"""Verify uploaded fold weights against one stored OOF prediction per fold."""

from __future__ import annotations

import csv
import json
from pathlib import Path

import numpy as np

from inference import PseudoSnpSVD64


ROOT = Path(__file__).resolve().parent
OOF = ROOT / "results" / "pseudosnp" / "oof_predictions_pip_ge_0.30.tsv"


def main() -> None:
    model = PseudoSnpSVD64(ROOT)
    examples: dict[int, dict[str, str]] = {}
    with OOF.open("r", encoding="utf-8", newline="") as handle:
        for row in csv.DictReader(handle, delimiter="\t"):
            fold = int(row["outer_fold"])
            examples.setdefault(fold, row)
            if len(examples) == 5:
                break

    if set(examples) != set(range(5)):
        raise RuntimeError("stored OOF evidence does not cover all five folds")

    checks = []
    for fold in range(5):
        row = examples[fold]
        observed = float(
            model.score_pair_by_fold(row["sequence_ref"], row["sequence_alt"])[fold]
        )
        expected = float(row["transfer_fixed_raw_score"])
        close = bool(np.isclose(observed, expected, rtol=0.0, atol=5e-6))
        checks.append(
            {
                "fold": fold,
                "example_id": row["example_id"],
                "expected": expected,
                "observed": observed,
                "absolute_error": abs(observed - expected),
                "passed": close,
            }
        )
    if not all(item["passed"] for item in checks):
        raise AssertionError(json.dumps(checks, indent=2))
    print(json.dumps({"status": "PASS", "checks": checks}, indent=2))


if __name__ == "__main__":
    main()