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/* lmpar.f -- translated by f2c (version 20020621).
You must link the resulting object file with the libraries:
-lf2c -lm (in that order)
*/
#include "cminpack.h"
#include <math.h>
#define real __cminpack_real__
#define min(a,b) ((a) <= (b) ? (a) : (b))
#define max(a,b) ((a) >= (b) ? (a) : (b))
__cminpack_attr__
void __cminpack_func__(lmpar)(int n, real *r, int ldr,
const int *ipvt, const real *diag, const real *qtb, real delta,
real *par, real *x, real *sdiag, real *wa1,
real *wa2)
{
/* Initialized data */
#define p1 .1
#define p001 .001
/* System generated locals */
real d1, d2;
/* Local variables */
int i, j, k, l;
real fp;
real sum, parc, parl;
int iter;
real temp, paru, dwarf;
int nsing;
real gnorm;
real dxnorm;
/* ********** */
/* subroutine lmpar */
/* given an m by n matrix a, an n by n nonsingular diagonal */
/* matrix d, an m-vector b, and a positive number delta, */
/* the problem is to determine a value for the parameter */
/* par such that if x solves the system */
/* a*x = b , sqrt(par)*d*x = 0 , */
/* in the least squares sense, and dxnorm is the euclidean */
/* norm of d*x, then either par is zero and */
/* (dxnorm-delta) .le. 0.1*delta , */
/* or par is positive and */
/* abs(dxnorm-delta) .le. 0.1*delta . */
/* this subroutine completes the solution of the problem */
/* if it is provided with the necessary information from the */
/* qr factorization, with column pivoting, of a. that is, if */
/* a*p = q*r, where p is a permutation matrix, q has orthogonal */
/* columns, and r is an upper triangular matrix with diagonal */
/* elements of nonincreasing magnitude, then lmpar expects */
/* the full upper triangle of r, the permutation matrix p, */
/* and the first n components of (q transpose)*b. on output */
/* lmpar also provides an upper triangular matrix s such that */
/* t t t */
/* p *(a *a + par*d*d)*p = s *s . */
/* s is employed within lmpar and may be of separate interest. */
/* only a few iterations are generally needed for convergence */
/* of the algorithm. if, however, the limit of 10 iterations */
/* is reached, then the output par will contain the best */
/* value obtained so far. */
/* the subroutine statement is */
/* subroutine lmpar(n,r,ldr,ipvt,diag,qtb,delta,par,x,sdiag, */
/* wa1,wa2) */
/* where */
/* n is a positive integer input variable set to the order of r. */
/* r is an n by n array. on input the full upper triangle */
/* must contain the full upper triangle of the matrix r. */
/* on output the full upper triangle is unaltered, and the */
/* strict lower triangle contains the strict upper triangle */
/* (transposed) of the upper triangular matrix s. */
/* ldr is a positive integer input variable not less than n */
/* which specifies the leading dimension of the array r. */
/* ipvt is an integer input array of length n which defines the */
/* permutation matrix p such that a*p = q*r. column j of p */
/* is column ipvt(j) of the identity matrix. */
/* diag is an input array of length n which must contain the */
/* diagonal elements of the matrix d. */
/* qtb is an input array of length n which must contain the first */
/* n elements of the vector (q transpose)*b. */
/* delta is a positive input variable which specifies an upper */
/* bound on the euclidean norm of d*x. */
/* par is a nonnegative variable. on input par contains an */
/* initial estimate of the levenberg-marquardt parameter. */
/* on output par contains the final estimate. */
/* x is an output array of length n which contains the least */
/* squares solution of the system a*x = b, sqrt(par)*d*x = 0, */
/* for the output par. */
/* sdiag is an output array of length n which contains the */
/* diagonal elements of the upper triangular matrix s. */
/* wa1 and wa2 are work arrays of length n. */
/* subprograms called */
/* minpack-supplied ... dpmpar,enorm,qrsolv */
/* fortran-supplied ... dabs,dmax1,dmin1,dsqrt */
/* argonne national laboratory. minpack project. march 1980. */
/* burton s. garbow, kenneth e. hillstrom, jorge j. more */
/* ********** */
/* dwarf is the smallest positive magnitude. */
dwarf = __cminpack_func__(dpmpar)(2);
/* compute and store in x the gauss-newton direction. if the */
/* jacobian is rank-deficient, obtain a least squares solution. */
nsing = n;
for (j = 0; j < n; ++j) {
wa1[j] = qtb[j];
if (r[j + j * ldr] == 0. && nsing == n) {
nsing = j;
}
if (nsing < n) {
wa1[j] = 0.;
}
/* L10: */
}
if (nsing >= 1) {
for (k = 1; k <= nsing; ++k) {
j = nsing - k;
wa1[j] /= r[j + j * ldr];
temp = wa1[j];
if (j >= 1) {
for (i = 0; i < j; ++i) {
wa1[i] -= r[i + j * ldr] * temp;
}
}
}
}
for (j = 0; j < n; ++j) {
l = ipvt[j]-1;
x[l] = wa1[j];
}
/* initialize the iteration counter. */
/* evaluate the function at the origin, and test */
/* for acceptance of the gauss-newton direction. */
iter = 0;
for (j = 0; j < n; ++j) {
wa2[j] = diag[j] * x[j];
}
dxnorm = __cminpack_func__(enorm)(n, wa2);
fp = dxnorm - delta;
if (fp <= p1 * delta) {
goto TERMINATE;
}
/* if the jacobian is not rank deficient, the newton */
/* step provides a lower bound, parl, for the zero of */
/* the function. otherwise set this bound to zero. */
parl = 0.;
if (nsing >= n) {
for (j = 0; j < n; ++j) {
l = ipvt[j]-1;
wa1[j] = diag[l] * (wa2[l] / dxnorm);
}
for (j = 0; j < n; ++j) {
sum = 0.;
if (j >= 1) {
for (i = 0; i < j; ++i) {
sum += r[i + j * ldr] * wa1[i];
}
}
wa1[j] = (wa1[j] - sum) / r[j + j * ldr];
}
temp = __cminpack_func__(enorm)(n, wa1);
parl = fp / delta / temp / temp;
}
/* calculate an upper bound, paru, for the zero of the function. */
for (j = 0; j < n; ++j) {
sum = 0.;
for (i = 0; i <= j; ++i) {
sum += r[i + j * ldr] * qtb[i];
}
l = ipvt[j]-1;
wa1[j] = sum / diag[l];
}
gnorm = __cminpack_func__(enorm)(n, wa1);
paru = gnorm / delta;
if (paru == 0.) {
paru = dwarf / min(delta,(real)p1);
}
/* if the input par lies outside of the interval (parl,paru), */
/* set par to the closer endpoint. */
*par = max(*par,parl);
*par = min(*par,paru);
if (*par == 0.) {
*par = gnorm / dxnorm;
}
/* beginning of an iteration. */
for (;;) {
++iter;
/* evaluate the function at the current value of par. */
if (*par == 0.) {
/* Computing MAX */
d1 = dwarf, d2 = p001 * paru;
*par = max(d1,d2);
}
temp = sqrt(*par);
for (j = 0; j < n; ++j) {
wa1[j] = temp * diag[j];
}
__cminpack_func__(qrsolv)(n, r, ldr, ipvt, wa1, qtb, x, sdiag, wa2);
for (j = 0; j < n; ++j) {
wa2[j] = diag[j] * x[j];
}
dxnorm = __cminpack_func__(enorm)(n, wa2);
temp = fp;
fp = dxnorm - delta;
/* if the function is small enough, accept the current value */
/* of par. also test for the exceptional cases where parl */
/* is zero or the number of iterations has reached 10. */
if (fabs(fp) <= p1 * delta || (parl == 0. && fp <= temp && temp < 0.) || iter == 10) {
goto TERMINATE;
}
/* compute the newton correction. */
for (j = 0; j < n; ++j) {
l = ipvt[j]-1;
wa1[j] = diag[l] * (wa2[l] / dxnorm);
}
for (j = 0; j < n; ++j) {
wa1[j] /= sdiag[j];
temp = wa1[j];
if (n > j+1) {
for (i = j+1; i < n; ++i) {
wa1[i] -= r[i + j * ldr] * temp;
}
}
}
temp = __cminpack_func__(enorm)(n, wa1);
parc = fp / delta / temp / temp;
/* depending on the sign of the function, update parl or paru. */
if (fp > 0.) {
parl = max(parl,*par);
}
if (fp < 0.) {
paru = min(paru,*par);
}
/* compute an improved estimate for par. */
/* Computing MAX */
d1 = parl, d2 = *par + parc;
*par = max(d1,d2);
/* end of an iteration. */
}
TERMINATE:
/* termination. */
if (iter == 0) {
*par = 0.;
}
/* last card of subroutine lmpar. */
} /* lmpar_ */
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