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diff --git a/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_wiener.py b/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_wiener.py
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+++ b/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_wiener.py
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+import networkx as nx
+
+
+def test_wiener_index_of_disconnected_graph():
+    assert nx.wiener_index(nx.empty_graph(2)) == float("inf")
+
+
+def test_wiener_index_of_directed_graph():
+    G = nx.complete_graph(3)
+    H = nx.DiGraph(G)
+    assert (2 * nx.wiener_index(G)) == nx.wiener_index(H)
+
+
+def test_wiener_index_of_complete_graph():
+    n = 10
+    G = nx.complete_graph(n)
+    assert nx.wiener_index(G) == (n * (n - 1) / 2)
+
+
+def test_wiener_index_of_path_graph():
+    # In P_n, there are n - 1 pairs of vertices at distance one, n -
+    # 2 pairs at distance two, n - 3 at distance three, ..., 1 at
+    # distance n - 1, so the Wiener index should be
+    #
+    #     1 * (n - 1) + 2 * (n - 2) + ... + (n - 2) * 2 + (n - 1) * 1
+    #
+    # For example, in P_5,
+    #
+    #     1 * 4 + 2 * 3 + 3 * 2 + 4 * 1 = 2 (1 * 4 + 2 * 3)
+    #
+    # and in P_6,
+    #
+    #     1 * 5 + 2 * 4 + 3 * 3 + 4 * 2 + 5 * 1 = 2 (1 * 5 + 2 * 4) + 3 * 3
+    #
+    # assuming n is *odd*, this gives the formula
+    #
+    #     2 \sum_{i = 1}^{(n - 1) / 2} [i * (n - i)]
+    #
+    # assuming n is *even*, this gives the formula
+    #
+    #     2 \sum_{i = 1}^{n / 2} [i * (n - i)] - (n / 2) ** 2
+    #
+    n = 9
+    G = nx.path_graph(n)
+    expected = 2 * sum(i * (n - i) for i in range(1, (n // 2) + 1))
+    actual = nx.wiener_index(G)
+    assert expected == actual
+
+
+def test_schultz_and_gutman_index_of_disconnected_graph():
+    n = 4
+    G = nx.Graph()
+    G.add_nodes_from(list(range(1, n + 1)))
+    expected = float("inf")
+
+    G.add_edge(1, 2)
+    G.add_edge(3, 4)
+
+    actual_1 = nx.schultz_index(G)
+    actual_2 = nx.gutman_index(G)
+
+    assert expected == actual_1
+    assert expected == actual_2
+
+
+def test_schultz_and_gutman_index_of_complete_bipartite_graph_1():
+    n = 3
+    m = 3
+    cbg = nx.complete_bipartite_graph(n, m)
+
+    expected_1 = n * m * (n + m) + 2 * n * (n - 1) * m + 2 * m * (m - 1) * n
+    actual_1 = nx.schultz_index(cbg)
+
+    expected_2 = n * m * (n * m) + n * (n - 1) * m * m + m * (m - 1) * n * n
+    actual_2 = nx.gutman_index(cbg)
+
+    assert expected_1 == actual_1
+    assert expected_2 == actual_2
+
+
+def test_schultz_and_gutman_index_of_complete_bipartite_graph_2():
+    n = 2
+    m = 5
+    cbg = nx.complete_bipartite_graph(n, m)
+
+    expected_1 = n * m * (n + m) + 2 * n * (n - 1) * m + 2 * m * (m - 1) * n
+    actual_1 = nx.schultz_index(cbg)
+
+    expected_2 = n * m * (n * m) + n * (n - 1) * m * m + m * (m - 1) * n * n
+    actual_2 = nx.gutman_index(cbg)
+
+    assert expected_1 == actual_1
+    assert expected_2 == actual_2
+
+
+def test_schultz_and_gutman_index_of_complete_graph():
+    n = 5
+    cg = nx.complete_graph(n)
+
+    expected_1 = n * (n - 1) * (n - 1)
+    actual_1 = nx.schultz_index(cg)
+
+    assert expected_1 == actual_1
+
+    expected_2 = n * (n - 1) * (n - 1) * (n - 1) / 2
+    actual_2 = nx.gutman_index(cg)
+
+    assert expected_2 == actual_2
+
+
+def test_schultz_and_gutman_index_of_odd_cycle_graph():
+    k = 5
+    n = 2 * k + 1
+    ocg = nx.cycle_graph(n)
+
+    expected_1 = 2 * n * k * (k + 1)
+    actual_1 = nx.schultz_index(ocg)
+
+    expected_2 = 2 * n * k * (k + 1)
+    actual_2 = nx.gutman_index(ocg)
+
+    assert expected_1 == actual_1
+    assert expected_2 == actual_2