Program dgelsd_example ! DGELSD Example Program Text ! Copyright 2017, Numerical Algorithms Group Ltd. http://www.nag.com ! .. Use Statements .. Use lapack_interfaces, Only: dgelsd Use lapack_precision, Only: dp ! .. Implicit None Statement .. Implicit None ! .. Parameters .. Integer, Parameter :: nin = 5, nout = 6 ! .. Local Scalars .. Real (Kind=dp) :: rcond Integer :: i, info, lda, liwork, lwork, m, n, rank ! .. Local Arrays .. Real (Kind=dp), Allocatable :: a(:, :), b(:), s(:), work(:) Real (Kind=dp) :: lw(1) Integer, Allocatable :: iwork(:) Integer :: liw(1) ! .. Intrinsic Procedures .. Intrinsic :: nint ! .. Executable Statements .. Write (nout, *) 'DGELSD Example Program Results' Write (nout, *) ! Skip heading in data file Read (nin, *) Read (nin, *) m, n lda = m Allocate (a(lda,n), b(n), s(m)) ! Read A and B from data file Read (nin, *)(a(i,1:n), i=1, m) Read (nin, *) b(1:m) ! Choose RCOND to reflect the relative accuracy of the input ! data rcond = 0.01_dp ! Call dgelsd in workspace query mode. lwork = -1 Call dgelsd(m, n, 1, a, lda, b, n, s, rcond, rank, lw, lwork, liw, info) lwork = nint(lw(1)) liwork = liw(1) Allocate (work(lwork), iwork(liwork)) ! Now Solve the least squares problem min( norm2(b - Ax) ) for the ! x of minimum norm. Call dgelsd(m, n, 1, a, lda, b, n, s, rcond, rank, work, lwork, iwork, & info) If (info==0) Then ! Print solution Write (nout, *) 'Least squares solution' Write (nout, 100) b(1:n) ! Print the effective rank of A Write (nout, *) Write (nout, *) 'Tolerance used to estimate the rank of A' Write (nout, 110) rcond Write (nout, *) 'Estimated rank of A' Write (nout, 120) rank ! Print singular values of A Write (nout, *) Write (nout, *) 'Singular values of A' Write (nout, 100) s(1:m) Else Write (nout, *) 'The SVD algorithm failed to converge' End If 100 Format (1X, 7F11.4) 110 Format (3X, 1P, E11.2) 120 Format (1X, I6) End Program