def test_summary_logger_can_accept_kwargs(self, tmpdir, simple_chromosomes, simple_evaluation_function):
log_file = tmpdir.join('log.txt')
logger = SummaryLogger(target=log_file, stdout=False)
pop = Population(chromosomes=simple_chromosomes,
eval_function=simple_evaluation_function)
pop.evaluate()
# lets make a first simple log
logger.log(pop, foo="bar", buzz="meh")
with open(log_file, "r") as f:
read_lines = f.readlines()
assert len(read_lines) == 1
first_line = read_lines[0]
assert "bar" in first_line
assert "meh" in first_line
last_entry = first_line.split(",")
assert len(last_entry) == 6
# lets log another one
logger.log(pop, buzz="moh")
with open(log_file, "r") as f:
read_lines = f.readlines()
assert len(read_lines) == 2
first_line = read_lines[-1]
assert "moh" in first_line
last_entry = first_line.split(",")
assert len(last_entry) == 5
def test_evaluate_func(self, simple_chromosomes):
def evaluation_function(x):
sleep(self.latency)
return x * x
pop = Population(simple_chromosomes, eval_function=evaluation_function)
t0 = time()
pop.evaluate()
t1 = time()
single_proc_time = t1 - t0
for individual in pop:
assert evaluation_function(
individual.chromosome) == individual.fitness
# with concurrency
pop = Population(simple_chromosomes,
eval_function=evaluation_function,
concurrent_workers=self.cpus)
t0 = time()
pop.evaluate()
t1 = time()
multi_proc_time = t1 - t0
for individual in pop:
assert evaluation_function(
individual.chromosome) == individual.fitness
if self.cpus > 1:
assert multi_proc_time < single_proc_time
def test_documented_best(self):
pop = Population(chromosomes=[100, 100, 100],
eval_function=lambda x: x * 2,
maximize=True)
assert pop.documented_best is None
pop.evaluate()
assert pop.documented_best.fitness == pop.current_best.fitness
pop.mutate(mutate_function=lambda x: x - 10, probability=1).evaluate()
assert pop.documented_best.fitness - 20 == pop.current_best.fitness
def test_mutate_resets(self):
pop = Population(chromosomes=[1, 1, 1],
eval_function=float,
maximize=True)
assert pop.current_best is None and pop.current_worst is None
pop.evaluate()
assert pop.current_best.fitness == 1 and pop.current_worst.fitness == 1
pop.mutate(lambda x: x)
assert pop.current_best is None and pop.current_worst is None
def test_current_worst(self, simple_chromosomes):
for maximize, worst in ((False, max(simple_chromosomes)),
(True, min(simple_chromosomes))):
pop = Population(chromosomes=simple_chromosomes,
eval_function=float,
maximize=maximize)
assert pop.current_worst is None
pop.evaluate()
assert pop.current_worst.chromosome == worst
def test_summarylogger_can_write_to_stdout(self, capsys, simple_chromosomes, simple_evaluation_function):
logger = SummaryLogger(target=None, stdout=True)
pop = Population(chromosomes=range(10),
eval_function=lambda x: x)
pop.evaluate()
logger.log(pop)
logger.log(pop)
read_stdout = [line for line in capsys.readouterr().out.split('\n') if line != '']
assert len(read_stdout) == 2
def test_evaluate_func(self, simple_chromosomes):
def evaluation_function(x):
return x * x
pop = Population(simple_chromosomes, eval_function=evaluation_function)
pop.evaluate()
for individual in pop:
assert evaluation_function(
individual.chromosome) == individual.fitness
def test_weights(self, simple_chromosomes, simple_evaluation_function):
for maximize in (False, True):
pop = Population(chromosomes=simple_chromosomes,
eval_function=simple_evaluation_function,
maximize=maximize)
with raises(RuntimeError):
assert min(pop._individual_weights) >= 0
pop.evaluate()
assert max(pop._individual_weights) == 1
assert min(pop._individual_weights) == 0
if maximize:
assert pop._individual_weights[0] == 0
else:
assert pop._individual_weights[0] == 1
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)
pop.evaluate()
# we should see that a file was created with an appropriate number of rows
logger.log(pop, foo="bar")
with open(log_file, "r") as f:
assert len(f.readlines()) == len(simple_chromosomes)
assert all(["bar" in line for line in f.readlines()])
# we should see that a file was created with an appropriate number of rows
logger.log(pop, foo="meh")
with open(log_file, "r") as f:
assert len(f.readlines()) == (2 * len(simple_chromosomes))
assert all(['meh' in line for line in f.readlines()[-10:]])
def test_baselogger_write_file_no_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)
# we should see that a file was created with an appropriate number of rows
pop.evaluate()
logger.log(pop)
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
logger.log(pop)
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
def test_summarylogger_write_file_mo_stdout(self, tmpdir, capsys):
log_file = tmpdir.join('log.txt')
logger = SummaryLogger(target=log_file, stdout=False)
pop = Population(chromosomes=range(10), eval_function=lambda x: x)
# we should see that a file was created with an appropriate number of rows
pop.evaluate()
logger.log(pop)
with open(log_file, "r") as f:
assert len(f.readlines()) == 1
# we should see that a file was created with an appropriate number of rows
logger.log(pop)
with open(log_file, "r") as f:
assert len(f.readlines()) == 2
read_stdout = [line for line in capsys.readouterr().out.split('\n') if line != '']
# there should be nothing printed
assert len(read_stdout) == 0
def test_evaluate_lambda(self, simple_chromosomes):
# without concurrency (note that I'm abusing a boolean operator to introduce some latency)
pop = Population(simple_chromosomes,
eval_function=lambda x: (sleep(self.latency) or x))
t0 = time()
pop.evaluate()
t1 = time()
single_proc_time = t1 - t0
for individual in pop:
assert individual.chromosome == individual.fitness
# with concurrency
pop = Population(simple_chromosomes,
eval_function=lambda x: (sleep(self.latency) or x),
concurrent_workers=self.cpus)
t0 = time()
pop.evaluate()
t1 = time()
multi_proc_time = t1 - t0
for individual in pop:
assert individual.chromosome == individual.fitness
if self.cpus > 1:
assert multi_proc_time < single_proc_time
def test_evaluate_lambda(self, simple_chromosomes):
pop = Population(simple_chromosomes, eval_function=lambda x: x)
pop.evaluate()
for individual in pop:
assert individual.chromosome == individual.fitness
