def test_construction_smax_graph3():
z=[10,3,3,3,3,2,2,2,2,2,2]
G=nx.li_smax_graph(z)
degs = sorted(G.degree().values(),reverse=True)
assert_equal(degs, z)
assert_raises(nx.exception.NetworkXError,
nx.li_smax_graph, z, create_using=nx.DiGraph())
def test_li_smax():
G = networkx.barabasi_albert_graph(25,1) #Any old graph
Gdegseq = G.degree().values() #degree sequence
Gdegseq.sort(reverse=True)
assert_true(not (sum(Gdegseq)%2)) #Tests the 'unconstrained version'
Gmax = networkx.li_smax_graph(Gdegseq)
Gmaxdegseq = Gmax.degree().values()
Gmaxdegseq.sort(reverse=True)
assert_equal(G.order(),Gmax.order()) #Sanity Check on the nodes
assert_equal(Gdegseq,Gmaxdegseq) #make sure both graphs have the same degree sequence
assert_true(networkx.s_metric(G) <= networkx.s_metric(Gmax)) #make sure the smax graph is actually bigger
def test_li_smax():
G = networkx.barabasi_albert_graph(25, 1) #Any old graph
Gdegseq = sorted(G.degree().values(), reverse=True) #degree sequence
# Tests the 'unconstrained version'
assert_true(not (sum(Gdegseq) % 2))
Gmax = networkx.li_smax_graph(Gdegseq)
Gmaxdegseq = sorted(Gmax.degree().values(), reverse=True)
assert_equal(G.order(), Gmax.order()) #Sanity Check on the nodes
# make sure both graphs have the same degree sequence
assert_equal(Gdegseq, Gmaxdegseq)
# make sure the smax graph is actually bigger
assert_true(networkx.s_metric(G) <= networkx.s_metric(Gmax))
def test_construction_smax_graph1():
z=[5,4,3,3,3,2,2,2]
G=nx.li_smax_graph(z)
degs = sorted(G.degree().values(),reverse=True)
assert_equal(degs, z)
