#!/usr/bin/env python3
"""Example: how to format predictions for PROTAC-Bench evaluation.

This script demonstrates the expected prediction format. Replace the
random predictions with your model's output.

Usage:
    python examples/example_submission.py
    python evaluation/evaluate.py --predictions example_predictions.csv --output my_results.json
"""
import json
from pathlib import Path

import numpy as np
import pandas as pd

DATA_DIR = Path(__file__).resolve().parent.parent / "data"


def main():
    # Load dataset
    df = pd.read_csv(DATA_DIR / "protac_bench.csv")
    print(f"Dataset: {len(df)} entries")

    # === Replace this with your model's predictions ===
    np.random.seed(42)
    predicted_probs = np.random.rand(len(df))
    # ==================================================

    # Format predictions: must have 'index' and 'predicted_probability' columns
    submission = pd.DataFrame({
        "index": range(len(df)),
        "predicted_probability": predicted_probs,
    })

    out_path = Path(__file__).resolve().parent.parent / "example_predictions.csv"
    submission.to_csv(out_path, index=False)
    print(f"Saved {len(submission)} predictions to {out_path}")
    print(f"\nTo evaluate, run:")
    print(f"  python evaluation/evaluate.py --predictions {out_path.name} --output results.json")


if __name__ == "__main__":
    main()