@not_implemented_for('directed')
@not_implemented_for('multigraph')
def adamic_adar_index(G, ebunch=None):
 def predict(u, v):
  return sum(((1 / log(G.degree(w))) for w in nx.common_neighbors(G, u, v)))
 return _apply_prediction(G, predict, ebunch)

@ not_implemented_for ( 'directed' ) @ not_implemented_for ( 'multigraph' ) def adamic_adar_index ( G , ebunch = None ) : def predict ( u , v ) : return sum ( ( ( 1 / log ( G . degree ( w ) ) ) for w in nx . common_neighbors ( G , u , v ) ) ) return _apply_prediction ( G , predict , ebunch )
compute the adamic-adar index of all node pairs in ebunch .