DynamicalSystems.jl

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About

DynamicalSystems.jl is ranked #9 of 91 in physics simulation software on Inferse, made by DynamicalSystems.jl. It runs on Linux, macOS, Windows. There is a free plan.

Compared on physics simulation software

Free plan: Yesjuliadynamics.github.io
Delivery mode: desktopjuliadynamics.github.io
Authoring tools: Yesjuliadynamics.github.io
3D visuals: Yesjuliadynamics.github.io
Offline access: Yesjuliadynamics.github.io
Data export: Yesjuliadynamics.github.io

Facts

Purpose: DynamicalSystems.jl is a Julia-based general-purpose library for nonlinear dynamics and nonlinear time-series analysis.juliadynamics.github.io · 4 Oct 2026
Open source: The project describes itself as 100% open source and community-built on GitHub.juliadynamics.github.io · 4 Oct 2026
Composable packages: The library re-exports packages for measured time-series analysis and dynamical-system instances, including ComplexityMeasures, DelayEmbeddings, ChaosTools, Attractors, and PeriodicOrbits.juliadynamics.github.io · 4 Oct 2026
Visualization: The documentation says the library includes functionality for interactive or offline animations and visualizations.juliadynamics.github.io · 4 Oct 2026
Documentation: The project says its documentation includes hundreds of tutorials and examples, with scientific descriptions and references for implemented algorithms.juliadynamics.github.io · 4 Oct 2026
Performance: The project says it is written entirely in Julia, optimized, and parallelized.juliadynamics.github.io · 4 Oct 2026
Installation: The documented installation command is `import Pkg; Pkg.add("DynamicalSystems")` in Julia.juliadynamics.github.io · 4 Oct 2026
Integrations: The documentation says Julia interoperability lets users of Python, R, and MATLAB use parts of the ecosystem, and gives juliacall as a Python example for ComplexityMeasures.jl.juliadynamics.github.io · 4 Oct 2026
Testing: The project says its functionality is extensively tested and its test suite is run and checked before code changes are merged.juliadynamics.github.io · 4 Oct 2026
Support: Users can ask questions through Julia Discourse, Julia Slack, or GitHub issues, with the project recommending Discourse for involved questions and issues for unexpected behavior.juliadynamics.github.io · 4 Oct 2026
Audience: The project describes use in scientific research and education, and says it gives teachers a framework for demonstrating runnable nonlinear-dynamics code.juliadynamics.github.io · 4 Oct 2026
Notable limitation: The documentation cautions that PredefinedDynamicalSystems.jl has no actual tests, is not guaranteed stable, and is intended for demonstrative examples.juliadynamics.github.io · 4 Oct 2026
Analysis methods: The library includes tools for complexity measures, delay embeddings, periodic orbits, stability analysis, attractor basins, continuation, chaos, fractal dimensions, surrogate testing, and recurrence quantification.juliadynamics.github.io · 4 Oct 2026
Reproducibility: The project aims to support reproducible analyses through Julia's environment support, testing, and a broad collection of ready to use algorithms.juliadynamics.github.io · 4 Oct 2026
Interactive visualization: With Makie in scope, the library provides visualization tools including interactive trajectory interfaces and specialized GUI applications.juliadynamics.github.io · 4 Oct 2026
Maintenance: The library is maintained by George Datseris and includes contributions from multiple people.juliadynamics.github.io · 4 Oct 2026
Compatibility caveat: The documentation says version numbers do not strictly follow SemVer 2.0 and minor breaking changes to individual algorithms may occur without a major version increment.juliadynamics.github.io · 4 Oct 2026