从metadata.json里读取labels_mean和labels_std

freqtrade/templates/freqaiprimer.py

@@ -51,7 +51,7 @@ class FreqaiPrimer(IStrategy):
     }
 
     freqai_info = {
-        "identifier": "divergence_model",  # 注意：实际目录是 test58，可能需要调整
+        "identifier": "test58",  # 与实际目录名一致，修正为 test58
         "model": "LightGBMRegressor",
         "feature_parameters": {
             "include_timeframes": ["3m", "15m", "1h"],
@@ -173,12 +173,7 @@ class FreqaiPrimer(IStrategy):
 
         # 从最新的子目录读取 metadata.json
         try:
-            # 优先使用实际目录名 test58（硬编码，临时解决方案）
-            # model_base_dir = "/freqtrade/user_data/models/test58"
-            
-            # 如果需要动态获取（推荐），取消注释以下代码：
             model_base_dir = os.path.join(self.config["user_data_dir"], "models", self.freqai_info["identifier"])
-            
             pair_clean = pair.replace('/', '_')  # 将 "KAITO/USDT" 转换为 "KAITO_USDT"
             sub_dirs = glob.glob(os.path.join(model_base_dir, f"sub-train-{pair_clean}_*"))
 
@@ -244,6 +239,92 @@ class FreqaiPrimer(IStrategy):
         logger.info(f"[{pair}] 动态卖出阈值：{self.sell_threshold:.4f}")
 
         if not self.stats_logged:
-            logger.info("===== 所有币对的 labels_mean 和 labels_std 汇总...
+            logger.info("===== 所有币对的 labels_mean 和 labels_std 汇总 =====")
+            for p, stats in self.pair_stats.items():
+                logger.info(f"[{p}] labels_mean：{stats['labels_mean']:.4f}, labels_std：{stats['labels_std']:.4f}")
+            logger.info("==============================================")
+            self.stats_logged = True
 
-出错了，请刷新以重新连接或重试。
+        logger.info(f"[{metadata['pair']}] 指标计算完成，列：{list(dataframe.columns)}")
+        return dataframe
+
+    def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
+        conditions = []
+
+        if "&-price_value_divergence" in df.columns:
+            buy_condition = (df["&-price_value_divergence"] < self.buy_threshold)
+            buy_condition &= (df["volume_z_score"] > 1.5)
+            buy_condition &= (df["rsi"] < 40)
+            buy_condition &= (df["close"] <= df["bb_lowerband"])
+            conditions.append(buy_condition)
+        else:
+            logger.warning("⚠️ &-price_value_divergence 列缺失，跳过该条件")
+
+        if len(conditions) > 0:
+            df.loc[reduce(lambda x, y: x & y, conditions), 'enter_long'] = 1
+            logger.info(f"[{metadata['pair']}] 入场信号触发，条件满足")
+
+        return df
+
+    def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
+        conditions = []
+
+        if "&-price_value_divergence" in df.columns:
+            sell_condition = (df["&-price_value_divergence"] > self.sell_threshold)
+            sell_condition |= (df["rsi"] > 75)
+            conditions.append(sell_condition)
+        else:
+            logger.warning("⚠️ &-price_value_divergence 列缺失，跳过该条件")
+
+        if len(conditions) > 0:
+            df.loc[reduce(lambda x, y: x & y, conditions), 'exit_long'] = 1
+            logger.info(f"[{metadata['pair']}] 出场信号触发，条件满足")
+
+        return df
+
+    def adjust_trade_position(self, trade: Trade, current_time: datetime,
+                            current_rate: float, current_profit: float,
+                            min_roi: Dict[float, float], max_profit: float):
+        hold_time = (current_time - trade.open_date_utc).total_seconds() / 60
+
+        if hold_time < 15:
+            logger.info(f"[{trade.pair}] 持仓时间 {hold_time:.1f} 分钟，未达到最小持仓时间 15 分钟，暂不退出")
+            return None
+
+        profit_ratio = (current_rate - trade.open_rate) / trade.open_rate
+        if profit_ratio >= self.trailing_stop_start and not self.trailing_stop_enabled:
+            self.trailing_stop_enabled = True
+            trade.adjust_max_rate(current_rate)
+            logger.info(f"[{trade.pair}] 价格上涨超过 {self.trailing_stop_start*100:.1f}%，启动 Trailing Stop")
+
+        if self.trailing_stop_enabled:
+            max_rate = trade.max_rate
+            trailing_stop_price = max_rate * (1 - self.trailing_stop_distance)
+            if current_rate < trailing_stop_price:
+                logger.info(f"[{trade.pair}] 价格回落至 Trailing Stop 点 {trailing_stop_price:.6f}，触发卖出")
+                return -1
+            trade.adjust_max_rate(current_rate)
+
+        if hold_time > 30:
+            logger.info(f"[{trade.pair}] 持仓时间超过30分钟，强制平仓")
+            return -1
+        return None
+
+    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
+                           time_in_force: str, current_time: datetime, **kwargs) -> bool:
+        recent_trades = Trade.get_trades(
+            pair=pair,
+            is_open=False,
+            close_date=current_time - datetime.timedelta(minutes=5)
+        ).all()
+        if len(recent_trades) > 0:
+            logger.info(f"[{pair}] 5分钟内有近期交易，跳过本次入场")
+            return False
+        self.trailing_stop_enabled = False
+        return True
+
+    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
+                          rate: float, time_in_force: str, exit_reason: str,
+                          current_time: datetime, **kwargs) -> bool:
+        logger.info(f"[{pair}] 退出交易，原因：{exit_reason}, 利润：{trade.calc_profit_ratio(rate):.2%}")
+        return True