增加TICK_MODE和BAR_MODE，支持回测。
This commit is contained in:
msincenselee
parent
c9fcaadab3
commit
dec9cd0299
@ -39,6 +39,12 @@ class CtaLineBar(object):
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"""
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# 区别：
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# -使用tick模式时，当tick到达后，最新一个lineBar[-1]是当前的正在拟合的bar，不断累积tick，传统按照OnBar来计算的话，是使用LineBar[-2]。
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# -使用bar模式时，当一个bar到达时，lineBar[-1]是当前生成出来的Bar,不再更新
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TICK_MODE = 'tick'
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BAR_MODE = 'bar'
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# 参数列表，保存了参数的名称
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paramList = ['vtSymbol']
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@ -52,6 +58,8 @@ class CtaLineBar(object):
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self.paramList.append('inputPreLen')
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self.paramList.append('inputEma1Len')
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self.paramList.append('inputEma2Len')
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self.paramList.append('inputMa1Len')
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self.paramList.append('inputMa2Len')
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self.paramList.append('inputDmiLen')
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self.paramList.append('inputDmiMax')
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self.paramList.append('inputAtr1Len')
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@ -75,10 +83,16 @@ class CtaLineBar(object):
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# 输入参数
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self.name = u'LineBar'
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self.mode = self.TICK_MODE
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self.barTimeInterval = 300
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self.inputPreLen = EMPTY_INT #1
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self.inputMa1Len = EMPTY_INT # 60
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self.inputMa2Len = EMPTY_INT # 240
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self.inputEma1Len = EMPTY_INT # 13
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self.inputEma2Len = EMPTY_INT # 21
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@ -115,10 +129,14 @@ class CtaLineBar(object):
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self.preHigh = [] # K线的前inputPreLen的的最高
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self.preLow = [] # K线的前inputPreLen的的最低
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self.lineEma1 = [] # K线的EMA1均线，周期是InputEmaLen1，包含当前bar
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self.lineMa1 = [] # K线的MA1均线，周期是InputMaLen1，不包含当前bar
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self.lineMa2 = [] # K线的MA2均线，周期是InputMaLen2，不包含当前bar
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self.lineEma1 = [] # K线的EMA1均线，周期是InputEmaLen1，不包含当前bar
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self.lineEma1MtmRate = [] # K线的EMA1均线 的momentum(3) 动能
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self.lineEma2 = [] # K线的EMA2均线，周期是InputEmaLen2，包含当前bar
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self.lineEma2 = [] # K线的EMA2均线，周期是InputEmaLen2，不包含当前bar
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self.lineEma2MtmRate = [] # K线的EMA2均线 的momentum(3) 动能
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# K线的DMI( Pdi，Mdi，ADX，Adxr) 计算数据
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@ -202,6 +220,10 @@ class CtaLineBar(object):
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d[key] = setting[key]
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def setMode(self,mode):
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"""Tick/Bar模式"""
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self.mode = mode
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def onTick(self, tick):
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"""行情更新
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:type tick: object
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@ -247,6 +269,7 @@ class CtaLineBar(object):
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"""OnBar事件"""
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# 计算相关数据
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self.__recountPreHighLow()
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self.__recountMa()
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self.__recountEma()
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self.__recountDmi()
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self.__recountAtr()
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@ -261,14 +284,25 @@ class CtaLineBar(object):
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def displayLastBar(self):
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"""显示最后一个Bar的信息"""
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msg = self.name
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msg = u'['+self.name+u']'
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if self.mode == self.TICK_MODE:
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displayBar = self.lineBar[-2]
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else:
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displayBar = self.lineBar[-1]
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if len(self.lineBar) < 2:
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return msg
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msg = msg + u'{0} o:{1};h{2};l:{3};c:{4},v:{5}'.\
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format(self.lineBar[-2].datetime, self.lineBar[-2].open, self.lineBar[-2].high,
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self.lineBar[-2].low, self.lineBar[-2].close, self.lineBar[-2].volume)
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format(displayBar.datetime, displayBar.open, displayBar.high,
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displayBar.low, displayBar.close, displayBar.volume)
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if self.inputMa1Len > 0 and len(self.lineMa1) > 0:
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msg = msg + u',MA({0}):{1}'.format(self.inputMa1Len, self.lineMa1[-1])
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if self.inputMa2Len > 0 and len(self.lineMa2) > 0:
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msg = msg + u',MA({0}):{1}'.format(self.inputMa2Len, self.lineMa2[-1])
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if self.inputEma1Len > 0 and len(self.lineEma1) > 0:
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msg = msg + u',EMA({0}):{1}'.format(self.inputEma1Len, self.lineEma1[-1])
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@ -469,7 +503,12 @@ class CtaLineBar(object):
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preHigh = EMPTY_FLOAT
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preLow = EMPTY_FLOAT
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for i in range(len(self.lineBar)-2, len(self.lineBar)-2-self.inputPreLen, -1):
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if self.mode == self.TICK_MODE:
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idx = 2
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else:
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idx = 1
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for i in range(len(self.lineBar)-idx, len(self.lineBar)-idx-self.inputPreLen, -1):
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if self.lineBar[i].high > preHigh or preHigh == EMPTY_FLOAT:
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preHigh = self.lineBar[i].high # 前InputPreLen周期高点
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@ -488,8 +527,61 @@ class CtaLineBar(object):
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self.preLow.append(preLow)
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#----------------------------------------------------------------------
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def __recountMa(self):
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"""计算K线的MA1 和MA2"""
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l = len(self.lineBar)
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# 1、lineBar满足长度才执行计算
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if len(self.lineBar) < max(7, self.inputMa1Len, self.inputMa2Len)+2:
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self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算MA需要：{1}'.
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format(len(self.lineBar), max(7, self.inputMa1Len, self.inputMa2Len)+2))
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return
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# 计算第一条MA均线
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if self.inputMa1Len > 0:
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if self.inputMa1Len > l:
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ma1Len = l
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else:
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ma1Len = self.inputMa1Len
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# 3、获取前InputN周期(不包含当前周期）的K线
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if self.mode == self.TICK_MODE:
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listClose=[x.close for x in self.lineBar[-ma1Len - 1:-1]]
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else:
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listClose=[x.close for x in self.lineBar[-ma1Len:]]
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barMa1 = ta.MA(numpy.array(listClose, dtype=float), ma1Len)[-1]
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barMa1 = round(float(barMa1), 3)
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if len(self.lineMa1) > self.inputMa1Len*8:
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del self.lineMa1[0]
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self.lineMa1.append(barMa1)
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# 计算第二条MA均线
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if self.inputMa2Len > 0:
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if self.inputMa2Len > l:
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ma2Len = l
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else:
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ma2Len = self.inputMa2Len
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# 3、获取前InputN周期(不包含当前周期）的K线
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if self.mode == self.TICK_MODE:
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listClose=[x.close for x in self.lineBar[-ma2Len - 1:-1]]
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else:
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listClose=[x.close for x in self.lineBar[-ma2Len:]]
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barMa2 = ta.MA(numpy.array(listClose, dtype=float), ma2Len)[-1]
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barMa2 = round(float(barMa2), 3)
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if len(self.lineMa2) > self.inputMa2Len*8:
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del self.lineMa2[0]
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self.lineMa2.append(barMa2)
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#----------------------------------------------------------------------
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def __recountEma(self):
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"""计算K线的EMA1 和EMA2"""
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l = len(self.lineBar)
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@ -508,8 +600,11 @@ class CtaLineBar(object):
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else:
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ema1Len = self.inputEma1Len
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# 3、获取前InputN周期(不包含当前周期）的自适应均线
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listClose=[x.close for x in self.lineBar[-ema1Len - 1:-1]]
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# 3、获取前InputN周期(不包含当前周期）的K线
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if self.mode == self.TICK_MODE:
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listClose=[x.close for x in self.lineBar[-ema1Len - 1:-1]]
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else:
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listClose=[x.close for x in self.lineBar[-ema1Len:]]
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barEma1 = ta.EMA(numpy.array(listClose, dtype=float), ema1Len)[-1]
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@ -528,7 +623,11 @@ class CtaLineBar(object):
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ema2Len = self.inputEma2Len
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# 3、获取前InputN周期(不包含当前周期）的自适应均线
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listClose=[x.close for x in self.lineBar[-ema2Len - 1:-1]]
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if self.mode == self.TICK_MODE:
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listClose=[x.close for x in self.lineBar[-ema2Len - 1:-1]]
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else:
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listClose=[x.close for x in self.lineBar[-ema2Len:]]
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barEma2 = ta.EMA(numpy.array(listClose, dtype=float), ema2Len)[-1]
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barEma2 = round(float(barEma2), 3)
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@ -555,7 +654,12 @@ class CtaLineBar(object):
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barPdm = EMPTY_FLOAT # InputP周期内的做多价差之和
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barMdm = EMPTY_FLOAT # InputP周期内的做空价差之和
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for i in range(len(self.lineBar)-2, len(self.lineBar)-2-self.inputDmiLen, -1): # 周期 inputDmiLen
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if self.mode == self.TICK_MODE:
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idx = 2
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else:
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idx = 1
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for i in range(len(self.lineBar)-idx, len(self.lineBar)-idx-self.inputDmiLen, -1): # 周期 inputDmiLen
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# 3.1、计算TR1
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# 当前周期最高与最低的价差
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@ -686,6 +790,11 @@ class CtaLineBar(object):
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format(len(self.lineBar), maxAtrLen+1))
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return
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if self.mode == self.TICK_MODE:
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idx = 2
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else:
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idx = 1
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# 首次计算
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if (self.inputAtr1Len > 0 and len(self.lineAtr1) < 1) \
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or (self.inputAtr2Len > 0 and len(self.lineAtr2) < 1) \
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@ -697,7 +806,8 @@ class CtaLineBar(object):
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barTr3 = EMPTY_FLOAT # 获取inputAtr3Len周期内的价差最大值之和
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j = 0
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for i in range(len(self.lineBar)-2, len(self.lineBar)-2-maxAtrLen, -1): # 周期 inputP
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for i in range(len(self.lineBar)-idx, len(self.lineBar)-idx-maxAtrLen, -1): # 周期 inputP
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# 3.1、计算TR
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# 当前周期最高与最低的价差
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@ -721,11 +831,11 @@ class CtaLineBar(object):
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else: # 只计算一个
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# 当前周期最高与最低的价差
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high_low_spread = self.lineBar[-2].high - self.lineBar[-2].low
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high_low_spread = self.lineBar[0-idx].high - self.lineBar[0-idx].low
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# 当前周期最高与昨收价的价差
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high_preclose_spread = abs(self.lineBar[-2].high - self.lineBar[-3].close)
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high_preclose_spread = abs(self.lineBar[0-idx].high - self.lineBar[-1-idx].close)
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# 当前周期最低与昨收价的价差
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low_preclose_spread = abs(self.lineBar[-2].low - self.lineBar[-3].close)
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low_preclose_spread = abs(self.lineBar[0-idx].low - self.lineBar[-1-idx].close)
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# 最大价差
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barTr1 = max(high_low_spread, high_preclose_spread, low_preclose_spread)
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@ -777,7 +887,10 @@ class CtaLineBar(object):
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format(len(self.lineBar), self.inputVolLen+1))
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return
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listVol = [x.volume for x in self.lineBar[-self.inputVolLen-1: -1]]
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if self.mode == self.TICK_MODE:
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listVol = [x.volume for x in self.lineBar[-self.inputVolLen-1: -1]]
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else:
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listVol = [x.volume for x in self.lineBar[-self.inputVolLen:]]
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sumVol = ta.SUM(numpy.array(listVol, dtype=float), timeperiod=self.inputVolLen)[-1]
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@ -801,7 +914,11 @@ class CtaLineBar(object):
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# 计算第1根RSI曲线
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# 3、inputRsi1Len(包含当前周期）的相对强弱
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listClose=[x.close for x in self.lineBar[-self.inputRsi1Len - 2:-1]]
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if self.mode == self.TICK_MODE:
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listClose=[x.close for x in self.lineBar[-self.inputRsi1Len - 2:-1]]
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else:
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listClose=[x.close for x in self.lineBar[-self.inputRsi1Len-1:]]
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barRsi = ta.RSI(numpy.array(listClose, dtype=float), self.inputRsi1Len)[-1]
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barRsi = round(float(barRsi), 3)
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@ -846,7 +963,11 @@ class CtaLineBar(object):
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if len(self.lineBar) < self.inputRsi2Len+2:
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return
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listClose=[x.close for x in self.lineBar[-self.inputRsi2Len - 2:]]
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if self.mode == self.TICK_MODE:
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listClose=[x.close for x in self.lineBar[-self.inputRsi2Len - 2:-1]]
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else:
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listClose=[x.close for x in self.lineBar[-self.inputRsi2Len - 1:]]
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barRsi = ta.RSI(numpy.array(listClose, dtype=float), self.inputRsi2Len)[-1]
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barRsi = round(float(barRsi), 3)
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@ -876,14 +997,20 @@ class CtaLineBar(object):
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format(len(self.lineBar), self.inputCmiLen))
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return
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listClose =[x.close for x in self.lineBar[-self.inputCmiLen:-1]]
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if self.mode == self.TICK_MODE:
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listClose =[x.close for x in self.lineBar[-self.inputCmiLen-1:-1]]
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idx = 2
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else:
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listClose =[x.close for x in self.lineBar[-self.inputCmiLen:]]
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idx = 1
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hhv = max(listClose)
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llv = min(listClose)
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if hhv==llv:
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cmi = 100
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else:
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cmi = abs(self.lineBar[-1].close-self.lineBar[-2].close)*100/(hhv-llv)
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cmi = abs(self.lineBar[0-idx].close-self.lineBar[-1-idx].close)*100/(hhv-llv)
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cmi = round(cmi, 2)
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@ -909,7 +1036,10 @@ class CtaLineBar(object):
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bollLen = self.inputBollLen
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# 不包含当前最新的Bar
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listClose=[x.close for x in self.lineBar[-bollLen - 1:-1]]
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if self.mode == self.TICK_MODE:
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listClose=[x.close for x in self.lineBar[-bollLen - 1:-1]]
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else:
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listClose=[x.close for x in self.lineBar[-bollLen :]]
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#
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upper, middle, lower = ta.BBANDS(numpy.array(listClose, dtype=float),
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timeperiod=bollLen, nbdevup=self.inputBollStdRate,
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@ -950,7 +1080,11 @@ class CtaLineBar(object):
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self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算KDJ需要：{1}'.format(len(self.lineBar), self.inputKdjLen+1))
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return
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listClose =[x.close for x in self.lineBar[-self.inputKdjLen:-1]]
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if self.mode == self.TICK_MODE:
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listClose =[x.close for x in self.lineBar[-self.inputKdjLen-1:-1]]
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else:
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listClose =[x.close for x in self.lineBar[-self.inputKdjLen:]]
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hhv = max(listClose)
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llv = min(listClose)
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@ -996,8 +1130,8 @@ class CtaLineBar(object):
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差离值（DIF）的计算： DIF = EMA12 - EMA26，即为talib-MACD返回值macd
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根据差离值计算其9日的EMA，即离差平均值，是所求的DEA值。
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今日DEA = （前一日DEA X 8/10 + 今日DIF X 2/10），即为talib-MACD返回值signal
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DIF与它自己的移动平均之间差距的大小一般BAR=（DIF-DEA)2，即为MACD柱状图。
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但是talib中MACD的计算是bar = (dif-dea)1
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DIF与它自己的移动平均之间差距的大小一般BAR=（DIF-DEA)*2，即为MACD柱状图。
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但是talib中MACD的计算是bar = (dif-dea)*1
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"""
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@ -1005,17 +1139,26 @@ class CtaLineBar(object):
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if self.inputMacdSlowPeriodLen <= EMPTY_INT: return
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if self.inputMacdSignalPeriodLen <= EMPTY_INT: return
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maxLen = max(self.inputMacdFastPeriodLen,self.inputMacdSlowPeriodLen)+self.inputMacdSignalPeriodLen
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maxLen = max(self.inputMacdFastPeriodLen,self.inputMacdSlowPeriodLen)+self.inputMacdSignalPeriodLen+1
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maxLen = maxLen * 3 # 注：数据长度需要足够，才能准确。测试过，3倍长度才可以与国内的文华等软件一致
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if len(self.lineBar) < maxLen:
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self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算MACD需要：{1}'.format(len(self.lineBar), maxLen))
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return
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listClose =[x.close for x in self.lineBar[-maxLen:-1]]
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if self.mode == self.TICK_MODE:
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listClose =[x.close for x in self.lineBar[-maxLen:-1]]
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else:
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listClose =[x.close for x in self.lineBar[-maxLen-1:]]
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dif, dea, macd = ta.MACD(numpy.array(listClose, dtype=float), fastperiod=self.inputMacdFastPeriodLen,
|
||||
slowperiod=self.inputMacdSlowPeriodLen, signalperiod=self.inputMacdSignalPeriodLen)
|
||||
|
||||
#dif, dea, macd = ta.MACDEXT(numpy.array(listClose, dtype=float),
|
||||
# fastperiod=self.inputMacdFastPeriodLen, fastmatype=1,
|
||||
# slowperiod=self.inputMacdSlowPeriodLen, slowmatype=1,
|
||||
# signalperiod=self.inputMacdSignalPeriodLen, signalmatype=1)
|
||||
|
||||
if len(self.lineDif) > maxLen:
|
||||
del self.lineDif[0]
|
||||
@ -1027,7 +1170,7 @@ class CtaLineBar(object):
|
||||
|
||||
if len(self.lineMacd) > maxLen:
|
||||
del self.lineMacd[0]
|
||||
self.lineMacd.append(macd[-1]*2)
|
||||
self.lineMacd.append(macd[-1]*2) # 国内一般是2倍
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
def writeCtaLog(self, content):
|
||||
|
||||
Loading…
Reference in New Issue
Block a user