def main():
""" Definiranje main funkcije .... """
#Inicijaliziraj mrezu
net_gen = NetworkGenerator(100) # implementirat broj nodova
net = net_gen.generate_random_network()
#Postavi algoritam i INITIATOR node
net.algorithms = ((ShoutAlgorithm, {'informationKey': 'I'}),)
# Zamjena range(1) za jedan node(Shout) ili vise(10) za multishout.
# Definiranje random INIT nodova
# for random_counter in range(1):
for random_counter in range(1):
rand_number = randrange(0, 100)
some_node = net.nodes()[rand_number]
some_node.memory['I'] = 'Slanje vremena'
#Napravi simulaciju, spremi u datoteku "Shout.tar.gz"
sim = Simulation(net)
write_npickle(net, 'Shout.tar.gz')
#sim.reset()
#Pokreni
sim.run()
# print memorije nodova ...
for node in net.nodes():
print node.memory
#Spremanje dijagrama nodova kao slika u png formatu
net.show(savefig="image.png")
def main():
#Inicijaliziraj mrezu
net_gen = NetworkGenerator(n_min=3, n_count=5, n_max=10) # broj nodova
net = net_gen.generate_random_network()
#Add distance sensor
for node in net.nodes():
node.compositeSensor = (NeighborsSensor, DistSensor)
#Postavi algoritam i INITIATOR node
net.algorithms = ((PTConstruction, {'informationKey': 'I'}),)
#Samo jedan node je INITIATOR!
some_node = net.nodes()[0]
some_node.memory['I'] = 'Hello distributed world'
write_npickle(net, 'PTConstruction.tar.gz')
#Napravi simulaciju
sim = Simulation(net)
# sim.reset()
#Debug
print "Prije pokretanja!"
#Pokreni
sim.run()
for node in net.nodes():
print node.memory
net.show(savefig="image.png")
def test_santoro2007(self):
N_ITERS = 5
N_NETWORKS = 15
N_NODES_STEP = 5
node_range = 100
nets = [
[(100, 100)],
[(100, 100), (175, 250), (250, 175), (100, 250),
(175, 175), (100, 175)],
[(100, 100), (150, 200), (175, 175), (175, 100),
(250, 175), (250, 250), (325, 250), (325, 325), (325, 400)]
]
for i, node_positions in enumerate(nets, start=1):
net = Network()
for node_pos in node_positions:
net.add_node(pos=node_pos, commRange=node_range)
name = 'Special %d' % i
net.algorithms = (YoYo, )
sim = Simulation(net, logLevel='WARNING')
sim.run()
min_id = min(sim.network.nodes(), key=lambda node: node.id).id
for node in sim.network.nodes():
if node.id == min_id:
# Check if the node with the smallest ID is the LEADER
assert node.status == 'LEADER', \
'%s: Node %d has status %s, not LEADER' % \
(name, node.id, node.status)
else:
# Check if every other node is PRUNED
assert node.status == 'PRUNED', \
'%s: Node %d has status %s, not PRUNED' % \
(name, node.id, node.status)
for i in range(N_ITERS):
for n_nodes in range(N_NODES_STEP,
N_NETWORKS*N_NODES_STEP+N_NODES_STEP,
N_NODES_STEP):
net_gen = NetworkGenerator(n_nodes)
net = net_gen.generate_random_network()
name = 'Random %d, %d nodes' % (i, n_nodes)
net.algorithms = (YoYo, )
sim = Simulation(net, logLevel='WARNING')
sim.run()
min_id = min(sim.network.nodes(), key=lambda node: node.id).id
for node in sim.network.nodes():
if node.id == min_id:
# Check if the node with the smallest ID is the LEADER
assert node.status == 'LEADER', \
'%s: Node %d has status %s, not LEADER' % \
(name, node.id, node.status)
else:
# Check if every other node is PRUNED
assert node.status == 'PRUNED', \
'%s: Node %d has status %s, not PRUNED' % \
(name, node.id, node.status)
