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SUBROUTINE SSYGVD( ITYPE, JOBZ, UPLO, N, A, LDA, B, LDB, W, WORK,
$ LWORK, IWORK, LIWORK, INFO )
*
* -- LAPACK driver routine (version 3.2) --
* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..
* November 2006
*
* .. Scalar Arguments ..
CHARACTER JOBZ, UPLO
INTEGER INFO, ITYPE, LDA, LDB, LIWORK, LWORK, N
* ..
* .. Array Arguments ..
INTEGER IWORK( * )
REAL A( LDA, * ), B( LDB, * ), W( * ), WORK( * )
* ..
*
* Purpose
* =======
*
* SSYGVD computes all the eigenvalues, and optionally, the eigenvectors
* of a real generalized symmetric-definite eigenproblem, of the form
* A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x. Here A and
* B are assumed to be symmetric and B is also positive definite.
* If eigenvectors are desired, it uses a divide and conquer algorithm.
*
* The divide and conquer algorithm makes very mild assumptions about
* floating point arithmetic. It will work on machines with a guard
* digit in add/subtract, or on those binary machines without guard
* digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or
* Cray-2. It could conceivably fail on hexadecimal or decimal machines
* without guard digits, but we know of none.
*
* Arguments
* =========
*
* ITYPE (input) INTEGER
* Specifies the problem type to be solved:
* = 1: A*x = (lambda)*B*x
* = 2: A*B*x = (lambda)*x
* = 3: B*A*x = (lambda)*x
*
* JOBZ (input) CHARACTER*1
* = 'N': Compute eigenvalues only;
* = 'V': Compute eigenvalues and eigenvectors.
*
* UPLO (input) CHARACTER*1
* = 'U': Upper triangles of A and B are stored;
* = 'L': Lower triangles of A and B are stored.
*
* N (input) INTEGER
* The order of the matrices A and B. N >= 0.
*
* A (input/output) REAL array, dimension (LDA, N)
* On entry, the symmetric matrix A. If UPLO = 'U', the
* leading N-by-N upper triangular part of A contains the
* upper triangular part of the matrix A. If UPLO = 'L',
* the leading N-by-N lower triangular part of A contains
* the lower triangular part of the matrix A.
*
* On exit, if JOBZ = 'V', then if INFO = 0, A contains the
* matrix Z of eigenvectors. The eigenvectors are normalized
* as follows:
* if ITYPE = 1 or 2, Z**T*B*Z = I;
* if ITYPE = 3, Z**T*inv(B)*Z = I.
* If JOBZ = 'N', then on exit the upper triangle (if UPLO='U')
* or the lower triangle (if UPLO='L') of A, including the
* diagonal, is destroyed.
*
* LDA (input) INTEGER
* The leading dimension of the array A. LDA >= max(1,N).
*
* B (input/output) REAL array, dimension (LDB, N)
* On entry, the symmetric matrix B. If UPLO = 'U', the
* leading N-by-N upper triangular part of B contains the
* upper triangular part of the matrix B. If UPLO = 'L',
* the leading N-by-N lower triangular part of B contains
* the lower triangular part of the matrix B.
*
* On exit, if INFO <= N, the part of B containing the matrix is
* overwritten by the triangular factor U or L from the Cholesky
* factorization B = U**T*U or B = L*L**T.
*
* LDB (input) INTEGER
* The leading dimension of the array B. LDB >= max(1,N).
*
* W (output) REAL array, dimension (N)
* If INFO = 0, the eigenvalues in ascending order.
*
* WORK (workspace/output) REAL array, dimension (MAX(1,LWORK))
* On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
* LWORK (input) INTEGER
* The dimension of the array WORK.
* If N <= 1, LWORK >= 1.
* If JOBZ = 'N' and N > 1, LWORK >= 2*N+1.
* If JOBZ = 'V' and N > 1, LWORK >= 1 + 6*N + 2*N**2.
*
* If LWORK = -1, then a workspace query is assumed; the routine
* only calculates the optimal sizes of the WORK and IWORK
* arrays, returns these values as the first entries of the WORK
* and IWORK arrays, and no error message related to LWORK or
* LIWORK is issued by XERBLA.
*
* IWORK (workspace/output) INTEGER array, dimension (MAX(1,LIWORK))
* On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.
*
* LIWORK (input) INTEGER
* The dimension of the array IWORK.
* If N <= 1, LIWORK >= 1.
* If JOBZ = 'N' and N > 1, LIWORK >= 1.
* If JOBZ = 'V' and N > 1, LIWORK >= 3 + 5*N.
*
* If LIWORK = -1, then a workspace query is assumed; the
* routine only calculates the optimal sizes of the WORK and
* IWORK arrays, returns these values as the first entries of
* the WORK and IWORK arrays, and no error message related to
* LWORK or LIWORK is issued by XERBLA.
*
* INFO (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: SPOTRF or SSYEVD returned an error code:
* <= N: if INFO = i and JOBZ = 'N', then the algorithm
* failed to converge; i off-diagonal elements of an
* intermediate tridiagonal form did not converge to
* zero;
* if INFO = i and JOBZ = 'V', then the algorithm
* failed to compute an eigenvalue while working on
* the submatrix lying in rows and columns INFO/(N+1)
* through mod(INFO,N+1);
* > N: if INFO = N + i, for 1 <= i <= N, then the leading
* minor of order i of B is not positive definite.
* The factorization of B could not be completed and
* no eigenvalues or eigenvectors were computed.
*
* Further Details
* ===============
*
* Based on contributions by
* Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA
*
* Modified so that no backsubstitution is performed if SSYEVD fails to
* converge (NEIG in old code could be greater than N causing out of
* bounds reference to A - reported by Ralf Meyer). Also corrected the
* description of INFO and the test on ITYPE. Sven, 16 Feb 05.
* =====================================================================
*
* .. Parameters ..
REAL ONE
PARAMETER ( ONE = 1.0E+0 )
* ..
* .. Local Scalars ..
LOGICAL LQUERY, UPPER, WANTZ
CHARACTER TRANS
INTEGER LIOPT, LIWMIN, LOPT, LWMIN
* ..
* .. External Functions ..
LOGICAL LSAME
EXTERNAL LSAME
* ..
* .. External Subroutines ..
EXTERNAL SPOTRF, SSYEVD, SSYGST, STRMM, STRSM, XERBLA
* ..
* .. Intrinsic Functions ..
INTRINSIC MAX, REAL
* ..
* .. Executable Statements ..
*
* Test the input parameters.
*
WANTZ = LSAME( JOBZ, 'V' )
UPPER = LSAME( UPLO, 'U' )
LQUERY = ( LWORK.EQ.-1 .OR. LIWORK.EQ.-1 )
*
INFO = 0
IF( N.LE.1 ) THEN
LIWMIN = 1
LWMIN = 1
ELSE IF( WANTZ ) THEN
LIWMIN = 3 + 5*N
LWMIN = 1 + 6*N + 2*N**2
ELSE
LIWMIN = 1
LWMIN = 2*N + 1
END IF
LOPT = LWMIN
LIOPT = LIWMIN
IF( ITYPE.LT.1 .OR. ITYPE.GT.3 ) THEN
INFO = -1
ELSE IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN
INFO = -2
ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN
INFO = -3
ELSE IF( N.LT.0 ) THEN
INFO = -4
ELSE IF( LDA.LT.MAX( 1, N ) ) THEN
INFO = -6
ELSE IF( LDB.LT.MAX( 1, N ) ) THEN
INFO = -8
END IF
*
IF( INFO.EQ.0 ) THEN
WORK( 1 ) = LOPT
IWORK( 1 ) = LIOPT
*
IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN
INFO = -11
ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN
INFO = -13
END IF
END IF
*
IF( INFO.NE.0 ) THEN
CALL XERBLA( 'SSYGVD', -INFO )
RETURN
ELSE IF( LQUERY ) THEN
RETURN
END IF
*
* Quick return if possible
*
IF( N.EQ.0 )
$ RETURN
*
* Form a Cholesky factorization of B.
*
CALL SPOTRF( UPLO, N, B, LDB, INFO )
IF( INFO.NE.0 ) THEN
INFO = N + INFO
RETURN
END IF
*
* Transform problem to standard eigenvalue problem and solve.
*
CALL SSYGST( ITYPE, UPLO, N, A, LDA, B, LDB, INFO )
CALL SSYEVD( JOBZ, UPLO, N, A, LDA, W, WORK, LWORK, IWORK, LIWORK,
$ INFO )
LOPT = MAX( REAL( LOPT ), REAL( WORK( 1 ) ) )
LIOPT = MAX( REAL( LIOPT ), REAL( IWORK( 1 ) ) )
*
IF( WANTZ .AND. INFO.EQ.0 ) THEN
*
* Backtransform eigenvectors to the original problem.
*
IF( ITYPE.EQ.1 .OR. ITYPE.EQ.2 ) THEN
*
* For A*x=(lambda)*B*x and A*B*x=(lambda)*x;
* backtransform eigenvectors: x = inv(L)'*y or inv(U)*y
*
IF( UPPER ) THEN
TRANS = 'N'
ELSE
TRANS = 'T'
END IF
*
CALL STRSM( 'Left', UPLO, TRANS, 'Non-unit', N, N, ONE,
$ B, LDB, A, LDA )
*
ELSE IF( ITYPE.EQ.3 ) THEN
*
* For B*A*x=(lambda)*x;
* backtransform eigenvectors: x = L*y or U'*y
*
IF( UPPER ) THEN
TRANS = 'T'
ELSE
TRANS = 'N'
END IF
*
CALL STRMM( 'Left', UPLO, TRANS, 'Non-unit', N, N, ONE,
$ B, LDB, A, LDA )
END IF
END IF
*
WORK( 1 ) = LOPT
IWORK( 1 ) = LIOPT
*
RETURN
*
* End of SSYGVD
*
END
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