code: def eigenvector_centrality(self, normalized=True, reversed=True, rating={},
                                 start=None, iterations=100, tolerance=0.0001):
          
          ec = proximity.eigenvector_centrality(
              self, normalized, reversed, rating, start, iterations, tolerance
          )
          for id, w in ec.iteritems(): self[id]._eigenvalue = w
          return ec
docs: Calculates eigenvector centrality and returns an node id -> weight dictionary.
          Node eigenvalue weights are updated in the process.