source.join_sim( sim )
gate = GatedQueue()
gate.join_sim( sim )
dispatch = BatchNNeighDispatcher()
# dispatch = NNeighDispatcher()
dispatch.set_environment( roadnet )
dispatch.join_sim( sim )
""" add some demands to jump-start the simulation """
preload = 0
distr = {}
for road1, road2, rate_data in normrategraph.edges_iter( data=True ) :
distr[(road1,road2)] = rate_data.get( 'rate', 0. )
bonus_demands = [ roadprob.samplepair( roadnet, distr ) for i in range(preload) ]
for p, q in bonus_demands : gate.demand_arrived( (p,q) )
""" end cheats """
vehicles = {}
for k in range( numveh ) :
veh = Vehicle() ; vehicles[ veh ] = None
veh.set_environment( f_dist )
veh.set_speed( vehspeed )
randpoint = roadprob.sampleaddress( roadnet, 'length' )
veh.set_location( randpoint )
veh.join_sim( sim )
# connect components in simulation schematic
""" source output connections """
# report demand arrivals to several places
def sim_init( self ) :
""" simulation setup """
# construct the simulation blocks
sim = Simulation()
self.sim = sim
if False :
script = sample_demands( self.horizon, self.rategraph, self.roadnet )
source = ScriptSource( script )
print 'obtained %d demands' % len( source.script )
debug_input()
else :
source = RoadnetDemandSource( self.roadnet, self.rategraph )
self.source = source
source.join_sim( sim )
gate = GatedQueue()
self.gate = gate
gate.join_sim( sim )
dispatch = BatchNNeighDispatcher()
self.dispatch = dispatch
dispatch.set_environment( roadnet )
dispatch.join_sim( sim )
""" add some demands to jump-start the simulation """
preload = 0
distr = {}
for road1, road2, rate_data in normrategraph.edges_iter( data=True ) :
distr[(road1,road2)] = rate_data.get( 'rate', 0. )
bonus_demands = [ roadprob.samplepair( roadnet, distr ) for i in range(preload) ]
for p, q in bonus_demands : gate.demand_arrived( (p,q) )
""" end cheats """
vehicles = {}
self.vehicles = vehicles
for k in range( self.numveh ) :
veh = Vehicle() ; vehicles[ veh ] = None
veh.set_environment( self.distance )
veh.set_speed( self.vehspeed )
randpoint = roadprob.sampleaddress( roadnet, 'length' )
veh.set_location( randpoint )
veh.join_sim( sim )
# make a recorder
recorder = UniformPoller( 1. )
self.recorder = recorder
def unassigned_query() :
return len( self.gate.demands ) + len( self.dispatch.demands )
recorder.set_query( unassigned_query )
recorder.join_sim( sim )
# report demand arrivals to several places
self.DEMANDS = []
def record_arrival( dem ) :
self.DEMANDS.append( dem )
def give_to_dispatch( dem ) :
p, q = dem
loc = p
#dispatch.demand_arrived( dem, loc )
self.gate.demand_arrived( dem )
source_out = source.source()
#source_out.connect( counting.increment )
source_out.connect( give_to_dispatch )
source_out.connect( record_arrival )
#source.source().connect( give_to_dispatch )
self.timer = data()
self.timer.last_time = sim.time
def say( dem ) :
p, q = dem
new_time = self.sim.time
elapsed = new_time - self.timer.last_time
print 'tick, %f: %s, %s' % ( elapsed, repr(p), repr(q) )
self.timer.last_time = new_time
source_out.connect( say )
def gimme( *args, **kwargs ) :
print "need a batch!!"
# creates an interface from gate to interactive dispatcher
gate_if = gate.spawn_interface()
self.gate_if = gate_if
dispatch.request_batch.connect( gate_if.request_in )
dispatch.request_batch.connect( gimme )
gate_if.batch_out.connect( dispatch.batch_arrived )
def hello( *args, **kwargs ) :
print 'vehicle is ready!'
# vehicle signal connections
for veh in vehicles :
vehconn = dispatch.spawn_interface() ; vehicles[veh] = vehconn
veh.ready.connect( vehconn.request_in )
veh.ready.connect( hello )
#veh.ready.connect( vehconn.request_in )
vehconn.demand_out.connect( veh.receive_demand )
v = random.choice( nodes )
label, length = road_iter.next()
roadnet.add_edge( u, v, label, length=length, oneway=True )
if True :
distr = {}
distr[('W','E')] = 1./5
distr[('N','E')] = 1./5
distr[('W','S')] = 3./5
Ed = roadEd( roadnet, distr, length_attr='length' )
print 'Ed computed %f' % Ed
pairs = [ ROADRAND.samplepair( roadnet, distr ) for i in range(20000) ]
dst = [ ROAD.distance( roadnet, p, q, 'length' ) for p,q in pairs ]
Ed_emp = np.mean( dst )
print 'Ed empirical %f' % Ed_emp
else :
ROADS = ['N', 'S', 'E', 'W' ]
#PAIRS = itertools.product( ROADS, ROADS )
#PAIRS = [ ('E','E') ]
edges = [ name for _,__,name in roadnet.edges( keys=True ) ]
#PAIRS = [ ( random.choice(edges), random.choice(edges) ) for i in range(5) ]
for road1, road2 in PAIRS :
Ed_cond = roadEd_conditional( roadnet, road1, road2 )
#
pairs = [ sample( roadnet, { (road1, road2) : 1.} ) for i in range(20000) ]