void POMSolver::solve(Room *room,
Vector<scalar_t> *prior,
Vector<ProbaView *> *views,
- Vector<scalar_t> *proba_presence,
+ Vector<scalar_t> *result_proba_presence,
int nb_frame,
char *convergence_file_format) {
scalar_t e = 0;
for(int i = 0; i < room->nb_positions(); i++) {
- scalar_t np = global_smoothing_coefficient * proba_absence[i] + (1 - global_smoothing_coefficient) / (1 + exp(log_prior_ratio[i] + sum[i]));
+ scalar_t np = global_smoothing_coefficient * proba_absence[i] +
+ (1 - global_smoothing_coefficient) / (1 + exp(log_prior_ratio[i] + sum[i]));
if(abs(proba_absence[i] - np) > e) e = abs(proba_absence[i] - np);
proba_absence[i] = np;
}
if(convergence_file_format) {
char buffer[buffer_size];
- for(int p = 0; p < room->nb_positions(); p++) (*proba_presence)[p] = 1 - proba_absence[p];
+ for(int p = 0; p < room->nb_positions(); p++) {
+ (*result_proba_presence)[p] = 1 - proba_absence[p];
+ }
+
for(int c = 0; c < room->nb_cameras(); c++) {
pomsprintf(buffer, buffer_size, convergence_file_format, c, nb_frame, it);
cout << "Saving " << buffer << "\n"; cout.flush();
- room->save_stochastic_view(buffer, c, (*views)[c], proba_presence);
+ room->save_stochastic_view(buffer, c, (*views)[c], result_proba_presence);
}
}
}
- for(int p = 0; p < room->nb_positions(); p++) (*proba_presence)[p] = 1 - proba_absence[p];
+ for(int p = 0; p < room->nb_positions(); p++) {
+ (*result_proba_presence)[p] = 1 - proba_absence[p];
+ }
}