def generate(seed_generation):
"""
Given a seed generation will return a new generation of candidate
solutions assuming the cantus_firmus and other settings in the closure.
"""
length = len(seed_generation)
# Keep the fittest 50%
new_generation = seed_generation[:length / 2]
# Breed the remaining 50% using roulette wheel selection
offspring = []
while len(offspring) < length / 2:
mum = ga.roulette_wheel_selection(seed_generation)
dad = ga.roulette_wheel_selection(seed_generation)
children = mum.breed(dad)
offspring.extend(children)
# Mutate
for genome in offspring:
genome.mutate(mutation_range, mutation_rate, cantus_firmus)
# Ensure the new generation is the right length
new_generation.extend(offspring)
new_generation = new_generation[:length]
return new_generation
def generate(seed_generation):
"""
Given a seed generation will return a new generation of candidate
solutions assuming the cantus_firmus and other settings in the closure.
"""
length = len(seed_generation)
# Keep the fittest 50%
new_generation = seed_generation[:length/2]
# Breed the remaining 50% using roulette wheel selection
offspring = []
while len(offspring) < length/2:
mum = ga.roulette_wheel_selection(seed_generation)
dad = ga.roulette_wheel_selection(seed_generation)
children = mum.breed(dad)
offspring.extend(children)
# Mutate
for genome in offspring:
genome.mutate(mutation_range, mutation_rate, cantus_firmus)
# Ensure the new generation is the right length
new_generation.extend(offspring)
new_generation = new_generation[:length]
return new_generation
def test_returns_genome(self):
"""
Ensures that the roulette wheel returns a selected genome.
"""
class Genome(object):
"""
A simple representation of a genome.
"""
def __init__(self, fitness):
self.fitness = fitness
population = [Genome(random.uniform(0.1, 10.0)) for i in range(4)]
result = roulette_wheel_selection(population)
self.assertIsInstance(
result, Genome,
"Expected result of roulette_wheel_selection is not a Genome")
def test_returns_genome_with_unfit_population(self):
"""
Ensures that the roulette wheel returns a randomly selected genome if
none of them have a positive fitness score.
"""
class Genome(object):
"""
A simple representation of a genome.
"""
def __init__(self, fitness):
self.fitness = fitness
population = [Genome(0.0) for i in range(4)]
result = roulette_wheel_selection(population)
self.assertIsInstance(
result, Genome,
"Expected result of roulette_wheel_selection is not a Genome")
