尝试增加arbr指标

util.py

@@ -19,6 +19,45 @@ CN_CODE_TYPE = {
     }
 
 
+def calculate_brar(df: pd.DataFrame, N: int = 26) -> pd.DataFrame:
+    """
+    计算AR和BR情绪指标
+
+    参数:
+        df (pd.DataFrame): 包含 'high', 'low', 'open', 'close' 列的DataFrame
+        N (int): 计算周期，默认通常为26
+    返回:
+        pd.DataFrame: 包含原始数据及计算出的 'ar' 和 'br' 列的DataFrame
+    """
+    # 创建副本，避免修改原始数据
+    data = df.copy()
+
+    # --- 计算 AR (人气指标) ---
+    # 公式: AR = (N日内 (最高价 - 开盘价) 之和) / (N日内 (开盘价 - 最低价) 之和) * 100
+    high_open = data['high'] - data['open']
+    open_low = data['open'] - data['low']
+
+    data['ar'] = (high_open.rolling(window=N, min_periods=1).sum() /
+                  open_low.rolling(window=N, min_periods=1).sum()) * 100
+
+    # --- 计算 BR (意愿指标) ---
+    # 公式: BR = (N日内 MAX(0, 最高价 - 前一日收盘价) 之和) /
+    #           (N日内 MAX(0, 前一日收盘价 - 最低价) 之和) * 100
+    prev_close = data['close'].shift(1)
+
+    # 计算多头意愿：当日最高价 - 前一日收盘价，若小于0则记为0
+    high_prev_close = data['high'] - prev_close
+    high_prev_close = high_prev_close.where(high_prev_close > 0, 0)
+
+    # 计算空头意愿：前一日收盘价 - 当日最低价，若小于0则记为0
+    prev_close_low = prev_close - data['low']
+    prev_close_low = prev_close_low.where(prev_close_low > 0, 0)
+
+    data['br'] = (high_prev_close.rolling(window=N, min_periods=1).sum() /
+                  prev_close_low.rolling(window=N, min_periods=1).sum()) * 100
+
+    return data
+
 
 def get_history_k(code, start_date='19700101', end_date=None):
 
@@ -36,8 +75,7 @@ def get_history_k(code, start_date='19700101', end_date=None):
         url = "https://api.zhituapi.com/hs/history/%s/d/f?token=6E0E86BC-15AD-4275-8A95-B02D168D63C1&st=%s"%(stock_code, start_date)
 
         if end_date is not None:
-            url += "&end_date=%s"%(end_date)
-
+            url += "&et=%s"%(end_date)
         response = requests.get(url)
 
         data = response.json()