nu = 20
strength = 0.5
lambda_ = 7
max_age = 10
for _ in range(1):
darwin = ugp4.Darwin(
constraints=library,
operators=operators,
mu=mu,
nu=nu,
lambda_=lambda_,
strength=strength,
max_age=max_age,
)
# Evolve____________________________________________________________________________________________________________
darwin.evolve()
logging.bare("This is the final population:")
for individual in darwin.population:
ugp4.print_individual(individual)
ugp4.logging.bare(individual.fitness)
ugp4.logging.bare("")
# Print best individuals
logging.bare("These are the best ever individuals:")
ugp4.print_individual(darwin.archive.individuals, plot=True)
ugp4.logging.log_cpu(ugp4.logging.INFO, "Program completed")
sys.exit(0)
mu = 10
nu = 20
strength = 0.7
lambda_ = 7
max_age = 10
darwin = ugp4.Darwin(
constraints=library,
operators=operators,
mu=mu,
nu=nu,
lambda_=lambda_,
strength=strength,
max_age=max_age,
)
# Evolve and print individuals in population
darwin.evolve()
logging.bare("This is the final population:")
for individual in darwin.population:
msg = f"Solution {str(individual.id)} "
ugp4.print_individual(individual, msg=msg, plot=False, score=True)
# Print best individuals
ugp4.print_individual(darwin.archive.individuals,
msg="These are the best ever individuals:",
plot=False)
ugp4.logging.log_cpu(ugp4.logging.INFO, "Program completed")
sys.exit(0)
operators += ugp4.GenOperator(ugp4.macro_pool_one_cut_point_crossover, 2)
operators += ugp4.GenOperator(ugp4.macro_pool_uniform_crossover, 2)
# Create the object that will manage the evolution
mu = 10
nu = 20
strength = 0.7
lambda_ = 7
max_age = 10
darwin = ugp4.Darwin(
constraints=library,
operators=operators,
mu=mu,
nu=nu,
lambda_=lambda_,
strength=strength,
max_age=max_age,
)
# Evolve
darwin.evolve()
# Print best individuals
logging.bare("These are the best ever individuals:")
for i in darwin.archive.individuals:
print(f"{i}\n\n\n")
ugp4.logging.log_cpu(ugp4.logging.INFO, "Program completed")
sys.exit(0)
mu = 10
nu = 20
strength = 0.7
lambda_ = 7
max_age = 10
darwin = ugp4.Darwin(
constraints=library,
operators=operators,
mu=mu,
nu=nu,
lambda_=lambda_,
strength=strength,
max_age=max_age,
)
# Evolve and print individuals in population
darwin.evolve()
logging.bare("Final population:")
for individual in darwin.population:
msg = f"Solution {str(individual.id)} "
ugp4.print_individual(individual, msg=msg, plot=False)
ugp4.logging.bare(f"Fitness: {individual.fitness}")
ugp4.logging.bare("")
# Print best individuals
ugp4.print_individual(darwin.archive.individuals, msg="Archive:", plot=True, score=True)
ugp4.logging.log_cpu(ugp4.logging.INFO, "Program completed")
sys.exit(0)
