SUBROUTINE SSYGVD( ITYPE, JOBZ, UPLO, N, A, LDA, B, LDB, W, WORK, $ LWORK, IWORK, LIWORK, INFO ) * * -- LAPACK driver routine (version 3.1) -- * 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