Files
cantera/ext/f2c_math/dgbefa.c
2004-08-05 19:15:05 +00:00

254 lines
6.7 KiB
C

/* dgbefa.f -- translated by f2c (version 20031025).
You must link the resulting object file with libf2c:
on Microsoft Windows system, link with libf2c.lib;
on Linux or Unix systems, link with .../path/to/libf2c.a -lm
or, if you install libf2c.a in a standard place, with -lf2c -lm
-- in that order, at the end of the command line, as in
cc *.o -lf2c -lm
Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
http://www.netlib.org/f2c/libf2c.zip
*/
#ifdef _cpluscplus
extern "C" {
#endif
#include "f2c.h"
/* Table of constant values */
static integer c__1 = 1;
/* Subroutine */ int dgbfa_(doublereal *abd, integer *lda, integer *n,
integer *ml, integer *mu, integer *ipvt, integer *info)
{
/* System generated locals */
integer abd_dim1, abd_offset, i__1, i__2, i__3, i__4;
/* Local variables */
static integer i__, j, k, l, m;
static doublereal t;
static integer i0, j0, j1, lm, mm, ju, jz, kp1, nm1;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *), daxpy_(integer *, doublereal *, doublereal *, integer
*, doublereal *, integer *);
extern integer idamax_(integer *, doublereal *, integer *);
/* dgbfa factors a double precision band matrix by elimination. */
/* dgbfa is usually called by dgbco, but it can be called */
/* directly with a saving in time if rcond is not needed. */
/* on entry */
/* abd double precision(lda, n) */
/* contains the matrix in band storage. the columns */
/* of the matrix are stored in the columns of abd and */
/* the diagonals of the matrix are stored in rows */
/* ml+1 through 2*ml+mu+1 of abd . */
/* see the comments below for details. */
/* lda integer */
/* the leading dimension of the array abd . */
/* lda must be .ge. 2*ml + mu + 1 . */
/* n integer */
/* the order of the original matrix. */
/* ml integer */
/* number of diagonals below the main diagonal. */
/* 0 .le. ml .lt. n . */
/* mu integer */
/* number of diagonals above the main diagonal. */
/* 0 .le. mu .lt. n . */
/* more efficient if ml .le. mu . */
/* on return */
/* abd an upper triangular matrix in band storage and */
/* the multipliers which were used to obtain it. */
/* the factorization can be written a = l*u where */
/* l is a product of permutation and unit lower */
/* triangular matrices and u is upper triangular. */
/* ipvt integer(n) */
/* an integer vector of pivot indices. */
/* info integer */
/* = 0 normal value. */
/* = k if u(k,k) .eq. 0.0 . this is not an error */
/* condition for this subroutine, but it does */
/* indicate that dgbsl will divide by zero if */
/* called. use rcond in dgbco for a reliable */
/* indication of singularity. */
/* band storage */
/* if a is a band matrix, the following program segment */
/* will set up the input. */
/* ml = (band width below the diagonal) */
/* mu = (band width above the diagonal) */
/* m = ml + mu + 1 */
/* do 20 j = 1, n */
/* i1 = max0(1, j-mu) */
/* i2 = min0(n, j+ml) */
/* do 10 i = i1, i2 */
/* k = i - j + m */
/* abd(k,j) = a(i,j) */
/* 10 continue */
/* 20 continue */
/* this uses rows ml+1 through 2*ml+mu+1 of abd . */
/* in addition, the first ml rows in abd are used for */
/* elements generated during the triangularization. */
/* the total number of rows needed in abd is 2*ml+mu+1 . */
/* the ml+mu by ml+mu upper left triangle and the */
/* ml by ml lower right triangle are not referenced. */
/* linpack. this version dated 08/14/78 . */
/* cleve moler, university of new mexico, argonne national lab. */
/* subroutines and functions */
/* blas daxpy,dscal,idamax */
/* fortran max0,min0 */
/* internal variables */
/* Parameter adjustments */
abd_dim1 = *lda;
abd_offset = 1 + abd_dim1;
abd -= abd_offset;
--ipvt;
/* Function Body */
m = *ml + *mu + 1;
*info = 0;
/* zero initial fill-in columns */
j0 = *mu + 2;
j1 = min(*n,m) - 1;
if (j1 < j0) {
goto L30;
}
i__1 = j1;
for (jz = j0; jz <= i__1; ++jz) {
i0 = m + 1 - jz;
i__2 = *ml;
for (i__ = i0; i__ <= i__2; ++i__) {
abd[i__ + jz * abd_dim1] = 0.;
/* L10: */
}
/* L20: */
}
L30:
jz = j1;
ju = 0;
/* gaussian elimination with partial pivoting */
nm1 = *n - 1;
if (nm1 < 1) {
goto L130;
}
i__1 = nm1;
for (k = 1; k <= i__1; ++k) {
kp1 = k + 1;
/* zero next fill-in column */
++jz;
if (jz > *n) {
goto L50;
}
if (*ml < 1) {
goto L50;
}
i__2 = *ml;
for (i__ = 1; i__ <= i__2; ++i__) {
abd[i__ + jz * abd_dim1] = 0.;
/* L40: */
}
L50:
/* find l = pivot index */
/* Computing MIN */
i__2 = *ml, i__3 = *n - k;
lm = min(i__2,i__3);
i__2 = lm + 1;
l = idamax_(&i__2, &abd[m + k * abd_dim1], &c__1) + m - 1;
ipvt[k] = l + k - m;
/* zero pivot implies this column already triangularized */
if (abd[l + k * abd_dim1] == 0.) {
goto L100;
}
/* interchange if necessary */
if (l == m) {
goto L60;
}
t = abd[l + k * abd_dim1];
abd[l + k * abd_dim1] = abd[m + k * abd_dim1];
abd[m + k * abd_dim1] = t;
L60:
/* compute multipliers */
t = -1. / abd[m + k * abd_dim1];
dscal_(&lm, &t, &abd[m + 1 + k * abd_dim1], &c__1);
/* row elimination with column indexing */
/* Computing MIN */
/* Computing MAX */
i__3 = ju, i__4 = *mu + ipvt[k];
i__2 = max(i__3,i__4);
ju = min(i__2,*n);
mm = m;
if (ju < kp1) {
goto L90;
}
i__2 = ju;
for (j = kp1; j <= i__2; ++j) {
--l;
--mm;
t = abd[l + j * abd_dim1];
if (l == mm) {
goto L70;
}
abd[l + j * abd_dim1] = abd[mm + j * abd_dim1];
abd[mm + j * abd_dim1] = t;
L70:
daxpy_(&lm, &t, &abd[m + 1 + k * abd_dim1], &c__1, &abd[mm + 1 +
j * abd_dim1], &c__1);
/* L80: */
}
L90:
goto L110;
L100:
*info = k;
L110:
/* L120: */
;
}
L130:
ipvt[*n] = *n;
if (abd[m + *n * abd_dim1] == 0.) {
*info = *n;
}
return 0;
} /* dgbfa_ */
#ifdef _cpluscplus
}
#endif