"""Recompute judged task F1 per system from test_answers.jsonl, plus a paired bootstrap against Heed.

    python3 score.py                      # first judge (Gemini 3.1 Pro), all public test notes
    python3 score.py --judge gpt          # second judge (GPT-5.4), the notes it also judged

Per note and system the judge gave each listed task good / fixable / wrong, and listed what was missed.
    precision = good / (good + fixable + wrong)
    recall    = good / (good + fixable + missed)
F1 is computed on the totals over the notes (micro), using only notes that have a valid verdict for every system.
Paired bootstrap: 4,000 resamples of the notes (seed 0), the same resamples for every system, system F1 minus Heed F1.
No third-party packages.
"""
import argparse
import json
import os
import random

HEED = "heed_qwen3_0.6b_int8_phone"
ORDER = [HEED, "claude_sonnet_5.5_key", "claude_haiku_5.5", "gemini_3.5_flash", "gpt_5.4_mini"]


def counts(verdicts):
    items = verdicts["items"]
    good = sum(1 for x in items if x["verdict"] == "good")
    fix = sum(1 for x in items if x["verdict"] == "fixable")
    wrong = sum(1 for x in items if x["verdict"] == "wrong")
    return good, fix, wrong, len(verdicts["missed"])


def f1(rows, ids):
    tp = sum(rows[i][0] for i in ids)
    listed = sum(rows[i][0] + rows[i][1] + rows[i][2] for i in ids)
    want = sum(rows[i][0] + rows[i][1] + rows[i][3] for i in ids)
    p, r = tp / max(1, listed), tp / max(1, want)
    return 2 * p * r / (p + r) if p + r else 0.0


def gap(a, b, ids, turns=4000):
    rnd = random.Random(0)
    d = sorted(f1(a, s) - f1(b, s) for s in ([rnd.choice(ids) for _ in ids] for _ in range(turns)))
    return 100 * (f1(a, ids) - f1(b, ids)), 100 * d[int(0.025 * turns)], 100 * d[int(0.975 * turns)]


def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--judge", choices=["gemini", "gpt"], default="gemini")
    ap.add_argument("--file", default=os.path.join(os.path.dirname(os.path.abspath(__file__)), "test_answers.jsonl"))
    args = ap.parse_args()
    field = "judge_gemini_3_1_pro" if args.judge == "gemini" else "judge_gpt_5_4"
    rows = {k: {} for k in ORDER}
    for line in open(args.file, encoding="utf-8"):
        r = json.loads(line)
        for k in ORDER:
            v = r["systems"].get(k, {}).get(field)
            if v:
                rows[k][r["id"]] = counts(v)
    ids = sorted(set.intersection(*[set(v) for v in rows.values()]))
    name = "Gemini 3.1 Pro" if args.judge == "gemini" else "GPT-5.4"
    print(f"Judge: {name}. {len(ids)} public test notes judged for all five systems. Judged task F1 (%), and system minus Heed [95% interval]")
    for k in ORDER:
        if k == HEED:
            print(f"  {k:30s} F1 {100 * f1(rows[k], ids):5.1f}")
        else:
            g = gap(rows[k], rows[HEED], ids)
            print(f"  {k:30s} F1 {100 * f1(rows[k], ids):5.1f}   minus Heed {g[0]:+5.1f} [{g[1]:+5.1f}, {g[2]:+5.1f}]")
    print("Verdict totals (good, fixable, wrong, missed):")
    for k in ORDER:
        t = [sum(rows[k][i][j] for i in ids) for j in range(4)]
        print(f"  {k:30s} {tuple(t)}")


if __name__ == "__main__":
    main()