import networkx as nx class BaseTestAttributeMixing: @classmethod def setup_class(cls): G = nx.Graph() G.add_nodes_from([0, 1], fish="one") G.add_nodes_from([2, 3], fish="two") G.add_nodes_from([4], fish="red") G.add_nodes_from([5], fish="blue") G.add_edges_from([(0, 1), (2, 3), (0, 4), (2, 5)]) cls.G = G D = nx.DiGraph() D.add_nodes_from([0, 1], fish="one") D.add_nodes_from([2, 3], fish="two") D.add_nodes_from([4], fish="red") D.add_nodes_from([5], fish="blue") D.add_edges_from([(0, 1), (2, 3), (0, 4), (2, 5)]) cls.D = D M = nx.MultiGraph() M.add_nodes_from([0, 1], fish="one") M.add_nodes_from([2, 3], fish="two") M.add_nodes_from([4], fish="red") M.add_nodes_from([5], fish="blue") M.add_edges_from([(0, 1), (0, 1), (2, 3)]) cls.M = M S = nx.Graph() S.add_nodes_from([0, 1], fish="one") S.add_nodes_from([2, 3], fish="two") S.add_nodes_from([4], fish="red") S.add_nodes_from([5], fish="blue") S.add_edge(0, 0) S.add_edge(2, 2) cls.S = S class BaseTestDegreeMixing: @classmethod def setup_class(cls): cls.P4 = nx.path_graph(4) cls.D = nx.DiGraph() cls.D.add_edges_from([(0, 2), (0, 3), (1, 3), (2, 3)]) cls.M = nx.MultiGraph() nx.add_path(cls.M, range(4)) cls.M.add_edge(0, 1) cls.S = nx.Graph() cls.S.add_edges_from([(0, 0), (1, 1)]) cls.W = nx.Graph() cls.W.add_edges_from([(0, 3), (1, 3), (2, 3)], weight=0.5) cls.W.add_edge(0, 2, weight=1) class BaseTestNumericMixing: @classmethod def setup_class(cls): N = nx.Graph() N.add_nodes_from([0, 1], margin=-2) N.add_nodes_from([2, 3], margin=-2) N.add_nodes_from([4], margin=-3) N.add_nodes_from([5], margin=-4) N.add_edges_from([(0, 1), (2, 3), (0, 4), (2, 5)]) cls.N = N F = nx.Graph() F.add_edges_from([(0, 3), (1, 3), (2, 3)], weight=0.5) F.add_edge(0, 2, weight=1) nx.set_node_attributes(F, dict(F.degree(weight="weight")), "margin") cls.F = F