使用 Pandas DF 计算 ADX 指标/平滑平均问题

如何解决使用 Pandas DF 计算 ADX 指标/平滑平均问题

我在 Python 中使用 Pandas DF 计算 ADX 指标时遇到问题。过去几天一直在绞尽脑汁想知道出了什么问题。我的想法可能与平滑平均值有关？结果的最后几行是：最后一行“2021-07-03”的 ADX 应该在 33 左右。

i.   date.      open.     high.     low.      close.              +DI.      -DM EMa.       -DI.         DX.          ADX.   
396 2021-06-30  35894.90  36088.87  34013.34  35036.58      ...   0.629251  -132.284380  -4.690877    1.309852   5.418229
397 2021-07-01  35048.78  35048.78  32720.03  33506.98      ...  -4.476247    57.794871   2.098175    2.764602   5.479026
398 2021-07-02  33502.26  33971.12  32698.40  33796.99      ...  -9.798669    52.972888   2.071717    1.536231   5.483165
399 2021-07-03  33831.62  34807.59  33322.38  34632.63      ...  -4.374875   -37.287497  -1.544599    0.478130   5.475540 

我的代码如下：

def adx_calc(df):

    for current in range(1,len(df.index)):
        previous = current - 1
        #True Range:
        tr = max((df.loc[current,'high'] - df.loc[current,'low']),(df.loc[current,'high'] - df.loc[previous,'close']),abs((df.loc[previous,'close'] - df.loc[current,'low'])))
        df.loc[current,'TR'] = tr
        df['ATR'] = df['TR'].ewm(span = 14).mean()
        # DM's:
        df.loc[current,'+DM'] = df.loc[current,'high']
        df.loc[current,'-DM'] = df.loc[previous,'low'] - df.loc[current,'low']
        # + DI:
        df['+DM_EMA'] = pd.DataFrame.ewm(df['+DM'],span = adx_time_period).mean()
        df.loc[current,'+DI'] = ((df.loc[current,'+DM_EMA'] / df.loc[current,'ATR']) * 100)
        # - DI:
        df['-DM_EMA'] = pd.DataFrame.ewm(df['-DM'],'-DI'] = ((df.loc[current,'-DM_EMA'] / df.loc[current,'ATR']) * 100)
        # # DX:
        df.loc[current,'DX'] = (abs((df.loc[current,'+DI'] - df.loc[current,'-DI'])) / abs((df.loc[current,'+DI'] + df.loc[current,'-DI'])))
        # # ADX:
        df['ADX'] = df['DX'].rolling(window=14).mean()```