dtgsen.c

来自「InsightToolkit-1.4.0(有大量的优化算法程序)」· C语言 代码 · 共 752 行 · 第 1/3 页

C
752
字号
/*  decomposition of a matrix pair (C, D) = Q*(A, B)*Z', then the         */
/*  reordered generalized real Schur form of (C, D) is given by           */
/*                                                                        */
/*           (C, D) = (Q*U)*(U'*(A, B)*W)*(Z*W)',                         */
/*                                                                        */
/*  and the first n1 columns of Q*U and Z*W span the corresponding        */
/*  deflating subspaces of (C, D) (Q and Z store Q*U and Z*W, resp.).     */
/*                                                                        */
/*  Note that if the selected eigenvalue is sufficiently ill-conditioned, */
/*  then its value may differ significantly from its value before         */
/*  reordering.                                                           */
/*                                                                        */
/*  The reciprocal condition numbers of the left and right eigenspaces    */
/*  spanned by the first n1 columns of U and W (or Q*U and Z*W) may       */
/*  be returned in DIF(1:2), corresponding to Difu and Difl, resp.        */
/*                                                                        */
/*  The Difu and Difl are defined as:                                     */
/*                                                                        */
/*       Difu[(A11, B11), (A22, B22)] = sigma-min( Zu )                   */
/*  and                                                                   */
/*       Difl[(A11, B11), (A22, B22)] = Difu[(A22, B22), (A11, B11)],     */
/*                                                                        */
/*  where sigma-min(Zu) is the smallest singular value of the             */
/*  (2*n1*n2)-by-(2*n1*n2) matrix                                         */
/*                                                                        */
/*       Zu = [ kron(In2, A11)  -kron(A22', In1) ]                        */
/*            [ kron(In2, B11)  -kron(B22', In1) ].                       */
/*                                                                        */
/*  Here, Inx is the identity matrix of size nx and A22' is the           */
/*  transpose of A22. kron(X, Y) is the Kronecker product between         */
/*  the matrices X and Y.                                                 */
/*                                                                        */
/*  When DIF(2) is small, small changes in (A, B) can cause large changes */
/*  in the deflating subspace. An approximate (asymptotic) bound on the   */
/*  maximum angular error in the computed deflating subspaces is          */
/*                                                                        */
/*       EPS * norm((A, B)) / DIF(2),                                     */
/*                                                                        */
/*  where EPS is the machine precision.                                   */
/*                                                                        */
/*  The reciprocal norm of the projectors on the left and right           */
/*  eigenspaces associated with (A11, B11) may be returned in PL and PR.  */
/*  They are computed as follows. First we compute L and R so that        */
/*  P*(A, B)*Q is block diagonal, where                                   */
/*                                                                        */
/*       P = ( I -L ) n1           Q = ( I R ) n1                         */
/*           ( 0  I ) n2    and        ( 0 I ) n2                         */
/*             n1 n2                    n1 n2                             */
/*                                                                        */
/*  and (L, R) is the solution to the generalized Sylvester equation      */
/*                                                                        */
/*       A11*R - L*A22 = -A12                                             */
/*       B11*R - L*B22 = -B12                                             */
/*                                                                        */
/*  Then PL = (F-norm(L)**2+1)**(-1/2) and PR = (F-norm(R)**2+1)**(-1/2). */
/*  An approximate (asymptotic) bound on the average absolute error of    */
/*  the selected eigenvalues is                                           */
/*                                                                        */
/*       EPS * norm((A, B)) / PL.                                         */
/*                                                                        */
/*  There are also global error bounds which valid for perturbations up   */
/*  to a certain restriction:  A lower bound (x) on the smallest          */
/*  F-norm(E,F) for which an eigenvalue of (A11, B11) may move and        */
/*  coalesce with an eigenvalue of (A22, B22) under perturbation (E,F),   */
/*  (i.e. (A + E, B + F), is                                              */
/*                                                                        */
/*   x = min(Difu,Difl)/((1/(PL*PL)+1/(PR*PR))**(1/2)+2*max(1/PL,1/PR)).  */
/*                                                                        */
/*  An approximate bound on x can be computed from DIF(1:2), PL and PR.   */
/*                                                                        */
/*  If y = ( F-norm(E,F) / x) <= 1, the angles between the perturbed      */
/*  (L', R') and unperturbed (L, R) left and right deflating subspaces    */
/*  associated with the selected cluster in the (1,1)-blocks can be       */
/*  bounded as                                                            */
/*                                                                        */
/*   max-angle(L, L') <= arctan( y * PL / (1 - y * (1 - PL * PL)**(1/2))  */
/*   max-angle(R, R') <= arctan( y * PR / (1 - y * (1 - PR * PR)**(1/2))  */
/*                                                                        */
/*  See LAPACK User's Guide section 4.11 or the following references      */
/*  for more information.                                                 */
/*                                                                        */
/*  Note that if the default method for computing the Frobenius-norm-     */
/*  based estimate DIF is not wanted (see DLATDF), then the parameter     */
/*  IDIFJB (see below) should be changed from 3 to 4 (routine DLATDF      */
/*  (IJOB = 2 will be used)). See DTGSYL for more details.                */
/*                                                                        */
/*  Based on contributions by                                             */
/*     Bo Kagstrom and Peter Poromaa, Department of Computing Science,    */
/*     Umea University, S-901 87 Umea, Sweden.                            */
/*                                                                        */
/*  References                                                            */
/*  ==========                                                            */
/*                                                                        */
/*  [1] B. Kagstrom; A Direct Method for Reordering Eigenvalues in the    */
/*      Generalized Real Schur Form of a Regular Matrix Pair (A, B), in   */
/*      M.S. Moonen et al (eds), Linear Algebra for Large Scale and       */
/*      Real-Time Applications, Kluwer Academic Publ. 1993, pp 195-218.   */
/*                                                                        */
/*  [2] B. Kagstrom and P. Poromaa; Computing Eigenspaces with Specified  */
/*      Eigenvalues of a Regular Matrix Pair (A, B) and Condition         */
/*      Estimation: Theory, Algorithms and Software,                      */
/*      Report UMINF - 94.04, Department of Computing Science, Umea       */
/*      University, S-901 87 Umea, Sweden, 1994. Also as LAPACK Working   */
/*      Note 87. To appear in Numerical Algorithms, 1996.                 */
/*                                                                        */
/*  [3] B. Kagstrom and P. Poromaa, LAPACK-Style Algorithms and Software  */
/*      for Solving the Generalized Sylvester Equation and Estimating the */
/*      Separation between Regular Matrix Pairs, Report UMINF - 93.23,    */
/*      Department of Computing Science, Umea University, S-901 87 Umea,  */
/*      Sweden, December 1993, Revised April 1994, Also as LAPACK Working */
/*      Note 75. To appear in ACM Trans. on Math. Software, Vol 22, No 1, */
/*      1996.                                                             */
/*                                                                        */
/*  ===================================================================== */

    /* Parameter adjustments */
    --select;
    a_dim1 = *lda;
    a_offset = 1 + a_dim1 * 1;
    a -= a_offset;
    b_dim1 = *ldb;
    b_offset = 1 + b_dim1 * 1;
    b -= b_offset;
    --alphar;
    --alphai;
    --beta;
    q_dim1 = *ldq;
    q_offset = 1 + q_dim1 * 1;
    q -= q_offset;
    z_dim1 = *ldz;
    z_offset = 1 + z_dim1 * 1;
    z -= z_offset;
    --dif;
    --work;
    --iwork;

/*     Decode and test the input parameters */

    *info = 0;
    lquery = *lwork == -1 || *liwork == -1;

    if (*ijob < 0 || *ijob > 5) {
        *info = -1;
    } else if (*n < 0) {
        *info = -5;
    } else if (*lda < max(1,*n)) {
        *info = -7;
    } else if (*ldb < max(1,*n)) {
        *info = -9;
    } else if (*ldq < 1 || (*wantq && *ldq < *n)) {
        *info = -14;
    } else if (*ldz < 1 || (*wantz && *ldz < *n)) {
        *info = -16;
    }

    if (*info != 0) {
        i__1 = -(*info);
        xerbla_("DTGSEN", &i__1);
        return;
    }

/*     Get machine constants */

    eps = dlamch_("P");
    smlnum = dlamch_("S") / eps;
    ierr = 0;

    wantp = *ijob == 1 || *ijob >= 4;
    wantd1 = *ijob == 2 || *ijob == 4;
    wantd2 = *ijob == 3 || *ijob == 5;
    wantd = wantd1 || wantd2;

/*     Set M to the dimension of the specified pair of deflating */
/*     subspaces. */

    *m = 0;
    pair = FALSE_;
    for (k = 1; k <= *n; ++k) {
        if (pair) {
            pair = FALSE_;
        } else {
            if (k < *n) {
                if (a[k + 1 + k * a_dim1] == 0.) {
                    if (select[k]) {
                        ++(*m);
                    }
                } else {
                    pair = TRUE_;
                    if (select[k] || select[k + 1]) {
                        *m += 2;
                    }
                }
            } else {
                if (select[*n]) {
                    ++(*m);
                }
            }
        }
    }

    if (*ijob == 1 || *ijob == 2 || *ijob == 4) {
        lwmin  = max(max(1, (*n << 2) + 16), (*m << 1) * (*n - *m));
        liwmin = max(1, *n + 6);
    } else if (*ijob == 3 || *ijob == 5) {
        lwmin  = max(max(1, (*n << 2) + 16), (*m << 2) * (*n - *m));
        liwmin = max(max(1, (*m << 1) * (*n - *m)), *n + 6);
    } else {
        lwmin = max(1,(*n << 2) + 16);
        liwmin = 1;
    }

    work[1] = (doublereal) lwmin;
    iwork[1] = liwmin;

    if (*lwork < lwmin && ! lquery) {
        *info = -22;
    } else if (*liwork < liwmin && ! lquery) {
        *info = -24;
    }

    if (*info != 0) {
        i__1 = -(*info);
        xerbla_("DTGSEN", &i__1);
        return;
    } else if (lquery) {
        return;
    }

/*     Quick return if possible. */

    if (*m == *n || *m == 0) {
        if (wantp) {
            *pl = 1.;
            *pr = 1.;
        }
        if (wantd) {
            dscale = 0.;
            dsum = 1.;
            for (i = 1; i <= *n; ++i) {
                dlassq_(n, &a[i * a_dim1 + 1], &c__1, &dscale, &dsum);
                dlassq_(n, &b[i * b_dim1 + 1], &c__1, &dscale, &dsum);
            }
            dif[1] = dscale * sqrt(dsum);
            dif[2] = dif[1];
        }
        goto L60;
    }

/*     Collect the selected blocks at the top-left corner of (A, B). */

    ks = 0;

⌨️ 快捷键说明

复制代码Ctrl + C
搜索代码Ctrl + F
全屏模式F11
增大字号Ctrl + =
减小字号Ctrl + -
显示快捷键?