From f2f577c07f390a220c5fcba0cd145d0ef9fd8eac Mon Sep 17 00:00:00 2001
From: aszerW <aszer27937@gmail.com>
Date: Sun, 19 Oct 2025 21:52:08 +0800
Subject: [PATCH] =?UTF-8?q?=E8=B6=8B=E5=8A=BF=E7=AD=96=E7=95=A5?=
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---
 .../strategies/SimpleRSIStrategy_Fixed.py     | 86 +++++++++++--------
 1 file changed, 51 insertions(+), 35 deletions(-)

diff --git a/user_data/strategies/SimpleRSIStrategy_Fixed.py b/user_data/strategies/SimpleRSIStrategy_Fixed.py
index 8d1e5d3..3fe0075 100644
--- a/user_data/strategies/SimpleRSIStrategy_Fixed.py
+++ b/user_data/strategies/SimpleRSIStrategy_Fixed.py
@@ -44,7 +44,7 @@ class SimpleRSIStrategyFixed(IStrategy):
         "0": 100
     }
 
-    timeframe = '1d'
+    timeframe = '1h'
 
     # 策略参数
     rsi_period_short = 6
@@ -61,44 +61,60 @@ class SimpleRSIStrategyFixed(IStrategy):
         """
         添加技术指标到数据框
         """
-        try:
-            # RSI 指标 (6, 12) 及位移
-            dataframe['rsi_6'] = ta.RSI(dataframe['close'], timeperiod=6)
-            dataframe['rsi_12'] = ta.RSI(dataframe['close'], timeperiod=12)
-            for i in range(1, 6):
-                dataframe[f'rsi_6_shift{i}'] = dataframe['rsi_6'].shift(i)
-                dataframe[f'rsi_12_shift{i}'] = dataframe['rsi_12'].shift(i)
+        df = dataframe.copy()  
+          
+        # 将date设置为索引用于resample  
+        df['date'] = df['date'].dt.tz_convert('Asia/Shanghai') 
+        df = df.set_index('date')  
+        df_resample = df.resample('24h', label='right').agg({  
+            'open': 'first',  
+            'high': 'max',  
+            'low': 'min',  
+            'close': 'last',  
+            'volume': 'sum'  
+        })  
 
-            # EMA 指标 (10, 20, 30) 及位移
-            dataframe['ema_10'] = ta.EMA(dataframe['close'], timeperiod=10)
-            dataframe['ema_20'] = ta.EMA(dataframe['close'], timeperiod=20)
-            dataframe['ema_30'] = ta.EMA(dataframe['close'], timeperiod=30)
-            for i in range(1, 6):
-                dataframe[f'ema_10_shift{i}'] = dataframe['ema_10'].shift(i)
-                dataframe[f'ema_20_shift{i}'] = dataframe['ema_20'].shift(i)
-                dataframe[f'ema_30_shift{i}'] = dataframe['ema_30'].shift(i)
+        # RSI 指标 (6, 12) 及位移
+        df_resample['rsi_6'] = ta.RSI(df_resample['close'], timeperiod=6)
+        df_resample['rsi_12'] = ta.RSI(df_resample['close'], timeperiod=12)
+        for i in range(1, 6):
+            df_resample[f'rsi_6_shift{i}'] = df_resample['rsi_6'].shift(i)
+            df_resample[f'rsi_12_shift{i}'] = df_resample['rsi_12'].shift(i)
 
-            # 方便条件判断的差值与比率（带除零保护）
-            dataframe['ema_10_20_diff'] = dataframe['ema_10'] - dataframe['ema_20']
-            dataframe['ema_10_20_ratio'] = np.where(
-                dataframe['ema_20'] != 0,
-                dataframe['ema_10_20_diff'] / dataframe['ema_20'],
-                0
+        # EMA 指标 (10, 20, 30) 及位移
+        df_resample['ema_10'] = ta.EMA(df_resample['close'], timeperiod=10)
+        df_resample['ema_20'] = ta.EMA(df_resample['close'], timeperiod=20)
+        df_resample['ema_30'] = ta.EMA(df_resample['close'], timeperiod=30)
+        for i in range(1, 6):
+            df_resample[f'ema_10_shift{i}'] = df_resample['ema_10'].shift(i)
+            df_resample[f'ema_20_shift{i}'] = df_resample['ema_20'].shift(i)
+            df_resample[f'ema_30_shift{i}'] = df_resample['ema_30'].shift(i)
+
+        # 方便条件判断的差值与比率（带除零保护）
+        df_resample['ema_10_20_diff'] = df_resample['ema_10'] - df_resample['ema_20']
+        df_resample['ema_10_20_ratio'] = np.where(
+            df_resample['ema_20'] != 0,
+            df_resample['ema_10_20_diff'] / df_resample['ema_20'],
+            0
+        )
+        for i in range(1, 6):
+            df_resample[f'ema_10_20_diff_shift{i}'] = df_resample['ema_10_20_diff'].shift(i)
+            df_resample[f'ema_10_20_ratio_shift{i}'] = np.where(
+            df_resample[f'ema_20_shift{i}'] != 0,
+            df_resample[f'ema_10_20_diff_shift{i}'] / df_resample[f'ema_20_shift{i}'],
+            0
             )
-            for i in range(1, 6):
-                dataframe[f'ema_10_20_diff_shift{i}'] = dataframe['ema_10_20_diff'].shift(i)
-                dataframe[f'ema_10_20_ratio_shift{i}'] = np.where(
-                    dataframe[f'ema_20_shift{i}'] != 0,
-                    dataframe[f'ema_10_20_diff_shift{i}'] / dataframe[f'ema_20_shift{i}'],
-                    0
-                )
-            dataframe.to_csv("rsi_eth2.csv", index=False, encoding='utf-8-sig')
-            logger.debug(f"Indicators populated successfully for {metadata.get('pair', 'unknown')}")
-            return dataframe
+        
+        df_resample = df_resample.drop(columns=['open', 'high', 'low', 'close', 'volume'])  
+        df_resample.index = df_resample.index.tz_convert('UTC')
+        dataframe = dataframe.join(df_resample,   
+                                   on='date',   
+                                   how='left').ffill()  
+        dataframe.to_csv("rsi_eth2.csv", index=False, encoding='utf-8-sig')
+        logger.debug(f"Indicators populated successfully for {metadata.get('pair', 'unknown')}")
+        return dataframe
+
 
-        except Exception as e:
-            logger.error(f"Error populating indicators: {e}")
-            return dataframe
 
     def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: Dict) -> pd.DataFrame:
         """