. Despite of that, there remains a need for accessible, efficient, and easy-to-use computational tools to study such systems. In this paper, we introduce ▪ , a simple yet powerful open-source Python module for the analysis of nonlinear dynamical systems. In particular, ▪ implements tools for trajectory simulation, bifurcation diagrams, Lyapunov exponents and several others chaotic indicators, period orbit detection and their manifolds, as well as escape and basins analysis. We demonstrate the capabilities of ▪ through a series of examples that reproduces well-known results in the literature while developing the mathematical analysis at the same time. We also provide the Jupyter notebook containing all the code used in this paper, including performance benchmarks. ▪ is freely available via the Python Package Index (PyPI) and is intended to support both research and teaching in nonlinear dynamics.
•An open source Python package for the analysis of dynamical systems.•pynamicalsys includes bifurcation diagrams, chaotic indicators, periodic orbits detection and their manifolds.•The package also includes quantification of basins of attractions, such as basin entropy and boundary dimension. |
|---|---|
| ISSN: | 0960-0779 |
| DOI: | 10.1016/j.chaos.2025.117269 |