https://github.com/pmli/l2-opt-interp-ex
L2-optimal interpolation experiments
https://github.com/pmli/l2-opt-interp-ex
research-data
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L2-optimal interpolation experiments
- Host: GitHub
- URL: https://github.com/pmli/l2-opt-interp-ex
- Owner: pmli
- License: mit
- Created: 2022-08-18T21:26:37.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-09-26T20:09:14.000Z (almost 4 years ago)
- Last Synced: 2025-09-05T02:38:20.780Z (10 months ago)
- Topics: research-data
- Language: Python
- Homepage:
- Size: 14.6 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
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README
# Code for Numerical Experiments in "A Unifying Framework for Interpolatory $\mathcal{L}_2$-optimal Reduced-order Modeling"
This repository contains code for numerical experiments reported in
> P. Mlinarić, S. Gugercin,
> **A Unifying Framework for Interpolatory $\mathcal{L}_2$-optimal Reduced-order
> Modeling**,
> [*arXiv preprint*](https://arxiv.org/abs/2209.00714),
> 2022
## Installation
To run the examples, at least Python 3.8 is needed
(the code was tested using Python 3.8.12).
The necessary packages are listed in [`requirements.txt`](requirements.txt).
They can be installed in a virtual environment by, e.g.,
```bash
python3 -m venv .venv
source .venv/bin/activate
pip install -U pip setuptools wheel
pip install -r requirements.txt
```
## Running the Experiments
The experiments are given as `runme_*.py` scripts.
They can be opened as Jupyter notebooks via
[`jupytext`](https://jupytext.readthedocs.io/en/latest/)
(included when installing via [`requirements.txt`](requirements.txt)).
## Author
Petar Mlinarić:
- affiliation: Virginia Tech
- email: mlinaric@vt.edu
- ORCiD: 0000-0002-9437-7698
## License
The code is published under the MIT license.
See [LICENSE](LICENSE).