singular values and right eigenvectors out of eigenvalue decomposition (EVD)

EVD_MTJ_DenseMatrix.java

package hex.pca;

import hex.util.LinearAlgebraUtils;
import no.uib.cipr.matrix.DenseMatrix;
import no.uib.cipr.matrix.NotConvergedException;

/**
 * @author mathemage </ha@h2o.ai>
 * @date   1.5.17
 */
public class EVD_MTJ_DenseMatrix implements SVDInterface {
  private DenseMatrix gramMatrix;
  private no.uib.cipr.matrix.EVD evd;
  private double[][] eigenvectors;

  EVD_MTJ_DenseMatrix(double[][] gramMatrix) {
    this.gramMatrix = new DenseMatrix(gramMatrix);
    runEVD();
  }

  @Override
  public double[] getSingularValues() {
    return evd.getRealEigenvalues();
  }

  @Override
  public double[][] getEigenvectors() {
    return eigenvectors;
  }

  private void runEVD() {
    int gramDimension = gramMatrix.numRows();
    try {
      // Note: gramMatrix will be overwritten after this
      evd = new no.uib.cipr.matrix.EVD(gramDimension).factor(gramMatrix);
    } catch (NotConvergedException e) {
      throw new RuntimeException(e);
    }
    double[] Vt_1D = evd.getRightEigenvectors().getData();
    eigenvectors = LinearAlgebraUtils.reshape1DArray(Vt_1D, gramDimension, gramDimension);
  }
}