def simulateBySymbol(filename, combineByOrderDate=False, agentNums=[100]):
"""
Treat all bidders for the same symbol, in ALL dates, as a distribution of values for that symbol.
"""
datasetFilename = "datasets/"+filename+".CSV"
resultsFilename = "results/"+filename+("-combined" if combineByOrderDate else "")+"-r"+str(max(agentNums))+".csv"
resultsFilenameTemp = "results/"+filename+"-temp.csv"
results = DataFrame(columns=COLUMNS)
print("\t{}".format(COLUMNS))
for symbol,allTimeTraders in torq.auctionsBySymbol(datasetFilename, combineByOrderDate):
date = 0
for agentNum in agentNums:
traders = [random.choice(allTimeTraders) for i in range(agentNum)]
print("Simulating auction {}-{} with {} traders".format(symbol,date,len(traders)))
totalBuyers = sum([t.isBuyer for t in traders])
totalSellers = len(traders)-totalBuyers
totalUnits = sum([t.totalUnits() for t in traders])
maxUnitsPerTrader = max([t.totalUnits() for t in traders]) # maxUnitsPerTrader is denoted in the paper by m.
stddev = np.sqrt(sum([t.totalUnits()**2 for t in traders]))
(buyersWALRAS, sellersWALRAS, sizeWALRAS, gainWALRAS) = WALRAS(traders) # sizeWALRAS is denoted in the paper by k.
(sizeMIDALottery, gainMIDALottery, gainMIDALottery, sizeMIDAVickrey, tradersGainMIDAVickrey, totalGainMIDAVickrey) = MIDA(traders, Lottery=True, Vickrey=True)
resultsRow = [
(symbol,date),
totalBuyers, totalSellers, totalBuyers+totalSellers, min(totalBuyers,totalSellers), totalUnits,
maxUnitsPerTrader, stddev,
buyersWALRAS, sellersWALRAS, sizeWALRAS,
gainWALRAS, gainMIDALottery, tradersGainMIDAVickrey, totalGainMIDAVickrey]
print("\t{}".format(resultsRow))
results.loc[len(results)] = resultsRow
results.to_csv(resultsFilenameTemp)
results.to_csv(resultsFilename)
os.remove(resultsFilenameTemp)
return results
def torqSimulateBySymbol(filename, combineByOrderDate=False, agentNums=[100]):
"""
Treat all bidders for the same symbol, in ALL dates, as a distribution of values for that symbol.
"""
datasetFilename = "datasets/" + filename + ".CSV"
resultsFilename = "results/" + filename + (
"-combined" if combineByOrderDate else "") + "-s" + str(
max(agentNums)) + ".csv"
return simulateAuctions(sampleAuctions(
agentNums, torq.auctionsBySymbol(datasetFilename, combineByOrderDate)),
resultsFilename,
keyColumns=("symbol", ))