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dlasd0.f(3) [centos man page]

dlasd0.f(3)							      LAPACK							       dlasd0.f(3)

NAME

       dlasd0.f -

SYNOPSIS

   Functions/Subroutines
       subroutine dlasd0 (N, SQRE, D, E, U, LDU, VT, LDVT, SMLSIZ, IWORK, WORK, INFO)
	   DLASD0 computes the singular values of a real upper bidiagonal n-by-m matrix B with diagonal d and off-diagonal e. Used by sbdsdc.

Function/Subroutine Documentation
   subroutine dlasd0 (integerN, integerSQRE, double precision, dimension( * )D, double precision, dimension( * )E, double precision, dimension(
       ldu, * )U, integerLDU, double precision, dimension( ldvt, * )VT, integerLDVT, integerSMLSIZ, integer, dimension( * )IWORK, double
       precision, dimension( * )WORK, integerINFO)
       DLASD0 computes the singular values of a real upper bidiagonal n-by-m matrix B with diagonal d and off-diagonal e. Used by sbdsdc.

       Purpose:

	    Using a divide and conquer approach, DLASD0 computes the singular
	    value decomposition (SVD) of a real upper bidiagonal N-by-M
	    matrix B with diagonal D and offdiagonal E, where M = N + SQRE.
	    The algorithm computes orthogonal matrices U and VT such that
	    B = U * S * VT. The singular values S are overwritten on D.

	    A related subroutine, DLASDA, computes only the singular values,
	    and optionally, the singular vectors in compact form.

       Parameters:
	   N

		     N is INTEGER
		    On entry, the row dimension of the upper bidiagonal matrix.
		    This is also the dimension of the main diagonal array D.

	   SQRE

		     SQRE is INTEGER
		    Specifies the column dimension of the bidiagonal matrix.
		    = 0: The bidiagonal matrix has column dimension M = N;
		    = 1: The bidiagonal matrix has column dimension M = N+1;

	   D

		     D is DOUBLE PRECISION array, dimension (N)
		    On entry D contains the main diagonal of the bidiagonal
		    matrix.
		    On exit D, if INFO = 0, contains its singular values.

	   E

		     E is DOUBLE PRECISION array, dimension (M-1)
		    Contains the subdiagonal entries of the bidiagonal matrix.
		    On exit, E has been destroyed.

	   U

		     U is DOUBLE PRECISION array, dimension at least (LDQ, N)
		    On exit, U contains the left singular vectors.

	   LDU

		     LDU is INTEGER
		    On entry, leading dimension of U.

	   VT

		     VT is DOUBLE PRECISION array, dimension at least (LDVT, M)
		    On exit, VT**T contains the right singular vectors.

	   LDVT

		     LDVT is INTEGER
		    On entry, leading dimension of VT.

	   SMLSIZ

		     SMLSIZ is INTEGER
		    On entry, maximum size of the subproblems at the
		    bottom of the computation tree.

	   IWORK

		     IWORK is INTEGER work array.
		    Dimension must be at least (8 * N)

	   WORK

		     WORK is DOUBLE PRECISION work array.
		    Dimension must be at least (3 * M**2 + 2 * M)

	   INFO

		     INFO is INTEGER
		     = 0:  successful exit.
		     < 0:  if INFO = -i, the i-th argument had an illegal value.
		     > 0:  if INFO = 1, a singular value did not converge

       Author:
	   Univ. of Tennessee

	   Univ. of California Berkeley

	   Univ. of Colorado Denver

	   NAG Ltd.

       Date:
	   September 2012

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

       Definition at line 152 of file dlasd0.f.

Author
       Generated automatically by Doxygen for LAPACK from the source code.

Version 3.4.2							  Tue Sep 25 2012						       dlasd0.f(3)

Check Out this Related Man Page

SLASD0(l)								 )								 SLASD0(l)

NAME

       SLASD0  -  a divide and conquer approach, SLASD0 computes the singular value decomposition (SVD) of a real upper bidiagonal N-by-M matrix B
       with diagonal D and offdiagonal E, where M = N + SQRE

SYNOPSIS

       SUBROUTINE SLASD0( N, SQRE, D, E, U, LDU, VT, LDVT, SMLSIZ, IWORK, WORK, INFO )

	   INTEGER	  INFO, LDU, LDVT, N, SMLSIZ, SQRE

	   INTEGER	  IWORK( * )

	   REAL 	  D( * ), E( * ), U( LDU, * ), VT( LDVT, * ), WORK( * )

PURPOSE

       Using a divide and conquer approach, SLASD0 computes the singular value decomposition (SVD) of a real upper bidiagonal N-by-M matrix B with
       diagonal  D and offdiagonal E, where M = N + SQRE. The algorithm computes orthogonal matrices U and VT such that B = U * S * VT. The singu-
       lar values S are overwritten on D.

       A related subroutine, SLASDA, computes only the singular values, and optionally, the singular vectors in compact form.

ARGUMENTS

       N      (input) INTEGER
	      On entry, the row dimension of the upper bidiagonal matrix.  This is also the dimension of the main diagonal array D.

       SQRE   (input) INTEGER
	      Specifies the column dimension of the bidiagonal matrix.	= 0: The bidiagonal matrix has column dimension M = N;
	      = 1: The bidiagonal matrix has column dimension M = N+1;

       D      (input/output) REAL array, dimension (N)
	      On entry D contains the main diagonal of the bidiagonal matrix.  On exit D, if INFO = 0, contains its singular values.

       E      (input) REAL array, dimension (M-1)
	      Contains the subdiagonal entries of the bidiagonal matrix.  On exit, E has been destroyed.

       U      (output) REAL array, dimension at least (LDQ, N)
	      On exit, U contains the left singular vectors.

       LDU    (input) INTEGER
	      On entry, leading dimension of U.

       VT     (output) REAL array, dimension at least (LDVT, M)
	      On exit, VT' contains the right singular vectors.

       LDVT   (input) INTEGER
	      On entry, leading dimension of VT.

	      SMLSIZ (input) INTEGER On entry, maximum size of the subproblems at the bottom of the computation tree.

       IWORK  INTEGER work array.
	      Dimension must be at least (8 * N)

       WORK   REAL work array.
	      Dimension must be at least (3 * M**2 + 2 * M)

       INFO   (output) INTEGER
	      = 0:  successful exit.
	      < 0:  if INFO = -i, the i-th argument had an illegal value.
	      > 0:  if INFO = 1, an singular value did not converge

FURTHER DETAILS

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

LAPACK version 3.0						   15 June 2000 							 SLASD0(l)
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