Python networkx.betweenness_centrality() Examples
The following are 30
code examples of networkx.betweenness_centrality().
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Example #1
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
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)
Example #2
| Source File: calc_network.py From MD-TASK with GNU General Public License v3.0 | 6 votes |
|
def calc_BC(protein_graph, prefix, generate_plots=True):
bc = nx.betweenness_centrality(protein_graph, normalized=False)
bc = np.asarray(list(bc.values()))
num_nodes = len(protein_graph.nodes())
nodes_axis = range(1, num_nodes + 1)
if generate_plots:
plt.plot(nodes_axis, bc)
plt.title("%s BC" % prefix, fontsize=18)
plt.xlabel('Node Indices', fontsize=16)
plt.ylabel('BC', fontsize=16)
plt.savefig("%s_BC.png" % prefix, dpi=300, bbox_inches='tight')
plt.close()
bc = bc.reshape(1, num_nodes)
np.savetxt("%s_bc.dat" % prefix, bc)
return bc
Example #3
| Source File: test_betweenness_centrality.py From qgisSpaceSyntaxToolkit with GNU General Public License v3.0 | 6 votes |
|
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)
Example #4
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 6 votes |
|
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)
Example #5
| Source File: test_betweenness_centrality.py From qgisSpaceSyntaxToolkit with GNU General Public License v3.0 | 6 votes |
|
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])
Example #6
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
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])
# normalized = True case
b_answer = {0: 2/3, 1: 1.0, 2: 2/3}
b = nx.betweenness_centrality(G,
weight=None,
normalized=True,
endpoints=True)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
Example #7
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
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])
# normalized = True case
b = nx.betweenness_centrality(G,
weight=None,
normalized=True,
endpoints=True)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n] / 21)
Example #8
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
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])
# normalized = True case
b = nx.betweenness_centrality(G,
weight=None,
normalized=True,
endpoints=True)
b_answer = {0: 0.4, 1: 0.4, 2: 0.4, 3: 0.4, 4: 0.4}
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n])
Example #9
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 6 votes |
|
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])
Example #10
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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])
Example #11
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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])
Example #12
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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)
Example #13
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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])
Example #14
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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)
Example #15
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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])
Example #16
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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])
Example #17
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
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
b = nx.betweenness_centrality(G,
weight='weight',
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
Example #18
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
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)
Example #19
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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)
Example #20
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
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)
Example #21
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
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
b = nx.betweenness_centrality(G,
weight='weight',
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
Example #22
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
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])
Example #23
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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)
Example #24
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
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])
Example #25
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
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])
Example #26
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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)
Example #27
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
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])
Example #28
| Source File: test_betweenness_centrality.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
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])
Example #29
| Source File: test_betweenness_centrality.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
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
b = nx.betweenness_centrality(G,
weight=None,
normalized=False)
for n in sorted(G):
assert_almost_equal(b[n], b_answer[n], places=3)
Example #30
| Source File: test_threshold.py From aws-kube-codesuite with Apache License 2.0 | 5 votes |
|
def test_fast_versions_properties_threshold_graphs(self):
cs = 'ddiiddid'
G = nxt.threshold_graph(cs)
assert_equal(nxt.density('ddiiddid'), nx.density(G))
assert_equal(sorted(nxt.degree_sequence(cs)),
sorted(d for n, d in G.degree()))
ts = nxt.triangle_sequence(cs)
assert_equal(ts, list(nx.triangles(G).values()))
assert_equal(sum(ts) // 3, nxt.triangles(cs))
c1 = nxt.cluster_sequence(cs)
c2 = list(nx.clustering(G).values())
assert_almost_equal(sum([abs(c - d) for c, d in zip(c1, c2)]), 0)
b1 = nx.betweenness_centrality(G).values()
b2 = nxt.betweenness_sequence(cs)
assert_true(sum([abs(c - d) for c, d in zip(b1, b2)]) < 1e-14)
assert_equal(nxt.eigenvalues(cs), [0, 1, 3, 3, 5, 7, 7, 8])
# Degree Correlation
assert_true(abs(nxt.degree_correlation(cs) + 0.593038821954) < 1e-12)
assert_equal(nxt.degree_correlation('diiiddi'), -0.8)
assert_equal(nxt.degree_correlation('did'), -1.0)
assert_equal(nxt.degree_correlation('ddd'), 1.0)
assert_equal(nxt.eigenvalues('dddiii'), [0, 0, 0, 0, 3, 3])
assert_equal(nxt.eigenvalues('dddiiid'), [0, 1, 1, 1, 4, 4, 7])
