Operator Inference in Python#
Attention
This documentation is for opinf version 0.5.x, which introduced major changes from the previous version 0.4.5.
See updates and notes for old versions here.
This package is a Python implementation of Operator Inference (OpInf), a projection-based model reduction technique for learning polynomial reduced-order models of dynamical systems. The procedure is data-driven and non-intrusive, making it a viable candidate for model reduction of “glass-box” systems where the structure of the governing equations is known but intrusive code queries are unavailable.
Get started with What is Operator Inference? or head straight to Installation and the first tutorial, Getting Started. See Literature for a list of scholarly works on operator inference.
Contents#
Operator Inference
API Reference
Developer Guide