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dbdsdc examples
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Man Page Details
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NAME
       DBDSDC - the singular value decomposition (SVD) of a real N-by-N (upper
       or lower) bidiagonal matrix B

SYNOPSIS
       SUBROUTINE DBDSDC( UPLO, COMPQ, N, D, E, U, LDU, VT, LDVT, Q, IQ, WORK,
                          IWORK, INFO )

           CHARACTER      COMPQ, UPLO

           INTEGER        INFO, LDU, LDVT, N

           INTEGER        IQ( * ), IWORK( * )

           DOUBLE         PRECISION  D(  * ), E( * ), Q( * ), U( LDU, * ), VT(
                          LDVT, * ), WORK( * )

PURPOSE
       DBDSDC computes the singular value decomposition (SVD) of a real N-by-N
       (upper  or  lower) bidiagonal matrix B:  B = U * S * VT, using a divide
       and conquer method, where S is  a  diagonal  matrix  with  non-negative
       diagonal elements (the singular values of B), and U and VT are orthogo-
       nal matrices of left and right singular vectors,  respectively.  DBDSDC
       can  be  used  to compute all singular values, and optionally, singular
       vectors or singular vectors in compact form.

       This code makes very mild assumptions about floating point  arithmetic.
       It  will  work  on  machines  with a guard digit in add/subtract, or on
       those binary machines without guard digits which subtract like the Cray
       X-MP,  Cray  Y-MP,  Cray C-90, or Cray-2.  It could conceivably fail on
       hexadecimal or decimal machines without guard digits, but  we  know  of
       none.  See DLASD3 for details.

       The  code  currently  calls DLASDQ if singular values only are desired.
       However, it can be slightly modified to compute singular  values  using
       the divide and conquer method.


ARGUMENTS
       UPLO    (input) CHARACTER*1
               = 'U':  B is upper bidiagonal.
               = 'L':  B is lower bidiagonal.

       COMPQ   (input) CHARACTER*1
               Specifies  whether  singular vectors are to be computed as fol-
               lows:
               = 'N':  Compute singular values only;
               = 'P':  Compute singular values and compute singular vectors in
               compact form; = 'I':  Compute singular values and singular vec-
               tors.

       N       (input) INTEGER
               The order of the matrix B.  N >= 0.

       D       (input/output) DOUBLE PRECISION array, dimension (N)
               On entry, the n diagonal elements of the bidiagonal  matrix  B.
               On exit, if INFO=0, the singular values of B.

       E       (input/output) DOUBLE PRECISION array, dimension (N-1)
               On entry, the elements of E contain the offdiagonal elements of
               the bidiagonal matrix whose SVD is desired.   On  exit,  E  has
               been destroyed.

       U       (output) DOUBLE PRECISION array, dimension (LDU,N)
               If   COMPQ  =  'I',  then: On exit, if INFO = 0, U contains the
               left singular vectors of the bidiagonal matrix.  For other val-
               ues of COMPQ, U is not referenced.

       LDU     (input) INTEGER
               The  leading  dimension of the array U.  LDU >= 1.  If singular
               vectors are desired, then LDU >= max( 1, N ).

       VT      (output) DOUBLE PRECISION array, dimension (LDVT,N)
               If  COMPQ = 'I', then: On exit, if INFO = 0, VT'  contains  the
               right  singular  vectors  of  the bidiagonal matrix.  For other
               values of COMPQ, VT is not referenced.

       LDVT    (input) INTEGER
               The leading dimension of the array VT.  LDVT >= 1.  If singular
               vectors are desired, then LDVT >= max( 1, N ).

       Q       (output) DOUBLE PRECISION array, dimension (LDQ)
               If   COMPQ  = 'P', then: On exit, if INFO = 0, Q and IQ contain
               the left and right singular vectors in a compact form,  requir-
               ing  O(N log N) space instead of 2*N**2.  In particular, Q con-
               tains all the DOUBLE PRECISION data in LDQ >= N*(11 +  2*SMLSIZ
               +  8*INT(LOG_2(N/(SMLSIZ+1)))) words of memory, where SMLSIZ is
               returned by ILAENV and is equal to the maximum size of the sub-
               problems  at  the bottom of the computation tree (usually about
               25).  For other values of COMPQ, Q is not referenced.

       IQ      (output) INTEGER array, dimension (LDIQ)
               If  COMPQ = 'P', then: On exit, if INFO = 0, Q and  IQ  contain
               the  left and right singular vectors in a compact form, requir-
               ing O(N log N) space instead of 2*N**2.  In particular, IQ con-
               tains  all  INTEGER  data in LDIQ >= N*(3 + 3*INT(LOG_2(N/(SML-
               SIZ+1)))) words of memory, where SMLSIZ is returned  by  ILAENV
               and is equal to the maximum size of the subproblems at the bot-
               tom of the computation tree (usually about 25).  For other val-
               ues of COMPQ, IQ is not referenced.

       WORK    (workspace) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
               If  COMPQ  =  'N'  then  LWORK >= (4 * N).  If COMPQ = 'P' then
               LWORK >= (6 * N).  If COMPQ = 'I' then LWORK >= (3 * N**2 + 4 *
               N).

       IWORK   (workspace) INTEGER array, dimension (8*N)

       INFO    (output) INTEGER
               = 0:  successful exit.
               < 0:  if INFO = -i, the i-th argument had an illegal value.
               >  0:   The algorithm failed to compute an singular value.  The
               update process of divide and conquer failed.

 Further Details
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  Based on contributions by
     Ming Gu and Huan Ren, Computer Science Division, University of
     California at Berkeley, USA

