class RateAnalyser(WinAnalyser):
def __init__(self):
super(RateAnalyser, self).__init__()
self.timeAndGold = AnalysisTree(2, WinAnalyser, {1: anyValueTime, 2: anyValueGold})
def analyze(self, data):
WinAnalyser.analyze(self, data)
timeStep = getTimeSection(data.timeStamp)
goldDiff = getGoldSection(data.goldDiff)
self.timeAndGold.analyze((goldDiff, timeStep), data)
def result(self):
timeAndGoldTable = [self.timeAndGold.result(keys) for keys in product(possibleGoldValues, possibleTimeValues)]
timeTable = [self.timeAndGold.result(keys) for keys in product((anyValueGold,), possibleTimeValues)]
goldTable = [self.timeAndGold.result(keys) for keys in product(possibleGoldValues, (anyValueTime,))]
winStatistic = self.timeAndGold.result((anyValueGold, anyValueTime))
return TimeGoldSpread(timeAndGoldTable, timeTable, goldTable, winStatistic)
analysisTree.clear()
gc.collect()
print('Everthing is saved')
def shouldAnalyze(dataSet):
return dataSet.itemId in Items.apItemIds and dataSet.eventType == FrameEventType.ITEM_PURCHASED
print('Ap item ids: ', Items.apItemIds)
with skipCounter:
lastTime = time.time()
for data in dataSets:
if not shouldAnalyze(data):
continue
if doneCount < skipCounter.object:
doneCount += 1
continue
analysisTree.analyze(mapDataToKey(data), data)
doneCount += 1
oneRuncount += 1
#Increase or decrease this number according to the memory available to you. This is for ~1GiB
if oneRuncount > 20000:
doPartialSaveAndClear(oneRuncount)
oneRuncount = 0
if time.time() - lastTime > 10:
print("{0} data sets analyzed".format(doneCount))
lastTime = time.time()
doPartialSaveAndClear(oneRuncount)
print("All data sets are now analysed")
print("Analysis saved to disk")
