LAPACK  3.6.1 LAPACK: Linear Algebra PACKage
 subroutine dposvx ( character FACT, character UPLO, integer N, integer NRHS, double precision, dimension( lda, * ) A, integer LDA, double precision, dimension( ldaf, * ) AF, integer LDAF, character EQUED, double precision, dimension( * ) S, double precision, dimension( ldb, * ) B, integer LDB, double precision, dimension( ldx, * ) X, integer LDX, double precision RCOND, double precision, dimension( * ) FERR, double precision, dimension( * ) BERR, double precision, dimension( * ) WORK, integer, dimension( * ) IWORK, integer INFO )

DPOSVX computes the solution to system of linear equations A * X = B for PO matrices

Purpose:
``` DPOSVX uses the Cholesky factorization A = U**T*U or A = L*L**T to
compute the solution to a real system of linear equations
A * X = B,
where A is an N-by-N symmetric positive definite matrix and X and B
are N-by-NRHS matrices.

Error bounds on the solution and a condition estimate are also
provided.```
Description:
``` The following steps are performed:

1. If FACT = 'E', real scaling factors are computed to equilibrate
the system:
diag(S) * A * diag(S) * inv(diag(S)) * X = diag(S) * B
Whether or not the system will be equilibrated depends on the
scaling of the matrix A, but if equilibration is used, A is
overwritten by diag(S)*A*diag(S) and B by diag(S)*B.

2. If FACT = 'N' or 'E', the Cholesky decomposition is used to
factor the matrix A (after equilibration if FACT = 'E') as
A = U**T* U,  if UPLO = 'U', or
A = L * L**T,  if UPLO = 'L',
where U is an upper triangular matrix and L is a lower triangular
matrix.

3. If the leading i-by-i principal minor is not positive definite,
then the routine returns with INFO = i. Otherwise, the factored
form of A is used to estimate the condition number of the matrix
A.  If the reciprocal of the condition number is less than machine
precision, INFO = N+1 is returned as a warning, but the routine
still goes on to solve for X and compute error bounds as
described below.

4. The system of equations is solved for X using the factored form
of A.

5. Iterative refinement is applied to improve the computed solution
matrix and calculate error bounds and backward error estimates
for it.

6. If equilibration was used, the matrix X is premultiplied by
diag(S) so that it solves the original system before
equilibration.```
Parameters
 [in] FACT ``` FACT is CHARACTER*1 Specifies whether or not the factored form of the matrix A is supplied on entry, and if not, whether the matrix A should be equilibrated before it is factored. = 'F': On entry, AF contains the factored form of A. If EQUED = 'Y', the matrix A has been equilibrated with scaling factors given by S. A and AF will not be modified. = 'N': The matrix A will be copied to AF and factored. = 'E': The matrix A will be equilibrated if necessary, then copied to AF and factored.``` [in] UPLO ``` UPLO is CHARACTER*1 = 'U': Upper triangle of A is stored; = 'L': Lower triangle of A is stored.``` [in] N ``` N is INTEGER The number of linear equations, i.e., the order of the matrix A. N >= 0.``` [in] NRHS ``` NRHS is INTEGER The number of right hand sides, i.e., the number of columns of the matrices B and X. NRHS >= 0.``` [in,out] A ``` A is DOUBLE PRECISION array, dimension (LDA,N) On entry, the symmetric matrix A, except if FACT = 'F' and EQUED = 'Y', then A must contain the equilibrated matrix diag(S)*A*diag(S). If UPLO = 'U', the leading N-by-N upper triangular part of A contains the upper triangular part of the matrix A, and the strictly lower triangular part of A is not referenced. If UPLO = 'L', the leading N-by-N lower triangular part of A contains the lower triangular part of the matrix A, and the strictly upper triangular part of A is not referenced. A is not modified if FACT = 'F' or 'N', or if FACT = 'E' and EQUED = 'N' on exit. On exit, if FACT = 'E' and EQUED = 'Y', A is overwritten by diag(S)*A*diag(S).``` [in] LDA ``` LDA is INTEGER The leading dimension of the array A. LDA >= max(1,N).``` [in,out] AF ``` AF is DOUBLE PRECISION array, dimension (LDAF,N) If FACT = 'F', then AF is an input argument and on entry contains the triangular factor U or L from the Cholesky factorization A = U**T*U or A = L*L**T, in the same storage format as A. If EQUED .ne. 'N', then AF is the factored form of the equilibrated matrix diag(S)*A*diag(S). If FACT = 'N', then AF is an output argument and on exit returns the triangular factor U or L from the Cholesky factorization A = U**T*U or A = L*L**T of the original matrix A. If FACT = 'E', then AF is an output argument and on exit returns the triangular factor U or L from the Cholesky factorization A = U**T*U or A = L*L**T of the equilibrated matrix A (see the description of A for the form of the equilibrated matrix).``` [in] LDAF ``` LDAF is INTEGER The leading dimension of the array AF. LDAF >= max(1,N).``` [in,out] EQUED ``` EQUED is CHARACTER*1 Specifies the form of equilibration that was done. = 'N': No equilibration (always true if FACT = 'N'). = 'Y': Equilibration was done, i.e., A has been replaced by diag(S) * A * diag(S). EQUED is an input argument if FACT = 'F'; otherwise, it is an output argument.``` [in,out] S ``` S is DOUBLE PRECISION array, dimension (N) The scale factors for A; not accessed if EQUED = 'N'. S is an input argument if FACT = 'F'; otherwise, S is an output argument. If FACT = 'F' and EQUED = 'Y', each element of S must be positive.``` [in,out] B ``` B is DOUBLE PRECISION array, dimension (LDB,NRHS) On entry, the N-by-NRHS right hand side matrix B. On exit, if EQUED = 'N', B is not modified; if EQUED = 'Y', B is overwritten by diag(S) * B.``` [in] LDB ``` LDB is INTEGER The leading dimension of the array B. LDB >= max(1,N).``` [out] X ``` X is DOUBLE PRECISION array, dimension (LDX,NRHS) If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X to the original system of equations. Note that if EQUED = 'Y', A and B are modified on exit, and the solution to the equilibrated system is inv(diag(S))*X.``` [in] LDX ``` LDX is INTEGER The leading dimension of the array X. LDX >= max(1,N).``` [out] RCOND ``` RCOND is DOUBLE PRECISION The estimate of the reciprocal condition number of the matrix A after equilibration (if done). If RCOND is less than the machine precision (in particular, if RCOND = 0), the matrix is singular to working precision. This condition is indicated by a return code of INFO > 0.``` [out] FERR ``` FERR is DOUBLE PRECISION array, dimension (NRHS) The estimated forward error bound for each solution vector X(j) (the j-th column of the solution matrix X). If XTRUE is the true solution corresponding to X(j), FERR(j) is an estimated upper bound for the magnitude of the largest element in (X(j) - XTRUE) divided by the magnitude of the largest element in X(j). The estimate is as reliable as the estimate for RCOND, and is almost always a slight overestimate of the true error.``` [out] BERR ``` BERR is DOUBLE PRECISION array, dimension (NRHS) The componentwise relative backward error of each solution vector X(j) (i.e., the smallest relative change in any element of A or B that makes X(j) an exact solution).``` [out] WORK ` WORK is DOUBLE PRECISION array, dimension (3*N)` [out] IWORK ` IWORK is INTEGER array, dimension (N)` [out] INFO ``` INFO is INTEGER = 0: successful exit < 0: if INFO = -i, the i-th argument had an illegal value > 0: if INFO = i, and i is <= N: the leading minor of order i of A is not positive definite, so the factorization could not be completed, and the solution has not been computed. RCOND = 0 is returned. = N+1: U is nonsingular, but RCOND is less than machine precision, meaning that the matrix is singular to working precision. Nevertheless, the solution and error bounds are computed because there are a number of situations where the computed solution can be more accurate than the value of RCOND would suggest.```
Date
April 2012

Definition at line 309 of file dposvx.f.

309 *
310 * -- LAPACK driver routine (version 3.4.1) --
311 * -- LAPACK is a software package provided by Univ. of Tennessee, --
312 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
313 * April 2012
314 *
315 * .. Scalar Arguments ..
316  CHARACTER equed, fact, uplo
317  INTEGER info, lda, ldaf, ldb, ldx, n, nrhs
318  DOUBLE PRECISION rcond
319 * ..
320 * .. Array Arguments ..
321  INTEGER iwork( * )
322  DOUBLE PRECISION a( lda, * ), af( ldaf, * ), b( ldb, * ),
323  \$ berr( * ), ferr( * ), s( * ), work( * ),
324  \$ x( ldx, * )
325 * ..
326 *
327 * =====================================================================
328 *
329 * .. Parameters ..
330  DOUBLE PRECISION zero, one
331  parameter ( zero = 0.0d+0, one = 1.0d+0 )
332 * ..
333 * .. Local Scalars ..
334  LOGICAL equil, nofact, rcequ
335  INTEGER i, infequ, j
336  DOUBLE PRECISION amax, anorm, bignum, scond, smax, smin, smlnum
337 * ..
338 * .. External Functions ..
339  LOGICAL lsame
340  DOUBLE PRECISION dlamch, dlansy
341  EXTERNAL lsame, dlamch, dlansy
342 * ..
343 * .. External Subroutines ..
344  EXTERNAL dlacpy, dlaqsy, dpocon, dpoequ, dporfs, dpotrf,
345  \$ dpotrs, xerbla
346 * ..
347 * .. Intrinsic Functions ..
348  INTRINSIC max, min
349 * ..
350 * .. Executable Statements ..
351 *
352  info = 0
353  nofact = lsame( fact, 'N' )
354  equil = lsame( fact, 'E' )
355  IF( nofact .OR. equil ) THEN
356  equed = 'N'
357  rcequ = .false.
358  ELSE
359  rcequ = lsame( equed, 'Y' )
360  smlnum = dlamch( 'Safe minimum' )
361  bignum = one / smlnum
362  END IF
363 *
364 * Test the input parameters.
365 *
366  IF( .NOT.nofact .AND. .NOT.equil .AND. .NOT.lsame( fact, 'F' ) )
367  \$ THEN
368  info = -1
369  ELSE IF( .NOT.lsame( uplo, 'U' ) .AND. .NOT.lsame( uplo, 'L' ) )
370  \$ THEN
371  info = -2
372  ELSE IF( n.LT.0 ) THEN
373  info = -3
374  ELSE IF( nrhs.LT.0 ) THEN
375  info = -4
376  ELSE IF( lda.LT.max( 1, n ) ) THEN
377  info = -6
378  ELSE IF( ldaf.LT.max( 1, n ) ) THEN
379  info = -8
380  ELSE IF( lsame( fact, 'F' ) .AND. .NOT.
381  \$ ( rcequ .OR. lsame( equed, 'N' ) ) ) THEN
382  info = -9
383  ELSE
384  IF( rcequ ) THEN
385  smin = bignum
386  smax = zero
387  DO 10 j = 1, n
388  smin = min( smin, s( j ) )
389  smax = max( smax, s( j ) )
390  10 CONTINUE
391  IF( smin.LE.zero ) THEN
392  info = -10
393  ELSE IF( n.GT.0 ) THEN
394  scond = max( smin, smlnum ) / min( smax, bignum )
395  ELSE
396  scond = one
397  END IF
398  END IF
399  IF( info.EQ.0 ) THEN
400  IF( ldb.LT.max( 1, n ) ) THEN
401  info = -12
402  ELSE IF( ldx.LT.max( 1, n ) ) THEN
403  info = -14
404  END IF
405  END IF
406  END IF
407 *
408  IF( info.NE.0 ) THEN
409  CALL xerbla( 'DPOSVX', -info )
410  RETURN
411  END IF
412 *
413  IF( equil ) THEN
414 *
415 * Compute row and column scalings to equilibrate the matrix A.
416 *
417  CALL dpoequ( n, a, lda, s, scond, amax, infequ )
418  IF( infequ.EQ.0 ) THEN
419 *
420 * Equilibrate the matrix.
421 *
422  CALL dlaqsy( uplo, n, a, lda, s, scond, amax, equed )
423  rcequ = lsame( equed, 'Y' )
424  END IF
425  END IF
426 *
427 * Scale the right hand side.
428 *
429  IF( rcequ ) THEN
430  DO 30 j = 1, nrhs
431  DO 20 i = 1, n
432  b( i, j ) = s( i )*b( i, j )
433  20 CONTINUE
434  30 CONTINUE
435  END IF
436 *
437  IF( nofact .OR. equil ) THEN
438 *
439 * Compute the Cholesky factorization A = U**T *U or A = L*L**T.
440 *
441  CALL dlacpy( uplo, n, n, a, lda, af, ldaf )
442  CALL dpotrf( uplo, n, af, ldaf, info )
443 *
444 * Return if INFO is non-zero.
445 *
446  IF( info.GT.0 )THEN
447  rcond = zero
448  RETURN
449  END IF
450  END IF
451 *
452 * Compute the norm of the matrix A.
453 *
454  anorm = dlansy( '1', uplo, n, a, lda, work )
455 *
456 * Compute the reciprocal of the condition number of A.
457 *
458  CALL dpocon( uplo, n, af, ldaf, anorm, rcond, work, iwork, info )
459 *
460 * Compute the solution matrix X.
461 *
462  CALL dlacpy( 'Full', n, nrhs, b, ldb, x, ldx )
463  CALL dpotrs( uplo, n, nrhs, af, ldaf, x, ldx, info )
464 *
465 * Use iterative refinement to improve the computed solution and
466 * compute error bounds and backward error estimates for it.
467 *
468  CALL dporfs( uplo, n, nrhs, a, lda, af, ldaf, b, ldb, x, ldx,
469  \$ ferr, berr, work, iwork, info )
470 *
471 * Transform the solution matrix X to a solution of the original
472 * system.
473 *
474  IF( rcequ ) THEN
475  DO 50 j = 1, nrhs
476  DO 40 i = 1, n
477  x( i, j ) = s( i )*x( i, j )
478  40 CONTINUE
479  50 CONTINUE
480  DO 60 j = 1, nrhs
481  ferr( j ) = ferr( j ) / scond
482  60 CONTINUE
483  END IF
484 *
485 * Set INFO = N+1 if the matrix is singular to working precision.
486 *
487  IF( rcond.LT.dlamch( 'Epsilon' ) )
488  \$ info = n + 1
489 *
490  RETURN
491 *
492 * End of DPOSVX
493 *
double precision function dlansy(NORM, UPLO, N, A, LDA, WORK)
DLANSY returns the value of the 1-norm, or the Frobenius norm, or the infinity norm, or the element of largest absolute value of a real symmetric matrix.
Definition: dlansy.f:124
subroutine dpotrf(UPLO, N, A, LDA, INFO)
DPOTRF
Definition: dpotrf.f:109
double precision function dlamch(CMACH)
DLAMCH
Definition: dlamch.f:65
subroutine dpocon(UPLO, N, A, LDA, ANORM, RCOND, WORK, IWORK, INFO)
DPOCON
Definition: dpocon.f:123
subroutine dlacpy(UPLO, M, N, A, LDA, B, LDB)
DLACPY copies all or part of one two-dimensional array to another.
Definition: dlacpy.f:105
subroutine xerbla(SRNAME, INFO)
XERBLA
Definition: xerbla.f:62
subroutine dlaqsy(UPLO, N, A, LDA, S, SCOND, AMAX, EQUED)
DLAQSY scales a symmetric/Hermitian matrix, using scaling factors computed by spoequ.
Definition: dlaqsy.f:135
subroutine dpotrs(UPLO, N, NRHS, A, LDA, B, LDB, INFO)
DPOTRS
Definition: dpotrs.f:112
subroutine dporfs(UPLO, N, NRHS, A, LDA, AF, LDAF, B, LDB, X, LDX, FERR, BERR, WORK, IWORK, INFO)
DPORFS
Definition: dporfs.f:185
subroutine dpoequ(N, A, LDA, S, SCOND, AMAX, INFO)
DPOEQU
Definition: dpoequ.f:114
logical function lsame(CA, CB)
LSAME
Definition: lsame.f:55

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