code: def test_simrank_between_versions(self):
      G = nx.cycle_graph(5)
      # _python tolerance 1e-4
      expected_python_tol4 = {
          0: 1,
          1: 0.394512499239852,
          2: 0.5703550452791322,
          3: 0.5703550452791323,
          4: 0.394512499239852,
      }
      # _numpy tolerance 1e-4
      expected_numpy_tol4 = {
          0: 1.0,
          1: 0.3947180735764555,
          2: 0.570482097206368,
          3: 0.570482097206368,
          4: 0.3947180735764555,
      }
      actual = nx.simrank_similarity(G, source=0)
      assert expected_numpy_tol4 == pytest.approx(actual, abs=1e-7)
      # versions differ at 1e-4 level but equal at 1e-3
      assert expected_python_tol4 != pytest.approx(actual, abs=1e-4)
      assert expected_python_tol4 == pytest.approx(actual, abs=1e-3)
  
      actual = nx.similarity._simrank_similarity_python(G, source=0)
      assert expected_python_tol4 == pytest.approx(actual, abs=1e-7)
      # versions differ at 1e-4 level but equal at 1e-3
      assert expected_numpy_tol4 != pytest.approx(actual, abs=1e-4)
      assert expected_numpy_tol4 == pytest.approx(actual, abs=1e-3)
  
imports: import pytest
  import networkx
  from networkx.algorithms.similarity import graph_edit_distance, optimal_edit_paths, optimize_graph_edit_distance
  from networkx.generators.classic import circular_ladder_graph, cycle_graph, path_graph, wheel_graph
label_desc: Use image node_id 35 for calling the TestSimilarity obj's underlying member method code with example usage: obj.test_simrank_between_versions() without return types