def test_simulated_annealing_runtime(self):
import simulations.turkish_vowel_harmony as current_simulation
configurations.load_configurations_from_dict(
current_simulation.configurations_dict)
self.initialise_segment_table('turkish_segment_table.txt')
initial_hmm = None
initial_rule_set = None
initial_hypothesis = Hypothesis.create_initial_hypothesis(
current_simulation.data, initial_hmm, initial_rule_set)
target_tuple = current_simulation.target_tuple
data = current_simulation.data
target_rule_set = RuleSet.load_form_flat_list(target_tuple[1])
target_hypothesis = Hypothesis.create_hypothesis(
HMM(target_tuple[0]), target_rule_set, data)
target_energy = target_hypothesis.get_energy()
simulated_annealing = SimulatedAnnealing(initial_hypothesis,
target_energy)
simulated_annealing.before_loop()
# mutate hypothesis for some time before measuring steps
for i in range(500):
simulated_annealing.make_step()
@timeit_best_of_N
def make_step_profiled():
simulated_annealing.make_step()
make_step_profiled()
def init_target_hypothesis(self):
target_tuple = self.simulation.target_tuple
target_rule_set = RuleSet.load_form_flat_list(target_tuple[1])
target_hypothesis = Hypothesis.create_hypothesis(
HMM(deepcopy(target_tuple[0])), target_rule_set)
target_energy = target_hypothesis.get_energy()
self.logger.info('Target hypothesis:')
log_hypothesis(target_hypothesis, self.logger.info)
self.logger.info('Target energy: {}'.format(target_energy))
self.logger.info('Target hypothesis energy signature: {}'.format(
target_hypothesis.get_recent_energy_signature()))
return target_hypothesis, target_energy
