def parametricAuction(bids, distributions, flagReserveInfo=False):
means = [d.mean() for d in distributions]
sigmas = [d.std() for d in distributions]
if bids == [] or bids is None:
raise AuctionExceptions.EmptyBidsException
if len(bids) != len(means) or len(bids) != len(sigmas):
raise AuctionExceptions.DifferentBidsAndReservesSize(bids, means)
# change name of this last exception
reserves = []
for i in range(len(bids)):
r = parametricReserve(means[i], sigmas[i])
reserves.append(r)
(allocation, price) = lazyVickrey(bids, reserves)
if flagReserveInfo == True:
winner = None
for i in range(len(allocation)):
if allocation[i] != 0: # in this case there is only one winner, with allocation set to 1
winner = i
if winner == None:
return (allocation, price, None, None)
if price[winner] == reserves[winner]:
isPriceFromReserve = True
else:
isPriceFromReserve = False
paramReserve = reserves[0] # for 1 dist
return (allocation, price, isPriceFromReserve, paramReserve)
else:
return (allocation, price)
def revenueParametricAuctionFromSamples(trainingSamples, testSamples, flagReserveInfo=False):
# trainingSamples = float[NUM_PLAYERS][NUM_TEST_SAMPLES]
"""generate many means and sigmas from trainingSamples"""
means = [getMeanEstimation(trainingSet) for trainingSet in trainingSamples]
sigmas = [getStdEstimation(trainingSet) for trainingSet in trainingSamples]
"""
test for exceptions
"""
"""testSamples are the new bids"""
reserves = []
for i in range(len(testSamples)):
reserves.append(parametricReserve(means[i], sigmas[i]))
# DO FOR ALL TEST SAMPLES
totalRevenue = 0
revenues = []
samples = zip(*testSamples)
numSamples = len(samples)
if flagReserveInfo == False:
totalRevenue = 0
for i in xrange(numSamples):
bids = samples[i]
(allocation, price) = lazyVickrey(bids, reserves)
revenue = sum(price)
totalRevenue += revenue
revenues.append(revenue)
return revenues
else: # if (flagReserveInfo==True):
revenues1 = []
revenue1 = 0
counterNotSell1 = 0
counterPriceFromReserve1 = 0
avgReservePrice1 = 0
for i in xrange(numSamples):
bids = samples[i]
(allocation, price) = lazyVickrey(bids, reserves)
winner = None
for i in range(len(allocation)):
if allocation[i] != 0: # in this case there is only one winner, with allocation set to 1
winner = i
if winner == None:
(allocation, prices, isPriceFromReserve, reservePrice) = (allocation, price, None, None)
else:
if price[winner] == reserves[winner]:
isPriceFromReserve = True
else:
isPriceFromReserve = False
paramReserve = reserves[0] # for 1 dist
(allocation, prices, isPriceFromReserve, reservePrice) = (
allocation,
price,
isPriceFromReserve,
paramReserve,
)
if isPriceFromReserve == None:
counterNotSell1 += 1
if isPriceFromReserve == True:
counterPriceFromReserve1 += 1
avgReservePrice1 = reservePrice
revenue1 = sum(prices)
revenues1.append(revenue1)
avgRevenue1 = sum(revenues1) / (numSamples * 1.0)
avgRevenue1 *= complex(1, 0)
avgRevenue1 = avgRevenue1.real
avgSellingPrice1 = avgRevenue1 * numSamples / (numSamples - counterNotSell1)
timeItemNotSold1 = counterNotSell1 * 1.0 / numSamples
timeReservePriceDeterminant1 = counterPriceFromReserve1 * 1.0 / numSamples
timeCompetitionDeterminant1 = 1 - timeReservePriceDeterminant1 - timeItemNotSold1
s1 = (
"AvgRevenue\t"
+ str(avgRevenue1)
+ "\tAvgSellingPrice\t"
+ str(avgSellingPrice1)
+ "\t%timeItemNotSold\t"
+ str(timeItemNotSold1)
+ "\t%timeReservePriceDeterminant\t"
+ str(timeReservePriceDeterminant1)
+ "\t%timeCompetitionDeterminant\t"
+ str(timeCompetitionDeterminant1)
+ "\tavgReservePrice\t"
+ str(avgReservePrice1)
)
return s1
