from __future__ import annotations

import argparse
import json
from pathlib import Path

import numpy as np


def summarize_variant(root: Path, tag: str) -> dict:
    ckpt_dir = root / tag / "checkpoint-100000"
    aggregate_files = sorted(ckpt_dir.glob("val_psnr_*.json"))
    if aggregate_files:
        data = json.loads(aggregate_files[-1].read_text(encoding="utf-8"))
        return {
            "tag": tag,
            "samples": data.get("num_samples", 0),
            "psnr_mean": data.get("psnr_mean"),
            "psnr_std": data.get("psnr_std"),
            "psnr_min": data.get("psnr_min"),
            "psnr_max": data.get("psnr_max"),
            "complete": True,
        }

    metrics_paths = sorted(ckpt_dir.glob("val*/metrics.json"))
    psnr_values = []
    for path in metrics_paths:
        data = json.loads(path.read_text(encoding="utf-8"))
        value = data.get("psnr_mean")
        if value is not None and np.isfinite(value):
            psnr_values.append(float(value))

    if not psnr_values:
        return {
            "tag": tag,
            "samples": 0,
            "psnr_mean": None,
            "psnr_std": None,
            "psnr_min": None,
            "psnr_max": None,
            "complete": False,
        }

    values = np.array(psnr_values, dtype=np.float64)
    return {
        "tag": tag,
        "samples": int(values.size),
        "psnr_mean": float(values.mean()),
        "psnr_std": float(values.std()),
        "psnr_min": float(values.min()),
        "psnr_max": float(values.max()),
        "complete": False,
    }


def main() -> None:
    parser = argparse.ArgumentParser(description="Summarize query val PSNR eval outputs.")
    parser.add_argument("--root", type=Path, default=Path("/workspace/Ctrl-World-Graph/eval_query_val"))
    parser.add_argument(
        "--tags",
        nargs="*",
        default=[
            "gps_query",
            "gine_query",
            "gatv2_query",
            "transformer_query",
            "edge_transformer_query",
            "hybrid_gine_transformer_query",
        ],
    )
    parser.add_argument("--out", type=Path, default=None)
    args = parser.parse_args()

    rows = [summarize_variant(args.root, tag) for tag in args.tags]
    rows.sort(key=lambda row: float("-inf") if row["psnr_mean"] is None else row["psnr_mean"], reverse=True)

    header = "tag\tsamples\tcomplete\tpsnr_mean\tpsnr_std\tpsnr_min\tpsnr_max"
    lines = [header]
    for row in rows:
        fmt = lambda value: "NA" if value is None else f"{value:.4f}"
        lines.append(
            f"{row['tag']}\t{row['samples']}\t{row['complete']}\t"
            f"{fmt(row['psnr_mean'])}\t{fmt(row['psnr_std'])}\t"
            f"{fmt(row['psnr_min'])}\t{fmt(row['psnr_max'])}"
        )
    text = "\n".join(lines)
    print(text)

    if args.out is not None:
        args.out.parent.mkdir(parents=True, exist_ok=True)
        args.out.write_text(text + "\n", encoding="utf-8")


if __name__ == "__main__":
    main()