コード例 #1
0
ファイル: macd_plots.py プロジェクト: ystar2016/PureQuant
class Kline:
    def __init__(self):
        config.loads('config.json')
        self.symbol = "BTC-USD-SWAP"
        self.timeframe = "1m"
        self.exchange = HUOBISWAP("", "", self.symbol)
        self.indicators = INDICATORS(self.exchange, self.symbol,
                                     self.timeframe)

    def update(self):
        table = self.exchange.get_kline(self.timeframe)
        table.reverse()
        try:
            df = pd.DataFrame(
                table,
                columns='time open high low close volume currency_volume'.
                split())
            df = df.astype({
                'time': 'datetime64[ns]',
                'open': 'float64',
                'high': 'float64',
                'low': 'float64',
                'close': 'float64',
                'volume': 'float64',
                'currency_volume': 'float64'
            })
        except:
            df = pd.DataFrame(
                table, columns='time open high low close volume'.split())
            df = df.astype({
                'time': 'datetime64[ns]',
                'open': 'float64',
                'high': 'float64',
                'low': 'float64',
                'close': 'float64',
                'volume': 'float64'
            })
        candlesticks = df['time open close high low'.split()]
        volumes = df['time open close volume'.split()]
        result = self.indicators.MACD(12, 26, 9)
        dif = result['DIF']
        dea = result['DEA']
        macd = result['MACD']
        if not plots:
            # first time we create the plots
            global ax, ax2, ax3
            plots.append(fplt.candlestick_ochl(candlesticks))
            plots.append(fplt.volume_ocv(volumes, ax=ax2))
            plots.append(fplt.plot(dif, ax=ax3, legend="DIF"))
            plots.append(fplt.plot(dea, ax=ax3, legend="DEA"))
            plots.append(fplt.plot(macd, ax=ax3, legend="MACD"))
        else:
            # every time after we just update the data sources on each plot
            plots[0].update_data(candlesticks)
            plots[1].update_data(volumes)
            plots[2].update_data(dif)
            plots[3].update_data(dea)
            plots[4].update_data(macd)
コード例 #2
0
class SIGNALIZE:
    """实盘时根据从交易所获取的k线数据绘制k线图、成交量图及指标"""
    def __init__(self, platform, symbol, time_frame):

        self.__platform = platform
        self.__symbol = symbol
        self.__time_frame = time_frame
        self.__market = MARKET(self.__platform, self.__symbol,
                               self.__time_frame)

        # pull some data
        self.__indicators = INDICATORS(self.__platform, self.__symbol,
                                       self.__time_frame)
        self.__kline = platform.get_kline(self.__time_frame)
        self.__kline.reverse()

        # format it in pandas
        try:  # dataframe有7列的情况
            self.__df = pd.DataFrame(self.__kline,
                                     columns=[
                                         'time', 'open', 'high', 'low',
                                         'close', 'volume', 'currency_volume'
                                     ])
            self.__df = self.__df.astype({
                'time': 'datetime64[ns]',
                'open': 'float64',
                'close': 'float64',
                'high': 'float64',
                'low': 'float64',
                'volume': 'float64',
                'currency_volume': 'float64'
            })
        except:  # dataframe只有6列的情况,如okex的现货k线数据
            self.__df = pd.DataFrame(
                self.__kline,
                columns=['time', 'open', 'high', 'low', 'close', 'volume'])
            self.__df = self.__df.astype({
                'time': 'datetime64[ns]',
                'open': 'float64',
                'close': 'float64',
                'high': 'float64',
                'low': 'float64',
                'volume': 'float64'
            })

        # create three plot 创建三层图纸,第一层画k线,第二层画成交量,第三层画一些适宜于副图显示的指标
        fplt.foreground = '#FFFFFF'  # 前景色
        fplt.background = '#333333'  # 背景色
        fplt.odd_plot_background = '#333333'  # 第二层图纸的背景色
        fplt.cross_hair_color = "#FFFFFF"  # 准星的颜色
        self.__ax, self.__ax2, self.__ax3 = fplt.create_plot(symbol, rows=3)

        # plot candle sticks
        candles = self.__df[['time', 'open', 'close', 'high', 'low']]
        fplt.candlestick_ochl(candles, ax=self.__ax)

        # overlay volume on the plot
        volumes = self.__df[['time', 'open', 'close', 'volume']]
        fplt.volume_ocv(volumes, ax=self.__ax2)
        fplt.add_legend("VOLUME", self.__ax2)  # 增加"VOLUME"图例

    """
    plot indicators
    """

    def show(self):
        """最后必须调用此函数以显示图像"""
        fplt.show()

    def plot_last(self, color=None):
        """在图上画出最新成交价这根横线,便于观察"""
        last = self.__market.last()
        array = np.empty(len(self.__kline))
        array.fill(last)
        color = color if color is not None else "#CD7F32"  # 默认设置为红色
        fplt.plot(self.__df['time'],
                  array,
                  color=color,
                  ax=self.__ax,
                  legend="LAST {}".format(last))

    def plot_array(self, array, ax, legend, color=None):
        """
        绘制任意的数组成线性
        :param array: 传入一个数组
        :param ax: 加载在第几行的图上
        :param legend: 图例名称
        :param color: 颜色
        :return:
        """
        if ax == 1:
            ax = self.__ax
        elif ax == 2:
            ax = self.__ax2
        elif ax == 3:
            ax = self.__ax3
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        fplt.plot(self.__df['time'], array, color=color, ax=ax, legend=legend)

    def plot_atr(self, length, color=None):
        """
        在图上画出ATR
        :param length: ATR指标参数
        :param color: 线的颜色
        :return:
        """
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        fplt.plot(self.__df['time'],
                  self.__indicators.ATR(length),
                  color=color,
                  ax=self.__ax3,
                  legend='ATR({})'.format(length))

    def plot_boll(self, length, color1=None, color2=None, color3=None):
        """
        在图上画出布林通道的上轨、中轨、下轨
        :param length: BOLL指标参数
        :param upperband_color: 上轨颜色
        :param middleband_color: 中轨颜色
        :param lowerband_color: 下轨颜色
        :return:
        """
        color1 = color1 if color1 is not None else "#FF0000"  # 默认设置为红色
        color2 = color2 if color2 is not None else "#00FF00"  # 默认设置为绿色
        color3 = color3 if color3 is not None else "#0000FF"  # 默认设置为蓝色
        upperband_array = self.__indicators.BOLL(length)['upperband']
        middleband_array = self.__indicators.BOLL(length)["middleband"]
        lowerband_array = self.__indicators.BOLL(length)["lowerband"]
        fplt.plot(self.__df['time'],
                  upperband_array,
                  color=color1,
                  ax=self.__ax,
                  legend='BOLL({})-UPPERBAND'.format(length))
        fplt.plot(self.__df['time'],
                  middleband_array,
                  color=color2,
                  ax=self.__ax,
                  legend='BOLL({})-MIDDLEBAND'.format(length))
        fplt.plot(self.__df['time'],
                  lowerband_array,
                  color=color3,
                  ax=self.__ax,
                  legend='BOLL({})-LOWERBAND'.format(length))
        # 副图上也加载
        fplt.plot(self.__df['time'],
                  upperband_array,
                  color=color1,
                  ax=self.__ax3,
                  legend='BOLL({})-UPPERBAND'.format(length))
        fplt.plot(self.__df['time'],
                  middleband_array,
                  color=color2,
                  ax=self.__ax3,
                  legend='BOLL({})-MIDDLEBAND'.format(length))
        fplt.plot(self.__df['time'],
                  lowerband_array,
                  color=color3,
                  ax=self.__ax3,
                  legend='BOLL({})-LOWERBAND'.format(length))

    def plot_highest(self, length, color=None):
        """
        在图上画出最高价
        :param length: HIGHEST指标参数
        :param color: 线的颜色
        :return:
        """
        color = color if color is not None else "#FF0000"  # 默认设置红黑色
        fplt.plot(self.__df['time'],
                  self.__indicators.HIGHEST(length),
                  color=color,
                  ax=self.__ax,
                  legend='HIGHEST({})'.format(length))
        # 副图也加载
        fplt.plot(self.__df['time'],
                  self.__indicators.HIGHEST(length),
                  color=color,
                  ax=self.__ax3,
                  legend='HIGHEST({})'.format(length))

    def plot_ma(self, length, color=None):
        """
        在图上画出移动平均线
        :param length: 简单移动平均线参数
        :param color: 线的颜色
        :return:
        """
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        # 主图与副图加载指标
        fplt.plot(self.__df['time'],
                  self.__indicators.MA(length),
                  color=color,
                  ax=self.__ax,
                  legend='MA({})'.format(length))
        fplt.plot(self.__df['time'],
                  self.__indicators.MA(length),
                  color=color,
                  ax=self.__ax3,
                  legend='MA({})'.format(length))

    def plot_macd(self,
                  fastperiod,
                  slowperiod,
                  signalperiod,
                  color1=None,
                  color2=None,
                  color3=None):
        """
        在图上画出MACD指标
        :param fastperiod:
        :param slowperiod:
        :param signalperiod:
        :param color1:
        :param color2:
        :param color3:
        :return:
        """
        color1 = color1 if color1 is not None else "#FF0000"  # 默认设置为红色
        color2 = color2 if color2 is not None else "#00FF00"  # 默认设置为绿色
        color3 = color3 if color3 is not None else "#0000FF"  # 默认设置为蓝色
        dif = self.__indicators.MACD(fastperiod, slowperiod,
                                     signalperiod)['DIF']
        dea = self.__indicators.MACD(fastperiod, slowperiod,
                                     signalperiod)["DEA"]
        macd = self.__indicators.MACD(fastperiod, slowperiod,
                                      signalperiod)["MACD"]
        fplt.plot(self.__df['time'],
                  dif,
                  color=color1,
                  ax=self.__ax3,
                  legend='MACD({}, {}, {})-DIF'.format(fastperiod, slowperiod,
                                                       signalperiod))
        fplt.plot(self.__df['time'],
                  dea,
                  color=color2,
                  ax=self.__ax3,
                  legend='MACD({}, {}, {})-DEA'.format(fastperiod, slowperiod,
                                                       signalperiod))
        fplt.plot(self.__df['time'],
                  macd,
                  color=color3,
                  ax=self.__ax3,
                  legend='MACD({}, {}, {})-MACD'.format(
                      fastperiod, slowperiod, signalperiod))

    def plot_ema(self, length, color=None):
        """
        在图上画出EMA指标
        :param length:
        :param color:
        :return:
        """
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        fplt.plot(self.__df['time'],
                  self.__indicators.EMA(length),
                  color=color,
                  ax=self.__ax,
                  legend='EMA({})'.format(length))
        # 副图也加载
        fplt.plot(self.__df['time'],
                  self.__indicators.EMA(length),
                  color=color,
                  ax=self.__ax3,
                  legend='EMA({})'.format(length))

    def plot_kama(self, length, color=None):
        """在图上画出KAMA指标"""
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        fplt.plot(self.__df['time'],
                  self.__indicators.KAMA(length),
                  color=color,
                  ax=self.__ax,
                  legend='KAMA({})'.format(length))
        # 副图也加载
        fplt.plot(self.__df['time'],
                  self.__indicators.KAMA(length),
                  color=color,
                  ax=self.__ax3,
                  legend='KAMA({})'.format(length))

    def plot_kdj(self,
                 fastk_period,
                 slowk_period,
                 slowd_period,
                 color1=None,
                 color2=None):
        """
        在图上画出KDJ指标
        :param fastk_period:
        :param slowk_period:
        :param slowd_period:
        :param color1:
        :param color2:
        :param color3:
        :return:
        """
        color1 = color1 if color1 is not None else "#FF0000"  # 默认设置为红色
        color2 = color2 if color2 is not None else "#00FF00"  # 默认设置为绿色
        k = self.__indicators.KDJ(fastk_period, slowk_period,
                                  slowd_period)['k']
        d = self.__indicators.KDJ(fastk_period, slowk_period,
                                  slowd_period)["d"]
        # 仅副图加载
        fplt.plot(self.__df['time'],
                  k,
                  color=color1,
                  ax=self.__ax3,
                  legend='KDJ({}, {}, {})-K'.format(fastk_period, slowk_period,
                                                    slowd_period))
        fplt.plot(self.__df['time'],
                  d,
                  color=color2,
                  ax=self.__ax3,
                  legend='KDJ({}, {}, {})-D'.format(fastk_period, slowk_period,
                                                    slowd_period))

    def plot_lowest(self, length, color=None):
        """LOWEST"""
        color = color if color is not None else "#FF0000"  # 默认设置红黑色
        fplt.plot(self.__df['time'],
                  self.__indicators.LOWEST(length),
                  color=color,
                  ax=self.__ax,
                  legend='LOWEST({})'.format(length))
        # 副图也加载
        fplt.plot(self.__df['time'],
                  self.__indicators.LOWEST(length),
                  color=color,
                  ax=self.__ax3,
                  legend='LOWEST({})'.format(length))

    def plot_obv(self, color=None):
        """OBV"""
        color = color if color is not None else "#FF0000"  # 默认设置红黑色
        # 仅副图加载
        fplt.plot(self.__df['time'],
                  self.__indicators.OBV(),
                  color=color,
                  ax=self.__ax3,
                  legend='OBV')

    def plot_rsi(self, length, color=None):
        """RSI"""
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        # 仅副图加载
        fplt.plot(self.__df['time'],
                  self.__indicators.RSI(length),
                  color=color,
                  ax=self.__ax3,
                  legend='RSI({})'.format(length))

    def plot_roc(self, length, color=None):
        """ROC"""
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        # 仅副图加载
        fplt.plot(self.__df['time'],
                  self.__indicators.ROC(length),
                  color=color,
                  ax=self.__ax3,
                  legend='ROC({})'.format(length))

    def plot_stochrsi(self,
                      timeperiod,
                      fastk_period,
                      fastd_period,
                      color1=None,
                      color2=None):
        """STOCHRSI"""
        color1 = color1 if color1 is not None else "#FF0000"  # 默认设置为红色
        color2 = color2 if color2 is not None else "#00FF00"  # 默认设置为绿色
        stochrsi = self.__indicators.STOCHRSI(timeperiod, fastk_period,
                                              fastd_period)['stochrsi']
        fastk = self.__indicators.STOCHRSI(timeperiod, fastk_period,
                                           fastd_period)["fastk"]
        # 仅副图加载
        fplt.plot(self.__df['time'],
                  stochrsi,
                  color=color1,
                  ax=self.__ax3,
                  legend='STOCHRSI({}, {}, {})-STOCHRSI'.format(
                      timeperiod, fastk_period, fastd_period))
        fplt.plot(self.__df['time'],
                  fastk,
                  color=color2,
                  ax=self.__ax3,
                  legend='STOCHRSI({}, {}, {})-FASTK'.format(
                      timeperiod, fastk_period, fastd_period))

    def plot_sar(self, color=None):
        """
        在图上画出SAR
        :param length: SAR指标参数
        :param color: 线的颜色
        :return:
        """
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        # 主副图均加载
        fplt.plot(self.__df['time'],
                  self.__indicators.SAR(),
                  color=color,
                  ax=self.__ax,
                  legend='SAR')
        fplt.plot(self.__df['time'],
                  self.__indicators.SAR(),
                  color=color,
                  ax=self.__ax3,
                  legend='SAR')

    def plot_stddev(self, length, color=None):
        """STDDEV"""
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        # 仅副图加载
        fplt.plot(self.__df['time'],
                  self.__indicators.STDDEV(length),
                  color=color,
                  ax=self.__ax3,
                  legend='STDDEV({})'.format(length))

    def plot_trix(self, length, color=None):
        """STDDEV"""
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        # 仅副图加载
        fplt.plot(self.__df['time'],
                  self.__indicators.TRIX(length),
                  color=color,
                  ax=self.__ax3,
                  legend='TRIX({})'.format(length))

    def plot_volume(self, color=None):
        """VOLUME"""
        color = color if color is not None else "#FF0000"  # 默认设置为红色
        # 仅副图均加载
        fplt.plot(self.__df['time'],
                  self.__indicators.VOLUME(),
                  color=color,
                  ax=self.__ax3,
                  legend='VOLUME')