LAPACK  3.4.2
LAPACK: Linear Algebra PACKage
 All Files Functions Groups
sbdsdc.f File Reference

Go to the source code of this file.

Functions/Subroutines

subroutine sbdsdc (UPLO, COMPQ, N, D, E, U, LDU, VT, LDVT, Q, IQ, WORK, IWORK, INFO)
 SBDSDC

Function/Subroutine Documentation

subroutine sbdsdc ( character  UPLO,
character  COMPQ,
integer  N,
real, dimension( * )  D,
real, dimension( * )  E,
real, dimension( ldu, * )  U,
integer  LDU,
real, dimension( ldvt, * )  VT,
integer  LDVT,
real, dimension( * )  Q,
integer, dimension( * )  IQ,
real, dimension( * )  WORK,
integer, dimension( * )  IWORK,
integer  INFO 
)

SBDSDC

Download SBDSDC + dependencies [TGZ] [ZIP] [TXT]
Purpose:
 SBDSDC 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 orthogonal matrices of left and right singular vectors,
 respectively. SBDSDC 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 SLASD3 for details.

 The code currently calls SLASDQ if singular values only are desired.
 However, it can be slightly modified to compute singular values
 using the divide and conquer method.
Parameters:
[in]UPLO
          UPLO is CHARACTER*1
          = 'U':  B is upper bidiagonal.
          = 'L':  B is lower bidiagonal.
[in]COMPQ
          COMPQ is CHARACTER*1
          Specifies whether singular vectors are to be computed
          as follows:
          = 'N':  Compute singular values only;
          = 'P':  Compute singular values and compute singular
                  vectors in compact form;
          = 'I':  Compute singular values and singular vectors.
[in]N
          N is INTEGER
          The order of the matrix B.  N >= 0.
[in,out]D
          D is REAL array, dimension (N)
          On entry, the n diagonal elements of the bidiagonal matrix B.
          On exit, if INFO=0, the singular values of B.
[in,out]E
          E is REAL 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.
[out]U
          U is REAL 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 values of COMPQ, U is not referenced.
[in]LDU
          LDU is INTEGER
          The leading dimension of the array U.  LDU >= 1.
          If singular vectors are desired, then LDU >= max( 1, N ).
[out]VT
          VT is REAL array, dimension (LDVT,N)
          If  COMPQ = 'I', then:
             On exit, if INFO = 0, VT**T contains the right singular
             vectors of the bidiagonal matrix.
          For other values of COMPQ, VT is not referenced.
[in]LDVT
          LDVT is INTEGER
          The leading dimension of the array VT.  LDVT >= 1.
          If singular vectors are desired, then LDVT >= max( 1, N ).
[out]Q
          Q is REAL 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,
             requiring O(N log N) space instead of 2*N**2.
             In particular, Q contains all the REAL 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 subproblems at the
             bottom of the computation tree (usually about 25).
          For other values of COMPQ, Q is not referenced.
[out]IQ
          IQ is 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,
             requiring O(N log N) space instead of 2*N**2.
             In particular, IQ contains all INTEGER data in
             LDIQ >= N*(3 + 3*INT(LOG_2(N/(SMLSIZ+1))))
             words of memory, where SMLSIZ is returned by ILAENV and
             is equal to the maximum size of the subproblems at the
             bottom of the computation tree (usually about 25).
          For other values of COMPQ, IQ is not referenced.
[out]WORK
          WORK is REAL 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).
[out]IWORK
          IWORK is INTEGER array, dimension (8*N)
[out]INFO
          INFO is INTEGER
          = 0:  successful exit.
          < 0:  if INFO = -i, the i-th argument had an illegal value.
          > 0:  The algorithm failed to compute a singular value.
                The update process of divide and conquer failed.
Author:
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.
Date:
November 2011
Contributors:
Ming Gu and Huan Ren, Computer Science Division, University of California at Berkeley, USA

Definition at line 205 of file sbdsdc.f.

Here is the call graph for this function:

Here is the caller graph for this function: