code: def _ellipsoid_bootstrap_expand(args):
      
  
      # Unzipping.
      points, pointvol = args
      rstate = np.random
  
      # Resampling.
      npoints, ndim = points.shape
      idxs = rstate.randint(npoints, size=npoints)  # resample
      idx_in = np.unique(idxs)  # selected objects
      sel = np.ones(npoints, dtype='bool')
      sel[idx_in] = False
      idx_out = np.arange(npoints)[sel]  # "missing" objects
      if len(idx_out) < 2:  # edge case
          idx_out = np.append(idx_out, [0, 1])
      points_in, points_out = points[idx_in], points[idx_out]
  
      # Compute bounding ellipsoid.
      ell = bounding_ellipsoid(points_in, pointvol=pointvol)
  
      # Compute normalized distances to missing points.
      dists = [ell.distance(p) for p in points_out]
  
      # Compute expansion factor.
      expand = max(1., max(dists))
  
      return expand
docs: Internal method used to compute the expansion factor for a bounding
      ellipsoid based on bootstrapping.