/usr/share/pyshared/networkx/algorithms/centrality/tests/test_eigenvector_centrality.py is in python-networkx 1.6-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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 | #!/usr/bin/env python
import math
from nose import SkipTest
from nose.tools import *
import networkx
class TestEigenvectorCentrality(object):
numpy=1 # nosetests attribute, use nosetests -a 'not numpy' to skip test
@classmethod
def setupClass(cls):
global np
try:
import numpy as np
except ImportError:
raise SkipTest('NumPy not available.')
def test_K5(self):
"""Eigenvector centrality: K5"""
G=networkx.complete_graph(5)
b=networkx.eigenvector_centrality(G)
v=math.sqrt(1/5.0)
b_answer=dict.fromkeys(G,v)
for n in sorted(G):
assert_almost_equal(b[n],b_answer[n])
b=networkx.eigenvector_centrality_numpy(G)
for n in sorted(G):
assert_almost_equal(b[n],b_answer[n],places=3)
def test_P3(self):
"""Eigenvector centrality: P3"""
G=networkx.path_graph(3)
b_answer={0: 0.5, 1: 0.7071, 2: 0.5}
b=networkx.eigenvector_centrality_numpy(G)
for n in sorted(G):
assert_almost_equal(b[n],b_answer[n],places=4)
class TestEigenvectorCentralityDirected(object):
numpy=1 # nosetests attribute, use nosetests -a 'not numpy' to skip test
@classmethod
def setupClass(cls):
global np
try:
import numpy as np
except ImportError:
raise SkipTest('NumPy not available.')
def setUp(self):
G=networkx.DiGraph()
edges=[(1,2),(1,3),(2,4),(3,2),(3,5),(4,2),(4,5),(4,6),\
(5,6),(5,7),(5,8),(6,8),(7,1),(7,5),\
(7,8),(8,6),(8,7)]
G.add_edges_from(edges,weight=2.0)
self.G=G
self.G.evc=[0.25368793, 0.19576478, 0.32817092, 0.40430835,
0.48199885, 0.15724483, 0.51346196, 0.32475403]
H=networkx.DiGraph()
edges=[(1,2),(1,3),(2,4),(3,2),(3,5),(4,2),(4,5),(4,6),\
(5,6),(5,7),(5,8),(6,8),(7,1),(7,5),\
(7,8),(8,6),(8,7)]
G.add_edges_from(edges)
self.H=G
self.H.evc=[0.25368793, 0.19576478, 0.32817092, 0.40430835,
0.48199885, 0.15724483, 0.51346196, 0.32475403]
def test_eigenvector_centrality_weighted(self):
G=self.G
p=networkx.eigenvector_centrality_numpy(G)
for (a,b) in zip(list(p.values()),self.G.evc):
assert_almost_equal(a,b)
def test_eigenvector_centrality_unweighted(self):
G=self.H
p=networkx.eigenvector_centrality_numpy(G)
for (a,b) in zip(list(p.values()),self.G.evc):
assert_almost_equal(a,b)
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