def test_misshapen_matrices(self):
data = [[3, 2, 0], [2, 0, 1]] # this is utter gibberish
with self.assertRaises(ValueError):
_validate_and_build_edge_list(
graph=np.array(data),
is_weighted=True,
weight_attribute="weight",
check_directed=True,
weight_default=1.0,
)
with self.assertRaises(ValueError):
_validate_and_build_edge_list(
graph=scipy.sparse.csr_matrix(data),
is_weighted=True,
weight_attribute="weight",
check_directed=True,
weight_default=1.0,
)
def test_empty_edge_list(self):
edges = []
results = _validate_and_build_edge_list(
graph=edges,
is_weighted=True,
weight_attribute="weight",
check_directed=False,
weight_default=1.0,
)
self.assertEqual([], results[1])
def test_unweighted_nx(self):
graph = nx.Graph()
graph.add_edge("dwayne", "nick")
graph.add_edge("nick", "ben")
with self.assertRaises(ValueError):
_validate_and_build_edge_list(
graph=graph,
is_weighted=True,
weight_attribute="weight",
check_directed=False,
weight_default=None,
)
_, edges = _validate_and_build_edge_list(
graph=graph,
is_weighted=True,
weight_attribute="weight",
check_directed=False,
weight_default=3.33333,
)
self.assertEqual(
[("dwayne", "nick", 3.33333), ("nick", "ben", 3.33333)],
edges,
)
graph.add_edge("salad", "sandwich", weight=100)
_, edges = _validate_and_build_edge_list(
graph=graph,
is_weighted=True,
weight_attribute="weight",
check_directed=False,
weight_default=3.33333,
)
self.assertEqual(
[
("dwayne", "nick", 3.33333),
("nick", "ben", 3.33333),
("salad", "sandwich", 100),
],
edges,
)
def test_empty_adj_matrices(self):
dense = np.array([])
with self.assertRaises(ValueError):
_validate_and_build_edge_list(
graph=dense,
is_weighted=True,
weight_attribute="weight",
check_directed=True,
weight_default=1.0,
)
sparse = scipy.sparse.csr_matrix([])
with self.assertRaises(ValueError):
_validate_and_build_edge_list(
graph=sparse,
is_weighted=True,
weight_attribute="weight",
check_directed=True,
weight_default=1.0,
)
def test_assert_wrong_types_in_tuples(self):
edges = [(True, 4, "sandwich")]
with self.assertRaises(ValueError):
_validate_and_build_edge_list(
graph=edges,
is_weighted=True,
weight_attribute="weight",
check_directed=False,
weight_default=1.0,
)
edges = [(True, False, 3.2)]
results = _validate_and_build_edge_list(
graph=edges,
is_weighted=True,
weight_attribute="weight",
check_directed=False,
weight_default=1.0,
)
self.assertEqual([("True", "False", 3.2)], results[1])
def test_valid_nx(self):
graph = add_edges_to_graph(nx.Graph())
expected = [("nick", "dwayne", 2.2), ("dwayne", "ben", 0.001)]
_, edges = _validate_and_build_edge_list(
graph=graph,
is_weighted=True,
weight_attribute="weight",
check_directed=False,
weight_default=1.0,
)
self.assertEqual(expected, edges)
with self.assertRaises(TypeError):
graph = add_edges_to_graph(nx.DiGraph())
_validate_and_build_edge_list(
graph=graph,
is_weighted=True,
weight_attribute="weight",
check_directed=False,
weight_default=1.0,
)
with self.assertRaises(TypeError):
graph = add_edges_to_graph(nx.MultiGraph())
_validate_and_build_edge_list(
graph=graph,
is_weighted=True,
weight_attribute="weight",
check_directed=False,
weight_default=1.0,
)
with self.assertRaises(TypeError):
graph = add_edges_to_graph(nx.MultiDiGraph())
_validate_and_build_edge_list(
graph=graph,
is_weighted=True,
weight_attribute="weight",
check_directed=False,
weight_default=1.0,
)
def test_matrices(self):
graph = add_edges_to_graph(nx.Graph())
di_graph = add_edges_to_graph(nx.DiGraph())
dense_undirected = nx.to_numpy_array(graph)
dense_directed = nx.to_numpy_array(di_graph)
sparse_undirected = nx.to_scipy_sparse_matrix(graph)
sparse_directed = nx.to_scipy_sparse_matrix(di_graph)
expected = [("0", "1", 2.2), ("1", "2", 0.001)]
_, edges = _validate_and_build_edge_list(
graph=dense_undirected,
is_weighted=True,
weight_attribute="weight",
check_directed=True,
weight_default=1.0,
)
self.assertEqual(expected, edges)
_, edges = _validate_and_build_edge_list(
graph=sparse_undirected,
is_weighted=True,
weight_attribute="weight",
check_directed=True,
weight_default=1.0,
)
self.assertEqual(expected, edges)
with self.assertRaises(ValueError):
_validate_and_build_edge_list(
graph=dense_directed,
is_weighted=True,
weight_attribute="weight",
check_directed=True,
weight_default=1.0,
)
with self.assertRaises(ValueError):
_validate_and_build_edge_list(
graph=sparse_directed,
is_weighted=True,
weight_attribute="weight",
check_directed=True,
weight_default=1.0,
)
