def main():
#load a distribution
straightMUpkl = "C:\\bmProjects\\courses\\fall2011\\csci2951\\" +\
"auctionSimulator\\hw4\\pricePrediction\\margDistPredictions\\" +\
"distPricePrediction_straightMU_10000_2011_12_4_1323040769.pkl"
margDist5 = margDistSCPP()
margDist5.loadPickle(straightMUpkl)
# margDist5.graphPdf()
margDist2 = margDistSCPP(margDistData=margDist5.data[0:2])
margDist2.graphPdf()
expectedPrices = margDist2.expectedPrices({'method':'iTsample','nSamples':8})
upv = margDist2.margUpv(expectedPrices = expectedPrices)
def main():
filename = "F:\\courses\\fall2011\\csci2951\\hw4\\distributionPricePrediction\\distPricePrediction_straightMU8_10000_2011_12_8_1323383753.pkl"
margDist = margDistSCPP()
margDist.loadPickle(filename)
# margDist.graphPdf()
expectedPrices = margDist.expectedPrices()
print'Arithmetic Expected Prices:'
print expectedPrices
upv = margDist.margUpv(expectedPrices)
print 'upv of arithmetic expected prices'
print upv
expectedPrices8 = margDist.expectedPrices({'method':'iTsample','nSamples':8})
print ''
print'Sampled Expected Prices (8 samples):'
print expectedPrices8
upv8 = margDist.margUpv(expectedPrices8)
print 'upv of sampled expected prices'
print upv8
#generate a random valuation
l = 3
v = simYW.randomValueVector()
bundles = simYW.allBundles()
valuation = simYW.valuation(bundles=bundles,
v = v,
l=l)
print'Bundles:'
print bundles.astype('int')
utility = riskAware.mUPV({'expectedPrices' : expectedPrices8,
'bundles' : bundles,
'valuation' : valuation,
'l' : l,
'A' : 3})
print 'utility:'
print utility