def _get_corr_stddevs(C, tau_ss, stddev_types, num_sites, phi_ss, NL=None,
                      tau_value=None):
    """
    Return standard deviations adjusted for single station sigma
    as the total standard deviation - as proposed to be used in
    the Swiss Hazard Model [2014].
    """
    stddevs = []
    temp_stddev = phi_ss * phi_ss

    if tau_value is not None and NL is not None:
        temp_stddev = temp_stddev + tau_value * tau_value * ((1 + NL) ** 2)
    else:
        temp_stddev = temp_stddev + C[tau_ss] * C[tau_ss]

    for stddev_type in stddev_types:
        if stddev_type == const.StdDev.TOTAL:
            stddevs.append(np.sqrt(temp_stddev) + np.zeros(num_sites))
    return stddevs
def _get_corr_stddevs ( C , tau_ss , stddev_types , num_sites , phi_ss , NL = None , tau_value = None ) : stddevs = [ ] temp_stddev = phi_ss * phi_ss if tau_value is not None and NL is not None : temp_stddev = temp_stddev + tau_value * tau_value * ( ( 1 + NL ) ** 2 ) else : temp_stddev = temp_stddev + C [ tau_ss ] * C [ tau_ss ] for stddev_type in stddev_types : if stddev_type == const . StdDev . TOTAL : stddevs . append ( np . sqrt ( temp_stddev ) + np . zeros ( num_sites ) ) return stddevs
Return standard deviations adjusted for single station sigma
    as the total standard deviation - as proposed to be used in
    the Swiss Hazard Model [2014].