def phase1(self):
# choose node pairs from (degree) weighted distribution
while sum(self.remaining_degree.values()) >= 2 * self.dmax**2:
u,v = sorted(random_weighted_sample(self.remaining_degree, 2))
if self.graph.has_edge(u,v):
continue
if random.random() < self.p(u,v): # accept edge
self.graph.add_edge(u,v)
self.update_remaining(u,v)
def phase1(self):
# choose node pairs from (degree) weighted distribution
while sum(self.remaining_degree.values()) >= 2 * self.dmax**2:
u,v = sorted(random_weighted_sample(self.remaining_degree, 2))
if self.graph.has_edge(u,v):
continue
if random.random() < self.p(u,v): # accept edge
self.graph.add_edge(u,v)
self.update_remaining(u,v)
def generate_sf(n, m0, m):
"""
Create Barabási–Albert graph (working around https://github.com/networkx/networkx/issues/3281)
"""
G = nx.complete_graph(m0)
while len(G) < n:
degrees = {node: val for (node, val) in G.degree()}
node = len(G)
G.add_node(node)
targets = random_weighted_sample(degrees, m)
G.add_edges_from(zip([node] * m, targets))
return G
def test_random_weighted_sample():
mapping = {'a': 10, 'b': 20}
s = random_weighted_sample(mapping, 2)
assert_equal(sorted(s), sorted(mapping.keys()))
assert_raises(ValueError, random_weighted_sample, mapping, 3)
def test_random_weighted_sample():
mapping = {"a": 10, "b": 20}
s = random_weighted_sample(mapping, 2, seed=1)
s = random_weighted_sample(mapping, 2)
assert sorted(s) == sorted(mapping.keys())
pytest.raises(ValueError, random_weighted_sample, mapping, 3)
def test_random_weighted_sample():
mapping = {'a': 10, 'b': 20}
s = random_weighted_sample(mapping, 2)
assert_equal(sorted(s), sorted(mapping.keys()))
assert_raises(ValueError, random_weighted_sample, mapping, 3)
