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