temp.py 文件源码

def add_MACD(data, Ns=[12,26,9]):
    '''
    :param data: DataFrame containing stock price info in the second column
    :param Ns: List of short term long term EMA to use and look-back window of MACD's EMA
    :return:
    '''
    symbol = data.columns.values[1]  # assuming stock price is in the second column in data
    MACD = cal_EMA(data.ix[:,[symbol]],N=Ns[0]) - cal_EMA(data.ix[:,[symbol]],N=Ns[1])
    data['MACD'] = MACD
    signal = cal_EMA(data.MACD[Ns[1]:],N=Ns[2])
    # # normalized them
    # MACD = (MACD - np.nanmean(MACD))/(2*np.nanstd(MACD))
    # signal  = (signal - np.nanmean(signal))/(2*np.nanstd(signal))
    data['MACD'] = MACD
    data['Signal'] = 'NaN'
    data.loc[Ns[1]:,'Signal'] = signal

    return data