def setUp(self):
self.model = TEST_MODEL
self.representation = [r.id for r in self.model.reactions]
random = Random(SEED)
args = {"representation": self.representation}
self.solutions = BestSolutionArchive()
for _ in range(10000):
self.solutions.add(set_generator(random, args), random.random(), None, True, 100)
self.decoder = ReactionKnockoutDecoder(self.representation, self.model)
def setUp(self):
self.model = TEST_MODEL
self.representation = [r.id for r in self.model.reactions]
random = Random(SEED)
args = {"representation": self.representation}
self.solutions = BestSolutionArchive()
for _ in range(10000):
self.solutions.add(set_generator(random, args), random.random(), None, True, 100)
self.decoder = ReactionSetDecoder(self.representation, self.model)
def test_randint(self):
random = RandomGenerator()
lower = 0
upper = 10
for _ in range(10000):
self.assertGreaterEqual(random.randint(lower, upper), lower)
self.assertLessEqual(random.randint(lower, upper), upper)
lower = -10
upper = 100
for _ in range(10000):
self.assertGreaterEqual(random.randint(lower, upper), lower)
self.assertLessEqual(random.randint(lower, upper), upper)
lower = 5
upper = 21
for _ in range(10000):
self.assertGreaterEqual(random.randint(lower, upper), lower)
self.assertLessEqual(random.randint(lower, upper), upper)
lower = -5
upper = 5
for _ in range(10000):
self.assertGreaterEqual(random.randint(lower, upper), lower)
self.assertLessEqual(random.randint(lower, upper), upper)
def test_randint(self):
random = RandomGenerator()
lower = 0
upper = 10
for _ in range(10000):
assert random.randint(lower, upper) >= lower
assert random.randint(lower, upper) <= upper
lower = -10
upper = 100
for _ in range(10000):
assert random.randint(lower, upper) >= lower
assert random.randint(lower, upper) <= upper
lower = 5
upper = 21
for _ in range(10000):
assert random.randint(lower, upper) >= lower
assert random.randint(lower, upper) <= upper
lower = -5
upper = 5
for _ in range(10000):
assert random.randint(lower, upper) >= lower
assert random.randint(lower, upper) <= upper
def test_seeded_methods(self):
random = RandomGenerator()
random.seed(SEED)
value = random.random()
random.seed(SEED)
assert value == random.random()
random.seed(SEED)
value = random.randint(1, 10)
random.seed(SEED)
assert value == random.randint(1, 10)
random.seed(SEED)
population = [1, 2, 3, 4, 5]
value = random.sample(population, 2)
random.seed(SEED)
assert value == random.sample(population, 2)
random.seed(SEED)
value = random.uniform()
random.seed(SEED)
assert value == random.uniform()
def test_random(self):
random = RandomGenerator()
for _ in range(1000):
assert random.random() >= 0
assert random.random() <= 1
def test_seeded_methods(self):
random = RandomGenerator()
random.seed(self.seed)
value = random.random()
random.seed(self.seed)
self.assertEqual(value, random.random())
random.seed(self.seed)
value = random.randint(1, 10)
random.seed(self.seed)
self.assertEqual(value, random.randint(1, 10))
random.seed(self.seed)
population = [1, 2, 3, 4, 5]
value = random.sample(population, 2)
random.seed(self.seed)
self.assertEqual(value, random.sample(population, 2))
random.seed(self.seed)
value = random.uniform()
random.seed(self.seed)
self.assertEqual(value, random.uniform())
def test_random(self):
random = RandomGenerator()
for _ in range(1000):
self.assertGreaterEqual(random.random(), 0)
self.assertLessEqual(random.random(), 1)
def setUp(self):
self.model = TEST_MODEL
self.args = {}
self.args.setdefault('representation', [r.id for r in self.model.reactions])
self.random = Random()
class TestGenerators(unittest.TestCase):
mockup_evolutionary_algorithm = namedtuple("EA", ["bounder"])
def setUp(self):
self.model = TEST_MODEL
self.args = {}
self.args.setdefault('representation', [r.id for r in self.model.reactions])
self.random = Random()
def test_set_generator(self):
random = Random(SEED)
representation = ["a", "b", "c", "d", "e", "f"]
max_size = 5
variable_size = False
expected = [[0, 1, 2, 4, 5],
[0, 2, 3, 4, 5],
[0, 1, 2, 3, 5],
[1, 2, 3, 4, 5],
[0, 2, 3, 4, 5]]
for i in range(len(expected)):
candidate = set_generator(random, dict(representation=representation,
max_size=max_size,
variable_size=variable_size))
self.assertEqual(candidate, expected[i])
def test_multiple_chromossome_set_generator(self):
random = Random(SEED)
args = dict(keys=["test_key_1", "test_key_2"],
test_key_1_representation=["a1", "a2", "a3", "a4", "a5"],
test_key_2_representation=["b1", "b2", "b3", "b4", "b5", "b6", "b7"],
test_key_1_max_size=3,
test_key_2_max_size=5,
variable_size=False)
candidate = multiple_chromosome_set_generator(random, args)
self.assertEqual(len(candidate['test_key_1']), 3)
self.assertEqual(len(candidate['test_key_2']), 5)
def test_fixed_size_set_generator(self):
candidates_file = os.path.join(CURRENT_PATH, "data", "fix_size_candidates.pkl")
self.random.seed(SEED)
self.args.setdefault('variable_size', False)
candidates = []
self.args['max_size'] = 10
for _ in range(1000):
candidate = set_generator(self.random, self.args)
self.assertEqual(len(candidate), 10)
candidate = unique_set_generator(self.random, self.args)
self.assertEqual(len(candidate), 10)
candidates.append(candidate)
with open(candidates_file, 'rb') as in_file:
if six.PY3:
expected_candidates = pickle.load(in_file, encoding="latin1")
else:
expected_candidates = pickle.load(in_file)
self.assertEqual(candidates, expected_candidates)
self.args['max_size'] = 20
for _ in range(1000):
candidate = set_generator(self.random, self.args)
self.assertEqual(len(candidate), 20)
candidate = unique_set_generator(self.random, self.args)
self.assertEqual(len(candidate), 20)
def test_variable_size_set_generator(self):
candidates_file = os.path.join(CURRENT_PATH, "data", "variable_size_candidates.pkl")
self.args.setdefault('variable_size', True)
self.random.seed(SEED)
candidates = []
self.args['max_size'] = 10
for _ in range(1000):
candidate = set_generator(self.random, self.args)
self.assertLessEqual(len(candidate), 10)
candidate = unique_set_generator(self.random, self.args)
self.assertLessEqual(len(candidate), 10)
candidates.append(candidate)
with open(candidates_file, 'rb') as in_file:
if six.PY3:
expected_candidates = pickle.load(in_file, encoding="latin1")
else:
expected_candidates = pickle.load(in_file)
self.assertEqual(candidates, expected_candidates)
self.args['max_size'] = 20
for _ in range(1000):
candidate = set_generator(self.random, self.args)
self.assertLessEqual(len(candidate), 20)
candidate = unique_set_generator(self.random, self.args)
self.assertLessEqual(len(candidate), 20)
def test_fixed_size_linear_set_generator(self):
ec = self.mockup_evolutionary_algorithm(Bounder(-10, 10))
self.args.setdefault('variable_size', False)
self.args['max_size'] = 10
self.args['_ec'] = ec
for _ in range(1000):
candidate = linear_set_generator(self.random, self.args)
for i, v in six.iteritems(candidate):
self.assertIsInstance(i, (int, numpy.int64, numpy.int32))
self.assertIsInstance(v, float)
self.assertLessEqual(len(candidate), 10)