Article URL: https://github.com/dynamicslab/pysindy Comments URL: https://news.ycombinator.com/item?id=49039007 Points: 3 # Comments: 1

PySINDy is a package for system identification, primarily revolving around the method of Sparse Identification of Nonlinear Dynamical systems (SINDy) method introduced in Brunton et al. (2016a). It also includes other methods from related literature. System identification refers to the process of using measurement data to infer the governing dynamics. Once discovered, these equations can make predictions about future states, can inform control inputs, or can enable the theoretical study using analytical techniques. The resulting models are inherently interpretable and generalizable. The preferred way to install is with pip or conda e.g. pip install pysindy. You may have to add the --user option. Pysindy also provides several extras, e.g. pip install pysindy[miosr]: Suppose we have measurements of the position of a particle obeying the following dynamical system at different points in time Note that this system of differential equations decouples into two differential equations whose solutions are simply This example uses the initial conditions x_0 = 3 and y_0 = 0.5. It then fits and prints the discovered model PySINDy provides numerous other features not shown here. We have a variety of tutorials and examples, starting with generating data and fitting models.