ssyevr.f −

**Functions/Subroutines**

subroutine **ssyevr** (JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK, IWORK, LIWORK, INFO)

SSYEVR computes the eigenvalues and, optionally, the left and/or right eigenvectors for SY matrices

**subroutine ssyevr (characterJOBZ, characterRANGE, characterUPLO, integerN, real, dimension( lda, * )A, integerLDA, realVL, realVU, integerIL, integerIU, realABSTOL, integerM, real, dimension( * )W, real, dimension( ldz, * )Z, integerLDZ, integer, dimension( * )ISUPPZ, real, dimension( * )WORK, integerLWORK, integer, dimension( * )IWORK, integerLIWORK, integerINFO)
SSYEVR computes the eigenvalues and, optionally, the left and/or right eigenvectors for SY matrices**

**Purpose:**

SSYEVR computes selected eigenvalues and, optionally, eigenvectors

of a real symmetric matrix A. Eigenvalues and eigenvectors can be

selected by specifying either a range of values or a range of

indices for the desired eigenvalues.

SSYEVR first reduces the matrix A to tridiagonal form T with a call

to SSYTRD. Then, whenever possible, SSYEVR calls SSTEMR to compute

the eigenspectrum using Relatively Robust Representations. SSTEMR

computes eigenvalues by the dqds algorithm, while orthogonal

eigenvectors are computed from various "good" L D L^T representations

(also known as Relatively Robust Representations). Gram-Schmidt

orthogonalization is avoided as far as possible. More specifically,

the various steps of the algorithm are as follows.

For each unreduced block (submatrix) of T,

(a) Compute T - sigma I = L D L^T, so that L and D

define all the wanted eigenvalues to high relative accuracy.

This means that small relative changes in the entries of D and L

cause only small relative changes in the eigenvalues and

eigenvectors. The standard (unfactored) representation of the

tridiagonal matrix T does not have this property in general.

(b) Compute the eigenvalues to suitable accuracy.

If the eigenvectors are desired, the algorithm attains full

accuracy of the computed eigenvalues only right before

the corresponding vectors have to be computed, see steps c) and d).

(c) For each cluster of close eigenvalues, select a new

shift close to the cluster, find a new factorization, and refine

the shifted eigenvalues to suitable accuracy.

(d) For each eigenvalue with a large enough relative separation compute

the corresponding eigenvector by forming a rank revealing twisted

factorization. Go back to (c) for any clusters that remain.

The desired accuracy of the output can be specified by the input

parameter ABSTOL.

For more details, see SSTEMR’s documentation and:

- Inderjit S. Dhillon and Beresford N. Parlett: "Multiple representations

to compute orthogonal eigenvectors of symmetric tridiagonal matrices,"

Linear Algebra and its Applications, 387(1), pp. 1-28, August 2004.

- Inderjit Dhillon and Beresford Parlett: "Orthogonal Eigenvectors and

Relative Gaps," SIAM Journal on Matrix Analysis and Applications, Vol. 25,

2004. Also LAPACK Working Note 154.

- Inderjit Dhillon: "A new O(n^2) algorithm for the symmetric

tridiagonal eigenvalue/eigenvector problem",

Computer Science Division Technical Report No. UCB/CSD-97-971,

UC Berkeley, May 1997.

Note 1 : SSYEVR calls SSTEMR when the full spectrum is requested

on machines which conform to the ieee-754 floating point standard.

SSYEVR calls SSTEBZ and SSTEIN on non-ieee machines and

when partial spectrum requests are made.

Normal execution of SSTEMR may create NaNs and infinities and

hence may abort due to a floating point exception in environments

which do not handle NaNs and infinities in the ieee standard default

manner.

**Parameters:**

*JOBZ*

JOBZ is CHARACTER*1

= ’N’: Compute eigenvalues only;

= ’V’: Compute eigenvalues and eigenvectors.

*RANGE*

RANGE is 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.

For RANGE = ’V’ or ’I’ and IU - IL < N - 1, SSTEBZ and

SSTEIN are called

*UPLO*

UPLO is CHARACTER*1

= ’U’: Upper triangle of A is stored;

= ’L’: Lower triangle of A is stored.

*N*

N is INTEGER

The order of the matrix A. N >= 0.

*A*

A is 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, the lower triangle (if UPLO=’L’) or the upper

triangle (if UPLO=’U’) of A, including the diagonal, is

destroyed.

*LDA*

LDA is INTEGER

The leading dimension of the array A. LDA >= max(1,N).

*VL*

VL is REAL

*VU*

VU is 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*

IL is INTEGER

*IU*

IU is 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*

ABSTOL is 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.

See "Computing Small Singular Values of Bidiagonal Matrices

with Guaranteed High Relative Accuracy," by Demmel and

Kahan, LAPACK Working Note #3.

If high relative accuracy is important, set ABSTOL to

SLAMCH( ’Safe minimum’ ). Doing so will guarantee that

eigenvalues are computed to high relative accuracy when

possible in future releases. The current code does not

make any guarantees about high relative accuracy, but

future releases will. See J. Barlow and J. Demmel,

"Computing Accurate Eigensystems of Scaled Diagonally

Dominant Matrices", LAPACK Working Note #7, for a discussion

of which matrices define their eigenvalues to high relative

accuracy.

*M*

M is INTEGER

The total number of eigenvalues found. 0 <= M <= N.

If RANGE = ’A’, M = N, and if RANGE = ’I’, M = IU-IL+1.

*W*

W is REAL array, dimension (N)

The first M elements contain the selected eigenvalues in

ascending order.

*Z*

Z is 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 A

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.

Supplying N columns is always safe.

*LDZ*

LDZ is INTEGER

The leading dimension of the array Z. LDZ >= 1, and if

JOBZ = ’V’, LDZ >= max(1,N).

*ISUPPZ*

ISUPPZ is 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 ).

Implemented only for RANGE = ’A’ or ’I’ and IU - IL = N - 1

*WORK*

WORK is REAL array, dimension (MAX(1,LWORK))

On exit, if INFO = 0, WORK(1) returns the optimal LWORK.

*LWORK*

LWORK is INTEGER

The dimension of the array WORK. LWORK >= max(1,26*N).

For optimal efficiency, LWORK >= (NB+6)*N,

where NB is the max of the blocksize for SSYTRD and SORMTR

returned by ILAENV.

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*

IWORK is INTEGER array, dimension (MAX(1,LIWORK))

On exit, if INFO = 0, IWORK(1) returns the optimal LWORK.

*LIWORK*

LIWORK is INTEGER

The dimension of the array IWORK. LIWORK >= max(1,10*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*

INFO is INTEGER

= 0: successful exit

< 0: if INFO = -i, the i-th argument had an illegal value

> 0: Internal error

**Author:**

Univ. of Tennessee

Univ. of California Berkeley

Univ. of Colorado Denver

NAG Ltd.

**Date:**

September 2012

**Contributors:**

Inderjit Dhillon, IBM Almaden, USA

Osni Marques, LBNL/NERSC, USA

Ken Stanley, Computer Science Division, University of California at Berkeley, USA

Jason Riedy, Computer Science Division, University of California at Berkeley, USA

Definition at line 326 of file ssyevr.f.

Generated automatically by Doxygen for LAPACK from the source code.