mini-pricing.py

from pathlib import Path

import pandas as pd
from minires import minires

# ==== Edit these numbers for your context ====
RESIN_COST_PER_GRAM = 0.06   # in your currency, e.g. 0.06 = €0.06/gram
OVERHEAD_PER_MINI = 1.50     # fixed overhead per miniature (packaging, time, etc.)
INPUT_CSV = Path("stl_features.csv")
OUTPUT_CSV = Path("mini_pricing.csv")
# =============================================

def main() -> None:
    if not INPUT_CSV.exists():
        raise SystemExit(f"Input CSV not found: {INPUT_CSV}. "
                         "Run stl-scanner.py first.")

    # Load STL features produced by stl-scanner.py
    df = pd.read_csv(INPUT_CSV)

    # Create MiniRes ensemble model
    model = minires(verbose=0)

    # Predict resin usage in grams
    grams = model.predict(df)

    df["predicted_grams"] = grams
    df["resin_cost"] = df["predicted_grams"] * RESIN_COST_PER_GRAM
    df["overhead"] = OVERHEAD_PER_MINI
    df["total_cost"] = df["resin_cost"] + df["overhead"]

    df.to_csv(OUTPUT_CSV, index=False)
    print(f"Wrote pricing table to {OUTPUT_CSV.resolve()}")

if __name__ == "__main__":
    main()