Python talib.STOCH属性代码示例

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def kdj(self, sym, frequency, fastk_period=5, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0):
        if not self.kbars_ready(sym, frequency):
            return [], []

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

        slowk, slowd = ta.STOCH(high=highs,
                                low=lows,
                                fastk_period=fastk_period,
                                close=closes,
                                slowk_period=slowk_period,
                                slowk_matype=slowk_matype,
                                slowd_period=slowd_period,
                                slowd_matype=slowd_matype)
        return slowk, slowd 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def calculate_stoch(self, period_name, closing_prices):
        slowk, slowd = talib.STOCH(self.highs, self.lows, closing_prices, fastk_period=14, slowk_period=2, slowk_matype=0, slowd_period=3, slowd_matype=0)
        self.current_indicators[period_name]['stoch_slowk'] = slowk[-1]
        self.current_indicators[period_name]['stoch_slowd'] = slowd[-1] 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def TA_KDJ(high:np.ndarray, 
           low:np.ndarray, 
           close:np.ndarray, 
           fastk_period:int=9, 
           slowk_matype:int=0, 
           slowk_period:int=3, 
           slowd_period:int=3) -> np.ndarray:
    '''
    参数设置:
        fastk_period = 9
        lowk_matype = 0, 
        slowk_period = 3, 
        slowd_period = 3

    返回: K, D, J
    '''
    K, D = talib.STOCH(high, 
                       low, 
                       close, 
                       fastk_period=fastk_period, 
                       slowk_matype=slowk_matype, 
                       slowk_period=slowk_period, 
                       slowd_period=slowd_period)
    J = 3 * K - 2 * D
    delta = np.r_[np.nan, np.diff(J)]
    return np.c_[K, D, J, delta] 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def STOCH(DataFrame, fastk_period=5, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0):
    slowk, slowd = talib.STOCH(DataFrame.high.values, DataFrame.low.values, DataFrame.close.values,
                               fastk_period, slowk_period, slowk_matype, slowd_period, slowd_matype)
    return pd.DataFrame({'STOCH_SLOWK': slowk, 'STOCH_SLOWD': slowd}, index=DataFrame.index) 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def __str__(self):
        return 'STOCH(symbol=%s, fast_k_period=%s, slow_k_period=%s, \
                      slow_k_ma_type=%s, slow_d_period=%s, self_d_ma_type=%s)' \
                      %(self.symbol, self.fast_k_period, self.slow_k_period, \
                      self.slow_k_ma_type, self.slow_d_period, self.slow_d_ma_type) 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def results(self, data_frame):
        try:
            slowk, slowd = talib.STOCH(data_frame['%s_High' %self.symbol].values,
                                       data_frame['%s_Low' %self.symbol].values,
                                       data_frame['%s_Close' %self.symbol].values,
                                       self.fast_k_period, self.slow_k_period,
                                       self.slow_k_ma_type, self.slow_d_period,
                                       self.slow_d_ma_type)
            data_frame[self.slowk] = slowk
            data_frame[self.slowd] = slowd
        except KeyError:
            data_frame[self.slowk] = np.nan
            data_frame[self.slowd] = np.nan 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def add_STOCH(self, fastk_period=5, slowk_period=3,
              slowk_matype=0, slowd_period=3, slowd_matype=0,
              types=['line', 'line'],
              colors=['primary', 'tertiary'],
              **kwargs):
    """Slow Stochastic Oscillator.

    Note that the first argument of types and colors refers to Slow Stoch %K,
    while second argument refers to Slow Stoch %D
    (signal line of %K obtained by MA).

    """
    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:
        kwargs['type'] = kwargs['kind']
    if 'kinds' in kwargs:
        types = kwargs['type']

    if 'type' in kwargs:
        types = [kwargs['type']] * 2
    if 'color' in kwargs:
        colors = [kwargs['color']] * 2

    name = 'STOCH({},{},{})'.format(str(fastk_period),
                                    str(slowk_period),
                                    str(slowd_period))
    slowk = name + r'[%k]'
    slowd = name + r'[%d]'
    self.sec[slowk] = dict(type=types[0], color=colors[0])
    self.sec[slowd] = dict(type=types[1], color=colors[1], on=slowk)
    self.ind[slowk], self.ind[slowd] = talib.STOCH(self.df[self.hi].values,
                                                   self.df[self.lo].values,
                                                   self.df[self.cl].values,
                                                   fastk_period, slowk_period,
                                                   slowk_matype, slowd_period,
                                                   slowd_matype) 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def stoch(candles: np.ndarray, fastk_period=14, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0,
          sequential=False) -> Stochastic:
    """
    The Stochastic Oscillator

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

    :return: Stochastic(k, d)
    """
    if not sequential and len(candles) > 240:
        candles = candles[-240:]

    k, d = talib.STOCH(
        candles[:, 3],
        candles[:, 4],
        candles[:, 2],
        fastk_period=fastk_period,
        slowk_period=slowk_period,
        slowk_matype=slowk_matype,
        slowd_period=slowd_period,
        slowd_matype=slowd_matype
    )

    if sequential:
        return Stochastic(k, d)
    else:
        return Stochastic(k[-1], d[-1]) 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def test_stoch():
    """test TA.STOCH"""

    stoch = TA.STOCH(ohlc, 9)
    talib_stoch = talib.STOCH(ohlc["high"], ohlc["low"], ohlc["close"], 9)

    #  talib_stoch[0] is "slowk"
    # assert talib_stoch[0][-1] == stoch.values[-1]
    # assert 76.27794470586021 == 80.7982311922445
    pass  # close enough 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def STOCH(frame, fastk=5, slowk=3, slowk_matype=0, slowd=3, slowd_matype=0, high_col='high', low_col='low',
          close_col='close'):
    return _frame_to_frame(frame, [high_col, low_col, close_col], ['SlowK', 'SlowD'], talib.STOCH, fastk, slowk,
                           slowk_matype, slowd, slowd_matype) 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def test_stoch(self):
        result = pandas_ta.stoch(self.high, self.low, self.close, fast_k=14, slow_k=14, slow_d=14)
        self.assertIsInstance(result, DataFrame)
        self.assertEqual(result.name, 'STOCH_14_14_14')
        self.assertEqual(len(result.columns), 4)

        result = pandas_ta.stoch(self.high, self.low, self.close)
        self.assertIsInstance(result, DataFrame)
        self.assertEqual(result.name, 'STOCH_14_5_3')

        try:
            tal_stochf = tal.STOCHF(self.high, self.low, self.close)
            tal_stoch = tal.STOCH(self.high, self.low, self.close)
            tal_stochdf = DataFrame({'STOCHF_14': tal_stochf[0], 'STOCHF_3': tal_stochf[1], 'STOCH_5': tal_stoch[0], 'STOCH_3': tal_stoch[1]})
            pdt.assert_frame_equal(result, tal_stochdf)
        except AssertionError as ae:
            try:
                stochfk_corr = pandas_ta.utils.df_error_analysis(result.iloc[:,0], tal_stochdf.iloc[:,0], col=CORRELATION)
                self.assertGreater(stochfk_corr, CORRELATION_THRESHOLD)
            except Exception as ex:
                error_analysis(result.iloc[:,0], CORRELATION, ex)

            try:
                stochfd_corr = pandas_ta.utils.df_error_analysis(result.iloc[:,1], tal_stochdf.iloc[:,1], col=CORRELATION)
                self.assertGreater(stochfd_corr, CORRELATION_THRESHOLD)
            except Exception as ex:
                error_analysis(result.iloc[:,1], CORRELATION, ex, newline=False)

            try:
                stochsk_corr = pandas_ta.utils.df_error_analysis(result.iloc[:,2], tal_stochdf.iloc[:,2], col=CORRELATION)
                self.assertGreater(stochsk_corr, CORRELATION_THRESHOLD)
            except Exception as ex:
                error_analysis(result.iloc[:,2], CORRELATION, ex, newline=False)

            try:
                stochsd_corr = pandas_ta.utils.df_error_analysis(result.iloc[:,3], tal_stochdf.iloc[:,3], col=CORRELATION)
                self.assertGreater(stochsd_corr, CORRELATION_THRESHOLD)
            except Exception as ex:
                error_analysis(result.iloc[:,3], CORRELATION, ex, newline=False) 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def STOCH(data, **kwargs):
    _check_talib_presence()
    _, phigh, plow, pclose, _ = _extract_ohlc(data)
    return talib.STOCH(phigh, plow, pclose, **kwargs) 

# 需要导入模块: import talib [as 别名]
# 或者: from talib import STOCH [as 别名]
def on_bar(self, bar):
        if self.cls_mode == gm.MD_MODE_PLAYBACK:
            if bar.strtime[0:10] != self.cur_date[0:10]:
                self.cur_date = bar.strtime[0:10] + ' 08:00:00'
                # 新的交易日
                self.init_data_newday()

        symbol = bar.exchange + '.' + bar.sec_id

        self.movement_stop_profit_loss(bar)
        self.fixation_stop_profit_loss(bar)

        pos = self.get_position(bar.exchange, bar.sec_id, OrderSide_Bid)

        # 补充当天价格
        if symbol in self.dict_price:
            if self.dict_price[symbol][0][-1] < bar.high:
                self.dict_price[symbol][0][-1] = bar.high

            if self.dict_price[symbol][1][-1] > bar.low:
                self.dict_price[symbol][1][-1] = bar.low

            self.dict_price[symbol][2][-1] = bar.close

        if self.dict_open_close_signal[symbol] is False:
            # 当天未有对该代码开、平仓
            if symbol in self.dict_price:
                slowk, slowd = talib.STOCH(high=self.dict_price[symbol][0],
                                           low=self.dict_price[symbol][1],
                                           close=self.dict_price[symbol][2],
                                           fastk_period=self.fastk_period,
                                           slowk_period=self.slowk_period,
                                           slowk_matype=self.slowk_matype,
                                           slowd_period=self.slowd_period,
                                           slowd_matype=self.slowd_matype)

                if pos is None and symbol not in self.dict_open_cum_days \
                        and (slowk[-1] < self.slowk_bid or slowd[-1] < self.slowd_bid):
                    # 有开仓机会则设置已开仓的交易天数
                    self.dict_open_cum_days[symbol] = 0

                    cash = self.get_cash()
                    cur_open_vol = self.open_vol
                    if cash.available / bar.close > self.open_vol:
                        cur_open_vol = self.open_vol
                    else:
                        cur_open_vol = int(cash.available / bar.close / 100) * 100

                    if cur_open_vol == 0:
                        print('no available cash to buy, available cash: %.2f' % cash.available)
                    else:
                        self.open_long(bar.exchange, bar.sec_id, bar.close, cur_open_vol)
                        self.dict_open_close_signal[symbol] = True
                        logging.info('open long, symbol:%s, time:%s, price:%.2f' % (symbol, bar.strtime, bar.close))
                elif pos is not None and (slowk[-1] > self.slowk_sell or slowd[-1] > self.slowd_sell):
                    vol = pos.volume - pos.volume_today
                    if vol > 0:
                        self.close_long(bar.exchange, bar.sec_id, bar.close, vol)
                        self.dict_open_close_signal[symbol] = True
                        logging.info('close long, symbol:%s, time:%s, price:%.2f' % (symbol, bar.strtime, bar.close))