code: def test_pairwise_bipartite_cc_functions():
      # Test functions for different kinds of bipartite clustering coefficients
      # between pairs of nodes using 3 example graphs from figure 5 p. 40
      # Latapy et al (2008)
      G1 = nx.Graph(
          [
              (0, 2),
              (0, 3),
              (0, 4),
              (0, 5),
              (0, 6),
              (1, 5),
              (1, 6),
              (1, 7),
          ]
      )
      G2 = nx.Graph([(0, 2), (0, 3), (0, 4), (1, 3), (1, 4), (1, 5)])
      G3 = nx.Graph(
          [
              (0, 2),
              (0, 3),
              (0, 4),
              (0, 5),
              (0, 6),
              (1, 5),
              (1, 6),
              (1, 7),
              (1, 8),
              (1, 9),
          ]
      )
      result = {
          0: [1 / 3.0, 2 / 3.0, 2 / 5.0],
          1: [1 / 2.0, 2 / 3.0, 2 / 3.0],
          2: [2 / 8.0, 2 / 5.0, 2 / 5.0],
      }
      for i, G in enumerate([G1, G2, G3]):
          assert bipartite.is_bipartite(G)
          assert cc_dot(set(G[0]), set(G[1])) == result[i][0]
          assert cc_min(set(G[0]), set(G[1])) == result[i][1]
          assert cc_max(set(G[0]), set(G[1])) == result[i][2]
  
file_path: networkx/networkx/algorithms/bipartite/tests/test_cluster.py
imports: import pytest
  import networkx
  from networkx.algorithms import bipartite
  from networkx.algorithms.bipartite.cluster import cc_dot, cc_max, cc_min
label_desc: Use image node_id 1 for calling a global function with example usage: test_pairwise_bipartite_cc_functions() without return types