def test_barabasi_albert_topology(self):
self.assertRaises(ValueError, fnss.barabasi_albert_topology, 0, 20, 30)
self.assertRaises(ValueError, fnss.barabasi_albert_topology, 50, 40, 20)
self.assertRaises(ValueError, fnss.barabasi_albert_topology, 10, 40, 20)
self.assertRaises(ValueError, fnss.barabasi_albert_topology, 50, -1, 20)
self.assertRaises(ValueError, fnss.barabasi_albert_topology, 10, 11, 16)
topology = fnss.barabasi_albert_topology(100, 11, 16)
self.assertEqual(100, topology.number_of_nodes())
def barabasi_albert(self, order, m=None, m0=None, **args):
"""
Creates a scale free graph after the Barabasi-Albert model.
Args:
order (int): Number of nodes.
m (int): Number of nodes a new node connects to.
m0 (int): Number of initially connected nodes
args (dict): Attributes for property generation:
min_bw (int): Minimal value for bandwidth on edge.
max_bw (int): Maximal value for bandwidth on edge.
bandwidth (string): {uniform, power} - How bandwidth should be
generated. If uniform is chosen distribution follows uniform
distribution, if power is chosen distribution follows a
power law.
min_cpu (int): Minimal value for CPU capacity.
max_cpu (int): Maximal value for CPU capacity.
min_distance (int): Minimal length of an edge.
max_distance (int): Maximal length of an edge.
delay (float, optional): Delay per kilometer of cable length.
substrate (optional, bool): Whether it is a substrate network.
Returns: FNSS object
"""
unconnected = True
if m is None or m0 is None:
m0 = 2
m = 1
if order > 2:
m0 = int(np.random.uniform(2, order - 1))
m = int(np.random.uniform(1, m0 - 1))
vnr = None
while unconnected:
vnr = fnss.barabasi_albert_topology(n=order, m=m, m0=m0)
unconnected = not nx.is_connected(vnr)
self.remove_unnecessary_attributes(args)
self.generate_attributes(vnr, **args)
vnr.graph['model'] = literals.NETWORK_MODEL_BARABASI_ALBERT
return vnr
def test_barabasi_albert_topology_zero_seed(self):
a = fnss.barabasi_albert_topology(100, 11, 16, seed=0)
b = fnss.barabasi_albert_topology(100, 11, 16, seed=0)
self.assertEqual(set(a.edges()), set(b.edges()))
def test_barabasi_albert_topology_constant_seed(self):
a = fnss.barabasi_albert_topology(100, 11, 16, seed=1)
b = fnss.barabasi_albert_topology(100, 11, 16, seed=2)
c = fnss.barabasi_albert_topology(100, 11, 16, seed=1)
self.assertEqual(set(a.edges()), set(c.edges()))
self.assertNotEqual(set(a.edges()), set(b.edges()))
def test_barabasi_albert_topology_zero_seed(self):
a = fnss.barabasi_albert_topology(100, 11, 16, seed=0)
b = fnss.barabasi_albert_topology(100, 11, 16, seed=0)
self.assertEqual(set(a.edges()), set(b.edges()))
def test_barabasi_albert_topology_constant_seed(self):
a = fnss.barabasi_albert_topology(100, 11, 16, seed=1)
b = fnss.barabasi_albert_topology(100, 11, 16, seed=2)
c = fnss.barabasi_albert_topology(100, 11, 16, seed=1)
self.assertEqual(set(a.edges()), set(c.edges()))
self.assertNotEqual(set(a.edges()), set(b.edges()))
