code: def update(self, egg, permute=False, nperms=1000,
                   parallel=False):
          
  
          # increment n
          self.n+=1
  
          next_weights = np.nanmean(_analyze_chunk(egg,
                            analysis=fingerprint_helper,
                            analysis_type='fingerprint',
                            pass_features=True,
                            permute=permute,
                            n_perms=nperms,
                            parallel=parallel).values, 0)
  
          if self.state is not None:
  
              # multiply states by n
              c = self.state*self.n
  
              # update state
              self.state = np.nansum(np.array([c, next_weights]), axis=0)/(self.n+1)
  
          else:
  
              self.state = next_weights
  
          # update the history
          self.history.append(next_weights)
docs: In-place method that updates fingerprint with new data
  
          Parameters
          ----------
          egg : quail.Egg
              Data to update fingerprint
          Returns
          ----------
          None