Examples of cern.colt.matrix.linalg.SingularValueDecomposition

cern.colt.matrix.linalg.SingularValueDecomposition
For an m x n matrix A with m >= n, the singular value decomposition is an m x n orthogonal matrix U, an n x n diagonal matrix S, and an n x n orthogonal matrix V so that A = U*S*V'.
The singular values, sigma[k] = S[k][k], are ordered so that sigma[0] >= sigma[1] >= ... >= sigma[n-1].
The singular value decomposition always exists, so the constructor will never fail. The matrix condition number and the effective numerical rank can be computed from this decomposition.

 */
public class MultinormalPCAGen extends MultinormalGen {
   private double[] lambda;


   private static SingularValueDecomposition getSvd (DoubleMatrix2D sigma) {
      return (new SingularValueDecomposition (sigma));
   }

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   public static DoubleMatrix2D decompPCA (DoubleMatrix2D sigma)   {
      // L'objet SingularValueDecomposition permet de recuperer la matrice
      // des valeurs propres en ordre decroissant et celle des vecteurs propres de
      // sigma (pour une matrice symetrique et definie-positive seulement).


      SingularValueDecomposition sv = getSvd (sigma);
      // D contient les valeurs propres sur la diagonale
      DoubleMatrix2D D = sv.getS ();
      // Calculer la racine carree des valeurs propres
      for (int i = 0; i < D.rows(); ++i)
         D.setQuick (i, i, Math.sqrt (D.getQuick (i, i)));
      DoubleMatrix2D P = sv.getV();
      // Multiplier par la matrice orthogonale (ici P)
      return P.zMult (D, null);
   }

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    * Computes and returns the eigenvalues of <TT>sigma</TT> in
    *  decreasing order.
    * 
    */
   public static double[] getLambda (DoubleMatrix2D sigma) {
      SingularValueDecomposition sv = getSvd (sigma);
      DoubleMatrix2D D = sv.getS ();
      double[] lambd = new double[D.rows()];
      for (int i = 0; i < D.rows(); ++i)
         lambd[i] = D.getQuick (i, i);
      return lambd;
   }

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  @Override
  public SVDecompositionResult evaluate(final DoubleMatrix2D x) {
    Validate.notNull(x);
    MatrixValidate.notNaNOrInfinite(x);
    final cern.colt.matrix.DoubleMatrix2D coltMatrix = ColtMathWrapper.wrap(x);
    final SingularValueDecomposition svd = new SingularValueDecomposition(coltMatrix);
    return new SVDecompositionColtResult(svd);
  }

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