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#!/usr/bin/env python
from nose.tools import *
from nose import SkipTest
from nose.plugins.attrib import attr
import networkx as nx
from networkx.algorithms import bipartite
class TestBipartiteBasic:
def test_is_bipartite(self):
assert_true(bipartite.is_bipartite(nx.path_graph(4)))
assert_true(bipartite.is_bipartite(nx.DiGraph([(1,0)])))
assert_false(bipartite.is_bipartite(nx.complete_graph(3)))
def test_bipartite_color(self):
G=nx.path_graph(4)
c=bipartite.color(G)
assert_equal(c,{0: 1, 1: 0, 2: 1, 3: 0})
@raises(nx.NetworkXError)
def test_not_bipartite_color(self):
c=bipartite.color(nx.complete_graph(4))
def test_bipartite_directed(self):
G = nx.bipartite_random_graph(10, 10, 0.1, directed=True)
assert_true(bipartite.is_bipartite(G))
def test_bipartite_sets(self):
G=nx.path_graph(4)
X,Y=bipartite.sets(G)
assert_equal(X,set([0,2]))
assert_equal(Y,set([1,3]))
def test_is_bipartite_node_set(self):
G=nx.path_graph(4)
assert_true(bipartite.is_bipartite_node_set(G,[0,2]))
assert_true(bipartite.is_bipartite_node_set(G,[1,3]))
assert_false(bipartite.is_bipartite_node_set(G,[1,2]))
G.add_path([10,20])
assert_true(bipartite.is_bipartite_node_set(G,[0,2,10]))
assert_true(bipartite.is_bipartite_node_set(G,[0,2,20]))
assert_true(bipartite.is_bipartite_node_set(G,[1,3,10]))
assert_true(bipartite.is_bipartite_node_set(G,[1,3,20]))
def test_bipartite_density(self):
G=nx.path_graph(5)
X,Y=bipartite.sets(G)
density=float(len(G.edges()))/(len(X)*len(Y))
assert_equal(bipartite.density(G,X),density)
D = nx.DiGraph(G.edges())
assert_equal(bipartite.density(D,X),density/2.0)
assert_equal(bipartite.density(nx.Graph(),{}),0.0)
def test_bipartite_degrees(self):
G=nx.path_graph(5)
X=set([1,3])
Y=set([0,2,4])
u,d=bipartite.degrees(G,Y)
assert_equal(u,{1:2,3:2})
assert_equal(d,{0:1,2:2,4:1})
def test_bipartite_weighted_degrees(self):
G=nx.path_graph(5)
G.add_edge(0,1,weight=0.1,other=0.2)
X=set([1,3])
Y=set([0,2,4])
u,d=bipartite.degrees(G,Y,weight='weight')
assert_equal(u,{1:1.1,3:2})
assert_equal(d,{0:0.1,2:2,4:1})
u,d=bipartite.degrees(G,Y,weight='other')
assert_equal(u,{1:1.2,3:2})
assert_equal(d,{0:0.2,2:2,4:1})
@attr('numpy')
def test_biadjacency_matrix_weight(self):
try:
import numpy
except ImportError:
raise SkipTest('numpy not available.')
G=nx.path_graph(5)
G.add_edge(0,1,weight=2,other=4)
X=[1,3]
Y=[0,2,4]
M = bipartite.biadjacency_matrix(G,X,weight='weight')
assert_equal(M[0,0], 2)
M = bipartite.biadjacency_matrix(G, X, weight='other')
assert_equal(M[0,0], 4)
@attr('numpy')
def test_biadjacency_matrix(self):
try:
import numpy
except ImportError:
raise SkipTest('numpy not available.')
tops = [2,5,10]
bots = [5,10,15]
for i in range(len(tops)):
G = nx.bipartite_random_graph(tops[i], bots[i], 0.2)
top = [n for n,d in G.nodes(data=True) if d['bipartite']==0]
M = bipartite.biadjacency_matrix(G, top)
assert_equal(M.shape[0],tops[i])
assert_equal(M.shape[1],bots[i])
@attr('numpy')
def test_biadjacency_matrix_order(self):
try:
import numpy
except ImportError:
raise SkipTest('numpy not available.')
G=nx.path_graph(5)
G.add_edge(0,1,weight=2)
X=[3,1]
Y=[4,2,0]
M = bipartite.biadjacency_matrix(G,X,Y,weight='weight')
assert_equal(M[1,2], 2)
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