code: def test_fast_versions_properties_threshold_graphs(self):
      cs = "ddiiddid"
      G = nxt.threshold_graph(cs)
      assert nxt.density("ddiiddid") == nx.density(G)
      assert sorted(nxt.degree_sequence(cs)) == sorted(
          d for n, d in G.degree()
      )
  
      ts = nxt.triangle_sequence(cs)
      assert ts == list(nx.triangles(G).values())
      assert sum(ts) // 3 == nxt.triangles(cs)
  
      c1 = nxt.cluster_sequence(cs)
      c2 = list(nx.clustering(G).values())
      assert sum(abs(c - d) for c, d in zip(c1, c2)) == pytest.approx(
          0, abs=1e-7
      )
  
      b1 = nx.betweenness_centrality(G).values()
      b2 = nxt.betweenness_sequence(cs)
      assert sum(abs(c - d) for c, d in zip(b1, b2)) < 1e-7
  
      assert nxt.eigenvalues(cs) == [0, 1, 3, 3, 5, 7, 7, 8]
  
      # Degree Correlation
      assert abs(nxt.degree_correlation(cs) + 0.593038821954) < 1e-12
      assert nxt.degree_correlation("diiiddi") == -0.8
      assert nxt.degree_correlation("did") == -1.0
      assert nxt.degree_correlation("ddd") == 1.0
      assert nxt.eigenvalues("dddiii") == [0, 0, 0, 0, 3, 3]
      assert nxt.eigenvalues("dddiiid") == [0, 1, 1, 1, 4, 4, 7]
  
imports: import pytest
  import networkx
  import networkx.algorithms.threshold
  from networkx.algorithms.isomorphism.isomorph import graph_could_be_isomorphic
label_desc: Use image node_id 15 for calling the TestGeneratorThreshold obj's underlying member method code with example usage: obj.test_fast_versions_properties_threshold_graphs() without return types