def _get_solver_timeout(self):
parameters_module = ParametersModule(self._solver_file_path,
self._cnf_file_path,
self._reports_folder_path,
self._max_threads_number,
self._handled_parameters_indexes,
self._start_parameters_values,
0,
0)
return Threads_Launcher.run_solver(parameters_module.get_parameters_list())
def _get_default_parameters_values(self):
parameters_module = ParametersModule(self._solver_file_path,
self._cnf_file_path,
self._reports_folder_path,
self._max_threads_number,
self._handled_parameters_indexes,
self._start_parameters_values,
0,
0)
parameters_module.get_parameters_list()
return parameters_module.get_last_handled_parameters_values()
def _start_sub_experiment(self):
self._tabued_number = 0
self._best_results.append((None, None))
if self._best_results[len(self._best_results)-2][0] is not None:
start_params_vals = self._best_results[len(self._best_results)-2][0]
start_values_generator = StartValues(self.get_solver_file_name(),
self._handled_parameters_indexes,
self._start_parameters_values_file_path)
self._start_parameters_values = start_values_generator.create_start_values(start_params_vals)
else:
print("Local minimum found.")
return False
parameters_module = ParametersModule(self._solver_file_path,
self._cnf_file_path,
self._reports_folder_path,
self._max_threads_number,
self._handled_parameters_indexes,
self._start_parameters_values,
self._max_delta,
self._max_hamming_distance)
parameters_module.skip_start_values()
if self._tabu_module.add_area(parameters_module.get_area()):
thread_launcher = ThreadsLauncher(parameters_module,
self._max_threads_number,
self._solver_timeout,
self._THREAD_LAUNCHER_SLEEPING_TIME,
functools.partial(TabuExperiment._check_params_on_tabu,
self),
functools.partial(TabuExperiment.__handle_result,
self),
functools.partial(SimpleExperiment._save_solver_output_data,
self,
self._reports_folder_path))
thread_launcher.run()
self._number_of_experiments_produced += 1
best_time = self._best_results[len(self._best_results)-1][1]
print("Iteration №" + str(self._number_of_experiments_produced) + ". Best time = "
+ str(best_time) + ". Parameters values: "
+ str(self._best_results[len(self._best_results)-1][0]) + "\n"
+ "Tabued number: " + str(self._tabued_number))
self._solver_timeout = best_time
return self._number_of_experiments_produced < self._restarts_number
else:
return False