# encoding: UTF-8 # AUTHOR:李来佳 # WeChat/QQ: 28888502 from vtConstant import * from ctaBase import * from datetime import datetime import talib as ta import numpy import copy,csv from pykalman import KalmanFilter DEBUGCTALOG = True PERIOD_SECOND = 'second' # 秒级别周期 PERIOD_MINUTE = 'minute' # 分钟级别周期 PERIOD_HOUR = 'hour' # 小时级别周期 PERIOD_DAY = 'day' # 日级别周期 class CtaLineBar(object): """CTA K线""" """ 使用方法: 1、在策略构造函数__init()中初始化 self.lineM = None # 1分钟K线 lineMSetting = {} lineMSetting['name'] = u'M1' lineMSetting['barTimeInterval'] = 60 # 1分钟对应60秒 lineMSetting['inputEma1Len'] = 7 # EMA线1的周期 lineMSetting['inputEma2Len'] = 21 # EMA线2的周期 lineMSetting['inputBollLen'] = 20 # 布林特线周期 lineMSetting['inputBollStdRate'] = 2 # 布林特线标准差 lineMSetting['minDiff'] = self.minDiff # 最小条 lineMSetting['shortSymbol'] = self.shortSymbol #商品短号 self.lineM = CtaLineBar(self, self.onBar, lineMSetting) 2、在onTick()中，需要导入tick数据 self.lineM.onTick(tick) self.lineM5.onTick(tick) # 如果你使用2个周期 3、在onBar事件中，按照k线结束使用；其他任何情况下bar内使用，通过对象使用即可，self.lineM.lineBar[-1].close """ # 区别： # -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]。 # -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 TICK_MODE = 'tick' BAR_MODE = 'bar' # 参数列表，保存了参数的名称 paramList = ['vtSymbol'] def __init__(self, strategy, onBarFunc, setting=None,): # OnBar事件回调函数 self.onBarFunc = onBarFunc # 参数列表 self.paramList.append('barTimeInterval') self.paramList.append('period') self.paramList.append('inputPreLen') self.paramList.append('inputEma1Len') self.paramList.append('inputEma2Len') self.paramList.append('inputMa1Len') self.paramList.append('inputMa2Len') self.paramList.append('inputMa3Len') self.paramList.append('inputDmiLen') self.paramList.append('inputDmiMax') self.paramList.append('inputAtr1Len') self.paramList.append('inputAtr2Len') self.paramList.append('inputAtr3Len') self.paramList.append('inputVolLen') self.paramList.append('inputRsi1Len') self.paramList.append('inputRsi2Len') self.paramList.append('inputCmiLen') self.paramList.append('inputBollLen') self.paramList.append('inputBollStdRate') self.paramList.append('inputKdjLen') self.paramList.append('inputCciLen') self.paramList.append('inputMacdFastPeriodLen') self.paramList.append('inputMacdSlowPeriodLen') self.paramList.append('inputMacdSignalPeriodLen') self.paramList.append('inputKF') self.paramList.append('minDiff') self.paramList.append('shortSymbol') self.paramList.append('activeDayJump') self.paramList.append('name') # 输入参数 self.name = u'LineBar' self.mode = self.TICK_MODE # 缺省为tick模式 self.period = PERIOD_SECOND # 缺省为分钟级别周期 self.barTimeInterval = 300 self.barMinuteInterval = self.barTimeInterval / 60 self.inputPreLen = EMPTY_INT #1 self.inputMa1Len = EMPTY_INT # 10 self.inputMa2Len = EMPTY_INT # 20 self.inputMa3Len = EMPTY_INT # 120 self.inputEma1Len = EMPTY_INT # 13 self.inputEma2Len = EMPTY_INT # 21 self.inputDmiLen = EMPTY_INT # 14 # DMI的计算周期 self.inputDmiMax = EMPTY_FLOAT # 30 # Dpi和Mdi的突破阈值 self.inputAtr1Len = EMPTY_INT # 10 # ATR波动率的计算周期(近端） self.inputAtr2Len = EMPTY_INT # 26 # ATR波动率的计算周期（常用） self.inputAtr3Len = EMPTY_INT # 50 # ATR波动率的计算周期（远端） self.inputVolLen = EMPTY_INT # 14 # 平均交易量的计算周期 self.inputRsi1Len = EMPTY_INT # 7 # RSI 相对强弱指数（快曲线） self.inputRsi2Len = EMPTY_INT # 14 # RSI 相对强弱指数（慢曲线） self.shortSymbol = EMPTY_STRING # 商品的短代码 self.minDiff = 1 # 商品的最小价格单位 self.round_n = 4 # round() 小数点的截断数量 self.activeDayJump = False # 隔夜跳空 # 当前的Tick self.curTick = None self.lastTick = None self.curTradingDay = EMPTY_STRING # K 线服务的策略 self.strategy = strategy # K线保存数据 self.bar = None # K线数据对象 self.lineBar = [] # K线缓存数据队列 self.barFirstTick =False # K线的第一条Tick数据 # K 线的相关计算结果数据 self.preHigh = [] # K线的前inputPreLen的的最高 self.preLow = [] # K线的前inputPreLen的的最低 self.lineMa1 = [] # K线的MA1均线，周期是InputMaLen1，不包含当前bar self.lineMa2 = [] # K线的MA2均线，周期是InputMaLen2，不包含当前bar self.lineMa3 = [] # K线的MA2均线，周期是InputMaLen2，不包含当前bar self.lineEma1 = [] # K线的EMA1均线，周期是InputEmaLen1，不包含当前bar self.lineEma1MtmRate = [] # K线的EMA1均线 的momentum(3) 动能 self.lineEma2 = [] # K线的EMA2均线，周期是InputEmaLen2，不包含当前bar self.lineEma2MtmRate = [] # K线的EMA2均线 的momentum(3) 动能 # K线的DMI( Pdi，Mdi，ADX，Adxr) 计算数据 self.barPdi = EMPTY_FLOAT # bar内的升动向指标，即做多的比率 self.barMdi = EMPTY_FLOAT # bar内的下降动向指标，即做空的比率 self.linePdi = [] # 升动向指标，即做多的比率 self.lineMdi = [] # 下降动向指标，即做空的比率 self.lineDx = [] # 趋向指标列表，最大长度为inputM*2 self.barAdx = EMPTY_FLOAT # Bar内计算的平均趋向指标 self.lineAdx = [] # 平均趋向指标 self.barAdxr = EMPTY_FLOAT # 趋向平均值，为当日ADX值与M日前的ADX值的均值 self.lineAdxr = [] # 平均趋向变化指标 # K线的基于DMI、ADX计算的结果 self.barAdxTrend = EMPTY_FLOAT # ADX值持续高于前一周期时，市场行情将维持原趋势 self.barAdxrTrend = EMPTY_FLOAT # ADXR值持续高于前一周期时,波动率比上一周期高 self.buyFilterCond = False # 多过滤器条件,做多趋势的判断，ADX高于前一天，上升动向> inputMM self.sellFilterCond = False # 空过滤器条件,做空趋势的判断，ADXR高于前一天，下降动向> inputMM # K线的ATR技术数据 self.lineAtr1 = [] # K线的ATR1,周期为inputAtr1Len self.lineAtr2 = [] # K线的ATR2,周期为inputAtr2Len self.lineAtr3 = [] # K线的ATR3,周期为inputAtr3Len self.barAtr1 = EMPTY_FLOAT self.barAtr2 = EMPTY_FLOAT self.barAtr3 = EMPTY_FLOAT # K线的交易量平均 self.lineAvgVol = [] # K 线的交易量平均 # K线的RSI计算数据 self.lineRsi1 = [] # 记录K线对应的RSI数值，只保留inputRsi1Len*8 self.lineRsi2 = [] # 记录K线对应的RSI数值，只保留inputRsi2Len*8 self.lowRsi = 30 # RSI的最低线 self.highRsi = 70 # RSI的最高线 self.lineRsiTop = [] # 记录RSI的最高峰，只保留 inputRsiLen个 self.lineRsiButtom = [] # 记录RSI的最低谷，只保留 inputRsiLen个 self.lastRsiTopButtom = {} # 最近的一个波峰/波谷 # K线的CMI计算数据 self.inputCmiLen = EMPTY_INT self.lineCmi = [] # 记录K线对应的Cmi数值，只保留inputCmiLen*8 # K线的布林特计算数据 self.inputBollLen = EMPTY_INT # K线周期 self.inputBollStdRate = 1.5 # 两倍标准差 self.lineBollClose = [] # 用于运算的close价格列表 self.lineUpperBand = [] # 上轨 self.lineMiddleBand = [] # 中线 self.lineLowerBand = [] # 下轨 self.lineBollStd = [] # 标准差 self.lastBollUpper = EMPTY_FLOAT # 最后一根K的Boll上轨数值（与MinDiff取整） self.lastBollMiddle = EMPTY_FLOAT # 最后一根K的Boll中轨数值（与MinDiff取整） self.lastBollLower = EMPTY_FLOAT # 最后一根K的Boll下轨数值（与MinDiff取整+1） # K线的KDJ指标计算数据 self.inputKdjLen = EMPTY_INT # KDJ指标的长度,缺省是9 self.lineK = [] # K为快速指标 self.lineD = [] # D为慢速指标 self.lineJ = [] # self.lineKdjTop = [] # 记录KDJ最高峰，只保留 inputKdjLen个 self.lineKdjButtom = [] # 记录KDJ的最低谷，只保留 inputKdjLen个 self.lastKdjTopButtom = {} # 最近的一个波峰/波谷 self.lastK = EMPTY_FLOAT # bar内计算时，最后一个未关闭的bar的实时K值 self.lastD = EMPTY_FLOAT # bar内计算时，最后一个未关闭的bar的实时值 self.lastJ = EMPTY_FLOAT # bar内计算时，最后一个未关闭的bar的实时J值 # K线的MACD计算数据 self.inputMacdFastPeriodLen = EMPTY_INT self.inputMacdSlowPeriodLen = EMPTY_INT self.inputMacdSignalPeriodLen = EMPTY_INT self.lineDif = [] # DIF = EMA12 - EMA26，即为talib-MACD返回值macd self.lineDea = [] # DEA = （前一日DEA X 8/10 + 今日DIF X 2/10），即为talib-MACD返回值 self.lineMacd = [] # (dif-dea)*2，但是talib中MACD的计算是bar = (dif-dea)*1,国内一般是乘以2 # K 线的CCI计算数据 self.inputCciLen = EMPTY_INT self.lineCci = [] # 卡尔曼过滤器 self.inputKF = False self.kf = None self.lineStateMean = [] self.lineStateCovar = [] if setting: self.setParam(setting) # 修正精度 if self.minDiff < 1: self.round_n = 7 ## 导入卡尔曼过滤器 if self.inputKF: try: self.kf = KalmanFilter(transition_matrices=[1], observation_matrices=[1], initial_state_mean=0, initial_state_covariance=1, observation_covariance=1, transition_covariance=0.01) except : self.writeCtaLog(u'导入卡尔曼过滤器失败,需先安装 pip install pykalman') self.inputKF = False def setParam(self, setting): """设置参数""" d = self.__dict__ for key in self.paramList: if key in setting: d[key] = setting[key] def setMode(self,mode): """Tick/Bar模式""" self.mode = mode def onTick(self, tick): """行情更新 :type tick: object """ # Tick 有效性检查 #if (tick.datetime- datetime.now()).seconds > 10: # self.writeCtaLog(u'无效的tick时间:{0}'.format(tick.datetime)) # return if tick.datetime.hour == 8 or tick.datetime.hour == 20: self.writeCtaLog(u'竞价排名tick时间:{0}'.format(tick.datetime)) return if self.lastTick is None: self.lastTick = tick self.curTick = tick # 3.生成x K线，若形成新Bar，则触发OnBar事件 self.__drawLineBar(tick) self.lastTick = tick # 4.执行 bar内计算 self.__recountKdj(countInBar=True) def addBar(self,bar): """予以外部初始化程序增加bar""" l1 = len(self.lineBar) if l1 == 0: self.lineBar.append(bar) self.curTradingDay = bar.date self.onBar(bar) return # 与最后一个BAR的时间比对，判断是否超过K线的周期 lastBar = self.lineBar[-1] self.curTradingDay = bar.tradingDay is_new_bar = False if self.period == PERIOD_SECOND and (bar.datetime-lastBar.datetime).seconds >= self.barTimeInterval: is_new_bar = True elif self.period == PERIOD_MINUTE and (bar.datetime - lastBar.datetime).seconds >= self.barTimeInterval*60: is_new_bar = True elif self.period == PERIOD_HOUR: if self.barTimeInterval == 1 and bar.datetime.hour != lastBar.datetime.hour : is_new_bar = True elif self.barTimeInterval == 2 and bar.datetime.hour != lastBar.datetime.hour \ and bar.datetime.hour in {1, 9, 11, 13, 15, 21, 23}: is_new_bar = True elif self.barTimeInterval == 4 and bar.datetime.hour != lastBar.datetime.hour \ and bar.datetime.hour in {1, 9, 13, 21}: is_new_bar = True elif self.period == PERIOD_DAY and bar.datetime.date != lastBar.datetime.date : is_new_bar = True if is_new_bar: # 添加新的bar self.lineBar.append(bar) # 将上一个Bar推送至OnBar事件 self.onBar(lastBar) return # 更新最后一个bar # 此段代码，针对一部分短周期生成长周期的k线更新，如3根5分钟k线，合并成1根15分钟k线。 lastBar.close = bar.close lastBar.high = max(lastBar.high, bar.high) lastBar.low = min(lastBar.low, bar.low) lastBar.volume = lastBar.volume + bar.volume lastBar.dayVolume = bar.dayVolume lastBar.mid4 = round((2*lastBar.close + lastBar.high + lastBar.low)/4, self.round_n) lastBar.mid5 = round((2*lastBar.close + lastBar.open + lastBar.high + lastBar.low)/5, self.round_n) def onBar(self, bar): """OnBar事件""" # 计算相关数据 bar.mid4 = round((2*bar.close + bar.high + bar.low)/4, self.round_n) bar.mid5 = round((2*bar.close + bar.open + bar.high + bar.low)/5, self.round_n) self.__recountPreHighLow() self.__recountMa() self.__recountEma() self.__recountDmi() self.__recountAtr() self.__recoundAvgVol() self.__recountRsi() self.__recountCmi() self.__recountKdj() self.__recountBoll() self.__recountMacd() self.__recountCci() self.__recountKF() # 回调上层调用者 self.onBarFunc(bar) def displayLastBar(self): """显示最后一个Bar的信息""" msg = u'['+self.name+u']' if len(self.lineBar) < 2: return msg if self.mode == self.TICK_MODE: displayBar = self.lineBar[-2] else: displayBar = self.lineBar[-1] msg = msg + u'{0} o:{1};h{2};l:{3};c:{4},v:{5}'.\ format(displayBar.date+' '+displayBar.time, displayBar.open, displayBar.high, displayBar.low, displayBar.close, displayBar.volume) if self.inputMa1Len > 0 and len(self.lineMa1) > 0: msg = msg + u',MA({0}):{1}'.format(self.inputMa1Len, self.lineMa1[-1]) if self.inputMa2Len > 0 and len(self.lineMa2) > 0: msg = msg + u',MA({0}):{1}'.format(self.inputMa2Len, self.lineMa2[-1]) if self.inputMa3Len > 0 and len(self.lineMa3) > 0: msg = msg + u',MA({0}):{1}'.format(self.inputMa3Len, self.lineMa3[-1]) if self.inputEma1Len > 0 and len(self.lineEma1) > 0: msg = msg + u',EMA({0}):{1}'.format(self.inputEma1Len, self.lineEma1[-1]) if self.inputEma2Len > 0 and len(self.lineEma2) > 0: msg = msg + u',EMA({0}):{1}'.format(self.inputEma2Len, self.lineEma2[-1]) if self.inputDmiLen > 0 and len(self.linePdi) > 0: msg = msg + u',Pdi:{1};Mdi:{1};Adx:{2}'.format(self.linePdi[-1], self.lineMdi[-1], self.lineAdx[-1]) if self.inputAtr1Len > 0 and len(self.lineAtr1) > 0: msg = msg + u',Atr({0}):{1}'.format(self.inputAtr1Len, self.lineAtr1[-1]) if self.inputAtr2Len > 0 and len(self.lineAtr2) > 0: msg = msg + u',Atr({0}):{1}'.format(self.inputAtr2Len, self.lineAtr2[-1]) if self.inputAtr3Len > 0 and len(self.lineAtr3) > 0: msg = msg + u',Atr({0}):{1}'.format(self.inputAtr3Len, self.lineAtr3[-1]) if self.inputVolLen > 0 and len(self.lineAvgVol) > 0: msg = msg + u',AvgVol({0}):{1}'.format(self.inputVolLen, self.lineAvgVol[-1]) if self.inputRsi1Len > 0 and len(self.lineRsi1) > 0: msg = msg + u',Rsi({0}):{1}'.format(self.inputRsi1Len, self.lineRsi1[-1]) if self.inputRsi2Len > 0 and len(self.lineRsi2) > 0: msg = msg + u',Rsi({0}):{1}'.format(self.inputRsi2Len, self.lineRsi2[-1]) if self.inputKdjLen > 0 and len(self.lineK) > 0: msg = msg + u',KDJ({0}):{1},{2},{3}'.format(self.inputKdjLen, round(self.lineK[-1], self.round_n), round(self.lineD[-1], self.round_n), round(self.lineJ[-1], self.round_n)) if self.inputCciLen > 0 and len(self.lineCci) > 0: msg = msg + u',Cci({0}):{1}'.format(self.inputCciLen, self.lineCci[-1]) if self.inputBollLen > 0 and len(self.lineUpperBand)>0: msg = msg + u',Boll({0}):u:{1},m:{2},l:{3}'.\ format(self.inputBollLen, round(self.lineUpperBand[-1], self.round_n), round(self.lineMiddleBand[-1], self.round_n), round(self.lineLowerBand[-1]), self.round_n) if self.inputMacdFastPeriodLen >0 and len(self.lineDif)>0: msg = msg + u',MACD({0},{1},{2}):Dif:{3},Dea{4},Macd:{5}'.\ format(self.inputMacdFastPeriodLen, self.inputMacdSlowPeriodLen, self.inputMacdSignalPeriodLen, round(self.lineDif[-1], self.round_n), round(self.lineDea[-1], self.round_n), round(self.lineMacd[-1], self.round_n)) if self.inputKF and len(self.lineKfMa) > 0: msg = msg + u',Kalman:{0}'.format( self.lineKfMa[-1]) return msg def __firstTick(self, tick): """ K线的第一个Tick数据""" self.bar = CtaBarData() # 创建新的K线 # 计算K线的整点分钟周期，这里周期最小是1分钟。如果你是采用非整点分钟，例如1.5分钟，请把这段注解掉 if self.barMinuteInterval and self.period == PERIOD_SECOND: self.barMinuteInterval = int(self.barTimeInterval / 60) if self.barMinuteInterval < 1: self.barMinuteInterval = 1 fixedMin = int( tick.datetime.minute /self.barMinuteInterval) * self.barMinuteInterval tick.datetime = tick.datetime.replace(minute=fixedMin) self.bar.vtSymbol = tick.vtSymbol self.bar.symbol = tick.symbol self.bar.exchange = tick.exchange self.bar.openInterest = tick.openInterest self.bar.open = tick.lastPrice # O L H C self.bar.high = tick.lastPrice self.bar.low = tick.lastPrice self.bar.close = tick.lastPrice self.bar.mid4 = tick.lastPrice # 4价均价 self.bar.mid5 = tick.lastPrice # 5价均价 # K线的日期时间 self.bar.tradingDay = tick.tradingDay # K线所在的交易日期 self.bar.date = tick.date # K线的日期，（夜盘的话，与交易日期不同哦） self.bar.datetime = tick.datetime # K线的日期时间（去除秒）设为第一个Tick的时间 self.bar.datetime = self.bar.datetime.replace(second=0, microsecond=0) self.bar.time = self.bar.datetime.strftime('%H:%M:%S') # K线的日总交易量，k线内交易量 self.bar.dayVolume = tick.volume if self.curTradingDay != self.bar.tradingDay or not self.lineBar: # bar的交易日与记录的当前交易日不一致：即该bar为新的交易日,bar的交易量为当前的tick.volume self.bar.volume = tick.volume self.curTradingDay = self.bar.tradingDay else: # bar的交易日与记录的当前交易日一致, 交易量为tick的volume，减去上一根bar的日总交易量 self.bar.volume = tick.volume - self.lineBar[-1].dayVolume self.barFirstTick = True # 标识该Tick属于该Bar的第一个tick数据 self.lineBar.append(self.bar) # 推入到lineBar队列 # ---------------------------------------------------------------------- def __drawLineBar(self, tick): """生成 line Bar """ l1 = len(self.lineBar) # 保存第一个K线数据 if l1 == 0: self.__firstTick(tick) return # 清除480周期前的数据， if l1 > 60 * 8: del self.lineBar[0] # 与最后一个BAR的时间比对，判断是否超过5分钟 lastBar = self.lineBar[-1] # 处理日内的间隔时段最后一个tick，如10:15分，11:30分，15:00 和 2:30分 endtick = False if (tick.datetime.hour == 10 and tick.datetime.minute == 15) \ or (tick.datetime.hour == 11 and tick.datetime.minute == 30) \ or (tick.datetime.hour == 15 and tick.datetime.minute == 00) \ or (tick.datetime.hour == 2 and tick.datetime.minute == 30): endtick = True # 夜盘1:30收盘 if self.shortSymbol in NIGHT_MARKET_SQ2 and tick.datetime.hour == 1 and tick.datetime.minute == 00: endtick = True # 夜盘23:00收盘 if self.shortSymbol in NIGHT_MARKET_SQ3 and tick.datetime.hour == 23 and tick.datetime.minute == 00: endtick = True # 夜盘23:30收盘 if self.shortSymbol in NIGHT_MARKET_ZZ or self.shortSymbol in NIGHT_MARKET_DL: if tick.datetime.hour == 23 and tick.datetime.minute == 30: endtick = True # 满足时间要求 # 1,秒周期，tick的时间，距离最后一个bar的开始时间，已经超出bar的时间周期（barTimeInterval） # 2，分钟、小时周期，取整=0 # 3、日周期，开盘时间 # 4、不是最后一个结束tick is_new_bar = False if ((self.period == PERIOD_SECOND and (tick.datetime-lastBar.datetime).seconds >= self.barTimeInterval) \ or (self.period == PERIOD_MINUTE and tick.datetime.minute % self.barTimeInterval == 0 and tick.datetime.minute != self.lastTick.datetime.minute) or (self.period == PERIOD_HOUR and self.barTimeInterval == 1 and tick.datetime and tick.datetime.hour != self.lastTick.datetime.hour) or (self.period == PERIOD_HOUR and self.barTimeInterval == 2 and tick.datetime and tick.datetime.hour != self.lastTick.datetime.hour and tick.datetime.hour in {1, 9, 11, 13, 21, 23}) or (self.period == PERIOD_HOUR and self.barTimeInterval == 4 and tick.datetime and tick.datetime.hour != self.lastTick.datetime.hour and tick.datetime.hour in {1, 9, 13, 21}) or (self.period == PERIOD_DAY and tick.datetime and (tick.datetime.hour == 21 or tick.datetime.hour == 9) and 14 <= self.lastTick.datetime.hour <= 15) ) and not endtick: # 创建并推入新的Bar self.__firstTick(tick) # 触发OnBar事件 self.onBar(lastBar) else: # 更新当前最后一个bar self.barFirstTick = False # 更新最高价、最低价、收盘价、成交量 lastBar.high = max(lastBar.high, tick.lastPrice) lastBar.low = min(lastBar.low, tick.lastPrice) lastBar.close = tick.lastPrice # 更新日内总交易量，和bar内交易量 lastBar.dayVolume = tick.volume if l1 == 1: # 针对第一个bar的tick volume更新 lastBar.volume = tick.volume else: # 针对新交易日的第一个bar：于上一个bar的时间在14，当前bar的时间不在14点,初始化为tick.volume if self.lineBar[-2].datetime.hour == 14 and tick.datetime.hour != 14 and not endtick: lastBar.volume = tick.volume else: # 其他情况，bar为同一交易日，将tick的volume，减去上一bar的dayVolume lastBar.volume = tick.volume - self.lineBar[-2].dayVolume # 更新Bar的颜色 if lastBar.close > lastBar.open: lastBar.color = COLOR_RED elif lastBar.close < lastBar.open: lastBar.color = COLOR_BLUE else: lastBar.color = COLOR_EQUAL # ---------------------------------------------------------------------- def __recountPreHighLow(self): """计算 K线的前周期最高和最低""" if self.inputPreLen <= 0: # 不计算 return # 1、lineBar满足长度才执行计算 if len(self.lineBar) < self.inputPreLen: self.writeCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算High、Low需要：{1}'. format(len(self.lineBar), self.inputPreLen)) return # 2.计算前inputPreLen周期内(不包含当前周期）的Bar高点和低点 preHigh = EMPTY_FLOAT preLow = EMPTY_FLOAT if self.mode == self.TICK_MODE: idx = 2 else: idx = 1 for i in range(len(self.lineBar)-idx, len(self.lineBar)-idx-self.inputPreLen, -1): if self.lineBar[i].high > preHigh or preHigh == EMPTY_FLOAT: preHigh = self.lineBar[i].high # 前InputPreLen周期高点 if self.lineBar[i].low < preLow or preLow == EMPTY_FLOAT: preLow = self.lineBar[i].low # 前InputPreLen周期低点 # 保存 if len(self.preHigh) > self.inputPreLen * 8: del self.preHigh[0] self.preHigh.append(preHigh) # 保存 if len(self.preLow)> self.inputPreLen * 8: del self.preLow[0] self.preLow.append(preLow) #---------------------------------------------------------------------- def __recountMa(self): """计算K线的MA1 和MA2""" l = len(self.lineBar) if not (self.inputMa1Len > 0 or self.inputMa2Len > 0 or self.inputMa3Len > 0): # 不计算 return # 1、lineBar满足长度才执行计算 if len(self.lineBar) < max(7, self.inputMa1Len, self.inputMa2Len, self.inputMa3Len)+2: self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算MA需要：{1}'. format(len(self.lineBar), max(7, self.inputMa1Len, self.inputMa2Len, self.inputMa3Len)+2)) return # 计算第一条MA均线 if self.inputMa1Len > 0: if self.inputMa1Len > l: ma1Len = l else: ma1Len = self.inputMa1Len # 3、获取前InputN周期(不包含当前周期）的K线 if self.mode == self.TICK_MODE: listClose=[x.close for x in self.lineBar[-ma1Len - 1:-1]] else: listClose=[x.close for x in self.lineBar[-ma1Len:]] barMa1 = ta.MA(numpy.array(listClose, dtype=float), ma1Len)[-1] barMa1 = round(float(barMa1), self.round_n) if len(self.lineMa1) > self.inputMa1Len*8: del self.lineMa1[0] self.lineMa1.append(barMa1) # 计算第二条MA均线 if self.inputMa2Len > 0: if self.inputMa2Len > l: ma2Len = l else: ma2Len = self.inputMa2Len # 3、获取前InputN周期(不包含当前周期）的K线 if self.mode == self.TICK_MODE: listClose=[x.close for x in self.lineBar[-ma2Len - 1:-1]] else: listClose=[x.close for x in self.lineBar[-ma2Len:]] barMa2 = ta.MA(numpy.array(listClose, dtype=float), ma2Len)[-1] barMa2 = round(float(barMa2), self.round_n) if len(self.lineMa2) > self.inputMa2Len*8: del self.lineMa2[0] self.lineMa2.append(barMa2) # 计算第三条MA均线 if self.inputMa3Len > 0: if self.inputMa3Len > l: ma3Len = l else: ma3Len = self.inputMa3Len # 3、获取前InputN周期(不包含当前周期）的K线 if self.mode == self.TICK_MODE: listClose = [x.close for x in self.lineBar[-ma3Len - 1:-1]] else: listClose = [x.close for x in self.lineBar[-ma3Len:]] barMa3 = ta.MA(numpy.array(listClose, dtype=float), ma3Len)[-1] barMa3 = round(float(barMa3), self.round_n) if len(self.lineMa3) > self.inputMa3Len * 8: del self.lineMa3[0] self.lineMa3.append(barMa3) #---------------------------------------------------------------------- def __recountEma(self): """计算K线的EMA1 和EMA2""" if not (self.inputEma1Len > 0 or self.inputEma2Len >0): # 不计算 return l = len(self.lineBar) # 1、lineBar满足长度才执行计算 if len(self.lineBar) < max(7, self.inputEma1Len, self.inputEma2Len)+2: self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算EMA需要：{1}'. format(len(self.lineBar), max(7, self.inputEma1Len, self.inputEma2Len)+2)) return # 计算第一条EMA均线 if self.inputEma1Len > 0: if self.inputEma1Len > l: ema1Len = l else: ema1Len = self.inputEma1Len # 3、获取前InputN周期(不包含当前周期）的K线 if self.mode == self.TICK_MODE: listClose=[x.close for x in self.lineBar[-ema1Len - 1:-1]] else: listClose=[x.close for x in self.lineBar[-ema1Len:]] barEma1 = ta.EMA(numpy.array(listClose, dtype=float), ema1Len)[-1] barEma1 = round(float(barEma1), self.round_n) if len(self.lineEma1) > self.inputEma1Len*8: del self.lineEma1[0] self.lineEma1.append(barEma1) # 计算第二条EMA均线 if self.inputEma2Len > 0: if self.inputEma2Len > l: ema2Len = l else: ema2Len = self.inputEma2Len # 3、获取前InputN周期(不包含当前周期）的自适应均线 if self.mode == self.TICK_MODE: listClose=[x.close for x in self.lineBar[-ema2Len - 1:-1]] else: listClose=[x.close for x in self.lineBar[-ema2Len:]] barEma2 = ta.EMA(numpy.array(listClose, dtype=float), ema2Len)[-1] barEma2 = round(float(barEma2), self.round_n) if len(self.lineEma2) > self.inputEma1Len*8: del self.lineEma2[0] self.lineEma2.append(barEma2) def __recountDmi(self): """计算K线的DMI数据和条件""" if self.inputDmiLen <= 0: # 不计算 return # 1、lineMx满足长度才执行计算 if len(self.lineBar) < self.inputDmiLen+1: self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算DMI需要：{1}'.format(len(self.lineBar), self.inputDmiLen+1)) return # 2、根据当前High，Low，(不包含当前周期）重新计算TR1，PDM，MDM和ATR barTr1 = EMPTY_FLOAT # 获取InputP周期内的价差最大值之和 barPdm = EMPTY_FLOAT # InputP周期内的做多价差之和 barMdm = EMPTY_FLOAT # InputP周期内的做空价差之和 if self.mode == self.TICK_MODE: idx = 2 else: idx = 1 for i in range(len(self.lineBar)-idx, len(self.lineBar)-idx-self.inputDmiLen, -1): # 周期 inputDmiLen # 3.1、计算TR1 # 当前周期最高与最低的价差 high_low_spread = self.lineBar[i].high - self.lineBar[i].low # 当前周期最高与昨收价的价差 high_preclose_spread = abs(self.lineBar[i].high - self.lineBar[i - 1].close) # 当前周期最低与昨收价的价差 low_preclose_spread = abs(self.lineBar[i].low - self.lineBar[i - 1].close) # 最大价差 max_spread = max(high_low_spread, high_preclose_spread, low_preclose_spread) barTr1 = barTr1 + float(max_spread) # 今高与昨高的价差 high_prehigh_spread = self.lineBar[i].high - self.lineBar[i - 1].high # 昨低与今低的价差 low_prelow_spread = self.lineBar[i - 1].low - self.lineBar[i].low # 3.2、计算周期内的做多价差之和 if high_prehigh_spread > 0 and high_prehigh_spread > low_prelow_spread: barPdm = barPdm + high_prehigh_spread # 3.3、计算周期内的做空价差之和 if low_prelow_spread > 0 and low_prelow_spread > high_prehigh_spread: barMdm = barMdm + low_prelow_spread # 6、计算上升动向指标，即做多的比率 if barTr1 == 0: self.barPdi = 0 else: self.barPdi = barPdm * 100 / barTr1 if len(self.linePdi) > self.inputDmiLen+1: del self.linePdi[0] self.linePdi.append(self.barPdi) # 7、计算下降动向指标，即做空的比率 if barTr1 == 0: self.barMdi = 0 else: self.barMdi = barMdm * 100 / barTr1 # 8、计算平均趋向指标 Adx，Adxr if self.barMdi + self.barPdi == 0: dx = 0 else: dx = 100 * abs(self.barMdi - self.barPdi) / (self.barMdi + self.barPdi) if len(self.lineMdi) > self.inputDmiLen+1: del self.lineMdi[0] self.lineMdi.append(self.barMdi) if len(self.lineDx) > self.inputDmiLen+1: del self.lineDx[0] self.lineDx.append(dx) # 平均趋向指标，MA计算 if len(self.lineDx) < self.inputDmiLen+1: self.barAdx = dx else: self.barAdx = ta.EMA(numpy.array(self.lineDx, dtype=float), self.inputDmiLen)[-1] # 保存Adx值 if len(self.lineAdx) > self.inputDmiLen+1: del self.lineAdx[0] self.lineAdx.append(self.barAdx) # 趋向平均值，为当日ADX值与1周期前的ADX值的均值 if len(self.lineAdx) == 1: self.barAdxr = self.lineAdx[-1] else: self.barAdxr = (self.lineAdx[-1] + self.lineAdx[-2]) / 2 # 保存Adxr值 if len(self.lineAdxr) > self.inputDmiLen+1: del self.lineAdxr[0] self.lineAdxr.append(self.barAdxr) # 7、计算A，ADX值持续高于前一周期时，市场行情将维持原趋势 if len(self.lineAdx) < 2: self.barAdxTrend = False elif self.lineAdx[-1] > self.lineAdx[-2]: self.barAdxTrend = True else: self.barAdxTrend = False # ADXR值持续高于前一周期时,波动率比上一周期高 if len(self.lineAdxr) < 2: self.barAdxrTrend = False elif self.lineAdxr[-1] > self.lineAdxr[-2]: self.barAdxrTrend = True else: self.barAdxrTrend = False # 多过滤器条件,做多趋势，ADX高于前一天，上升动向> inputDmiMax if self.barPdi > self.barMdi and self.barAdxTrend and self.barAdxrTrend and self.barPdi >= self.inputDmiMax: self.buyFilterCond = True self.writeCtaLog(u'{0}[DEBUG]Buy Signal On Bar,Pdi:{1}>Mdi:{2},adx[-1]:{3}>Adx[-2]:{4}' .format(self.curTick.datetime, self.barPdi, self.barMdi, self.lineAdx[-1], self.lineAdx[-2])) else: self.buyFilterCond = False # 空过滤器条件 做空趋势，ADXR高于前一天，下降动向> inputMM if self.barPdi < self.barMdi and self.barAdxTrend and self.barAdxrTrend and self.barMdi >= self.inputDmiMax: self.sellFilterCond = True self.writeCtaLog(u'{0}[DEBUG]Short Signal On Bar,Pdi:{1}Adx[-2]:{4}' .format(self.curTick.datetime, self.barPdi, self.barMdi, self.lineAdx[-1], self.lineAdx[-2])) else: self.sellFilterCond = False def __recountAtr(self): """计算Mx K线的各类数据和条件""" # 1、lineMx满足长度才执行计算 maxAtrLen = max(self.inputAtr1Len, self.inputAtr2Len, self.inputAtr3Len) if maxAtrLen <= 0: # 不计算 return if len(self.lineBar) < maxAtrLen+1: self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算ATR需要：{1}'. format(len(self.lineBar), maxAtrLen+1)) return if self.mode == self.TICK_MODE: idx = 2 else: idx = 1 # 首次计算 if (self.inputAtr1Len > 0 and len(self.lineAtr1) < 1) \ or (self.inputAtr2Len > 0 and len(self.lineAtr2) < 1) \ or (self.inputAtr3Len > 0 and len(self.lineAtr3) < 1): # 根据当前High，Low，(不包含当前周期）重新计算TR1和ATR barTr1 = EMPTY_FLOAT # 获取inputAtr1Len周期内的价差最大值之和 barTr2 = EMPTY_FLOAT # 获取inputAtr2Len周期内的价差最大值之和 barTr3 = EMPTY_FLOAT # 获取inputAtr3Len周期内的价差最大值之和 j = 0 for i in range(len(self.lineBar)-idx, len(self.lineBar)-idx-maxAtrLen, -1): # 周期 inputP # 3.1、计算TR # 当前周期最高与最低的价差 high_low_spread = self.lineBar[i].high - self.lineBar[i].low # 当前周期最高与昨收价的价差 high_preclose_spread = abs(self.lineBar[i].high - self.lineBar[i - 1].close) # 当前周期最低与昨收价的价差 low_preclose_spread = abs(self.lineBar[i].low - self.lineBar[i - 1].close) # 最大价差 max_spread = max(high_low_spread, high_preclose_spread, low_preclose_spread) if j < self.inputAtr1Len: barTr1 = barTr1 + float(max_spread) if j < self.inputAtr2Len: barTr2 = barTr2 + float(max_spread) if j < self.inputAtr3Len: barTr3 = barTr3 + float(max_spread) j = j + 1 else: # 只计算一个 # 当前周期最高与最低的价差 high_low_spread = self.lineBar[0-idx].high - self.lineBar[0-idx].low # 当前周期最高与昨收价的价差 high_preclose_spread = abs(self.lineBar[0-idx].high - self.lineBar[-1-idx].close) # 当前周期最低与昨收价的价差 low_preclose_spread = abs(self.lineBar[0-idx].low - self.lineBar[-1-idx].close) # 最大价差 barTr1 = max(high_low_spread, high_preclose_spread, low_preclose_spread) barTr2 = barTr1 barTr3 = barTr1 # 计算 ATR if self.inputAtr1Len > 0: if len(self.lineAtr1) < 1: self.barAtr1 = round(barTr1 / self.inputAtr1Len, self.round_n) else: self.barAtr1 = round((self.lineAtr1[-1]*(self.inputAtr1Len -1) + barTr1) / self.inputAtr1Len, self.round_n) if len(self.lineAtr1) > self. inputAtr1Len+1 : del self.lineAtr1[0] self.lineAtr1.append(self.barAtr1) if self.inputAtr2Len > 0: if len(self.lineAtr2) < 1: self.barAtr2 = round(barTr2 / self.inputAtr2Len, self.round_n) else: self.barAtr2 = round((self.lineAtr2[-1]*(self.inputAtr2Len -1) + barTr2) / self.inputAtr2Len, self.round_n) if len(self.lineAtr2) > self. inputAtr2Len+1: del self.lineAtr2[0] self.lineAtr2.append(self.barAtr2) if self.inputAtr3Len > 0: if len(self.lineAtr3) < 1: self.barAtr3 = round(barTr3 / self.inputAtr3Len, self.round_n) else: self.barAtr3 = round((self.lineAtr3[-1]*(self.inputAtr3Len -1) + barTr3) / self.inputAtr3Len, self.round_n) if len(self.lineAtr3) > self. inputAtr3Len+1: del self.lineAtr3[0] self.lineAtr3.append(self.barAtr3) #---------------------------------------------------------------------- def __recoundAvgVol(self): """计算平均成交量""" # 1、lineBar满足长度才执行计算 if self.inputVolLen <= 0: # 不计算 return if len(self.lineBar) < self.inputVolLen+1: self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算Avg Vol需要：{1}'. format(len(self.lineBar), self.inputVolLen+1)) return if self.mode == self.TICK_MODE: listVol = [x.volume for x in self.lineBar[-self.inputVolLen-1: -1]] else: listVol = [x.volume for x in self.lineBar[-self.inputVolLen:]] sumVol = ta.SUM(numpy.array(listVol, dtype=float), timeperiod=self.inputVolLen)[-1] avgVol = round(sumVol/self.inputVolLen, 0) self.lineAvgVol.append(avgVol) # ---------------------------------------------------------------------- def __recountRsi(self): """计算K线的RSI""" if self.inputRsi1Len <= 0 and self.inputRsi2Len <= 0: return # 1、lineBar满足长度才执行计算 if len(self.lineBar) < self.inputRsi1Len+2: self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算RSI需要：{1}'. format(len(self.lineBar), self.inputRsi1Len + 2)) return # 计算第1根RSI曲线 # 3、inputRsi1Len(包含当前周期）的相对强弱 if self.mode == self.TICK_MODE: listClose=[x.close for x in self.lineBar[-self.inputRsi1Len - 2:-1]] idx = 2 else: listClose=[x.close for x in self.lineBar[-self.inputRsi1Len-1:]] idx = 1 barRsi = ta.RSI(numpy.array(listClose, dtype=float), self.inputRsi1Len)[-1] barRsi = round(float(barRsi), self.round_n) l = len(self.lineRsi1) if l > self.inputRsi1Len*8: del self.lineRsi1[0] self.lineRsi1.append(barRsi) if l > 3: # 峰 if self.lineRsi1[-1] < self.lineRsi1[-2] and self.lineRsi1[-3] < self.lineRsi1[-2]: t={} t["Type"] = u'T' t["RSI"] = self.lineRsi1[-2] t["Close"] = self.lineBar[-1-idx].close if len(self.lineRsiTop) > self.inputRsi1Len: del self.lineRsiTop[0] self.lineRsiTop.append( t ) self.lastRsiTopButtom = self.lineRsiTop[-1] # 谷 elif self.lineRsi1[-1] > self.lineRsi1[-2] and self.lineRsi1[-3] > self.lineRsi1[-2]: b={} b["Type"] = u'B' b["RSI"] = self.lineRsi1[-2] b["Close"] = self.lineBar[-1-idx].close if len(self.lineRsiButtom) > self.inputRsi1Len: del self.lineRsiButtom[0] self.lineRsiButtom.append(b) self.lastRsiTopButtom = self.lineRsiButtom[-1] # 计算第二根RSI曲线 if self.inputRsi2Len > 0: if len(self.lineBar) < self.inputRsi2Len+2: return if self.mode == self.TICK_MODE: listClose=[x.close for x in self.lineBar[-self.inputRsi2Len - 2:-1]] else: listClose=[x.close for x in self.lineBar[-self.inputRsi2Len - 1:]] barRsi = ta.RSI(numpy.array(listClose, dtype=float), self.inputRsi2Len)[-1] barRsi = round(float(barRsi), self.round_n) l = len(self.lineRsi2) if l > self.inputRsi2Len*8: del self.lineRsi2[0] self.lineRsi2.append(barRsi) def __recountCmi(self): """市场波动指数（Choppy Market Index，CMI）是一个用来判断市场走势类型的技术分析指标。 它通过计算当前收盘价与一定周期前的收盘价的差值与这段时间内价格波动的范围的比值，来判断目前的股价走势是趋势还是盘整。 市场波动指数CMI的计算公式： CMI=(Abs(Close-ref(close,(n-1)))*100/(HHV(high,n)-LLV(low,n)) 其中，Abs是绝对值。 n是周期数，例如３０。 市场波动指数CMI的使用方法： 这个指标的重要用途是来区分目前的股价走势类型：盘整，趋势。当CMI指标小于２０时，市场走势是盘整；当CMI指标大于２０时，市场在趋势期。 CMI指标还可以用于预测股价走势类型的转变。因为物极必反，当CMI长期处于０附近，此时，股价走势很可能从盘整转为趋势；当CMI长期处于１００附近，此时，股价趋势很可能变弱，形成盘整。 """ if self.inputCmiLen <= EMPTY_INT: return # 1、lineBar满足长度才执行计算 if len(self.lineBar) < self.inputCmiLen: self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算CMI需要：{1}'. format(len(self.lineBar), self.inputCmiLen)) return if self.mode == self.TICK_MODE: listClose =[x.close for x in self.lineBar[-self.inputCmiLen-1:-1]] idx = 2 else: listClose =[x.close for x in self.lineBar[-self.inputCmiLen:]] idx = 1 hhv = max(listClose) llv = min(listClose) if hhv==llv: cmi = 100 else: cmi = abs(self.lineBar[0-idx].close-self.lineBar[-1-idx].close)*100/(hhv-llv) cmi = round(cmi, self.round_n) if len(self.lineCmi) > self.inputCmiLen: del self.lineCmi[0] self.lineCmi.append(cmi) def __recountBoll(self): """布林特线""" if self.inputBollLen <= EMPTY_INT: return l = len(self.lineBar) if l < min(14, self.inputBollLen)+1: self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算Boll需要：{1}'. format(len(self.lineBar), min(14, self.inputBollLen)+1)) return if l < self.inputBollLen+2: bollLen = l-1 else: bollLen = self.inputBollLen # 不包含当前最新的Bar if self.mode == self.TICK_MODE: listClose=[x.close for x in self.lineBar[-bollLen - 1:-1]] else: listClose=[x.close for x in self.lineBar[-bollLen :]] # upper, middle, lower = ta.BBANDS(numpy.array(listClose, dtype=float), timeperiod=bollLen, nbdevup=self.inputBollStdRate, nbdevdn=self.inputBollStdRate, matype=0) if len(self.lineUpperBand) > self.inputBollLen*8: del self.lineUpperBand[0] if len(self.lineMiddleBand) > self.inputBollLen*8: del self.lineMiddleBand[0] if len(self.lineLowerBand) > self.inputBollLen*8: del self.lineLowerBand[0] if len(self.lineBollStd) > self.inputBollLen * 8: del self.lineBollStd[0] # 1标准差 std = (upper[-1] - lower[-1]) / (self.inputBollStdRate*2) self.lineBollStd.append(std) u = round(upper[-1], self.round_n) self.lineUpperBand.append(u) # 上轨 self.lastBollUpper = u - u % self.minDiff # 上轨取整 m = round(middle[-1], self.round_n) self.lineMiddleBand.append(m) # 中轨 self.lastBollMiddle = m - m % self.minDiff # 中轨取整 l = round(lower[-1], self.round_n) self.lineLowerBand.append(l) # 下轨 self.lastBollLower = l - l % self.minDiff # 下轨取整 def __recountKdj(self, countInBar = False): """KDJ指标""" """ KDJ指标的中文名称又叫随机指标，是一个超买超卖指标,最早起源于期货市场，由乔治·莱恩（George Lane）首创。 随机指标KDJ最早是以KD指标的形式出现，而KD指标是在威廉指标的基础上发展起来的。 不过KD指标只判断股票的超买超卖的现象，在KDJ指标中则融合了移动平均线速度上的观念，形成比较准确的买卖信号依据。在实践中，K线与D线配合J线组成KDJ指标来使用。 KDJ指标在设计过程中主要是研究最高价、最低价和收盘价之间的关系，同时也融合了动量观念、强弱指标和移动平均线的一些优点。 因此，能够比较迅速、快捷、直观地研判行情，被广泛用于股市的中短期趋势分析，是期货和股票市场上最常用的技术分析工具。   第一步 计算RSV：即未成熟随机值（Raw Stochastic Value）。 RSV 指标主要用来分析市场是处于“超买”还是“超卖”状态： - RSV高于80%时候市场即为超买状况，行情即将见顶，应当考虑出仓； - RSV低于20%时候，市场为超卖状况，行情即将见底，此时可以考虑加仓。     N日RSV=(N日收盘价-N日内最低价）÷(N日内最高价-N日内最低价）×100%     第二步 计算K值：当日K值 = 2/3前1日K值 + 1/3当日RSV ;      第三步 计算D值：当日D值 = 2/3前1日D值 + 1/3当日K值；      第四步 计算J值：当日J值 = 3当日K值 - 2当日D值.  """ if self.inputKdjLen <= EMPTY_INT: return if len(self.lineBar) < self.inputKdjLen+1: if not countInBar: 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)) return # 数据是Tick模式，非bar内计算 if self.mode == self.TICK_MODE and not countInBar: listClose =[x.close for x in self.lineBar[-self.inputKdjLen-1:-1]] listHigh = [x.high for x in self.lineBar[-self.inputKdjLen - 1:-1]] listLow = [x.low for x in self.lineBar[-self.inputKdjLen - 1:-1]] idx = 2 else: listClose =[x.close for x in self.lineBar[-self.inputKdjLen:]] listHigh = [x.high for x in self.lineBar[-self.inputKdjLen :]] listLow = [x.low for x in self.lineBar[-self.inputKdjLen :]] idx = 1 hhv = max(listHigh) llv = min(listLow) if len(self.lineK) > 0: lastK = self.lineK[-1] else: lastK = 0 if len(self.lineD) > 0: lastD = self.lineD[-1] else: lastD = 0 if hhv == llv: rsv = 50 else: rsv = (self.lineBar[-1].close - llv)/(hhv - llv) * 100 k = 2*lastK/3 + rsv/3 if k < 0: k = 0 if k > 100: k = 100 d = 2*lastD/3 + k/3 if d < 0: d = 0 if d > 100: d = 100 j = 3*k - 2*d if countInBar: self.lastD = d self.lastK = k self.lastJ = j return if len(self.lineK) > self.inputKdjLen * 8: del self.lineK[0] self.lineK.append(k) if len(self.lineD) > self.inputKdjLen * 8: del self.lineD[0] self.lineD.append(d) l = len(self.lineJ) if l > self.inputKdjLen * 8: del self.lineJ[0] self.lineJ.append(j) #增加KDJ的J谷顶和波底 if l > 3: # 峰 if self.lineJ[-1] < self.lineJ[-2] and self.lineJ[-3] <= self.lineJ[-2]: t={} t["Type"] = u'T' t["J"] = self.lineJ[-2] t["Close"] = self.lineBar[-1-idx].close if len(self.lineKdjTop) > self.inputKdjLen: del self.lineKdjTop[0] self.lineKdjTop.append( t ) self.lastKdjTopButtom = self.lineKdjTop[-1] # 谷 elif self.lineJ[-1] > self.lineJ[-2] and self.lineJ[-3] >= self.lineJ[-2]: b={} b["Type"] = u'B' b["J"] = self.lineJ[-2] b["Close"] = self.lineBar[-1-idx].close if len(self.lineKdjButtom) > self.inputKdjLen: del self.lineKdjButtom[0] self.lineKdjButtom.append(b) self.lastKdjTopButtom = self.lineKdjButtom[-1] def __recountMacd(self): """ Macd计算方法： 12日EMA的计算：EMA12 = 前一日EMA12 X 11/13 + 今日收盘 X 2/13 26日EMA的计算：EMA26 = 前一日EMA26 X 25/27 + 今日收盘 X 2/27 差离值（DIF）的计算： DIF = EMA12 - EMA26，即为talib-MACD返回值macd 根据差离值计算其9日的EMA，即离差平均值，是所求的DEA值。 今日DEA = （前一日DEA X 8/10 + 今日DIF X 2/10），即为talib-MACD返回值signal 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。 但是talib中MACD的计算是bar = (dif-dea)*1 """ if self.inputMacdFastPeriodLen <= EMPTY_INT: return if self.inputMacdSlowPeriodLen <= EMPTY_INT: return if self.inputMacdSignalPeriodLen <= EMPTY_INT: return maxLen = max(self.inputMacdFastPeriodLen,self.inputMacdSlowPeriodLen)+self.inputMacdSignalPeriodLen+1 #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 if len(self.lineBar) < maxLen: 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)) return if self.mode == self.TICK_MODE: listClose =[x.close for x in self.lineBar[-maxLen:-1]] else: listClose =[x.close for x in self.lineBar[-maxLen-1:]] 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] self.lineDif.append(dif[-1]) if len(self.lineDea) > maxLen: del self.lineDea[0] self.lineDea.append(dea[-1]) if len(self.lineMacd) > maxLen: del self.lineMacd[0] self.lineMacd.append(macd[-1]*2) # 国内一般是2倍 def __recountCci(self): """CCI计算 顺势指标又叫CCI指标，CCI指标是美国股市技术分析 家唐纳德·蓝伯特(Donald Lambert)于20世纪80年代提出的，专门测量股价、外汇或者贵金属交易 是否已超出常态分布范围。属于超买超卖类指标中较特殊的一种。波动于正无穷大和负无穷大之间。但是，又不需要以0为中轴线，这一点也和波动于正无穷大 和负无穷大的指标不同。 它最早是用于期货市场的判断，后运用于股票市场的研判，并被广泛使用。与大多数单一利用股票的收盘价、开盘价、最高价或最低价而发明出的各种技术分析 指标不同，CCI指标是根据统计学原理，引进价格与固定期间的股价平均区间的偏离程度的概念，强调股价平均绝对偏差在股市技术分析中的重要性，是一种比 较独特的技术指标。 它与其他超买超卖型指标又有自己比较独特之处。象KDJ、W%R等大多数超买超卖型指标都有“0-100”上下界限，因此，它们对待一般常态行情的研判比较适用 ，而对于那些短期内暴涨暴跌的股票的价格走势时，就可能会发生指标钝化的现象。而CCI指标却是波动于正无穷大到负无穷大之间，因此不会出现指标钝化现 象，这样就有利于投资者更好地研判行情，特别是那些短期内暴涨暴跌的非常态行情。 http://baike.baidu.com/view/53690.htm?fromtitle=CCI%E6%8C%87%E6%A0%87&fromid=4316895&type=syn """ if self.inputCciLen <= 0: return # 1、lineBar满足长度才执行计算 if len(self.lineBar) < self.inputCciLen+2: self.debugCtaLog(u'数据未充分,当前Bar数据数量：{0}，计算CCI需要：{1}'. format(len(self.lineBar), self.inputCciLen + 2)) return # 计算第1根RSI曲线 # 3、inputCc1Len(包含当前周期） if self.mode == self.TICK_MODE: listClose = [x.close for x in self.lineBar[-self.inputCciLen - 2:-1]] listHigh = [x.high for x in self.lineBar[-self.inputCciLen - 2:-1]] listLow = [x.low for x in self.lineBar[-self.inputCciLen - 2:-1]] idx = 2 else: listClose = [x.close for x in self.lineBar[-self.inputCciLen-1:]] listHigh = [x.high for x in self.lineBar[-self.inputCciLen - 1:]] listLow = [x.low for x in self.lineBar[-self.inputCciLen - 1:]] idx = 1 barCci = ta.CCI(high=numpy.array(listHigh, dtype=float), low=numpy.array(listLow, dtype=float), close=numpy.array(listClose, dtype=float), timeperiod=self.inputCciLen)[-1] barCci = round(float(barCci), 3) l = len(self.lineCci) if l > self.inputCciLen*8: del self.lineCci[0] self.lineCci.append(barCci) def __recountKF(self): """计算卡尔曼过滤器均线""" min_len = 20 if not self.inputKF or self.kf is None: return if len(self.lineBar) < min_len: # 数量不足时，不做滤波处理，直接吻合（若改为EMA更好） if self.mode == self.TICK_MODE and len(self.lineBar)>1: self.lineStateMean.append(self.lineBar[-2].close) else: self.lineStateMean.append(self.lineBar[-1].close) return if len(self.lineStateMean) ==0 or len(self.lineStateCovar) ==0: # 3、获取前InputN周期(不包含当前周期）的K线 if self.mode == self.TICK_MODE: listClose = [x.close for x in self.lineBar[-min_len - 1:-1]] else: listClose = [x.close for x in self.lineBar[-min_len:]] state_means, state_covariances = self.kf.filter(numpy.array(listClose, dtype=float)) m = state_means[-1].item() c = state_covariances[-1].item() else: m = self.lineStateMean[-1] c = self.lineStateCovar[-1] if self.mode == self.TICK_MODE: o = self.lineBar[-2].close else: o = self.lineBar[-1].close state_means, state_covariances = self.kf.filter_update(filtered_state_mean=m, filtered_state_covariance=c, observation=numpy.array(o, dtype=float)) m = state_means[-1].item() c = state_covariances[-1].item() if len(self.lineStateMean) > min_len: del self.lineStateMean[0] if len(self.lineStateCovar) > min_len: del self.lineStateCovar[0] self.lineStateMean.append(m) self.lineStateCovar.append(c) # ---------------------------------------------------------------------- def writeCtaLog(self, content): """记录CTA日志""" self.strategy.writeCtaLog(u'['+self.name+u']'+content) def debugCtaLog(self,content): """记录CTA日志""" if DEBUGCTALOG: self.strategy.writeCtaLog(u'['+self.name+u'-DEBUG]'+content) class CtaDayBar(object): """日线""" # 区别： # -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]。 # -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 TICK_MODE = 'tick' BAR_MODE = 'bar' # 参数列表，保存了参数的名称 paramList = ['vtSymbol'] def __init__(self, strategy, onBarFunc, setting=None, ): self.paramList.append('inputPreLen') self.paramList.append('minDiff') self.paramList.append('shortSymbol') self.paramList.append('name') # 输入参数 self.name = u'DayBar' self.mode = self.TICK_MODE self.inputPreLen = EMPTY_INT # 1 # OnBar事件回调函数 self.onBarFunc = onBarFunc self.lineBar = [] self.currTick = None self.lastTick = None self.shortSymbol = EMPTY_STRING # 商品的短代码 self.minDiff = 1 # 商品的最小价格单位 def onTick(self, tick): """行情更新""" if self.currTick is None: self.currTick = tick self.__drawLineBar(tick) self.lastTick = tick def addBar(self, bar): """予以外部初始化程序增加bar""" l1 = len(self.lineBar) if l1 == 0: bar.datetme = bar.datetime.replace(minute=0, second=0) bar.time = bar.datetime.strftime('%H:%M:%S') self.lineBar.append(bar) return # 与最后一个BAR的时间比对，判断是否超过K线的周期 lastBar = self.lineBar[-1] if bar.tradingDay != lastBar.datetime: bar.datetme = bar.datetime.replace(minute=0, second=0) bar.time = bar.datetime.strftime('%H:%M:%S') self.lineBar.append(bar) self.onBar(lastBar) return # 更新最后一个bar # 此段代码，针对一部分短周期生成长周期的k线更新，如3根5分钟k线，合并成1根15分钟k线。 lastBar.close = bar.close lastBar.high = max(lastBar.high, bar.high) lastBar.low = min(lastBar.low, bar.low) lastBar.mid4 = round((2 * lastBar.close + lastBar.high + lastBar.low) / 4, self.round_n) lastBar.mid5 = round((2 * lastBar.close + lastBar.open + lastBar.high + lastBar.low) / 5, self.round_n) def __firstTick(self, tick): """ K线的第一个Tick数据""" self.bar = CtaBarData() # 创建新的K线 self.bar.vtSymbol = tick.vtSymbol self.bar.symbol = tick.symbol self.bar.exchange = tick.exchange self.bar.openInterest = tick.openInterest self.bar.open = tick.lastPrice # O L H C self.bar.high = tick.lastPrice self.bar.low = tick.lastPrice self.bar.close = tick.lastPrice # K线的日期时间 self.bar.tradingDay = tick.tradingDay # K线所在的交易日期 self.bar.date = tick.date # K线的日期，（夜盘的话，与交易日期不同哦） self.bar.datetime = tick.datetime # K线的日期时间（去除分钟、秒）设为第一个Tick的时间 self.bar.datetime = self.bar.datetime.replace(minute=0, second=0, microsecond=0) self.bar.time = self.bar.datetime.strftime('%H:%M:%S') self.barFirstTick = True # 标识该Tick属于该Bar的第一个tick数据 self.lineBar.append(self.bar) # 推入到lineBar队列 # ---------------------------------------------------------------------- def __drawLineBar(self, tick): """生成 line Bar """ l1 = len(self.lineBar) # 保存第一个K线数据 if l1 == 0: self.__firstTick(tick) return # 清除480周期前的数据， if l1 > 60 * 8: del self.lineBar[0] # 与最后一个BAR的时间比对，判断是否超过5分钟 lastBar = self.lineBar[-1] # 处理日内的间隔时段最后一个tick，如10:15分，11:30分，15:00 和 2:30分 endtick = False if (tick.datetime.hour == 10 and tick.datetime.minute == 15) \ or (tick.datetime.hour == 11 and tick.datetime.minute == 30) \ or (tick.datetime.hour == 15 and tick.datetime.minute == 00) \ or (tick.datetime.hour == 2 and tick.datetime.minute == 30): endtick = True # 夜盘1:30收盘 if self.shortSymbol in NIGHT_MARKET_SQ2 and tick.datetime.hour == 1 and tick.datetime.minute == 00: endtick = True # 夜盘23:00收盘 if self.shortSymbol in NIGHT_MARKET_SQ3 and tick.datetime.hour == 23 and tick.datetime.minute == 00: endtick = True # 夜盘23:30收盘 if self.shortSymbol in NIGHT_MARKET_ZZ or self.shortSymbol in NIGHT_MARKET_DL: if tick.datetime.hour == 23 and tick.datetime.minute == 30: endtick = True # 满足时间要求,tick的时间(夜盘21点；或者日盘9点，上一个tick为日盘收盘时间 if (tick.datetime.hour == 21 or tick.datetime.hour == 9 ) and 14 <= self.lastTick.datetime.hour <= 15: # 创建并推入新的Bar self.__firstTick(tick) # 触发OnBar事件 self.onBar(lastBar) else: # 更新当前最后一个bar self.barFirstTick = False # 更新最高价、最低价、收盘价、成交量 lastBar.high = max(lastBar.high, tick.lastPrice) lastBar.low = min(lastBar.low, tick.lastPrice) lastBar.close = tick.lastPrice # 更新Bar的颜色 if lastBar.close > lastBar.open: lastBar.color = COLOR_RED elif lastBar.close < lastBar.open: lastBar.color = COLOR_BLUE else: lastBar.color = COLOR_EQUAL def displayLastBar(self): """显示最后一个Bar的信息""" msg = u'[' + self.name + u']' if len(self.lineBar) < 2: return msg if self.mode == self.TICK_MODE: displayBar = self.lineBar[-2] else: displayBar = self.lineBar[-1] msg = msg + u'{0} o:{1};h{2};l:{3};c:{4}'. \ format(displayBar.date + ' ' + displayBar.time, displayBar.open, displayBar.high, displayBar.low, displayBar.close) return msg def onBar(self, bar): """OnBar事件""" self.__recountPreHighLow() # 回调上层调用者 self.onBarFunc(bar) # ---------------------------------------------------------------------- def __recountPreHighLow(self): """计算 K线的前周期最高和最低""" if self.inputPreLen <= 0: return # 不计算 # 1、lineBar满足长度才执行计算 if len(self.lineBar) < self.inputPreLen: self.writeCtaLog(u'数据未充分,当前{0}r数据数量：{1}，计算High、Low需要：{2}'. format(self.name, len(self.lineBar), self.inputPreLen)) return # 2.计算前inputPreLen周期内(不包含当前周期）的Bar高点和低点 preHigh = EMPTY_FLOAT preLow = EMPTY_FLOAT if self.mode == self.TICK_MODE: idx = 2 else: idx = 1 for i in range(len(self.lineBar)-idx, len(self.lineBar)-idx-self.inputPreLen, -1): if self.lineBar[i].high > preHigh or preHigh == EMPTY_FLOAT: preHigh = self.lineBar[i].high # 前InputPreLen周期高点 if self.lineBar[i].low < preLow or preLow == EMPTY_FLOAT: preLow = self.lineBar[i].low # 前InputPreLen周期低点 # 保存 if len(self.preHigh) > self.inputPreLen * 8: del self.preHigh[0] self.preHigh.append(preHigh) # 保存 if len(self.preLow)> self.inputPreLen * 8: del self.preLow[0] self.preLow.append(preLow)