

def Elogp_Edges(self, SS, LP):
    ' This should be different depending on assorative / non-assortative model\n    '
    Elogp_Edges = (np.sum((self['edge_variational'] * LP['E_logsoftev_EdgeLik'])) + np.sum(((1 - np.sum(LP['edge_variational'], axis=1)) * LP['E_logsoftev_EdgeEps'])))
    return Elogp_Edges

dataset/ETHPy150Open daeilkim/refinery/refinery/bnpy/bnpy-dev/bnpy/obsmodel/BernRelObsModel.py BernRelObsModel.Elogp_Edges/VarMisuse@24/64 `LP`->`self`