A Python toolkit for the analysis of dynamical systems
Project description
pynamicalsys: A Python toolkit for the analysis of dynamical systems
Overview
pynamicalsys is designed to provide a fast, flexible, and user-friendly environment for analyzing nonlinear dynamical systems. It is intended for students, researchers, educators, and enthusiasts who want to explore the world of chaos and dynamical systems. Beyond standard tools like trajectory generation and Lyapunov exponents calculation, pynamicalsys includes advanced features such as
- Linear dependence index for chaos detection.
- Recurrence plots and recurrence time statistics.
- Chaos indicators based on weighted Birkhoff averages.
- Statistical measures of diffusion and transport in dynamical systems.
- Computation of periodic orbits, their stability and their manifolds.
- Basin metric for quantifying the structure of basins of attraction.
- Plot styling for consistent and customizable visualizations.
pynamicalsys is built on top of NumPy and Numba, ensuring high performance and efficiency. Thanks to Numba accelerated computation, pynamicalsys offers speedups up to 130x compared to the original Python implementation of the algorithms. This makes it suitable for large-scale simulations and analyses.
Installation
Prerequisites
- Python 3.8 or higher
- pip (Python package installer)
Install via PyPI
To install the latest stable release, run in your command line:
$ pip install pynamicalsys
Note: On Windows, it is strongly recommended to use Anaconda. It simplifies dependency management and avoids potential issues with scientific libraries during installation. Be sure to run the command from the Anaconda Prompt, not from Command Prompt or PowerShell, to ensure the correct environment is activated.
Upgrade via PyPI
To upgrade your current version of pynamicalsys to the latest stable release, run in your command line:
$ pip install pynamicalsys --upgrade
Install from source
If you want to install the development version from the source repository, clone the repo and install with:
$ git clone https://github.com/mrolims/pynamicalsys.git
$ cd pynamicalsys
$ pip install .
Verifying the installation
After installation, you can verify it by running Python and importing the package:
>>> import pynamicalsys
>>> pynamicalsys.__version__
Troubleshooting
If you encounter any issues, make sure you have the latest version of pip:
$ pip install --upgrade pip build
Citation
Currently, our research paper is under review, but in the mean time, if you use pynamicalsys in your work, you can cite the arXiv version:
@misc{pynamicalsys,
title={pynamicalsys: A Python toolkit for the analysis of dynamical systems},
author={Matheus Rolim Sales and Leonardo Costa de Souza and Daniel Borin and Michele Mugnaine and José Danilo Szezech Jr. and Ricardo Luiz Viana and Iberê Luiz Caldas and Edson Denis Leonel and Chris G. Antonopoulos},
year={2025},
eprint={2506.14044},
archivePrefix={arXiv},
primaryClass={nlin.CD},
url={https://arxiv.org/abs/2506.14044},
}
Contributing
We welcome contributions from the community! To get started, please see our Contributing Guidelines.
License
This project is licensed under the GNU General Public License v3.0.
See the LICENSE file for details.
Acknowledgments
This project was financed, in part, by the São Paulo Research Foundation (FAPESP, Brazil), under process numbers 2023/08698-9 and 2024/09208-8.
Disclaimer
As opiniões, hipóteses e conclusões ou recomendações expressas neste material são de responsabilidade do(s) autor(es) e não necessariamente refletem a visão da Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, Brasil).
The opinions, hypotheses, and conclusions or recommendations expressed in this material are the sole responsibility of the author(s) and do not necessarily reflect the views of the São Paulo Research Foundation (FAPESP, Brazil).
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