def Elogp_Lam(self):
    logNormC = gammaln(self.obsPrior.lamA + self.obsPrior.lamB) \
             - gammaln(self.obsPrior.lamA) - gammaln(self.obsPrior.lamB)
    logPDF = 0
    for k in xrange(self.K):
        logPDF += (self.obsPrior.lamA - 1.0)*self.comp[k].ElogLamA \
                + (self.obsPrior.lamB - 1.0)*self.comp[k].ElogLamB
    return np.sum(logPDF + (self.K * logNormC) )
Get the log pdf of the beta for ELBO
dataset/ETHPy150Open daeilkim/refinery/refinery/bnpy/bnpy-dev/bnpy/obsmodel/BernRelObsModel.py/BernRelObsModel.Elogp_Lam