code: def sims_by_vec(self, vec, normalize=None):
          
          if normalize is None:
              normalize = self.qindex.normalize
          norm, self.qindex.normalize = self.qindex.normalize, normalize # store old value
          self.qindex.num_best = self.topsims
          sims = self.qindex[vec]
          self.qindex.normalize = norm # restore old value of qindex.normalize
          return self.sims2scores(sims)
docs: Find the most similar documents to a given vector (=already processed document).