添加klu的3种形态识别

web/app.py

@@ -352,39 +352,8 @@ def analyze_chan(df, symbol=None, timeframe=None):
     
     # 初始化多时间周期数据以获取EMA52
     ema52_dict = None
-    # 先暂时不用这个功能，太慢了
-    if symbol and timeframe and False:
-        try:
-            # 获取不同时间周期的数据用于初始化
-            df_1h = get_kl_data(symbol, '1h', limit=1500) if timeframe != '1h' else df
-            df_1d = get_kl_data(symbol, '1d', limit=2000) if timeframe != '1d' else df
-            df_1M = get_kl_data(symbol, '1M', limit=1500) if timeframe != '1M' else df
-            
-            # 添加指标
-            if df_1h is not None and len(df_1h) > 0:
-                df_1h = add_indicators(df_1h)
-            if df_1d is not None and len(df_1d) > 0:
-                df_1d = add_indicators(df_1d)
-            if df_1M is not None and len(df_1M) > 0:
-                df_1M = add_indicators(df_1M)
-            
-            # 初始化多时间周期数据
-            chan.init_dataframes(df, df_1h, df_1d, df_1M)
-            
-            # 获取EMA52数据
-            ema52_dict = chan.get_ema52_dict()
-            # 处理NaN值
-            if ema52_dict:
-                for key, value in ema52_dict.items():
-                    if pd.isna(value) or value is None:
-                        ema52_dict[key] = None
-                    else:
-                        ema52_dict[key] = float(value)
-        except Exception as e:
-            print(f"获取多时间周期EMA52数据失败: {e}")
-            ema52_dict = None
-    
     # 获取分析结果
+    klu_list = chan.get_kl_data(df)
     klc_list = chan.get_klc_list(df)
     bi_list = chan.cal_bi_list(klc_list)
     #for index in range(0, 10):
@@ -408,8 +377,6 @@ def analyze_chan(df, symbol=None, timeframe=None):
     chan_macd = None
     chan_macd_data = {}
     try:
-        # 直接使用ChanLun的get_klu_list方法获取KLU列表
-        klu_list = chan.get_klu_list(df)
         
         if klu_list and len(klu_list) > 0:
             print(f"获取到KLU列表，长度: {len(klu_list)}")
@@ -457,20 +424,6 @@ def analyze_chan(df, symbol=None, timeframe=None):
             'cross0_down_list': []
         }
     
-    # 获取原始K线数据用于KLU分型分析
-    klu_list = []
-    try:
-        # 尝试获取KLU数据
-        if hasattr(chan, 'get_klu_list'):
-            klu_list = chan.get_klu_list(df)
-        elif hasattr(chan, 'klu_list'):
-            klu_list = chan.klu_list
-        else:
-            # 如果没有专门的KLU方法，尝试从KLC获取原始K线数据
-            pass
-    except Exception as e:
-        klu_list = []
-    
     # 提取K线分型信息
     klc_fx_info = []
     for klc in klc_list: