153 lines
4.9 KiB
Python
153 lines
4.9 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""regime_tracker.py — 温区平滑跟踪 + 周期记录（2026-08-13）
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设计（老莫确认方向 + 数据选参）：
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- 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）
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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）
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- 温区周期记录：regime_cycles 表（start/end/regime/days），供策略评估归因
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- 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）
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写表: regime_cycles(date_start, date_end, regime, days)
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输出: market_regime_smoothed.json（当前平滑温区 + 温度）
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"""
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import sys
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import json
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import sqlite3
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from pathlib import Path
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from datetime import datetime
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_SCRIPT_DIR = Path(__file__).resolve().parent
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sys.path.insert(0, str(_SCRIPT_DIR))
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sys.path.insert(0, "/home/hmo/MoFin")
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DB = "/home/hmo/MoFin/data/mofin.db"
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OUT = "/home/hmo/MoFin/data/market_regime_smoothed.json"
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# 滞回确认天数（数据选参：K=5 甜区）
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CONFIRM_DAYS = 5
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def load_daily_regime():
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"""读取 market_regime 逐日数据（时间正序）"""
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conn = sqlite3.connect(DB, timeout=5)
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rows = conn.execute(
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"SELECT date, above_ma20, adx, regime FROM market_regime ORDER BY date ASC"
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).fetchall()
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conn.close()
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return rows
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def classify_day(above, adx):
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"""单日温区（与 market_regime 同逻辑）"""
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if above == 1 and adx is not None and adx >= 20:
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return "trend_up"
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if adx is not None and adx < 20:
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return "choppy"
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return "trend_down"
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def smooth_states(rows, k=CONFIRM_DAYS):
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"""滞回确认：连续 K 天同温区才确认切换。返回 (states, cycles)"""
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dates = [r[0] for r in rows]
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raw = [classify_day(r[1], r[2]) for r in rows]
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n = len(dates)
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# 状态机：current 确认态；每 K 天窗口看是否一致
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states = [None] * n
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current = None
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for i in range(n):
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if i < k - 1:
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continue
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window = raw[i - k + 1:i + 1]
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if len(set(window)) == 1:
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# 连续 K 天同温区 → 确认（切换）
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current = window[0]
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states[i] = current if current is not None else raw[i]
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# 开头填补（前 K-1 天用原始值）
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for i in range(min(k - 1, n)):
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states[i] = raw[i]
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# 聚合周期
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cycles = []
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cur = None
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for i in range(n):
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s = states[i]
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if cur is None or s != cur["regime"]:
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if cur:
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cycles.append(cur)
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cur = {"regime": s, "start": dates[i], "end": dates[i], "days": 1}
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else:
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cur["end"] = dates[i]
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cur["days"] += 1
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if cur:
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cycles.append(cur)
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return states, cycles, dates
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def save_cycles(cycles):
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"""写入 regime_cycles 表"""
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conn = sqlite3.connect(DB, timeout=30)
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conn.execute("PRAGMA busy_timeout=30000")
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conn.execute("""
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CREATE TABLE IF NOT EXISTS regime_cycles (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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regime TEXT,
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start_date TEXT,
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end_date TEXT,
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days INTEGER,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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)
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""")
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# 清空重建（保持与 market_regime 同步）
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conn.execute("DELETE FROM regime_cycles")
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for cy in cycles:
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conn.execute(
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"INSERT INTO regime_cycles (regime, start_date, end_date, days) VALUES (?,?,?,?)",
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(cy["regime"], cy["start"], cy["end"], cy["days"])
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)
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conn.commit()
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conn.close()
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return len(cycles)
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def get_temp():
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"""实时温度（rsi 档位，不滞后）"""
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try:
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from temp_band import get_market_temp
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return get_market_temp()
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except Exception:
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return {"band": "unknown", "rsi": None}
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def main():
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rows = load_daily_regime()
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if len(rows) < CONFIRM_DAYS + 1:
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print(f"数据不足: {len(rows)} 条")
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return
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states, cycles, dates = smooth_states(rows)
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n_cycles = save_cycles(cycles)
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# 当前平滑温区（最新确认态）
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current_regime = states[-1]
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current_date = dates[-1]
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temp = get_temp()
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# 最近周期列表
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recent = cycles[-8:]
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out = {
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"current_regime": current_regime,
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"current_date": current_date,
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"confirm_days": CONFIRM_DAYS,
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"temp": temp,
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"total_cycles": n_cycles,
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"recent_cycles": recent,
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"updated_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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}
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Path(OUT).write_text(json.dumps(out, ensure_ascii=False, indent=1), encoding="utf-8")
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print(f"平滑温区: {current_regime} (确认期{CONFIRM_DAYS}天, 至{current_date})")
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print(f"温度: {temp.get('band')} (rsi={temp.get('rsi')})")
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print(f"周期总数: {n_cycles}")
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print("最近周期:")
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for cy in recent:
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print(f" {cy['regime']:<12} {cy['start']} ~ {cy['end']} ({cy['days']}天)")
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if __name__ == "__main__":
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main()
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