DeepAI AI Chat
Log In Sign Up

PySINDy: A comprehensive Python package for robust sparse system identification

by   Alan A. Kaptanoglu, et al.
University of Washington

Automated data-driven modeling, the process of directly discovering the governing equations of a system from data, is increasingly being used across the scientific community. PySINDy is a Python package that provides tools for applying the sparse identification of nonlinear dynamics (SINDy) approach to data-driven model discovery. In this major update to PySINDy, we implement several advanced features that enable the discovery of more general differential equations from noisy and limited data. The library of candidate terms is extended for the identification of actuated systems, partial differential equations (PDEs), and implicit differential equations. Robust formulations, including the integral form of SINDy and ensembling techniques, are also implemented to improve performance for real-world data. Finally, we provide a range of new optimization algorithms, including several sparse regression techniques and algorithms to enforce and promote inequality constraints and stability. Together, these updates enable entirely new SINDy model discovery capabilities that have not been reported in the literature, such as constrained PDE identification and ensembling with different sparse regression optimizers.


Robust Data-Driven Discovery of Partial Differential Equations under Uncertainties

Robust physics (e.g., governing equations and laws) discovery is of grea...

Learning Sparse Nonlinear Dynamics via Mixed-Integer Optimization

Discovering governing equations of complex dynamical systems directly fr...

SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics

Accurately modeling the nonlinear dynamics of a system from measurement ...

Stability selection enables robust learning of partial differential equations from limited noisy data

We present a statistical learning framework for robust identification of...

Arby - Fast data-driven surrogates

The availability of fast to evaluate and reliable predictive models is h...

Sparsistent Model Discovery

Discovering the partial differential equations underlying a spatio-tempo...