def test_random_gnm_undirected_empty_graph(self):
graph = retworkx.undirected_gnm_random_graph(20, 0)
self.assertEqual(len(graph), 20)
self.assertEqual(len(graph.edges()), 0)
# passing a seed when passing zero edges has no effect
graph = retworkx.undirected_gnm_random_graph(20, 0, 44)
self.assertEqual(len(graph), 20)
self.assertEqual(len(graph.edges()), 0)
def test_random_gnm_undirected(self):
graph = retworkx.undirected_gnm_random_graph(20, 100)
self.assertEqual(len(graph), 20)
self.assertEqual(len(graph.edges()), 100)
# with other arguments equal, same seed results in same graph
graph_s1 = retworkx.undirected_gnm_random_graph(20, 100, seed=10)
graph_s2 = retworkx.undirected_gnm_random_graph(20, 100, seed=10)
self.assertEqual(graph_s1.edge_list(), graph_s2.edge_list())
def test_random_gnm_undirected_complete_graph(self):
n = 20
max_m = n * (n - 1) // 2
# passing the max edges for the passed number of nodes
graph = retworkx.undirected_gnm_random_graph(n, max_m)
self.assertEqual(len(graph), n)
self.assertEqual(len(graph.edges()), max_m)
# passing m > the max edges n(n-1)/2 still returns the max edges
graph = retworkx.undirected_gnm_random_graph(n, max_m + 1)
self.assertEqual(len(graph), n)
self.assertEqual(len(graph.edges()), max_m)
# passing a seed when passing max edges has no effect
graph = retworkx.undirected_gnm_random_graph(n, max_m, 55)
self.assertEqual(len(graph), n)
self.assertEqual(len(graph.edges()), max_m)
def test_gnm_random_against_networkx(self):
rx_graph = retworkx.undirected_gnm_random_graph(10, 13, seed=42)
nx_graph = networkx.Graph(list(rx_graph.edge_list()))
nx_matches = networkx.max_weight_matching(nx_graph)
rx_matches = retworkx.max_weight_matching(rx_graph,
verify_optimum=True)
self.compare_rx_nx_sets(rx_graph, rx_matches, nx_matches, 42, nx_graph)
def test_large_partial_random(self) -> None:
"""Test a random (partial) mapping on a large randomly generated graph"""
size = 100
# Note that graph may have "gaps" in the node counts, i.e. the numbering is noncontiguous.
graph = rx.undirected_gnm_random_graph(size, size**2 // 10)
for i in graph.node_indexes():
try:
graph.remove_edge(i, i) # Remove self-loops.
except rx.NoEdgeBetweenNodes:
continue
# Make sure the graph is connected by adding C_n
graph.add_edges_from_no_data([(i, i + 1)
for i in range(len(graph) - 1)])
swapper = ApproximateTokenSwapper(
graph) # type: ApproximateTokenSwapper[int]
# Generate a randomized permutation.
rand_perm = random.permutation(graph.nodes())
permutation = dict(zip(graph.nodes(), rand_perm))
mapping = dict(itertools.islice(permutation.items(), 0, size,
2)) # Drop every 2nd element.
out = list(swapper.map(mapping, trials=40))
util.swap_permutation([out], mapping, allow_missing_keys=True)
self.assertEqual({i: i for i in mapping.values()}, mapping)
def setup(self, num_nodes, num_edges):
random.seed(1234)
self.graph = retworkx.undirected_gnm_random_graph(num_nodes,
num_edges,
seed=4242)
for edge in self.graph.edge_indices():
self.graph.update_edge_by_index(edge, random.randint(0, 20000))
def test_random_gnm_induced_subgraph_isomorphism(self):
graph = retworkx.undirected_gnm_random_graph(50, 150)
nodes = random.sample(range(50), 25)
subgraph = graph.subgraph(nodes)
self.assertTrue(
retworkx.is_subgraph_isomorphic(graph,
subgraph,
id_order=True,
induced=True))
def test_weight_fn_raises(self):
path = os.path.join(tempfile.gettempdir(), "fail.txt")
graph = retworkx.undirected_gnm_random_graph(5, 4)
def weight_fn(edge):
raise KeyError
self.addCleanup(cleanup_file, path)
with self.assertRaises(KeyError):
graph.write_edge_list(path, weight_fn=weight_fn)
def test_random_gnm_non_induced_subgraph_isomorphism(self):
graph = retworkx.undirected_gnm_random_graph(50, 150)
nodes = random.sample(range(50), 25)
subgraph = graph.subgraph(nodes)
indexes = list(subgraph.edge_indices())
for idx in random.sample(indexes, len(indexes) // 2):
subgraph.remove_edge_from_index(idx)
self.assertTrue(
retworkx.is_subgraph_isomorphic(graph,
subgraph,
id_order=True,
induced=False))
def test_random_gnm_undirected_invalid_probability(self):
with self.assertRaises(ValueError):
retworkx.undirected_gnm_random_graph(23, -5)
def test_random_gnm_undirected_invalid_num_nodes(self):
with self.assertRaises(ValueError):
retworkx.undirected_gnm_random_graph(-23, 5)
def test_invalid_return_type_weight_fn(self):
path = os.path.join(tempfile.gettempdir(), "fail.txt")
graph = retworkx.undirected_gnm_random_graph(5, 4)
self.addCleanup(cleanup_file, path)
with self.assertRaises(TypeError):
graph.write_edge_list(path, weight_fn=lambda _: 4.5)
def setup(self, num_nodes, num_edges):
self.graph = retworkx.undirected_gnm_random_graph(num_nodes,
num_edges,
seed=42)
