code: package xyz.lejon.bayes.models.dolda;
  
  import org.apache.commons.configuration.ConfigurationException;
  import org.jblas.DoubleMatrix;
  import org.jblas.Solve;
  
  import xyz.lejon.configuration.DOLDAConfiguration;
  import xyz.lejon.sampling.FastMVNSamplerJBLAS;
  
  /**
   * This class implements the DO_Probit normal sampler as described in 
   * 'Diagonal Orthant Multinomial Probit Models', James E. Johndrow, Kristian Lum and David B. Dunson
   * 
   * It differs from plain BLR in that it does not sample sigma squared.
   * 
   * @author Leif Jonsson
   *
   */
  public class DOLDAGibbsJBlasDOProbitNormal extends EDOLDANormal {
  
  	private static final long serialVersionUID = 1L;
  
  	public DOLDAGibbsJBlasDOProbitNormal(DOLDAConfiguration parentCfg, double[][] xs, int[] iys) throws ConfigurationException {
  		super(parentCfg, xs, iys);
  		System.out.println("Using Beta sampler: " + this.getClass().getName());
  	}
  	
  	@Override
  	protected void sampleBetas(double [][] Xs, double [][] XtXs, double [][] Xts, double [][] precisions) {
  		
  		// Update diagonal elements of precision matrix
  		for (int i = 0; i < precisions.length; i++) {
  			precisions[i][i] =  XtXs[i][i] + (1 / c);
  		}
  		
  		for (int k = 0; k < noClasses; k++) {
  			sampleBeta(Xs, XtXs, Xts, precisions, k);
  			saveBetaSample(k);
  		}
  	}
  
  	protected void sampleBeta(double [][] Xs, double [][] XtXs, double [][] Xts, double [][] precisions,  int k) {
  		// Code review done Mans and Leif: 2015-11-02
  
  		DoubleMatrix X = new DoubleMatrix(Xs);
  		DoubleMatrix Xt = new DoubleMatrix(Xts);
  		DoubleMatrix precision = new DoubleMatrix(precisions);
  
  		double [] zColk = Ast[k]; // Our latent variables, a^T (transposed colvector for category k). 
  		DoubleMatrix zColKd = new DoubleMatrix(zColk);
  		//DoubleMatrix pInv = null;
  		DoubleMatrix localMu = new DoubleMatrix(X.columns, 1);
  		synchronized (betaLock) {
  			DoubleMatrix localTilde = Xt.mmul(zColKd); // X^T * a_k 
  			localMu = Solve.solve(precision, localTilde); // precision^-1 * localTilde => (X^T * X + L)^-1 X^T a_k
  			//localMu = pInv.mmul(localTilde);
  			//pInv = BlasOps.blasInvert(precision);
  		}
  		
  		//FastMVNSamplerJBLAS mvn = new FastMVNSamplerJBLAS(pInv);
  		FastMVNSamplerJBLAS mvn = new FastMVNSamplerJBLAS(precision, true);
  		betas[k] = mvn.sample(localMu);
  	}
  }
  