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authorjason <jason@8a072113-8704-0410-8d35-dd094bca7971>2008-10-28 01:38:50 +0000
committerjason <jason@8a072113-8704-0410-8d35-dd094bca7971>2008-10-28 01:38:50 +0000
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Move LAPACK trunk into position.
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+ SUBROUTINE DPPSVX( FACT, UPLO, N, NRHS, AP, AFP, EQUED, S, B, LDB,
+ $ X, LDX, RCOND, FERR, BERR, WORK, IWORK, INFO )
+*
+* -- LAPACK driver routine (version 3.1) --
+* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..
+* November 2006
+*
+* .. Scalar Arguments ..
+ CHARACTER EQUED, FACT, UPLO
+ INTEGER INFO, LDB, LDX, N, NRHS
+ DOUBLE PRECISION RCOND
+* ..
+* .. Array Arguments ..
+ 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 definite 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. 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.
+*
+* 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 factored 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 necessary, 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.
+*
+* AP (input/output) DOUBLE PRECISION array, dimension (N*(N+1)/2)
+* On entry, the upper or lower triangle of the symmetric 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 or 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 argument if FACT = 'F'; otherwise, it is an
+* output argument.
+*
+* S (input or output) 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.
+*
+* B (input/output) 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.
+*
+* 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 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.
+*
+* 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 particular, if RCOND = 0), the matrix
+* is singular to working precision. This condition is
+* indicated by a return code of INFO > 0.
+*
+* FERR (output) 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.
+*
+* 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 element 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: 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.
+*
+* 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 ]
+*
+* =====================================================================
+*
+* .. Parameters ..
+ DOUBLE PRECISION ZERO, ONE
+ PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 )
+* ..
+* .. Local Scalars ..
+ LOGICAL EQUIL, NOFACT, RCEQU
+ INTEGER I, INFEQU, J
+ DOUBLE PRECISION AMAX, ANORM, BIGNUM, SCOND, SMAX, SMIN, SMLNUM
+* ..
+* .. External Functions ..
+ LOGICAL LSAME
+ DOUBLE PRECISION DLAMCH, DLANSP
+ EXTERNAL LSAME, DLAMCH, DLANSP
+* ..
+* .. External Subroutines ..
+ EXTERNAL DCOPY, DLACPY, DLAQSP, DPPCON, DPPEQU, DPPRFS,
+ $ DPPTRF, DPPTRS, XERBLA
+* ..
+* .. Intrinsic Functions ..
+ INTRINSIC MAX, MIN
+* ..
+* .. Executable Statements ..
+*
+ INFO = 0
+ NOFACT = LSAME( FACT, 'N' )
+ EQUIL = LSAME( FACT, 'E' )
+ IF( NOFACT .OR. EQUIL ) THEN
+ EQUED = 'N'
+ RCEQU = .FALSE.
+ ELSE
+ RCEQU = LSAME( EQUED, 'Y' )
+ SMLNUM = DLAMCH( 'Safe minimum' )
+ BIGNUM = ONE / SMLNUM
+ END IF
+*
+* Test the input parameters.
+*
+ IF( .NOT.NOFACT .AND. .NOT.EQUIL .AND. .NOT.LSAME( FACT, 'F' ) )
+ $ THEN
+ INFO = -1
+ ELSE IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) )
+ $ THEN
+ INFO = -2
+ ELSE IF( N.LT.0 ) THEN
+ INFO = -3
+ ELSE IF( NRHS.LT.0 ) THEN
+ INFO = -4
+ ELSE IF( LSAME( FACT, 'F' ) .AND. .NOT.
+ $ ( RCEQU .OR. LSAME( EQUED, 'N' ) ) ) THEN
+ INFO = -7
+ ELSE
+ IF( RCEQU ) THEN
+ SMIN = BIGNUM
+ SMAX = ZERO
+ DO 10 J = 1, N
+ SMIN = MIN( SMIN, S( J ) )
+ SMAX = MAX( SMAX, S( J ) )
+ 10 CONTINUE
+ IF( SMIN.LE.ZERO ) THEN
+ INFO = -8
+ ELSE IF( N.GT.0 ) THEN
+ SCOND = MAX( SMIN, SMLNUM ) / MIN( SMAX, BIGNUM )
+ ELSE
+ SCOND = ONE
+ END IF
+ END IF
+ IF( INFO.EQ.0 ) THEN
+ IF( LDB.LT.MAX( 1, N ) ) THEN
+ INFO = -10
+ ELSE IF( LDX.LT.MAX( 1, N ) ) THEN
+ INFO = -12
+ END IF
+ END IF
+ END IF
+*
+ IF( INFO.NE.0 ) THEN
+ CALL XERBLA( 'DPPSVX', -INFO )
+ RETURN
+ END IF
+*
+ IF( EQUIL ) THEN
+*
+* Compute row and column scalings to equilibrate the matrix A.
+*
+ CALL DPPEQU( UPLO, N, AP, S, SCOND, AMAX, INFEQU )
+ IF( INFEQU.EQ.0 ) THEN
+*
+* Equilibrate the matrix.
+*
+ CALL DLAQSP( UPLO, N, AP, S, SCOND, AMAX, EQUED )
+ RCEQU = LSAME( EQUED, 'Y' )
+ END IF
+ END IF
+*
+* Scale the right-hand side.
+*
+ IF( RCEQU ) THEN
+ DO 30 J = 1, NRHS
+ DO 20 I = 1, N
+ B( I, J ) = S( I )*B( I, J )
+ 20 CONTINUE
+ 30 CONTINUE
+ END IF
+*
+ IF( NOFACT .OR. EQUIL ) THEN
+*
+* Compute the Cholesky factorization A = U'*U or A = L*L'.
+*
+ CALL DCOPY( N*( N+1 ) / 2, AP, 1, AFP, 1 )
+ CALL DPPTRF( UPLO, N, AFP, INFO )
+*
+* Return if INFO is non-zero.
+*
+ IF( INFO.GT.0 )THEN
+ RCOND = ZERO
+ RETURN
+ END IF
+ END IF
+*
+* Compute the norm of the matrix A.
+*
+ ANORM = DLANSP( 'I', UPLO, N, AP, WORK )
+*
+* Compute the reciprocal of the condition number of A.
+*
+ CALL DPPCON( UPLO, N, AFP, ANORM, RCOND, WORK, IWORK, INFO )
+*
+* Compute the solution matrix X.
+*
+ CALL DLACPY( 'Full', N, NRHS, B, LDB, X, LDX )
+ CALL DPPTRS( UPLO, N, NRHS, AFP, X, LDX, INFO )
+*
+* Use iterative refinement to improve the computed solution and
+* compute error bounds and backward error estimates for it.
+*
+ CALL DPPRFS( UPLO, N, NRHS, AP, AFP, B, LDB, X, LDX, FERR, BERR,
+ $ WORK, IWORK, INFO )
+*
+* Transform the solution matrix X to a solution of the original
+* system.
+*
+ IF( RCEQU ) THEN
+ DO 50 J = 1, NRHS
+ DO 40 I = 1, N
+ X( I, J ) = S( I )*X( I, J )
+ 40 CONTINUE
+ 50 CONTINUE
+ DO 60 J = 1, NRHS
+ FERR( J ) = FERR( J ) / SCOND
+ 60 CONTINUE
+ END IF
+*
+* Set INFO = N+1 if the matrix is singular to working precision.
+*
+ IF( RCOND.LT.DLAMCH( 'Epsilon' ) )
+ $ INFO = N + 1
+*
+ RETURN
+*
+* End of DPPSVX
+*
+ END