# Run 2026-03-10_0834_6b761f

Conventional optimization (stochastic, regret, robust) and plotting for **variant_zero**, **variant_one**, and **variant_two**. Config and input data (scenario, series, variant_*) are in this folder. Run the commands below from the **eta-incerto** project root. Replace `DATA_REPO` with the path to the data repo clone (e.g. `../research-and-optimization-data-management-organizer` or an absolute path such as `C:/Git/research-and-optimization-data-management-organizer`).

## Run optimization from the data repo

From **eta-incerto** root, point `--run-dir` at this run in the data repo:

```bash
python -m examples.conventional.main --run-dir DATA_REPO/runs/2026-03-10_0834_6b761f --config config
```

Results are written to `results/` inside this run folder.

## Run plotting from the data repo

From **eta-incerto** root, run the plot entry point with this run directory:

```bash
python -m examples.conventional.main_plot --run-dir DATA_REPO/runs/2026-03-10_0834_6b761f
```

Plots are written to `plots/` inside this run folder (config uses `config.json` in the run dir).

## Optional: run from inside the run directory

```bash
cd DATA_REPO/runs/2026-03-10_0834_6b761f
python -m examples.conventional.main --run-dir . --config config
python -m examples.conventional.main_plot --run-dir .
```

## Config and results

- **config** – main config (`config.json`); includes conventional, antifragile/pymoo, and plot settings.
- **results/** – optimization outputs (e.g. `.h5`, LP exports).
- **plots/** – generated figures (e.g. technical summary, investment summary).
