Metadata-Version: 2.1
Name: opinf
Version: 0.4.5
Summary: Operator Inference for data-driven model reduction of dynamical systems.
Author-email: Willcox Research Group <kwillcox@oden.utexas.edu>
Maintainer-email: "Shane A. McQuarrie" <shanemcq@utexas.edu>
License: MIT License
        
        Copyright (c) 2023 Willcox Research Group
        
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Project-URL: homepage, https://willcox-research-group.github.io/rom-operator-inference-Python3/source/index.html
Project-URL: documentation, https://willcox-research-group.github.io/rom-operator-inference-Python3/source/index.html
Project-URL: repository, https://github.com/Willcox-Research-Group/rom-operator-inference-Python3.git
Keywords: operator inference,model reduction,scientific machine learning
Classifier: Programming Language :: Python :: 3
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Classifier: Development Status :: 4 - Beta
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Provides-Extra: tests
Provides-Extra: docs
License-File: LICENSE

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# Operator Inference in Python

This is a Python implementation of Operator Inference for learning projection-based 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.
The methodology was [introduced in 2016 by Peherstorfer and Willcox](https://www.sciencedirect.com/science/article/pii/S0045782516301104).

[**See the Documentation Here**](https://Willcox-Research-Group.github.io/rom-operator-inference-Python3/).

---

**Contributors**:
[Shane McQuarrie](https://github.com/shanemcq18),
[Renee Swischuk](https://github.com/swischuk),
[Elizabeth Qian](https://github.com/elizqian),
[Boris Kramer](http://kramer.ucsd.edu/),
[Karen Willcox](https://kiwi.oden.utexas.edu/).
