feat: 温区平滑+周期记录——滞回确认K=5(数据选参:112周期/20.7天/无1天噪音), regime_cycles表, router v3读平滑温区(当前trend_down→v_oversold/s2_panic主导0.8,v_weak观察0.24,避免被2天choppy误判)

2026-08-13 09:43:38 +08:00
parent 06fbdf5961
commit a62b05f11d
3 changed files with 211 additions and 3 deletions
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+#!/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()