def ironedMyersonAuction(bids, distributions,flagReserveInfo=False):
if bids==[] or bids is None:
raise AuctionExceptions.EmptyBidsException
if len(bids)!=len(distributions):
raise AuctionExceptions.DifferentBidsAndReservesSize(bids,distributions)
#change name of this last exception
virtualValues=[ironedVirtualValuation(bids[i], distributions[i]) for i in range(len(bids)) ]
virtualValuesCheck=[virtualValuation(bids[i], distributions[i]) for i in range(len(bids)) ] #TODO REMOVE
#print "virtualValues",virtualValues
#print "virtualValuesCheck",virtualValuesCheck
reserves=[0]*len(bids)# print "virtualValues", virtualValues
(allocation, priceListAux) = eagerVickrey(virtualValues,reserves)
if sum(allocation) == 0:
if (flagReserveInfo==False):
return (allocation, priceListAux)
else:
return (allocation, priceListAux, None, 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
secondVirtualValue = priceListAux[winner]
secondVirtualValue = max(secondVirtualValue,0)
firstVirtualValue = max(virtualValues)
#this function find root of auxRootFinding in the interval [0,bids[winner]]
#in fact fsolve does not guarantee interval [0,bids[winner], it just gives x0 as the initial guess (include this login in aux function)
#if (secondVirtualValue > ironedVirtualValuation(bids[winner], distributions[winner])):
# print "error: secondVirtualValue >bids[winner]", secondVirtualValue, ironedVirtualValuation(bids[winner], distributions[winner])
priceAux = scipy.optimize.fsolve(auxRootFindingIroned, bids[winner], (secondVirtualValue, distributions[winner], 0, bids[winner]))
myersonReserve = scipy.optimize.fsolve(auxRootFindingIroned, bids[winner], (0, distributions[winner], 0, bids[winner]))
price = [0 for i in allocation]
price[winner]=priceAux[0]
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 priceListAux[winner]==reserves[winner]: # equivalent to secondVirtualValue < 0
isPriceFromReserve = True
else:
isPriceFromReserve = False
return (allocation,price,isPriceFromReserve,myersonReserve)
else:
return (allocation,price)
def revenueIronedMyersonAuctionFromSamples(trainingSamples,testSamples):
# trainingSamples = float[NUM_PLAYERS][NUM_TEST_SAMPLES]
'''generate many means and sigmas from trainingSamples'''
distributions=[getDistribution(trainingSet) for trainingSet in trainingSamples]
'''
test for exceptions
'''
'''testSamples are the new bids'''
#DO FOR ALL TEST SAMPLES
totalRevenue=0
revenues=[]
samples = zip(*testSamples)
numSamples = len(samples)
for i in xrange(numSamples):
bids = samples[i]
#call to regular ironedMyersonAuction since I know bids and distribution
virtualValues=[ironedVirtualValuation(bids[i], distributions[i]) for i in range(len(bids)) ]
reserves=[0]*len(bids)
(allocation, priceListAux) = eagerVickrey(virtualValues,reserves)
if sum(allocation) == 0:
priceList = priceListAux
else:
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
secondVirtualValue = priceListAux[winner]
secondVirtualValue = max(secondVirtualValue,0)
price = scipy.optimize.fsolve(auxRootFindingIroned, bids[winner], (secondVirtualValue, distributions[winner], 0, bids[winner]))
priceList = [0 for i in allocation]
priceList[winner]=price
revenue = sum(priceList)
totalRevenue+=revenue
revenues.append(revenue)
return revenues
def auxRootFindingIroned(value,secondVirtualValue, distribution, minPrice, maxPrice):
return ironedVirtualValuation(value,distribution) - secondVirtualValue + isNotInInterval(value,minPrice,maxPrice)