code: def repvals(self, method):
          
          if method == 'pct':
              return pk_scoreatpercentile(self.d, [50., 84.134, 15.866])
          if method == 'gauss':
              m, s = self.d.mean(), self.d.std()
              return np.asarray([m, m + s, m - s])
          raise ValueError('unknown representative-value method "%s"' % method)
docs: Compute representative statistical values for this Uval. `method`
          may be either 'pct' or 'gauss'.
  
          Returns (best, plus_one_sigma, minus_one_sigma), where `best` is the
          "best" value in some sense, and the others correspond to values at
          the ~84 and 16 percentile limits, respectively. Because of the
          sampled nature of the Uval system, there is no single method to
          compute these numbers.
  
          The "pct" method returns the 50th, 15.866th, and 84.134th percentile
          values.
  
          The "gauss" method computes the mean μ and standard deviation σ of the
          samples and returns [μ, μ+σ, μ-σ].