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+ SUBROUTINE DGESVX( FACT, TRANS, N, NRHS, A, LDA, AF, LDAF, IPIV,
+ $ EQUED, R, C, 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, TRANS
+ INTEGER INFO, LDA, LDAF, LDB, LDX, N, NRHS
+ DOUBLE PRECISION RCOND
+* ..
+* .. Array Arguments ..
+ INTEGER IPIV( * ), IWORK( * )
+ DOUBLE PRECISION A( LDA, * ), AF( LDAF, * ), B( LDB, * ),
+ $ BERR( * ), C( * ), FERR( * ), R( * ),
+ $ WORK( * ), X( LDX, * )
+* ..
+*
+* Purpose
+* =======
+*
+* DGESVX uses the LU factorization to compute the solution to a real
+* system of linear equations
+* A * X = B,
+* where A is an N-by-N 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:
+* TRANS = 'N': diag(R)*A*diag(C) *inv(diag(C))*X = diag(R)*B
+* TRANS = 'T': (diag(R)*A*diag(C))**T *inv(diag(R))*X = diag(C)*B
+* TRANS = 'C': (diag(R)*A*diag(C))**H *inv(diag(R))*X = diag(C)*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(R)*A*diag(C) and B by diag(R)*B (if TRANS='N')
+* or diag(C)*B (if TRANS = 'T' or 'C').
+*
+* 2. If FACT = 'N' or 'E', the LU decomposition is used to factor the
+* matrix A (after equilibration if FACT = 'E') as
+* A = P * L * U,
+* where P is a permutation matrix, L is a unit lower triangular
+* matrix, and U is upper triangular.
+*
+* 3. If some U(i,i)=0, so that U is exactly singular, 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(C) (if TRANS = 'N') or diag(R) (if TRANS = 'T' or 'C') 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, AF and IPIV contain the factored form of A.
+* If EQUED is not 'N', the matrix A has been
+* equilibrated with scaling factors given by R and C.
+* A, AF, and IPIV are not 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.
+*
+* TRANS (input) CHARACTER*1
+* Specifies the form of the system of equations:
+* = 'N': A * X = B (No transpose)
+* = 'T': A**T * X = B (Transpose)
+* = 'C': A**H * X = B (Transpose)
+*
+* 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.
+*
+* A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
+* On entry, the N-by-N matrix A. If FACT = 'F' and EQUED is
+* not 'N', then A must have been equilibrated by the scaling
+* factors in R and/or C. A is not modified if FACT = 'F' or
+* 'N', or if FACT = 'E' and EQUED = 'N' on exit.
+*
+* On exit, if EQUED .ne. 'N', A is scaled as follows:
+* EQUED = 'R': A := diag(R) * A
+* EQUED = 'C': A := A * diag(C)
+* EQUED = 'B': A := diag(R) * A * diag(C).
+*
+* LDA (input) INTEGER
+* The leading dimension of the array A. LDA >= max(1,N).
+*
+* AF (input or output) DOUBLE PRECISION array, dimension (LDAF,N)
+* If FACT = 'F', then AF is an input argument and on entry
+* contains the factors L and U from the factorization
+* A = P*L*U as computed by DGETRF. If EQUED .ne. 'N', then
+* AF is the factored form of the equilibrated matrix A.
+*
+* If FACT = 'N', then AF is an output argument and on exit
+* returns the factors L and U from the factorization A = P*L*U
+* of the original matrix A.
+*
+* If FACT = 'E', then AF is an output argument and on exit
+* returns the factors L and U from the factorization A = P*L*U
+* of the equilibrated matrix A (see the description of A for
+* the form of the equilibrated matrix).
+*
+* LDAF (input) INTEGER
+* The leading dimension of the array AF. LDAF >= max(1,N).
+*
+* IPIV (input or output) INTEGER array, dimension (N)
+* If FACT = 'F', then IPIV is an input argument and on entry
+* contains the pivot indices from the factorization A = P*L*U
+* as computed by DGETRF; row i of the matrix was interchanged
+* with row IPIV(i).
+*
+* If FACT = 'N', then IPIV is an output argument and on exit
+* contains the pivot indices from the factorization A = P*L*U
+* of the original matrix A.
+*
+* If FACT = 'E', then IPIV is an output argument and on exit
+* contains the pivot indices from the factorization A = P*L*U
+* of the equilibrated matrix A.
+*
+* EQUED (input or output) CHARACTER*1
+* Specifies the form of equilibration that was done.
+* = 'N': No equilibration (always true if FACT = 'N').
+* = 'R': Row equilibration, i.e., A has been premultiplied by
+* diag(R).
+* = 'C': Column equilibration, i.e., A has been postmultiplied
+* by diag(C).
+* = 'B': Both row and column equilibration, i.e., A has been
+* replaced by diag(R) * A * diag(C).
+* EQUED is an input argument if FACT = 'F'; otherwise, it is an
+* output argument.
+*
+* R (input or output) DOUBLE PRECISION array, dimension (N)
+* The row scale factors for A. If EQUED = 'R' or 'B', A is
+* multiplied on the left by diag(R); if EQUED = 'N' or 'C', R
+* is not accessed. R is an input argument if FACT = 'F';
+* otherwise, R is an output argument. If FACT = 'F' and
+* EQUED = 'R' or 'B', each element of R must be positive.
+*
+* C (input or output) DOUBLE PRECISION array, dimension (N)
+* The column scale factors for A. If EQUED = 'C' or 'B', A is
+* multiplied on the right by diag(C); if EQUED = 'N' or 'R', C
+* is not accessed. C is an input argument if FACT = 'F';
+* otherwise, C is an output argument. If FACT = 'F' and
+* EQUED = 'C' or 'B', each element of C 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 TRANS = 'N' and EQUED = 'R' or 'B', B is overwritten by
+* diag(R)*B;
+* if TRANS = 'T' or 'C' and EQUED = 'C' or 'B', B is
+* overwritten by diag(C)*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 A and B are
+* modified on exit if EQUED .ne. 'N', and the solution to the
+* equilibrated system is inv(diag(C))*X if TRANS = 'N' and
+* EQUED = 'C' or 'B', or inv(diag(R))*X if TRANS = 'T' or 'C'
+* and EQUED = 'R' or 'B'.
+*
+* 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/output) DOUBLE PRECISION array, dimension (4*N)
+* On exit, WORK(1) contains the reciprocal pivot growth
+* factor norm(A)/norm(U). The "max absolute element" norm is
+* used. If WORK(1) is much less than 1, then the stability
+* of the LU factorization of the (equilibrated) matrix A
+* could be poor. This also means that the solution X, condition
+* estimator RCOND, and forward error bound FERR could be
+* unreliable. If factorization fails with 0<INFO<=N, then
+* WORK(1) contains the reciprocal pivot growth factor for the
+* leading INFO columns of A.
+*
+* 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: U(i,i) is exactly zero. The factorization has
+* been completed, but the factor U is exactly
+* singular, so the solution and error bounds
+* could not be 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.
+*
+* =====================================================================
+*
+* .. Parameters ..
+ DOUBLE PRECISION ZERO, ONE
+ PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 )
+* ..
+* .. Local Scalars ..
+ LOGICAL COLEQU, EQUIL, NOFACT, NOTRAN, ROWEQU
+ CHARACTER NORM
+ INTEGER I, INFEQU, J
+ DOUBLE PRECISION AMAX, ANORM, BIGNUM, COLCND, RCMAX, RCMIN,
+ $ ROWCND, RPVGRW, SMLNUM
+* ..
+* .. External Functions ..
+ LOGICAL LSAME
+ DOUBLE PRECISION DLAMCH, DLANGE, DLANTR
+ EXTERNAL LSAME, DLAMCH, DLANGE, DLANTR
+* ..
+* .. External Subroutines ..
+ EXTERNAL DGECON, DGEEQU, DGERFS, DGETRF, DGETRS, DLACPY,
+ $ DLAQGE, XERBLA
+* ..
+* .. Intrinsic Functions ..
+ INTRINSIC MAX, MIN
+* ..
+* .. Executable Statements ..
+*
+ INFO = 0
+ NOFACT = LSAME( FACT, 'N' )
+ EQUIL = LSAME( FACT, 'E' )
+ NOTRAN = LSAME( TRANS, 'N' )
+ IF( NOFACT .OR. EQUIL ) THEN
+ EQUED = 'N'
+ ROWEQU = .FALSE.
+ COLEQU = .FALSE.
+ ELSE
+ ROWEQU = LSAME( EQUED, 'R' ) .OR. LSAME( EQUED, 'B' )
+ COLEQU = LSAME( EQUED, 'C' ) .OR. LSAME( EQUED, 'B' )
+ 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.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) .AND. .NOT.
+ $ LSAME( TRANS, 'C' ) ) THEN
+ INFO = -2
+ ELSE IF( N.LT.0 ) THEN
+ INFO = -3
+ ELSE IF( NRHS.LT.0 ) THEN
+ INFO = -4
+ ELSE IF( LDA.LT.MAX( 1, N ) ) THEN
+ INFO = -6
+ ELSE IF( LDAF.LT.MAX( 1, N ) ) THEN
+ INFO = -8
+ ELSE IF( LSAME( FACT, 'F' ) .AND. .NOT.
+ $ ( ROWEQU .OR. COLEQU .OR. LSAME( EQUED, 'N' ) ) ) THEN
+ INFO = -10
+ ELSE
+ IF( ROWEQU ) THEN
+ RCMIN = BIGNUM
+ RCMAX = ZERO
+ DO 10 J = 1, N
+ RCMIN = MIN( RCMIN, R( J ) )
+ RCMAX = MAX( RCMAX, R( J ) )
+ 10 CONTINUE
+ IF( RCMIN.LE.ZERO ) THEN
+ INFO = -11
+ ELSE IF( N.GT.0 ) THEN
+ ROWCND = MAX( RCMIN, SMLNUM ) / MIN( RCMAX, BIGNUM )
+ ELSE
+ ROWCND = ONE
+ END IF
+ END IF
+ IF( COLEQU .AND. INFO.EQ.0 ) THEN
+ RCMIN = BIGNUM
+ RCMAX = ZERO
+ DO 20 J = 1, N
+ RCMIN = MIN( RCMIN, C( J ) )
+ RCMAX = MAX( RCMAX, C( J ) )
+ 20 CONTINUE
+ IF( RCMIN.LE.ZERO ) THEN
+ INFO = -12
+ ELSE IF( N.GT.0 ) THEN
+ COLCND = MAX( RCMIN, SMLNUM ) / MIN( RCMAX, BIGNUM )
+ ELSE
+ COLCND = ONE
+ END IF
+ END IF
+ IF( INFO.EQ.0 ) THEN
+ IF( LDB.LT.MAX( 1, N ) ) THEN
+ INFO = -14
+ ELSE IF( LDX.LT.MAX( 1, N ) ) THEN
+ INFO = -16
+ END IF
+ END IF
+ END IF
+*
+ IF( INFO.NE.0 ) THEN
+ CALL XERBLA( 'DGESVX', -INFO )
+ RETURN
+ END IF
+*
+ IF( EQUIL ) THEN
+*
+* Compute row and column scalings to equilibrate the matrix A.
+*
+ CALL DGEEQU( N, N, A, LDA, R, C, ROWCND, COLCND, AMAX, INFEQU )
+ IF( INFEQU.EQ.0 ) THEN
+*
+* Equilibrate the matrix.
+*
+ CALL DLAQGE( N, N, A, LDA, R, C, ROWCND, COLCND, AMAX,
+ $ EQUED )
+ ROWEQU = LSAME( EQUED, 'R' ) .OR. LSAME( EQUED, 'B' )
+ COLEQU = LSAME( EQUED, 'C' ) .OR. LSAME( EQUED, 'B' )
+ END IF
+ END IF
+*
+* Scale the right hand side.
+*
+ IF( NOTRAN ) THEN
+ IF( ROWEQU ) THEN
+ DO 40 J = 1, NRHS
+ DO 30 I = 1, N
+ B( I, J ) = R( I )*B( I, J )
+ 30 CONTINUE
+ 40 CONTINUE
+ END IF
+ ELSE IF( COLEQU ) THEN
+ DO 60 J = 1, NRHS
+ DO 50 I = 1, N
+ B( I, J ) = C( I )*B( I, J )
+ 50 CONTINUE
+ 60 CONTINUE
+ END IF
+*
+ IF( NOFACT .OR. EQUIL ) THEN
+*
+* Compute the LU factorization of A.
+*
+ CALL DLACPY( 'Full', N, N, A, LDA, AF, LDAF )
+ CALL DGETRF( N, N, AF, LDAF, IPIV, INFO )
+*
+* Return if INFO is non-zero.
+*
+ IF( INFO.GT.0 ) THEN
+*
+* Compute the reciprocal pivot growth factor of the
+* leading rank-deficient INFO columns of A.
+*
+ RPVGRW = DLANTR( 'M', 'U', 'N', INFO, INFO, AF, LDAF,
+ $ WORK )
+ IF( RPVGRW.EQ.ZERO ) THEN
+ RPVGRW = ONE
+ ELSE
+ RPVGRW = DLANGE( 'M', N, INFO, A, LDA, WORK ) / RPVGRW
+ END IF
+ WORK( 1 ) = RPVGRW
+ RCOND = ZERO
+ RETURN
+ END IF
+ END IF
+*
+* Compute the norm of the matrix A and the
+* reciprocal pivot growth factor RPVGRW.
+*
+ IF( NOTRAN ) THEN
+ NORM = '1'
+ ELSE
+ NORM = 'I'
+ END IF
+ ANORM = DLANGE( NORM, N, N, A, LDA, WORK )
+ RPVGRW = DLANTR( 'M', 'U', 'N', N, N, AF, LDAF, WORK )
+ IF( RPVGRW.EQ.ZERO ) THEN
+ RPVGRW = ONE
+ ELSE
+ RPVGRW = DLANGE( 'M', N, N, A, LDA, WORK ) / RPVGRW
+ END IF
+*
+* Compute the reciprocal of the condition number of A.
+*
+ CALL DGECON( NORM, N, AF, LDAF, ANORM, RCOND, WORK, IWORK, INFO )
+*
+* Compute the solution matrix X.
+*
+ CALL DLACPY( 'Full', N, NRHS, B, LDB, X, LDX )
+ CALL DGETRS( TRANS, N, NRHS, AF, LDAF, IPIV, X, LDX, INFO )
+*
+* Use iterative refinement to improve the computed solution and
+* compute error bounds and backward error estimates for it.
+*
+ CALL DGERFS( TRANS, N, NRHS, A, LDA, AF, LDAF, IPIV, B, LDB, X,
+ $ LDX, FERR, BERR, WORK, IWORK, INFO )
+*
+* Transform the solution matrix X to a solution of the original
+* system.
+*
+ IF( NOTRAN ) THEN
+ IF( COLEQU ) THEN
+ DO 80 J = 1, NRHS
+ DO 70 I = 1, N
+ X( I, J ) = C( I )*X( I, J )
+ 70 CONTINUE
+ 80 CONTINUE
+ DO 90 J = 1, NRHS
+ FERR( J ) = FERR( J ) / COLCND
+ 90 CONTINUE
+ END IF
+ ELSE IF( ROWEQU ) THEN
+ DO 110 J = 1, NRHS
+ DO 100 I = 1, N
+ X( I, J ) = R( I )*X( I, J )
+ 100 CONTINUE
+ 110 CONTINUE
+ DO 120 J = 1, NRHS
+ FERR( J ) = FERR( J ) / ROWCND
+ 120 CONTINUE
+ END IF
+*
+ WORK( 1 ) = RPVGRW
+*
+* Set INFO = N+1 if the matrix is singular to working precision.
+*
+ IF( RCOND.LT.DLAMCH( 'Epsilon' ) )
+ $ INFO = N + 1
+ RETURN
+*
+* End of DGESVX
+*
+ END