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from itertools import permutations
import pytest
import networkx as nx
from networkx.testing import almost_equal
class TestNeighborConnectivity:
def test_degree_p4(self):
G = nx.path_graph(4)
answer = {1: 2.0, 2: 1.5}
nd = nx.average_degree_connectivity(G)
assert nd == answer
D = G.to_directed()
answer = {2: 2.0, 4: 1.5}
nd = nx.average_degree_connectivity(D)
assert nd == answer
answer = {1: 2.0, 2: 1.5}
D = G.to_directed()
nd = nx.average_degree_connectivity(D, source="in", target="in")
assert nd == answer
D = G.to_directed()
nd = nx.average_degree_connectivity(D, source="in", target="in")
assert nd == answer
def test_degree_p4_weighted(self):
G = nx.path_graph(4)
G[1][2]["weight"] = 4
answer = {1: 2.0, 2: 1.8}
nd = nx.average_degree_connectivity(G, weight="weight")
assert nd == answer
answer = {1: 2.0, 2: 1.5}
nd = nx.average_degree_connectivity(G)
assert nd == answer
D = G.to_directed()
answer = {2: 2.0, 4: 1.8}
nd = nx.average_degree_connectivity(D, weight="weight")
assert nd == answer
answer = {1: 2.0, 2: 1.8}
D = G.to_directed()
nd = nx.average_degree_connectivity(
D, weight="weight", source="in", target="in"
)
assert nd == answer
D = G.to_directed()
nd = nx.average_degree_connectivity(
D, source="in", target="out", weight="weight"
)
assert nd == answer
def test_weight_keyword(self):
G = nx.path_graph(4)
G[1][2]["other"] = 4
answer = {1: 2.0, 2: 1.8}
nd = nx.average_degree_connectivity(G, weight="other")
assert nd == answer
answer = {1: 2.0, 2: 1.5}
nd = nx.average_degree_connectivity(G, weight=None)
assert nd == answer
D = G.to_directed()
answer = {2: 2.0, 4: 1.8}
nd = nx.average_degree_connectivity(D, weight="other")
assert nd == answer
answer = {1: 2.0, 2: 1.8}
D = G.to_directed()
nd = nx.average_degree_connectivity(D, weight="other", source="in", target="in")
assert nd == answer
D = G.to_directed()
nd = nx.average_degree_connectivity(D, weight="other", source="in", target="in")
assert nd == answer
def test_degree_barrat(self):
G = nx.star_graph(5)
G.add_edges_from([(5, 6), (5, 7), (5, 8), (5, 9)])
G[0][5]["weight"] = 5
nd = nx.average_degree_connectivity(G)[5]
assert nd == 1.8
nd = nx.average_degree_connectivity(G, weight="weight")[5]
assert almost_equal(nd, 3.222222, places=5)
nd = nx.k_nearest_neighbors(G, weight="weight")[5]
assert almost_equal(nd, 3.222222, places=5)
def test_zero_deg(self):
G = nx.DiGraph()
G.add_edge(1, 2)
G.add_edge(1, 3)
G.add_edge(1, 4)
c = nx.average_degree_connectivity(G)
assert c == {1: 0, 3: 1}
c = nx.average_degree_connectivity(G, source="in", target="in")
assert c == {0: 0, 1: 0}
c = nx.average_degree_connectivity(G, source="in", target="out")
assert c == {0: 0, 1: 3}
c = nx.average_degree_connectivity(G, source="in", target="in+out")
assert c == {0: 0, 1: 3}
c = nx.average_degree_connectivity(G, source="out", target="out")
assert c == {0: 0, 3: 0}
c = nx.average_degree_connectivity(G, source="out", target="in")
assert c == {0: 0, 3: 1}
c = nx.average_degree_connectivity(G, source="out", target="in+out")
assert c == {0: 0, 3: 1}
def test_in_out_weight(self):
G = nx.DiGraph()
G.add_edge(1, 2, weight=1)
G.add_edge(1, 3, weight=1)
G.add_edge(3, 1, weight=1)
for s, t in permutations(["in", "out", "in+out"], 2):
c = nx.average_degree_connectivity(G, source=s, target=t)
cw = nx.average_degree_connectivity(G, source=s, target=t, weight="weight")
assert c == cw
def test_invalid_source(self):
with pytest.raises(ValueError):
G = nx.DiGraph()
nx.average_degree_connectivity(G, source="bogus")
def test_invalid_target(self):
with pytest.raises(ValueError):
G = nx.DiGraph()
nx.average_degree_connectivity(G, target="bogus")
def test_single_node(self):
# TODO Is this really the intended behavior for providing a
# single node as the argument `nodes`? Shouldn't the function
# just return the connectivity value itself?
G = nx.trivial_graph()
conn = nx.average_degree_connectivity(G, nodes=0)
assert conn == {0: 0}
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