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main.py

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+import importlib
+import pandas as pd
+from utils import initialize, shutdown, get_rates, close_all, send_order
+from backtest import BacktestEngine
+from logger import logger
+from config import INITIAL_CAPITAL, STRATEGIES, BUY_THRESHOLD, SELL_THRESHOLD
+
+# 导入优化器
+from optimizer import run_optimizer
+
+def run_realtime():
+    if not initialize():
+        logger.error("MT5初始化失败")
+        return
+
+    signals = []
+    weights = []
+    for strat, weight in STRATEGIES:
+        try:
+            logger.info(f"执行策略：{strat.__class__.__module__}")
+            signal = strat.generate_signal()
+            signals.append(signal)
+            weights.append(weight)
+        except Exception as e:
+            logger.exception(f"运行策略 {strat.__class__.__module__} 时出错：{e}")
+
+    weighted_signal_sum = sum(s * w for s, w in zip(signals, weights))
+
+    if weighted_signal_sum >= BUY_THRESHOLD:
+        logger.info(f"加权信号总和 ({weighted_signal_sum:.2f}) 达到买入阈值 ({BUY_THRESHOLD})，发送买入信号")
+        close_all("XAUUSD")
+        send_order("XAUUSD", 'buy')
+    elif weighted_signal_sum <= SELL_THRESHOLD:
+        logger.info(f"加权信号总和 ({weighted_signal_sum:.2f}) 达到卖出阈值 ({SELL_THRESHOLD})，发送卖出信号")
+        close_all("XAUUSD")
+        send_order("XAUUSD", 'sell')
+    else:
+        logger.info(f"加权信号总和 ({weighted_signal_sum:.2f}) 未达到交易阈值，无操作")
+
+    shutdown()
+
+def run_backtest():
+    if not initialize():
+        logger.error("MT5初始化失败")
+        return
+
+    symbol = "XAUUSD"
+    timeframe = 1  # M1
+    count = 50000
+    rates = get_rates(symbol, timeframe, count)
+    shutdown()
+
+    if rates is None:
+        logger.error("获取历史数据失败")
+        return
+
+    logger.info(f"初始资金: {INITIAL_CAPITAL}")
+
+    df = pd.DataFrame(rates)
+    engine = BacktestEngine(df)
+    signals_list = []
+    weights = []
+
+    for strat, weight in STRATEGIES:
+        try:
+            logger.info(f"回测策略：{strat.__class__.__module__}")
+            signals = engine.run_strategy(strat)
+            signals_list.append(signals)
+            weights.append(weight)
+        except Exception as e:
+            logger.exception(f"回测策略 {strat.__class__.__module__} 时出错：{e}")
+
+    combined_signal = engine.combine_signals(signals_list, weights, BUY_THRESHOLD, SELL_THRESHOLD)
+    cum_ret = engine.calc_returns(combined_signal)
+    final_capital = INITIAL_CAPITAL * (1 + cum_ret.iloc[-1])
+    logger.info("策略组合回测完成")
+    logger.info(f"最终资金: {final_capital:.2f}")
+    logger.info(cum_ret.tail())
+
+
+if __name__ == "__main__":
+    # --- 选择运行模式 ---
+    # 1. 运行一次回测 (使用config.py中的默认权重)
+    # run_backtest()
+
+    # 2. 运行实盘交易 (使用config.py中的默认权重)
+    # run_realtime()
+
+    # 3. 运行遗传算法优化，寻找最佳权重
+    run_optimizer()