#NEWLINE# def E_log_pdf( self , Data ) : #NEWLINE# #INDENT# ' Calculate E[ log p( x_n | theta ) ] for each x_n in Data.X\n        \n        Args\n        -------\n        Data : bnpy XData object\n                with attribute Data.X, numpy 2D array of size nObs x D\n\n        Returns\n        -------\n        logp : numpy 1D array, length nObs\n    ' #NEWLINE# logPDFConst = ( ( ( ( - 0.5 ) * self . D ) * LOGTWOPI ) + ( 0.5 * np . sum ( self . E_logLam ( ) ) ) ) #NEWLINE# logPDFData = ( ( - 0.5 ) * self . E_distMahalanobis ( Data . X ) ) #NEWLINE# return ( logPDFConst + logPDFData )