def __call__(self, *args, **kwargs):
nGames = self.nGames
if args:
nGames = args[0]
agentList = self.agentsFromType(agentTypeList = self.agentTypeList,
A = self.A,
m = self.m,
margDistPrediction = self.margDistPrediction)
agentSurplus = []
for g in xrange(nGames):
# all agents draw new valuation function
for agent in agentList:
agent.randomValuation(vmin = self.vmin,
vmax = self.vmax,
m = self.m)
auction = simultaneousAuction(agentList = agentList)
auction.runAuction()
auction.notifyAgents()
agentSurplus.append( auction.agentSurplus() )
return numpy.atleast_2d(agentSurplus).astype(numpy.float)
def __call__(self, *args , **kwargs):
agentList = self.agentsFromType(agentTypeList = self.agentTypeList,
A = self.A,
m = self.m,
margDistPrediction = self.margDistPrediction)
agentSurplus = []
for g in xrange(0,self.nGames):
v = numpy.random.random_integers(low = self.vmin, high = self.vmax, size= self.m)
v.sort()
v = v[::-1]
l = numpy.random.random_integers(low = 1, high = self.m)
for agent in agentList:
agent.v = v
agent.l = l
auction = simultaneousAuction(agentList = agentList)
auction.runAuction()
auction.notifyAgents()
agentSurplus.append( auction.agentSurplus() )
return numpy.atleast_2d(agentSurplus).astype(numpy.float)
def comp2Agents(**kwargs):
oDir = kwargs.get('oDir')
pp1 = kwargs.get('pp1')
n1 = kwargs.get('n1',4)
pp2 = kwargs.get('pp2')
n2 = kwargs.get('n2',4)
agentType1 = kwargs.get('agentType1')
agentType2 = kwargs.get('agentType2')
m = kwargs.get('m',5)
minValuation = kwargs.get('minValuation',0)
maxValuation = kwargs.get('maxValuation',50)
nGames = kwargs.get('nGames',1000)
parallel = kwargs.get('parallel',True)
nProc = kwargs.get('nProc', multiprocessing.cpu_count() - 1)
verbose = kwargs.get('verbose', True)
if verbose:
print ''
print 'In comp2Agents(...)'
print 'oDir = {0}'.format(oDir)
print 'agentType1 = {0}'.format(agentType1)
print 'n1 = {0}'.format(n1)
print 'agentType2 = {0}'.format(agentType2)
print 'n2 = {0}'.format(n2)
print 'm = {0}'.format(m)
print 'nGames = {0}'.format(nGames)
print 'minValuation = {0}'.format(minValuation)
print 'maxValuation = {0}'.format(maxValuation)
print ''
if parallel:
pool = multiprocessing.Pool(nProc)
nGameList = [nGames//nProc]*nProc
nGameList[-1] += (nGames % nProc)
if verbose:
print 'Running parallel simulation.'
print 'Number of cores = {0}'.format(nProc)
print 'Number of simulations per core = {0}'.format(nGameList)
print 'Total Number of simulations = {0}'.format((sum(nGameList)))
results = []
for p in xrange(nProc):
subArgs = copy.deepcopy(kwargs)
subArgs.update(kwargs)
subArgs['parallel'] = False
subArgs['nGames'] = nGameList[p]
subArgs['verbose'] = False
subArgs['oDir'] = None
results.append(pool.apply_async(comp2Agents, kwds = subArgs))
pool.close()
pool.join()
for idx, r in enumerate(results):
if idx == 0:
agentSurplus = r.get()
else:
agentSurplus = numpy.concatenate((agentSurplus,r.get()))
r._value = []
else:
auction = simultaneousAuction( m = m,
nPrice = 2,
reserve = 0)
for i in xrange(n1):
agent = agentFactory(agentType = agentType1,
m = m,
vmin = minValuation,
vmax = maxValuation )
agent.pricePrediction = pp1
auction.attachAgents(agent)
for i in xrange(n2):
agent = agentFactory(agentType = agentType2,
m = m,
vmin = minValuation,
vmax = maxValuation )
agent.pricePrediction = pp2
auction.attachAgents(agent)
agentSurplus = numpy.zeros((nGames,n1+n2))
for itr in xrange(nGames):
if verbose:
print 'Simulating {0} out of {1} auctions'.format(itr,nGames)
[agent.randomValuation() for agent in auction.agentList]
if verbose:
for idx, agent in enumerate(auction.agentList):
print 'agent[{0}] = {1} ; l = {2}, v = {3}'.format(idx, agent.type(), agent.l, agent.v)
auction.runAuction()
auction.notifyAgents()
surplus = auction.agentSurplus()
agentSurplus[itr,:] = surplus
if verbose:
print 'Agent Surplus = {0}'.format(surplus)
if oDir:
oDir = os.path.realpath(oDir)
if not os.path.exists(oDir):
os.makedirs(oDir)
sFile = os.path.join(oDir,'{0}_{1}_agentSurplus.txt'.format(agentType1,agentType2))
numpy.savetxt(sFile, agentSurplus)
return agentSurplus
