def testStockGroupWeightGenerationWithRiskAndReward(self):
listSize = 5
stockList = []
for i in range(0,listSize):
stockList.append(Stock(str(i),'test'+str(i), (0.2+ 0.01*i), (0.1 + 0.01*i)))
assert(len(stockList)==listSize)
StockCoRelation.resetMatrix()
for i in range(0,listSize):
for j in range(i,listSize):
StockCoRelation.addCorelation(stockList[i].uid, stockList[j].uid, 0)
stockGroup = StockGroup(stockList)
w = WeightVectorGenerator(100, listSize, 0, 65-listSize*3)
weightCount = 0
for i in range(0, 100):
(weightClass, weightVector) = w.getWeightVectorAndClassTuple()
while weightClass is not len(stockList):
(weightClass, weightVector) = w.getWeightVectorAndClassTuple()
weightCount += 1
stockGroup.setPlotBestRewardByRisk( (weightClass, weightVector) )
#print "%s" % (" \n".join([",".join([str(stock.uid), str(stock.reward), str(stock.risk)]) for stock in stockList]))
#print "Weights created %s" % weightCount
graphPlot = stockGroup.getPlotBestRewardByRisk()
graphIndex = graphPlot.keys()
graphIndex = sorted(graphIndex)
for i in range(0, len(graphIndex)):
print "%s %s" % (graphIndex[i], graphPlot[graphIndex[i]])
assert('01234'== stockGroup.getGroupId())
def getCombination(newStock, listOfStocks):
combinationStockGroupList = {}
queue = []
currentStockList = []
queue.append((0,[newStock]))
count = 0
while len(queue) is not 0:
(startPoint, currentStockList) = queue.pop()
stockGroup = StockGroup(currentStockList)
print "Got combination of size: %d" % len(currentStockList)
combinationStockGroupList[stockGroup.getGroupId()] = stockGroup
newStockGroupList = []
for i in range(startPoint, len(listOfStocks)):
newStockGroupList = currentStockList[:]
newStockGroupList.append(listOfStocks[i])
queue.append((i+1,newStockGroupList,))
count += 1
print "********* Count of total combinations %d for length %d" % (count, len(combinationStockGroupList))
return combinationStockGroupList
