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Dynax

"Dynamical systems in JAX"

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This is WIP. Expect things to break!

This package allows for straight-forward simulation, fitting and linearization of dynamical systems by combing JAX, Diffrax, Equinox, and scipy.optimize. Its main features include:

  • estimation of ODE parameters and their covariance via the prediction-error method (example)
  • estimation of the initial state (example)
  • estimation of linear ODE parameters via matching of frequency-response functions (example)
  • estimation from multiple experiments
  • estimation with a poor man's multiple shooting (example)
  • input-output linearization of continuous-time input affine systems
  • input-output linearization of discrete-time systems (example)
  • estimation of a system's relative-degree (example)

Documentation is on its way. Until then, have a look at the example and test folders.

Installing

Requires Python 3.9+, JAX 0.4.23+, Equinox 0.11+ and Diffrax 0.5+. With a suitable version of jaxlib installed:

pip install .

Testing

Install with

pip install .[dev]

and run

pytest

To also test the examples, do

pytest --runslow

Related software

  • nlgreyfast: Matlab library for fitting ODE's with mutliple shooting
  • dynamax: inference and learning for probablistic state-space models