.TH "SRC/strsen.f" 3 "Version 3.12.0" "LAPACK" \" -*- nroff -*- .ad l .nh .SH NAME SRC/strsen.f .SH SYNOPSIS .br .PP .SS "Functions/Subroutines" .in +1c .ti -1c .RI "subroutine \fBstrsen\fP (job, compq, select, n, t, ldt, q, ldq, wr, wi, m, s, sep, work, lwork, iwork, liwork, info)" .br .RI "\fBSTRSEN\fP " .in -1c .SH "Function/Subroutine Documentation" .PP .SS "subroutine strsen (character job, character compq, logical, dimension( * ) select, integer n, real, dimension( ldt, * ) t, integer ldt, real, dimension( ldq, * ) q, integer ldq, real, dimension( * ) wr, real, dimension( * ) wi, integer m, real s, real sep, real, dimension( * ) work, integer lwork, integer, dimension( * ) iwork, integer liwork, integer info)" .PP \fBSTRSEN\fP .PP \fBPurpose:\fP .RS 4 .PP .nf !> !> STRSEN reorders the real Schur factorization of a real matrix !> A = Q*T*Q**T, so that a selected cluster of eigenvalues appears in !> the leading diagonal blocks of the upper quasi-triangular matrix T, !> and the leading columns of Q form an orthonormal basis of the !> corresponding right invariant subspace\&. !> !> Optionally the routine computes the reciprocal condition numbers of !> the cluster of eigenvalues and/or the invariant subspace\&. !> !> T must be in Schur canonical form (as returned by SHSEQR), that is, !> block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; each !> 2-by-2 diagonal block has its diagonal elements equal and its !> off-diagonal elements of opposite sign\&. !> .fi .PP .RE .PP \fBParameters\fP .RS 4 \fIJOB\fP .PP .nf !> JOB is CHARACTER*1 !> Specifies whether condition numbers are required for the !> cluster of eigenvalues (S) or the invariant subspace (SEP): !> = 'N': none; !> = 'E': for eigenvalues only (S); !> = 'V': for invariant subspace only (SEP); !> = 'B': for both eigenvalues and invariant subspace (S and !> SEP)\&. !> .fi .PP .br \fICOMPQ\fP .PP .nf !> COMPQ is CHARACTER*1 !> = 'V': update the matrix Q of Schur vectors; !> = 'N': do not update Q\&. !> .fi .PP .br \fISELECT\fP .PP .nf !> SELECT is LOGICAL array, dimension (N) !> SELECT specifies the eigenvalues in the selected cluster\&. To !> select a real eigenvalue w(j), SELECT(j) must be set to !> \&.TRUE\&.\&. To select a complex conjugate pair of eigenvalues !> w(j) and w(j+1), corresponding to a 2-by-2 diagonal block, !> either SELECT(j) or SELECT(j+1) or both must be set to !> \&.TRUE\&.; a complex conjugate pair of eigenvalues must be !> either both included in the cluster or both excluded\&. !> .fi .PP .br \fIN\fP .PP .nf !> N is INTEGER !> The order of the matrix T\&. N >= 0\&. !> .fi .PP .br \fIT\fP .PP .nf !> T is REAL array, dimension (LDT,N) !> On entry, the upper quasi-triangular matrix T, in Schur !> canonical form\&. !> On exit, T is overwritten by the reordered matrix T, again in !> Schur canonical form, with the selected eigenvalues in the !> leading diagonal blocks\&. !> .fi .PP .br \fILDT\fP .PP .nf !> LDT is INTEGER !> The leading dimension of the array T\&. LDT >= max(1,N)\&. !> .fi .PP .br \fIQ\fP .PP .nf !> Q is REAL array, dimension (LDQ,N) !> On entry, if COMPQ = 'V', the matrix Q of Schur vectors\&. !> On exit, if COMPQ = 'V', Q has been postmultiplied by the !> orthogonal transformation matrix which reorders T; the !> leading M columns of Q form an orthonormal basis for the !> specified invariant subspace\&. !> If COMPQ = 'N', Q is not referenced\&. !> .fi .PP .br \fILDQ\fP .PP .nf !> LDQ is INTEGER !> The leading dimension of the array Q\&. !> LDQ >= 1; and if COMPQ = 'V', LDQ >= N\&. !> .fi .PP .br \fIWR\fP .PP .nf !> WR is REAL array, dimension (N) !> .fi .PP .br \fIWI\fP .PP .nf !> WI is REAL array, dimension (N) !> !> The real and imaginary parts, respectively, of the reordered !> eigenvalues of T\&. The eigenvalues are stored in the same !> order as on the diagonal of T, with WR(i) = T(i,i) and, if !> T(i:i+1,i:i+1) is a 2-by-2 diagonal block, WI(i) > 0 and !> WI(i+1) = -WI(i)\&. Note that if a complex eigenvalue is !> sufficiently ill-conditioned, then its value may differ !> significantly from its value before reordering\&. !> .fi .PP .br \fIM\fP .PP .nf !> M is INTEGER !> The dimension of the specified invariant subspace\&. !> 0 < = M <= N\&. !> .fi .PP .br \fIS\fP .PP .nf !> S is REAL !> If JOB = 'E' or 'B', S is a lower bound on the reciprocal !> condition number for the selected cluster of eigenvalues\&. !> S cannot underestimate the true reciprocal condition number !> by more than a factor of sqrt(N)\&. If M = 0 or N, S = 1\&. !> If JOB = 'N' or 'V', S is not referenced\&. !> .fi .PP .br \fISEP\fP .PP .nf !> SEP is REAL !> If JOB = 'V' or 'B', SEP is the estimated reciprocal !> condition number of the specified invariant subspace\&. If !> M = 0 or N, SEP = norm(T)\&. !> If JOB = 'N' or 'E', SEP is not referenced\&. !> .fi .PP .br \fIWORK\fP .PP .nf !> WORK is REAL array, dimension (MAX(1,LWORK)) !> On exit, if INFO = 0, WORK(1) returns the optimal LWORK\&. !> .fi .PP .br \fILWORK\fP .PP .nf !> LWORK is INTEGER !> The dimension of the array WORK\&. !> If JOB = 'N', LWORK >= max(1,N); !> if JOB = 'E', LWORK >= max(1,M*(N-M)); !> if JOB = 'V' or 'B', LWORK >= max(1,2*M*(N-M))\&. !> !> If LWORK = -1, then a workspace query is assumed; the routine !> only calculates the optimal size of the WORK array, returns !> this value as the first entry of the WORK array, and no error !> message related to LWORK is issued by XERBLA\&. !> .fi .PP .br \fIIWORK\fP .PP .nf !> IWORK is INTEGER array, dimension (MAX(1,LIWORK)) !> On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK\&. !> .fi .PP .br \fILIWORK\fP .PP .nf !> LIWORK is INTEGER !> The dimension of the array IWORK\&. !> If JOB = 'N' or 'E', LIWORK >= 1; !> if JOB = 'V' or 'B', LIWORK >= max(1,M*(N-M))\&. !> !> If LIWORK = -1, then a workspace query is assumed; the !> routine only calculates the optimal size of the IWORK array, !> returns this value as the first entry of the IWORK array, and !> no error message related to LIWORK is issued by XERBLA\&. !> .fi .PP .br \fIINFO\fP .PP .nf !> INFO is INTEGER !> = 0: successful exit !> < 0: if INFO = -i, the i-th argument had an illegal value !> = 1: reordering of T failed because some eigenvalues are too !> close to separate (the problem is very ill-conditioned); !> T may have been partially reordered, and WR and WI !> contain the eigenvalues in the same order as in T; S and !> SEP (if requested) are set to zero\&. !> .fi .PP .RE .PP \fBAuthor\fP .RS 4 Univ\&. of Tennessee .PP Univ\&. of California Berkeley .PP Univ\&. of Colorado Denver .PP NAG Ltd\&. .RE .PP \fBFurther Details:\fP .RS 4 .PP .nf !> !> STRSEN first collects the selected eigenvalues by computing an !> orthogonal transformation Z to move them to the top left corner of T\&. !> In other words, the selected eigenvalues are the eigenvalues of T11 !> in: !> !> Z**T * T * Z = ( T11 T12 ) n1 !> ( 0 T22 ) n2 !> n1 n2 !> !> where N = n1+n2 and Z**T means the transpose of Z\&. The first n1 columns !> of Z span the specified invariant subspace of T\&. !> !> If T has been obtained from the real Schur factorization of a matrix !> A = Q*T*Q**T, then the reordered real Schur factorization of A is given !> by A = (Q*Z)*(Z**T*T*Z)*(Q*Z)**T, and the first n1 columns of Q*Z span !> the corresponding invariant subspace of A\&. !> !> The reciprocal condition number of the average of the eigenvalues of !> T11 may be returned in S\&. S lies between 0 (very badly conditioned) !> and 1 (very well conditioned)\&. It is computed as follows\&. First we !> compute R so that !> !> P = ( I R ) n1 !> ( 0 0 ) n2 !> n1 n2 !> !> is the projector on the invariant subspace associated with T11\&. !> R is the solution of the Sylvester equation: !> !> T11*R - R*T22 = T12\&. !> !> Let F-norm(M) denote the Frobenius-norm of M and 2-norm(M) denote !> the two-norm of M\&. Then S is computed as the lower bound !> !> (1 + F-norm(R)**2)**(-1/2) !> !> on the reciprocal of 2-norm(P), the true reciprocal condition number\&. !> S cannot underestimate 1 / 2-norm(P) by more than a factor of !> sqrt(N)\&. !> !> An approximate error bound for the computed average of the !> eigenvalues of T11 is !> !> EPS * norm(T) / S !> !> where EPS is the machine precision\&. !> !> The reciprocal condition number of the right invariant subspace !> spanned by the first n1 columns of Z (or of Q*Z) is returned in SEP\&. !> SEP is defined as the separation of T11 and T22: !> !> sep( T11, T22 ) = sigma-min( C ) !> !> where sigma-min(C) is the smallest singular value of the !> n1*n2-by-n1*n2 matrix !> !> C = kprod( I(n2), T11 ) - kprod( transpose(T22), I(n1) ) !> !> I(m) is an m by m identity matrix, and kprod denotes the Kronecker !> product\&. We estimate sigma-min(C) by the reciprocal of an estimate of !> the 1-norm of inverse(C)\&. The true reciprocal 1-norm of inverse(C) !> cannot differ from sigma-min(C) by more than a factor of sqrt(n1*n2)\&. !> !> When SEP is small, small changes in T can cause large changes in !> the invariant subspace\&. An approximate bound on the maximum angular !> error in the computed right invariant subspace is !> !> EPS * norm(T) / SEP !> .fi .PP .RE .PP .PP Definition at line \fB312\fP of file \fBstrsen\&.f\fP\&. .SH "Author" .PP Generated automatically by Doxygen for LAPACK from the source code\&.