C++ Population::compute_statistics方法代码示例

//.........这里部分代码省略.........
				// sort according to fitness (error)
				//P->sort(i,tree_comp_fitness);

				///printf("\n\n***********Generation %d after genetic operations (not sorted, new trees marked with f9.999999E+99)************\n", i-1);
				//P->print_population_without_parameters(i-1);
				//printf("\n***********************************************************************\n");

				// update the best individual - structure and complete tree (for PARAMETER INHERITANCE)
				//P->update_ext_archive();
				//---------------------------------------------------------------------------------------------

				// sort according to F
				// VITAL! Both populations must be sorted, trees[] and complete_trees[]...
				P->sort(i,tree_comp_F);

				///printf("\n\n***********Generation %d after genetic operations (not sorted, new trees marked with f9.999999E+99)************\n", i-1);
				///P->print_population_without_parameters(i-1);
				///printf("\n***********************************************************************\n");

				// update the best individual - structure and complete tree (for PARAMETER INHERITANCE)
				P->update_ext_archive();

				// compute elapsed time
				elapsed_time = (int)(P->compute_time(start, finish, &delta_t));

				if (VERBOSE) {
					// print elapsed time
					cout << "Elapsed time: " << elapsed_time << " sec";  //total seconds

					// print out the best member - population WITHOUT parameters
					P->print_population_without_parameters(i);

					// print out the best member - population WITH parameters
					P->print_population_with_parameters(i);
				}

				// compute statistical data relating to population (vital if data is shared through populations)
				// IT's REALLY IMPORTANT that this function is executed after evaluate and sort,
				// as evaluate uses statistical data referring to the previous generation
				P->compute_statistics();

				// evaluate termination condition
				check_end=P->terminate(p_parameters->threshold);
				last_gen = i;

				// for the split data set, re-tune and re-evaluate the individuals on the merged data set
				if (p_parameters->split) {
					if ((check_end) || (i==p_parameters->G)) {
						cout << "\nBest Individual re-tuning and re-evaluation on the whole dataset" << endl;
						P->split_data(p_parameters, p_problem,last_gen,last_gen);
						P->evaluate(i,p_parameters->G);
					}
				}

				// PRINT TO FILE OPERATIONS (in case of crash, data is saved)  -------------------------
				// print to file (if termination criterion met, it closes the stream of data to file )
				pop_reporter.stats2file(p_parameters, P, DIR_RUN_K, i, check_end);
				// write the test-points (training set), and the corresponding values of g_obj and the best individual (only one)
				pop_reporter.points2file(p_parameters, p_problem, P, DIR_RUN_K, i, check_end, start, finish, delta_t,SEED[cur_run]);
				// write best individual's expression ATTENZIONE: cambiato il 7/4/2015... da verificare
				pop_reporter.update_best2file_build(P, DIR_RUN_K, i, check_end); //old function: update_best2file(P, DIR_RUN_K, i, check_end);
				// update the list of the best-so-far individuals (see elite or archive) - truncation! ATTENZIONE: cambiato il 7/4/2015... da verificare
				pop_reporter.archive2file_build(P, DIR_RUN_K, i, check_end);  //old function: objective_table2file(P, DIR_RUN_K, i, check_end);
				// update no of tree evaluations
				pop_reporter.n_tree_eval2file(P, DIR_RUN_K, i, check_end);
				// -------------------------------------------------------------------------------------

				if (check_end)
					break;
			}

			# pragma omp critical
			{
				cout << "Elapsed time to complete run " << cur_run+1 << ": " << elapsed_time << " sec" << endl;  //total seconds
				//termination criterion satisfied
				if (check_end) {
					cout << "Termination criterion satisfied (RMSE < " << p_parameters->threshold << ")." << endl;
					cout << "Possible solution: " << endl;
					P->print_population_with_parameters(last_gen);
					cout << "Check latest_archive.txt for solutions\n" << endl;
				}
				else {
					P->print_population_with_parameters(last_gen);
				}
			}

			// just for test
			//P->get_tree_derivative_given_norm_vector(problem, P->complete_trees[0]);

			/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////


			// write node statistics to file
			pop_reporter.node_stats2file(p_parameters, P, DIR_RUN_K);

			// end - free memory allocated to Population
			delete P;


}