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import pytest
import networkx as nx
class TestAverageNeighbor:
def test_degree_p4(self):
G = nx.path_graph(4)
answer = {0: 2, 1: 1.5, 2: 1.5, 3: 2}
nd = nx.average_neighbor_degree(G)
assert nd == answer
D = G.to_directed()
nd = nx.average_neighbor_degree(D)
assert nd == answer
D = nx.DiGraph(G.edges(data=True))
nd = nx.average_neighbor_degree(D)
assert nd == {0: 1, 1: 1, 2: 0, 3: 0}
nd = nx.average_neighbor_degree(D, "in", "out")
assert nd == {0: 0, 1: 1, 2: 1, 3: 1}
nd = nx.average_neighbor_degree(D, "out", "in")
assert nd == {0: 1, 1: 1, 2: 1, 3: 0}
nd = nx.average_neighbor_degree(D, "in", "in")
assert nd == {0: 0, 1: 0, 2: 1, 3: 1}
def test_degree_p4_weighted(self):
G = nx.path_graph(4)
G[1][2]["weight"] = 4
answer = {0: 2, 1: 1.8, 2: 1.8, 3: 2}
nd = nx.average_neighbor_degree(G, weight="weight")
assert nd == answer
D = G.to_directed()
nd = nx.average_neighbor_degree(D, weight="weight")
assert nd == answer
D = nx.DiGraph(G.edges(data=True))
print(D.edges(data=True))
nd = nx.average_neighbor_degree(D, weight="weight")
assert nd == {0: 1, 1: 1, 2: 0, 3: 0}
nd = nx.average_neighbor_degree(D, "out", "out", weight="weight")
assert nd == {0: 1, 1: 1, 2: 0, 3: 0}
nd = nx.average_neighbor_degree(D, "in", "in", weight="weight")
assert nd == {0: 0, 1: 0, 2: 1, 3: 1}
nd = nx.average_neighbor_degree(D, "in", "out", weight="weight")
assert nd == {0: 0, 1: 1, 2: 1, 3: 1}
nd = nx.average_neighbor_degree(D, "out", "in", weight="weight")
assert nd == {0: 1, 1: 1, 2: 1, 3: 0}
D = G.to_directed()
nd = nx.average_neighbor_degree(D, weight="weight")
assert nd == answer
nd = nx.average_neighbor_degree(D, source="out", target="out", weight="weight")
assert nd == answer
D = G.to_directed()
nd = nx.average_neighbor_degree(D, source="in", target="in", weight="weight")
assert nd == answer
def test_degree_k4(self):
G = nx.complete_graph(4)
answer = {0: 3, 1: 3, 2: 3, 3: 3}
nd = nx.average_neighbor_degree(G)
assert nd == answer
D = G.to_directed()
nd = nx.average_neighbor_degree(D)
assert nd == answer
D = G.to_directed()
nd = nx.average_neighbor_degree(D)
assert nd == answer
D = G.to_directed()
nd = nx.average_neighbor_degree(D, source="in", target="in")
assert nd == answer
def test_degree_k4_nodes(self):
G = nx.complete_graph(4)
answer = {1: 3.0, 2: 3.0}
nd = nx.average_neighbor_degree(G, nodes=[1, 2])
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_neighbor_degree(G)[5]
assert nd == 1.8
nd = nx.average_neighbor_degree(G, weight="weight")[5]
assert nd == pytest.approx(3.222222, abs=1e-5)
def test_error_invalid_source_target(self):
G = nx.path_graph(4)
with pytest.raises(nx.NetworkXError):
nx.average_neighbor_degree(G, "error")
with pytest.raises(nx.NetworkXError):
nx.average_neighbor_degree(G, "in", "error")
G = G.to_directed()
with pytest.raises(nx.NetworkXError):
nx.average_neighbor_degree(G, "error")
with pytest.raises(nx.NetworkXError):
nx.average_neighbor_degree(G, "in", "error")
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