def HGT_simulations_main__performance_rate(): common_classes = CommonClassesCreator() number_of_activations, population_factors, \ HGT_factors, mutation_factors = common_classes.get_simulation_variables() HGT_factor = 0.5 avg_performance_rate = list() for i in xrange(1000): avg_performance_rate.append((0, [0] * i)) common_classes.create_next_HGT_process(HGT_factor) for _ in xrange(number_of_activations): current_performance_rate = get_performance_rate_of_single_run( common_classes) performance_rate_with_same_generation = avg_performance_rate[len( current_performance_rate)] avg_performance_rate[len(current_performance_rate)] = ( performance_rate_with_same_generation[0] + 1, [ a + b for a, b in zip(performance_rate_with_same_generation[1], current_performance_rate) ]) for i in xrange(len(avg_performance_rate)): if avg_performance_rate[i][0] is not 0: average_rate_for_generation_i = [ avg_rate / avg_performance_rate[i][0] for avg_rate in avg_performance_rate[i][1] ] print "performance rate for " + str(i) + " generation is: " + str( average_rate_for_generation_i)
def HGT_simulations_main__population_factor(): common_classes = CommonClassesCreator() number_of_activations, population_factors, \ HGT_factors, mutation_factors = common_classes.get_simulation_variables() HGT_factor = 0.2 number_of_generations_per_factor = list() for population_factor in population_factors: generation_number = 0 common_classes.create_next_HGT_process(HGT_factor) for _ in xrange(number_of_activations): generation_number += get_number_of_generations_of_single_run( common_classes, population_factor) avg_number_of_generations = float( generation_number) / number_of_activations print "number_of_generations for " + str( population_factor) + " population is: " + str( avg_number_of_generations) number_of_generations_per_factor.append(avg_number_of_generations) print "number_of_generations_per_factor: " + str( number_of_generations_per_factor)
def HGT_simulations_main__HGT_factor(): common_classes = CommonClassesCreator() number_of_activations, population_factors, \ HGT_factors, mutation_factors = common_classes.get_simulation_variables() number_of_generations_per_factor = list() for HGT_factor in HGT_factors: generation_number = 0 common_classes.create_next_HGT_process(HGT_factor) for _ in xrange(number_of_activations): generation_number += get_number_of_generations_of_single_run(common_classes) avg_number_of_generations = float(generation_number) / number_of_activations print "number_of_generations for " + str(HGT_factor) + " factor is: " + str(avg_number_of_generations) number_of_generations_per_factor.append(avg_number_of_generations) print "number_of_generations_per_factor: " + str(number_of_generations_per_factor)
def HGT_simulations_main__performance_rate(): common_classes = CommonClassesCreator() number_of_activations, population_factors, \ HGT_factors, mutation_factors = common_classes.get_simulation_variables() HGT_factor = 0.5 avg_performance_rate = list() for i in xrange(1000): avg_performance_rate.append((0, [0]*i)) common_classes.create_next_HGT_process(HGT_factor) for _ in xrange(number_of_activations): current_performance_rate = get_performance_rate_of_single_run(common_classes) performance_rate_with_same_generation = avg_performance_rate[len(current_performance_rate)] avg_performance_rate[len(current_performance_rate)] = (performance_rate_with_same_generation[0]+1, [a+b for a, b in zip(performance_rate_with_same_generation[1],current_performance_rate)]) for i in xrange(len(avg_performance_rate)): if avg_performance_rate[i][0] is not 0: average_rate_for_generation_i = [avg_rate / avg_performance_rate[i][0] for avg_rate in avg_performance_rate[i][1]] print "performance rate for " + str(i) + " generation is: " + str(average_rate_for_generation_i)