Нелинейная подгонка с использованием GSL

Поэтому я пытаюсь изменить какой-то код, который я нашел Вот чтобы соответствовать другой функции, но моя слегка измененная версия не сходится, и я не понимаю, почему.

Функция, которую я пытаюсь найти для наименьшего квадрата: «A + лямбда»log (t) + bЖурнал (т) ^ 2. Вот код

main.cpp

#include <stdlib.h>
#include <stdio.h>
#include <gsl/gsl_rng.h>
#include <gsl/gsl_randist.h>
#include <gsl/gsl_vector.h>
#include <gsl/gsl_blas.h>
#include <gsl/gsl_multifit_nlin.h>

#include "expfit.c"
#define N 40 // All "N"s are 40

void print_state (size_t iter, gsl_multifit_fdfsolver * s);//The prototype of some function

int main (void){

const gsl_multifit_fdfsolver_type *T; //pointer to a newly allocated instance of a solver of type T
gsl_multifit_fdfsolver *s;
int status;
unsigned int i, iter = 0;
const size_t n = N; //N number of observations
const size_t p = 3;//3 parameters

gsl_matrix *covar = gsl_matrix_alloc (p, p); // creates a pxp gsl_matrix
double y[N], sigma[N]; //declares vector variables that will hold the noise data. They are "N" long
struct data d = { n, y, sigma}; //Populates struct d with variables n, y and sigma. Struct data is defined in expfit.c
gsl_multifit_function_fdf f;
double x_init[3] = { 0, -.1, -.1 }; //initial x values !These are initial guesses to the solution!
gsl_vector_view x = gsl_vector_view_array (x_init, p);//view arrays allow one to litterally view elements of a certain array without modifying or created a copy of the original array. Essentially a pointer to the original data.
const gsl_rng_type * type; // pointer to a new random number generator type. RNG type will be assigned later
gsl_rng * r; //Pointer to a new RNG

gsl_rng_env_setup();

type = gsl_rng_default; //Assigns random number generator type
r = gsl_rng_alloc (type); // Allocates memory for new RNG of type "type"
f.f = &logb_f;
f.df = &logb_df;
f.fdf = &logb_fdf;
f.n = n;
f.p = p;
f.params = &d;for (i = 0; i < n; i++){// This is where the data is being generated

double t = i; // t is being redclared at each iteration for some reason wtf
if(t==0){//since log(0) is undefined, I said they equal 0 at t=0
y[i] = 2.0 -.5 * 0 - 0 + gsl_ran_gaussian (r, 0.1);
}else{
y[i] = 2.0 -.5 * log (t) - pow(log(t),2) + gsl_ran_gaussian (r, 0.1); //This is the noised up data
}
sigma[i] = .1; //not sure what this sigma does
printf ("data: %u %g %g\n", i, y[i], sigma[i]);//Printing out the data at each iteration
};

T = gsl_multifit_fdfsolver_lmsder; // Not sure what this is doing
s = gsl_multifit_fdfsolver_alloc (T, n, p);
gsl_multifit_fdfsolver_set (s, &f, &x.vector);

print_state (iter, s);

do{
iter++;
status = gsl_multifit_fdfsolver_iterate (s);

printf ("status = %s\n", gsl_strerror (status));

print_state (iter, s);

if (status)
break;

status = gsl_multifit_test_delta (s->dx, s->x, 1e-4, 1e-4);

}while (status == GSL_CONTINUE && iter < 500);

gsl_multifit_covar (s->J, 0.0, covar);

#define FIT(i) gsl_vector_get(s->x, i)
#define ERR(i) sqrt(gsl_matrix_get(covar,i,i))

{
double chi = gsl_blas_dnrm2(s->f);
double dof = n - p;
double c = GSL_MAX_DBL(1, chi / sqrt(dof));

printf("chisq/dof = %g\n",  pow(chi, 2.0) / dof);

printf ("A      = %.5f +/- %.5f\n", FIT(0), c*ERR(0));
printf ("lambda = %.5f +/- %.5f\n", FIT(1), c*ERR(1));
printf ("b      = %.5f +/- %.5f\n", FIT(2), c*ERR(2));
}

printf ("status = %s\n", gsl_strerror (status));

gsl_multifit_fdfsolver_free (s);
gsl_matrix_free (covar);
gsl_rng_free (r);
return 0;
}

void print_state (size_t iter, gsl_multifit_fdfsolver * s){
printf ("iter: %3zu x = % 15.8f % 15.8f % 15.8f ""|f(x)| = %g\n",
iter,
gsl_vector_get (s->x, 0),
gsl_vector_get (s->x, 1),
gsl_vector_get (s->x, 2),
gsl_blas_dnrm2 (s->f));
}

expfit.c

//
//  expfit.c
//  test
//
//  Created by [] on 4/11/15.
//  Copyright (c) 2015 []. All rights reserved.
//
#include <stdlib.h>
#include <stdio.h>
#include <math.h>
#include <gsl/gsl_rng.h>
#include <gsl/gsl_randist.h>
#include <gsl/gsl_vector.h>
#include <gsl/gsl_blas.h>
#include <gsl/gsl_multifit_nlin.h>

#include "expfit.h"
/* expfit.c -- model functions for exponential + background */

struct data {
size_t n;
double * y;
double * sigma;
};

int logb_f (const gsl_vector * x, void *data, gsl_vector * f){
size_t n = ((struct data *)data)->n;
double *y = ((struct data *)data)->y;
double *sigma = ((struct data *) data)->sigma;

double A = gsl_vector_get (x, 0);
double lambda = gsl_vector_get (x, 1);
double b = gsl_vector_get (x, 2);
double Yi;//will hold the value of the function to be stored into the vector set
double t;//time variable.
size_t i;//iterative variable

for (i = 0; i < n; i++){
/* Model Yi = A + lambda*log(i) + b*lambda*log(i)^2 */
t = i;

if(t==0){ //need if statement to bypass log(0) when t==0 since the value of log is undefined there
Yi = A + lambda * log(t) + b * pow(log(t),2);//function for t==0
}else{
Yi = A + lambda * log(t) + b * pow(log(t),2); // This is the function we used
}
gsl_vector_set (f, i, (Yi - y[i])/sigma[i]);
}

return GSL_SUCCESS;
}

int logb_df (const gsl_vector * x, void *data, gsl_matrix * J){
size_t n = ((struct data *)data)->n;
double *sigma = ((struct data *) data)->sigma;

//double A = gsl_vector_get (x, 0);
//double lambda = gsl_vector_get (x, 1);
//double b = gsl_vector_get(x,2);

size_t i;

for (i = 0; i < n; i++){
/* Jacobian matrix J(i,j) = dfi / dxj, */
/* where fi = (Yi - yi)/sigma[i],      */
/*       Yi = A + lambda*log(i) + b*log(i)^2  */
/* and the xj are the parameters (A,lambda,b) */
double t = i;
double s = sigma[i];

gsl_matrix_set (J, i, 0, 1/s);
gsl_matrix_set (J, i, 1, log(t)/s);
gsl_matrix_set (J, i, 2, pow(log(t),2)/s);
}
return GSL_SUCCESS;
}

int logb_fdf (const gsl_vector * x, void *data, gsl_vector * f, gsl_matrix * J){
logb_f (x, data, f);
logb_df (x, data, J);

return GSL_SUCCESS;
}

А вот и заголовочный файл, только если вы этого хотите

//
//  expfit.h
//  test
//
//  Created by [] on 4/11/15.
//  Copyright (c) 2015 []. All rights reserved.
//

#ifndef __test__expfit__
#define __test__expfit__

#include <stdio.h>

#endif /* defined(__test__expfit__) */