#include "blaswrap.h" #include "f2c.h" /* Subroutine */ int dgbsvx_(char *fact, char *trans, integer *n, integer *kl, integer *ku, integer *nrhs, doublereal *ab, integer *ldab, doublereal *afb, integer *ldafb, integer *ipiv, char *equed, doublereal *r__, doublereal *c__, doublereal *b, integer *ldb, doublereal *x, integer *ldx, doublereal *rcond, doublereal *ferr, doublereal *berr, doublereal *work, integer *iwork, integer *info) { /* -- LAPACK driver routine (version 3.0) -- Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., Courant Institute, Argonne National Lab, and Rice University June 30, 1999 Purpose ======= DGBSVX uses the LU factorization to compute the solution to a real system of linear equations A * X = B, A**T * X = B, or A**H * X = B, where A is a band matrix of order N with KL subdiagonals and KU superdiagonals, 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 by this subroutine: 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 = L * U, where L is a product of permutation and unit lower triangular matrices with KL subdiagonals, and U is upper triangular with KL+KU superdiagonals. 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, AFB 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. AB, AFB, and IPIV are not modified. = 'N': The matrix A will be copied to AFB and factored. = 'E': The matrix A will be equilibrated if necessary, then copied to AFB 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. KL (input) INTEGER The number of subdiagonals within the band of A. KL >= 0. KU (input) INTEGER The number of superdiagonals within the band of A. KU >= 0. NRHS (input) INTEGER The number of right hand sides, i.e., the number of columns of the matrices B and X. NRHS >= 0. AB (input/output) DOUBLE PRECISION array, dimension (LDAB,N) On entry, the matrix A in band storage, in rows 1 to KL+KU+1. The j-th column of A is stored in the j-th column of the array AB as follows: AB(KU+1+i-j,j) = A(i,j) for max(1,j-KU)<=i<=min(N,j+kl) If FACT = 'F' and EQUED is not 'N', then A must have been equilibrated by the scaling factors in R and/or C. AB 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). LDAB (input) INTEGER The leading dimension of the array AB. LDAB >= KL+KU+1. AFB (input or output) DOUBLE PRECISION array, dimension (LDAFB,N) If FACT = 'F', then AFB is an input argument and on entry contains details of the LU factorization of the band matrix A, as computed by DGBTRF. U is stored as an upper triangular band matrix with KL+KU superdiagonals in rows 1 to KL+KU+1, and the multipliers used during the factorization are stored in rows KL+KU+2 to 2*KL+KU+1. If EQUED .ne. 'N', then AFB is the factored form of the equilibrated matrix A. If FACT = 'N', then AFB is an output argument and on exit returns details of the LU factorization of A. If FACT = 'E', then AFB is an output argument and on exit returns details of the LU factorization of the equilibrated matrix A (see the description of AB for the form of the equilibrated matrix). LDAFB (input) INTEGER The leading dimension of the array AFB. LDAFB >= 2*KL+KU+1. 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 = L*U as computed by DGBTRF; 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 = 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 = 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 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 (3*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 */ /* Table of constant values */ static integer c__1 = 1; /* System generated locals */ integer ab_dim1, ab_offset, afb_dim1, afb_offset, b_dim1, b_offset, x_dim1, x_offset, i__1, i__2, i__3, i__4, i__5; doublereal d__1, d__2, d__3; /* Local variables */ static doublereal amax; static char norm[1]; static integer i__, j; extern logical lsame_(char *, char *); static doublereal rcmin, rcmax, anorm; extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *, doublereal *, integer *); static logical equil; static integer j1, j2; extern doublereal dlamch_(char *), dlangb_(char *, integer *, integer *, integer *, doublereal *, integer *, doublereal *); extern /* Subroutine */ int dlaqgb_(integer *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, char *), dgbcon_(char *, integer *, integer *, integer *, doublereal *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, integer *); static doublereal colcnd; extern doublereal dlantb_(char *, char *, char *, integer *, integer *, doublereal *, integer *, doublereal *); extern /* Subroutine */ int dgbequ_(integer *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *), dgbrfs_( char *, integer *, integer *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *, integer *), dgbtrf_(integer *, integer *, integer *, integer *, doublereal *, integer *, integer *, integer *); static logical nofact; extern /* Subroutine */ int dlacpy_(char *, integer *, integer *, doublereal *, integer *, doublereal *, integer *), xerbla_(char *, integer *); static doublereal bignum; extern /* Subroutine */ int dgbtrs_(char *, integer *, integer *, integer *, integer *, doublereal *, integer *, integer *, doublereal *, integer *, integer *); static integer infequ; static logical colequ; static doublereal rowcnd; static logical notran; static doublereal smlnum; static logical rowequ; static doublereal rpvgrw; #define b_ref(a_1,a_2) b[(a_2)*b_dim1 + a_1] #define x_ref(a_1,a_2) x[(a_2)*x_dim1 + a_1] #define ab_ref(a_1,a_2) ab[(a_2)*ab_dim1 + a_1] #define afb_ref(a_1,a_2) afb[(a_2)*afb_dim1 + a_1] ab_dim1 = *ldab; ab_offset = 1 + ab_dim1 * 1; ab -= ab_offset; afb_dim1 = *ldafb; afb_offset = 1 + afb_dim1 * 1; afb -= afb_offset; --ipiv; --r__; --c__; b_dim1 = *ldb; b_offset = 1 + b_dim1 * 1; b -= b_offset; x_dim1 = *ldx; x_offset = 1 + x_dim1 * 1; 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 = dlamch_("Safe minimum"); bignum = 1. / 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 (*kl < 0) { *info = -4; } else if (*ku < 0) { *info = -5; } else if (*nrhs < 0) { *info = -6; } else if (*ldab < *kl + *ku + 1) { *info = -8; } else if (*ldafb < (*kl << 1) + *ku + 1) { *info = -10; } else if (lsame_(fact, "F") && ! (rowequ || colequ || lsame_(equed, "N"))) { *info = -12; } else { if (rowequ) { rcmin = bignum; rcmax = 0.; i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MIN */ d__1 = rcmin, d__2 = r__[j]; rcmin = min(d__1,d__2); /* Computing MAX */ d__1 = rcmax, d__2 = r__[j]; rcmax = max(d__1,d__2); /* L10: */ } if (rcmin <= 0.) { *info = -13; } else if (*n > 0) { rowcnd = max(rcmin,smlnum) / min(rcmax,bignum); } else { rowcnd = 1.; } } if (colequ && *info == 0) { rcmin = bignum; rcmax = 0.; i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MIN */ d__1 = rcmin, d__2 = c__[j]; rcmin = min(d__1,d__2); /* Computing MAX */ d__1 = rcmax, d__2 = c__[j]; rcmax = max(d__1,d__2); /* L20: */ } if (rcmin <= 0.) { *info = -14; } else if (*n > 0) { colcnd = max(rcmin,smlnum) / min(rcmax,bignum); } else { colcnd = 1.; } } if (*info == 0) { if (*ldb < max(1,*n)) { *info = -16; } else if (*ldx < max(1,*n)) { *info = -18; } } } if (*info != 0) { i__1 = -(*info); xerbla_("DGBSVX", &i__1); return 0; } if (equil) { /* Compute row and column scalings to equilibrate the matrix A. */ dgbequ_(n, n, kl, ku, &ab[ab_offset], ldab, &r__[1], &c__[1], &rowcnd, &colcnd, &amax, &infequ); if (infequ == 0) { /* Equilibrate the matrix. */ dlaqgb_(n, n, kl, ku, &ab[ab_offset], ldab, &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_ref(i__, j) = r__[i__] * b_ref(i__, j); /* 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_ref(i__, j) = c__[i__] * b_ref(i__, j); /* L50: */ } /* L60: */ } } if (nofact || equil) { /* Compute the LU factorization of the band matrix A. */ i__1 = *n; for (j = 1; j <= i__1; ++j) { /* Computing MAX */ i__2 = j - *ku; j1 = max(i__2,1); /* Computing MIN */ i__2 = j + *kl; j2 = min(i__2,*n); i__2 = j2 - j1 + 1; dcopy_(&i__2, &ab_ref(*ku + 1 - j + j1, j), &c__1, &afb_ref(*kl + *ku + 1 - j + j1, j), &c__1); /* L70: */ } dgbtrf_(n, n, kl, ku, &afb[afb_offset], ldafb, &ipiv[1], info); /* Return if INFO is non-zero. */ if (*info != 0) { if (*info > 0) { /* Compute the reciprocal pivot growth factor of the leading rank-deficient INFO columns of A. */ anorm = 0.; i__1 = *info; for (j = 1; j <= i__1; ++j) { /* Computing MAX */ i__2 = *ku + 2 - j; /* Computing MIN */ i__4 = *n + *ku + 1 - j, i__5 = *kl + *ku + 1; i__3 = min(i__4,i__5); for (i__ = max(i__2,1); i__ <= i__3; ++i__) { /* Computing MAX */ d__2 = anorm, d__3 = (d__1 = ab_ref(i__, j), abs(d__1) ); anorm = max(d__2,d__3); /* L80: */ } /* L90: */ } /* Computing MAX */ i__1 = 1, i__3 = *kl + *ku + 2 - *info; /* Computing MIN */ i__4 = *info - 1, i__5 = *kl + *ku; i__2 = min(i__4,i__5); rpvgrw = dlantb_("M", "U", "N", info, &i__2, &afb_ref(max( i__1,i__3), 1), ldafb, &work[1]); if (rpvgrw == 0.) { rpvgrw = 1.; } else { rpvgrw = anorm / rpvgrw; } work[1] = rpvgrw; *rcond = 0.; } 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 = dlangb_(norm, n, kl, ku, &ab[ab_offset], ldab, &work[1]); i__1 = *kl + *ku; rpvgrw = dlantb_("M", "U", "N", n, &i__1, &afb[afb_offset], ldafb, &work[ 1]); if (rpvgrw == 0.) { rpvgrw = 1.; } else { rpvgrw = dlangb_("M", n, kl, ku, &ab[ab_offset], ldab, &work[1]) / rpvgrw; } /* Compute the reciprocal of the condition number of A. */ dgbcon_(norm, n, kl, ku, &afb[afb_offset], ldafb, &ipiv[1], &anorm, rcond, &work[1], &iwork[1], info); /* Set INFO = N+1 if the matrix is singular to working precision. */ if (*rcond < dlamch_("Epsilon")) { *info = *n + 1; } /* Compute the solution matrix X. */ dlacpy_("Full", n, nrhs, &b[b_offset], ldb, &x[x_offset], ldx); dgbtrs_(trans, n, kl, ku, nrhs, &afb[afb_offset], ldafb, &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. */ dgbrfs_(trans, n, kl, ku, nrhs, &ab[ab_offset], ldab, &afb[afb_offset], ldafb, &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__3 = *n; for (i__ = 1; i__ <= i__3; ++i__) { x_ref(i__, j) = c__[i__] * x_ref(i__, j); /* L100: */ } /* L110: */ } i__1 = *nrhs; for (j = 1; j <= i__1; ++j) { ferr[j] /= colcnd; /* L120: */ } } } else if (rowequ) { i__1 = *nrhs; for (j = 1; j <= i__1; ++j) { i__3 = *n; for (i__ = 1; i__ <= i__3; ++i__) { x_ref(i__, j) = r__[i__] * x_ref(i__, j); /* L130: */ } /* L140: */ } i__1 = *nrhs; for (j = 1; j <= i__1; ++j) { ferr[j] /= rowcnd; /* L150: */ } } work[1] = rpvgrw; return 0; /* End of DGBSVX */ } /* dgbsvx_ */ #undef afb_ref #undef ab_ref #undef x_ref #undef b_ref