DOUBLE PRECISION routines for (real) symmetric tridiagonal matrix
dstebz
USAGE:
m, nsplit, w, iblock, isplit, info = NumRu::Lapack.dstebz( range, order, vl, vu, il, iu, abstol, d, e, [:usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTEBZ( RANGE, ORDER, N, VL, VU, IL, IU, ABSTOL, D, E, M, NSPLIT, W, IBLOCK, ISPLIT, WORK, IWORK, INFO )
* Purpose
* =======
*
* DSTEBZ computes the eigenvalues of a symmetric tridiagonal
* matrix T. The user may ask for all eigenvalues, all eigenvalues
* in the half-open interval (VL, VU], or the IL-th through IU-th
* eigenvalues.
*
* To avoid overflow, the matrix must be scaled so that its
* largest element is no greater than overflow**(1/2) *
* underflow**(1/4) in absolute value, and for greatest
* accuracy, it should not be much smaller than that.
*
* See W. Kahan "Accurate Eigenvalues of a Symmetric Tridiagonal
* Matrix", Report CS41, Computer Science Dept., Stanford
* University, July 21, 1966.
*
* Arguments
* =========
*
* RANGE (input) CHARACTER*1
* = 'A': ("All") all eigenvalues will be found.
* = 'V': ("Value") all eigenvalues in the half-open interval
* (VL, VU] will be found.
* = 'I': ("Index") the IL-th through IU-th eigenvalues (of the
* entire matrix) will be found.
*
* ORDER (input) CHARACTER*1
* = 'B': ("By Block") the eigenvalues will be grouped by
* split-off block (see IBLOCK, ISPLIT) and
* ordered from smallest to largest within
* the block.
* = 'E': ("Entire matrix")
* the eigenvalues for the entire matrix
* will be ordered from smallest to
* largest.
*
* N (input) INTEGER
* The order of the tridiagonal matrix T. N >= 0.
*
* VL (input) DOUBLE PRECISION
* VU (input) DOUBLE PRECISION
* If RANGE='V', the lower and upper bounds of the interval to
* be searched for eigenvalues. Eigenvalues less than or equal
* to VL, or greater than VU, will not be returned. 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 tolerance for the eigenvalues. An eigenvalue
* (or cluster) is considered to be located if it has been
* determined to lie in an interval whose width is ABSTOL or
* less. If ABSTOL is less than or equal to zero, then ULP*|T|
* will be used, where |T| means the 1-norm of T.
*
* Eigenvalues will be computed most accurately when ABSTOL is
* set to twice the underflow threshold 2*DLAMCH('S'), not zero.
*
* D (input) DOUBLE PRECISION array, dimension (N)
* The n diagonal elements of the tridiagonal matrix T.
*
* E (input) DOUBLE PRECISION array, dimension (N-1)
* The (n-1) off-diagonal elements of the tridiagonal matrix T.
*
* M (output) INTEGER
* The actual number of eigenvalues found. 0 <= M <= N.
* (See also the description of INFO=2,3.)
*
* NSPLIT (output) INTEGER
* The number of diagonal blocks in the matrix T.
* 1 <= NSPLIT <= N.
*
* W (output) DOUBLE PRECISION array, dimension (N)
* On exit, the first M elements of W will contain the
* eigenvalues. (DSTEBZ may use the remaining N-M elements as
* workspace.)
*
* IBLOCK (output) INTEGER array, dimension (N)
* At each row/column j where E(j) is zero or small, the
* matrix T is considered to split into a block diagonal
* matrix. On exit, if INFO = 0, IBLOCK(i) specifies to which
* block (from 1 to the number of blocks) the eigenvalue W(i)
* belongs. (DSTEBZ may use the remaining N-M elements as
* workspace.)
*
* ISPLIT (output) 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., and the NSPLIT-th consists of rows/columns
* ISPLIT(NSPLIT-1)+1 through ISPLIT(NSPLIT)=N.
* (Only the first NSPLIT elements will actually be used, but
* since the user cannot know a priori what value NSPLIT will
* have, N words must be reserved for ISPLIT.)
*
* WORK (workspace) DOUBLE PRECISION array, dimension (4*N)
*
* IWORK (workspace) INTEGER array, dimension (3*N)
*
* INFO (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: some or all of the eigenvalues failed to converge or
* were not computed:
* =1 or 3: Bisection failed to converge for some
* eigenvalues; these eigenvalues are flagged by a
* negative block number. The effect is that the
* eigenvalues may not be as accurate as the
* absolute and relative tolerances. This is
* generally caused by unexpectedly inaccurate
* arithmetic.
* =2 or 3: RANGE='I' only: Not all of the eigenvalues
* IL:IU were found.
* Effect: M < IU+1-IL
* Cause: non-monotonic arithmetic, causing the
* Sturm sequence to be non-monotonic.
* Cure: recalculate, using RANGE='A', and pick
* out eigenvalues IL:IU. In some cases,
* increasing the PARAMETER "FUDGE" may
* make things work.
* = 4: RANGE='I', and the Gershgorin interval
* initially used was too small. No eigenvalues
* were computed.
* Probable cause: your machine has sloppy
* floating-point arithmetic.
* Cure: Increase the PARAMETER "FUDGE",
* recompile, and try again.
*
* Internal Parameters
* ===================
*
* RELFAC DOUBLE PRECISION, default = 2.0e0
* The relative tolerance. An interval (a,b] lies within
* "relative tolerance" if b-a < RELFAC*ulp*max(|a|,|b|),
* where "ulp" is the machine precision (distance from 1 to
* the next larger floating point number.)
*
* FUDGE DOUBLE PRECISION, default = 2
* A "fudge factor" to widen the Gershgorin intervals. Ideally,
* a value of 1 should work, but on machines with sloppy
* arithmetic, this needs to be larger. The default for
* publicly released versions should be large enough to handle
* the worst machine around. Note that this has no effect
* on accuracy of the solution.
*
* =====================================================================
*
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dstedc
USAGE:
work, iwork, info, d, e, z = NumRu::Lapack.dstedc( compz, d, e, z, [:lwork => lwork, :liwork => liwork, :usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTEDC( COMPZ, N, D, E, Z, LDZ, WORK, LWORK, IWORK, LIWORK, INFO )
* Purpose
* =======
*
* DSTEDC computes all eigenvalues and, optionally, eigenvectors of a
* symmetric tridiagonal matrix using the divide and conquer method.
* The eigenvectors of a full or band real symmetric matrix can also be
* found if DSYTRD or DSPTRD or DSBTRD has been used to reduce this
* matrix to tridiagonal form.
*
* This code 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. See DLAED3 for details.
*
* Arguments
* =========
*
* COMPZ (input) CHARACTER*1
* = 'N': Compute eigenvalues only.
* = 'I': Compute eigenvectors of tridiagonal matrix also.
* = 'V': Compute eigenvectors of original dense symmetric
* matrix also. On entry, Z contains the orthogonal
* matrix used to reduce the original matrix to
* tridiagonal form.
*
* N (input) INTEGER
* The dimension of the symmetric tridiagonal matrix. N >= 0.
*
* D (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the diagonal elements of the tridiagonal matrix.
* On exit, if INFO = 0, the eigenvalues in ascending order.
*
* E (input/output) DOUBLE PRECISION array, dimension (N-1)
* On entry, the subdiagonal elements of the tridiagonal matrix.
* On exit, E has been destroyed.
*
* Z (input/output) DOUBLE PRECISION array, dimension (LDZ,N)
* On entry, if COMPZ = 'V', then Z contains the orthogonal
* matrix used in the reduction to tridiagonal form.
* On exit, if INFO = 0, then if COMPZ = 'V', Z contains the
* orthonormal eigenvectors of the original symmetric matrix,
* and if COMPZ = 'I', Z contains the orthonormal eigenvectors
* of the symmetric tridiagonal matrix.
* If COMPZ = 'N', then Z is not referenced.
*
* LDZ (input) INTEGER
* The leading dimension of the array Z. LDZ >= 1.
* If eigenvectors are desired, then LDZ >= max(1,N).
*
* WORK (workspace/output) DOUBLE PRECISION array,
* dimension (LWORK)
* On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
* LWORK (input) INTEGER
* The dimension of the array WORK.
* If COMPZ = 'N' or N <= 1 then LWORK must be at least 1.
* If COMPZ = 'V' and N > 1 then LWORK must be at least
* ( 1 + 3*N + 2*N*lg N + 3*N**2 ),
* where lg( N ) = smallest integer k such
* that 2**k >= N.
* If COMPZ = 'I' and N > 1 then LWORK must be at least
* ( 1 + 4*N + N**2 ).
* Note that for COMPZ = 'I' or 'V', then if N is less than or
* equal to the minimum divide size, usually 25, then LWORK need
* only be max(1,2*(N-1)).
*
* 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 LIWORK.
*
* LIWORK (input) INTEGER
* The dimension of the array IWORK.
* If COMPZ = 'N' or N <= 1 then LIWORK must be at least 1.
* If COMPZ = 'V' and N > 1 then LIWORK must be at least
* ( 6 + 6*N + 5*N*lg N ).
* If COMPZ = 'I' and N > 1 then LIWORK must be at least
* ( 3 + 5*N ).
* Note that for COMPZ = 'I' or 'V', then if N is less than or
* equal to the minimum divide size, usually 25, then LIWORK
* need only be 1.
*
* 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: The algorithm failed to compute an eigenvalue while
* working on the submatrix lying in rows and columns
* INFO/(N+1) through mod(INFO,N+1).
*
* Further Details
* ===============
*
* Based on contributions by
* Jeff Rutter, Computer Science Division, University of California
* at Berkeley, USA
* Modified by Francoise Tisseur, University of Tennessee.
*
* =====================================================================
*
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dstegr
USAGE:
m, w, z, isuppz, work, iwork, info, d, e = NumRu::Lapack.dstegr( jobz, range, d, e, vl, vu, il, iu, abstol, [:lwork => lwork, :liwork => liwork, :usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTEGR( JOBZ, RANGE, N, D, E, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK, IWORK, LIWORK, INFO )
* Purpose
* =======
*
* DSTEGR computes selected eigenvalues and, optionally, eigenvectors
* of a real symmetric tridiagonal matrix T. Any such unreduced matrix has
* a well defined set of pairwise different real eigenvalues, the corresponding
* real eigenvectors are pairwise orthogonal.
*
* The spectrum may be computed either completely or partially by specifying
* either an interval (VL,VU] or a range of indices IL:IU for the desired
* eigenvalues.
*
* DSTEGR is a compatability wrapper around the improved DSTEMR routine.
* See DSTEMR for further details.
*
* One important change is that the ABSTOL parameter no longer provides any
* benefit and hence is no longer used.
*
* Note : DSTEGR and DSTEMR work only on machines which follow
* IEEE-754 floating-point standard in their handling of infinities and
* NaNs. Normal execution may create these exceptiona values and hence
* may abort due to a floating point exception in environments which
* do not conform to the IEEE-754 standard.
*
* 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.
*
* N (input) INTEGER
* The order of the matrix. N >= 0.
*
* D (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the N diagonal elements of the tridiagonal matrix
* T. On exit, D is overwritten.
*
* E (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the (N-1) subdiagonal elements of the tridiagonal
* matrix T in elements 1 to N-1 of E. E(N) need not be set on
* input, but is used internally as workspace.
* On exit, E is overwritten.
*
* 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.
* Not referenced if RANGE = 'A' or 'V'.
*
* ABSTOL (input) DOUBLE PRECISION
* Unused. Was the absolute error tolerance for the
* eigenvalues/eigenvectors in previous versions.
*
* 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', and if INFO = 0, then 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.
* Supplying N columns is always safe.
*
* LDZ (input) INTEGER
* The leading dimension of the array Z. LDZ >= 1, and if
* JOBZ = 'V', then 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 computed eigenvector
* is nonzero only in elements ISUPPZ( 2*i-1 ) through
* ISUPPZ( 2*i ). This is relevant in the case when the matrix
* is split. ISUPPZ is only accessed when JOBZ is 'V' and N > 0.
*
* WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK)
* On exit, if INFO = 0, WORK(1) returns the optimal
* (and minimal) LWORK.
*
* LWORK (input) INTEGER
* The dimension of the array WORK. LWORK >= max(1,18*N)
* if JOBZ = 'V', and LWORK >= max(1,12*N) if JOBZ = 'N'.
* 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. LIWORK >= max(1,10*N)
* if the eigenvectors are desired, and LIWORK >= max(1,8*N)
* if only the eigenvalues are to be computed.
* 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
* On exit, INFO
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: if INFO = 1X, internal error in DLARRE,
* if INFO = 2X, internal error in DLARRV.
* Here, the digit X = ABS( IINFO ) < 10, where IINFO is
* the nonzero error code returned by DLARRE or
* DLARRV, respectively.
*
* Further Details
* ===============
*
* Based on contributions by
* Inderjit Dhillon, IBM Almaden, USA
* Osni Marques, LBNL/NERSC, USA
* Christof Voemel, LBNL/NERSC, USA
*
* =====================================================================
*
* .. Local Scalars ..
LOGICAL TRYRAC
* ..
* .. External Subroutines ..
EXTERNAL DSTEMR
* ..
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dstein
USAGE:
z, ifail, info = NumRu::Lapack.dstein( d, e, w, iblock, isplit, [:usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTEIN( N, D, E, M, W, IBLOCK, ISPLIT, Z, LDZ, WORK, IWORK, IFAIL, INFO )
* Purpose
* =======
*
* DSTEIN computes the eigenvectors of a real symmetric tridiagonal
* matrix T corresponding to specified eigenvalues, using inverse
* iteration.
*
* The maximum number of iterations allowed for each eigenvector is
* specified by an internal parameter MAXITS (currently set to 5).
*
* Arguments
* =========
*
* N (input) INTEGER
* The order of the matrix. N >= 0.
*
* D (input) DOUBLE PRECISION array, dimension (N)
* The n diagonal elements of the tridiagonal matrix T.
*
* E (input) DOUBLE PRECISION array, dimension (N-1)
* The (n-1) subdiagonal elements of the tridiagonal matrix
* T, in elements 1 to N-1.
*
* M (input) INTEGER
* The number of eigenvectors to be found. 0 <= M <= N.
*
* W (input) DOUBLE PRECISION 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 DSTEBZ with ORDER = 'B' is expected here. )
*
* 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. ( The output array IBLOCK
* from DSTEBZ is expected here. )
*
* 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.
* ( The output array ISPLIT from DSTEBZ is expected here. )
*
* Z (output) DOUBLE PRECISION array, dimension (LDZ, M)
* The computed eigenvectors. The eigenvector associated
* with the eigenvalue W(i) is stored in the i-th column of
* Z. Any vector which fails to converge is set to its current
* iterate after MAXITS iterations.
*
* LDZ (input) INTEGER
* The leading dimension of the array Z. LDZ >= max(1,N).
*
* WORK (workspace) DOUBLE PRECISION array, dimension (5*N)
*
* IWORK (workspace) INTEGER array, dimension (N)
*
* IFAIL (output) INTEGER array, dimension (M)
* On normal exit, all elements of IFAIL are zero.
* If one or more eigenvectors fail to converge after
* MAXITS iterations, then their indices are stored in
* array IFAIL.
*
* INFO (output) INTEGER
* = 0: successful exit.
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: if INFO = i, then i eigenvectors failed to converge
* in MAXITS iterations. Their indices are stored in
* array IFAIL.
*
* Internal Parameters
* ===================
*
* MAXITS INTEGER, default = 5
* The maximum number of iterations performed.
*
* EXTRA INTEGER, default = 2
* The number of iterations performed after norm growth
* criterion is satisfied, should be at least 1.
*
* =====================================================================
*
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dstemr
USAGE:
m, w, z, isuppz, work, iwork, info, d, e, tryrac = NumRu::Lapack.dstemr( jobz, range, d, e, vl, vu, il, iu, nzc, tryrac, [:lwork => lwork, :liwork => liwork, :usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTEMR( JOBZ, RANGE, N, D, E, VL, VU, IL, IU, M, W, Z, LDZ, NZC, ISUPPZ, TRYRAC, WORK, LWORK, IWORK, LIWORK, INFO )
* Purpose
* =======
*
* DSTEMR computes selected eigenvalues and, optionally, eigenvectors
* of a real symmetric tridiagonal matrix T. Any such unreduced matrix has
* a well defined set of pairwise different real eigenvalues, the corresponding
* real eigenvectors are pairwise orthogonal.
*
* The spectrum may be computed either completely or partially by specifying
* either an interval (VL,VU] or a range of indices IL:IU for the desired
* eigenvalues.
*
* Depending on the number of desired eigenvalues, these are computed either
* by bisection or the dqds algorithm. Numerically orthogonal eigenvectors are
* computed by the use of various suitable L D L^T factorizations near clusters
* of close eigenvalues (referred to as RRRs, Relatively Robust
* Representations). An informal sketch of the algorithm 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.
*
* For more details, see:
* - 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.
*
* Further Details
* 1.DSTEMR works only on machines which follow IEEE-754
* floating-point standard in their handling of infinities and NaNs.
* This permits the use of efficient inner loops avoiding a check for
* zero divisors.
*
* 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.
*
* N (input) INTEGER
* The order of the matrix. N >= 0.
*
* D (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the N diagonal elements of the tridiagonal matrix
* T. On exit, D is overwritten.
*
* E (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the (N-1) subdiagonal elements of the tridiagonal
* matrix T in elements 1 to N-1 of E. E(N) need not be set on
* input, but is used internally as workspace.
* On exit, E is overwritten.
*
* 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.
* Not referenced if RANGE = 'A' or 'V'.
*
* 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', and if INFO = 0, then 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 can be computed with a workspace
* query by setting NZC = -1, see below.
*
* LDZ (input) INTEGER
* The leading dimension of the array Z. LDZ >= 1, and if
* JOBZ = 'V', then LDZ >= max(1,N).
*
* NZC (input) INTEGER
* The number of eigenvectors to be held in the array Z.
* If RANGE = 'A', then NZC >= max(1,N).
* If RANGE = 'V', then NZC >= the number of eigenvalues in (VL,VU].
* If RANGE = 'I', then NZC >= IU-IL+1.
* If NZC = -1, then a workspace query is assumed; the
* routine calculates the number of columns of the array Z that
* are needed to hold the eigenvectors.
* This value is returned as the first entry of the Z array, and
* no error message related to NZC is issued by XERBLA.
*
* 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 computed eigenvector
* is nonzero only in elements ISUPPZ( 2*i-1 ) through
* ISUPPZ( 2*i ). This is relevant in the case when the matrix
* is split. ISUPPZ is only accessed when JOBZ is 'V' and N > 0.
*
* TRYRAC (input/output) LOGICAL
* If TRYRAC.EQ..TRUE., indicates that the code should check whether
* the tridiagonal matrix defines its eigenvalues to high relative
* accuracy. If so, the code uses relative-accuracy preserving
* algorithms that might be (a bit) slower depending on the matrix.
* If the matrix does not define its eigenvalues to high relative
* accuracy, the code can uses possibly faster algorithms.
* If TRYRAC.EQ..FALSE., the code is not required to guarantee
* relatively accurate eigenvalues and can use the fastest possible
* techniques.
* On exit, a .TRUE. TRYRAC will be set to .FALSE. if the matrix
* does not define its eigenvalues to high relative accuracy.
*
* WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK)
* On exit, if INFO = 0, WORK(1) returns the optimal
* (and minimal) LWORK.
*
* LWORK (input) INTEGER
* The dimension of the array WORK. LWORK >= max(1,18*N)
* if JOBZ = 'V', and LWORK >= max(1,12*N) if JOBZ = 'N'.
* 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. LIWORK >= max(1,10*N)
* if the eigenvectors are desired, and LIWORK >= max(1,8*N)
* if only the eigenvalues are to be computed.
* 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
* On exit, INFO
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: if INFO = 1X, internal error in DLARRE,
* if INFO = 2X, internal error in DLARRV.
* Here, the digit X = ABS( IINFO ) < 10, where IINFO is
* the nonzero error code returned by DLARRE or
* DLARRV, respectively.
*
*
* Further Details
* ===============
*
* Based on contributions by
* Beresford Parlett, University of California, Berkeley, USA
* Jim Demmel, University of California, Berkeley, USA
* Inderjit Dhillon, University of Texas, Austin, USA
* Osni Marques, LBNL/NERSC, USA
* Christof Voemel, University of California, Berkeley, USA
*
* =====================================================================
*
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dsteqr
USAGE:
info, d, e, z = NumRu::Lapack.dsteqr( compz, d, e, z, [:usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTEQR( COMPZ, N, D, E, Z, LDZ, WORK, INFO )
* Purpose
* =======
*
* DSTEQR computes all eigenvalues and, optionally, eigenvectors of a
* symmetric tridiagonal matrix using the implicit QL or QR method.
* The eigenvectors of a full or band symmetric matrix can also be found
* if DSYTRD or DSPTRD or DSBTRD has been used to reduce this matrix to
* tridiagonal form.
*
* Arguments
* =========
*
* COMPZ (input) CHARACTER*1
* = 'N': Compute eigenvalues only.
* = 'V': Compute eigenvalues and eigenvectors of the original
* symmetric matrix. On entry, Z must contain the
* orthogonal matrix used to reduce the original matrix
* to tridiagonal form.
* = 'I': Compute eigenvalues and eigenvectors of the
* tridiagonal matrix. Z is initialized to the identity
* matrix.
*
* N (input) INTEGER
* The order of the matrix. N >= 0.
*
* D (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the diagonal elements of the tridiagonal matrix.
* On exit, if INFO = 0, the eigenvalues in ascending order.
*
* E (input/output) DOUBLE PRECISION array, dimension (N-1)
* On entry, the (n-1) subdiagonal elements of the tridiagonal
* matrix.
* On exit, E has been destroyed.
*
* Z (input/output) DOUBLE PRECISION array, dimension (LDZ, N)
* On entry, if COMPZ = 'V', then Z contains the orthogonal
* matrix used in the reduction to tridiagonal form.
* On exit, if INFO = 0, then if COMPZ = 'V', Z contains the
* orthonormal eigenvectors of the original symmetric matrix,
* and if COMPZ = 'I', Z contains the orthonormal eigenvectors
* of the symmetric tridiagonal matrix.
* If COMPZ = 'N', then Z is not referenced.
*
* LDZ (input) INTEGER
* The leading dimension of the array Z. LDZ >= 1, and if
* eigenvectors are desired, then LDZ >= max(1,N).
*
* WORK (workspace) DOUBLE PRECISION array, dimension (max(1,2*N-2))
* If COMPZ = 'N', then WORK is not referenced.
*
* INFO (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: the algorithm has failed to find all the eigenvalues in
* a total of 30*N iterations; if INFO = i, then i
* elements of E have not converged to zero; on exit, D
* and E contain the elements of a symmetric tridiagonal
* matrix which is orthogonally similar to the original
* matrix.
*
* =====================================================================
*
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dsterf
USAGE:
info, d, e = NumRu::Lapack.dsterf( d, e, [:usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTERF( N, D, E, INFO )
* Purpose
* =======
*
* DSTERF computes all eigenvalues of a symmetric tridiagonal matrix
* using the Pal-Walker-Kahan variant of the QL or QR algorithm.
*
* Arguments
* =========
*
* N (input) INTEGER
* The order of the matrix. N >= 0.
*
* D (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the n diagonal elements of the tridiagonal matrix.
* On exit, if INFO = 0, the eigenvalues in ascending order.
*
* E (input/output) DOUBLE PRECISION array, dimension (N-1)
* On entry, the (n-1) subdiagonal elements of the tridiagonal
* matrix.
* On exit, E has been destroyed.
*
* INFO (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: the algorithm failed to find all of the eigenvalues in
* a total of 30*N iterations; if INFO = i, then i
* elements of E have not converged to zero.
*
* =====================================================================
*
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dstev
USAGE:
z, info, d, e = NumRu::Lapack.dstev( jobz, d, e, [:usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTEV( JOBZ, N, D, E, Z, LDZ, WORK, INFO )
* Purpose
* =======
*
* DSTEV computes all eigenvalues and, optionally, eigenvectors of a
* real symmetric tridiagonal matrix A.
*
* Arguments
* =========
*
* JOBZ (input) CHARACTER*1
* = 'N': Compute eigenvalues only;
* = 'V': Compute eigenvalues and eigenvectors.
*
* N (input) INTEGER
* The order of the matrix. N >= 0.
*
* D (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the n diagonal elements of the tridiagonal matrix
* A.
* On exit, if INFO = 0, the eigenvalues in ascending order.
*
* E (input/output) DOUBLE PRECISION array, dimension (N-1)
* On entry, the (n-1) subdiagonal elements of the tridiagonal
* matrix A, stored in elements 1 to N-1 of E.
* On exit, the contents of E are destroyed.
*
* Z (output) DOUBLE PRECISION array, dimension (LDZ, N)
* If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal
* eigenvectors of the matrix A, with the i-th column of Z
* holding the eigenvector associated with D(i).
* If JOBZ = 'N', then Z is not referenced.
*
* LDZ (input) INTEGER
* The leading dimension of the array Z. LDZ >= 1, and if
* JOBZ = 'V', LDZ >= max(1,N).
*
* WORK (workspace) DOUBLE PRECISION array, dimension (max(1,2*N-2))
* If JOBZ = 'N', WORK is not referenced.
*
* INFO (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: if INFO = i, the algorithm failed to converge; i
* off-diagonal elements of E did not converge to zero.
*
* =====================================================================
*
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dstevd
USAGE:
z, work, iwork, info, d, e = NumRu::Lapack.dstevd( jobz, d, e, [:lwork => lwork, :liwork => liwork, :usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTEVD( JOBZ, N, D, E, Z, LDZ, WORK, LWORK, IWORK, LIWORK, INFO )
* Purpose
* =======
*
* DSTEVD computes all eigenvalues and, optionally, eigenvectors of a
* real symmetric tridiagonal matrix. 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
* =========
*
* JOBZ (input) CHARACTER*1
* = 'N': Compute eigenvalues only;
* = 'V': Compute eigenvalues and eigenvectors.
*
* N (input) INTEGER
* The order of the matrix. N >= 0.
*
* D (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the n diagonal elements of the tridiagonal matrix
* A.
* On exit, if INFO = 0, the eigenvalues in ascending order.
*
* E (input/output) DOUBLE PRECISION array, dimension (N-1)
* On entry, the (n-1) subdiagonal elements of the tridiagonal
* matrix A, stored in elements 1 to N-1 of E.
* On exit, the contents of E are destroyed.
*
* Z (output) DOUBLE PRECISION array, dimension (LDZ, N)
* If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal
* eigenvectors of the matrix A, with the i-th column of Z
* holding the eigenvector associated with D(i).
* If JOBZ = 'N', then Z is not referenced.
*
* LDZ (input) INTEGER
* The leading dimension of the array Z. LDZ >= 1, and if
* JOBZ = 'V', LDZ >= max(1,N).
*
* WORK (workspace/output) DOUBLE PRECISION array,
* dimension (LWORK)
* On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
* LWORK (input) INTEGER
* The dimension of the array WORK.
* If JOBZ = 'N' or N <= 1 then LWORK must be at least 1.
* If JOBZ = 'V' and N > 1 then LWORK must be at least
* ( 1 + 4*N + N**2 ).
*
* 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 (workspace/output) INTEGER array, dimension (MAX(1,LIWORK))
* On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.
*
* LIWORK (input) INTEGER
* The dimension of the array IWORK.
* If JOBZ = 'N' or N <= 1 then LIWORK must be at least 1.
* If JOBZ = 'V' and N > 1 then LIWORK must be at least 3+5*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 (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: if INFO = i, the algorithm failed to converge; i
* off-diagonal elements of E did not converge to zero.
*
* =====================================================================
*
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dstevr
USAGE:
m, w, z, isuppz, work, iwork, info, d, e = NumRu::Lapack.dstevr( jobz, range, d, e, vl, vu, il, iu, abstol, [:lwork => lwork, :liwork => liwork, :usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTEVR( JOBZ, RANGE, N, D, E, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK, IWORK, LIWORK, INFO )
* Purpose
* =======
*
* DSTEVR computes selected eigenvalues and, optionally, eigenvectors
* of a real symmetric tridiagonal matrix T. Eigenvalues and
* eigenvectors can be selected by specifying either a range of values
* or a range of indices for the desired eigenvalues.
*
* Whenever possible, DSTEVR 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 the i-th
* unreduced block of T,
* (a) Compute T - sigma_i = L_i D_i L_i^T, such that L_i D_i L_i^T
* is a relatively robust representation,
* (b) Compute the eigenvalues, lambda_j, of L_i D_i L_i^T to high
* relative accuracy by the dqds algorithm,
* (c) If there is a cluster of close eigenvalues, "choose" sigma_i
* close to the cluster, and go to step (a),
* (d) Given the approximate eigenvalue lambda_j of L_i D_i L_i^T,
* compute the corresponding eigenvector by forming a
* rank-revealing twisted factorization.
* The desired accuracy of the output can be specified by the input
* parameter ABSTOL.
*
* For more details, see "A new O(n^2) algorithm for the symmetric
* tridiagonal eigenvalue/eigenvector problem", by Inderjit Dhillon,
* Computer Science Division Technical Report No. UCB//CSD-97-971,
* UC Berkeley, May 1997.
*
*
* Note 1 : DSTEVR calls DSTEMR when the full spectrum is requested
* on machines which conform to the ieee-754 floating point standard.
* DSTEVR calls DSTEBZ and DSTEIN 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
*
* N (input) INTEGER
* The order of the matrix. N >= 0.
*
* D (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the n diagonal elements of the tridiagonal matrix
* A.
* On exit, D may be multiplied by a constant factor chosen
* to avoid over/underflow in computing the eigenvalues.
*
* E (input/output) DOUBLE PRECISION array, dimension (max(1,N-1))
* On entry, the (n-1) subdiagonal elements of the tridiagonal
* matrix A in elements 1 to N-1 of E.
* On exit, E may be multiplied by a constant factor chosen
* to avoid over/underflow in computing the eigenvalues.
*
* 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).
* 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 ).
********** 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 (and
* minimal) LWORK.
*
* LWORK (input) INTEGER
* The dimension of the array WORK. LWORK >= max(1,20*N).
*
* 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 (workspace/output) INTEGER array, dimension (MAX(1,LIWORK))
* On exit, if INFO = 0, IWORK(1) returns the optimal (and
* minimal) LIWORK.
*
* 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 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 (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
*
* =====================================================================
*
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dstevx
USAGE:
m, w, z, ifail, info, d, e = NumRu::Lapack.dstevx( jobz, range, d, e, vl, vu, il, iu, abstol, [:usage => usage, :help => help])
FORTRAN MANUAL
SUBROUTINE DSTEVX( JOBZ, RANGE, N, D, E, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, WORK, IWORK, IFAIL, INFO )
* Purpose
* =======
*
* DSTEVX computes selected eigenvalues and, optionally, eigenvectors
* of a real symmetric tridiagonal matrix A. Eigenvalues and
* eigenvectors can be selected by specifying either a range of values
* or a range of indices for the desired eigenvalues.
*
* 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.
*
* N (input) INTEGER
* The order of the matrix. N >= 0.
*
* D (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the n diagonal elements of the tridiagonal matrix
* A.
* On exit, D may be multiplied by a constant factor chosen
* to avoid over/underflow in computing the eigenvalues.
*
* E (input/output) DOUBLE PRECISION array, dimension (max(1,N-1))
* On entry, the (n-1) subdiagonal elements of the tridiagonal
* matrix A in elements 1 to N-1 of E.
* On exit, E may be multiplied by a constant factor chosen
* to avoid over/underflow in computing the eigenvalues.
*
* 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.
*
* Eigenvalues will be computed most accurately when ABSTOL is
* set to twice the underflow threshold 2*DLAMCH('S'), not zero.
* If this routine returns with INFO>0, indicating that some
* eigenvectors did not converge, try setting ABSTOL to
* 2*DLAMCH('S').
*
* See "Computing Small Singular Values of Bidiagonal Matrices
* with Guaranteed High Relative Accuracy," by Demmel and
* Kahan, LAPACK Working Note #3.
*
* 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 an eigenvector fails to converge (INFO > 0), then that
* column of Z contains the latest approximation to the
* eigenvector, and the index of the eigenvector is returned
* in IFAIL. 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).
*
* WORK (workspace) DOUBLE PRECISION array, dimension (5*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: if INFO = i, then i eigenvectors failed to converge.
* Their indices are stored in array IFAIL.
*
* =====================================================================
*
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