import os
import json
import argparse
from pathlib import Path
import pandas as pd
import matplotlib.pyplot as plt

# ------------------ 参数解析 ------------------ #
def parse_args():
    p = argparse.ArgumentParser()
    p.add_argument("root", type=str,
                   help="Directory containing 12 month subfolders (e.g., 2407 .. 2506)")
    p.add_argument("--out-dir", type=str, default=None,
                   help="Output directory (default: ROOT)")
    return p.parse_args()

# ------------------ JSON加载函数 ------------------ #
def load_month_values_json(root: Path, month: str):
    # 常见路径候选
    candidates = []
    candidates.append(root / month / "values.json")
    candidates.append(root / f"{month}_full" / "values.json")
    candidates.append(root / f"{month}_lr4e-5" / "values.json")

    # fallback：任意以 month 开头的子目录
    for path in sorted(root.glob(f"{month}*/values.json")):
        if path not in candidates:
            candidates.append(path)
    for path in sorted(root.glob(f"{month}*/metrics.json")):
        if path not in candidates:
            candidates.append(path)

    for c in candidates:
        if c.exists():
            return c
    return None

# ------------------ 主逻辑 ------------------ #
def main():
    args = parse_args()
    root = Path(args.root)
    out_dir = Path(args.out_dir) if args.out_dir else root

    months = ["origin", "2407","2408","2409","2410","2411","2412",
              "2501","2502","2503","2504","2505","2506"]

    main_tasks = [
        "arc_easy",
        "arc_challenge",
        "hellaswag",
        "sciq",
        "truthfulqa_mc1",
        "truthfulqa_mc2",
    ]

    records = []

    for tag in months:
        path = load_month_values_json(root, tag)
        if path is None:
            continue

        with open(path, "r", encoding="utf-8") as f:
            data = json.load(f)

        for rec in data.get("tasks", []):
            task = rec.get("task", "")
            metric = rec.get("metric", "")
            value = rec.get("value", None)
            if task in main_tasks and metric in ("acc", "acc_norm"):
                records.append({
                    "month": tag,
                    "task": task,
                    "metric": metric,
                    "value": value
                })

        for rec in data.get("groups", []):
            group = rec.get("group", "")
            metric = rec.get("metric", "")
            value = rec.get("value", None)
            if group == "mmlu" and metric == "acc":
                records.append({
                    "month": tag,
                    "task": "mmlu",
                    "metric": "acc",
                    "value": value
                })

    df = pd.DataFrame.from_records(records)
    if df.empty:
        df = pd.DataFrame(columns=["month","task","metric","value"])

    # 月份排序
    def month_sort_key(x):
        if x == "origin":
            return (0, 0)
        try:
            return (1, int(x))
        except Exception:
            return (2, x)

    df["month"] = pd.Categorical(
        df["month"],
        categories=sorted(df["month"].unique(), key=month_sort_key),
        ordered=True
    )
    df = df.sort_values(["task","metric","month"])

    # 保存 CSV
    csv_path = out_dir / "monthly_metrics.csv"
    df.to_csv(csv_path, index=False)

    # 画折线图
    plt.figure(figsize=(12, 6))
    series_keys = sorted(df[["task","metric"]].drop_duplicates().apply(tuple, axis=1))
    n = len(series_keys)
    cmap = plt.colormaps['tab20'].resampled(n)


    for i, (task, metric) in enumerate(series_keys):
        sub = df[(df["task"] == task) & (df["metric"] == metric)].sort_values("month")
        if sub.empty:
            continue
        color = cmap(i % n) if n <= 20 else cmap(i / n)
        plt.plot(sub["month"].astype(str), sub["value"],
                 marker="o",
                 color=color,
                 label=f"{task}—{metric}")

    plt.xlabel("Month")
    plt.ylabel("Score")
    plt.title("Monthly Evaluation Trends (Main Tasks)")
    plt.legend(loc='best', bbox_to_anchor=(1, 0.5))
    plt.tight_layout()

    png_path = out_dir / "monthly_metrics.png"
    plt.savefig(png_path, dpi=150)

if __name__ == "__main__":
    main()