.venv/Lib/site-packages/networkx/algorithms/tests/test_clique.py

import pytest

import networkx as nx
from networkx import convert_node_labels_to_integers as cnlti


class TestCliques:
    def setup_method(self):
        z = [3, 4, 3, 4, 2, 4, 2, 1, 1, 1, 1]
        self.G = cnlti(nx.generators.havel_hakimi_graph(z), first_label=1)
        self.cl = list(nx.find_cliques(self.G))
        H = nx.complete_graph(6)
        H = nx.relabel_nodes(H, {i: i + 1 for i in range(6)})
        H.remove_edges_from([(2, 6), (2, 5), (2, 4), (1, 3), (5, 3)])
        self.H = H

    def test_find_cliques1(self):
        cl = list(nx.find_cliques(self.G))
        rcl = nx.find_cliques_recursive(self.G)
        expected = [[2, 6, 1, 3], [2, 6, 4], [5, 4, 7], [8, 9], [10, 11]]
        assert sorted(map(sorted, cl)) == sorted(map(sorted, rcl))
        assert sorted(map(sorted, cl)) == sorted(map(sorted, expected))

    def test_selfloops(self):
        self.G.add_edge(1, 1)
        cl = list(nx.find_cliques(self.G))
        rcl = list(nx.find_cliques_recursive(self.G))
        assert set(map(frozenset, cl)) == set(map(frozenset, rcl))
        answer = [{2, 6, 1, 3}, {2, 6, 4}, {5, 4, 7}, {8, 9}, {10, 11}]
        assert len(answer) == len(cl)
        assert all(set(c) in answer for c in cl)

    def test_find_cliques2(self):
        hcl = list(nx.find_cliques(self.H))
        assert sorted(map(sorted, hcl)) == [[1, 2], [1, 4, 5, 6], [2, 3], [3, 4, 6]]

    def test_find_cliques3(self):
        # all cliques are [[2, 6, 1, 3], [2, 6, 4], [5, 4, 7], [8, 9], [10, 11]]

        cl = list(nx.find_cliques(self.G, [2]))
        rcl = nx.find_cliques_recursive(self.G, [2])
        expected = [[2, 6, 1, 3], [2, 6, 4]]
        assert sorted(map(sorted, rcl)) == sorted(map(sorted, expected))
        assert sorted(map(sorted, cl)) == sorted(map(sorted, expected))

        cl = list(nx.find_cliques(self.G, [2, 3]))
        rcl = nx.find_cliques_recursive(self.G, [2, 3])
        expected = [[2, 6, 1, 3]]
        assert sorted(map(sorted, rcl)) == sorted(map(sorted, expected))
        assert sorted(map(sorted, cl)) == sorted(map(sorted, expected))

        cl = list(nx.find_cliques(self.G, [2, 6, 4]))
        rcl = nx.find_cliques_recursive(self.G, [2, 6, 4])
        expected = [[2, 6, 4]]
        assert sorted(map(sorted, rcl)) == sorted(map(sorted, expected))
        assert sorted(map(sorted, cl)) == sorted(map(sorted, expected))

        cl = list(nx.find_cliques(self.G, [2, 6, 4]))
        rcl = nx.find_cliques_recursive(self.G, [2, 6, 4])
        expected = [[2, 6, 4]]
        assert sorted(map(sorted, rcl)) == sorted(map(sorted, expected))
        assert sorted(map(sorted, cl)) == sorted(map(sorted, expected))

        with pytest.raises(ValueError):
            list(nx.find_cliques(self.G, [2, 6, 4, 1]))

        with pytest.raises(ValueError):
            list(nx.find_cliques_recursive(self.G, [2, 6, 4, 1]))

    def test_number_of_cliques(self):
        G = self.G
        assert nx.number_of_cliques(G, 1) == 1
        assert list(nx.number_of_cliques(G, [1]).values()) == [1]
        assert list(nx.number_of_cliques(G, [1, 2]).values()) == [1, 2]
        assert nx.number_of_cliques(G, [1, 2]) == {1: 1, 2: 2}
        assert nx.number_of_cliques(G, 2) == 2
        assert nx.number_of_cliques(G) == {
            1: 1,
            2: 2,
            3: 1,
            4: 2,
            5: 1,
            6: 2,
            7: 1,
            8: 1,
            9: 1,
            10: 1,
            11: 1,
        }
        assert nx.number_of_cliques(G, nodes=list(G)) == {
            1: 1,
            2: 2,
            3: 1,
            4: 2,
            5: 1,
            6: 2,
            7: 1,
            8: 1,
            9: 1,
            10: 1,
            11: 1,
        }
        assert nx.number_of_cliques(G, nodes=[2, 3, 4]) == {2: 2, 3: 1, 4: 2}
        assert nx.number_of_cliques(G, cliques=self.cl) == {
            1: 1,
            2: 2,
            3: 1,
            4: 2,
            5: 1,
            6: 2,
            7: 1,
            8: 1,
            9: 1,
            10: 1,
            11: 1,
        }
        assert nx.number_of_cliques(G, list(G), cliques=self.cl) == {
            1: 1,
            2: 2,
            3: 1,
            4: 2,
            5: 1,
            6: 2,
            7: 1,
            8: 1,
            9: 1,
            10: 1,
            11: 1,
        }

    def test_node_clique_number(self):
        G = self.G
        assert nx.node_clique_number(G, 1) == 4
        assert list(nx.node_clique_number(G, [1]).values()) == [4]
        assert list(nx.node_clique_number(G, [1, 2]).values()) == [4, 4]
        assert nx.node_clique_number(G, [1, 2]) == {1: 4, 2: 4}
        assert nx.node_clique_number(G, 1) == 4
        assert nx.node_clique_number(G) == {
            1: 4,
            2: 4,
            3: 4,
            4: 3,
            5: 3,
            6: 4,
            7: 3,
            8: 2,
            9: 2,
            10: 2,
            11: 2,
        }
        assert nx.node_clique_number(G, cliques=self.cl) == {
            1: 4,
            2: 4,
            3: 4,
            4: 3,
            5: 3,
            6: 4,
            7: 3,
            8: 2,
            9: 2,
            10: 2,
            11: 2,
        }
        assert nx.node_clique_number(G, [1, 2], cliques=self.cl) == {1: 4, 2: 4}
        assert nx.node_clique_number(G, 1, cliques=self.cl) == 4

    def test_make_clique_bipartite(self):
        G = self.G
        B = nx.make_clique_bipartite(G)
        assert sorted(B) == [-5, -4, -3, -2, -1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
        # Project onto the nodes of the original graph.
        H = nx.projected_graph(B, range(1, 12))
        assert H.adj == G.adj
        # Project onto the nodes representing the cliques.
        H1 = nx.projected_graph(B, range(-5, 0))
        # Relabel the negative numbers as positive ones.
        H1 = nx.relabel_nodes(H1, {-v: v for v in range(1, 6)})
        assert sorted(H1) == [1, 2, 3, 4, 5]

    def test_make_max_clique_graph(self):
        """Tests that the maximal clique graph is the same as the bipartite
        clique graph after being projected onto the nodes representing the
        cliques.

        """
        G = self.G
        B = nx.make_clique_bipartite(G)
        # Project onto the nodes representing the cliques.
        H1 = nx.projected_graph(B, range(-5, 0))
        # Relabel the negative numbers as nonnegative ones, starting at
        # 0.
        H1 = nx.relabel_nodes(H1, {-v: v - 1 for v in range(1, 6)})
        H2 = nx.make_max_clique_graph(G)
        assert H1.adj == H2.adj

    def test_directed(self):
        with pytest.raises(nx.NetworkXNotImplemented):
            next(nx.find_cliques(nx.DiGraph()))

    def test_find_cliques_trivial(self):
        G = nx.Graph()
        assert sorted(nx.find_cliques(G)) == []
        assert sorted(nx.find_cliques_recursive(G)) == []

    def test_make_max_clique_graph_create_using(self):
        G = nx.Graph([(1, 2), (3, 1), (4, 1), (5, 6)])
        E = nx.Graph([(0, 1), (0, 2), (1, 2)])
        E.add_node(3)
        assert nx.is_isomorphic(nx.make_max_clique_graph(G, create_using=nx.Graph), E)


class TestEnumerateAllCliques:
    def test_paper_figure_4(self):
        # Same graph as given in Fig. 4 of paper enumerate_all_cliques is
        # based on.
        # http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1559964&isnumber=33129
        G = nx.Graph()
        edges_fig_4 = [
            ("a", "b"),
            ("a", "c"),
            ("a", "d"),
            ("a", "e"),
            ("b", "c"),
            ("b", "d"),
            ("b", "e"),
            ("c", "d"),
            ("c", "e"),
            ("d", "e"),
            ("f", "b"),
            ("f", "c"),
            ("f", "g"),
            ("g", "f"),
            ("g", "c"),
            ("g", "d"),
            ("g", "e"),
        ]
        G.add_edges_from(edges_fig_4)

        cliques = list(nx.enumerate_all_cliques(G))
        clique_sizes = list(map(len, cliques))
        assert sorted(clique_sizes) == clique_sizes

        expected_cliques = [
            ["a"],
            ["b"],
            ["c"],
            ["d"],
            ["e"],
            ["f"],
            ["g"],
            ["a", "b"],
            ["a", "b", "d"],
            ["a", "b", "d", "e"],
            ["a", "b", "e"],
            ["a", "c"],
            ["a", "c", "d"],
            ["a", "c", "d", "e"],
            ["a", "c", "e"],
            ["a", "d"],
            ["a", "d", "e"],
            ["a", "e"],
            ["b", "c"],
            ["b", "c", "d"],
            ["b", "c", "d", "e"],
            ["b", "c", "e"],
            ["b", "c", "f"],
            ["b", "d"],
            ["b", "d", "e"],
            ["b", "e"],
            ["b", "f"],
            ["c", "d"],
            ["c", "d", "e"],
            ["c", "d", "e", "g"],
            ["c", "d", "g"],
            ["c", "e"],
            ["c", "e", "g"],
            ["c", "f"],
            ["c", "f", "g"],
            ["c", "g"],
            ["d", "e"],
            ["d", "e", "g"],
            ["d", "g"],
            ["e", "g"],
            ["f", "g"],
            ["a", "b", "c"],
            ["a", "b", "c", "d"],
            ["a", "b", "c", "d", "e"],
            ["a", "b", "c", "e"],
        ]

        assert sorted(map(sorted, cliques)) == sorted(map(sorted, expected_cliques))