def orderAdd_Updata(form, orderType):
#记录账单
pManager = gol._Get_Setting('manageBills', None)
pBills = pManager[orderType]
billInfo = pBills.OnCreat_BillInfo()
billInfo['usrID'] = form.orderUsrName.data
billInfo['usrBillType'] = "卖出"
billInfo['recordTime'] = datetime.datetime.now()
billInfo['recorder'] = form.recorderName.data
billInfo['tradeID'] = ""
billInfo['tradeID_Relation'] = ""
billInfo['tradeParty'] = form.orderUsrName.data
billInfo['tradeType'] = orderType
billInfo['tradeTypeTarget'] = form.orderTargetType.data
billInfo['tradeTarget'] = form.orderTarget.data
billInfo['tradePrice'] = myData_Trans.To_Float(
form.orderPrice.data.split(' ')[0].replace('￥', ''))
billInfo['tradeNum'] = myData_Trans.To_Float(
form.orderNum.data.split(' ')[0])
billInfo['tradeMoney'] = myData_Trans.To_Float(
form.orderMoney.data.replace('￥', ''))
billInfo['tradePoundage'] = 0
billInfo['tradeProfit'] = billInfo['tradeMoney']
billInfo['tradeTime'] = datetime.datetime.now()
billInfo['isDel'] = False
billInfo['remark'] = form.orderRemark.data
return pBills.Add_ByDict(billInfo)
def InitBystr(self, strSet, typeTime):
self.values = []
self.typeTime = typeTime
if(strSet == "*"):
self.allVlid = True
return
#多个配置
if(strSet.count(",") > 0):
values = strSet.split(',')
for x in values:
pSet = myTimeSets.myTimeSet(x, typeTime)
self.setTimes.append(pSet)
#self.values.append(myData_Trans.To_Int(x))
return
#区间配置
if(strSet.count("-") > 0):
temps = strSet.split('-')
self.minTime = myData_Trans.To_Float(temps[0])
self.maxTime = myData_Trans.To_Float(temps[1])
#self.values = range(myData_Trans.To_Int(temps[0]), myData_Trans.To_Int(temps[1]))
return
else:
if(strSet.count(".") > 0):
self.values.append(myData_Trans.To_Float(strSet))
else:
self.values.append(myData_Trans.To_Int(strSet))
def initWind(self, direction, speed, higth=0, startTime="", duration=-1):
self.wind_Speed = myData_Trans.To_Float(str(speed))
self.wind_Direction = self.initWind_Direction(direction)
self.wind_Direction2 = 90 - self.wind_Direction
if (self.wind_Direction2 < 0): self.wind_Direction2 += 360
self.wind_Height = myData_Trans.To_Float(str(higth))
self.wind_Tiem_start = startTime
if (type(self.wind_Tiem_start) == str):
self.wind_Tiem_start = myData_Trans.Tran_ToDatetime(startTime)
self.wind_Tiem_duration = duration
def _Trans_Value(self, value, utype):
if(utype == "string"):
return str(value)
elif(utype == "float"):
if(type(value) == float): return value
if(type(value) == int): return value
return myData_Trans.To_Float(value)
elif(utype == "int"):
if(type(value) == int): return value
return myData_Trans.To_Int(value)
elif(utype == "bool"):
if(type(value) == bool): return value
return myData_Trans.To_Bool(value)
elif(utype == "datetime"):
if(type(value) == datetime.datetime): return value
return self._Trans_Value_Datetime(value)
elif(utype == "list"):
if(type(value) == list): return value
if(value == None): return []
if(value.count("~*^") > 0):
data = list(json.loads(value.replace("~*^", ",")))
return data
else:
return []
return value
def get(self):
#提取股票信息
pMsg = copy.deepcopy(gol._Get_Setting('Return_strFormat', {}))
pRisks = gol._Get_Value('zxcRisk_Control', None)
bResult = True
# 组装参数并添加
#dicParam = {"边界限制": True,"定量监测": False, "监测间隔": 0.01,"止盈线": 0.20, "止损线": -0.05, "动态止盈": True, "动态止损": True, "止盈回撤": 0.01, "止盈比例": 0.20, "止损回撤": 0.01, "止损比例": 0.20 }
usrID = request.args.get('usrID', '')
usrTag = request.args.get('usrTag', '')
code_id = request.args.get('code_id', "")
code_name = request.args.get('code_name', "")
removeSet = myData_Trans.To_Bool(request.args.get('removeSet', False))
paramInfo = myData_Trans.Tran_ToDict(request.args.get('setInfo', "{}"))
paramInfo['removeSet'] = removeSet
dtTrade = request.args.get('time', "")
dateTag = request.args.get('dateTag', "")
stockPrice = myData_Trans.To_Float(
str(request.args.get('stockPrice', 0)))
stockNum = myData_Trans.To_Int(str(request.args.get('stockNum', 0)))
if (removeSet == False and (stockPrice == 0 or stockNum == 0)):
bResult = False
pMsg['text'] = "股价、数量不能为0."
if (usrID == "" and usrTag == ""):
bResult = False
pMsg['text'] = "用户信息不能为空."
if (bResult):
strR = pRisks.addRiskSet(usrID, usrTag, code_id, code_name,
stockPrice, stockNum, dtTrade, dateTag,
paramInfo)
#解析参数
strTag = "风控设置：" + code_name + "\n"
if (bResult):
if (removeSet == False):
if (stockPrice == 0 or stockNum == 0):
pMsg['text'] = strTag + " --已成功修改参数信息."
else:
trade = myData.iif(stockNum > 0, "买入", "卖出")
if (stockNum % 100 == 0):
pMsg[
'text'] = strTag + F"新增{trade}：{str(abs(stockNum))} 股.\n{trade}均价：{stockPrice} 元/股)."
else:
pMsg[
'text'] = strTag + F"新增{trade}：{str(abs(stockNum))} 张.\n{trade}均价：{stockPrice} 元/张."
bResult = True
else:
pMsg['text'] = strTag + " --设置已成功移除."
bResult = True
pMsg['result'] = bResult
if (bResult == ""): pMsg['text'] = strTag + "操作失败！"
return pMsg
def newData_ByInfo(self, dataInfo, checkTime=True):
#解析所有返回数据
if len(dataInfo) > 50:
stkid = dataInfo[11:19]
info = dataInfo[21:len(dataInfo) - 2]
vargs = info.split(',')
qd = self.newData()
qd.id = stkid[2:]
qd.idTag = stkid
qd.rawline = info
qd.name = vargs[0]
qd.openPrice = vargs[1]
qd.preClose = vargs[2]
qd.lastPrice = vargs[3]
qd.highPrice = vargs[4]
qd.lowPrice = vargs[5]
qd.buyPrice = vargs[6]
qd.sellPrice = vargs[7]
qd.tradeValume = vargs[8]
qd.tradeTurnover = vargs[9]
qd.buy1Volume = vargs[10]
qd.buy1Price = vargs[11]
qd.buy2Volume = vargs[12]
qd.buy2Price = vargs[13]
qd.buy3Volume = vargs[14]
qd.buy3Price = vargs[15]
qd.buy4Volume = vargs[16]
qd.buy4Price = vargs[17]
qd.buy5Volume = vargs[18]
qd.buy5Price = vargs[19]
qd.sell1Volume = vargs[20]
qd.sell1Price = vargs[21]
qd.sell2Volume = vargs[22]
qd.sell2Price = vargs[23]
qd.sell3Volume = vargs[24]
qd.sell3Price = vargs[25]
qd.sell4Volume = vargs[26]
qd.sell4Price = vargs[27]
qd.sell5Volume = vargs[28]
qd.sell5Price = vargs[29]
qd.date = vargs[30]
qd.time = vargs[31]
#时间检查(是否当天)
if (checkTime):
if (qd.checkTime() == False):
return None
#设置数据
qd.value = myData_Trans.To_Float(qd.lastPrice)
return qd
return None
def fromValueList(self, lstValue):
self.dataList = lstValue
dtNow = lstValue[0]
if(type(dtNow) == str): dtNow = myData_Trans.Tran_ToDatetime(dtNow)
self.date = str(dtNow.year) + "-" + str(dtNow.month) + "-" + str(dtNow.day)
self.time = str(dtNow.hour) + ":" + str(dtNow.minute) + ":" + str(dtNow.second)
self.lastPrice = str(lstValue[1])
self.highPrice = str(lstValue[2])
self.lowPrice = str(lstValue[3])
self.buyPrice = str(lstValue[4])
self.sellPrice = str(lstValue[5])
self.tradeValume = str(lstValue[6])
self.tradeTurnover = str(lstValue[7])
self.buy1Volume = str(lstValue[8]) #买1-5量
self.buy2Volume = str(lstValue[9])
self.buy3Volume = str(lstValue[10])
self.buy4Volume = str(lstValue[11])
self.buy5Volume = str(lstValue[12])
self.buy1Price = str(lstValue[13]) #买1-5价格
self.buy2Price = str(lstValue[14])
self.buy3Price = str(lstValue[15])
self.buy4Price = str(lstValue[16])
self.buy5Price = str(lstValue[17])
self.sell1Volume = str(lstValue[18]) #卖1-5量
self.sell2Volume = str(lstValue[19])
self.sell3Volume = str(lstValue[20])
self.sell4Volume = str(lstValue[21])
self.sell5Volume = str(lstValue[22])
self.sell1Price = str(lstValue[23])
self.sell2Price = str(lstValue[24])
self.sell3Price = str(lstValue[25])
self.sell4Price = str(lstValue[26])
self.sell5Price = str(lstValue[27])
self.priceOpen = myData_Trans.To_Float(self.openPrice) #开盘价格
self.priceBase = myData_Trans.To_Float(self.preClose) #前一收盘价格
return True
def _getH_delta(self):
if (self.hasChimney == False): return 0
# 参数提取
T0 = self.air.temperature
T1 = myData_Trans.To_Float(str(self.chimney_temperature_outlet))
Vs = myData_Trans.To_Float(str(self.chimney_smoke_speed_outlet))
D = myData_Trans.To_Float(str(self.chimney_diameter))
U = myData_Trans.To_Float(str(self.chimney_wind_speed_outlet))
if (self.chimney_wind_speed_outlet == ""):
U = self.wind.getWind_Speed(self.height_Leak, self.air)
# 计算烟气热释放率，KJ/s
Pa = 1010
h = Vs * 1
r = D / 2
Qv = math.pi * r * r * h
T_delta = T1 - T0
Qh = 0.35 * Pa * Qv * T_delta / (T1 + 273.15)
# 计算烟气抬升高度
if (Qh > 2100 or T_delta > 35):
Hs = myData.iif(self.height_Leak > 240, 240, self.height_Leak)
if (Qh > 21000):
H_delta = 1.303 * math.pow(Qh, 1 / 3) * math.pow(Hs, 2 / 3) / U
else:
H_delta = 0.292 * math.pow(Qh, 3 / 5) * math.pow(Hs, 2 / 5) / U
elif (Qh < 2100 and Qh > 1700):
Hs = myData.iif(self.height_Leak > 240, 240, self.height_Leak)
H1_delta = 2 * (1.5 * Vs * D + 0.01 * Qh) / U - 0.048 * (Qh -
1700) / U
H2_delta = 0.292 * math.pow(Qh, 3 / 5) * math.pow(Hs, 2 / 5) / U
H_delta = H1_delta + (H2_delta - H1_delta) * (Qh - 1700) / 400
elif (Qh < 1700 or T_delta < 35):
H_delta = 2 * (1.5 * Vs * D + 0.01 * Qh) / U
return H_delta
def Trans_FromDict(self, dictSets, canLog = True):
#验证股票信息
#pStocks = gol._Get_Value('setsStock', None)
#lstStock = pStocks._Find(dictSets.get('标的编号',""), dictSets.get('标的名称',""), exType="")
#if(len(lstStock) != 1): return{}
#pStock = lstStock[0]
#self.stockID = pStock.code_id
#self.stockName = pStock.code_name
#交易信息必须存在
if(dictSets == None): return False
index = -1
strTime = dictSets.get('日期', "")
if(type(strTime) != str): strTime = myData_Trans.Tran_ToDatetime_str(dictSets['日期'], "%Y-%m-%d %H:%M:%S")
for x in self.logOperates:
if(x['时间'] == strTime):
index += 1
break
#解析信息
self.ID = dictSets.get('ID',-1)
self.usrID = dictSets['用户名']
self.stockID = dictSets.get('标的编号',"")
self.stockName = dictSets.get('标的名称',"")
stockNum_temp = myData_Trans.To_Float(str(dictSets.get("标的数量", 0)))
stockAvg_temp = myData_Trans.To_Float(str(dictSets.get("标的均价", 0)))
stockPosition_temp = myData_Trans.To_Float(str(dictSets.get("标的仓位", 1)))
if(stockNum_temp == 0 or stockNum_temp == 0): return False
self.datetime = dictSets.get("日期", self.datetime)
self.remark = dictSets.get("备注", self.remark)
self.isDel = not dictSets.get('isDel', not self.valid)
if(canLog):
#提取时间
strTime = self.datetime
if(type(strTime) != str): strTime = myData_Trans.Tran_ToDatetime_str(strTime, "%Y-%m-%d %H:%M:%S")
#存在则更新
if(index == -1):
self.logOperates.append({"股数": stockNum_temp,"股价":stockAvg_temp,"时间": strTime}) #仓位变化记录
else:
self.logOperates[index] = {"股数": stockNum_temp,"股价":stockAvg_temp,"时间": strTime}
else:
self.logOperates = dictSets.get('操作日志', self.logOperates)
#计算仓位变化
if(index == -1):
stockNum = self.stockNum
if(stockNum_temp > 0):
#买入时更新成本
stockNum += abs(stockNum_temp)
stockMoney = self.stockAvg * self.stockNum + stockNum_temp * stockAvg_temp
self.stockPosition = (stockNum_temp * stockPosition_temp + self.stockNum * self.stockPosition) / stockNum
self.stockAvg = stockMoney / stockNum
self.stockNum = int(stockNum)
else:
#卖出更新仓位
self.stockPosition = (stockNum_temp * stockPosition_temp + self.stockNum * self.stockPosition) / stockNum
if(self.stockPosition <= 0):
self.stockPosition = 0
self.valid = False
self.stockFee = dictSets.get("手续费率", self.stockFee)
self.stopProfit = dictSets.get("止盈线", self.stopProfit)
self.stopLoss = dictSets.get("止损线", self.stopLoss)
self.stopProfit_Dynamic = dictSets.get("动态止盈", self.stopProfit_Dynamic)
self.stopLoss_Dynamic = dictSets.get("动态止损", self.stopLoss_Dynamic)
self.stopProfit_Retreat = dictSets.get("止盈回撤", self.stopProfit_Retreat)
self.stopLoss_Retreat = dictSets.get("止损回撤", self.stopLoss_Retreat)
self.stopProfit_Trade = dictSets.get("止盈比例", self.stopProfit_Trade)
self.stopLoss_Trade = dictSets.get("止损比例", self.stopLoss_Trade)
self.priceMax = dictSets.get("最高价格", self.priceMax)
self.priceCost = dictSets.get("成本价格", self.stockAvg)
self.priceAvg_sell = dictSets.get("卖出均价", stockAvg_temp)
self.priceNow = dictSets.get("当前价格", stockAvg_temp)
self.profitMax_Stage = dictSets.get("阶段浮盈", self.profitMax_Stage)
self.profitNow = dictSets.get("当前浮盈", self.profitNow)
self.stopProfit_goon = dictSets.get("止盈状态", self.stopProfit_goon)
return True
def transData(dataType):
dir = "D:\\myDevEvn\\UCMLCoreYunUMS7.6.1.8\\Standard\\Html\\BPObject\\sln_12002\\BusinessUnit\\我的测试\\data\\"
pTable = myIO_xlsx.DtTable()
pTable.Load_csv(dir + "dcjd_2020_08_20_pm.csv")
indFields = pTable.Get_Index_Fields(pTable.dataField)
ind_data = indFields[dataType]
ind_name = indFields['"时间"']
ind_lng = indFields['"经度"']
ind_lat = indFields['"纬度"']
# 循环提取数据
maxValue = -999999
lstRows = []
rows = pTable._Rows()
for i in range(0, rows):
row = pTable[i]
value = myData_Trans.To_Float(row[ind_data].replace('"', ''))
if (value > maxValue):
maxValue = value
name = row[ind_name].replace('"', '')
name = ""
lng = myData_Trans.To_Float(row[ind_lng].replace('"', ''))
lat = myData_Trans.To_Float(row[ind_lat].replace('"', ''))
jsonInfo = {"name": name, "value": [lng, lat, value]}
lstRows.append(jsonInfo)
# 插值加密
dataAdds = []
deltaDic = 1.0 / 111000 * 5
for i in range(0, rows - 1):
value0 = lstRows[i]['value']
value1 = lstRows[i + 1]['value']
name = lstRows[i]['name']
_deltaDic, linePoints = myData_Geometry.breakLine(
value0[0], value0[1], value1[0], value1[1], deltaDic)
if (len(linePoints) > 0):
#计算插值
dicT = myData_Geometry.distance(value0[0], value0[1], value1[0],
value1[1])
valueT = (value1[2] - value0[2]) / 2
x0 = value0[0]
y0 = value0[1]
numPoint = len(linePoints)
for x in range(0, numPoint, 2):
x1 = linePoints[x]
y1 = linePoints[x + 1]
dicTemp = myData_Geometry.distance(x0, y0, x1, y1)
valueTemp = value0[2] + valueT * (dicTemp / dicT)
jsonInfo = {"name": name, "value": [x1, y1, valueTemp]}
dataAdds.append({"index": i, "jsonInfo": jsonInfo})
# 添加插值
for i in range(len(dataAdds) - 1, -1, -1):
dataAdd = dataAdds[i]
jsonInfo = dataAdd["jsonInfo"]
ind = dataAdd["index"]
lstRows.insert(ind, jsonInfo)
dataInfo = [lstRows, maxValue]
strData = str(dataInfo).replace("'", '"')
path = dir + dataType.replace('"', '') + ".json"
myIO.Save_File(path, strData, True, False)
pass
def toValueList(self):
dtNow = self.getTime(False)
if(len(self.dataList) > 1 and self.dataList[0] == dtNow and type(self.dataList[4]) != str):
return self.dataList
self.dataList = []
self.dataList.append(dtNow) #时间
if(type(self.lastPrice) == str):
self.dataList.append(myData_Trans.To_Float(self.lastPrice)) #最后价格
self.dataList.append(myData_Trans.To_Float(self.highPrice)) #最高价格
self.dataList.append(myData_Trans.To_Float(self.lowPrice)) #最低价格
self.dataList.append(myData_Trans.To_Float(self.buyPrice)) #买价
self.dataList.append(myData_Trans.To_Float(self.sellPrice)) #卖价
self.dataList.append(myData_Trans.To_Float(self.tradeValume)) #成交量
self.dataList.append(myData_Trans.To_Float(self.tradeTurnover)) #成交额
self.dataList.append(myData_Trans.To_Float(self.buy1Volume)) #买1-5量
self.dataList.append(myData_Trans.To_Float(self.buy2Volume))
self.dataList.append(myData_Trans.To_Float(self.buy3Volume))
self.dataList.append(myData_Trans.To_Float(self.buy4Volume))
self.dataList.append(myData_Trans.To_Float(self.buy5Volume))
self.dataList.append(myData_Trans.To_Float(self.buy1Price)) #买1-5价格
self.dataList.append(myData_Trans.To_Float(self.buy2Price))
self.dataList.append(myData_Trans.To_Float(self.buy3Price))
self.dataList.append(myData_Trans.To_Float(self.buy4Price))
self.dataList.append(myData_Trans.To_Float(self.buy5Price))
self.dataList.append(myData_Trans.To_Float(self.sell1Volume)) #卖1-5量
self.dataList.append(myData_Trans.To_Float(self.sell2Volume))
self.dataList.append(myData_Trans.To_Float(self.sell3Volume))
self.dataList.append(myData_Trans.To_Float(self.sell4Volume))
self.dataList.append(myData_Trans.To_Float(self.sell5Volume))
self.dataList.append(myData_Trans.To_Float(self.sell1Price)) #卖1-5价格
self.dataList.append(myData_Trans.To_Float(self.sell2Price))
self.dataList.append(myData_Trans.To_Float(self.sell3Price))
self.dataList.append(myData_Trans.To_Float(self.sell4Price))
self.dataList.append(myData_Trans.To_Float(self.sell5Price))
self.priceOpen = myData_Trans.To_Float(self.openPrice) #开盘价格
self.priceBase = myData_Trans.To_Float(self.preClose) #前一收盘价格
else:
self.dataList.append((self.lastPrice)) #最后价格
self.dataList.append((self.highPrice)) #最高价格
self.dataList.append((self.lowPrice)) #最低价格
self.dataList.append((self.buyPrice)) #买价
self.dataList.append((self.sellPrice)) #卖价
self.dataList.append((self.tradeValume)) #成交量
self.dataList.append((self.tradeTurnover)) #成交额
self.dataList.append((self.buy1Volume)) #买1-5量
self.dataList.append((self.buy2Volume))
self.dataList.append((self.buy3Volume))
self.dataList.append((self.buy4Volume))
self.dataList.append((self.buy5Volume))
self.dataList.append((self.buy1Price)) #买1-5价格
self.dataList.append((self.buy2Price))
self.dataList.append((self.buy3Price))
self.dataList.append((self.buy4Price))
self.dataList.append((self.buy5Price))
self.dataList.append((self.sell1Volume)) #卖1-5量
self.dataList.append((self.sell2Volume))
self.dataList.append((self.sell3Volume))
self.dataList.append((self.sell4Volume))
self.dataList.append((self.sell5Volume))
self.dataList.append((self.sell1Price)) #卖1-5价格
self.dataList.append((self.sell2Price))
self.dataList.append((self.sell3Price))
self.dataList.append((self.sell4Price))
self.dataList.append((self.sell5Price))
self.priceOpen = self.openPrice #开盘价格
self.priceBase = self.preClose #前一收盘价格
self.priceRiseFall = self.dataList[1] / self.priceBase - 1 #涨跌幅
return self.dataList
def toValueFloat(self, value):
value = myData_Trans.To_Float(str(value))
return round(value, 6)
def Trans_FromDict(self, dictSets, canLog=True):
#验证股票信息
#pStocks = gol._Get_Value('setsStock', None)
#lstStock = pStocks._Find(dictSets.get('标的编号',""), dictSets.get('标的名称',""), exType="")
#if(len(lstStock) != 1): return{}
#pStock = lstStock[0]
#self.stockID = pStock.code_id
#self.stockName = pStock.code_name
#交易信息必须存在
if (dictSets == None): return False
bExsit = False
index = -1
strTime = dictSets.get('操作时间', "")
if (type(strTime) != str):
strTime = myData_Trans.Tran_ToDatetime_str(dictSets['操作时间'],
"%Y-%m-%d %H:%M:%S")
for x in self.logOperates:
index += 1
if (x['时间'] == strTime):
bExsit = True
break
#解析信息
self.ID = dictSets.get('ID', self.ID)
self.usrID = dictSets.get('用户名', self.usrID)
self.usrTag = dictSets.get('用户标签', self.usrTag)
self.stockID = dictSets.get('标的编号', self.stockID)
self.stockName = dictSets.get('标的名称', self.stockName)
self.stockType = dictSets.get('标的类型', self.stockType)
stockNum_temp = myData_Trans.To_Float(str(dictSets.get("标的数量", 0)))
stockAvg_temp = myData_Trans.To_Float(str(dictSets.get("标的均价", 0)))
stockPosition_temp = myData_Trans.To_Float(str(dictSets.get("标的仓位",
1)))
if (stockNum_temp == 0 or stockNum_temp == 0): return False
self.logDatetime = dictSets.get("操作时间", self.logDatetime)
if (type(self.logDatetime) == str):
self.logDatetime = myData_Trans.Tran_ToDatetime(
self.logDatetime, "%Y-%m-%d %H:%M:%S")
self.remark = dictSets.get("备注", self.remark)
self.isDel = dictSets.get('isDel', not self.valid)
if (canLog):
#提取时间
strTime = self.logDatetime
if (type(strTime) != str):
strTime = myData_Trans.Tran_ToDatetime_str(
strTime, "%Y-%m-%d %H:%M:%S")
#存在则更新
if (bExsit == False):
self.logOperates.append({
"股数": stockNum_temp,
"股价": stockAvg_temp,
"时间": strTime
}) #仓位变化记录
else:
self.logOperates[index] = {
"股数": stockNum_temp,
"股价": stockAvg_temp,
"时间": strTime
}
else:
self.logOperates = dictSets.get('操作日志', self.logOperates)
self.sumOperates = dictSets.get('操作统计数', 0)
#计算仓位变化
if (bExsit == False):
stockNum = self.stockNum
if (stockNum_temp > 0):
#买入时更新成本
stockNum += abs(stockNum_temp)
stockMoney = self.stockAvg * self.stockNum + stockNum_temp * stockAvg_temp
self.stockPosition = (
stockNum_temp * stockPosition_temp +
self.stockNum * self.stockPosition) / stockNum
self.stockAvg = stockMoney / stockNum
self.stockNum = int(stockNum)
else:
#卖出更新仓位
if (stockNum == 0):
stockNum = stockNum_temp
self.stockNum = int(stockNum)
self.stockAvg = stockAvg_temp
self.stockPosition = (
stockNum_temp * stockPosition_temp +
self.stockNum * self.stockPosition) / stockNum
if (self.stockPosition <= 0):
self.stockPosition = 0
self.valid = False
self.stockFee = dictSets.get("手续费率", self.stockFee)
self.limitHit = dictSets.get("边界限制", self.limitHit)
self.fixHit = dictSets.get("定量监测", self.fixHit)
self.deltaProfit = dictSets.get("监测间隔", self.deltaProfit)
self.stopProfit = dictSets.get("止盈线", self.stopProfit)
self.stopLoss = dictSets.get("止损线", self.stopLoss)
self.stopProfit_Dynamic = dictSets.get("动态止盈", self.stopProfit_Dynamic)
self.stopLoss_Dynamic = dictSets.get("动态止损", self.stopLoss_Dynamic)
self.stopProfit_Retreat = dictSets.get("止盈回撤", self.stopProfit_Retreat)
self.stopLoss_Retreat = dictSets.get("止损回撤", self.stopLoss_Retreat)
self.stopProfit_Trade = dictSets.get("止盈比例", self.stopProfit_Trade)
self.stopLoss_Trade = dictSets.get("止损比例", self.stopLoss_Trade)
self.priceMax = dictSets.get("最高价格", self.priceMax)
self.priceCost = dictSets.get("成本价格", self.stockAvg)
self.priceAvg_sell = dictSets.get("卖出均价", stockAvg_temp)
self.priceNow = dictSets.get("当前价格", stockAvg_temp)
self.profitMax_Stage = dictSets.get("阶段止盈", self.profitMax_Stage)
self.profitMin_Stage = dictSets.get("阶段止损", self.profitMin_Stage)
self.profitNow = dictSets.get("当前浮盈", self.profitNow)
self.stopProfit_goon = dictSets.get("止盈状态", self.stopProfit_goon)
self.stopLoss_goon = dictSets.get("止损状态", self.stopLoss_goon)
self.date = dictSets.get("建仓日期", self.date).replace("'", "")
if (self.date == ""):
self.date = myData_Trans.Tran_ToDatetime_str(
self.logDatetime, "%Y-%m-%d")
#操盘记录数不一致，更新统计判断
if (self.sumOperates != len(self.logOperates)):
self.Static_Profit(self.priceNow)
return True
def newData_ByInfo(self, dataInfo, checkTime=True):
#解析所有返回数据
if len(dataInfo) > 50:
values = dataInfo.split('=')
stkid = values[0][11:]
info = values[1][1:len(values[1]) - 4]
vargs = info.split(',')
# 区分股票与期权
qd = self.newData()
if (stkid.count('CON_OP') == 1):
#var hq_str_CON_OP_代码=“买量(0)，买价，最新价，卖价，卖量，持仓量，涨幅，行权价，昨收价，开盘价，涨停价，跌停价(11),
# 申卖 价五，申卖量五，申卖价四，申卖量四，申卖价三，申卖量三，申卖价二，申卖量二，申卖价一，申卖量一，申买价一，
# 申买量一 ，申买价二，申买量二，申买价三，申买量三，申买价四，申买量四，申买价五，申买量五，行情时间，主力合约标识，状态码，
# 标的证券类型，标的股票，期权合约简称，振幅(38)，最高价，最低价，成交量，成交额，分红调整标志，昨结算价，认购认沽标志，
# 到期日，剩余天数，虚实值标志，内在价值，时间价值
qd.id = stkid[7:]
qd.idTag = "sh." + qd.id
qd.rawline = info
qd.buyPrice = vargs[1]
qd.lastPrice = vargs[2]
qd.sellPrice = vargs[3]
qd.preClose = vargs[8]
qd.openPrice = vargs[9]
qd.sell5Price = vargs[12]
qd.sell5Volume = vargs[13]
qd.sell4Price = vargs[14]
qd.sell4Volume = vargs[15]
qd.sell3Price = vargs[16]
qd.sell3Volume = vargs[17]
qd.sell2Price = vargs[18]
qd.sell2Volume = vargs[19]
qd.sell1Price = vargs[20]
qd.sell1Volume = vargs[21]
qd.buy1Price = vargs[22]
qd.buy1Volume = vargs[23]
qd.buy2Price = vargs[24]
qd.buy2Volume = vargs[25]
qd.buy3Price = vargs[26]
qd.buy3Volume = vargs[27]
qd.buy4Price = vargs[28]
qd.buy4Volume = vargs[29]
qd.buy5Price = vargs[30]
qd.buy5Volume = vargs[31]
qd.date = vargs[32].split(' ')[0]
qd.time = vargs[32].split(' ')[1]
qd.name = vargs[37]
qd.highPrice = vargs[39]
qd.lowPrice = vargs[40]
qd.tradeValume = vargs[41]
qd.tradeTurnover = vargs[42]
else:
#var hq_str_sh510050=证券简称,今日开盘价,昨日收盘价,最近成交价,最高成交价,最低成交价,买入价,
# 卖出价,成交数量,成交金额,买数量一,买价位一,买数量二,买价位二,买数量三 ,买价位三,买数量四,
# 买价位四,买数量五,买价位五,卖数量一,卖价位一,卖数量二,卖价位二,卖数量三,卖价位三,卖数量四,
# 卖价位四,卖数量五,卖价位五,行情日期,行情时间,停牌状态
qd.id = stkid[2:]
qd.idTag = "sh." + qd.id
qd.rawline = info
qd.name = vargs[0]
qd.openPrice = vargs[1]
qd.preClose = vargs[2]
qd.lastPrice = vargs[3]
qd.highPrice = vargs[4]
qd.lowPrice = vargs[5]
qd.buyPrice = vargs[6]
qd.sellPrice = vargs[7]
qd.tradeValume = vargs[8]
qd.tradeTurnover = vargs[9]
qd.buy1Volume = vargs[10]
qd.buy1Price = vargs[11]
qd.buy2Volume = vargs[12]
qd.buy2Price = vargs[13]
qd.buy3Volume = vargs[14]
qd.buy3Price = vargs[15]
qd.buy4Volume = vargs[16]
qd.buy4Price = vargs[17]
qd.buy5Volume = vargs[18]
qd.buy5Price = vargs[19]
qd.sell1Volume = vargs[20]
qd.sell1Price = vargs[21]
qd.sell2Volume = vargs[22]
qd.sell2Price = vargs[23]
qd.sell3Volume = vargs[24]
qd.sell3Price = vargs[25]
qd.sell4Volume = vargs[26]
qd.sell4Price = vargs[27]
qd.sell5Volume = vargs[28]
qd.sell5Price = vargs[29]
qd.date = vargs[30]
qd.time = vargs[31]
#时间检查(是否当天)
if (checkTime):
if (qd.checkTime() == False):
return None
#设置数据
qd.value = myData_Trans.To_Float(qd.lastPrice)
return qd
return None
def runModel(self):
if (self.modeRunning): return False
self.modeRunning = True
try:
self.modeState = 1
self._Create_Result()
self.modelResult['data']['tag'] = self.tag
self.modelResult['data']['concentration_unit'] = "mg/m3"
self.modelResult['data']['results'] = []
# 参数提取
Q = self.massrate_Leak
u = self.wind.getWind_Speed(self.height_Leak, self.air)
H = self.height_Leak
H_delta = self._getH_delta()
H += H_delta
# 循环计算所有目标点
for x in self.infoTargets:
id = x[0]
longitude_Target = myData_Trans.To_Float(str(x[1]))
latitude_Target = myData_Trans.To_Float(str(x[2]))
z = myData_Trans.To_Float(str(x[3]))
# 坐标系调整
deltaX = (longitude_Target -
self.longitude_Leak) * 111000 * math.cos(
math.radians(self.latitude_Leak))
deltaY = (latitude_Target - self.latitude_Leak) * 111000
angle_Target = math.atan2(deltaY,
deltaX) / (2 * math.acos(-1)) * 360
angle_wind = self.wind.wind_Direction2 + 180
if (angle_wind > 360): angle_wind -= 360
angle = angle_Target - angle_wind
deltaXY = math.sqrt(deltaX * deltaX + deltaY * deltaY)
deltaY = math.sin(math.radians(angle)) * deltaXY
deltaX = math.cos(math.radians(angle)) * deltaXY
if (deltaX < 0):
Cxyz = 0
else:
# 高斯方程扩散公式实现
self.air.initAir_Ratio(deltaX)
theta_y = self.air.ratio_y
theta_z = self.air.ratio_z
if (z > 50):
Cxyz = Q / (2 * math.pi * u * theta_y * theta_z
) * math.exp(-deltaY * deltaY /
(2 * theta_y * theta_y) +
math.pow(z - H, 2) /
(2 * theta_z * theta_z))
else:
#Cxyz = Q / (math.pi * u * theta_y * theta_z) * math.exp(- math.pow(z - H, 2) / (2 * theta_z * theta_z))
Cxyz = Q / (2 * math.pi * u * theta_y *
theta_z) * math.exp(
-deltaY * deltaY /
(2 * theta_y * theta_y)) * (
math.exp(-math.pow(z - H, 2) /
(2 * theta_z * theta_z)) +
math.exp(-math.pow(z + H, 2) /
(2 * theta_z * theta_z)))
# 组装返回结果
res = {"id": id, "concentration": Cxyz}
self.modelResult['data']['results'].append(res)
self.modeState = 2
except Exception as err:
self.modeState = -2
self.modelResult['err'] = err
finally:
self.modeRunning = False
self.modelResult['success'] = myData.iif(self.modeState == 2, 1, 0)
return self.modeState == 2
