code: def weight_by_edge_odds_ratios(self,
                                     edges_expected_weight,
                                     flag_as_significant):
          
          for edge_id, expected_weight in edges_expected_weight:
              edge_obj = self.edges[edge_id]
              edge_obj.weight /= expected_weight
              if edge_id in flag_as_significant:
                  edge_obj.significant = True
              else:
                  edge_obj.significant = False
docs: Applied during the permutation test. Update the edges in the
          network to be weighted by their odds ratios. The odds ratio measures
          how unexpected the observed edge weight is based on the expected
          weight.
  
          Parameters
          -----------
          edges_expected_weight : list(tup(int, int), float)
            A tuple list of (edge id, edge expected weight) generated from the
            permutation test step.
          flag_as_significant : [set|list](tup(int, int))
            A set or list of edge ids that are considered significant against
            the null model of random associations generated in the permutation
            test