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qrfac_.c
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qrfac_.c
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/* qrfac.f -- translated by f2c (version 20020621).
You must link the resulting object file with the libraries:
-lf2c -lm (in that order)
*/
#include "minpack.h"
#include <math.h>
#include "minpackP.h"
__minpack_attr__
void __minpack_func__(qrfac)(const int *m, const int *n, real *a, const int *
lda, const int *pivot, int *ipvt, const int *lipvt, real *rdiag,
real *acnorm, real *wa)
{
/* Initialized data */
#define p05 .05
const int c__1 = 1;
/* System generated locals */
int a_dim1, a_offset, i__1, i__2, i__3;
real d__1, d__2, d__3;
/* Local variables */
int i__, j, k, jp1;
real sum;
int kmax;
real temp;
int minmn;
real epsmch;
real ajnorm;
/* ********** */
/* subroutine qrfac */
/* this subroutine uses householder transformations with column */
/* pivoting (optional) to compute a qr factorization of the */
/* m by n matrix a. that is, qrfac determines an orthogonal */
/* matrix q, a permutation matrix p, and an upper trapezoidal */
/* matrix r with diagonal elements of nonincreasing magnitude, */
/* such that a*p = q*r. the householder transformation for */
/* column k, k = 1,2,...,min(m,n), is of the form */
/* t */
/* i - (1/u(k))*u*u */
/* where u has zeros in the first k-1 positions. the form of */
/* this transformation and the method of pivoting first */
/* appeared in the corresponding linpack subroutine. */
/* the subroutine statement is */
/* subroutine qrfac(m,n,a,lda,pivot,ipvt,lipvt,rdiag,acnorm,wa) */
/* where */
/* m is a positive integer input variable set to the number */
/* of rows of a. */
/* n is a positive integer input variable set to the number */
/* of columns of a. */
/* a is an m by n array. on input a contains the matrix for */
/* which the qr factorization is to be computed. on output */
/* the strict upper trapezoidal part of a contains the strict */
/* upper trapezoidal part of r, and the lower trapezoidal */
/* part of a contains a factored form of q (the non-trivial */
/* elements of the u vectors described above). */
/* lda is a positive integer input variable not less than m */
/* which specifies the leading dimension of the array a. */
/* pivot is a logical input variable. if pivot is set true, */
/* then column pivoting is enforced. if pivot is set false, */
/* then no column pivoting is done. */
/* ipvt is an integer output array of length lipvt. ipvt */
/* defines the permutation matrix p such that a*p = q*r. */
/* column j of p is column ipvt(j) of the identity matrix. */
/* if pivot is false, ipvt is not referenced. */
/* lipvt is a positive integer input variable. if pivot is false, */
/* then lipvt may be as small as 1. if pivot is true, then */
/* lipvt must be at least n. */
/* rdiag is an output array of length n which contains the */
/* diagonal elements of r. */
/* acnorm is an output array of length n which contains the */
/* norms of the corresponding columns of the input matrix a. */
/* if this information is not needed, then acnorm can coincide */
/* with rdiag. */
/* wa is a work array of length n. if pivot is false, then wa */
/* can coincide with rdiag. */
/* subprograms called */
/* minpack-supplied ... dpmpar,enorm */
/* fortran-supplied ... dmax1,dsqrt,min0 */
/* argonne national laboratory. minpack project. march 1980. */
/* burton s. garbow, kenneth e. hillstrom, jorge j. more */
/* ********** */
/* Parameter adjustments */
--wa;
--acnorm;
--rdiag;
a_dim1 = *lda;
a_offset = 1 + a_dim1 * 1;
a -= a_offset;
--ipvt;
(void)lipvt;
/* Function Body */
/* epsmch is the machine precision. */
epsmch = __minpack_func__(dpmpar)(&c__1);
/* compute the initial column norms and initialize several arrays. */
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
acnorm[j] = __minpack_func__(enorm)(m, &a[j * a_dim1 + 1]);
rdiag[j] = acnorm[j];
wa[j] = rdiag[j];
if (*pivot) {
ipvt[j] = j;
}
/* L10: */
}
/* reduce a to r with householder transformations. */
minmn = min(*m,*n);
i__1 = minmn;
for (j = 1; j <= i__1; ++j) {
if (! (*pivot)) {
goto L40;
}
/* bring the column of largest norm into the pivot position. */
kmax = j;
i__2 = *n;
for (k = j; k <= i__2; ++k) {
if (rdiag[k] > rdiag[kmax]) {
kmax = k;
}
/* L20: */
}
if (kmax == j) {
goto L40;
}
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp = a[i__ + j * a_dim1];
a[i__ + j * a_dim1] = a[i__ + kmax * a_dim1];
a[i__ + kmax * a_dim1] = temp;
/* L30: */
}
rdiag[kmax] = rdiag[j];
wa[kmax] = wa[j];
k = ipvt[j];
ipvt[j] = ipvt[kmax];
ipvt[kmax] = k;
L40:
/* compute the householder transformation to reduce the */
/* j-th column of a to a multiple of the j-th unit vector. */
i__2 = *m - j + 1;
ajnorm = __minpack_func__(enorm)(&i__2, &a[j + j * a_dim1]);
if (ajnorm == 0.) {
goto L100;
}
if (a[j + j * a_dim1] < 0.) {
ajnorm = -ajnorm;
}
i__2 = *m;
for (i__ = j; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] /= ajnorm;
/* L50: */
}
a[j + j * a_dim1] += 1;
/* apply the transformation to the remaining columns */
/* and update the norms. */
jp1 = j + 1;
if (*n < jp1) {
goto L100;
}
i__2 = *n;
for (k = jp1; k <= i__2; ++k) {
sum = 0.;
i__3 = *m;
for (i__ = j; i__ <= i__3; ++i__) {
sum += a[i__ + j * a_dim1] * a[i__ + k * a_dim1];
/* L60: */
}
temp = sum / a[j + j * a_dim1];
i__3 = *m;
for (i__ = j; i__ <= i__3; ++i__) {
a[i__ + k * a_dim1] -= temp * a[i__ + j * a_dim1];
/* L70: */
}
if (! (*pivot) || rdiag[k] == 0.) {
goto L80;
}
temp = a[j + k * a_dim1] / rdiag[k];
/* Computing MAX */
/* Computing 2nd power */
d__3 = temp;
d__1 = 0., d__2 = 1 - d__3 * d__3;
rdiag[k] *= sqrt((max(d__1,d__2)));
/* Computing 2nd power */
d__1 = rdiag[k] / wa[k];
if (p05 * (d__1 * d__1) > epsmch) {
goto L80;
}
i__3 = *m - j;
rdiag[k] = __minpack_func__(enorm)(&i__3, &a[jp1 + k * a_dim1]);
wa[k] = rdiag[k];
L80:
/* L90: */
;
}
L100:
rdiag[j] = -ajnorm;
/* L110: */
}
return;
/* last card of subroutine qrfac. */
} /* qrfac_ */