A repository for exploring nonlinear dynamics, chaos, fractals, and related topics using Python.
The Dynamical Systems Visualizer is a modular, containerized web application for modeling and visualizing a variety of chaotic and dynamical systems in two or three dimensions. The app is fully Dockerized and can be run locally or deployed to the cloud with ease.
The visualizer provides interactive 3D renderings of several well-known dynamical systems. Example screenshots:
These visualizations highlight the rich and complex behaviors of nonlinear systems, including chaos and fractal structures.
- Lightweight & High-Performance: Built with vanilla JavaScript and Three.js, without heavy frameworks.
- Interactive Controls: Real-time camera manipulation (rotate, pan, zoom) and parameter adjustment.
- Responsive Design: Works on both desktop and mobile devices.
- Multiple Systems Supported: Lorenz, Rössler, Chua, and Chen attractors, with more planned.
- Development: Easily served locally with any static file server or via Docker.
- Modern Python API: Implemented with FastAPI and Pydantic for robust, type-safe endpoints.
- Dynamical System Computation: Supports multiple systems (Lorenz, Rössler, Chua, Chen, etc.) with real-time parameterization.
- CORS Enabled: Allows seamless communication with the frontend.
- Containerized: Runs in its own Docker container for isolation and reproducibility.
- Separation of Concerns: Frontend and backend are containerized separately for modular deployment.
- Simple Orchestration: Use
docker-composeto build and run the entire application stack. - Consistent Environments: Ensures identical behavior across platforms and deployments.
- Refactor and modularize visualization code for easier extension.
- Add more dynamical systems and visualization types.
- Expand unit testing and improve logging for reliability.
- Enhance user interface and add more interactive features.
See the dynamical_systems_visualizer directory for up-to-date code and documentation.