def __init__(self, startDate, endDate, trader, stock): self.stockTs = loadStockTs(stock, startDate, endDate) self.scoreTs = loadScoreTs(stock) self.trader = trader self.amountStockOwned = 0 dates = self.stockTs.getDateList() self.timeSpan = TimeSpan(dates[5], dates[-1])
def generateNeuralNet(self, stock, loadDataSetFromFile=False, randomScoreTs=False, maxEpochs=1000):
logit.debug('Downloading Stock Data')
targetTs = loadStockTs(stock, self.startDate, self.endDate)
scoreTs = loadScoreTs(stock, wordCounterTsFilename=self.wordCounterTsFilename)
if randomScoreTs:
scoreTs = scoreTs.mapValues(lambda val: random.random())
scaledInputTs, offset, scale = scoreTs.normalize()
scaledTargetTs, offset, scale = targetTs.normalize()
createNet = lambda historySize: createNLayerFFNet(historySize, 5, 10)
nn = NeuralNet(createNet, 3, scaledInputTs, scaledTargetTs, targetScalingFactor=scale, targetOffset=offset, loadDataSetFromFile=loadDataSetFromFile)
nn.train(maxEpochs=maxEpochs)
return nn
