#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""temp_band.py — 市场温度分档模块（2026-08-13）

结论（数据验证）：三态骨架 + 温度(rsi)连续维度。
- 三态（trend_up/choppy/trend_down）= market_regime.py 已有（策略类型分类）
- 温度（rsi 分档）= 本模块（力度维度，仓位乘数）

数据依据（2026-08-13 分市场状态检验）：
  v_weak choppy: 恐慌<45 -> 71%胜率 / 中性45-60 -> 46% / 亢奋>60 -> 37%
  v_oversold trend_down: 恐慌<35 -> 64% / 偏弱35-50 -> 53% / 中性>50 -> 0%
  s2_panic trend_down 恐慌<35: 86%胜率 +16.6%

档位：panic(<35) / fear(35-45) / neutral(45-60) / greed(60-70) / euphoria(>70)
用法：
  from temp_band import get_market_temp, temp_multiplier
  t = get_market_temp()      # {rsi, band, regime}
  mult = temp_multiplier(t["band"], strategy_family="mr")
"""
import sqlite3
from pathlib import Path

from market_config import MARKETS

DB = Path("/home/hmo/MoFin/data/mofin.db")
INDEX = "sh000001"  # A股默认指数（兜底）；实际以 MARKETS[market]['index_code'] 为准


def calc_rsi(series, n=14):
    result = [None] * len(series)
    if len(series) < n + 1:
        return result
    gains, losses = [], []
    for i in range(1, len(series)):
        ch = series[i] - series[i - 1]
        gains.append(max(ch, 0))
        losses.append(max(-ch, 0))
        if i >= n:
            avg_g = sum(gains[i - n:i]) / n
            avg_l = sum(losses[i - n:i]) / n
            rs = avg_g / avg_l if avg_l > 0 else 100
            result[i] = 100 - 100 / (1 + rs)
    return result


def temp_band(rsi):
    """连续 rsi -> 温度档位"""
    if rsi is None:
        return "unknown"
    if rsi < 35:
        return "panic"
    if rsi < 45:
        return "fear"
    if rsi < 60:
        return "neutral"
    if rsi < 70:
        return "greed"
    return "euphoria"


def temp_multiplier(band, strategy_family="mr"):
    """温度 -> 仓位乘数。mr=均值回复（恐慌重仓），trend=趋势（恐慌回避）"""
    if strategy_family == "trend":
        return {
            "panic": 0.0, "fear": 0.0, "neutral": 0.5,
            "greed": 1.0, "euphoria": 0.5, "unknown": 0.5,
        }.get(band, 0.5)
    return {
        "panic": 1.5, "fear": 1.0, "neutral": 0.8,
        "greed": 0.5, "euphoria": 0.3, "unknown": 0.5,
    }.get(band, 0.5)


def get_market_temp(market='a', db_path=None):
    """读取指定市场最新温度（rsi + 档位 + regime）。

    market: 'a'(默认, A股 sh000001) / 'hk'(港股 hkHSI)。
    指数代码从 market_config.MARKETS 读取，不写死。
    """
    db = db_path or DB
    index_code = MARKETS.get(market, MARKETS['a'])['index_code']
    conn = sqlite3.connect(str(db), timeout=5)
    try:
        # 指数最近 30 日收盘算 rsi
        rows = conn.execute(
            "SELECT date, close FROM stock_daily WHERE code=? ORDER BY date DESC LIMIT 30",
            (index_code,)
        ).fetchall()
        # 最新 regime（按市场过滤——否则 A 股温度会误读港股 regime）
        reg = conn.execute(
            "SELECT date, regime FROM market_regime WHERE market=? ORDER BY date DESC LIMIT 1",
            (market,)
        ).fetchone()
    finally:
        conn.close()
    if not rows or len(rows) < 15:
        return {"rsi": None, "band": "unknown", "regime": "unknown", "date": ""}
    rows = list(reversed(rows))
    closes = [r[1] for r in rows]
    dates = [r[0] for r in rows]
    rsi_series = calc_rsi(closes)
    rsi_now = rsi_series[-1] if rsi_series else None
    band = temp_band(rsi_now)
    regime = reg[1] if reg else "unknown"
    reg_date = reg[0] if reg else ""
    return {
        "rsi": round(rsi_now, 1) if rsi_now is not None else None,
        "band": band,
        "regime": regime,
        "date": dates[-1],
        "regime_date": reg_date,
    }


if __name__ == "__main__":
    t = get_market_temp()
    print(f"温度: rsi={t['rsi']} band={t['band']} regime={t['regime']} ({t['date']})")
    print(f"  mr 乘数: {temp_multiplier(t['band'], 'mr')}")
    print(f"  trend 乘数: {temp_multiplier(t['band'], 'trend')}")