def _get_mean(self, sites, rup, dists, imt, stddev_types):
        """
        See :meth:`superclass method
        <.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
        for spec of input and result values.
        """
        # Zhao et al. 2006 - Vs30 + Rrup
        mean_zh06, stds1 = super().get_mean_and_stddevs(sites, rup, dists, imt,
                                                        stddev_types)
        #
        # Atkinson and Macias (2009) - Rrup
        gmpe = AtkinsonMacias2009()
        mean_am09, stds2 = gmpe.get_mean_and_stddevs(sites, rup, dists, imt,
                                                     stddev_types)
        #
        # Abrahamson et al. (2015) - Rrup + vs30 + backarc
        gmpe = AbrahamsonEtAl2015SInter()
        mean_ab15, stds3 = gmpe.get_mean_and_stddevs(sites, rup, dists, imt,
                                                     stddev_types)
        #
        # Ghofrani and Atkinson (2014) - Rrup + vs30
        gmpe = GhofraniAtkinson2014()
        mean_ga14, stds4 = gmpe.get_mean_and_stddevs(sites, rup, dists, imt,
                                                     stddev_types)
        # Computing adjusted mean and stds
        cff = self.SITE_COEFFS[imt]
        mean_adj = (np.log(np.exp(mean_zh06)*cff['mf'])*0.1 +
                    mean_am09*0.5 + mean_ab15*0.2 +
                    np.log(np.exp(mean_ga14)*cff['mf'])*0.2)
        return mean_adj
def _get_mean ( self , sites , rup , dists , imt , stddev_types ) : mean_zh06 , stds1 = super ( ) . get_mean_and_stddevs ( sites , rup , dists , imt , stddev_types ) gmpe = AtkinsonMacias2009 ( ) mean_am09 , stds2 = gmpe . get_mean_and_stddevs ( sites , rup , dists , imt , stddev_types ) gmpe = AbrahamsonEtAl2015SInter ( ) mean_ab15 , stds3 = gmpe . get_mean_and_stddevs ( sites , rup , dists , imt , stddev_types ) gmpe = GhofraniAtkinson2014 ( ) mean_ga14 , stds4 = gmpe . get_mean_and_stddevs ( sites , rup , dists , imt , stddev_types ) cff = self . SITE_COEFFS [ imt ] mean_adj = ( np . log ( np . exp ( mean_zh06 ) * cff [ 'mf' ] ) * 0.1 + mean_am09 * 0.5 + mean_ab15 * 0.2 + np . log ( np . exp ( mean_ga14 ) * cff [ 'mf' ] ) * 0.2 ) return mean_adj
See :meth:`superclass method
        <.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
        for spec of input and result values.