def __run_solver(solver_name, timeout, handled_parameters, active_parameters_values):
pm = ParametersModule(FileModule.get_solver_file_path(solver_name),
Config.Filepaths.RESULTS_FOLDER,
Config.Defaults.USED_CORES_NUMBER,
handled_parameters,
active_parameters_values)
tl = ThreadsLauncher(pm, Config.Defaults.USED_CORES_NUMBER, timeout, 0.5,
functools.partial(UI.__save_solver_output_data,
Config.Filepaths.RESULTS_FOLDER))
tl.run()
UI.__process_results(tl.get_results(), timeout)
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
def _find_random_point(self):
random_parameters_module = RandomParametersModule(self._solver_file_path,
self._cnf_file_path,
self._reports_folder_path,
self._max_threads_number,
self._handled_parameters_indexes,
self._start_parameters_values,
10)
thread_launcher = ThreadsLauncher(random_parameters_module,
self._max_threads_number,
# максимально допустимое время не более чем в 1.5 раза хуже стартового
self._best_results[0][1]*1.5,
self._THREAD_LAUNCHER_SLEEPING_TIME,
functools.partial(AnnealingExperiment.__check_random_params_on_tabu,
self),
functools.partial(AnnealingExperiment.__handle_random_result,
self,
random_parameters_module),
functools.partial(SimpleExperiment._save_solver_output_data,
self,
self._reports_folder_path))
thread_launcher.run()
