/usr/lib/python2.7/dist-packages/networkx/generators/tests/test_threshold.py is in python-networkx 1.8.1-0ubuntu3.
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"""Threshold Graphs
================
"""
from nose.tools import *
from nose import SkipTest
from nose.plugins.attrib import attr
import networkx as nx
import networkx.generators.threshold as nxt
from networkx.algorithms.isomorphism.isomorph import graph_could_be_isomorphic
cnlti = nx.convert_node_labels_to_integers
class TestGeneratorThreshold():
def test_threshold_sequence_graph_test(self):
G=nx.star_graph(10)
assert_true(nxt.is_threshold_graph(G))
assert_true(nxt.is_threshold_sequence(list(G.degree().values())))
G=nx.complete_graph(10)
assert_true(nxt.is_threshold_graph(G))
assert_true(nxt.is_threshold_sequence(list(G.degree().values())))
deg=[3,2,2,1,1,1]
assert_false(nxt.is_threshold_sequence(deg))
deg=[3,2,2,1]
assert_true(nxt.is_threshold_sequence(deg))
G=nx.generators.havel_hakimi_graph(deg)
assert_true(nxt.is_threshold_graph(G))
def test_creation_sequences(self):
deg=[3,2,2,1]
G=nx.generators.havel_hakimi_graph(deg)
cs0=nxt.creation_sequence(deg)
H0=nxt.threshold_graph(cs0)
assert_equal(''.join(cs0), 'ddid')
cs1=nxt.creation_sequence(deg, with_labels=True)
H1=nxt.threshold_graph(cs1)
assert_equal(cs1, [(1, 'd'), (2, 'd'), (3, 'i'), (0, 'd')])
cs2=nxt.creation_sequence(deg, compact=True)
H2=nxt.threshold_graph(cs2)
assert_equal(cs2, [2, 1, 1])
assert_equal(''.join(nxt.uncompact(cs2)), 'ddid')
assert_true(graph_could_be_isomorphic(H0,G))
assert_true(graph_could_be_isomorphic(H0,H1))
assert_true(graph_could_be_isomorphic(H0,H2))
def test_shortest_path(self):
deg=[3,2,2,1]
G=nx.generators.havel_hakimi_graph(deg)
cs1=nxt.creation_sequence(deg, with_labels=True)
for n, m in [(3, 0), (0, 3), (0, 2), (0, 1), (1, 3),
(3, 1), (1, 2), (2, 3)]:
assert_equal(nxt.shortest_path(cs1,n,m),
nx.shortest_path(G, n, m))
spl=nxt.shortest_path_length(cs1,3)
spl2=nxt.shortest_path_length([ t for v,t in cs1],2)
assert_equal(spl, spl2)
spld={}
for j,pl in enumerate(spl):
n=cs1[j][0]
spld[n]=pl
assert_equal(spld, nx.single_source_shortest_path_length(G, 3))
def test_weights_thresholds(self):
wseq=[3,4,3,3,5,6,5,4,5,6]
cs=nxt.weights_to_creation_sequence(wseq,threshold=10)
wseq=nxt.creation_sequence_to_weights(cs)
cs2=nxt.weights_to_creation_sequence(wseq)
assert_equal(cs, cs2)
wseq=nxt.creation_sequence_to_weights(nxt.uncompact([3,1,2,3,3,2,3]))
assert_equal(wseq,
[s*0.125 for s in [4,4,4,3,5,5,2,2,2,6,6,6,1,1,7,7,7]])
wseq=nxt.creation_sequence_to_weights([3,1,2,3,3,2,3])
assert_equal(wseq,
[s*0.125 for s in [4,4,4,3,5,5,2,2,2,6,6,6,1,1,7,7,7]])
wseq=nxt.creation_sequence_to_weights(list(enumerate('ddidiiidididi')))
assert_equal(wseq,
[s*0.1 for s in [5,5,4,6,3,3,3,7,2,8,1,9,0]])
wseq=nxt.creation_sequence_to_weights('ddidiiidididi')
assert_equal(wseq,
[s*0.1 for s in [5,5,4,6,3,3,3,7,2,8,1,9,0]])
wseq=nxt.creation_sequence_to_weights('ddidiiidididid')
ws=[s/float(12) for s in [6,6,5,7,4,4,4,8,3,9,2,10,1,11]]
assert_true(sum([abs(c-d) for c,d in zip(wseq,ws)]) < 1e-14)
def test_finding_routines(self):
G=nx.Graph({1:[2],2:[3],3:[4],4:[5],5:[6]})
G.add_edge(2,4)
G.add_edge(2,5)
G.add_edge(2,7)
G.add_edge(3,6)
G.add_edge(4,6)
# Alternating 4 cycle
assert_equal(nxt.find_alternating_4_cycle(G), [1, 2, 3, 6])
# Threshold graph
TG=nxt.find_threshold_graph(G)
assert_true(nxt.is_threshold_graph(TG))
assert_equal(sorted(TG.nodes()), [1, 2, 3, 4, 5, 7])
cs=nxt.creation_sequence(TG.degree(),with_labels=True)
assert_equal(nxt.find_creation_sequence(G), cs)
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(G.degree().values()))
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])
def test_tg_creation_routines(self):
s=nxt.left_d_threshold_sequence(5,7)
s=nxt.right_d_threshold_sequence(5,7)
s1=nxt.swap_d(s,1.0,1.0)
@attr('numpy')
def test_eigenvectors(self):
try:
import numpy as N
eigenval=N.linalg.eigvals
except ImportError:
raise SkipTest('NumPy not available.')
cs='ddiiddid'
G=nxt.threshold_graph(cs)
(tgeval,tgevec)=nxt.eigenvectors(cs)
dot=N.dot
assert_equal([ abs(dot(lv,lv)-1.0)<1e-9 for lv in tgevec ], [True]*8)
lapl=nx.laplacian_matrix(G)
# tgev=[ dot(lv,dot(lapl,lv)) for lv in tgevec ]
# assert_true(sum([abs(c-d) for c,d in zip(tgev,tgeval)]) < 1e-9)
# tgev.sort()
# lev=list(eigenval(lapl))
# lev.sort()
# assert_true(sum([abs(c-d) for c,d in zip(tgev,lev)]) < 1e-9)
def test_create_using(self):
cs='ddiiddid'
G=nxt.threshold_graph(cs)
assert_raises(nx.exception.NetworkXError,
nxt.threshold_graph, cs, create_using=nx.DiGraph())
MG=nxt.threshold_graph(cs,create_using=nx.MultiGraph())
assert_equal(MG.edges(), G.edges())
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