Esempio n. 1
0
    def feedWithStockData(self, limit_date = None, fresh = False):
        if self.last_day is None:
            stockData, x_data, y_data = self.__getStockData(to_date = limit_date, fresh=fresh)
        else:
            last_date = csvmgr.stockDayToDatetime(self.last_day)
            last_date += timedelta(1)
            stockData, x_data, y_data = self.__getStockData(from_date = last_date, to_date = limit_date, fresh=fresh)

        print "Fitting..."
        self.last_day = csvmgr.getLastDayFromStock(stockData)
Esempio n. 2
0
    def feedWithStockData(self, limit_date = None, fresh = False):
        if self.last_day is None:
            stockData, x_data, y_data = self.__getStockData(to_date = limit_date, fresh=fresh)
        else:
            last_date = csvmgr.stockDayToDatetime(self.last_day)
            last_date += timedelta(1)
            stockData, x_data, y_data = self.__getStockData(from_date = last_date, to_date = limit_date, fresh=fresh)

        print "Fitting..."
        self.model.fit(x_data, y_data, batch_size=self.batch_size, nb_epoch=self.nb_epoch,
                        show_accuracy=True)

        self.last_day = csvmgr.getLastDayFromStock(stockData)
Esempio n. 3
0
    def __getStockData(self, from_date=None, to_date=None, fresh=False):
        maxlen = self.days_seq
        stockData = csvmgr.getStockData(self.csv_id, force_update=fresh)

        if from_date is None:
            from_date = csvmgr.stockDayToDatetime(csvmgr.getFirstDayFromStock(stockData))
        if to_date is None:
            to_date = csvmgr.stockDayToDatetime(csvmgr.getLastDayFromStock(stockData))

        if (to_date-from_date) <= timedelta(maxlen):
            from_date -= timedelta(maxlen+20)

        stockData = csvmgr.filterStockData(stockData, from_date, to_date)

        print "Getting stock data from "+csvmgr.getFirstDayFromStock(stockData) + " to " + csvmgr.getLastDayFromStock(stockData)

        stockValues = csvmgr.getPricesFromStock(stockData)

        x_data = numpy.array([stockValues[i:i+maxlen] for i in xrange(len(stockValues)-maxlen)])
        y_data = numpy.array([floor(stockValues[i]/stockValues[i-1]) for i in xrange(maxlen,len(stockValues))])

        return stockData, x_data, y_data