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DGELSD Example Program in Fortran
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* =============================================================================
*
* DGELSD Example.
* ==============
*
* Program computes the minimum norm-solution to a real linear least squares
* problem using the singular value decomposition of A,
* where A is the coefficient matrix:
*
* 0.12 -8.19 7.69 -2.26 -4.71
* -6.91 2.22 -5.12 -9.08 9.96
* -3.33 -8.94 -6.72 -4.40 -9.98
* 3.97 3.33 -2.74 -7.92 -3.20
*
* and B is the right-hand side matrix:
*
* 7.30 0.47 -6.28
* 1.33 6.58 -3.42
* 2.68 -1.71 3.46
* -9.62 -0.79 0.41
*
* Description.
* ============
*
* The routine computes the minimum-norm solution to a real linear least
* squares problem: minimize ||b - A*x|| using the singular value
* decomposition (SVD) of A. A is an m-by-n matrix which may be rank-deficient.
*
* Several right hand side vectors b and solution vectors x can be handled
* in a single call; they are stored as the columns of the m-by-nrhs right
* hand side matrix B and the n-by-nrhs solution matrix X.
*
* The effective rank of A is determined by treating as zero those singular
* values which are less than rcond times the largest singular value.
*
* Example Program Results.
* ========================
*
* DGELSD Example Program Results
*
* Minimum norm solution
* -0.69 -0.24 0.06
* -0.80 -0.08 0.21
* 0.38 0.12 -0.65
* 0.29 -0.24 0.42
* 0.29 0.35 -0.30
*
* Effective rank = 4
*
* Singular values
* 18.66 15.99 10.01 8.51
* =============================================================================
*
* .. Parameters ..
INTEGER M, N, NRHS
PARAMETER ( M = 4, N = 5, NRHS = 3 )
INTEGER LDA, LDB
PARAMETER ( LDA = M, LDB = N )
INTEGER LWMAX
PARAMETER ( LWMAX = 1000 )
*
* .. Local Scalars ..
INTEGER INFO, LWORK, RANK
DOUBLE PRECISION RCOND
*
* .. Local Arrays ..
* IWORK dimension should be at least 3*MIN(M,N)*NLVL + 11*MIN(M,N),
* where NLVL = MAX( 0, INT( LOG_2( MIN(M,N)/(SMLSIZ+1) ) )+1 )
* and SMLSIZ = 25
INTEGER IWORK( 3*M*0+11*M )
DOUBLE PRECISION A( LDA, N ), B( LDB, NRHS ), S( M ),
$ WORK( LWMAX )
DATA A/
$ 0.12,-6.91,-3.33, 3.97,
$ -8.19, 2.22,-8.94, 3.33,
$ 7.69,-5.12,-6.72,-2.74,
$ -2.26,-9.08,-4.40,-7.92,
$ -4.71, 9.96,-9.98,-3.20
$ /
DATA B/
$ 7.30, 1.33, 2.68,-9.62, 0.00,
$ 0.47, 6.58,-1.71,-0.79, 0.00,
$ -6.28,-3.42, 3.46, 0.41, 0.00
$ /
*
* .. External Subroutines ..
EXTERNAL DGELSD
EXTERNAL PRINT_MATRIX
*
* .. Intrinsic Functions ..
INTRINSIC INT, MIN
*
* .. Executable Statements ..
WRITE(*,*)'DGELSD Example Program Results'
* Negative RCOND means using default (machine precision) value
RCOND = -1.0
*
* Query the optimal workspace.
*
LWORK = -1
CALL DGELSD( M, N, NRHS, A, LDA, B, LDB, S, RCOND, RANK, WORK,
$ LWORK, IWORK, INFO )
LWORK = MIN( LWMAX, INT( WORK( 1 ) ) )
*
* Solve the equations A*X = B.
*
CALL DGELSD( M, N, NRHS, A, LDA, B, LDB, S, RCOND, RANK, WORK,
$ LWORK, IWORK, INFO )
*
* Check for convergence.
*
IF( INFO.GT.0 ) THEN
WRITE(*,*)'The algorithm computing SVD failed to converge;'
WRITE(*,*)'the least squares solution could not be computed.'
STOP
END IF
*
* Print minimum norm solution.
*
CALL PRINT_MATRIX( 'Minimum norm solution', N, NRHS, B, LDB )
*
* Print effective rank.
*
WRITE(*,'(/A,I6)')' Effective rank = ', RANK
*
* Print singular values.
*
CALL PRINT_MATRIX( 'Singular values', 1, M, S, 1 )
STOP
END
*
* End of DGELSD Example.
*
* =============================================================================
*
* Auxiliary routine: printing a matrix.
*
SUBROUTINE PRINT_MATRIX( DESC, M, N, A, LDA )
CHARACTER*(*) DESC
INTEGER M, N, LDA
DOUBLE PRECISION A( LDA, * )
*
INTEGER I, J
*
WRITE(*,*)
WRITE(*,*) DESC
DO I = 1, M
WRITE(*,9998) ( A( I, J ), J = 1, N )
END DO
*
9998 FORMAT( 11(:,1X,F6.2) )
RETURN
END
Parent topic: DGELSD Example