@@ -8,41 +8,34 @@ T. Wenzel, F. Marchetti, E. Perracchione
```
It was used to carry out the numerical experiments and generate the figures for the publication.
The experiments were performed on Linux systems in 2023 and should work with Python versions of that time (e.g., `python3.9`).
The experiments were performed on Linux systems in 2023 and should work with Python versions of that time (e.g., `python3.7`).
The steps below each indicate a setup to be executed in a terminal, resulting in a URL printed to be opened in a browser to view and run the indicated notebooks.
To reproduce the figures and results CHANGE FROM HERE ON!!!
------------------------------------
## Installation
The data collected during the experiments is contained within this repository (in the `notebooks/data_figures` folder), and generating the figures is straightforward:
To create an virtual environment and install the required packages, simply run the `setup.sh` file.
To setup an evironment for regenerating the figures, execute:
```bash
export BASEDIR=$PWD
virtualenv -p python3.9 venv-figures # replace python3.9 with something suitable
. venv-figures/bin/activate
pip install-r requirements-figures.txt
cd$BASEDIR/pymor && pip install-e.
cd$BASEDIR&& ./start_notebook_server.sh
```
After opening the printed URL (the one with `127....`) in a browser, run
- for Figure 1: [`MC_adaptive_model__analysis.md`](notebooks/MC_adaptive_model__analysis.md)
## Downloading data
For the experiments described in Section 4.1, i.e. for the file [`section_4.1_compute_visualize.py`](`section_4.1_compute_visualize.py`), no data is required.
For the experiments described in the Sections 4.2 and 4.3, a data download is required, for which we make use of code from
["bmdal_reg"](https://github.com/dholzmueller/bmdal_reg), see the code within the folder `utils_data`.
## Rerunning experiments and reproducing the plots
To rereun the numerical experiments of Section 4.2 and reproduce its plots, execute:
