sets regularization weights from parameter bounds
    which approximates the KL expansion.  Called by
    zero_order_tikhonov().

    Parameters
    ----------
    pst : pyemu.Pst
        a control file instance

def regweight_from_parbound(pst):
    """sets regularization weights from parameter bounds
    which approximates the KL expansion.  Called by
    zero_order_tikhonov().

    Parameters
    ----------
    pst : pyemu.Pst
        a control file instance

    """

    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))