Operator Inference in Python
This package is a Python implementation of the Operator Inference framework 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.
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Release files for opinf 0.6.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| opinf-0.6.0.tar.gz | 146.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| opinf-0.6.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 324.9 kB
Release files / opinf-0.6.0.tar.gz
| Download URL | opinf-0.6.0.tar.gz |
|---|---|
| Size | 146.1 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/6.2.0 CPython/3.13.7
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Release files / opinf-0.6.0-py3-none-any.whl
| Download URL | opinf-0.6.0-py3-none-any.whl |
|---|---|
| Size | 178.8 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/6.2.0 CPython/3.13.7
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