"""Plot measured evaluation summaries and collect comparable seed-level results."""

from pathlib import Path
import argparse, json, csv
import numpy as np
import matplotlib

matplotlib.use("Agg")
import matplotlib.pyplot as plt
from matplotlib import font_manager

ROOT = Path(__file__).resolve().parents[1]
for f in (ROOT / "assets/fonts").glob("*.ttf"):
    font_manager.fontManager.addfont(str(f))
plt.rcParams.update(
    {"font.family": "Ubuntu", "mathtext.fontset": "cm", "pdf.fonttype": 42}
)


def plot(paths, output):
    records = [json.loads(Path(p).read_text()) for p in paths]
    rows = []
    for d in records:
        if d.get("protocol") != "split-first-v1":
            raise ValueError("Use corrected evaluation outputs")
        for search, metrics in d["summary"]["inverse"].items():
            rows.append(
                {
                    "method": d["method"],
                    "search": search,
                    "seed": d["seed"],
                    **{k: v["mean"] for k, v in metrics.items()},
                }
            )
    if not rows:
        raise ValueError("No inverse results for this catalog and target split")
    out = Path(output)
    out.mkdir(parents=True, exist_ok=True)
    with open(out / "summary.csv", "w") as f:
        writer = csv.DictWriter(f, fieldnames=list(rows[0]))
        writer.writeheader()
        writer.writerows(rows)
    fig, axes = plt.subplots(1, 2, figsize=(10, 4), layout="constrained")
    labels = [
        r["method"] + "\n" + r["search"] + "\nseed " + str(r["seed"]) for r in rows
    ]
    for ax, k, title in zip(
        axes,
        ["top5", "measured_regret"],
        [
            "Exact Top-5 recovery (higher is better)",
            "Measured regret (lower is better)",
        ],
    ):
        ax.bar(np.arange(len(rows)), [r[k] for r in rows], color="#62AEDD", width=0.6)
        ax.set_xticks(np.arange(len(rows)), labels, fontsize=8)
        ax.set_title(title, fontsize=11)
        ax.spines[["top", "right"]].set_visible(False)
        ax.grid(axis="y", alpha=0.2)
        ax.set_axisbelow(True)
    for ext in ["pdf", "png"]:
        fig.savefig(out / f"evaluation.{ext}", dpi=220)
    plt.close(fig)


if __name__ == "__main__":
    p = argparse.ArgumentParser()
    p.add_argument("results", nargs="+")
    p.add_argument("--output", default="plots")
    a = p.parse_args()
    plot(a.results, a.output)