bdsdc - Man Page

bdsdc: bidiagonal SVD, divide and conquer

Synopsis

Functions

subroutine dbdsdc (uplo, compq, n, d, e, u, ldu, vt, ldvt, q, iq, work, iwork, info)
DBDSDC
subroutine sbdsdc (uplo, compq, n, d, e, u, ldu, vt, ldvt, q, iq, work, iwork, info)
SBDSDC

Detailed Description

Function Documentation

subroutine dbdsdc (character uplo, character compq, integer n, double precision, dimension( * ) d, double precision, dimension( * ) e, double precision, dimension( ldu, * ) u, integer ldu, double precision, dimension( ldvt, * ) vt, integer ldvt, double precision, dimension( * ) q, integer, dimension( * ) iq, double precision, dimension( * ) work, integer, dimension( * ) iwork, integer info)

DBDSDC  

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 orthogonal 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.

 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.
Parameters

UPLO

          UPLO is CHARACTER*1
          = 'U':  B is upper bidiagonal.
          = 'L':  B is lower bidiagonal.

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.

N

          N is INTEGER
          The order of the matrix B.  N >= 0.

D

          D is 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

          E is 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

          U is 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 values of COMPQ, U is not referenced.

LDU

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

VT

          VT is DOUBLE PRECISION 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.

LDVT

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

Q

          Q is 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,
             requiring O(N log N) space instead of 2*N**2.
             In particular, Q contains 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 subproblems at the
             bottom of the computation tree (usually about 25).
          For other values of COMPQ, Q is not referenced.

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.

WORK

          WORK is 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

          IWORK is INTEGER array, dimension (8*N)

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.

Contributors:

Ming Gu and Huan Ren, Computer Science Division, University of California at Berkeley, USA

Definition at line 196 of file dbdsdc.f.

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  

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.

 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

UPLO

          UPLO is CHARACTER*1
          = 'U':  B is upper bidiagonal.
          = 'L':  B is lower bidiagonal.

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.

N

          N is INTEGER
          The order of the matrix B.  N >= 0.

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.

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.

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.

LDU

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

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.

LDVT

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

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.

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.

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).

IWORK

          IWORK is INTEGER array, dimension (8*N)

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.

Contributors:

Ming Gu and Huan Ren, Computer Science Division, University of California at Berkeley, USA

Definition at line 196 of file sbdsdc.f.

Author

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Info

Tue Nov 28 2023 12:08:43 Version 3.12.0 LAPACK