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)