<gh_stars>0
#!/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()))
