File: //lib/python3/dist-packages/networkx/algorithms/bipartite/tests/test_generators.py
#!/usr/bin/env python
import pytest
import networkx as nx
from networkx.algorithms.bipartite.generators import *
"""Generators - Bipartite
----------------------
"""
class TestGeneratorsBipartite():
def test_complete_bipartite_graph(self):
G = complete_bipartite_graph(0, 0)
assert nx.is_isomorphic(G, nx.null_graph())
for i in [1, 5]:
G = complete_bipartite_graph(i, 0)
assert nx.is_isomorphic(G, nx.empty_graph(i))
G = complete_bipartite_graph(0, i)
assert nx.is_isomorphic(G, nx.empty_graph(i))
G = complete_bipartite_graph(2, 2)
assert nx.is_isomorphic(G, nx.cycle_graph(4))
G = complete_bipartite_graph(1, 5)
assert nx.is_isomorphic(G, nx.star_graph(5))
G = complete_bipartite_graph(5, 1)
assert nx.is_isomorphic(G, nx.star_graph(5))
# complete_bipartite_graph(m1,m2) is a connected graph with
# m1+m2 nodes and m1*m2 edges
for m1, m2 in [(5, 11), (7, 3)]:
G = complete_bipartite_graph(m1, m2)
assert nx.number_of_nodes(G) == m1 + m2
assert nx.number_of_edges(G) == m1 * m2
pytest.raises(nx.NetworkXError, complete_bipartite_graph,
7, 3, create_using=nx.DiGraph)
pytest.raises(nx.NetworkXError, complete_bipartite_graph,
7, 3, create_using=nx.DiGraph)
pytest.raises(nx.NetworkXError, complete_bipartite_graph,
7, 3, create_using=nx.MultiDiGraph)
mG = complete_bipartite_graph(7, 3, create_using=nx.MultiGraph)
assert mG.is_multigraph()
assert sorted(mG.edges()) == sorted(G.edges())
mG = complete_bipartite_graph(7, 3, create_using=nx.MultiGraph)
assert mG.is_multigraph()
assert sorted(mG.edges()) == sorted(G.edges())
mG = complete_bipartite_graph(7, 3) # default to Graph
assert sorted(mG.edges()) == sorted(G.edges())
assert not mG.is_multigraph()
assert not mG.is_directed()
# specify nodes rather than number of nodes
G = complete_bipartite_graph([1, 2], ['a', 'b'])
has_edges = G.has_edge(1, 'a') & G.has_edge(1, 'b') &\
G.has_edge(2, 'a') & G.has_edge(2, 'b')
assert has_edges
assert G.size() == 4
def test_configuration_model(self):
aseq = []
bseq = []
G = configuration_model(aseq, bseq)
assert len(G) == 0
aseq = [0, 0]
bseq = [0, 0]
G = configuration_model(aseq, bseq)
assert len(G) == 4
assert G.number_of_edges() == 0
aseq = [3, 3, 3, 3]
bseq = [2, 2, 2, 2, 2]
pytest.raises(nx.NetworkXError,
configuration_model, aseq, bseq)
aseq = [3, 3, 3, 3]
bseq = [2, 2, 2, 2, 2, 2]
G = configuration_model(aseq, bseq)
assert (sorted(d for n, d in G.degree()) ==
[2, 2, 2, 2, 2, 2, 3, 3, 3, 3])
aseq = [2, 2, 2, 2, 2, 2]
bseq = [3, 3, 3, 3]
G = configuration_model(aseq, bseq)
assert (sorted(d for n, d in G.degree()) ==
[2, 2, 2, 2, 2, 2, 3, 3, 3, 3])
aseq = [2, 2, 2, 1, 1, 1]
bseq = [3, 3, 3]
G = configuration_model(aseq, bseq)
assert G.is_multigraph()
assert not G.is_directed()
assert (sorted(d for n, d in G.degree()) ==
[1, 1, 1, 2, 2, 2, 3, 3, 3])
GU = nx.project(nx.Graph(G), range(len(aseq)))
assert GU.number_of_nodes() == 6
GD = nx.project(nx.Graph(G), range(len(aseq), len(aseq) + len(bseq)))
assert GD.number_of_nodes() == 3
G = reverse_havel_hakimi_graph(aseq, bseq, create_using=nx.Graph)
assert not G.is_multigraph()
assert not G.is_directed()
pytest.raises(nx.NetworkXError,
configuration_model, aseq, bseq,
create_using=nx.DiGraph())
pytest.raises(nx.NetworkXError,
configuration_model, aseq, bseq,
create_using=nx.DiGraph)
pytest.raises(nx.NetworkXError,
configuration_model, aseq, bseq,
create_using=nx.MultiDiGraph)
def test_havel_hakimi_graph(self):
aseq = []
bseq = []
G = havel_hakimi_graph(aseq, bseq)
assert len(G) == 0
aseq = [0, 0]
bseq = [0, 0]
G = havel_hakimi_graph(aseq, bseq)
assert len(G) == 4
assert G.number_of_edges() == 0
aseq = [3, 3, 3, 3]
bseq = [2, 2, 2, 2, 2]
pytest.raises(nx.NetworkXError,
havel_hakimi_graph, aseq, bseq)
bseq = [2, 2, 2, 2, 2, 2]
G = havel_hakimi_graph(aseq, bseq)
assert (sorted(d for n, d in G.degree()) ==
[2, 2, 2, 2, 2, 2, 3, 3, 3, 3])
aseq = [2, 2, 2, 2, 2, 2]
bseq = [3, 3, 3, 3]
G = havel_hakimi_graph(aseq, bseq)
assert G.is_multigraph()
assert not G.is_directed()
assert (sorted(d for n, d in G.degree()) ==
[2, 2, 2, 2, 2, 2, 3, 3, 3, 3])
GU = nx.project(nx.Graph(G), range(len(aseq)))
assert GU.number_of_nodes() == 6
GD = nx.project(nx.Graph(G), range(len(aseq), len(aseq) + len(bseq)))
assert GD.number_of_nodes() == 4
G = reverse_havel_hakimi_graph(aseq, bseq, create_using=nx.Graph)
assert not G.is_multigraph()
assert not G.is_directed()
pytest.raises(nx.NetworkXError,
havel_hakimi_graph, aseq, bseq,
create_using=nx.DiGraph)
pytest.raises(nx.NetworkXError,
havel_hakimi_graph, aseq, bseq,
create_using=nx.DiGraph)
pytest.raises(nx.NetworkXError,
havel_hakimi_graph, aseq, bseq,
create_using=nx.MultiDiGraph)
def test_reverse_havel_hakimi_graph(self):
aseq = []
bseq = []
G = reverse_havel_hakimi_graph(aseq, bseq)
assert len(G) == 0
aseq = [0, 0]
bseq = [0, 0]
G = reverse_havel_hakimi_graph(aseq, bseq)
assert len(G) == 4
assert G.number_of_edges() == 0
aseq = [3, 3, 3, 3]
bseq = [2, 2, 2, 2, 2]
pytest.raises(nx.NetworkXError,
reverse_havel_hakimi_graph, aseq, bseq)
bseq = [2, 2, 2, 2, 2, 2]
G = reverse_havel_hakimi_graph(aseq, bseq)
assert (sorted(d for n, d in G.degree()) ==
[2, 2, 2, 2, 2, 2, 3, 3, 3, 3])
aseq = [2, 2, 2, 2, 2, 2]
bseq = [3, 3, 3, 3]
G = reverse_havel_hakimi_graph(aseq, bseq)
assert (sorted(d for n, d in G.degree()) ==
[2, 2, 2, 2, 2, 2, 3, 3, 3, 3])
aseq = [2, 2, 2, 1, 1, 1]
bseq = [3, 3, 3]
G = reverse_havel_hakimi_graph(aseq, bseq)
assert G.is_multigraph()
assert not G.is_directed()
assert (sorted(d for n, d in G.degree()) ==
[1, 1, 1, 2, 2, 2, 3, 3, 3])
GU = nx.project(nx.Graph(G), range(len(aseq)))
assert GU.number_of_nodes() == 6
GD = nx.project(nx.Graph(G), range(len(aseq), len(aseq) + len(bseq)))
assert GD.number_of_nodes() == 3
G = reverse_havel_hakimi_graph(aseq, bseq, create_using=nx.Graph)
assert not G.is_multigraph()
assert not G.is_directed()
pytest.raises(nx.NetworkXError,
reverse_havel_hakimi_graph, aseq, bseq,
create_using=nx.DiGraph)
pytest.raises(nx.NetworkXError,
reverse_havel_hakimi_graph, aseq, bseq,
create_using=nx.DiGraph)
pytest.raises(nx.NetworkXError,
reverse_havel_hakimi_graph, aseq, bseq,
create_using=nx.MultiDiGraph)
def test_alternating_havel_hakimi_graph(self):
aseq = []
bseq = []
G = alternating_havel_hakimi_graph(aseq, bseq)
assert len(G) == 0
aseq = [0, 0]
bseq = [0, 0]
G = alternating_havel_hakimi_graph(aseq, bseq)
assert len(G) == 4
assert G.number_of_edges() == 0
aseq = [3, 3, 3, 3]
bseq = [2, 2, 2, 2, 2]
pytest.raises(nx.NetworkXError,
alternating_havel_hakimi_graph, aseq, bseq)
bseq = [2, 2, 2, 2, 2, 2]
G = alternating_havel_hakimi_graph(aseq, bseq)
assert (sorted(d for n, d in G.degree()) ==
[2, 2, 2, 2, 2, 2, 3, 3, 3, 3])
aseq = [2, 2, 2, 2, 2, 2]
bseq = [3, 3, 3, 3]
G = alternating_havel_hakimi_graph(aseq, bseq)
assert (sorted(d for n, d in G.degree()) ==
[2, 2, 2, 2, 2, 2, 3, 3, 3, 3])
aseq = [2, 2, 2, 1, 1, 1]
bseq = [3, 3, 3]
G = alternating_havel_hakimi_graph(aseq, bseq)
assert G.is_multigraph()
assert not G.is_directed()
assert (sorted(d for n, d in G.degree()) ==
[1, 1, 1, 2, 2, 2, 3, 3, 3])
GU = nx.project(nx.Graph(G), range(len(aseq)))
assert GU.number_of_nodes() == 6
GD = nx.project(nx.Graph(G), range(len(aseq), len(aseq) + len(bseq)))
assert GD.number_of_nodes() == 3
G = reverse_havel_hakimi_graph(aseq, bseq, create_using=nx.Graph)
assert not G.is_multigraph()
assert not G.is_directed()
pytest.raises(nx.NetworkXError,
alternating_havel_hakimi_graph, aseq, bseq,
create_using=nx.DiGraph)
pytest.raises(nx.NetworkXError,
alternating_havel_hakimi_graph, aseq, bseq,
create_using=nx.DiGraph)
pytest.raises(nx.NetworkXError,
alternating_havel_hakimi_graph, aseq, bseq,
create_using=nx.MultiDiGraph)
def test_preferential_attachment(self):
aseq = [3, 2, 1, 1]
G = preferential_attachment_graph(aseq, 0.5)
assert G.is_multigraph()
assert not G.is_directed()
G = preferential_attachment_graph(aseq, 0.5, create_using=nx.Graph)
assert not G.is_multigraph()
assert not G.is_directed()
pytest.raises(nx.NetworkXError,
preferential_attachment_graph, aseq, 0.5,
create_using=nx.DiGraph())
pytest.raises(nx.NetworkXError,
preferential_attachment_graph, aseq, 0.5,
create_using=nx.DiGraph())
pytest.raises(nx.NetworkXError,
preferential_attachment_graph, aseq, 0.5,
create_using=nx.DiGraph())
def test_random_graph(self):
n = 10
m = 20
G = random_graph(n, m, 0.9)
assert len(G) == 30
assert nx.is_bipartite(G)
X, Y = nx.algorithms.bipartite.sets(G)
assert set(range(n)) == X
assert set(range(n, n + m)) == Y
def test_random_digraph(self):
n = 10
m = 20
G = random_graph(n, m, 0.9, directed=True)
assert len(G) == 30
assert nx.is_bipartite(G)
X, Y = nx.algorithms.bipartite.sets(G)
assert set(range(n)) == X
assert set(range(n, n + m)) == Y
def test_gnmk_random_graph(self):
n = 10
m = 20
edges = 100
# set seed because sometimes it is not connected
# which raises an error in bipartite.sets(G) below.
G = gnmk_random_graph(n, m, edges, seed=1234)
assert len(G) == n + m
assert nx.is_bipartite(G)
X, Y = nx.algorithms.bipartite.sets(G)
#print(X)
assert set(range(n)) == X
assert set(range(n, n + m)) == Y
assert edges == len(list(G.edges()))
def test_gnmk_random_graph_complete(self):
n = 10
m = 20
edges = 200
G = gnmk_random_graph(n, m, edges)
assert len(G) == n + m
assert nx.is_bipartite(G)
X, Y = nx.algorithms.bipartite.sets(G)
#print(X)
assert set(range(n)) == X
assert set(range(n, n + m)) == Y
assert edges == len(list(G.edges()))