"""Generate public v5 engine goldens; expected values come from accepted research."""
from __future__ import annotations

import json
import hashlib
import platform
from pathlib import Path

from scripts.research import varga_resolution_lib as vr

ROOT = Path(__file__).resolve().parents[2]


def main():
    cache = ROOT / "artifacts/varga-impl-validation-20260930/replay-cache"
    accepted_path = ROOT / "docs/research/varga_resolution_research_2026_09_30.json"
    accepted = json.loads(accepted_path.read_text(encoding="utf-8"))
    records = []
    for case in vr.load_cases()[:12]:
        for radius in (10, 30):
            replay = vr.CaseReplay(case, radius, cache_dir=cache)
            state = vr.replay_scores(replay.public, replay.probes, replay.true_time)
            for chart in ("D1", "D9", "D10"):
                segments = replay.segments((chart,))
                ordered = vr.select_probes_by_segment(replay.public, replay.probes, segments, replay.true_time)
                summary = vr.segment_shares(vr.minute_weights(state, "raw"), segments, replay.true_time)
                accepted_cell = next(row for row in accepted["m1"]["by_radius"][str(radius)][chart]["raw"]["per_case"]
                                     if row["case_id"] == replay.case_id)
                actual_cell = {key: summary[key] for key in ("top_share", "top_is_truth", "truth_retained", "alive_segments")}
                actual_cell["segments_in_window"] = len(segments)
                if any(value != accepted_cell[key] for key, value in actual_cell.items()):
                    raise ValueError(f"accepted_raw_parity_mismatch:{replay.case_id}:{radius}:{chart}; use the calibrated Python runtime")
                records.append({
                    "case_id": replay.case_id, "radius": radius, "chart": chart,
                    "rows": replay.public,
                    "posterior_rows": state["public"], "eliminated": sorted(state["eliminated"]),
                    "probes": replay.probes, "segments": segments,
                    "offsets": {minute: vr.offset_of(minute, replay.true_time) for minute in replay.times},
                    "truth_offset": 0, "truth_time": replay.true_time,
                    "expected_summary": summary, "accepted_cell": actual_cell,
                    "expected_order": [probe["semantic_key"] for probe in ordered["asked"]],
                    "answers": {probe["semantic_key"]: vr.optimal_answer(probe, replay.true_time) for probe in replay.probes},
                })
    path = ROOT / "frontend/tests/fixtures/varga-segment-v5-golden.json"
    path.write_text(vr.stable_json({
        "source": "v5 public AA engine responses; raw cells strictly verified against accepted research",
        "python_version": platform.python_version(),
        "accepted_sha256": hashlib.sha256(accepted_path.read_bytes()).hexdigest(),
        "order_source": "sequential accepted research function; m2 JSON does not store semantic-key lists",
        "records": records,
    }), encoding="utf-8")
    print(f"generated {len(records)} chart goldens across 12 public cases")


if __name__ == "__main__":
    main()