def test_attributes_chromosome_impl_lambdas():
# Create the Genetic algorithm
ga = GA()
# Set necessary attributes
ga.chromosome_length = 3
ga.generation_goal = 1
# Set gene_impl to None so it won't interfere
ga.gene_impl = None
# Set chromosome_impl
ga.chromosome_impl = lambda: [
random.randrange(1,100),
random.uniform(10,5),
random.choice(["up","down"])
]
# Evolve the genetic algorithm
ga.evolve()
def test_attributes_chromosome_impl_functions():
# Create the Genetic algorithm
ga = GA()
# Set necessary attributes
ga.chromosome_length = 3
ga.generation_goal = 1
# Create chromosome_impl user function
def user_chromosome_function():
chromosome_data = [
random.randrange(1,100),
random.uniform(10,5),
random.choice(["up","down"])
]
return chromosome_data
# Set the chromosome_impl
ga.chromosome_impl = user_chromosome_function
# Evolve the genetic algorithm
ga.evolve()