#include "blaswrap.h" #include "f2c.h" /* Subroutine */ int sgesvx_(char *fact, char *trans, integer *n, integer * nrhs, real *a, integer *lda, real *af, integer *ldaf, integer *ipiv, char *equed, real *r__, real *c__, real *b, integer *ldb, real *x, integer *ldx, real *rcond, real *ferr, real *berr, real *work, integer *iwork, integer *info) { /* -- LAPACK driver routine (version 3.1) -- Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. November 2006 Purpose ======= SGESVX 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) REAL 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) REAL 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 SGETRF. 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 SGETRF; 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) REAL 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) REAL 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) REAL 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) REAL 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) REAL 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) REAL 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) REAL 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) REAL 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 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. ===================================================================== Parameter adjustments */ /* System generated locals */ integer a_dim1, a_offset, af_dim1, af_offset, b_dim1, b_offset, x_dim1, x_offset, i__1, i__2; real r__1, r__2; /* Local variables */ static integer i__, j; static real amax; static char norm[1]; extern logical lsame_(char *, char *); static real rcmin, rcmax, anorm; static logical equil; static real colcnd; extern doublereal slamch_(char *), slange_(char *, integer *, integer *, real *, integer *, real *); static logical nofact; extern /* Subroutine */ int slaqge_(integer *, integer *, real *, integer *, real *, real *, real *, real *, real *, char *), xerbla_(char *, integer *), sgecon_(char *, integer *, real *, integer *, real *, real *, real *, integer *, integer *); static real bignum; static integer infequ; static logical colequ; extern /* Subroutine */ int sgeequ_(integer *, integer *, real *, integer *, real *, real *, real *, real *, real *, integer *), sgerfs_( char *, integer *, integer *, real *, integer *, real *, integer * , integer *, real *, integer *, real *, integer *, real *, real *, real *, integer *, integer *), sgetrf_(integer *, integer *, real *, integer *, integer *, integer *); static real rowcnd; extern /* Subroutine */ int slacpy_(char *, integer *, integer *, real *, integer *, real *, integer *); static logical notran; extern doublereal slantr_(char *, char *, char *, integer *, integer *, real *, integer *, real *); extern /* Subroutine */ int sgetrs_(char *, integer *, integer *, real *, integer *, integer *, real *, integer *, integer *); static real smlnum; static logical rowequ; static real rpvgrw; a_dim1 = *lda; a_offset = 1 + a_dim1; a -= a_offset; af_dim1 = *ldaf; af_offset = 1 + af_dim1; af -= af_offset; --ipiv; --r__; --c__; b_dim1 = *ldb; b_offset = 1 + b_dim1; b -= b_offset; x_dim1 = *ldx; x_offset = 1 + x_dim1; x -= x_offset; --ferr; --berr; --work; --iwork; /* Function Body */ *info = 0; nofact = lsame_(fact, "N"); equil = lsame_(fact, "E"); notran = lsame_(trans, "N"); if (nofact || equil) { *(unsigned char *)equed = 'N'; rowequ = FALSE_; colequ = FALSE_; } else { rowequ = lsame_(equed, "R") || lsame_(equed, "B"); colequ = lsame_(equed, "C") || lsame_(equed, "B"); smlnum = slamch_("Safe minimum"); bignum = 1.f / smlnum; } /* Test the input parameters. */ if (! nofact && ! equil && ! lsame_(fact, "F")) { *info = -1; } else if (! notran && ! lsame_(trans, "T") && ! lsame_(trans, "C")) { *info = -2; } else if (*n < 0) { *info = -3; } else if (*nrhs < 0) { *info = -4; } else if (*lda < max(1,*n)) { *info = -6; } else if (*ldaf < max(1,*n)) { *info = -8; } else if (lsame_(fact, "F") && ! (rowequ || colequ || lsame_(equed, "N"))) { *info = -10; } else { if (rowequ) { rcmin = bignum; rcmax = 0.f; i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MIN */ r__1 = rcmin, r__2 = r__[j]; rcmin = dmin(r__1,r__2); /* Computing MAX */ r__1 = rcmax, r__2 = r__[j]; rcmax = dmax(r__1,r__2); /* L10: */ } if (rcmin <= 0.f) { *info = -11; } else if (*n > 0) { rowcnd = dmax(rcmin,smlnum) / dmin(rcmax,bignum); } else { rowcnd = 1.f; } } if (colequ && *info == 0) { rcmin = bignum; rcmax = 0.f; i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MIN */ r__1 = rcmin, r__2 = c__[j]; rcmin = dmin(r__1,r__2); /* Computing MAX */ r__1 = rcmax, r__2 = c__[j]; rcmax = dmax(r__1,r__2); /* L20: */ } if (rcmin <= 0.f) { *info = -12; } else if (*n > 0) { colcnd = dmax(rcmin,smlnum) / dmin(rcmax,bignum); } else { colcnd = 1.f; } } if (*info == 0) { if (*ldb < max(1,*n)) { *info = -14; } else if (*ldx < max(1,*n)) { *info = -16; } } } if (*info != 0) { i__1 = -(*info); xerbla_("SGESVX", &i__1); return 0; } if (equil) { /* Compute row and column scalings to equilibrate the matrix A. */ sgeequ_(n, n, &a[a_offset], lda, &r__[1], &c__[1], &rowcnd, &colcnd, & amax, &infequ); if (infequ == 0) { /* Equilibrate the matrix. */ slaqge_(n, n, &a[a_offset], lda, &r__[1], &c__[1], &rowcnd, & colcnd, &amax, equed); rowequ = lsame_(equed, "R") || lsame_(equed, "B"); colequ = lsame_(equed, "C") || lsame_(equed, "B"); } } /* Scale the right hand side. */ if (notran) { if (rowequ) { i__1 = *nrhs; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = r__[i__] * b[i__ + j * b_dim1]; /* L30: */ } /* L40: */ } } } else if (colequ) { i__1 = *nrhs; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { b[i__ + j * b_dim1] = c__[i__] * b[i__ + j * b_dim1]; /* L50: */ } /* L60: */ } } if (nofact || equil) { /* Compute the LU factorization of A. */ slacpy_("Full", n, n, &a[a_offset], lda, &af[af_offset], ldaf); sgetrf_(n, n, &af[af_offset], ldaf, &ipiv[1], info); /* Return if INFO is non-zero. */ if (*info > 0) { /* Compute the reciprocal pivot growth factor of the leading rank-deficient INFO columns of A. */ rpvgrw = slantr_("M", "U", "N", info, info, &af[af_offset], ldaf, &work[1]); if (rpvgrw == 0.f) { rpvgrw = 1.f; } else { rpvgrw = slange_("M", n, info, &a[a_offset], lda, &work[1]) / rpvgrw; } work[1] = rpvgrw; *rcond = 0.f; return 0; } } /* Compute the norm of the matrix A and the reciprocal pivot growth factor RPVGRW. */ if (notran) { *(unsigned char *)norm = '1'; } else { *(unsigned char *)norm = 'I'; } anorm = slange_(norm, n, n, &a[a_offset], lda, &work[1]); rpvgrw = slantr_("M", "U", "N", n, n, &af[af_offset], ldaf, &work[1]); if (rpvgrw == 0.f) { rpvgrw = 1.f; } else { rpvgrw = slange_("M", n, n, &a[a_offset], lda, &work[1]) / rpvgrw; } /* Compute the reciprocal of the condition number of A. */ sgecon_(norm, n, &af[af_offset], ldaf, &anorm, rcond, &work[1], &iwork[1], info); /* Compute the solution matrix X. */ slacpy_("Full", n, nrhs, &b[b_offset], ldb, &x[x_offset], ldx); sgetrs_(trans, n, nrhs, &af[af_offset], ldaf, &ipiv[1], &x[x_offset], ldx, info); /* Use iterative refinement to improve the computed solution and compute error bounds and backward error estimates for it. */ sgerfs_(trans, n, nrhs, &a[a_offset], lda, &af[af_offset], ldaf, &ipiv[1], &b[b_offset], ldb, &x[x_offset], ldx, &ferr[1], &berr[1], &work[ 1], &iwork[1], info); /* Transform the solution matrix X to a solution of the original system. */ if (notran) { if (colequ) { i__1 = *nrhs; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { x[i__ + j * x_dim1] = c__[i__] * x[i__ + j * x_dim1]; /* L70: */ } /* L80: */ } i__1 = *nrhs; for (j = 1; j <= i__1; ++j) { ferr[j] /= colcnd; /* L90: */ } } } else if (rowequ) { i__1 = *nrhs; for (j = 1; j <= i__1; ++j) { i__2 = *n; for (i__ = 1; i__ <= i__2; ++i__) { x[i__ + j * x_dim1] = r__[i__] * x[i__ + j * x_dim1]; /* L100: */ } /* L110: */ } i__1 = *nrhs; for (j = 1; j <= i__1; ++j) { ferr[j] /= rowcnd; /* L120: */ } } /* Set INFO = N+1 if the matrix is singular to working precision. */ if (*rcond < slamch_("Epsilon")) { *info = *n + 1; } work[1] = rpvgrw; return 0; /* End of SGESVX */ } /* sgesvx_ */