Package org.ejml.alg.dense.decomposition.chol

Examples of org.ejml.alg.dense.decomposition.chol.CholeskyDecompositionInner

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     *
     * @return A new solver for symmetric positive definite matrices.
     */
    public static LinearSolver<DenseMatrix64F> symmPosDef( int matrixWidth ) {
        if(matrixWidth < EjmlParameters.SWITCH_BLOCK64_CHOLESKY )  {
            CholeskyDecompositionCommon decomp = new CholeskyDecompositionInner(true);
            return new LinearSolverChol(decomp);
        } else {
            if( EjmlParameters.MEMORY == EjmlParameters.MemoryUsage.FASTER )
                return new LinearSolverCholBlock64();
            else {
                CholeskyDecompositionCommon decomp = new CholeskyDecompositionInner(true);
                return new LinearSolverChol(decomp);
            }
        }
    }
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public class TestLinearSolverChol {

    @Test
    public void standardTests() {

        CholeskyDecompositionInner alg = new CholeskyDecompositionInner(true);
        LinearSolverChol solver = new LinearSolverChol(alg);

        BaseCholeskySolveTests tests = new BaseCholeskySolveTests();
        tests.standardTests(solver);
    }
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     * @return A new CholeskyDecomposition.
     */
    public static CholeskyDecomposition<DenseMatrix64F> chol( int matrixSize , boolean lower )
    {
        if( matrixSize < EjmlParameters.SWITCH_BLOCK64_CHOLESKY ) {
            return new CholeskyDecompositionInner(lower);
        } else if( EjmlParameters.MEMORY == EjmlParameters.MemoryUsage.FASTER ){
            return new CholeskyDecompositionBlock64(lower);
        } else {
            return new CholeskyDecompositionBlock(EjmlParameters.BLOCK_WIDTH_CHOL);
        }
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     * @param cov The covariance of the stribution.  Not modified.
     */
    public CovarianceRandomDraw( Random rand , DenseMatrix64F cov )
    {
        r = new DenseMatrix64F(cov.numRows,1);
        CholeskyDecompositionInner choleky = new CholeskyDecompositionInner( true);

        choleky.decompose(cov);

        A = choleky.getT();
        this.rand = rand;
    }
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     */
    public static boolean isPositiveDefinite( DenseMatrix64F A ) {
        if( !isSquare(A))
           return false;

        CholeskyDecompositionInner chol = new CholeskyDecompositionInner(true);
        if( chol.inputModified() )
            A = A.copy();

        return chol.decompose(A);
    }
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    }

    private static void runAlgorithms( DenseMatrix64F A , DenseMatrix64F b ,int numTrials )
    {
        System.out.println("Solve Cholesky         = "+solve(
                new LinearSolverChol(new CholeskyDecompositionInner(true)),
                A,b,numTrials));
        System.out.println("Solve Cholesky LDL     = "+solve(
                new LinearSolverCholLDL(new CholeskyDecompositionLDL()),
                A,b,numTrials));
    }
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//        System.out.println("invert GJ No Pivot     = "+ invertGJ_NoPivot(mat,numTrials));
//        System.out.println("invert GJ               = "+ invertGJ(mat,numTrials));
//        System.out.println("invert LU-NR            = "+ invertLU_nr(mat,numTrials));
//        System.out.println("invert LU-Alt           = "+ invertLU_alt(mat,numTrials));
        System.out.println("invert Cholesky Inner       = "+ invertCholesky(
                new LinearSolverChol(new CholeskyDecompositionInner( true)),
                mat,numTrials));
        System.out.println("invert Cholesky Block Dense = "+ invertCholesky(
                new LinearSolverChol(new CholeskyDecompositionBlock( EjmlParameters.BLOCK_WIDTH_CHOL)),
                mat,numTrials));
//        System.out.println("invert default              = "+ invertCholesky(
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Related Classes of org.ejml.alg.dense.decomposition.chol.CholeskyDecompositionInner

  • org.ejml.alg.dense.linsol.BenchmarkInvertSymPosDef
  • org.ejml.alg.dense.linsol.BenchmarkSolveSymPosDef
  • org.ejml.alg.dense.linsol.chol.TestLinearSolverChol
  • org.ejml.factory.DecompositionFactory
  • org.ejml.factory.LinearSolverFactory
  • org.ejml.ops.CovarianceRandomDraw
  • org.ejml.ops.MatrixFeatures
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