def test_clear_delays(self):
topo = fnss.star_topology(12)
fnss.set_delays_constant(topo, 1, 'ms', None)
self.assertEqual(topo.number_of_edges(),
len(nx.get_edge_attributes(topo, 'delay')))
fnss.clear_delays(topo)
self.assertEqual(0, len(nx.get_edge_attributes(topo, 'delay')))
def test_clear_delays(self):
topo = fnss.star_topology(12)
fnss.set_delays_constant(topo, 1, 'ms', None)
self.assertEqual(topo.number_of_edges(),
len(nx.get_edge_attributes(topo, 'delay')))
fnss.clear_delays(topo)
self.assertEqual(0, len(nx.get_edge_attributes(topo, 'delay')))
def star(self, order, **args):
"""
Creates a Star-Topology
Args:
order (int): Number of 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
"""
vnr = fnss.star_topology(order - 1)
self.remove_unnecessary_attributes(args)
self.generate_attributes(vnr, **args)
vnr.graph['model'] = literals.NETWORK_MODEL_STAR
return vnr
def test_clear_weights(self):
# create new topology to avoid parameters pollution
G = fnss.star_topology(12)
fnss.set_weights_constant(G, 3, None)
self.assertEqual(G.number_of_edges(),
len(nx.get_edge_attributes(G, 'weight')))
fnss.clear_weights(G)
self.assertEqual(0, len(nx.get_edge_attributes(G, 'weight')))
def test_clear_weights(self):
# create new topology to avoid parameters pollution
G = fnss.star_topology(12)
fnss.set_weights_constant(G, 3, None)
self.assertEqual(G.number_of_edges(),
len(nx.get_edge_attributes(G, 'weight')))
fnss.clear_weights(G)
self.assertEqual(0, len(nx.get_edge_attributes(G, 'weight')))
def test_star_connectivity(n):
G = fnss.star_topology(n)
self.assertEqual(n + 1, G.number_of_nodes())
self.assertEqual(n, G.number_of_edges())
self.assertEqual('root', G.node[0]['type'])
for i in range(1, n + 1):
self.assertEqual('leaf', G.node[i]['type'])
self.assertTrue(G.has_edge(i, 0))
self.assertTrue(G.has_edge(0, i))
def test_star_connectivity(n):
G = fnss.star_topology(n)
self.assertEquals(n + 1, G.number_of_nodes())
self.assertEquals(n, G.number_of_edges())
self.assertEquals('root', G.node[0]['type'])
for i in range(1, n + 1):
self.assertEquals('leaf', G.node[i]['type'])
self.assertTrue(G.has_edge(i, 0))
self.assertTrue(G.has_edge(0, i))
def test_fan_in_out_capacities_undirected(self):
topology = fnss.star_topology(3)
fnss.set_capacities_constant(topology, 10, 'Mbps')
in_cap, out_cap = fnss.fan_in_out_capacities(topology)
self.assertEquals({0: 30, 1: 10, 2: 10, 3: 10}, in_cap)
self.assertEquals(in_cap, out_cap)
def test_fan_in_out_capacities_undirected(self):
topology = fnss.star_topology(3)
fnss.set_capacities_constant(topology, 10, 'Mbps')
in_cap, out_cap = fnss.fan_in_out_capacities(topology)
self.assertEqual({0: 30, 1: 10, 2: 10, 3: 10}, in_cap)
self.assertEqual(in_cap, out_cap)
