code: def vectorize_damping(params, damping=1.0, increase_list=[['psf-', 1e4]]):
      
      damp_vec = np.ones(len(params)) * damping
      for nm, fctr in increase_list:
          for a in range(damp_vec.size):
              if nm in params[a]:
                  damp_vec[a] *= fctr
      return damp_vec
docs: Returns a non-constant damping vector, allowing certain parameters to be
      more strongly damped than others.
  
      Parameters
      ----------
          params : List
              The list of parameter names, in order.
          damping : Float
              The default value of the damping.
          increase_list: List
              A nested 2-element list of the params to increase and their
              scale factors. All parameters containing the string
              increase_list[i][0] are increased by a factor increase_list[i][1].
      Returns
      -------
          damp_vec : np.ndarray
              The damping vector to use.