def E_logpLam( self ):
    lp = np.zeros( self.K) 
    for k in xrange( self.K ):
      lp[k] = 0.5*(self.obsPrior.v - 1 -self.D)*self.comp[k].ElogdetLam()
      lp[k] -= 0.5*self.comp[k].E_traceLam( cholS=self.obsPrior.cholinvW())
    return lp.sum() - self.K * self.obsPrior.get_log_norm_const()
dataset/ETHPy150Open daeilkim/refinery/refinery/bnpy/bnpy-dev/bnpy/obsmodel/ZMGaussObsModel.py/ZMGaussObsModel.E_logpLam/swapped operands of `-`