--- rpl/lapack/lapack/dsyevr.f 2010/12/21 13:53:39 1.8 +++ rpl/lapack/lapack/dsyevr.f 2011/11/21 20:43:04 1.9 @@ -1,11 +1,334 @@ +*> \brief DSYEVR computes the eigenvalues and, optionally, the left and/or right eigenvectors for SY matrices +* +* =========== DOCUMENTATION =========== +* +* Online html documentation available at +* http://www.netlib.org/lapack/explore-html/ +* +*> \htmlonly +*> Download DSYEVR + dependencies +*> +*> [TGZ] +*> +*> [ZIP] +*> +*> [TXT] +*> \endhtmlonly +* +* Definition: +* =========== +* +* SUBROUTINE DSYEVR( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, +* ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK, +* IWORK, LIWORK, INFO ) +* +* .. Scalar Arguments .. +* CHARACTER JOBZ, RANGE, UPLO +* INTEGER IL, INFO, IU, LDA, LDZ, LIWORK, LWORK, M, N +* DOUBLE PRECISION ABSTOL, VL, VU +* .. +* .. Array Arguments .. +* INTEGER ISUPPZ( * ), IWORK( * ) +* DOUBLE PRECISION A( LDA, * ), W( * ), WORK( * ), Z( LDZ, * ) +* .. +* +* +*> \par Purpose: +* ============= +*> +*> \verbatim +*> +*> DSYEVR 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. +*> +*> DSYEVR first reduces the matrix A to tridiagonal form T with a call +*> to DSYTRD. Then, whenever possible, DSYEVR calls DSTEMR to compute +*> the eigenspectrum using Relatively Robust Representations. DSTEMR +*> 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 DSTEMR'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 : DSYEVR calls DSTEMR when the full spectrum is requested +*> on machines which conform to the ieee-754 floating point standard. +*> DSYEVR calls DSTEBZ and SSTEIN on non-ieee machines and +*> when partial spectrum requests are made. +*> +*> Normal execution of DSTEMR 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. +*> \endverbatim +* +* Arguments: +* ========== +* +*> \param[in] JOBZ +*> \verbatim +*> JOBZ is CHARACTER*1 +*> = 'N': Compute eigenvalues only; +*> = 'V': Compute eigenvalues and eigenvectors. +*> \endverbatim +*> +*> \param[in] RANGE +*> \verbatim +*> 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, DSTEBZ and +*> DSTEIN are called +*> \endverbatim +*> +*> \param[in] UPLO +*> \verbatim +*> UPLO is CHARACTER*1 +*> = 'U': Upper triangle of A is stored; +*> = 'L': Lower triangle of A is stored. +*> \endverbatim +*> +*> \param[in] N +*> \verbatim +*> N is INTEGER +*> The order of the matrix A. N >= 0. +*> \endverbatim +*> +*> \param[in,out] A +*> \verbatim +*> A is DOUBLE PRECISION 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. +*> \endverbatim +*> +*> \param[in] LDA +*> \verbatim +*> LDA is INTEGER +*> The leading dimension of the array A. LDA >= max(1,N). +*> \endverbatim +*> +*> \param[in] VL +*> \verbatim +*> VL is DOUBLE PRECISION +*> \endverbatim +*> +*> \param[in] VU +*> \verbatim +*> VU is DOUBLE PRECISION +*> 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'. +*> \endverbatim +*> +*> \param[in] IL +*> \verbatim +*> IL is INTEGER +*> \endverbatim +*> +*> \param[in] IU +*> \verbatim +*> 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'. +*> \endverbatim +*> +*> \param[in] ABSTOL +*> \verbatim +*> ABSTOL is DOUBLE PRECISION +*> 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 +*> DLAMCH( '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. +*> \endverbatim +*> +*> \param[out] M +*> \verbatim +*> 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. +*> \endverbatim +*> +*> \param[out] W +*> \verbatim +*> W is DOUBLE PRECISION array, dimension (N) +*> The first M elements contain the selected eigenvalues in +*> ascending order. +*> \endverbatim +*> +*> \param[out] Z +*> \verbatim +*> Z is DOUBLE PRECISION 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. +*> \endverbatim +*> +*> \param[in] LDZ +*> \verbatim +*> LDZ is INTEGER +*> The leading dimension of the array Z. LDZ >= 1, and if +*> JOBZ = 'V', LDZ >= max(1,N). +*> \endverbatim +*> +*> \param[out] ISUPPZ +*> \verbatim +*> 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 +*> \endverbatim +*> +*> \param[out] WORK +*> \verbatim +*> WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK)) +*> On exit, if INFO = 0, WORK(1) returns the optimal LWORK. +*> \endverbatim +*> +*> \param[in] LWORK +*> \verbatim +*> 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 DSYTRD and DORMTR +*> returned by ILAENV. +*> +*> 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. +*> \endverbatim +*> +*> \param[out] IWORK +*> \verbatim +*> IWORK is INTEGER array, dimension (MAX(1,LIWORK)) +*> On exit, if INFO = 0, IWORK(1) returns the optimal LWORK. +*> \endverbatim +*> +*> \param[in] LIWORK +*> \verbatim +*> 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 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. +*> \endverbatim +*> +*> \param[out] INFO +*> \verbatim +*> INFO is INTEGER +*> = 0: successful exit +*> < 0: if INFO = -i, the i-th argument had an illegal value +*> > 0: Internal error +*> \endverbatim +* +* Authors: +* ======== +* +*> \author Univ. of Tennessee +*> \author Univ. of California Berkeley +*> \author Univ. of Colorado Denver +*> \author NAG Ltd. +* +*> \date November 2011 +* +*> \ingroup doubleSYeigen +* +*> \par Contributors: +* ================== +*> +*> Inderjit Dhillon, IBM Almaden, USA \n +*> Osni Marques, LBNL/NERSC, USA \n +*> Ken Stanley, Computer Science Division, University of +*> California at Berkeley, USA \n +*> Jason Riedy, Computer Science Division, University of +*> California at Berkeley, USA \n +*> +* ===================================================================== SUBROUTINE DSYEVR( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, $ ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK, $ IWORK, LIWORK, INFO ) * -* -- LAPACK driver routine (version 3.2.2) -- +* -- LAPACK driver routine (version 3.4.0) -- * -- LAPACK is a software package provided by Univ. of Tennessee, -- * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- -* June 2010 +* November 2011 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE, UPLO @@ -17,214 +340,6 @@ DOUBLE PRECISION A( LDA, * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * -* Purpose -* ======= -* -* DSYEVR 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. -* -* DSYEVR first reduces the matrix A to tridiagonal form T with a call -* to DSYTRD. Then, whenever possible, DSYEVR calls DSTEMR to compute -* the eigenspectrum using Relatively Robust Representations. DSTEMR -* 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 DSTEMR'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 : DSYEVR calls DSTEMR when the full spectrum is requested -* on machines which conform to the ieee-754 floating point standard. -* DSYEVR calls DSTEBZ and SSTEIN on non-ieee machines and -* when partial spectrum requests are made. -* -* Normal execution of DSTEMR 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. -* -* Arguments -* ========= -* -* 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. -********** For RANGE = 'V' or 'I' and IU - IL < N - 1, DSTEBZ and -********** DSTEIN are called -* -* UPLO (input) CHARACTER*1 -* = 'U': Upper triangle of A is stored; -* = 'L': Lower triangle of A is stored. -* -* N (input) INTEGER -* The order of the matrix A. N >= 0. -* -* A (input/output) DOUBLE PRECISION 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 (input) INTEGER -* The leading dimension of the array A. LDA >= max(1,N). -* -* VL (input) DOUBLE PRECISION -* VU (input) DOUBLE PRECISION -* 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) DOUBLE PRECISION -* 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 -* DLAMCH( '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 (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) DOUBLE PRECISION array, dimension (N) -* The first M elements contain the selected eigenvalues in -* ascending order. -* -* Z (output) DOUBLE PRECISION 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 (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 ). -********** Implemented only for RANGE = 'A' or 'I' and IU - IL = N - 1 -* -* WORK (workspace/output) DOUBLE PRECISION 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. LWORK >= max(1,26*N). -* For optimal efficiency, LWORK >= (NB+6)*N, -* where NB is the max of the blocksize for DSYTRD and DORMTR -* returned by ILAENV. -* -* 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 (MAX(1,LIWORK)) -* On exit, if INFO = 0, IWORK(1) returns the optimal LWORK. -* -* LIWORK (input) 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 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: Internal error -* -* Further Details -* =============== -* -* Based on contributions by -* 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 -* * ===================================================================== * * .. Parameters ..