def test_baselogger_can_write_to_stdout(self, capsys, simple_chromosomes):
logger = BaseLogger(target=None, stdout=True)
pop = Population(chromosomes=simple_chromosomes,
eval_function=lambda x: x)
pop.evaluate()
logger.log(pop)
read_stdout = [line for line in capsys.readouterr().out.split('\n') if line != '']
assert len(read_stdout) == len(pop)
def test_baselogger_works_via_evolution(self, tmpdir, capsys):
log_file = tmpdir.join('log.txt')
logger = BaseLogger(target=log_file, stdout=True)
pop = Population(chromosomes=range(10),
eval_function=lambda x: x,
logger=logger)
evo = (Evolution().survive(fraction=0.5).breed(
parent_picker=pick_random,
combiner=lambda mom, dad: (mom + dad) / 2 +
(random.random() - 0.5),
n_parents=2).log(foo='bar'))
_ = pop.evolve(evolution=evo, n=2)
# check characteristics of the file
with open(log_file, "r") as f:
read_file = [item.replace("\n", "") for item in f.readlines()]
# size of the log should be appropriate
assert len(read_file) == 2 * len(pop)
# bar needs to be in every single line
assert all(['bar' in row for row in read_file])
# check characteristics of stoud
read_stdout = [
line for line in capsys.readouterr().out.split('\n') if line != ''
]
assert len(read_stdout) == 2 * len(pop)
assert all(['bar' in row for row in read_stdout])
def test_baselogger_can_accept_kwargs(self, tmpdir, simple_chromosomes,
simple_evaluation_function):
log_file = tmpdir.join('log.txt')
logger = BaseLogger(target=log_file, stdout=False)
pop = Population(chromosomes=simple_chromosomes,
eval_function=simple_evaluation_function,
logger=logger)
# we should see that a file was created with an appropriate number of rows
pop.log(foo="bar")
with open(log_file, "r") as f:
assert len(f.readlines()) == len(simple_chromosomes)
assert all(["bar" in l for l in f.readlines()])
# we should see that a file was created with an appropriate number of rows
pop.log(foo="meh")
with open(log_file, "r") as f:
assert len(f.readlines()) == (2 * len(simple_chromosomes))
assert all(['meh' in l for l in f.readlines()[-10:]])
def __init__(self,
chromosomes: Iterable,
eval_function: Callable[..., float],
maximize: bool = True,
logger=None,
generation: int = 0,
intended_size: Optional[int] = None,
checkpoint_target: Optional[str] = None,
serializer=None):
self.id = str(uuid4())[:6]
self.documented_best = None
self.eval_function = eval_function
self.generation = generation
self.individuals = [
Individual(chromosome=chromosome) for chromosome in chromosomes
]
self.intended_size = intended_size or len(self.individuals)
self.maximize = maximize
self.logger = logger or BaseLogger()
self.serializer = serializer or SimpleSerializer(
target=checkpoint_target)
def test_baselogger_can_write_file_without_stdout(
self, tmpdir, capsys, simple_chromosomes,
simple_evaluation_function):
log_file = tmpdir.join('log.txt')
logger = BaseLogger(target=log_file, stdout=False)
pop = Population(chromosomes=simple_chromosomes,
eval_function=simple_evaluation_function,
logger=logger)
# we should see that a file was created with an appropriate number of rows
pop.log()
with open(log_file, "r") as f:
assert len(f.readlines()) == len(simple_chromosomes)
# we should see that a file was created with an appropriate number of rows
pop.log()
with open(log_file, "r") as f:
assert len(f.readlines()) == (2 * len(simple_chromosomes))
read_stdout = [
line for line in capsys.readouterr().out.split('\n') if line != ''
]
# there should be nothing printed
assert len(read_stdout) == 0
child_x = (mom[0] + dad[0]) / 2
child_y = (mom[1] + dad[1]) / 2
return child_x, child_y
def add_noise(chromosome, sigma):
"""
This is a function that will add some noise to the chromosome.
"""
new_x = chromosome[0] + (random.random() - 0.5) * sigma
new_y = chromosome[1] + (random.random() - 0.5) * sigma
return new_x, new_y
pop = Population(chromosomes=[random_start() for _ in range(200)],
eval_function=func_to_optimise,
maximize=True,
logger=BaseLogger(target="/tmp/evol.log"))
evo1 = (Evolution().survive(fraction=0.1).breed(
parent_picker=pick_random_parents,
combiner=make_child).mutate(mutate_function=add_noise, sigma=0.2).log())
evo2 = (Evolution().survive(n=10).breed(parent_picker=pick_random_parents,
combiner=make_child).mutate(
mutate_function=add_noise,
sigma=0.1).log())
evo3 = (Evolution().repeat(evo1, n=20).repeat(evo2, n=20))
pop = pop.evolve(evo3, n=3)
child_x = (mom[0] + dad[0]) / 2
child_y = (mom[1] + dad[1]) / 2
return child_x, child_y
def add_noise(chromosome, sigma):
"""
This is a function that will add some noise to the chromosome.
"""
new_x = chromosome[0] + (random.random() - 0.5) * sigma
new_y = chromosome[1] + (random.random() - 0.5) * sigma
return new_x, new_y
with NamedTemporaryFile() as tmpfile:
logger = BaseLogger(target=tmpfile.name)
pop = Population(chromosomes=[random_start() for _ in range(200)],
eval_function=func_to_optimise,
maximize=True, concurrent_workers=2)
evo1 = (Evolution()
.survive(fraction=0.1)
.breed(parent_picker=pick_random_parents, combiner=make_child)
.mutate(mutate_function=add_noise, sigma=0.2)
.callback(logger.log))
evo2 = (Evolution()
.survive(n=10)
.breed(parent_picker=pick_random_parents, combiner=make_child)
.mutate(mutate_function=add_noise, sigma=0.1)
.callback(logger.log))