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#!/usr/bin/env python
from nose.tools import *
from nose import SkipTest
import networkx
# Example from
# A. Langville and C. Meyer, "A survey of eigenvector methods of web
# information retrieval." http://citeseer.ist.psu.edu/713792.html
class TestHITS:
def setUp(self):
G=networkx.DiGraph()
edges=[(1,3),(1,5),\
(2,1),\
(3,5),\
(5,4),(5,3),\
(6,5)]
G.add_edges_from(edges,weight=1)
self.G=G
self.G.a=dict(zip(G,[0.000000, 0.000000, 0.366025,
0.133975, 0.500000, 0.000000]))
self.G.h=dict(zip(G,[ 0.366025, 0.000000, 0.211325,
0.000000, 0.211325, 0.211325]))
def test_hits(self):
G=self.G
h,a=networkx.hits(G,tol=1.e-08)
for n in G:
assert_almost_equal(h[n],G.h[n],places=4)
for n in G:
assert_almost_equal(a[n],G.a[n],places=4)
def test_hits_numpy(self):
G=self.G
h,a=networkx.hits_numpy(G)
for n in G:
assert_almost_equal(h[n],G.h[n],places=4)
for n in G:
assert_almost_equal(a[n],G.a[n],places=4)
def test_hits_scipy(self):
G=self.G
h,a=networkx.hits_scipy(G,tol=1.e-08)
for n in G:
assert_almost_equal(h[n],G.h[n],places=4)
for n in G:
assert_almost_equal(a[n],G.a[n],places=4)
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