code: def regweight_from_parbound(pst):
      
  
      pst.parameter_data.index = pst.parameter_data.parnme
      pst.prior_information.index = pst.prior_information.pilbl
      for idx, parnme in enumerate(pst.prior_information.pilbl):
          if parnme in pst.parameter_data.index:
              row = pst.parameter_data.loc[parnme, :]
              lbnd,ubnd = row["parlbnd"], row["parubnd"]
              if row["partrans"].lower() == "log":
                  weight = 1.0 / (np.log10(ubnd) - np.log10(lbnd))
              else:
                  weight = 1.0 / (ubnd - lbnd)
              pst.prior_information.loc[parnme, "weight"] = weight
          else:
              print("prior information name does not correspond" +\
                    " to a parameter: " + str(parnme))
docs: sets regularization weights from parameter bounds
      which approximates the KL expansion.  Called by
      zero_order_tikhonov().
  
      Parameters
      ----------
      pst : pyemu.Pst
          a control file instance