Fixed database typo and removed unnecessary class identifier.

venv/Lib/site-packages/networkx/algorithms/community/tests/test_asyn_fluid.py

@@ -0,0 +1,127 @@
+import pytest
+from networkx import Graph, NetworkXError
+from networkx.algorithms.community.asyn_fluid import asyn_fluidc
+
+
+def test_exceptions():
+    test = Graph()
+    test.add_node("a")
+    pytest.raises(NetworkXError, asyn_fluidc, test, "hi")
+    pytest.raises(NetworkXError, asyn_fluidc, test, -1)
+    pytest.raises(NetworkXError, asyn_fluidc, test, 3)
+    test.add_node("b")
+    pytest.raises(NetworkXError, asyn_fluidc, test, 1)
+
+
+def test_single_node():
+    test = Graph()
+
+    test.add_node("a")
+
+    # ground truth
+    ground_truth = {frozenset(["a"])}
+
+    communities = asyn_fluidc(test, 1)
+    result = {frozenset(c) for c in communities}
+    assert result == ground_truth
+
+
+def test_two_nodes():
+    test = Graph()
+
+    test.add_edge("a", "b")
+
+    # ground truth
+    ground_truth = {frozenset(["a"]), frozenset(["b"])}
+
+    communities = asyn_fluidc(test, 2)
+    result = {frozenset(c) for c in communities}
+    assert result == ground_truth
+
+
+def test_two_clique_communities():
+    test = Graph()
+
+    # c1
+    test.add_edge("a", "b")
+    test.add_edge("a", "c")
+    test.add_edge("b", "c")
+
+    # connection
+    test.add_edge("c", "d")
+
+    # c2
+    test.add_edge("d", "e")
+    test.add_edge("d", "f")
+    test.add_edge("f", "e")
+
+    # ground truth
+    ground_truth = {frozenset(["a", "c", "b"]), frozenset(["e", "d", "f"])}
+
+    communities = asyn_fluidc(test, 2, seed=7)
+    result = {frozenset(c) for c in communities}
+    assert result == ground_truth
+
+
+def test_five_clique_ring():
+    test = Graph()
+
+    # c1
+    test.add_edge("1a", "1b")
+    test.add_edge("1a", "1c")
+    test.add_edge("1a", "1d")
+    test.add_edge("1b", "1c")
+    test.add_edge("1b", "1d")
+    test.add_edge("1c", "1d")
+
+    # c2
+    test.add_edge("2a", "2b")
+    test.add_edge("2a", "2c")
+    test.add_edge("2a", "2d")
+    test.add_edge("2b", "2c")
+    test.add_edge("2b", "2d")
+    test.add_edge("2c", "2d")
+
+    # c3
+    test.add_edge("3a", "3b")
+    test.add_edge("3a", "3c")
+    test.add_edge("3a", "3d")
+    test.add_edge("3b", "3c")
+    test.add_edge("3b", "3d")
+    test.add_edge("3c", "3d")
+
+    # c4
+    test.add_edge("4a", "4b")
+    test.add_edge("4a", "4c")
+    test.add_edge("4a", "4d")
+    test.add_edge("4b", "4c")
+    test.add_edge("4b", "4d")
+    test.add_edge("4c", "4d")
+
+    # c5
+    test.add_edge("5a", "5b")
+    test.add_edge("5a", "5c")
+    test.add_edge("5a", "5d")
+    test.add_edge("5b", "5c")
+    test.add_edge("5b", "5d")
+    test.add_edge("5c", "5d")
+
+    # connections
+    test.add_edge("1a", "2c")
+    test.add_edge("2a", "3c")
+    test.add_edge("3a", "4c")
+    test.add_edge("4a", "5c")
+    test.add_edge("5a", "1c")
+
+    # ground truth
+    ground_truth = {
+        frozenset(["1a", "1b", "1c", "1d"]),
+        frozenset(["2a", "2b", "2c", "2d"]),
+        frozenset(["3a", "3b", "3c", "3d"]),
+        frozenset(["4a", "4b", "4c", "4d"]),
+        frozenset(["5a", "5b", "5c", "5d"]),
+    }
+
+    communities = asyn_fluidc(test, 5, seed=9)
+    result = {frozenset(c) for c in communities}
+    assert result == ground_truth

venv/Lib/site-packages/networkx/algorithms/community/tests/test_centrality.py

@@ -0,0 +1,86 @@
+"""Unit tests for the :mod:`networkx.algorithms.community.centrality`
+module.
+
+"""
+from operator import itemgetter
+
+
+import networkx as nx
+from networkx.algorithms.community import girvan_newman
+
+
+def set_of_sets(iterable):
+    return set(map(frozenset, iterable))
+
+
+def validate_communities(result, expected):
+    assert set_of_sets(result) == set_of_sets(expected)
+
+
+def validate_possible_communities(result, *expected):
+    assert any(set_of_sets(result) == set_of_sets(p) for p in expected)
+
+
+class TestGirvanNewman:
+    """Unit tests for the
+    :func:`networkx.algorithms.community.centrality.girvan_newman`
+    function.
+
+    """
+
+    def test_no_edges(self):
+        G = nx.empty_graph(3)
+        communities = list(girvan_newman(G))
+        assert len(communities) == 1
+        validate_communities(communities[0], [{0}, {1}, {2}])
+
+    def test_undirected(self):
+        # Start with the graph .-.-.-.
+        G = nx.path_graph(4)
+        communities = list(girvan_newman(G))
+        assert len(communities) == 3
+        # After one removal, we get the graph .-. .-.
+        validate_communities(communities[0], [{0, 1}, {2, 3}])
+        # After the next, we get the graph .-. . ., but there are two
+        # symmetric possible versions.
+        validate_possible_communities(
+            communities[1], [{0}, {1}, {2, 3}], [{0, 1}, {2}, {3}]
+        )
+        # After the last removal, we always get the empty graph.
+        validate_communities(communities[2], [{0}, {1}, {2}, {3}])
+
+    def test_directed(self):
+        G = nx.DiGraph(nx.path_graph(4))
+        communities = list(girvan_newman(G))
+        assert len(communities) == 3
+        validate_communities(communities[0], [{0, 1}, {2, 3}])
+        validate_possible_communities(
+            communities[1], [{0}, {1}, {2, 3}], [{0, 1}, {2}, {3}]
+        )
+        validate_communities(communities[2], [{0}, {1}, {2}, {3}])
+
+    def test_selfloops(self):
+        G = nx.path_graph(4)
+        G.add_edge(0, 0)
+        G.add_edge(2, 2)
+        communities = list(girvan_newman(G))
+        assert len(communities) == 3
+        validate_communities(communities[0], [{0, 1}, {2, 3}])
+        validate_possible_communities(
+            communities[1], [{0}, {1}, {2, 3}], [{0, 1}, {2}, {3}]
+        )
+        validate_communities(communities[2], [{0}, {1}, {2}, {3}])
+
+    def test_most_valuable_edge(self):
+        G = nx.Graph()
+        G.add_weighted_edges_from([(0, 1, 3), (1, 2, 2), (2, 3, 1)])
+        # Let the most valuable edge be the one with the highest weight.
+
+        def heaviest(G):
+            return max(G.edges(data="weight"), key=itemgetter(2))[:2]
+
+        communities = list(girvan_newman(G, heaviest))
+        assert len(communities) == 3
+        validate_communities(communities[0], [{0}, {1, 2, 3}])
+        validate_communities(communities[1], [{0}, {1}, {2, 3}])
+        validate_communities(communities[2], [{0}, {1}, {2}, {3}])

venv/Lib/site-packages/networkx/algorithms/community/tests/test_kclique.py

@@ -0,0 +1,92 @@
+from itertools import combinations
+
+import pytest
+
+import networkx as nx
+from networkx.algorithms.community import k_clique_communities
+
+
+def test_overlapping_K5():
+    G = nx.Graph()
+    G.add_edges_from(combinations(range(5), 2))  # Add a five clique
+    G.add_edges_from(combinations(range(2, 7), 2))  # Add another five clique
+    c = list(k_clique_communities(G, 4))
+    assert c == [frozenset(range(7))]
+    c = set(k_clique_communities(G, 5))
+    assert c == {frozenset(range(5)), frozenset(range(2, 7))}
+
+
+def test_isolated_K5():
+    G = nx.Graph()
+    G.add_edges_from(combinations(range(0, 5), 2))  # Add a five clique
+    G.add_edges_from(combinations(range(5, 10), 2))  # Add another five clique
+    c = set(k_clique_communities(G, 5))
+    assert c == {frozenset(range(5)), frozenset(range(5, 10))}
+
+
+class TestZacharyKarateClub:
+    def setup(self):
+        self.G = nx.karate_club_graph()
+
+    def _check_communities(self, k, expected):
+        communities = set(k_clique_communities(self.G, k))
+        assert communities == expected
+
+    def test_k2(self):
+        # clique percolation with k=2 is just connected components
+        expected = {frozenset(self.G)}
+        self._check_communities(2, expected)
+
+    def test_k3(self):
+        comm1 = [
+            0,
+            1,
+            2,
+            3,
+            7,
+            8,
+            12,
+            13,
+            14,
+            15,
+            17,
+            18,
+            19,
+            20,
+            21,
+            22,
+            23,
+            26,
+            27,
+            28,
+            29,
+            30,
+            31,
+            32,
+            33,
+        ]
+        comm2 = [0, 4, 5, 6, 10, 16]
+        comm3 = [24, 25, 31]
+        expected = {frozenset(comm1), frozenset(comm2), frozenset(comm3)}
+        self._check_communities(3, expected)
+
+    def test_k4(self):
+        expected = {
+            frozenset([0, 1, 2, 3, 7, 13]),
+            frozenset([8, 32, 30, 33]),
+            frozenset([32, 33, 29, 23]),
+        }
+        self._check_communities(4, expected)
+
+    def test_k5(self):
+        expected = {frozenset([0, 1, 2, 3, 7, 13])}
+        self._check_communities(5, expected)
+
+    def test_k6(self):
+        expected = set()
+        self._check_communities(6, expected)
+
+
+def test_bad_k():
+    with pytest.raises(nx.NetworkXError):
+        list(k_clique_communities(nx.Graph(), 1))

venv/Lib/site-packages/networkx/algorithms/community/tests/test_kernighan_lin.py

@@ -0,0 +1,59 @@
+"""Unit tests for the :mod:`networkx.algorithms.community.kernighan_lin`
+module.
+
+"""
+import pytest
+
+import networkx as nx
+from networkx.algorithms.community import kernighan_lin_bisection
+from itertools import permutations
+
+
+def assert_partition_equal(x, y):
+    assert set(map(frozenset, x)) == set(map(frozenset, y))
+
+
+def test_partition():
+    G = nx.barbell_graph(3, 0)
+    C = kernighan_lin_bisection(G)
+    assert_partition_equal(C, [{0, 1, 2}, {3, 4, 5}])
+
+
+def test_partition_argument():
+    G = nx.barbell_graph(3, 0)
+    partition = [{0, 1, 2}, {3, 4, 5}]
+    C = kernighan_lin_bisection(G, partition)
+    assert_partition_equal(C, partition)
+
+
+def test_seed_argument():
+    G = nx.barbell_graph(3, 0)
+    C = kernighan_lin_bisection(G, seed=1)
+    assert_partition_equal(C, [{0, 1, 2}, {3, 4, 5}])
+
+
+def test_non_disjoint_partition():
+    with pytest.raises(nx.NetworkXError):
+        G = nx.barbell_graph(3, 0)
+        partition = ({0, 1, 2}, {2, 3, 4, 5})
+        kernighan_lin_bisection(G, partition)
+
+
+def test_too_many_blocks():
+    with pytest.raises(nx.NetworkXError):
+        G = nx.barbell_graph(3, 0)
+        partition = ({0, 1}, {2}, {3, 4, 5})
+        kernighan_lin_bisection(G, partition)
+
+
+def test_multigraph():
+    G = nx.cycle_graph(4)
+    M = nx.MultiGraph(G.edges())
+    M.add_edges_from(G.edges())
+    M.remove_edge(1, 2)
+    for labels in permutations(range(4)):
+        mapping = dict(zip(M, labels))
+        A, B = kernighan_lin_bisection(nx.relabel_nodes(M, mapping), seed=0)
+        assert_partition_equal(
+            [A, B], [{mapping[0], mapping[1]}, {mapping[2], mapping[3]}]
+        )

venv/Lib/site-packages/networkx/algorithms/community/tests/test_label_propagation.py

@@ -0,0 +1,154 @@
+from itertools import chain
+from itertools import combinations
+
+import pytest
+
+import networkx as nx
+from networkx.algorithms.community import label_propagation_communities
+from networkx.algorithms.community import asyn_lpa_communities
+
+
+def test_directed_not_supported():
+    with pytest.raises(nx.NetworkXNotImplemented):
+        # not supported for directed graphs
+        test = nx.DiGraph()
+        test.add_edge("a", "b")
+        test.add_edge("a", "c")
+        test.add_edge("b", "d")
+        result = label_propagation_communities(test)
+
+
+def test_one_node():
+    test = nx.Graph()
+    test.add_node("a")
+
+    # The expected communities are:
+    ground_truth = {frozenset(["a"])}
+
+    communities = label_propagation_communities(test)
+    result = {frozenset(c) for c in communities}
+    assert result == ground_truth
+
+
+def test_unconnected_communities():
+    test = nx.Graph()
+    # community 1
+    test.add_edge("a", "c")
+    test.add_edge("a", "d")
+    test.add_edge("d", "c")
+    # community 2
+    test.add_edge("b", "e")
+    test.add_edge("e", "f")
+    test.add_edge("f", "b")
+
+    # The expected communities are:
+    ground_truth = {frozenset(["a", "c", "d"]), frozenset(["b", "e", "f"])}
+
+    communities = label_propagation_communities(test)
+    result = {frozenset(c) for c in communities}
+    assert result == ground_truth
+
+
+def test_connected_communities():
+    test = nx.Graph()
+    # community 1
+    test.add_edge("a", "b")
+    test.add_edge("c", "a")
+    test.add_edge("c", "b")
+    test.add_edge("d", "a")
+    test.add_edge("d", "b")
+    test.add_edge("d", "c")
+    test.add_edge("e", "a")
+    test.add_edge("e", "b")
+    test.add_edge("e", "c")
+    test.add_edge("e", "d")
+    # community 2
+    test.add_edge("1", "2")
+    test.add_edge("3", "1")
+    test.add_edge("3", "2")
+    test.add_edge("4", "1")
+    test.add_edge("4", "2")
+    test.add_edge("4", "3")
+    test.add_edge("5", "1")
+    test.add_edge("5", "2")
+    test.add_edge("5", "3")
+    test.add_edge("5", "4")
+    # edge between community 1 and 2
+    test.add_edge("a", "1")
+    # community 3
+    test.add_edge("x", "y")
+    # community 4 with only a single node
+    test.add_node("z")
+
+    # The expected communities are:
+    ground_truth1 = {
+        frozenset(["a", "b", "c", "d", "e"]),
+        frozenset(["1", "2", "3", "4", "5"]),
+        frozenset(["x", "y"]),
+        frozenset(["z"]),
+    }
+    ground_truth2 = {
+        frozenset(["a", "b", "c", "d", "e", "1", "2", "3", "4", "5"]),
+        frozenset(["x", "y"]),
+        frozenset(["z"]),
+    }
+    ground_truth = (ground_truth1, ground_truth2)
+
+    communities = label_propagation_communities(test)
+    result = {frozenset(c) for c in communities}
+    assert result in ground_truth
+
+
+def test_termination():
+    # ensure termination of asyn_lpa_communities in two cases
+    # that led to an endless loop in a previous version
+    test1 = nx.karate_club_graph()
+    test2 = nx.caveman_graph(2, 10)
+    test2.add_edges_from([(0, 20), (20, 10)])
+    asyn_lpa_communities(test1)
+    asyn_lpa_communities(test2)
+
+
+class TestAsynLpaCommunities:
+    def _check_communities(self, G, expected):
+        """Checks that the communities computed from the given graph ``G``
+        using the :func:`~networkx.asyn_lpa_communities` function match
+        the set of nodes given in ``expected``.
+
+        ``expected`` must be a :class:`set` of :class:`frozenset`
+        instances, each element of which is a node in the graph.
+
+        """
+        communities = asyn_lpa_communities(G)
+        result = {frozenset(c) for c in communities}
+        assert result == expected
+
+    def test_null_graph(self):
+        G = nx.null_graph()
+        ground_truth = set()
+        self._check_communities(G, ground_truth)
+
+    def test_single_node(self):
+        G = nx.empty_graph(1)
+        ground_truth = {frozenset([0])}
+        self._check_communities(G, ground_truth)
+
+    def test_simple_communities(self):
+        # This graph is the disjoint union of two triangles.
+        G = nx.Graph(["ab", "ac", "bc", "de", "df", "fe"])
+        ground_truth = {frozenset("abc"), frozenset("def")}
+        self._check_communities(G, ground_truth)
+
+    def test_seed_argument(self):
+        G = nx.Graph(["ab", "ac", "bc", "de", "df", "fe"])
+        ground_truth = {frozenset("abc"), frozenset("def")}
+        communities = asyn_lpa_communities(G, seed=1)
+        result = {frozenset(c) for c in communities}
+        assert result == ground_truth
+
+    def test_several_communities(self):
+        # This graph is the disjoint union of five triangles.
+        ground_truth = {frozenset(range(3 * i, 3 * (i + 1))) for i in range(5)}
+        edges = chain.from_iterable(combinations(c, 2) for c in ground_truth)
+        G = nx.Graph(edges)
+        self._check_communities(G, ground_truth)

venv/Lib/site-packages/networkx/algorithms/community/tests/test_lukes.py

@@ -0,0 +1,154 @@
+from itertools import product
+
+import pytest
+
+import networkx as nx
+from networkx.algorithms.community import lukes_partitioning
+
+EWL = "e_weight"
+NWL = "n_weight"
+
+
+# first test from the Lukes original paper
+def paper_1_case(float_edge_wt=False, explicit_node_wt=True, directed=False):
+
+    # problem-specific constants
+    limit = 3
+
+    # configuration
+    if float_edge_wt:
+        shift = 0.001
+    else:
+        shift = 0
+
+    if directed:
+        example_1 = nx.DiGraph()
+    else:
+        example_1 = nx.Graph()
+
+    # graph creation
+    example_1.add_edge(1, 2, **{EWL: 3 + shift})
+    example_1.add_edge(1, 4, **{EWL: 2 + shift})
+    example_1.add_edge(2, 3, **{EWL: 4 + shift})
+    example_1.add_edge(2, 5, **{EWL: 6 + shift})
+
+    # node weights
+    if explicit_node_wt:
+        nx.set_node_attributes(example_1, 1, NWL)
+        wtu = NWL
+    else:
+        wtu = None
+
+    # partitioning
+    clusters_1 = {
+        frozenset(x)
+        for x in lukes_partitioning(example_1, limit, node_weight=wtu, edge_weight=EWL)
+    }
+
+    return clusters_1
+
+
+# second test from the Lukes original paper
+def paper_2_case(explicit_edge_wt=True, directed=False):
+
+    # problem specific constants
+    byte_block_size = 32
+
+    # configuration
+    if directed:
+        example_2 = nx.DiGraph()
+    else:
+        example_2 = nx.Graph()
+
+    if explicit_edge_wt:
+        edic = {EWL: 1}
+        wtu = EWL
+    else:
+        edic = {}
+        wtu = None
+
+    # graph creation
+    example_2.add_edge("name", "home_address", **edic)
+    example_2.add_edge("name", "education", **edic)
+    example_2.add_edge("education", "bs", **edic)
+    example_2.add_edge("education", "ms", **edic)
+    example_2.add_edge("education", "phd", **edic)
+    example_2.add_edge("name", "telephone", **edic)
+    example_2.add_edge("telephone", "home", **edic)
+    example_2.add_edge("telephone", "office", **edic)
+    example_2.add_edge("office", "no1", **edic)
+    example_2.add_edge("office", "no2", **edic)
+
+    example_2.nodes["name"][NWL] = 20
+    example_2.nodes["education"][NWL] = 10
+    example_2.nodes["bs"][NWL] = 1
+    example_2.nodes["ms"][NWL] = 1
+    example_2.nodes["phd"][NWL] = 1
+    example_2.nodes["home_address"][NWL] = 8
+    example_2.nodes["telephone"][NWL] = 8
+    example_2.nodes["home"][NWL] = 8
+    example_2.nodes["office"][NWL] = 4
+    example_2.nodes["no1"][NWL] = 1
+    example_2.nodes["no2"][NWL] = 1
+
+    # partitioning
+    clusters_2 = {
+        frozenset(x)
+        for x in lukes_partitioning(
+            example_2, byte_block_size, node_weight=NWL, edge_weight=wtu
+        )
+    }
+
+    return clusters_2
+
+
+def test_paper_1_case():
+    ground_truth = {frozenset([1, 4]), frozenset([2, 3, 5])}
+
+    tf = (True, False)
+    for flt, nwt, drc in product(tf, tf, tf):
+        part = paper_1_case(flt, nwt, drc)
+        assert part == ground_truth
+
+
+def test_paper_2_case():
+    ground_truth = {
+        frozenset(["education", "bs", "ms", "phd"]),
+        frozenset(["name", "home_address"]),
+        frozenset(["telephone", "home", "office", "no1", "no2"]),
+    }
+
+    tf = (True, False)
+    for ewt, drc in product(tf, tf):
+        part = paper_2_case(ewt, drc)
+        assert part == ground_truth
+
+
+def test_mandatory_tree():
+    not_a_tree = nx.complete_graph(4)
+
+    with pytest.raises(nx.NotATree):
+        lukes_partitioning(not_a_tree, 5)
+
+
+def test_mandatory_integrality():
+
+    byte_block_size = 32
+
+    ex_1_broken = nx.DiGraph()
+
+    ex_1_broken.add_edge(1, 2, **{EWL: 3.2})
+    ex_1_broken.add_edge(1, 4, **{EWL: 2.4})
+    ex_1_broken.add_edge(2, 3, **{EWL: 4.0})
+    ex_1_broken.add_edge(2, 5, **{EWL: 6.3})
+
+    ex_1_broken.nodes[1][NWL] = 1.2  # !
+    ex_1_broken.nodes[2][NWL] = 1
+    ex_1_broken.nodes[3][NWL] = 1
+    ex_1_broken.nodes[4][NWL] = 1
+    ex_1_broken.nodes[5][NWL] = 2
+
+    with pytest.raises(TypeError):
+        lukes_partitioning(
+            ex_1_broken, byte_block_size, node_weight=NWL, edge_weight=EWL
+        )

venv/Lib/site-packages/networkx/algorithms/community/tests/test_modularity_max.py

@@ -0,0 +1,39 @@
+import networkx as nx
+from networkx.algorithms.community import (
+    greedy_modularity_communities,
+    naive_greedy_modularity_communities,
+)
+
+
+class TestCNM:
+    def setup(self):
+        self.G = nx.karate_club_graph()
+
+    def _check_communities(self, expected):
+        communities = set(greedy_modularity_communities(self.G))
+        assert communities == expected
+
+    def test_karate_club(self):
+        john_a = frozenset(
+            [8, 14, 15, 18, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33]
+        )
+        mr_hi = frozenset([0, 4, 5, 6, 10, 11, 16, 19])
+        overlap = frozenset([1, 2, 3, 7, 9, 12, 13, 17, 21])
+        self._check_communities({john_a, overlap, mr_hi})
+
+
+class TestNaive:
+    def setup(self):
+        self.G = nx.karate_club_graph()
+
+    def _check_communities(self, expected):
+        communities = set(naive_greedy_modularity_communities(self.G))
+        assert communities == expected
+
+    def test_karate_club(self):
+        john_a = frozenset(
+            [8, 14, 15, 18, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33]
+        )
+        mr_hi = frozenset([0, 4, 5, 6, 10, 11, 16, 19])
+        overlap = frozenset([1, 2, 3, 7, 9, 12, 13, 17, 21])
+        self._check_communities({john_a, overlap, mr_hi})

venv/Lib/site-packages/networkx/algorithms/community/tests/test_quality.py

@@ -0,0 +1,84 @@
+"""Unit tests for the :mod:`networkx.algorithms.community.quality`
+module.
+
+"""
+
+import networkx as nx
+from networkx import barbell_graph
+from networkx.algorithms.community import coverage
+from networkx.algorithms.community import modularity
+from networkx.algorithms.community import performance
+from networkx.algorithms.community.quality import inter_community_edges
+from networkx.testing import almost_equal
+
+
+class TestPerformance:
+    """Unit tests for the :func:`performance` function."""
+
+    def test_bad_partition(self):
+        """Tests that a poor partition has a low performance measure."""
+        G = barbell_graph(3, 0)
+        partition = [{0, 1, 4}, {2, 3, 5}]
+        assert almost_equal(8 / 15, performance(G, partition))
+
+    def test_good_partition(self):
+        """Tests that a good partition has a high performance measure.
+
+        """
+        G = barbell_graph(3, 0)
+        partition = [{0, 1, 2}, {3, 4, 5}]
+        assert almost_equal(14 / 15, performance(G, partition))
+
+
+class TestCoverage:
+    """Unit tests for the :func:`coverage` function."""
+
+    def test_bad_partition(self):
+        """Tests that a poor partition has a low coverage measure."""
+        G = barbell_graph(3, 0)
+        partition = [{0, 1, 4}, {2, 3, 5}]
+        assert almost_equal(3 / 7, coverage(G, partition))
+
+    def test_good_partition(self):
+        """Tests that a good partition has a high coverage measure."""
+        G = barbell_graph(3, 0)
+        partition = [{0, 1, 2}, {3, 4, 5}]
+        assert almost_equal(6 / 7, coverage(G, partition))
+
+
+def test_modularity():
+    G = nx.barbell_graph(3, 0)
+    C = [{0, 1, 4}, {2, 3, 5}]
+    assert almost_equal(-16 / (14 ** 2), modularity(G, C))
+    C = [{0, 1, 2}, {3, 4, 5}]
+    assert almost_equal((35 * 2) / (14 ** 2), modularity(G, C))
+
+    n = 1000
+    G = nx.erdos_renyi_graph(n, 0.09, seed=42, directed=True)
+    C = [set(range(n // 2)), set(range(n // 2, n))]
+    assert almost_equal(0.00017154251389292754, modularity(G, C))
+
+    G = nx.margulis_gabber_galil_graph(10)
+    mid_value = G.number_of_nodes() // 2
+    nodes = list(G.nodes)
+    C = [set(nodes[:mid_value]), set(nodes[mid_value:])]
+    assert almost_equal(0.13, modularity(G, C))
+
+    G = nx.DiGraph()
+    G.add_edges_from([(2, 1), (2, 3), (3, 4)])
+    C = [{1, 2}, {3, 4}]
+    assert almost_equal(2 / 9, modularity(G, C))
+
+
+def test_inter_community_edges_with_digraphs():
+    G = nx.complete_graph(2, create_using=nx.DiGraph())
+    partition = [{0}, {1}]
+    assert inter_community_edges(G, partition) == 2
+
+    G = nx.complete_graph(10, create_using=nx.DiGraph())
+    partition = [{0}, {1, 2}, {3, 4, 5}, {6, 7, 8, 9}]
+    assert inter_community_edges(G, partition) == 70
+
+    G = nx.cycle_graph(4, create_using=nx.DiGraph())
+    partition = [{0, 1}, {2, 3}]
+    assert inter_community_edges(G, partition) == 2

venv/Lib/site-packages/networkx/algorithms/community/tests/test_utils.py

@@ -0,0 +1,29 @@
+"""Unit tests for the :mod:`networkx.algorithms.community.utils` module.
+
+"""
+
+import networkx as nx
+from networkx.algorithms.community import is_partition
+
+
+def test_is_partition():
+    G = nx.empty_graph(3)
+    assert is_partition(G, [{0, 1}, {2}])
+    assert is_partition(G, ({0, 1}, {2}))
+    assert is_partition(G, ([0, 1], [2]))
+    assert is_partition(G, [[0, 1], [2]])
+
+
+def test_not_covering():
+    G = nx.empty_graph(3)
+    assert not is_partition(G, [{0}, {1}])
+
+
+def test_not_disjoint():
+    G = nx.empty_graph(3)
+    assert not is_partition(G, [{0, 1}, {1, 2}])
+
+
+def test_not_node():
+    G = nx.empty_graph(3)
+    assert not is_partition(G, [{0, 1}, {3}])