Why Gemfury?
Push, build, and install
RubyGems
npm packages
Python packages
Maven artifacts
PHP packages
Go Modules
Debian packages
RPM packages
NuGet packages
cytora
Repository URL to install this package:
|
Version:
2.1 ▾
|
#!/usr/bin/env python
from nose.tools import *
import networkx as nx
def weighted_G():
G = nx.Graph()
G.add_edge(0, 1, weight=3)
G.add_edge(0, 2, weight=2)
G.add_edge(0, 3, weight=6)
G.add_edge(0, 4, weight=4)
G.add_edge(1, 3, weight=5)
G.add_edge(1, 5, weight=5)
G.add_edge(2, 4, weight=1)
G.add_edge(3, 4, weight=2)
G.add_edge(3, 5, weight=1)
G.add_edge(4, 5, weight=4)
return G
class TestBetweennessCentrality(object):
def test_K5(self):
"""Betweenness centrality: K5"""
G = nx.complete_graph(5)
b = nx.betweenness_centrality(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_K5_endpoints(self):
"""Betweenness centrality: K5 endpoints"""
G = nx.complete_graph(5)
b = nx.betweenness_centrality(G,
weight=None,
normalized=False,
endpoints=True)
b_answer = {0: 4.0, 1: 4.0, 2: 4.0, 3: 4.0, 4: 4.0}
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
def test_P3_normalized(self):
"""Betweenness centrality: P3 normalized"""
G = nx.path_graph(3)
b = nx.betweenness_centrality(G,
weight=None,
normalized=True)
b_answer = {0: 0.0, 1: 1.0, 2: 0.0}
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
def test_P3(self):
"""Betweenness centrality: P3"""
G = nx.path_graph(3)
b_answer = {0: 0.0, 1: 1.0, 2: 0.0}
b = nx.betweenness_centrality(G,
weight=None,
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
def test_P3_endpoints(self):
"""Betweenness centrality: P3 endpoints"""
G = nx.path_graph(3)
b_answer = {0: 2.0, 1: 3.0, 2: 2.0}
b = nx.betweenness_centrality(G,
weight=None,
normalized=False,
endpoints=True)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
def test_krackhardt_kite_graph(self):
"""Betweenness centrality: Krackhardt kite graph"""
G = nx.krackhardt_kite_graph()
b_answer = {0: 1.667, 1: 1.667, 2: 0.000, 3: 7.333, 4: 0.000,
5: 16.667, 6: 16.667, 7: 28.000, 8: 16.000, 9: 0.000}
for b in b_answer:
b_answer[b] /= 2.0
b = nx.betweenness_centrality(G,
weight=None,
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
def test_krackhardt_kite_graph_normalized(self):
"""Betweenness centrality: Krackhardt kite graph normalized"""
G = nx.krackhardt_kite_graph()
b_answer = {0: 0.023, 1: 0.023, 2: 0.000, 3: 0.102, 4: 0.000,
5: 0.231, 6: 0.231, 7: 0.389, 8: 0.222, 9: 0.000}
b = nx.betweenness_centrality(G,
weight=None,
normalized=True)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
def test_florentine_families_graph(self):
"""Betweenness centrality: Florentine families graph"""
G = nx.florentine_families_graph()
b_answer =\
{'Acciaiuoli': 0.000,
'Albizzi': 0.212,
'Barbadori': 0.093,
'Bischeri': 0.104,
'Castellani': 0.055,
'Ginori': 0.000,
'Guadagni': 0.255,
'Lamberteschi': 0.000,
'Medici': 0.522,
'Pazzi': 0.000,
'Peruzzi': 0.022,
'Ridolfi': 0.114,
'Salviati': 0.143,
'Strozzi': 0.103,
'Tornabuoni': 0.092}
b = nx.betweenness_centrality(G,
weight=None,
normalized=True)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
def test_ladder_graph(self):
"""Betweenness centrality: Ladder graph"""
G = nx.Graph() # ladder_graph(3)
G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3),
(2, 4), (4, 5), (3, 5)])
b_answer = {0: 1.667, 1: 1.667, 2: 6.667,
3: 6.667, 4: 1.667, 5: 1.667}
for b in b_answer:
b_answer[b] /= 2.0
b = nx.betweenness_centrality(G,
weight=None,
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
def test_disconnected_path(self):
"""Betweenness centrality: disconnected path"""
G = nx.Graph()
nx.add_path(G, [0, 1, 2])
nx.add_path(G, [3, 4, 5, 6])
b_answer = {0: 0, 1: 1, 2: 0, 3: 0, 4: 2, 5: 2, 6: 0}
b = nx.betweenness_centrality(G,
weight=None,
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
def test_disconnected_path_endpoints(self):
"""Betweenness centrality: disconnected path endpoints"""
G = nx.Graph()
nx.add_path(G, [0, 1, 2])
nx.add_path(G, [3, 4, 5, 6])
b_answer = {0: 2, 1: 3, 2: 2, 3: 3, 4: 5, 5: 5, 6: 3}
b = nx.betweenness_centrality(G,
weight=None,
normalized=False,
endpoints=True)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
def test_directed_path(self):
"""Betweenness centrality: directed path"""
G = nx.DiGraph()
nx.add_path(G, [0, 1, 2])
b = nx.betweenness_centrality(G,
weight=None,
normalized=False)
b_answer = {0: 0.0, 1: 1.0, 2: 0.0}
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
def test_directed_path_normalized(self):
"""Betweenness centrality: directed path normalized"""
G = nx.DiGraph()
nx.add_path(G, [0, 1, 2])
b = nx.betweenness_centrality(G,
weight=None,
normalized=True)
b_answer = {0: 0.0, 1: 0.5, 2: 0.0}
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
class TestWeightedBetweennessCentrality(object):
def test_K5(self):
"""Weighted betweenness centrality: K5"""
G = nx.complete_graph(5)
b = nx.betweenness_centrality(G,
weight='weight',
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_normalized(self):
"""Weighted betweenness centrality: P3 normalized"""
G = nx.path_graph(3)
b = nx.betweenness_centrality(G,
weight='weight',
normalized=True)
b_answer = {0: 0.0, 1: 1.0, 2: 0.0}
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
def test_P3(self):
"""Weighted betweenness centrality: P3"""
G = nx.path_graph(3)
b_answer = {0: 0.0, 1: 1.0, 2: 0.0}
b = nx.betweenness_centrality(G,
weight='weight',
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
def test_krackhardt_kite_graph(self):
"""Weighted betweenness centrality: Krackhardt kite graph"""
G = nx.krackhardt_kite_graph()
b_answer = {0: 1.667, 1: 1.667, 2: 0.000, 3: 7.333, 4: 0.000,
5: 16.667, 6: 16.667, 7: 28.000, 8: 16.000, 9: 0.000}
for b in b_answer:
b_answer[b] /= 2.0
b = nx.betweenness_centrality(G,
weight='weight',
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
def test_krackhardt_kite_graph_normalized(self):
"""Weighted betweenness centrality:
Krackhardt kite graph normalized
"""
G = nx.krackhardt_kite_graph()
b_answer = {0: 0.023, 1: 0.023, 2: 0.000, 3: 0.102, 4: 0.000,
5: 0.231, 6: 0.231, 7: 0.389, 8: 0.222, 9: 0.000}
b = nx.betweenness_centrality(G,
weight='weight',
normalized=True)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
def test_florentine_families_graph(self):
"""Weighted betweenness centrality:
Florentine families graph"""
G = nx.florentine_families_graph()
b_answer =\
{'Acciaiuoli': 0.000,
'Albizzi': 0.212,
'Barbadori': 0.093,
'Bischeri': 0.104,
'Castellani': 0.055,
'Ginori': 0.000,
'Guadagni': 0.255,
'Lamberteschi': 0.000,
'Medici': 0.522,
'Pazzi': 0.000,
'Peruzzi': 0.022,
'Ridolfi': 0.114,
'Salviati': 0.143,
'Strozzi': 0.103,
'Tornabuoni': 0.092}
b = nx.betweenness_centrality(G,
weight='weight',
normalized=True)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
def test_ladder_graph(self):
"""Weighted betweenness centrality: Ladder graph"""
G = nx.Graph() # ladder_graph(3)
G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3),
(2, 4), (4, 5), (3, 5)])
b_answer = {0: 1.667, 1: 1.667, 2: 6.667,
3: 6.667, 4: 1.667, 5: 1.667}
for b in b_answer:
b_answer[b] /= 2.0
b = nx.betweenness_centrality(G,
weight='weight',
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
def test_G(self):
"""Weighted betweenness centrality: G"""
G = weighted_G()
b_answer = {0: 2.0, 1: 0.0, 2: 4.0, 3: 3.0, 4: 4.0, 5: 0.0}
b = nx.betweenness_centrality(G,
weight='weight',
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
def test_G2(self):
"""Weighted betweenness centrality: G2"""
G = nx.DiGraph()
G.add_weighted_edges_from([('s', 'u', 10), ('s', 'x', 5),
('u', 'v', 1), ('u', 'x', 2),
('v', 'y', 1), ('x', 'u', 3),
('x', 'v', 5), ('x', 'y', 2),
('y', 's', 7), ('y', 'v', 6)])
b_answer = {'y': 5.0, 'x': 5.0, 's': 4.0, 'u': 2.0, 'v': 2.0}
b = nx.betweenness_centrality(G,
weight='weight',
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
class TestEdgeBetweennessCentrality(object):
def test_K5(self):
"""Edge betweenness centrality: K5"""
G = nx.complete_graph(5)
b = nx.edge_betweenness_centrality(G, weight=None, normalized=False)
b_answer = dict.fromkeys(G.edges(), 1)
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n])
def test_normalized_K5(self):
"""Edge betweenness centrality: K5"""
G = nx.complete_graph(5)
b = nx.edge_betweenness_centrality(G, weight=None, normalized=True)
b_answer = dict.fromkeys(G.edges(), 1 / 10.0)
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n])
def test_C4(self):
"""Edge betweenness centrality: C4"""
G = nx.cycle_graph(4)
b = nx.edge_betweenness_centrality(G, weight=None, normalized=True)
b_answer = {(0, 1): 2, (0, 3): 2, (1, 2): 2, (2, 3): 2}
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n] / 6.0)
def test_P4(self):
"""Edge betweenness centrality: P4"""
G = nx.path_graph(4)
b = nx.edge_betweenness_centrality(G, weight=None, normalized=False)
b_answer = {(0, 1): 3, (1, 2): 4, (2, 3): 3}
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n])
def test_normalized_P4(self):
"""Edge betweenness centrality: P4"""
G = nx.path_graph(4)
b = nx.edge_betweenness_centrality(G, weight=None, normalized=True)
b_answer = {(0, 1): 3, (1, 2): 4, (2, 3): 3}
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n] / 6.0)
def test_balanced_tree(self):
"""Edge betweenness centrality: balanced tree"""
G = nx.balanced_tree(r=2, h=2)
b = nx.edge_betweenness_centrality(G, weight=None, normalized=False)
b_answer = {(0, 1): 12, (0, 2): 12,
(1, 3): 6, (1, 4): 6, (2, 5): 6, (2, 6): 6}
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n])
class TestWeightedEdgeBetweennessCentrality(object):
def test_K5(self):
"""Edge betweenness centrality: K5"""
G = nx.complete_graph(5)
b = nx.edge_betweenness_centrality(G, weight='weight', normalized=False)
b_answer = dict.fromkeys(G.edges(), 1)
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n])
def test_C4(self):
"""Edge betweenness centrality: C4"""
G = nx.cycle_graph(4)
b = nx.edge_betweenness_centrality(G, weight='weight', normalized=False)
b_answer = {(0, 1): 2, (0, 3): 2, (1, 2): 2, (2, 3): 2}
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n])
def test_P4(self):
"""Edge betweenness centrality: P4"""
G = nx.path_graph(4)
b = nx.edge_betweenness_centrality(G, weight='weight', normalized=False)
b_answer = {(0, 1): 3, (1, 2): 4, (2, 3): 3}
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n])
def test_balanced_tree(self):
"""Edge betweenness centrality: balanced tree"""
G = nx.balanced_tree(r=2, h=2)
b = nx.edge_betweenness_centrality(G, weight='weight', normalized=False)
b_answer = {(0, 1): 12, (0, 2): 12,
(1, 3): 6, (1, 4): 6, (2, 5): 6, (2, 6): 6}
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n])
def test_weighted_graph(self):
eList = [(0, 1, 5), (0, 2, 4), (0, 3, 3),
(0, 4, 2), (1, 2, 4), (1, 3, 1),
(1, 4, 3), (2, 4, 5), (3, 4, 4)]
G = nx.Graph()
G.add_weighted_edges_from(eList)
b = nx.edge_betweenness_centrality(G, weight='weight', normalized=False)
b_answer = {(0, 1): 0.0,
(0, 2): 1.0,
(0, 3): 2.0,
(0, 4): 1.0,
(1, 2): 2.0,
(1, 3): 3.5,
(1, 4): 1.5,
(2, 4): 1.0,
(3, 4): 0.5}
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n])
def test_normalized_weighted_graph(self):
eList = [(0, 1, 5), (0, 2, 4), (0, 3, 3),
(0, 4, 2), (1, 2, 4), (1, 3, 1),
(1, 4, 3), (2, 4, 5), (3, 4, 4)]
G = nx.Graph()
G.add_weighted_edges_from(eList)
b = nx.edge_betweenness_centrality(G, weight='weight', normalized=True)
b_answer = {(0, 1): 0.0,
(0, 2): 1.0,
(0, 3): 2.0,
(0, 4): 1.0,
(1, 2): 2.0,
(1, 3): 3.5,
(1, 4): 1.5,
(2, 4): 1.0,
(3, 4): 0.5}
norm = len(G) * (len(G) - 1) / 2.0
for n in sorted(G.edges()):
assert_almost_equal(b[n], b_answer[n] / norm)