def getNeedToUpdateDaysOfFactor(self, code, factor):
self.setIPODate(code)
listDate = self.listDate
delistDate = self.delistDate
today = datetime.datetime.now().strftime("%Y%m%d")
yesterday = TradedayDataProcess.getPreviousTradeday(today)
endDate = min(delistDate, yesterday)
lastDate = self.getLastDate(code, factor)
if lastDate != EMPTY_STRING:
startDate = max(listDate,
TradedayDataProcess.getNextTradeday(lastDate))
else:
startDate = listDate
return [startDate, endDate]
pass
def getLastTradedayTickData(self, code, date):
previousday = TradedayDataProcess.getPreviousTradeday(date, 250)
days = list(TradedayDataProcess.getTradedays(previousday, date))
days.reverse()
data = pd.DataFrame()
for day in days:
if day < date:
#data=TickDataProcess().getDataByDateFromLocalFile(code,day)
data = TickDataProcess().getTickShotDataFromInfluxdbServer(
code, day)
if data.shape[0] > 0:
return data
pass
pass
pass
return data
pass
def __computerFactor(self, code, startDate, endDate):
#需要前推100天来获取计算得数据
startDate = TradedayDataProcess.getPreviousTradeday(startDate, 100)
[listDate, delistDate] = super().setIPODate(code)
startDate = max(startDate, listDate)
dailyData = KLineDataProcess('daily')
mydata = dailyData.getDataByDate(code, startDate, endDate)
if mydata.shape[0] == 0:
return pd.DataFrame()
mydata['return'] = (mydata['close'] / mydata['preClose'] - 1)
mydata.loc[mydata['status'] == '停牌', 'return'] = np.nan
mydata.loc[mydata['date'] == listDate, 'return'] = np.nan
mydata['yesterdayReturn'] = mydata['return'].shift(1)
mydata['closeStd20'] = mydata['yesterdayReturn'].rolling(
20, min_periods=16).std()
mydata['ts_closeStd20'] = mydata['closeStd20'].rolling(
50, min_periods=20).apply(
(lambda x: pd.Series(x).rank().iloc[-1] / len(x)), raw=True)
mycolumns = ['date', 'yesterdayReturn', 'closeStd20', 'ts_closeStd20']
mydata = mydata[mycolumns]
return mydata