sph_dataset / examples /README.md
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# Running the Examples
**You do not need to download the full dataset.** Each script has a cap (`N_SUBSET` or
`MAX_IMAGES`) that limits how many simulations or images are loaded. Download any small
subset of simulation directories and point `DATA_DIRS` at them — the scripts will use only
what is available.
## Requirements
```bash
pip install numpy pillow scikit-learn matplotlib torch
```
## Expected data layout
Each simulation directory must contain:
```
<sim_dir>/
parameters.json # process parameters
monitor/position-bounds_melt.dat # melt-pool bounds (regression + classification)
frames.csv # frame labels (generation only)
frames/side/<frame>.png # side-profile images (generation only)
```
Point `DATA_DIRS` in each script at one or more parent directories that hold these
simulation folders.
## Regression — Melt-Pool Width Prediction
```bash
python example_regression.py
```
- **Reviewer shortcut:** set `N_SUBSET = 30` (already the default) to use only the first
30 simulations found — ~1 min on CPU. Set `None` to use all.
- Predicts steady-state melt-pool width from four process parameters.
- Results (parity plots + feature importance) are saved to `runs/regression_<timestamp>/`.
## Classification — Keyhole vs Conduction
```bash
python example_classification.py
```
- **Reviewer shortcut:** set `N_SUBSET = 30` (already the default) to use only the first
30 simulations found — ~1 min on CPU. Set `None` to use all.
- Labels are derived automatically from simulation output — no manual annotation needed.
- Results (confusion matrices + feature importance) are saved to `runs/classification_<timestamp>/`.
## Generation — Unconditional VAE on Side Profiles
```bash
python example_generation.py
```
- **Reviewer shortcut:** set `MAX_IMAGES = 500` (already the default) to cap the number of
frames loaded — ~2 min on CPU. Set `None` to use all images.
- Only frames labeled Keyhole or Conduction are used; Initial Emptiness and Forming Phase are excluded.
- Results (sample grids, reconstructions, loss curve) are saved to `runs/generation_<timestamp>/`.