Examples of org.netlib.util.intW

org.netlib.util.intW

        if (notspd)
            throw new MatrixNotSPDException();
        if (B.numRows() != n)
            throw new IllegalArgumentException("B.numRows() != n");


        intW info = new intW(0);
        if (upper)
            LAPACK.getInstance().dpptrs(UpLo.Upper.netlib(), Cu.numRows(),
                    B.numColumns(), Cu.getData(), B.getData(), Matrices.ld(Cu.numRows()), info);
        else
            LAPACK.getInstance().dpptrs(UpLo.Lower.netlib(), Cl.numRows(),

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        double anorm = A.norm(Norm.One);


        double[] work = new double[3 * n];
        int[] iwork = new int[n];


        intW info = new intW(0);
        doubleW rcond = new doubleW(0);
        if (upper)
            LAPACK.getInstance().dppcon(UpLo.Upper.netlib(), n, Cu.getData(), anorm,
                    rcond, work, iwork, info);
        else

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        int lwork;


        // Query optimal workspace. First for computing the factorization
        {
            work = new double[1];
            intW info = new intW(0);
            LAPACK.getInstance().dgeqrf(m, n, new double[0], Matrices.ld(m), new double[0],
                    work, -1, info);


            if (info.val != 0)
                lwork = n;
            else
                lwork = (int) work[0];
            lwork = Math.max(1, lwork);
            work = new double[lwork];
        }


        // Workspace needed for generating an explicit orthogonal matrix
        {
            workGen = new double[1];
            intW info = new intW(0);
            LAPACK.getInstance().dorgqr(m, n, k, new double[0],
              Matrices.ld(m), new double[0], workGen, -1, info);


            if (info.val != 0)
                lwork = n;

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            throw new IllegalArgumentException("R == null");


        /*
         * Calculate factorisation, and extract the triangular factor
         */
        intW info = new intW(0);
        LAPACK.getInstance().dgeqrf(m, n, A.getData(), Matrices.ld(m), tau, work,
                work.length, info);


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

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        double[] newData = data.clone();
        int[] ipiv = new int[numRows];


        // Query optimal workspace
        double[] work = new double[1];
        intW info = new intW(0);
        LAPACK.getInstance().dsysv(uplo.netlib(), numRows, X.numColumns(),
                newData, Matrices.ld(numRows), ipiv, Xd, Matrices.ld(numRows),
                work, -1, info);


        // Allocate workspace

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


        X.set(B);


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


        if (info.val > 0)
            throw new MatrixNotSPDException();

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        uplo = upper ? UpLo.Upper : UpLo.Lower;


        // Find the needed workspace
        double[] worksize = new double[1];
        int[] iworksize = new int[1];
        intW info = new intW(0);
        LAPACK.getInstance().dspevd(job.netlib(), uplo.netlib(), n, new double[0],
                new double[0], new double[0], Matrices.ld(n), worksize, -1, iworksize, -1, info);


        // Allocate workspace
        int lwork = 0, liwork = 0;

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    private SymmPackEVD factor(Matrix A, double[] data)
            throws NotConvergedException {
        if (A.numRows() != n)
            throw new IllegalArgumentException("A.numRows() != n");


        intW info = new intW(0);
        LAPACK.getInstance().dspevd(job.netlib(), uplo.netlib(), n, data, w,
                job == JobEig.All ? Z.getData() : new double[0], Matrices.ld(n), work,
                work.length, iwork, iwork.length, info);


        if (info.val > 0)

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        isuppz = new int[2 * Math.max(1, n)];


        // Find the needed workspace
        double[] worksize = new double[1];
        int[] iworksize = new int[1];
        intW info = new intW(0);
        LAPACK.getInstance().dsyevr(job.netlib(), range.netlib(), uplo.netlib(), n,
          new double[0], Matrices.ld(n), 0, 0, 0, 0, abstol, new intW(1), new double[0], new double[0],
          Matrices.ld(n), isuppz, worksize, -1, iworksize, -1, info);


        // Allocate workspace
        int lwork = 0, liwork = 0;
        if (info.val != 0) {

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    private SymmDenseEVD factor(Matrix A, double[] data)
            throws NotConvergedException {
        if (A.numRows() != n)
            throw new IllegalArgumentException("A.numRows() != n");


        intW info = new intW(0);
        LAPACK.getInstance().dsyevr(job.netlib(), range.netlib(), uplo.netlib(), n, data,
          Matrices.ld(n), 0, 0, 0, 0, abstol, new intW(1), w,
                job == JobEig.All ? Z.getData() : new double[0], Matrices.ld(n), isuppz, work,
                work.length, iwork, iwork.length, info);


        if (info.val > 0)
            throw new NotConvergedException(

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