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import pytest
pytest.importorskip("numpy")
import random
import networkx as nx
from networkx import lattice_reference, omega, random_reference, sigma
rng = 42
def test_random_reference():
G = nx.connected_watts_strogatz_graph(50, 6, 0.1, seed=rng)
Gr = random_reference(G, niter=1, seed=rng)
C = nx.average_clustering(G)
Cr = nx.average_clustering(Gr)
assert C > Cr
with pytest.raises(nx.NetworkXError):
next(random_reference(nx.Graph()))
with pytest.raises(nx.NetworkXNotImplemented):
next(random_reference(nx.DiGraph()))
H = nx.Graph(((0, 1), (2, 3)))
Hl = random_reference(H, niter=1, seed=rng)
def test_lattice_reference():
G = nx.connected_watts_strogatz_graph(50, 6, 1, seed=rng)
Gl = lattice_reference(G, niter=1, seed=rng)
L = nx.average_shortest_path_length(G)
Ll = nx.average_shortest_path_length(Gl)
assert Ll > L
pytest.raises(nx.NetworkXError, lattice_reference, nx.Graph())
pytest.raises(nx.NetworkXNotImplemented, lattice_reference, nx.DiGraph())
H = nx.Graph(((0, 1), (2, 3)))
Hl = lattice_reference(H, niter=1)
def test_sigma():
Gs = nx.connected_watts_strogatz_graph(50, 6, 0.1, seed=rng)
Gr = nx.connected_watts_strogatz_graph(50, 6, 1, seed=rng)
sigmas = sigma(Gs, niter=1, nrand=2, seed=rng)
sigmar = sigma(Gr, niter=1, nrand=2, seed=rng)
assert sigmar < sigmas
def test_omega():
Gl = nx.connected_watts_strogatz_graph(50, 6, 0, seed=rng)
Gr = nx.connected_watts_strogatz_graph(50, 6, 1, seed=rng)
Gs = nx.connected_watts_strogatz_graph(50, 6, 0.1, seed=rng)
omegal = omega(Gl, niter=1, nrand=1, seed=rng)
omegar = omega(Gr, niter=1, nrand=1, seed=rng)
omegas = omega(Gs, niter=1, nrand=1, seed=rng)
assert omegal < omegas and omegas < omegar
# Test that omega lies within the [-1, 1] bounds
G_barbell = nx.barbell_graph(5, 1)
G_karate = nx.karate_club_graph()
omega_barbell = nx.omega(G_barbell)
omega_karate = nx.omega(G_karate, nrand=2)
omegas = (omegal, omegar, omegas, omega_barbell, omega_karate)
for o in omegas:
assert -1 <= o <= 1
@pytest.mark.parametrize("f", (nx.random_reference, nx.lattice_reference))
def test_graph_no_edges(f):
G = nx.Graph()
G.add_nodes_from([0, 1, 2, 3])
with pytest.raises(nx.NetworkXError, match="Graph has fewer that 2 edges"):
f(G)
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