examples/README.md

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

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

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

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

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>/.