docs: def ess(weights):
      r"""Calculate the normalized effective sample size :math:`ESS` [LC95]_
      of samples with ``weights`` :math:`\omega_i`.  :math:`ESS=0` is
      terrible and :math:`ESS=1` is perfect.
  
      .. math::
  
          ESS = \frac{1}{1+C^2}
  
      where
  
      .. math::
  
          C^2 = \frac{1}{N} \sum_{i=1}^N (N \bar{\omega}_i - 1)^2
  
      .. math::
  
          \bar{\omega}_i = \frac{\omega_i}{\sum_i \omega_i}
  
      :param weights:
  
          Vector-like array; the samples' weights
  
      """
      # normalize weights
      w = _np.asarray(weights) / _np.sum(weights)
  
      # ess
      coeff_var = _np.sum((len(w) * w - 1)**2) / len(w)
  
      return  1.0 / (1.0 + coeff_var)