/usr/lib/python2.7/dist-packages/networkx/algorithms/centrality/tests/test_current_flow_betweenness_centrality.py is in python-networkx 1.9+dfsg1-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 | #!/usr/bin/env python
from nose.tools import *
from nose import SkipTest
import networkx
from nose.plugins.attrib import attr
from networkx import edge_current_flow_betweenness_centrality \
as edge_current_flow
from networkx import approximate_current_flow_betweenness_centrality \
as approximate_cfbc
class TestFlowBetweennessCentrality(object):
numpy=1 # nosetests attribute, use nosetests -a 'not numpy' to skip test
@classmethod
def setupClass(cls):
global np
try:
import numpy as np
import scipy
except ImportError:
raise SkipTest('NumPy not available.')
def test_K4_normalized(self):
"""Betweenness centrality: K4"""
G=networkx.complete_graph(4)
b=networkx.current_flow_betweenness_centrality(G,normalized=True)
b_answer={0: 0.25, 1: 0.25, 2: 0.25, 3: 0.25}
for n in sorted(G):
assert_almost_equal(b[n],b_answer[n])
G.add_edge(0,1,{'weight':0.5,'other':0.3})
b=networkx.current_flow_betweenness_centrality(G,normalized=True,weight=None)
for n in sorted(G):
assert_almost_equal(b[n],b_answer[n])
wb_answer={0: 0.2222222, 1: 0.2222222, 2: 0.30555555, 3: 0.30555555}
b=networkx.current_flow_betweenness_centrality(G,normalized=True)
for n in sorted(G):
assert_almost_equal(b[n],wb_answer[n])
wb_answer={0: 0.2051282, 1: 0.2051282, 2: 0.33974358, 3: 0.33974358}
b=networkx.current_flow_betweenness_centrality(G,normalized=True,weight='other')
for n in sorted(G):
assert_almost_equal(b[n],wb_answer[n])
def test_K4(self):
"""Betweenness centrality: K4"""
G=networkx.complete_graph(4)
for solver in ['full','lu','cg']:
b=networkx.current_flow_betweenness_centrality(G, normalized=False,
solver=solver)
b_answer={0: 0.75, 1: 0.75, 2: 0.75, 3: 0.75}
for n in sorted(G):
assert_almost_equal(b[n],b_answer[n])
def test_P4_normalized(self):
"""Betweenness centrality: P4 normalized"""
G=networkx.path_graph(4)
b=networkx.current_flow_betweenness_centrality(G,normalized=True)
b_answer={0: 0, 1: 2./3, 2: 2./3, 3:0}
for n in sorted(G):
assert_almost_equal(b[n],b_answer[n])
def test_P4(self):
"""Betweenness centrality: P4"""
G=networkx.path_graph(4)
b=networkx.current_flow_betweenness_centrality(G,normalized=False)
b_answer={0: 0, 1: 2, 2: 2, 3: 0}
for n in sorted(G):
assert_almost_equal(b[n],b_answer[n])
def test_star(self):
"""Betweenness centrality: star """
G=networkx.Graph()
G.add_star(['a','b','c','d'])
b=networkx.current_flow_betweenness_centrality(G,normalized=True)
b_answer={'a': 1.0, 'b': 0.0, 'c': 0.0, 'd':0.0}
for n in sorted(G):
assert_almost_equal(b[n],b_answer[n])
def test_solers(self):
"""Betweenness centrality: alternate solvers"""
G=networkx.complete_graph(4)
for solver in ['full','lu','cg']:
b=networkx.current_flow_betweenness_centrality(G,normalized=False,
solver=solver)
b_answer={0: 0.75, 1: 0.75, 2: 0.75, 3: 0.75}
for n in sorted(G):
assert_almost_equal(b[n],b_answer[n])
class TestApproximateFlowBetweennessCentrality(object):
numpy=1 # nosetests attribute, use nosetests -a 'not numpy' to skip test
@classmethod
def setupClass(cls):
global np
global assert_allclose
try:
import numpy as np
import scipy
from numpy.testing import assert_allclose
except ImportError:
raise SkipTest('NumPy not available.')
def test_K4_normalized(self):
"Approximate current-flow betweenness centrality: K4 normalized"
G=networkx.complete_graph(4)
b=networkx.current_flow_betweenness_centrality(G,normalized=True)
epsilon=0.1
ba = approximate_cfbc(G,normalized=True, epsilon=0.5*epsilon)
for n in sorted(G):
assert_allclose(b[n],ba[n],atol=epsilon)
def test_K4(self):
"Approximate current-flow betweenness centrality: K4"
G=networkx.complete_graph(4)
b=networkx.current_flow_betweenness_centrality(G,normalized=False)
epsilon=0.1
ba = approximate_cfbc(G,normalized=False, epsilon=0.5*epsilon)
for n in sorted(G):
assert_allclose(b[n],ba[n],atol=epsilon*len(G)**2)
def test_star(self):
"Approximate current-flow betweenness centrality: star"
G=networkx.Graph()
G.add_star(['a','b','c','d'])
b=networkx.current_flow_betweenness_centrality(G,normalized=True)
epsilon=0.1
ba = approximate_cfbc(G,normalized=True, epsilon=0.5*epsilon)
for n in sorted(G):
assert_allclose(b[n],ba[n],atol=epsilon)
def test_grid(self):
"Approximate current-flow betweenness centrality: 2d grid"
G=networkx.grid_2d_graph(4,4)
b=networkx.current_flow_betweenness_centrality(G,normalized=True)
epsilon=0.1
ba = approximate_cfbc(G,normalized=True, epsilon=0.5*epsilon)
for n in sorted(G):
assert_allclose(b[n],ba[n],atol=epsilon)
def test_solvers(self):
"Approximate current-flow betweenness centrality: solvers"
G=networkx.complete_graph(4)
epsilon=0.1
for solver in ['full','lu','cg']:
b=approximate_cfbc(G,normalized=False,solver=solver,
epsilon=0.5*epsilon)
b_answer={0: 0.75, 1: 0.75, 2: 0.75, 3: 0.75}
for n in sorted(G):
assert_allclose(b[n],b_answer[n],atol=epsilon)
class TestWeightedFlowBetweennessCentrality(object):
pass
class TestEdgeFlowBetweennessCentrality(object):
numpy=1 # nosetests attribute, use nosetests -a 'not numpy' to skip test
@classmethod
def setupClass(cls):
global np
try:
import numpy as np
import scipy
except ImportError:
raise SkipTest('NumPy not available.')
def test_K4(self):
"""Edge flow betweenness centrality: K4"""
G=networkx.complete_graph(4)
b=edge_current_flow(G,normalized=True)
b_answer=dict.fromkeys(G.edges(),0.25)
for (s,t),v1 in b_answer.items():
v2=b.get((s,t),b.get((t,s)))
assert_almost_equal(v1,v2)
def test_K4_normalized(self):
"""Edge flow betweenness centrality: K4"""
G=networkx.complete_graph(4)
b=edge_current_flow(G,normalized=False)
b_answer=dict.fromkeys(G.edges(),0.75)
for (s,t),v1 in b_answer.items():
v2=b.get((s,t),b.get((t,s)))
assert_almost_equal(v1,v2)
def test_C4(self):
"""Edge flow betweenness centrality: C4"""
G=networkx.cycle_graph(4)
b=edge_current_flow(G,normalized=False)
b_answer={(0, 1):1.25,(0, 3):1.25, (1, 2):1.25, (2, 3): 1.25}
for (s,t),v1 in b_answer.items():
v2=b.get((s,t),b.get((t,s)))
assert_almost_equal(v1,v2)
def test_P4(self):
"""Edge betweenness centrality: P4"""
G=networkx.path_graph(4)
b=edge_current_flow(G,normalized=False)
b_answer={(0, 1):1.5,(1, 2):2.0, (2, 3):1.5}
for (s,t),v1 in b_answer.items():
v2=b.get((s,t),b.get((t,s)))
assert_almost_equal(v1,v2)
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