def setUp(self):
net_gen = NetworkGenerator(100)
self.net = net_gen.generate_random_network()
self.algorithms_ok = ((SomeNodeAlgorithm,
{'rp1': 1, 'rp2': 2, 'rp3': 3, }),
(SomeNetworkAlgorithm,
{}),
SomeNetworkAlgorithm,
(SomeAlgorithmWithInheritance,
{'rp1': 1, 'rp2': 2, 'rp3': 3, 'rp4': 4}),
(SomeAlgorithmWithInheritanceChild,
{'rp1': 1, 'rp2': 2, 'rp3': 3, 'rp4': 4,
'rp5': 5, 'rp6': 6}),
)
self.check = [
# wrong_format
(PymoteNetworkError, [(SomeNodeAlgorithm,
{'rp1': 1, 'rp2': 2, 'rp3': 3}), ]),
# wrong_base_class
(PymoteNetworkError, ((Node, {}),)),
# missing_req_params
(PymoteAlgorithmException, ((SomeNodeAlgorithm,
{'rp1': 1, }),)),
(PymoteAlgorithmException, ((SomeAlgorithmWithInheritance,
{'rp1': 1, }),)),
]
def test_sim(self):
netgen = NetworkGenerator(degree=9, n_min=100, n_max=300)
for lm_pct in [5, 10, 20, 33]:
for net_count in range(100):
net = netgen.generate()
for node in net.nodes()[:int(lm_pct * len(net.nodes())/100)]:
node.compositeSensor = CompositeSensor(('TruePosSensor'))
net.algorithms = ALGORITHMS
sim = Simulation(net)
sim.run()
write_npickle(net, '%d-%d.gz' % (net_count,lm_pct))
def test_sim(self):
netgen = NetworkGenerator(degree=9, n_min=100, n_max=300)
for lm_pct in [5, 10, 20, 33]:
for net_count in range(100):
net = netgen.generate()
for node in net.nodes()[:int(lm_pct * len(net.nodes()) / 100)]:
node.compositeSensor = CompositeSensor(('TruePosSensor'))
net.algorithms = ALGORITHMS
sim = Simulation(net)
sim.run()
write_npickle(net, '%d-%d.gz' % (net_count, lm_pct))
def setUp(self):
net_gen = NetworkGenerator(100)
self.net = net_gen.generate_random_network()
self.net.algorithms = ((DVHop, {'truePositionKey': 'tp',
'hopsizeKey': 'hs',
'dataKey': 'I'
}),
(Trilaterate, {'truePositionKey': 'tp',
'hopsizeKey': 'hs',
'positionKey': 'pos',
'dataKey': 'I'}),
)
for node in self.net.nodes()[:10]:
node.compositeSensor = (TruePosSensor,)
def test_random_generation(self):
"""Test different random generation parameters"""
for input, output in self.in_out:
if isclass(output) and issubclass(output, Exception):
self.assertRaises(output, NetworkGenerator, input)
continue
net_gen = NetworkGenerator(**input)
if output == None:
self.assertEqual(None, net_gen.generate_random_network())
elif isinstance(output, dict):
net = net_gen.generate_random_network()
try:
net.validate_params(output)
except AssertionError:
self.fail("Network params did not validate.")
def test_random_generation(self):
"""Test different random generation parameters"""
for input, output in self.in_out:
if isclass(output) and issubclass(output, Exception):
self.assertRaises(output, NetworkGenerator, input)
continue
net_gen = NetworkGenerator(**input)
if output==None:
self.assertEqual(None, net_gen.generate_random_network())
elif isinstance(output, dict):
net = net_gen.generate_random_network()
try:
net.validate_params(output)
except AssertionError:
self.fail("Network params did not validate.")
def setUp(self):
net_gen = NetworkGenerator(100)
self.net = net_gen.generate_random_network()
self.algorithms_ok = (
(SomeNodeAlgorithm, {
'rp1': 1,
'rp2': 2,
'rp3': 3,
}),
(SomeNetworkAlgorithm, {}),
SomeNetworkAlgorithm,
(SomeAlgorithmWithInheritance, {
'rp1': 1,
'rp2': 2,
'rp3': 3,
'rp4': 4
}),
(SomeAlgorithmWithInheritanceChild, {
'rp1': 1,
'rp2': 2,
'rp3': 3,
'rp4': 4,
'rp5': 5,
'rp6': 6
}),
)
self.check = [
# wrong_format
(PymoteNetworkError, [
(SomeNodeAlgorithm, {
'rp1': 1,
'rp2': 2,
'rp3': 3
}),
]),
# wrong_base_class
(PymoteNetworkError, ((Node, {}), )),
# missing_req_params
(PymoteAlgorithmException, ((SomeNodeAlgorithm, {
'rp1': 1,
}), )),
(PymoteAlgorithmException, ((SomeAlgorithmWithInheritance, {
'rp1': 1,
}), )),
]
from pymote.npickle import write_npickle
from pymote.conf import global_settings
from distributed_voronoi import DistributedVoronoi
from point2D import Point2D
from voronoi import VoronoiDiagram
# Do not show log
logging.config.dictConfig({'version': 1,'loggers':{}})
VoronoiDiagram.start()
global_settings.ENVIRONMENT2D_SHAPE = VoronoiDiagram.panel_dim()
# generates the network with 10 hosts
net_gen = NetworkGenerator(n_count=99, n_min=1, n_max=100)
net = net_gen.generate_random_network()
# Defines the network algorithm
net.algorithms = ((DistributedVoronoi, {'informationKey':'axis'}),)
# Assign to node memory its position
for node in net.nodes():
node.memory['axis'] = (int(net.pos[node][0]), int(net.pos[node][1]))
# Creates and starts the simulation
sim = Simulation(net)
sim.run()
from pymote.algorithms.KVM.PTConstruction import PTConstruction
from pymote.networkgenerator import NetworkGenerator
from pymote.network import Network
from pymote.simulation import Simulation
from pymote.npickle import write_pickle
net_gen = NetworkGenerator(7)
net = net_gen.generate_random_network()
#NAPOMENA: u saturated makla random initiatore
net.algorithms = (PTConstruction, )
#net.nodes()[0].memory['I'] = "Koja je tvoja temperatura?"
net.show()
#write_pickle(net, 'PTConstruction_mreza.tar.gz')
sim = Simulation(net)
sim.run()
for node in net.nodes():
print "\n"
print node.id, node.memory, node.status
#sim.reset()
print "\nDone script."
def random_network(): net_gen = NetworkGenerator(10, commRange=400) net = net_gen.generate_random_network() return net
def network10():
net_gen = NetworkGenerator(30, comm_range=500)
net = net_gen.generate_random_network()
return net
def network8():
net_gen = NetworkGenerator(50, comm_range=300)
net = net_gen.generate_random_network()
return net
def network6():
net_gen = NetworkGenerator(20, comm_range=400)
net = net_gen.generate_random_network()
return net
xpositions = []
xestpositions = []
deltapos = []
esterror = []
positions = []
newpos = []
anchpositions = []
message_stats = []
position_stats = []
consume = []
energy = []
# Network Topology setup
Node.cid = 1 # start node id
net_gen = NetworkGenerator(n_count=n, degree=degree)
net = net_gen.generate_homogeneous_network() # A random homogeneous topology
#net_gen = Toplogy(n_count=n, degree=degree, n_max=n, n_min=n, connected=False)
#net = net_gen.generate_grid_network(randomness=0.2)
# Computes no. of anchors
f_anchors = (int)(100 / p_anchors)
n_anchors = (int)(n * p_anchors / 100.0)
# Set some nodes as anchor based on number of desired anchors
# Two arrays are populated with location of nodes to be plotted later
for node in net.nodes():
xpositions.append(net.pos[node][0])
if (node.id % f_anchors == 0): # anchor nodes
node.compositeSensor = (TruePosSensor, )
xpositions = []
xestpositions = []
deltapos = []
esterror = []
positions = []
newpos = []
anchpositions = []
message_stats = []
position_stats = []
consume = []
energy = []
# Network Topology setup
Node.cid = 1 # start node id
net_gen = NetworkGenerator(n_count=n, degree=degree)
net = net_gen.generate_homogeneous_network() # A random homogeneous topology
#net_gen = Toplogy(n_count=n, degree=degree, n_max=n, n_min=n, connected=False)
#net = net_gen.generate_grid_network(randomness=0.2)
# Computes no. of anchors
f_anchors = (int)(100 / p_anchors)
n_anchors = (int)(n * p_anchors/100.0)
# Set some nodes as anchor based on number of desired anchors
# Two arrays are populated with location of nodes to be plotted later
for node in net.nodes():
xpositions.append(net.pos[node][0])
if (node.id % f_anchors==0): # anchor nodes
node.compositeSensor = (TruePosSensor,)
def medium_random():
net_gen = NetworkGenerator(20, commRange=250)
net = net_gen.generate_random_network()
return net
def get_arch_random4():
net_gen = NetworkGenerator(20, comm_range=400)
net8 = net_gen.generate_random_network()
return net8
def get_arch_random3():
net_gen = NetworkGenerator(15, comm_range=300)
net7 = net_gen.generate_random_network()
return net7
