Operator Inference for Quadratic Manifold Encodings
<p>This is the code and data for the numerical results in our preprint</p> <p>> Benner, Goyal, Heiland, Pontes: *A quadratic decoder approach to nonintrusive reduced-order modeling of nonlinear dynamical systems*</p> <p>To reproduce the results and plots, unzip this repo, `cd` into it, and run</p> <p>```sh<br> python runme.py<br> ```</p> <p>in an environment that comes with</p> <p> * `python` (tested for version `3.8.10`)<br> * `numpy` (tested for version `1.19.5`, `1.23.3`)<br> * `scipy` (tested for version `1.5.2`, `1.9.1`)<br> * `matplotlib` (tested for version `3.3.2`, `3.6.0`)</p> <p> </p>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4