LAPACK 3.12.1
LAPACK: Linear Algebra PACKage
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subroutine ctgsna | ( | character | job, |
character | howmny, | ||
logical, dimension( * ) | select, | ||
integer | n, | ||
complex, dimension( lda, * ) | a, | ||
integer | lda, | ||
complex, dimension( ldb, * ) | b, | ||
integer | ldb, | ||
complex, dimension( ldvl, * ) | vl, | ||
integer | ldvl, | ||
complex, dimension( ldvr, * ) | vr, | ||
integer | ldvr, | ||
real, dimension( * ) | s, | ||
real, dimension( * ) | dif, | ||
integer | mm, | ||
integer | m, | ||
complex, dimension( * ) | work, | ||
integer | lwork, | ||
integer, dimension( * ) | iwork, | ||
integer | info ) |
CTGSNA
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!> !> CTGSNA estimates reciprocal condition numbers for specified !> eigenvalues and/or eigenvectors of a matrix pair (A, B). !> !> (A, B) must be in generalized Schur canonical form, that is, A and !> B are both upper triangular. !>
[in] | JOB | !> JOB is CHARACTER*1 !> Specifies whether condition numbers are required for !> eigenvalues (S) or eigenvectors (DIF): !> = 'E': for eigenvalues only (S); !> = 'V': for eigenvectors only (DIF); !> = 'B': for both eigenvalues and eigenvectors (S and DIF). !> |
[in] | HOWMNY | !> HOWMNY is CHARACTER*1 !> = 'A': compute condition numbers for all eigenpairs; !> = 'S': compute condition numbers for selected eigenpairs !> specified by the array SELECT. !> |
[in] | SELECT | !> SELECT is LOGICAL array, dimension (N) !> If HOWMNY = 'S', SELECT specifies the eigenpairs for which !> condition numbers are required. To select condition numbers !> for the corresponding j-th eigenvalue and/or eigenvector, !> SELECT(j) must be set to .TRUE.. !> If HOWMNY = 'A', SELECT is not referenced. !> |
[in] | N | !> N is INTEGER !> The order of the square matrix pair (A, B). N >= 0. !> |
[in] | A | !> A is COMPLEX array, dimension (LDA,N) !> The upper triangular matrix A in the pair (A,B). !> |
[in] | LDA | !> LDA is INTEGER !> The leading dimension of the array A. LDA >= max(1,N). !> |
[in] | B | !> B is COMPLEX array, dimension (LDB,N) !> The upper triangular matrix B in the pair (A, B). !> |
[in] | LDB | !> LDB is INTEGER !> The leading dimension of the array B. LDB >= max(1,N). !> |
[in] | VL | !> VL is COMPLEX array, dimension (LDVL,M) !> IF JOB = 'E' or 'B', VL must contain left eigenvectors of !> (A, B), corresponding to the eigenpairs specified by HOWMNY !> and SELECT. The eigenvectors must be stored in consecutive !> columns of VL, as returned by CTGEVC. !> If JOB = 'V', VL is not referenced. !> |
[in] | LDVL | !> LDVL is INTEGER !> The leading dimension of the array VL. LDVL >= 1; and !> If JOB = 'E' or 'B', LDVL >= N. !> |
[in] | VR | !> VR is COMPLEX array, dimension (LDVR,M) !> IF JOB = 'E' or 'B', VR must contain right eigenvectors of !> (A, B), corresponding to the eigenpairs specified by HOWMNY !> and SELECT. The eigenvectors must be stored in consecutive !> columns of VR, as returned by CTGEVC. !> If JOB = 'V', VR is not referenced. !> |
[in] | LDVR | !> LDVR is INTEGER !> The leading dimension of the array VR. LDVR >= 1; !> If JOB = 'E' or 'B', LDVR >= N. !> |
[out] | S | !> S is REAL array, dimension (MM) !> If JOB = 'E' or 'B', the reciprocal condition numbers of the !> selected eigenvalues, stored in consecutive elements of the !> array. !> If JOB = 'V', S is not referenced. !> |
[out] | DIF | !> DIF is REAL array, dimension (MM) !> If JOB = 'V' or 'B', the estimated reciprocal condition !> numbers of the selected eigenvectors, stored in consecutive !> elements of the array. !> If the eigenvalues cannot be reordered to compute DIF(j), !> DIF(j) is set to 0; this can only occur when the true value !> would be very small anyway. !> For each eigenvalue/vector specified by SELECT, DIF stores !> a Frobenius norm-based estimate of Difl. !> If JOB = 'E', DIF is not referenced. !> |
[in] | MM | !> MM is INTEGER !> The number of elements in the arrays S and DIF. MM >= M. !> |
[out] | M | !> M is INTEGER !> The number of elements of the arrays S and DIF used to store !> the specified condition numbers; for each selected eigenvalue !> one element is used. If HOWMNY = 'A', M is set to N. !> |
[out] | WORK | !> WORK is COMPLEX array, dimension (MAX(1,LWORK)) !> On exit, if INFO = 0, WORK(1) returns the optimal LWORK. !> |
[in] | LWORK | !> LWORK is INTEGER !> The dimension of the array WORK. LWORK >= max(1,N). !> If JOB = 'V' or 'B', LWORK >= max(1,2*N*N). !> |
[out] | IWORK | !> IWORK is INTEGER array, dimension (N+2) !> If JOB = 'E', IWORK is not referenced. !> |
[out] | INFO | !> INFO is INTEGER !> = 0: Successful exit !> < 0: If INFO = -i, the i-th argument had an illegal value !> |
!> !> The reciprocal of the condition number of the i-th generalized !> eigenvalue w = (a, b) is defined as !> !> S(I) = (|v**HAu|**2 + |v**HBu|**2)**(1/2) / (norm(u)*norm(v)) !> !> where u and v are the right and left eigenvectors of (A, B) !> corresponding to w; |z| denotes the absolute value of the complex !> number, and norm(u) denotes the 2-norm of the vector u. The pair !> (a, b) corresponds to an eigenvalue w = a/b (= v**HAu/v**HBu) of the !> matrix pair (A, B). If both a and b equal zero, then (A,B) is !> singular and S(I) = -1 is returned. !> !> An approximate error bound on the chordal distance between the i-th !> computed generalized eigenvalue w and the corresponding exact !> eigenvalue lambda is !> !> chord(w, lambda) <= EPS * norm(A, B) / S(I), !> !> where EPS is the machine precision. !> !> The reciprocal of the condition number of the right eigenvector u !> and left eigenvector v corresponding to the generalized eigenvalue w !> is defined as follows. Suppose !> !> (A, B) = ( a * ) ( b * ) 1 !> ( 0 A22 ),( 0 B22 ) n-1 !> 1 n-1 1 n-1 !> !> Then the reciprocal condition number DIF(I) is !> !> Difl[(a, b), (A22, B22)] = sigma-min( Zl ) !> !> where sigma-min(Zl) denotes the smallest singular value of !> !> Zl = [ kron(a, In-1) -kron(1, A22) ] !> [ kron(b, In-1) -kron(1, B22) ]. !> !> Here In-1 is the identity matrix of size n-1 and X**H is the conjugate !> transpose of X. kron(X, Y) is the Kronecker product between the !> matrices X and Y. !> !> We approximate the smallest singular value of Zl with an upper !> bound. This is done by CLATDF. !> !> An approximate error bound for a computed eigenvector VL(i) or !> VR(i) is given by !> !> EPS * norm(A, B) / DIF(i). !> !> See ref. [2-3] for more details and further 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. !>
Definition at line 306 of file ctgsna.f.