概要
本サンプルはFortran言語によりLAPACKルーチンZGELSDを利用するサンプルプログラムです。
以下の線形最小二乗問題を解きます。
最小ノルム解を


及び


入力データ
(本ルーチンの詳細はZGELSD のマニュアルページを参照)1 2 3 4 5 6 7 8 9 10 11 12 13
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ZGELSD Example Program Data 4 5 :Values of M and N ( 0.47,-0.34) (-0.32,-0.23) ( 0.35,-0.60) ( 0.89, 0.71) (-0.19, 0.06) (-0.40, 0.54) (-0.05, 0.20) (-0.52,-0.34) (-0.45,-0.45) ( 0.11,-0.85) ( 0.60, 0.01) (-0.26,-0.44) ( 0.87,-0.11) (-0.02,-0.57) ( 1.44, 0.80) ( 0.80,-1.02) (-0.43, 0.17) (-0.34,-0.09) ( 1.14,-0.78) ( 0.07, 1.14) :End of A ( 2.15,-0.20) (-2.24, 1.82) ( 4.45,-4.28) ( 5.70,-6.25) :End of vector b
出力結果
(本ルーチンの詳細はZGELSD のマニュアルページを参照)1 2 3 4 5 6 7 8 9 10 11 12 13 14
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Warning: Floating underflow occurred ZGELSD Example Program Results Least squares solution ( 3.9747,-1.8377) (-0.9186, 0.8253) (-0.3105, 0.1477) ( 1.0050, 0.8626) (-0.2256,-1.9425) Tolerance used to estimate the rank of A 1.00E-02 Estimated rank of A 3 Singular values of A 2.9979 1.9983 1.0044 0.0064
ソースコード
(本ルーチンの詳細はZGELSD のマニュアルページを参照)※本サンプルソースコードのご利用手順は「サンプルのコンパイル及び実行方法」をご参照下さい。
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Program zgelsd_example ! ZGELSD Example Program Text ! Copyright 2017, Numerical Algorithms Group Ltd. http://www.nag.com ! .. Use Statements .. Use lapack_interfaces, Only: zgelsd 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, lrwork, lwork, m, n, rank ! .. Local Arrays .. Complex (Kind=dp), Allocatable :: a(:, :), b(:), work(:) Complex (Kind=dp) :: lw(1) Real (Kind=dp) :: lrw(1) Real (Kind=dp), Allocatable :: rwork(:), s(:) Integer, Allocatable :: iwork(:) Integer :: liw(1) ! .. Intrinsic Procedures .. Intrinsic :: nint, real ! .. Executable Statements .. Write (nout, *) 'ZGELSD 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 = 0.01E0_dp ! Call zgelsd in workspace query mode. lwork = -1 Call zgelsd(m, n, 1, a, lda, b, n, s, rcond, rank, lw, lwork, lrw, liw, & info) lwork = nint(real(lw(1))) lrwork = nint(lrw(1)) liwork = liw(1) Allocate (work(lwork), rwork(lrwork), iwork(liwork)) ! Solve the least squares problem min( norm2(b - Ax) ) for the ! x of minimum norm. Call zgelsd(m, n, 1, a, lda, b, n, s, rcond, rank, work, lwork, rwork, & 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, 130) s(1:m) Else If (info>0) Then Write (nout, *) 'The SVD algorithm failed to converge' End If 100 Format (4(' (',F7.4,',',F7.4,')',:)) 110 Format (3X, 1P, E11.2) 120 Format (1X, I6) 130 Format (1X, 7F11.4) End Program