org.netlib.lapack
Class SSYGVD
java.lang.Object
org.netlib.lapack.SSYGVD
public class SSYGVD
- extends java.lang.Object
SSYGVD is a simplified interface to the JLAPACK routine ssygvd.
This interface converts Java-style 2D row-major arrays into
the 1D column-major linearized arrays expected by the lower
level JLAPACK routines. Using this interface also allows you
to omit offset and leading dimension arguments. However, because
of these conversions, these routines will be slower than the low
level ones. Following is the description from the original Fortran
source. Contact seymour@cs.utk.edu with any questions.
* ..
*
* 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 (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 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.
*
* IWORK (workspace/output) INTEGER array, dimension (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 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.
*
* 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, SSYEVD failed to converge;
* i off-diagonal elements of an intermediate
* tridiagonal form did not converge to zero;
* > 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
*
* =====================================================================
*
* .. Parameters ..
|
Method Summary |
static void |
SSYGVD(int itype,
java.lang.String jobz,
java.lang.String uplo,
int n,
float[][] a,
float[][] b,
float[] w,
float[] work,
int lwork,
int[] iwork,
int liwork,
intW info)
|
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
SSYGVD
public SSYGVD()
SSYGVD
public static void SSYGVD(int itype,
java.lang.String jobz,
java.lang.String uplo,
int n,
float[][] a,
float[][] b,
float[] w,
float[] work,
int lwork,
int[] iwork,
int liwork,
intW info)