nlopt_opt NLOPT_STDCALL nlopt_create(nlopt_algorithm algorithm, unsigned n)
{
nlopt_opt opt;
if (((int) algorithm) < 0 || algorithm >= NLOPT_NUM_ALGORITHMS)
return NULL;
opt = (nlopt_opt) malloc(sizeof(struct nlopt_opt_s));
if (opt) {
opt->algorithm = algorithm;
opt->n = n;
opt->f = NULL; opt->f_data = NULL; opt->pre = NULL;
opt->maximize = 0;
opt->munge_on_destroy = opt->munge_on_copy = NULL;
opt->lb = opt->ub = NULL;
opt->m = opt->m_alloc = 0;
opt->fc = NULL;
opt->p = opt->p_alloc = 0;
opt->h = NULL;
opt->stopval = -HUGE_VAL;
opt->ftol_rel = opt->ftol_abs = 0;
opt->xtol_rel = 0; opt->xtol_abs = NULL;
opt->maxeval = 0;
opt->maxtime = 0;
opt->force_stop = 0;
opt->force_stop_child = NULL;
opt->local_opt = NULL;
opt->stochastic_population = 0;
opt->vector_storage = 0;
opt->dx = NULL;
opt->work = NULL;
if (n > 0) {
opt->lb = (double *) malloc(sizeof(double) * (n));
if (!opt->lb) goto oom;
opt->ub = (double *) malloc(sizeof(double) * (n));
if (!opt->ub) goto oom;
opt->xtol_abs = (double *) malloc(sizeof(double) * (n));
if (!opt->xtol_abs) goto oom;
nlopt_set_lower_bounds1(opt, -HUGE_VAL);
nlopt_set_upper_bounds1(opt, +HUGE_VAL);
nlopt_set_xtol_abs1(opt, 0.0);
}
}
return opt;
oom:
nlopt_destroy(opt);
return NULL;
}
void minim_nlopt(density_t *ndft){
nlopt_opt opt;
double minf;
int i, status;
double *x;
nlopt_function_data function_data;
nlopt_par par;
x = (double *)malloc(ipf.npar*sizeof(double));
for(i = 0; i < ipf.npar; i++) x[i] = gsl_vector_get(ipf.gamma, i);
/* Here we choose the minimization method from NLOPT (check the
avaible algorithms at
http://ab-initio.mit.edu/wiki/index.php/NLopt_Algorithms)
and specify the dimension of the problem */
par.algorithm = 1; parse_int("nlopt_algorithm", &par.algorithm);
switch(par.algorithm){
case 1 :
opt = nlopt_create(NLOPT_LN_BOBYQA, ipf.npar);
if(myid == 0) printf("\n\n%s", nlopt_algorithm_name(NLOPT_LN_BOBYQA));
break;
case 2 :
opt = nlopt_create(NLOPT_GN_DIRECT, ipf.npar);
if(myid == 0) printf("\n\n%s", nlopt_algorithm_name(NLOPT_GN_DIRECT));
break;
case 3 :
opt = nlopt_create(NLOPT_GD_STOGO, ipf.npar);
if(myid == 0) printf("\n\n%s", nlopt_algorithm_name(NLOPT_GD_STOGO));
break;
case 4:
opt = nlopt_create(NLOPT_GN_ESCH, ipf.npar);
if(myid == 0) printf("\n\n%s", nlopt_algorithm_name(NLOPT_GN_ESCH));
break;
default :
if(myid == 0) printf("\n\nWARNING: wrong choice for the NLOPT algorithm\nTHe optimization will start with the default algorithm:");
opt = nlopt_create(NLOPT_GN_DIRECT_L, ipf.npar);
if(myid == 0) printf("\n%s", nlopt_algorithm_name(NLOPT_GN_DIRECT_L));
break;
}
nlopt_set_min_objective(opt, nlopt_gfunction, &function_data);
par.rel_tol = 1e-4; parse_double("nlopt_rel_tol", &par.rel_tol);
nlopt_set_xtol_rel(opt, par.rel_tol);
/* Set the lower and upper bounds of the optimization
to a single constant lb or ub respectively */
par.lb = -2.0; parse_double("nlopt_lb", &par.lb);
par.ub = 2.0; parse_double("nlopt_ub", &par.ub);
nlopt_set_lower_bounds1(opt, par.lb);
nlopt_set_upper_bounds1(opt, par.ub);
function_data.counter = 0;
function_data.ndft = density_get_val(ndft);
messages_basic("\n\n\nStarting the optimization.\n\n\n");
if ((status = nlopt_optimize(opt, x, &minf)) < 0){
if (myid == 0) printf("nlopt failed! status = %d\n", status);
parallel_end(EXIT_FAILURE);
}
if(myid == 0) printf("Success. status = %d, iterations = %d, minf = %.12lg\n", status, function_data.counter, minf);
if(myid == 0) {for(i = 0; i < ipf.npar; i++) printf("%.5f ", x[i]);}
nlopt_destroy(opt);
for(i = 0; i < ipf.npar; i++) gsl_vector_set(ipf.gamma, i, x[i]);
ipf_write(ipf, ipf_ref, "pot");
parallel_end(EXIT_SUCCESS);
}
