From ad73d9a4ed858dfe18626a803480f9bd759a5065 Mon Sep 17 00:00:00 2001
From: Ubuntu <ubuntu@niyon.lxd>
Date: Wed, 13 Aug 2025 09:05:05 +0800
Subject: [PATCH] revert to HEAD^^

---
 freqtrade/templates/freqaiprimer.py | 51 +++++++----------------------
 1 file changed, 11 insertions(+), 40 deletions(-)

diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py
index 549b3f47..a7875442 100644
--- a/freqtrade/templates/freqaiprimer.py
+++ b/freqtrade/templates/freqaiprimer.py
@@ -406,18 +406,12 @@ class FreqaiPrimer(IStrategy):
         trend_score = self.get_market_trend(dataframe=dataframe, metadata=metadata)
 
         # 动态调整成交量和 RSI 阈值
-        # 使用 Hyperopt 参数动态调整成交量 Z 分数阈值
-        volume_z_score_min = self.buy_params['volume_z_score_min']
-        volume_z_score_max = self.buy_params['volume_z_score_max']
+        volume_z_score_min = 0.5
+        volume_z_score_max = 1.5
         volume_z_score_threshold = self.linear_map(trend_score, 0, 100, volume_z_score_max, volume_z_score_min)
-        logger.info(f"[{pair}] 动态调整成交量 Z 分数阈值：{volume_z_score_threshold:.2f} (趋势得分: {trend_score})")
-
-        # 使用 Hyperopt 参数动态调整 RSI 阈值
-        rsi_min = self.buy_params['rsi_min']
-        rsi_max = self.buy_params['rsi_max']
+        rsi_min = 35
+        rsi_max = 55
         rsi_threshold = self.linear_map(trend_score, 0, 100, rsi_max, rsi_min)
-        logger.info(f"[{pair}] 动态调整 RSI 阈值：{rsi_threshold:.2f} (趋势得分: {trend_score})")
-        logger.info(f"[{pair}] 动态调整 RSI 阈值：{rsi_threshold:.2f} (趋势得分: {trend_score})")
         stochrsi_min = 25
         stochrsi_max = 45
         stochrsi_threshold = self.linear_map(trend_score, 0, 100, stochrsi_max, stochrsi_min)
@@ -569,17 +563,9 @@ class FreqaiPrimer(IStrategy):
 
             # 综合卖出条件：根据 trend_score 调整逻辑
             #如果趋势得分为100，拒绝退出
-
-            # 当趋势得分为 100 时，完全禁止出场
-            trend_top_threshold = 100
-            if trend_score >= trend_top_threshold:
-                logger.info(f"[{pair}] 趋势得分为 {trend_score}，完全禁止出场")
+            if trend_score > 92:
+                logger.info(f"[{pair}] 趋势得分为100，拒绝退出")
                 return dataframe
-
-            # 动态调整 sell_threshold，趋势越强，阈值越高
-            sell_threshold_multiplier = self.linear_map(trend_score, 0, 100, 1.0, 1.5)
-            self.sell_threshold *= sell_threshold_multiplier
-            logger.info(f"[{pair}] 动态调整卖出阈值：{self.sell_threshold:.4f} (趋势得分: {trend_score})")
             
             trend_sell_threshold = 85
             if trend_score > trend_sell_threshold:
@@ -615,26 +601,11 @@ class FreqaiPrimer(IStrategy):
 
     def buy_space(self):
         return [
-            # Buy thresholds
-            DecimalParameter(-0.1, -0.01, name="buy_threshold_min", default=-0.035, decimals=3),
-            DecimalParameter(-0.02, -0.001, name="buy_threshold_max", default=-0.001, decimals=3),
-
-            # Add position threshold
-            DecimalParameter(-0.05, -0.01, name="add_position_threshold", default=-0.021, decimals=3),
-
-            # Cooldown period (in minutes)
-            IntParameter(1, 10, name="cooldown_period_minutes", default=9),
-
-            # Maximum entry position adjustments
-            IntParameter(1, 3, name="max_entry_position_adjustment", default=3),
-
-            # Volume Z-score thresholds
-            DecimalParameter(0.3, 0.6, name="volume_z_score_min", default=0.5, decimals=2),
-            DecimalParameter(1.0, 1.8, name="volume_z_score_max", default=1.5, decimals=2),
-
-            # RSI thresholds
-            IntParameter(30, 40, name="rsi_min", default=35),
-            IntParameter(50, 70, name="rsi_max", default=55)
+            DecimalParameter(-0.1, -0.01, name="buy_threshold_min"),
+            DecimalParameter(-0.02, -0.001, name="buy_threshold_max"),
+            DecimalParameter(-0.05, -0.01, name="add_position_threshold", default=-0.02),
+            IntParameter(1, 10, name="cooldown_period_minutes", default=5),
+            IntParameter(1, 3, name="max_entry_position_adjustment", default=2)
         ]
 
     def sell_space(self):