docs: def footrule_dist(params1, params2=None):
      r"""Compute Spearman's footrule distance between two models.
  
      This function computes Spearman's footrule distance between the rankings
      induced by two parameter vectors. Let :math:`\sigma_i` be the rank of item
      ``i`` in the model described by ``params1``, and :math:`\tau_i` be its rank
      in the model described by ``params2``. Spearman's footrule distance is
      defined by
  
      .. math::
  
        \sum_{i=1}^N | \sigma_i - \tau_i |
  
      By convention, items with the lowest parameters are ranked first (i.e.,
      sorted using the natural order).
  
      If the argument ``params2`` is ``None``, the second model is assumed to
      rank the items by their index: item ``0`` has rank 1, item ``1`` has rank
      2, etc.
  
      Parameters
      ----------
      params1 : array_like
          Parameters of the first model.
      params2 : array_like, optional
          Parameters of the second model.
  
      Returns
      -------
      dist : float
          Spearman's footrule distance.
      """
      assert params2 is None or len(params1) == len(params2)
      ranks1 = rankdata(params1, method="average")
      if params2 is None:
          ranks2 = np.arange(1, len(params1) + 1, dtype=float)
      else:
          ranks2 = rankdata(params2, method="average")
      return np.sum(np.abs(ranks1 - ranks2))