SUBROUTINE SSPGVX( ITYPE, JOBZ, RANGE, UPLO, N, AP, BP, VL, VU,
$ IL, IU, ABSTOL, M, W, Z, LDZ, WORK, IWORK,
$ IFAIL, INFO )
*
* -- LAPACK driver routine (version 3.1) --
* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..
* November 2006
*
* .. Scalar Arguments ..
CHARACTER JOBZ, RANGE, UPLO
INTEGER IL, INFO, ITYPE, IU, LDZ, M, N
REAL ABSTOL, VL, VU
* ..
* .. Array Arguments ..
INTEGER IFAIL( * ), IWORK( * )
REAL AP( * ), BP( * ), W( * ), WORK( * ),
$ Z( LDZ, * )
* ..
*
* Purpose
* =======
*
* SSPGVX computes selected eigenvalues, and optionally, 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, stored in packed storage, and B
* is also positive definite. Eigenvalues and eigenvectors can be
* selected by specifying either a range of values or a range of indices
* for the desired eigenvalues.
*
* 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.
*
* RANGE (input) CHARACTER*1
* = 'A': all eigenvalues will be found.
* = 'V': all eigenvalues in the half-open interval (VL,VU]
* will be found.
* = 'I': the IL-th through IU-th eigenvalues will be found.
*
* UPLO (input) CHARACTER*1
* = 'U': Upper triangle of A and B are stored;
* = 'L': Lower triangle of A and B are stored.
*
* N (input) INTEGER
* The order of the matrix pencil (A,B). N >= 0.
*
* AP (input/output) REAL array, dimension (N*(N+1)/2)
* On entry, the upper or lower triangle of the symmetric matrix
* A, packed columnwise in a linear array. The j-th column of A
* is stored in the array AP as follows:
* if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j;
* if UPLO = 'L', AP(i + (j-1)*(2*n-j)/2) = A(i,j) for j<=i<=n.
*
* On exit, the contents of AP are destroyed.
*
* BP (input/output) REAL array, dimension (N*(N+1)/2)
* On entry, the upper or lower triangle of the symmetric matrix
* B, packed columnwise in a linear array. The j-th column of B
* is stored in the array BP as follows:
* if UPLO = 'U', BP(i + (j-1)*j/2) = B(i,j) for 1<=i<=j;
* if UPLO = 'L', BP(i + (j-1)*(2*n-j)/2) = B(i,j) for j<=i<=n.
*
* On exit, the triangular factor U or L from the Cholesky
* factorization B = U**T*U or B = L*L**T, in the same storage
* format as B.
*
* VL (input) REAL
* VU (input) REAL
* If RANGE='V', the lower and upper bounds of the interval to
* be searched for eigenvalues. VL < VU.
* Not referenced if RANGE = 'A' or 'I'.
*
* IL (input) INTEGER
* IU (input) INTEGER
* If RANGE='I', the indices (in ascending order) of the
* smallest and largest eigenvalues to be returned.
* 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0.
* Not referenced if RANGE = 'A' or 'V'.
*
* ABSTOL (input) REAL
* The absolute error tolerance for the eigenvalues.
* An approximate eigenvalue is accepted as converged
* when it is determined to lie in an interval [a,b]
* of width less than or equal to
*
* ABSTOL + EPS * max( |a|,|b| ) ,
*
* where EPS is the machine precision. If ABSTOL is less than
* or equal to zero, then EPS*|T| will be used in its place,
* where |T| is the 1-norm of the tridiagonal matrix obtained
* by reducing A to tridiagonal form.
*
* Eigenvalues will be computed most accurately when ABSTOL is
* set to twice the underflow threshold 2*SLAMCH('S'), not zero.
* If this routine returns with INFO>0, indicating that some
* eigenvectors did not converge, try setting ABSTOL to
* 2*SLAMCH('S').
*
* M (output) INTEGER
* The total number of eigenvalues found. 0 <= M <= N.
* If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1.
*
* W (output) REAL array, dimension (N)
* On normal exit, the first M elements contain the selected
* eigenvalues in ascending order.
*
* Z (output) REAL array, dimension (LDZ, max(1,M))
* If JOBZ = 'N', then Z is not referenced.
* If JOBZ = 'V', then if INFO = 0, the first M columns of Z
* contain the orthonormal eigenvectors of the matrix A
* corresponding to the selected eigenvalues, with the i-th
* column of Z holding the eigenvector associated with W(i).
* 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 an eigenvector fails to converge, then that column of Z
* contains the latest approximation to the eigenvector, and the
* index of the eigenvector is returned in IFAIL.
* Note: the user must ensure that at least max(1,M) columns are
* supplied in the array Z; if RANGE = 'V', the exact value of M
* is not known in advance and an upper bound must be used.
*
* LDZ (input) INTEGER
* The leading dimension of the array Z. LDZ >= 1, and if
* JOBZ = 'V', LDZ >= max(1,N).
*
* WORK (workspace) REAL array, dimension (8*N)
*
* IWORK (workspace) INTEGER array, dimension (5*N)
*
* IFAIL (output) INTEGER array, dimension (N)
* If JOBZ = 'V', then if INFO = 0, the first M elements of
* IFAIL are zero. If INFO > 0, then IFAIL contains the
* indices of the eigenvectors that failed to converge.
* If JOBZ = 'N', then IFAIL is not referenced.
*
* INFO (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: SPPTRF or SSPEVX returned an error code:
* <= N: if INFO = i, SSPEVX failed to converge;
* i eigenvectors failed to converge. Their indices
* are stored in array IFAIL.
* > 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
*
* =====================================================================
*
* .. Local Scalars ..
LOGICAL ALLEIG, INDEIG, UPPER, VALEIG, WANTZ
CHARACTER TRANS
INTEGER J
* ..
* .. External Functions ..
LOGICAL LSAME
EXTERNAL LSAME
* ..
* .. External Subroutines ..
EXTERNAL SPPTRF, SSPEVX, SSPGST, STPMV, STPSV, XERBLA
* ..
* .. Intrinsic Functions ..
INTRINSIC MIN
* ..
* .. Executable Statements ..
*
* Test the input parameters.
*
UPPER = LSAME( UPLO, 'U' )
WANTZ = LSAME( JOBZ, 'V' )
ALLEIG = LSAME( RANGE, 'A' )
VALEIG = LSAME( RANGE, 'V' )
INDEIG = LSAME( RANGE, 'I' )
*
INFO = 0
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.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN
INFO = -3
ELSE IF( .NOT.( UPPER .OR. LSAME( UPLO, 'L' ) ) ) THEN
INFO = -4
ELSE IF( N.LT.0 ) THEN
INFO = -5
ELSE
IF( VALEIG ) THEN
IF( N.GT.0 .AND. VU.LE.VL ) THEN
INFO = -9
END IF
ELSE IF( INDEIG ) THEN
IF( IL.LT.1 ) THEN
INFO = -10
ELSE IF( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) THEN
INFO = -11
END IF
END IF
END IF
IF( INFO.EQ.0 ) THEN
IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN
INFO = -16
END IF
END IF
*
IF( INFO.NE.0 ) THEN
CALL XERBLA( 'SSPGVX', -INFO )
RETURN
END IF
*
* Quick return if possible
*
M = 0
IF( N.EQ.0 )
$ RETURN
*
* Form a Cholesky factorization of B.
*
CALL SPPTRF( UPLO, N, BP, INFO )
IF( INFO.NE.0 ) THEN
INFO = N + INFO
RETURN
END IF
*
* Transform problem to standard eigenvalue problem and solve.
*
CALL SSPGST( ITYPE, UPLO, N, AP, BP, INFO )
CALL SSPEVX( JOBZ, RANGE, UPLO, N, AP, VL, VU, IL, IU, ABSTOL, M,
$ W, Z, LDZ, WORK, IWORK, IFAIL, INFO )
*
IF( WANTZ ) THEN
*
* Backtransform eigenvectors to the original problem.
*
IF( INFO.GT.0 )
$ M = INFO - 1
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
*
DO 10 J = 1, M
CALL STPSV( UPLO, TRANS, 'Non-unit', N, BP, Z( 1, J ),
$ 1 )
10 CONTINUE
*
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
*
DO 20 J = 1, M
CALL STPMV( UPLO, TRANS, 'Non-unit', N, BP, Z( 1, J ),
$ 1 )
20 CONTINUE
END IF
END IF
*
RETURN
*
* End of SSPGVX
*
END