docstr: Edge betweenness centrality: normalized weighted multigraph
docstr_tok: ["Edge","betweenness","centrality",":","normalized","weighted","multigraph"]
code: def test_normalized_weighted_multigraph(self):
      """Edge betweenness centrality: normalized weighted multigraph"""
      eList = [
          (0, 1, 5),
          (0, 1, 4),
          (0, 2, 4),
          (0, 3, 3),
          (0, 3, 3),
          (0, 4, 2),
          (1, 2, 4),
          (1, 3, 1),
          (1, 3, 2),
          (1, 4, 3),
          (1, 4, 4),
          (2, 4, 5),
          (3, 4, 4),
          (3, 4, 4),
      ]
      G = nx.MultiGraph()
      G.add_weighted_edges_from(eList)
      b = nx.edge_betweenness_centrality(
          G, weight="weight", normalized=True
      )
      b_answer = {
          (0, 1, 0): 0.0,
          (0, 1, 1): 0.5,
          (0, 2, 0): 1.0,
          (0, 3, 0): 0.75,
          (0, 3, 1): 0.75,
          (0, 4, 0): 1.0,
          (1, 2, 0): 2.0,
          (1, 3, 0): 3.0,
          (1, 3, 1): 0.0,
          (1, 4, 0): 1.5,
          (1, 4, 1): 0.0,
          (2, 4, 0): 1.0,
          (3, 4, 0): 0.25,
          (3, 4, 1): 0.25,
      }
      norm = len(G) * (len(G) - 1) / 2
      for n in sorted(G.edges(keys=True)):
          assert b[n] == pytest.approx(b_answer[n] / norm, abs=1e-7)
  
imports: import pytest
  import networkx
label_desc: Use image node_id 8 for calling the TestWeightedEdgeBetweennessCentrality obj's underlying member method code with example usage: obj.test_normalized_weighted_multigraph() without return types