def test_from_igraph_invalid_attribute():
n = 100
m = 500
K = np.zeros((n, n))
for _ in range(m):
e = np.random.choice(n, 2, replace=False)
K[e[0], e[1]] = K[e[1], e[0]] = 1
g = igraph.Graph.Adjacency(K.tolist())
G = graphtools.from_igraph(g, attribute="invalid")
def test_from_igraph_weighted():
n = 100
m = 500
K = np.zeros((n, n))
for _ in range(m):
e = np.random.choice(n, 2, replace=False)
K[e[0], e[1]] = K[e[1], e[0]] = np.random.uniform(0, 1)
g = igraph.Graph.Weighted_Adjacency(K.tolist())
G = graphtools.from_igraph(g)
G2 = graphtools.Graph(K, precomputed="adjacency")
assert np.all(G.K == G2.K)
def test_from_igraph():
n = 100
m = 500
K = np.zeros((n, n))
for _ in range(m):
e = np.random.choice(n, 2, replace=False)
K[e[0], e[1]] = K[e[1], e[0]] = 1
g = igraph.Graph.Adjacency(K.tolist())
G = graphtools.from_igraph(g, attribute=None)
G2 = graphtools.Graph(K, precomputed="adjacency")
assert np.all(G.K == G2.K)
def test_from_igraph_invalid_attribute():
with assert_warns_message(
UserWarning,
"Edge attribute invalid not found. Returning unweighted graph"):
n = 100
m = 500
K = np.zeros((n, n))
for _ in range(m):
e = np.random.choice(n, 2, replace=False)
K[e[0], e[1]] = K[e[1], e[0]] = 1
g = igraph.Graph.Adjacency(K.tolist())
G = graphtools.from_igraph(g, attribute="invalid")
def test_from_igraph_invalid_precomputed():
with assert_warns_message(
UserWarning,
"Cannot build graph from igraph with precomputed=affinity. Use 'adjacency' instead.",
):
n = 100
m = 500
K = np.zeros((n, n))
for _ in range(m):
e = np.random.choice(n, 2, replace=False)
K[e[0], e[1]] = K[e[1], e[0]] = 1
g = igraph.Graph.Adjacency(K.tolist())
G = graphtools.from_igraph(g, attribute=None, precomputed="affinity")