Package org.netlib.util

Examples of org.netlib.util.intW

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        if (singular)
            throw new MatrixSingularException();
        if (B.numRows() != n)
            throw new IllegalArgumentException("B.numRows() != n");

        intW info = new intW(0);
        LAPACK.getInstance().dgbtrs(trans.netlib(), n, kl, ku, B.numColumns(),
                LU.getData(), 2 * kl + ku + 1, ipiv, B.getData(), Matrices.ld(n), info);

        if (info.val < 0)
            throw new IllegalArgumentException();
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        X.set(B);

        int[] piv = new int[numRows];

        intW info = new intW(0);
        LAPACK.getInstance().dgesv(numRows, B.numColumns(),
                data.clone(), Matrices.ld(numRows), piv, Xd, Matrices.ld(numRows), info);

        if (info.val > 0)
            throw new MatrixSingularException();
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                Xtmp.set(i, j, B.get(i, j));
        double[] newData = data.clone();

        // Query optimal workspace
        double[] work = new double[1];
        intW info = new intW(0);
        LAPACK.getInstance().dgels(trans.netlib(), numRows, numColumns, nrhs,
                newData, Matrices.ld(numRows), Xtmp.getData(), Matrices.ld(numRows, numColumns),
                work, -1, info);

        // Allocate workspace
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        X.set(B);

        int[] ipiv = new int[numRows];

        intW info = new intW(0);
        LAPACK.getInstance().dspsv(uplo.netlib(), numRows, X.numColumns(),
                data.clone(), ipiv, Xd, Matrices.ld(numRows), info);

        if (info.val > 0)
            throw new MatrixSingularException();
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        double[] Xd = ((DenseMatrix) X).getData();

        X.set(B);

        intW info = new intW(0);
        LAPACK.getInstance().dppsv(uplo.netlib(), numRows, X.numColumns(),
                data.clone(), Xd, Matrices.ld(numRows), info);

        if (info.val > 0)
            throw new MatrixNotSPDException();
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     * @return The current decomposition
     */
    public DenseLU factor(DenseMatrix A) {
        singular = false;

        intW info = new intW(0);
        LAPACK.getInstance().dgetrf(A.numRows(), A.numColumns(),
                A.getData(), Matrices.ld(A.numRows()), piv, info);

        if (info.val > 0)
            singular = true;
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        double anorm = A.norm(norm);

        int n = A.numRows();

        intW info = new intW(0);
        doubleW rcond = new doubleW(0);
        LAPACK.getInstance().dgecon(norm.netlib(), n, LU.getData(), Matrices.ld(n), anorm,
                rcond, new double[4 * n], new int[n], info);

        if (info.val < 0)
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        if (singular)
            throw new MatrixSingularException();
        if (B.numRows() != LU.numRows())
            throw new IllegalArgumentException("B.numRows() != LU.numRows()");

        intW info = new intW(0);
        LAPACK.getInstance().dgetrs(trans.netlib(), LU.numRows(),
                B.numColumns(), LU.getData(), Matrices.ld(LU.numRows()),
                piv, B.getData(), Matrices.ld(LU.numRows()), info);

        if (info.val < 0)
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        double[] Xd = ((DenseMatrix) X).getData();

        X.set(B);

        intW info = new intW(0);
        LAPACK.getInstance().dptsv(numRows, X.numColumns(),
                diag.clone(), offDiag.clone(), Xd, Matrices.ld(numRows), info);

        if (info.val > 0)
            throw new MatrixNotSPDException();
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        checkSolve(B, X);

        double[] Xd = ((DenseMatrix) X).getData();

        X.set(B);
        intW info = new intW(0);
        LAPACK.getInstance().dgtsv(numRows, X.numColumns(),
                offDiag.clone(), diag.clone(), offDiag.clone(), Xd, Matrices.ld(numRows), info);

        if (info.val > 0)
            throw new MatrixSingularException();
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Related Classes of org.netlib.util.intW

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  • ch.akuhn.matrix.eigenvalues.FewEigenvalues
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  • com.nr.ran.HashAll
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