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import networkx as nx
from networkx.testing import almost_equal
class TestSubsetBetweennessCentrality:
def test_K5(self):
"""Betweenness Centrality Subset: K5"""
G = nx.complete_graph(5)
b = nx.betweenness_centrality_subset(
G, sources=[0], targets=[1, 3], weight=None
)
b_answer = {0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0}
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
def test_P5_directed(self):
"""Betweenness Centrality Subset: P5 directed"""
G = nx.DiGraph()
nx.add_path(G, range(5))
b_answer = {0: 0, 1: 1, 2: 1, 3: 0, 4: 0, 5: 0}
b = nx.betweenness_centrality_subset(G, sources=[0], targets=[3], weight=None)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
def test_P5(self):
"""Betweenness Centrality Subset: P5"""
G = nx.Graph()
nx.add_path(G, range(5))
b_answer = {0: 0, 1: 0.5, 2: 0.5, 3: 0, 4: 0, 5: 0}
b = nx.betweenness_centrality_subset(G, sources=[0], targets=[3], weight=None)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
def test_P5_multiple_target(self):
"""Betweenness Centrality Subset: P5 multiple target"""
G = nx.Graph()
nx.add_path(G, range(5))
b_answer = {0: 0, 1: 1, 2: 1, 3: 0.5, 4: 0, 5: 0}
b = nx.betweenness_centrality_subset(
G, sources=[0], targets=[3, 4], weight=None
)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
def test_box(self):
"""Betweenness Centrality Subset: box"""
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)])
b_answer = {0: 0, 1: 0.25, 2: 0.25, 3: 0}
b = nx.betweenness_centrality_subset(G, sources=[0], targets=[3], weight=None)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
def test_box_and_path(self):
"""Betweenness Centrality Subset: box and path"""
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3), (3, 4), (4, 5)])
b_answer = {0: 0, 1: 0.5, 2: 0.5, 3: 0.5, 4: 0, 5: 0}
b = nx.betweenness_centrality_subset(
G, sources=[0], targets=[3, 4], weight=None
)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
def test_box_and_path2(self):
"""Betweenness Centrality Subset: box and path multiple target"""
G = nx.Graph()
G.add_edges_from([(0, 1), (1, 2), (2, 3), (1, 20), (20, 3), (3, 4)])
b_answer = {0: 0, 1: 1.0, 2: 0.5, 20: 0.5, 3: 0.5, 4: 0}
b = nx.betweenness_centrality_subset(
G, sources=[0], targets=[3, 4], weight=None
)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
def test_diamond_multi_path(self):
"""Betweenness Centrality Subset: Diamond Multi Path"""
G = nx.Graph()
G.add_edges_from(
[
(1, 2),
(1, 3),
(1, 4),
(1, 5),
(1, 10),
(10, 11),
(11, 12),
(12, 9),
(2, 6),
(3, 6),
(4, 6),
(5, 7),
(7, 8),
(6, 8),
(8, 9),
]
)
b = nx.betweenness_centrality_subset(G, sources=[1], targets=[9], weight=None)
expected_b = {
1: 0,
2: 1.0 / 10,
3: 1.0 / 10,
4: 1.0 / 10,
5: 1.0 / 10,
6: 3.0 / 10,
7: 1.0 / 10,
8: 4.0 / 10,
9: 0,
10: 1.0 / 10,
11: 1.0 / 10,
12: 1.0 / 10,
}
for n in sorted(G):
assert almost_equal(b[n], expected_b[n])
class TestBetweennessCentralitySources:
def test_K5(self):
"""Betweenness Centrality Sources: K5"""
G = nx.complete_graph(5)
b = nx.betweenness_centrality_source(G, weight=None, normalized=False)
b_answer = {0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0}
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
def test_P3(self):
"""Betweenness Centrality Sources: P3"""
G = nx.path_graph(3)
b_answer = {0: 0.0, 1: 1.0, 2: 0.0}
b = nx.betweenness_centrality_source(G, weight=None, normalized=True)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
class TestEdgeSubsetBetweennessCentrality:
def test_K5(self):
"""Edge betweenness subset centrality: K5"""
G = nx.complete_graph(5)
b = nx.edge_betweenness_centrality_subset(
G, sources=[0], targets=[1, 3], weight=None
)
b_answer = dict.fromkeys(G.edges(), 0)
b_answer[(0, 3)] = b_answer[(0, 1)] = 0.5
for n in sorted(G.edges()):
assert almost_equal(b[n], b_answer[n])
def test_P5_directed(self):
"""Edge betweenness subset centrality: P5 directed"""
G = nx.DiGraph()
nx.add_path(G, range(5))
b_answer = dict.fromkeys(G.edges(), 0)
b_answer[(0, 1)] = b_answer[(1, 2)] = b_answer[(2, 3)] = 1
b = nx.edge_betweenness_centrality_subset(
G, sources=[0], targets=[3], weight=None
)
for n in sorted(G.edges()):
assert almost_equal(b[n], b_answer[n])
def test_P5(self):
"""Edge betweenness subset centrality: P5"""
G = nx.Graph()
nx.add_path(G, range(5))
b_answer = dict.fromkeys(G.edges(), 0)
b_answer[(0, 1)] = b_answer[(1, 2)] = b_answer[(2, 3)] = 0.5
b = nx.edge_betweenness_centrality_subset(
G, sources=[0], targets=[3], weight=None
)
for n in sorted(G.edges()):
assert almost_equal(b[n], b_answer[n])
def test_P5_multiple_target(self):
"""Edge betweenness subset centrality: P5 multiple target"""
G = nx.Graph()
nx.add_path(G, range(5))
b_answer = dict.fromkeys(G.edges(), 0)
b_answer[(0, 1)] = b_answer[(1, 2)] = b_answer[(2, 3)] = 1
b_answer[(3, 4)] = 0.5
b = nx.edge_betweenness_centrality_subset(
G, sources=[0], targets=[3, 4], weight=None
)
for n in sorted(G.edges()):
assert almost_equal(b[n], b_answer[n])
def test_box(self):
"""Edge betweenness subset centrality: box"""
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)])
b_answer = dict.fromkeys(G.edges(), 0)
b_answer[(0, 1)] = b_answer[(0, 2)] = 0.25
b_answer[(1, 3)] = b_answer[(2, 3)] = 0.25
b = nx.edge_betweenness_centrality_subset(
G, sources=[0], targets=[3], weight=None
)
for n in sorted(G.edges()):
assert almost_equal(b[n], b_answer[n])
def test_box_and_path(self):
"""Edge betweenness subset centrality: box and path"""
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3), (3, 4), (4, 5)])
b_answer = dict.fromkeys(G.edges(), 0)
b_answer[(0, 1)] = b_answer[(0, 2)] = 0.5
b_answer[(1, 3)] = b_answer[(2, 3)] = 0.5
b_answer[(3, 4)] = 0.5
b = nx.edge_betweenness_centrality_subset(
G, sources=[0], targets=[3, 4], weight=None
)
for n in sorted(G.edges()):
assert almost_equal(b[n], b_answer[n])
def test_box_and_path2(self):
"""Edge betweenness subset centrality: box and path multiple target"""
G = nx.Graph()
G.add_edges_from([(0, 1), (1, 2), (2, 3), (1, 20), (20, 3), (3, 4)])
b_answer = dict.fromkeys(G.edges(), 0)
b_answer[(0, 1)] = 1.0
b_answer[(1, 20)] = b_answer[(3, 20)] = 0.5
b_answer[(1, 2)] = b_answer[(2, 3)] = 0.5
b_answer[(3, 4)] = 0.5
b = nx.edge_betweenness_centrality_subset(
G, sources=[0], targets=[3, 4], weight=None
)
for n in sorted(G.edges()):
assert almost_equal(b[n], b_answer[n])
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