docstr: Weighted betweenness centrality: Les Miserables graph
docstr_tok: ["Weighted","betweenness","centrality",":","Les","Miserables","graph"]
code: def test_les_miserables_graph(self):
      """Weighted betweenness centrality: Les Miserables graph"""
      G = nx.les_miserables_graph()
      b_answer = {
          "Napoleon": 0.000,
          "Myriel": 0.177,
          "MlleBaptistine": 0.000,
          "MmeMagloire": 0.000,
          "CountessDeLo": 0.000,
          "Geborand": 0.000,
          "Champtercier": 0.000,
          "Cravatte": 0.000,
          "Count": 0.000,
          "OldMan": 0.000,
          "Valjean": 0.454,
          "Labarre": 0.000,
          "Marguerite": 0.009,
          "MmeDeR": 0.000,
          "Isabeau": 0.000,
          "Gervais": 0.000,
          "Listolier": 0.000,
          "Tholomyes": 0.066,
          "Fameuil": 0.000,
          "Blacheville": 0.000,
          "Favourite": 0.000,
          "Dahlia": 0.000,
          "Zephine": 0.000,
          "Fantine": 0.114,
          "MmeThenardier": 0.046,
          "Thenardier": 0.129,
          "Cosette": 0.075,
          "Javert": 0.193,
          "Fauchelevent": 0.026,
          "Bamatabois": 0.080,
          "Perpetue": 0.000,
          "Simplice": 0.001,
          "Scaufflaire": 0.000,
          "Woman1": 0.000,
          "Judge": 0.000,
          "Champmathieu": 0.000,
          "Brevet": 0.000,
          "Chenildieu": 0.000,
          "Cochepaille": 0.000,
          "Pontmercy": 0.023,
          "Boulatruelle": 0.000,
          "Eponine": 0.023,
          "Anzelma": 0.000,
          "Woman2": 0.000,
          "MotherInnocent": 0.000,
          "Gribier": 0.000,
          "MmeBurgon": 0.026,
          "Jondrette": 0.000,
          "Gavroche": 0.285,
          "Gillenormand": 0.024,
          "Magnon": 0.005,
          "MlleGillenormand": 0.036,
          "MmePontmercy": 0.005,
          "MlleVaubois": 0.000,
          "LtGillenormand": 0.015,
          "Marius": 0.072,
          "BaronessT": 0.004,
          "Mabeuf": 0.089,
          "Enjolras": 0.003,
          "Combeferre": 0.000,
          "Prouvaire": 0.000,
          "Feuilly": 0.004,
          "Courfeyrac": 0.001,
          "Bahorel": 0.007,
          "Bossuet": 0.028,
          "Joly": 0.000,
          "Grantaire": 0.036,
          "MotherPlutarch": 0.000,
          "Gueulemer": 0.025,
          "Babet": 0.015,
          "Claquesous": 0.042,
          "Montparnasse": 0.050,
          "Toussaint": 0.011,
          "Child1": 0.000,
          "Child2": 0.000,
          "Brujon": 0.002,
          "MmeHucheloup": 0.034,
      }
  
      b = nx.betweenness_centrality(G, weight="weight", normalized=True)
      for n in sorted(G):
          assert b[n] == pytest.approx(b_answer[n], abs=1e-3)
  
imports: import pytest
  import networkx
label_desc: Use image node_id 7 for calling the TestWeightedBetweennessCentrality obj's underlying member method code with example usage: obj.test_les_miserables_graph() without return types