def test_generate_random_graph_erdos_renyi(self):
# Given
num_nodes = 3
target_graph = nx.Graph()
target_graph.add_edges_from([(0, 1), (1, 2), (0, 2)])
# When
graph = generate_random_graph_erdos_renyi(num_nodes, 1)
# Then
assert compare_graphs(graph, target_graph)
# Given
num_nodes = 3
target_graph = nx.Graph()
# When
graph = generate_random_graph_erdos_renyi(num_nodes, 1)
# Then
assert compare_graphs(graph, target_graph)
# Given
num_nodes = 20
weight_sampler = uniform_sampler()
# When
graph = generate_random_graph_erdos_renyi(num_nodes, 0.8,
weight_sampler)
def test_generate_random_regular_graph(self):
# Given
num_nodes = 4
degree = 2
# When
graph = generate_random_regular_graph(num_nodes, degree)
# Then
for n in graph.nodes():
node_in_edge = [n in e for e in graph.edges()]
assert sum(node_in_edge) == degree
# Given
num_nodes = 20
degree = 3
weight_sampler = uniform_sampler()
# When
graph = generate_random_regular_graph(num_nodes, degree,
weight_sampler)
# Then
for edge in graph.edges:
assert "weight" in graph.edges[edge].keys()
assert len(graph.nodes) == num_nodes
def test_generate_barbell_graph(self):
n_vertices = 4
graph = generate_barbell_graph(n_vertices, uniform_sampler())
for edge in graph.edges:
assert "weight" in graph.edges[edge].keys()
assert len(graph.nodes) == n_vertices * 2
def test_seed(self):
# Given
num_nodes = 4
degree = 2
seed = 123
weight_sampler = uniform_sampler()
target_graph = generate_random_regular_graph(
num_nodes, degree, weight_sampler=weight_sampler, seed=seed)
# When
graph = generate_random_regular_graph(num_nodes,
degree,
weight_sampler=uniform_sampler(),
seed=seed)
# Then
assert compare_graphs(graph, target_graph)
def test_generate_ladder_graph(self):
# Given
length_of_ladder = 4
weight_sampler = uniform_sampler()
# When
graph = generate_ladder_graph(length_of_ladder, weight_sampler)
# Then
for edge in graph.edges:
assert "weight" in graph.edges[edge].keys()
assert len(graph.nodes) == length_of_ladder * 2
def test_generate_caveman_graph(self):
# Given
number_of_cliques = 3
size_of_cliques = 4
weight_sampler = uniform_sampler()
# When
graph = generate_caveman_graph(number_of_cliques, size_of_cliques,
weight_sampler)
# Then
for edge in graph.edges:
assert "weight" in graph.edges[edge].keys()
assert len(graph.nodes) == number_of_cliques * 4
"num_nodes": 10,
"random_weights": True
}
# When
graph = generate_graph_from_specs(specs)
# Then
for edge in graph.edges:
assert "weight" in graph.edges[edge].keys()
@pytest.mark.parametrize(
"sampler",
[
uniform_sampler(),
uniform_sampler(2, 3),
constant_sampler(-1),
normal_sampler(2, 1),
choice_sampler([2, 1, 6]),
],
)
class TestSamplers:
def test_generates_numbers(self, sampler):
assert isinstance(next(sampler), numbers.Number)
def test_can_be_reused(self, sampler):
next(sampler)
next(sampler)
def test_generates_same_number_when_seeded(self, sampler):