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dppsvx


 NAME
      DPPSVX - use 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,

 SYNOPSIS
      SUBROUTINE DPPSVX( FACT, UPLO, N, NRHS, AP, AFP, EQUED, S,
                         B, LDB, X, LDX, RCOND, FERR, BERR, WORK,
                         IWORK, INFO )

          CHARACTER      EQUED, FACT, UPLO

          INTEGER        INFO, LDB, LDX, N, NRHS

          DOUBLE         PRECISION RCOND

          INTEGER        IWORK( * )

          DOUBLE         PRECISION AFP( * ), AP( * ), B( LDB, * ),
                         BERR( * ), FERR( * ), S( * ), WORK( * ),
                         X( LDX, * )

 PURPOSE
      DPPSVX 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 defin-
      ite matrix stored in packed format 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. 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, steps 4-6 are skipped.

      4. The system of equations is solved for X using the fac-
      tored 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.

 ARGUMENTS
      FACT    (input) 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, AFP contains the fac-
              tored form of A.  If EQUED = 'Y', the matrix A has
              been equilibrated with scaling factors given by S.
              AP and AFP will not be modified.  = 'N':  The matrix
              A will be copied to AFP and factored.
              = 'E':  The matrix A will be equilibrated if neces-
              sary, then copied to AFP and factored.

      UPLO    (input) CHARACTER*1
              = 'U':  Upper triangle of A is stored;
              = 'L':  Lower triangle of A is stored.

      N       (input) INTEGER
              The number of linear equations, i.e., the order of
              the matrix A.  N >= 0.

      NRHS    (input) INTEGER
              The number of right hand sides, i.e., the number of
              columns of the matrices B and X.  NRHS >= 0.

 (N*(N+1)/2)
      AP      (input/output) DOUBLE PRECISION array, dimension
              On entry, the upper or lower triangle of the sym-
              metric matrix A, packed columnwise in a linear
              array, except if FACT = 'F' and EQUED = 'Y', then A
              must contain the equilibrated matrix
              diag(S)*A*diag(S).  The j-th column of A is stored
              in the array AP as follows: if UPLO = 'U', AP(i +
              (j-1)*j/2) = A(i,j) for 1<=i<=j; if UPLO = 'L', AP(i
              + (j-1)*(2n-j)/2) = A(i,j) for j<=i<=n.  See below
              for further details.  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).

      AFP     (input or output) DOUBLE PRECISION array, dimension
              (N*(N+1)/2) If FACT = 'F', then AFP is an input
              argument and on entry contains the triangular factor
              U or L from the Cholesky factorization A = U'*U or A
              = L*L', in the same storage format as A.  If EQUED
              .ne. 'N', then AFP is the factored form of the
              equilibrated matrix A.

              If FACT = 'N', then AFP is an output argument and on
              exit returns the triangular factor U or L from the
              Cholesky factorization A = U'*U or A = L*L' of the
              original matrix A.

              If FACT = 'E', then AFP is an output argument and on
              exit returns the triangular factor U or L from the
              Cholesky factorization A = U'*U or A = L*L' of the
              equilibrated matrix A (see the description of AP for
              the form of the equilibrated matrix).

      EQUED   (input/output) 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 variable if FACT = 'F'; otherwise, it is an
              output variable.

      S       (input/output) DOUBLE PRECISION array, dimension (N)
              The scale factors for A; not accessed if EQUED =
              'N'.  S is an input variable if FACT = 'F'; other-
              wise, S is an output variable.  If FACT = 'F' and
              EQUED = 'Y', each element of S must be positive.

 (LDB,NRHS)

      B       (input/output) DOUBLE PRECISION array, dimension
              On entry, the N-by-NRHS righthand side matrix B.  On
              exit, if EQUED = 'N', B is not modified; if EQUED =
              'Y', B is overwritten by diag(S) * B.

      LDB     (input) INTEGER
              The leading dimension of the array B.  LDB >=
              max(1,N).

      X       (output) DOUBLE PRECISION array, dimension (LDX,NRHS)
              If INFO = 0, 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.

      LDX     (input) INTEGER
              The leading dimension of the array X.  LDX >=
              max(1,N).

      RCOND   (output) 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 partic-
              ular, if RCOND = 0), the matrix is singular to work-
              ing precision.  This condition is indicated by a
              return code of INFO > 0, and the solution and error
              bounds are not computed.

      FERR    (output) DOUBLE PRECISION array, dimension (NRHS)
              The estimated forward error bounds for each solution
              vector X(j) (the j-th column of the solution matrix
              X).  If XTRUE is the true solution, FERR(j) bounds
              the magnitude of the largest entry in (X(j) - XTRUE)
              divided by the magnitude of the largest entry in
              X(j).  The quality of the error bound depends on the
              quality of the estimate of norm(inv(A)) computed in
              the code; if the estimate of norm(inv(A)) is accu-
              rate, the error bound is guaranteed.

      BERR    (output) DOUBLE PRECISION array, dimension (NRHS)
              The componentwise relative backward error of each
              solution vector X(j) (i.e., the smallest relative
              change in any entry of A or B that makes X(j) an
              exact solution).

      WORK    (workspace) DOUBLE PRECISION array, dimension (3*N)

      IWORK   (workspace) INTEGER array, dimension (N)

      INFO    (output) INTEGER
              = 0:  successful exit
              < 0:  if INFO = -i, the i-th argument had an illegal

              value
              > 0:  if INFO = i, and i is
              <= N: if INFO = i, the leading minor of order i of A
              is not positive definite, so the factorization could
              not be completed, and the solution and error bounds
              could not be computed.  = N+1: RCOND is less than
              machine precision.  The factorization has been com-
              pleted, but the matrix is singular to working preci-
              sion, and the solution and error bounds have not
              been computed.

 FURTHER DETAILS
      The packed storage scheme is illustrated by the following
      example when N = 4, UPLO = 'U':

      Two-dimensional storage of the symmetric matrix A:

         a11 a12 a13 a14
             a22 a23 a24
                 a33 a34     (aij = conjg(aji))
                     a44

      Packed storage of the upper triangle of A:

      AP = [ a11, a12, a22, a13, a23, a33, a14, a24, a34, a44 ]