Python talib.MINUS_DI Examples

def results(self, data_frame):
        try:
            adx = talib.ADX(data_frame['%s_High' %self.symbol].values,
                            data_frame['%s_Low' %self.symbol].values,
                            data_frame['%s_Close' %self.symbol].values,
                            timeperiod=self.period)
            plus_di = talib.PLUS_DI(data_frame['%s_High' %self.symbol].values,
                                    data_frame['%s_Low' %self.symbol].values,
                                    data_frame['%s_Close' %self.symbol].values,
                                    timeperiod=self.period)
            minus_di = talib.MINUS_DI(data_frame['%s_High' %self.symbol].values,
                                      data_frame['%s_Low' %self.symbol].values,
                                      data_frame['%s_Close' %self.symbol].values,
                                      timeperiod=self.period)
            data_frame[self.value] = adx
            data_frame[self.plus_di] = plus_di
            data_frame[self.minus_di] = minus_di
        except KeyError:
            data_frame[self.value] = np.nan
            data_frame[self.plus_di] = np.nan
            data_frame[self.minus_di] = np.nan 

def add_MINUS_DI(self, timeperiod=14,
                 type='line', color='decreasing', **kwargs):
    """Minus Directional Indicator."""

    if not (self.has_high and self.has_low and self.has_close):
        raise Exception()

    utils.kwargs_check(kwargs, VALID_TA_KWARGS)
    if 'kind' in kwargs:
        type = kwargs['kind']

    name = 'MINUS_DI({})'.format(str(timeperiod))
    self.sec[name] = dict(type=type, color=color)
    self.ind[name] = talib.MINUS_DI(self.df[self.hi].values,
                                    self.df[self.lo].values,
                                    self.df[self.cl].values,
                                    timeperiod) 

def di(candles: np.ndarray, period=14, sequential=False) -> DI:
    """
    DI - Directional Indicator

    :param candles: np.ndarray
    :param period: int - default=14
    :param sequential: bool - default=False

    :return: DI(plus, minus)
    """
    if not sequential and len(candles) > 240:
        candles = candles[-240:]

    MINUS_DI = talib.MINUS_DI(candles[:, 3], candles[:, 4], candles[:, 2], timeperiod=period)
    PLUS_DI = talib.PLUS_DI(candles[:, 3], candles[:, 4], candles[:, 2], timeperiod=period)

    if sequential:
        return DI(PLUS_DI, MINUS_DI)
    else:
        return DI(PLUS_DI[-1], MINUS_DI[-1]) 

def before_trading(context):
    prices = history_bars(context.s1, context.window, '1d', fields=['high', 'low', 'close', 'open'])
    highP = prices['high']
    lowP = prices['low']
    closeP = prices['close']
    openP = prices['open']

    context.ADX = ta.ADXR(highP, lowP, closeP, timeperiod=14)
    context.Pdi = ta.PLUS_DI(highP, lowP, closeP, timeperiod=14)
    context.Ndi = ta.MINUS_DI(highP, lowP, closeP, timeperiod=14)

    context.MA_tw = ta.MA(closeP, timeperiod=20)[-5:]
    context.MA_fi = ta.MA(closeP, timeperiod=50)[-5:]
    context.MA_fork = context.MA_tw > context.MA_fi

    context.SAR = ta.SAR(highP, lowP, acceleration=context.acceleration, maximum=0.2)

    # context.JQ_selOpen = (context.ADX[-1]>=20) #& (context.ADX[-2]>=20) & (context.ADX[-1]<=30) & (context.ADX[-2]<=30)
    context.JW_selOpen = (context.Pdi[-1] <= context.Ndi[-1]) & (context.Pdi[-2] >= context.Ndi[-2])
    context.JE_selOpen = (context.MA_fork[-1]) & (context.MA_fork[-2]) & (not context.MA_fork[-3])
    context.JR_selOpen = (context.SAR[-1] >= 0.95 * openP[-1]) & (context.SAR[-2] <= 1.05 * closeP[-2])
    context.J_selOpen = context.JQ_selOpen & context.JW_selOpen & context.JE_selOpen & context.JR_selOpen

    # context.JQ_buyOpen = context.JQ_selOpen
    context.JW_buyOpen = (context.Pdi[-1] >= context.Ndi[-1]) & (context.Pdi[-2] <= context.Ndi[-2])
    context.JE_buyOpen = (not context.MA_fork[-1]) & (not context.MA_fork[-2]) & (not context.MA_fork[-3])
    context.JR_buyOpen = (context.SAR[-2] >= 0.95 * openP[-2]) & (context.SAR[-1] <= 1.05 * closeP[-1])
    context.J_buyOpen = context.JQ_buyOpen & context.JW_buyOpen & context.JE_buyOpen & context.JR_buyOpen


# 你选择的期货数据更新将会触发此段逻辑，例如日线或分钟线更新 

def minus_di(self, sym, frequency, *args, **kwargs):
        if not self.kbars_ready(sym, frequency):
            return []

        highs = self.high(sym, frequency)
        lows = self.low(sym, frequency)
        closes = self.close(sym, frequency)

        return ta.MINUS_DI(highs, lows, closes, *args, **kwargs) 

def di_minus(high, low, close, period=14):
    return talib.MINUS_DI(high, low, close, period) 

def test_dmi():
    '''test TA.DMI'''

    dmp = TA.DMI(ohlc, 14, False)["DI+"]
    talib_dmp = talib.PLUS_DI(ohlc["high"], ohlc["low"], ohlc["close"], timeperiod=14)

    # assert talib_dmp[-1] == dmp.values[-1]
    # assert 25.399441371241316 == 24.99395020211371
    pass  #  close enough

    dmn = TA.DMI(ohlc, 14, False)["DI-"]
    talib_dmn = talib.MINUS_DI(ohlc["high"], ohlc["low"], ohlc["close"], timeperiod=14)

    assert talib_dmn[-1] == dmn.values[-1] 

def MINUS_DI(frame, n=14, high_col='high', low_col='low', close_col='close'):
    return _frame_to_series(frame, [high_col, low_col, close_col], talib.MINUS_DI, n) 

def MINUS_DI(data, **kwargs):
    _check_talib_presence()
    _, phigh, plow, pclose, _ = _extract_ohlc(data)
    return talib.MINUS_DI(phigh, plow, pclose, **kwargs)