#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""regime_tracker.py — 温区平滑跟踪 + 周期记录（2026-08-13）

设计（老莫确认方向 + 数据选参）：
- 实时温区判定：滞回确认 K=5（连续5天同温区才确认，滞后约5天，宁慢勿错）
  数据依据：K=5 → 112周期/平均20.7天/无1天噪音（vs 原始457周期/151个1天）
- 温区周期记录：regime_cycles 表（start/end/regime/days），供策略评估归因
- 温度（rsi）：不滞后，实时反映恐慌/亢奋（与温区互补：温区滞后、温度实时）

写表: regime_cycles(date_start, date_end, regime, days)
输出: market_regime_smoothed.json（当前平滑温区 + 温度）
"""
import sys
import json
import sqlite3
from pathlib import Path
from datetime import datetime

_SCRIPT_DIR = Path(__file__).resolve().parent
sys.path.insert(0, str(_SCRIPT_DIR))
sys.path.insert(0, "/home/hmo/MoFin")

DB = "/home/hmo/MoFin/data/mofin.db"
OUT = "/home/hmo/MoFin/data/market_regime_smoothed.json"

# 滞回确认天数（数据选参：K=5 甜区）
CONFIRM_DAYS = 5

def load_daily_regime():
    """读取 market_regime 逐日数据（时间正序）"""
    conn = sqlite3.connect(DB, timeout=5)
    rows = conn.execute(
        "SELECT date, above_ma20, adx, regime FROM market_regime ORDER BY date ASC"
    ).fetchall()
    conn.close()
    return rows

def classify_day(above, adx):
    """单日温区（与 market_regime 同逻辑）"""
    if above == 1 and adx is not None and adx >= 20:
        return "trend_up"
    if adx is not None and adx < 20:
        return "choppy"
    return "trend_down"

def smooth_states(rows, k=CONFIRM_DAYS):
    """滞回确认：连续 K 天同温区才确认切换。返回 (states, cycles)"""
    dates = [r[0] for r in rows]
    raw = [classify_day(r[1], r[2]) for r in rows]
    n = len(dates)

    # 状态机：current 确认态；每 K 天窗口看是否一致
    states = [None] * n
    current = None
    for i in range(n):
        if i < k - 1:
            continue
        window = raw[i - k + 1:i + 1]
        if len(set(window)) == 1:
            # 连续 K 天同温区 → 确认（切换）
            current = window[0]
        states[i] = current if current is not None else raw[i]
    # 开头填补（前 K-1 天用原始值）
    for i in range(min(k - 1, n)):
        states[i] = raw[i]

    # 聚合周期
    cycles = []
    cur = None
    for i in range(n):
        s = states[i]
        if cur is None or s != cur["regime"]:
            if cur:
                cycles.append(cur)
            cur = {"regime": s, "start": dates[i], "end": dates[i], "days": 1}
        else:
            cur["end"] = dates[i]
            cur["days"] += 1
    if cur:
        cycles.append(cur)
    return states, cycles, dates

def save_cycles(cycles):
    """写入 regime_cycles 表"""
    conn = sqlite3.connect(DB, timeout=30)
    conn.execute("PRAGMA busy_timeout=30000")
    conn.execute("""
        CREATE TABLE IF NOT EXISTS regime_cycles (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            regime TEXT,
            start_date TEXT,
            end_date TEXT,
            days INTEGER,
            created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
        )
    """)
    # 清空重建（保持与 market_regime 同步）
    conn.execute("DELETE FROM regime_cycles")
    for cy in cycles:
        conn.execute(
            "INSERT INTO regime_cycles (regime, start_date, end_date, days) VALUES (?,?,?,?)",
            (cy["regime"], cy["start"], cy["end"], cy["days"])
        )
    conn.commit()
    conn.close()
    return len(cycles)

def get_temp():
    """实时温度（rsi 档位，不滞后）"""
    try:
        from temp_band import get_market_temp
        return get_market_temp()
    except Exception:
        return {"band": "unknown", "rsi": None}

def main():
    rows = load_daily_regime()
    if len(rows) < CONFIRM_DAYS + 1:
        print(f"数据不足: {len(rows)} 条")
        return

    states, cycles, dates = smooth_states(rows)
    n_cycles = save_cycles(cycles)

    # 当前平滑温区（最新确认态）
    current_regime = states[-1]
    current_date = dates[-1]
    temp = get_temp()

    # 最近周期列表
    recent = cycles[-8:]
    out = {
        "current_regime": current_regime,
        "current_date": current_date,
        "confirm_days": CONFIRM_DAYS,
        "temp": temp,
        "total_cycles": n_cycles,
        "recent_cycles": recent,
        "updated_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
    }
    Path(OUT).write_text(json.dumps(out, ensure_ascii=False, indent=1), encoding="utf-8")

    print(f"平滑温区: {current_regime} (确认期{CONFIRM_DAYS}天, 至{current_date})")
    print(f"温度: {temp.get('band')} (rsi={temp.get('rsi')})")
    print(f"周期总数: {n_cycles}")
    print("最近周期:")
    for cy in recent:
        print(f"  {cy['regime']:<12} {cy['start']} ~ {cy['end']} ({cy['days']}天)")

if __name__ == "__main__":
    main()