public class SLARRV
- extends java.lang.Object
SLARRV is a simplified interface to the JLAPACK routine slarrv.
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 email@example.com with any questions.
* SLARRV computes the eigenvectors of the tridiagonal matrix
* T = L D L^T given L, D and the eigenvalues of L D L^T.
* The input eigenvalues should have high relative accuracy with
* respect to the entries of L and D. The desired accuracy of the
* output can be specified by the input parameter TOL.
* N (input) INTEGER
* The order of the matrix. N >= 0.
* D (input/output) REAL array, dimension (N)
* On entry, the n diagonal elements of the diagonal matrix D.
* On exit, D may be overwritten.
* L (input/output) REAL array, dimension (N-1)
* On entry, the (n-1) subdiagonal elements of the unit
* bidiagonal matrix L in elements 1 to N-1 of L. L(N) need
* not be set. On exit, L is overwritten.
* ISPLIT (input) INTEGER array, dimension (N)
* The splitting points, at which T breaks up into submatrices.
* The first submatrix consists of rows/columns 1 to
* ISPLIT( 1 ), the second of rows/columns ISPLIT( 1 )+1
* through ISPLIT( 2 ), etc.
* TOL (input) REAL
* The absolute error tolerance for the
* Errors in the input eigenvalues must be bounded by TOL.
* The eigenvectors output have residual norms
* bounded by TOL, and the dot products between different
* eigenvectors are bounded by TOL. TOL must be at least
* N*EPS*|T|, where EPS is the machine precision and |T| is
* the 1-norm of the tridiagonal matrix.
* M (input) INTEGER
* The total number of eigenvalues found. 0 <= M <= N.
* If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1.
* W (input) REAL array, dimension (N)
* The first M elements of W contain the eigenvalues for
* which eigenvectors are to be computed. The eigenvalues
* should be grouped by split-off block and ordered from
* smallest to largest within the block ( The output array
* W from SLARRE is expected here ).
* Errors in W must be bounded by TOL (see above).
* IBLOCK (input) INTEGER array, dimension (N)
* The submatrix indices associated with the corresponding
* eigenvalues in W; IBLOCK(i)=1 if eigenvalue W(i) belongs to
* the first submatrix from the top, =2 if W(i) belongs to
* the second submatrix, etc.
* Z (output) REAL array, dimension (LDZ, max(1,M) )
* If JOBZ = 'V', then if INFO = 0, the first M columns of Z
* contain the orthonormal eigenvectors of the matrix T
* corresponding to the selected eigenvalues, with the i-th
* column of Z holding the eigenvector associated with W(i).
* If JOBZ = 'N', then Z is not referenced.
* 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).
* ISUPPZ (output) INTEGER ARRAY, dimension ( 2*max(1,M) )
* The support of the eigenvectors in Z, i.e., the indices
* indicating the nonzero elements in Z. The i-th eigenvector
* is nonzero only in elements ISUPPZ( 2*i-1 ) through
* ISUPPZ( 2*i ).
* WORK (workspace) REAL array, dimension (13*N)
* IWORK (workspace) INTEGER array, dimension (6*N)
* INFO (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: if INFO = 1, internal error in SLARRB
* if INFO = 2, internal error in SSTEIN
* Further Details
* Based on contributions by
* Inderjit Dhillon, IBM Almaden, USA
* Osni Marques, LBNL/NERSC, USA
* .. Parameters ..
|Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
public static void SLARRV(int n,