This directory showcases the following examples of PySINDy in action.
This notebook gives an almost exhaustive overview of the different features available in PySINDy. It's a good reference for how to set various options and work with different types of datasets.
We recommend that people new to SINDy start here. We give a gentle introduction to the SINDy method and how different steps in the algorithm are represented in PySINDy. We also show how to use PySINDy to learn a model for a simple linear differential equation.
This notebook uses PySINDy to reproduce the examples in the original SINDy paper. Namely, it applies PySINDy to the following problems:
- Linear 2D ODE
- Cubic 2D ODE
- Linear 3D ODE
- Lorenz system
- Fluid wake behind a cylinder
- Logistic map
- Hopf system
Shows how PySINDy interfaces with various Scikit-learn objects.
- Cross-validation
- Sparse regressors
Explore the differentiation methods available in PySINDy on pure differentiation problems and as components in the SINDy algorithm.
See a demonstration of PySINDy objects designed to conform to the Scikit-time API.