📄 lmdif.c
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#include "f2c.h"
#include "netlib.h"
extern double sqrt(double); /* #include <math.h> */
/* Table of constant values */
static integer c__1 = 1;
/* ====================================================================== */
/* NIST Guide to Available Math Software. */
/* Fullsource for module LMDIF from package MINPACK. */
/* Retrieved from NETLIB on Wed Jul 3 14:18:04 1996. */
/* ====================================================================== */
/* Subroutine */ void lmdif_(fcn, m, n, x, fvec, ftol, xtol, gtol, maxfev,
epsfcn, diag, mode, factor, nprint, info, nfev, fjac, ldfjac, ipvt,
qtf, wa1, wa2, wa3, wa4, errors)
void (*fcn) (integer*,integer*,doublereal*,doublereal*,integer*);
integer *m, *n;
doublereal *x, *fvec, *ftol, *xtol, *gtol;
integer *maxfev;
doublereal *epsfcn, *diag;
integer *mode;
doublereal *factor;
integer *nprint, *info, *nfev;
doublereal *fjac;
integer *ldfjac, *ipvt;
doublereal *qtf, *wa1, *wa2, *wa3, *wa4;
doublereal *errors;
{
/* Local variables */
static integer iter;
static doublereal temp, temp1, temp2;
static integer i, j, l, iflag;
static doublereal delta;
static doublereal ratio;
static doublereal fnorm, gnorm;
static doublereal pnorm, xnorm, fnorm1, actred, dirder, epsmch, prered;
static doublereal par, sum;
/* ********** */
/* subroutine lmdif */
/* the purpose of lmdif is to minimize the sum of the squares of */
/* m nonlinear functions in n variables by a modification of */
/* the levenberg-marquardt algorithm. the user must provide a */
/* subroutine which calculates the functions. the jacobian is */
/* then calculated by a forward-difference approximation. */
/* the subroutine statement is */
/* subroutine lmdif(fcn,m,n,x,fvec,ftol,xtol,gtol,maxfev,epsfcn, */
/* diag,mode,factor,nprint,info,nfev,fjac, */
/* ldfjac,ipvt,qtf,wa1,wa2,wa3,wa4) */
/* where */
/* fcn is the name of the user-supplied subroutine which */
/* calculates the functions. fcn must be declared */
/* in an external statement in the user calling */
/* program, and should be written as follows. */
/* subroutine fcn(m,n,x,fvec,iflag) */
/* integer m,n,iflag */
/* double precision x(n),fvec(m) */
/* ---------- */
/* calculate the functions at x and */
/* return this vector in fvec. */
/* ---------- */
/* return */
/* end */
/* the value of iflag should not be changed by fcn unless */
/* the user wants to terminate execution of lmdif. */
/* in this case set iflag to a negative integer. */
/* m is a positive integer input variable set to the number */
/* of functions. */
/* n is a positive integer input variable set to the number */
/* of variables. n must not exceed m. */
/* x is an array of length n. on input x must contain */
/* an initial estimate of the solution vector. on output x */
/* contains the final estimate of the solution vector. */
/* fvec is an output array of length m which contains */
/* the functions evaluated at the output x. */
/* ftol is a nonnegative input variable. termination */
/* occurs when both the actual and predicted relative */
/* reductions in the sum of squares are at most ftol. */
/* therefore, ftol measures the relative error desired */
/* in the sum of squares. */
/* xtol is a nonnegative input variable. termination */
/* occurs when the relative error between two consecutive */
/* iterates is at most xtol. therefore, xtol measures the */
/* relative error desired in the approximate solution. */
/* gtol is a nonnegative input variable. termination */
/* occurs when the cosine of the angle between fvec and */
/* any column of the jacobian is at most gtol in absolute */
/* value. therefore, gtol measures the orthogonality */
/* desired between the function vector and the columns */
/* of the jacobian. */
/* maxfev is a positive integer input variable. termination */
/* occurs when the number of calls to fcn is at least */
/* maxfev by the end of an iteration. */
/* epsfcn is an input variable used in determining a suitable */
/* step length for the forward-difference approximation. this */
/* approximation assumes that the relative errors in the */
/* functions are of the order of epsfcn. if epsfcn is less */
/* than the machine precision, it is assumed that the relative */
/* errors in the functions are of the order of the machine */
/* precision. */
/* diag is an array of length n. if mode = 1 (see */
/* below), diag is internally set. if mode = 2, diag */
/* must contain positive entries that serve as */
/* multiplicative scale factors for the variables. */
/* mode is an integer input variable. if mode = 1, the */
/* variables will be scaled internally. if mode = 2, */
/* the scaling is specified by the input diag. other */
/* values of mode are equivalent to mode = 1. */
/* factor is a positive input variable used in determining the */
/* initial step bound. this bound is set to the product of */
/* factor and the euclidean norm of diag*x if nonzero, or else */
/* to factor itself. in most cases factor should lie in the */
/* interval (.1,100.). 100. is a generally recommended value. */
/* nprint is an integer input variable that enables controlled */
/* printing of iterates if it is positive. in this case, */
/* fcn is called with iflag = 0 at the beginning of the first */
/* iteration and every nprint iterations thereafter and */
/* immediately prior to return, with x and fvec available */
/* for printing. if nprint is not positive, no special calls */
/* of fcn with iflag = 0 are made. */
/* info is an integer output variable. if the user has */
/* terminated execution, info is set to the (negative) */
/* value of iflag. see description of fcn. otherwise, */
/* info is set as follows. */
/* info = 0 improper input parameters. */
/* info = 1 both actual and predicted relative reductions */
/* in the sum of squares are at most ftol. */
/* info = 2 relative error between two consecutive iterates */
/* is at most xtol. */
/* info = 3 conditions for info = 1 and info = 2 both hold. */
/* info = 4 the cosine of the angle between fvec and any */
/* column of the jacobian is at most gtol in */
/* absolute value. */
/* info = 5 number of calls to fcn has reached or */
/* exceeded maxfev. */
/* info = 6 ftol is too small. no further reduction in */
/* the sum of squares is possible. */
/* info = 7 xtol is too small. no further improvement in */
/* the approximate solution x is possible. */
/* info = 8 gtol is too small. fvec is orthogonal to the */
/* columns of the jacobian to machine precision. */
/* nfev is an integer output variable set to the number of */
/* calls to fcn. */
/* fjac is an output m by n array. the upper n by n submatrix */
/* of fjac contains an upper triangular matrix r with */
/* diagonal elements of nonincreasing magnitude such that */
/* t t t */
/* p *(jac *jac)*p = r *r, */
/* where p is a permutation matrix and jac is the final */
/* calculated jacobian. column j of p is column ipvt(j) */
/* (see below) of the identity matrix. the lower trapezoidal */
/* part of fjac contains information generated during */
/* the computation of r. */
/* ldfjac is a positive integer input variable not less than m */
/* which specifies the leading dimension of the array fjac. */
/* ipvt is an integer output array of length n. ipvt */
/* defines a permutation matrix p such that jac*p = q*r, */
/* where jac is the final calculated jacobian, q is */
/* orthogonal (not stored), and r is upper triangular */
/* with diagonal elements of nonincreasing magnitude. */
/* column j of p is column ipvt(j) of the identity matrix. */
/* qtf is an output array of length n which contains */
/* the first n elements of the vector (q transpose)*fvec. */
/* wa1, wa2, and wa3 are work arrays of length n. */
/* wa4 is a work array of length m. */
/* argonne national laboratory. minpack project. march 1980. */
/* burton s. garbow, kenneth e. hillstrom, jorge j. more */
/* ********** */
/* epsmch is the machine precision. */
epsmch = dpmpar_(&c__1);
*info = 0;
iflag = 0;
*nfev = 0;
/* check the input parameters for errors. */
if (*n <= 0 || *m < *n || *ldfjac < *m || *ftol < 0. || *xtol < 0. || *gtol < 0. || *maxfev <= 0 || *factor <= 0.) {
goto L300;
}
if (*mode == 2)
for (j = 0; j < *n; ++j) {
if (diag[j] <= 0.) {
goto L300;
}
}
/* evaluate the function at the starting point */
/* and calculate its norm. */
iflag = 1;
(*fcn)(m, n, x, fvec, &iflag);
*nfev = 1;
if (iflag < 0) {
goto L300;
}
fnorm = enorm_(m, fvec);
errors[0] = fnorm;
/* initialize levenberg-marquardt parameter and iteration counter. */
par = 0.;
iter = 1;
/* beginning of the outer loop. */
L30:
/* calculate the jacobian matrix. */
iflag = 2;
fdjac2_(fcn, m, n, x, fvec, fjac, ldfjac, &iflag, epsfcn, wa4);
*nfev += *n;
if (iflag < 0) {
goto L300;
}
/* if requested, call fcn to enable printing of iterates. */
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