Overview | Package | Class | Tree | Deprecated | Index | Help
PREV CLASS NEXT CLASS | FRAMES NO FRAMES
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD

## org.netlib.lapack
Class DGGSVP

    java.lang.Object
      org.netlib.lapack.DGGSVP

    public class DGGSVP

extends java.lang.Object

    DGGSVP is a simplified interface to the JLAPACK routine dggsvp.
    This interface converts Java-style 2D row-major arrays into
    the 1D column-major linearized arrays expected by the lower
    level JLAPACK routines.  Using this interface also allows you
    to omit offset and leading dimension arguments.  However, because
    of these conversions, these routines will be slower than the low
    level ones.  Following is the description from the original Fortran
    source.  Contact seymour@cs.utk.edu with any questions.

     *     ..
     *
     *  Purpose
     *  =======
     *
     *  DGGSVP computes orthogonal matrices U, V and Q such that
     *
     *                   N-K-L  K    L
     *   U'*A*Q =     K ( 0    A12  A13 )  if M-K-L >= 0;
     *                L ( 0     0   A23 )
     *            M-K-L ( 0     0    0  )
     *
     *                   N-K-L  K    L
     *          =     K ( 0    A12  A13 )  if M-K-L < 0;
     *              M-K ( 0     0   A23 )
     *
     *                 N-K-L  K    L
     *   V'*B*Q =   L ( 0     0   B13 )
     *            P-L ( 0     0    0  )
     *
     *  where the K-by-K matrix A12 and L-by-L matrix B13 are nonsingular
     *  upper triangular; A23 is L-by-L upper triangular if M-K-L >= 0,
     *  otherwise A23 is (M-K)-by-L upper trapezoidal.  K+L = the effective
     *  numerical rank of the (M+P)-by-N matrix (A',B')'.  Z' denotes the
     *  transpose of Z.
     *
     *  This decomposition is the preprocessing step for computing the
     *  Generalized Singular Value Decomposition (GSVD), see subroutine
     *  DGGSVD.
     *
     *  Arguments
     *  =========
     *
     *  JOBU    (input) CHARACTER*1
     *          = 'U':  Orthogonal matrix U is computed;
     *          = 'N':  U is not computed.
     *
     *  JOBV    (input) CHARACTER*1
     *          = 'V':  Orthogonal matrix V is computed;
     *          = 'N':  V is not computed.
     *
     *  JOBQ    (input) CHARACTER*1
     *          = 'Q':  Orthogonal matrix Q is computed;
     *          = 'N':  Q is not computed.
     *
     *  M       (input) INTEGER
     *          The number of rows of the matrix A.  M >= 0.
     *
     *  P       (input) INTEGER
     *          The number of rows of the matrix B.  P >= 0.
     *
     *  N       (input) INTEGER
     *          The number of columns of the matrices A and B.  N >= 0.
     *
     *  A       (input/output) DOUBLE PRECISION array, dimension (LDA,N)
     *          On entry, the M-by-N matrix A.
     *          On exit, A contains the triangular (or trapezoidal) matrix
     *          described in the Purpose section.
     *
     *  LDA     (input) INTEGER
     *          The leading dimension of the array A. LDA >= max(1,M).
     *
     *  B       (input/output) DOUBLE PRECISION array, dimension (LDB,N)
     *          On entry, the P-by-N matrix B.
     *          On exit, B contains the triangular matrix described in
     *          the Purpose section.
     *
     *  LDB     (input) INTEGER
     *          The leading dimension of the array B. LDB >= max(1,P).
     *
     *  TOLA    (input) DOUBLE PRECISION
     *  TOLB    (input) DOUBLE PRECISION
     *          TOLA and TOLB are the thresholds to determine the effective
     *          numerical rank of matrix B and a subblock of A. Generally,
     *          they are set to
     *             TOLA = MAX(M,N)*norm(A)*MAZHEPS,
     *             TOLB = MAX(P,N)*norm(B)*MAZHEPS.
     *          The size of TOLA and TOLB may affect the size of backward
     *          errors of the decomposition.
     *
     *  K       (output) INTEGER
     *  L       (output) INTEGER
     *          On exit, K and L specify the dimension of the subblocks
     *          described in Purpose.
     *          K + L = effective numerical rank of (A',B')'.
     *
     *  U       (output) DOUBLE PRECISION array, dimension (LDU,M)
     *          If JOBU = 'U', U contains the orthogonal matrix U.
     *          If JOBU = 'N', U is not referenced.
     *
     *  LDU     (input) INTEGER
     *          The leading dimension of the array U. LDU >= max(1,M) if
     *          JOBU = 'U'; LDU >= 1 otherwise.
     *
     *  V       (output) DOUBLE PRECISION array, dimension (LDV,M)
     *          If JOBV = 'V', V contains the orthogonal matrix V.
     *          If JOBV = 'N', V is not referenced.
     *
     *  LDV     (input) INTEGER
     *          The leading dimension of the array V. LDV >= max(1,P) if
     *          JOBV = 'V'; LDV >= 1 otherwise.
     *
     *  Q       (output) DOUBLE PRECISION array, dimension (LDQ,N)
     *          If JOBQ = 'Q', Q contains the orthogonal matrix Q.
     *          If JOBQ = 'N', Q is not referenced.
     *
     *  LDQ     (input) INTEGER
     *          The leading dimension of the array Q. LDQ >= max(1,N) if
     *          JOBQ = 'Q'; LDQ >= 1 otherwise.
     *
     *  IWORK   (workspace) INTEGER array, dimension (N)
     *
     *  TAU     (workspace) DOUBLE PRECISION array, dimension (N)
     *
     *  WORK    (workspace) DOUBLE PRECISION array, dimension (max(3*N,M,P))

     *
     *  INFO    (output) INTEGER
     *          = 0:  successful exit
     *          < 0:  if INFO = -i, the i-th argument had an illegal value.
     *
     *
     *  Further Details
     *  ===============
     *
     *  The subroutine uses LAPACK subroutine DGEQPF for the QR factorization
     *  with column pivoting to detect the effective numerical rank of the
     *  a matrix. It may be replaced by a better rank determination strategy.
     *
     *  =====================================================================
     *
     *     .. Parameters ..

Constructor Summary
`DGGSVP()`

Method Summary
`static void` | `DGGSVP(java.lang.String jobu, java.lang.String jobv, java.lang.String jobq, int m, int p, int n, double[][] a, double[][] b, double tola, double tolb, intW k, intW l, double[][] u, double[][] v, double[][] q, int[] iwork, double[] tau, double[] work, intW info)`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### DGGSVP

    public DGGSVP()

Method Detail

### DGGSVP

    public static void DGGSVP(java.lang.String jobu,
                              java.lang.String jobv,
                              java.lang.String jobq,
                              int m,
                              int p,
                              int n,
                              double[][] a,
                              double[][] b,
                              double tola,
                              double tolb,
                              intW k,
                              intW l,
                              double[][] u,
                              double[][] v,
                              double[][] q,
                              int[] iwork,
                              double[] tau,
                              double[] work,
                              intW info)

Overview | Package | Class | Tree | Deprecated | Index | Help
PREV CLASS NEXT CLASS | FRAMES NO FRAMES
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD