def rate_observed(self) :
# convenience
horizon = self.horizon
recorder = self.recorder
dispatch = self.dispatch
arrivalrate = totalrate( self.rategraph )
total_demands = len( self.DEMANDS )
nleft = len( dispatch.demands )
print 'arrival rate (simulated, observed): %f, %f' % ( arrivalrate, total_demands / horizon )
if True :
# see what this does
rate_observed = sum([ veh.notches for veh in self.vehicles ]) / self.horizon
else :
#overrate_est = float( nleft - preload ) / horizon
take_only_last = .25 * horizon
take_num = int( np.ceil( take_only_last / recorder.T ) )
DY = float( self.tape[-1] - self.tape[-take_num] )
DT = take_num * recorder.T
overrate_est = float( DY ) / DT
rate_observed = arrivalrate - overrate_est
return rate_observed
normrategraph.add_edge( 'LEFT', 'RIGHT', rate=1. )
probe = RoadmapEMD()
probe.horizon = 10000.
complexity_computed = []
complexity_estimated = []
def showresults() :
plt.scatter( complexity_computed, complexity_estimated )
for t in range(1) :
roadnet, rategraph = get_sim_setting( mu=2. )
R = totalrate( rategraph )
n_rategraph = scale_rates( rategraph, 1. / R )
enroute_velocity = carryMileageRate( roadnet, n_rategraph )
balance_velocity = fetchMileageRate( roadnet, n_rategraph )
complexity = enroute_velocity + balance_velocity
#complexity = moverscomplexity( roadnet, n_rategraph )
for k in range(1) :
numveh = np.random.randint(1,5+1)
rate_predicted = convert_complexity_and_servicerate( complexity, numveh )
simrates = scale_rates( n_rategraph, .99 * rate_predicted )
probe.scenario( roadnet, simrates, numveh, 1. )
