factor.py 文件源码

def KDJ(security_list, fastk_period=5, slowk_period=3, fastd_period=3):
    def SMA_CN(close, timeperiod):
        close = np.nan_to_num(close)
        return reduce(lambda x, y: ((timeperiod - 1) * x + y) / timeperiod, close)

    # ????????????
    if isinstance(security_list, str):
        security_list = [security_list]
    # ?? KDJ
    n = max(fastk_period, slowk_period, fastd_period)
    k = {}
    d = {}
    j = {}
    for stock in security_list:

        security_data = attribute_history(
            stock, n * 2, '1d', fields=['high', 'low', 'close'], df=False)
        high = security_data['high']
        low = security_data['low']
        close = security_data['close']
        kValue, dValue = talib.STOCHF(
            high, low, close, fastk_period, fastd_period, fastd_matype=0)
        kValue = np.array(map(lambda x: SMA_CN(
            kValue[:x], slowk_period), range(1, len(kValue) + 1)))
        dValue = np.array(map(lambda x: SMA_CN(
            kValue[:x], fastd_period), range(1, len(kValue) + 1)))
        jValue = 3 * kValue - 2 * dValue

        def func(arr): return np.array(
            [0 if x < 0 else (100 if x > 100 else x) for x in arr])

        k[stock] = func(kValue)
        d[stock] = func(dValue)
        j[stock] = func(jValue)
    return k, d, j

# RSI