Award winning software library for nonlinear dynamics and nonlinear timeseries analysis
DynamicalSystems.jl is an award-winning Julia software library for nonlinear dynamics and nonlinear timeseries analysis.
To install DynamicalSystems.jl, run import Pkg; Pkg.add("DynamicalSystems")
.
To learn how to use it and see its contents visit the documentation, which you can either find online or build locally by running the docs/make.jl
file.
DynamicalSystems.jl is part of JuliaDynamics, an organization dedicated to creating high quality scientific software.
Aspects of DynamicalSystems.jl that make it stand out among other codebases for nonlinear dynamics or nonlinear timeseries analysis are:
The primary goal of DynamicalSystems.jl is to be a library in the literal sense: where people go to learn something (here in particular for nonlinear dynamics). That is why the main priority is that the documentation is detailed and references articles and why the source code is written as clearly as possible, so that it is examinable by any user.
The second goal is to fill the missing gap of high quality general purpose software for nonlinear dynamics which can be easily extended with new functionality. The purpose of this is to make the field of nonlinear dynamics accessible and reproducible.
The third goal is to fundamentally change the perception of the role of code in both scientific education as well as research. It is rarely the case that real, runnable code is shown in the classroom, because it is often long and messy. This is especially hurtful for nonlinear dynamics, a field where computer-assisted exploration is critical. And published scientific work in this field fares even worse, with the overwhelming majority of published research not sharing the code used to create the paper. This makes reproducing these papers difficult, while some times straight-out impossible. DynamicalSystems.jl can change this situation, because it is high level (requires writing little code to get lots of results) while offering extensive and well-tested functionality.