/*-------------------------------------------------------------------------*/
void
poly_sizeopt_run(poly_sizeopt_t *data, mpz_t ad, mpz_t p, mpz_t d)
{
double pol_norm;
double alpha_proj;
int status;
curr_poly_t *c = (curr_poly_t *)(data->internal);
mpz_set(c->gmp_d, d);
mpz_set(c->gmp_p, p);
mpz_neg(c->gmp_lina[0], c->gmp_d);
mpz_set(c->gmp_lina[1], c->gmp_p);
status = pol_expand(c, data->gmp_N, ad, p, d,
data->max_stage1_norm, data->degree);
if (status != 2) {
if (status == 0)
fprintf(stderr, "expand failed\n");
return;
}
optimize_initial(c, data->degree, &pol_norm, 0);
stage2_root_score(data->degree, c->gmp_a, 100, &alpha_proj, 1);
if (pol_norm * exp(alpha_proj) <= data->max_sizeopt_norm) {
data->callback(data->degree, c->gmp_a, c->gmp_lina,
pol_norm, alpha_proj,
data->callback_data);
}
}
/*-------------------------------------------------------------------------*/
static void
optimize(curr_poly_t *c, poly_stage2_t *data,
root_sieve_t *rs, assess_t *assess,
stage2_stat_t *stats)
{
int err;
double skewness;
double pol_norm;
double alpha_proj;
double log_max_norm_2 = log(data->max_norm_2);
profile_start(PROF_ALL);
while (1) {
err = read_a5pd(c, data);
if (err < 0) {
if (feof(data->infile))
break;
continue;
}
if (!pol_expand(c, data->gmp_N)) {
mpz_out_str(stdout, 10, c->gmp_a[5]);
fprintf(stderr, "expand failed\n");
continue;
}
profile_start(PROF_INITIAL_OPTIMIZE);
optimize_1(c, &skewness, &pol_norm, &alpha_proj);
profile_stop(PROF_INITIAL_OPTIMIZE);
if (pol_norm * exp(alpha_proj) > data->max_norm_1)
continue;
root_sieve_run(c, log_max_norm_2, data, rs, assess,
stats, skewness, pol_norm, alpha_proj);
}
profile_stop(PROF_ALL);
}
