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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
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