1、准备更新order单前备份

src/strategies/OpenTwoFactorStrategy.py

@@ -141,7 +141,6 @@ class SimpleLimitBuyStrategyLong(Strategy):
                 pnl_per_unit = open - avg_entry_price  # 当前浮动盈亏（以收盘价计算）
 
                 stop_position_points = range_1_ago * self.profit_factor
-                stop_position_points = 20
 
                 self.log(
                     f"[{current_datetime}] PnL per unit: {pnl_per_unit:.2f}, 目标: {stop_position_points:.2f}"
@@ -656,7 +655,7 @@ class SimpleLimitBuyStrategy(Strategy):
                 pnl_per_unit = open - avg_entry_price  # 当前浮动盈亏（以收盘价计算）
 
                 self.log(
-                    f"[{current_datetime}] 止盈信号 - PnL per unit: {pnl_per_unit:.2f}, 目标: {self.take_profit_points:.2f}, 止损: {-self.stop_loss_points:.2f}"
+                    f"[{current_datetime}] 止盈信号 - PnL per unit: {pnl_per_unit:.2f}, 目标: {range_1_ago * self.profit_factor_l:.2f}, 止损: {-self.stop_loss_points:.2f}"
                 )
 
                 # 止盈条件
@@ -712,7 +711,7 @@ class SimpleLimitBuyStrategy(Strategy):
                 pnl_per_unit = avg_entry_price - open  # 当前浮动盈亏（以收盘价计算）
 
                 self.log(
-                    f"[{current_datetime}] 止盈信号 - PnL per unit: {pnl_per_unit:.2f}, 目标: {self.take_profit_points:.2f}, 止损: {-self.stop_loss_points:.2f}"
+                    f"[{current_datetime}] 止盈信号 - PnL per unit: {pnl_per_unit:.2f}, 目标: {range_1_ago * self.profit_factor_l:.2f}, 止损: {-self.stop_loss_points:.2f}"
                 )
 
                 # 止盈条件

src/strategies/base_strategy.py

@@ -5,6 +5,8 @@ from datetime import datetime
 import math
 from typing import Dict, Any, Optional, List, TYPE_CHECKING
 
+import numpy as np
+
 # 使用 TYPE_CHECKING 避免循环导入，但保留类型提示
 from ..backtest_context import BacktestContext  # 转发引用 BacktestEngine
 from ..core_data import Bar, Order, Trade  # 导入必要的类型
@@ -201,3 +203,12 @@ class Strategy(ABC):
 
     def get_price_history(self, key: str):
         return self.context.get_price_history(key)
+
+    def get_indicator_tuple(self):
+        close = np.array(self.get_price_history("close"))
+        open = np.array(self.get_price_history("open"))
+        high = np.array(self.get_price_history("high"))
+        low = np.array(self.get_price_history("low"))
+        volume = np.array(self.get_price_history("volume"))
+
+        return (close, open, high, low, volume)