"""
PySWMM 内水氾濫デモ
=====================

目的
----
EPA SWMM の入力ファイル（.inp）を PySWMM から実行し、
マンホール越水量、ノード水深、管渠流量をCSVへ出力します。

実務での使い方
--------------
1. SWMM GUI / swmmio / 自作スクリプトで .inp を作成
2. このスクリプトで複数降雨ケースを自動実行
3. マンホール越水量をCSV化
4. ANUGA等の2次元氾濫解析へ点源として渡す

注意
----
このサンプルはデモサイト用の最小構成です。
実務では、管渠台帳、マンホール地盤高、排水区、吐口水位、
ポンプ運転条件、キャリブレーション結果を反映してください。
"""

from __future__ import annotations

import argparse
import math
from pathlib import Path
from typing import Any

import pandas as pd


def safe_get(obj: Any, name: str, default: float = math.nan) -> float:
    """PySWMMのバージョン差・属性未定義に備えた安全な属性取得。"""
    try:
        value = getattr(obj, name)
        return float(value() if callable(value) else value)
    except Exception:
        return default


def create_synthetic_results(out_csv: Path) -> pd.DataFrame:
    """PySWMMをインストールしていない環境でもページ確認できる簡易結果を作成。"""
    import numpy as np

    minutes = np.arange(0, 181, 5)
    rain = 7 * np.exp(-((minutes - 70) / 30) ** 2) + 3 * np.exp(-((minutes - 105) / 18) ** 2)
    rows = []
    for minute, r in zip(minutes, rain):
        for node_id, coef, lag in [("J1", 0.05, 0), ("J2", 0.04, 10), ("J3", 0.025, 20), ("J4", 0.015, 25)]:
            rr = float(np.interp(max(0, minute - lag), minutes, rain))
            flooding = max(0.0, coef * (rr - 4.0))
            depth = 0.25 + 2.2 * (1 - math.exp(-rr / 7.0))
            rows.append({
                "elapsed_min": int(minute),
                "object_type": "node",
                "object_id": node_id,
                "depth_m": depth,
                "flooding_m3s": flooding,
                "flow_m3s": math.nan,
                "velocity_ms": math.nan,
            })
        for link_id, coef, lag in [("C1", 0.7, 5), ("C2", 0.55, 10), ("C3", 0.5, 15), ("C4", 0.45, 20)]:
            rr = float(np.interp(max(0, minute - lag), minutes, rain))
            rows.append({
                "elapsed_min": int(minute),
                "object_type": "link",
                "object_id": link_id,
                "depth_m": math.nan,
                "flooding_m3s": math.nan,
                "flow_m3s": coef * (rr / 7.0) ** 1.2,
                "velocity_ms": 0.4 + 0.8 * min(1.0, rr / 8.0),
            })
    df = pd.DataFrame(rows)
    out_csv.parent.mkdir(parents=True, exist_ok=True)
    df.to_csv(out_csv, index=False)
    return df


def run_pyswmm(inp_path: Path, out_csv: Path) -> pd.DataFrame:
    """PySWMMでSWMMモデルを実行し、時系列をCSVへ保存。"""
    try:
        from pyswmm import Links, Nodes, Simulation
    except ImportError as exc:
        raise RuntimeError(
            "pyswmm が見つかりません。`pip install pyswmm` 後に再実行してください。"
        ) from exc

    if not inp_path.exists():
        raise FileNotFoundError(f"入力ファイルがありません: {inp_path}")

    rows: list[dict[str, Any]] = []
    with Simulation(str(inp_path)) as sim:
        nodes = Nodes(sim)
        links = Links(sim)
        start_time = None

        for _ in sim:
            current_time = sim.current_time
            if start_time is None:
                start_time = current_time
            elapsed_min = int((current_time - start_time).total_seconds() / 60)

            for node in nodes:
                rows.append({
                    "datetime": current_time.isoformat(),
                    "elapsed_min": elapsed_min,
                    "object_type": "node",
                    "object_id": node.nodeid,
                    "depth_m": safe_get(node, "depth"),
                    "head_m": safe_get(node, "head"),
                    "flooding_m3s": safe_get(node, "flooding", 0.0),
                    "total_inflow_m3s": safe_get(node, "total_inflow"),
                    "flow_m3s": math.nan,
                    "velocity_ms": math.nan,
                })

            for link in links:
                rows.append({
                    "datetime": current_time.isoformat(),
                    "elapsed_min": elapsed_min,
                    "object_type": "link",
                    "object_id": link.linkid,
                    "depth_m": safe_get(link, "depth"),
                    "head_m": math.nan,
                    "flooding_m3s": math.nan,
                    "total_inflow_m3s": math.nan,
                    "flow_m3s": safe_get(link, "flow"),
                    "velocity_ms": safe_get(link, "velocity"),
                })

    df = pd.DataFrame(rows)
    out_csv.parent.mkdir(parents=True, exist_ok=True)
    df.to_csv(out_csv, index=False)
    return df


def summarize_overflow(df: pd.DataFrame, dt_seconds: int = 300) -> pd.DataFrame:
    """ノード別の総越水量と最大越水流量を集計。"""
    nodes = df[df["object_type"] == "node"].copy()
    if "flooding_m3s" not in nodes:
        return pd.DataFrame()
    nodes["overflow_volume_m3"] = nodes["flooding_m3s"].fillna(0) * dt_seconds
    return (
        nodes.groupby("object_id", as_index=False)
        .agg(
            total_overflow_m3=("overflow_volume_m3", "sum"),
            max_overflow_m3s=("flooding_m3s", "max"),
            max_depth_m=("depth_m", "max"),
        )
        .sort_values("total_overflow_m3", ascending=False)
    )


def main() -> None:
    parser = argparse.ArgumentParser(description="PySWMM内水氾濫デモを実行します。")
    parser.add_argument("--inp", default="../data/demo_inland_flood.inp", help="SWMM入力ファイル")
    parser.add_argument("--out", default="../outputs/pyswmm_timeseries.csv", help="出力CSV")
    parser.add_argument("--synthetic", action="store_true", help="PySWMMなしで確認用の疑似結果を作成")
    args = parser.parse_args()

    base = Path(__file__).resolve().parent
    inp_path = (base / args.inp).resolve()
    out_csv = (base / args.out).resolve()

    if args.synthetic:
        df = create_synthetic_results(out_csv)
    else:
        try:
            df = run_pyswmm(inp_path, out_csv)
        except RuntimeError as e:
            print(e)
            print("確認用の疑似結果を作成します。")
            df = create_synthetic_results(out_csv)

    summary = summarize_overflow(df)
    summary_csv = out_csv.with_name("overflow_summary.csv")
    summary.to_csv(summary_csv, index=False)

    print(f"時系列CSV: {out_csv}")
    print(f"越水集計CSV: {summary_csv}")
    print(summary.to_string(index=False))


if __name__ == "__main__":
    main()