def set_parameters(self, **kwargs):
r"""Set the algorithm parameters/arguments.
See Also
* :func:`niapy.algorithms.Algorithm.set_parameters`
"""
kwargs.pop('population_size', None)
Algorithm.set_parameters(self, population_size=1, **kwargs)
self.candidates = None
def set_parameters(self, population_size=20, alpha=1, beta_min=1, gamma=2, **kwargs):
r"""Set the parameters of the algorithm.
Args:
population_size (Optional[int]): Population size.
alpha (Optional[float]): Step size.
beta_min (Optional[float]): Minimum value of beta.
gamma (Optional[float]): Absorption coefficient.
kwargs (Dict[str, Any]): Additional arguments.
See Also:
* :func:`niapy.algorithms.Algorithm.set_parameters`
"""
Algorithm.set_parameters(self, population_size=population_size, **kwargs)
self.alpha = alpha
self.beta_min = beta_min
self.gamma = gamma
class AlgorithmBaseTestCase(TestCase):
r"""Test case for testing Algorithm class.
Date:
April 2019
Author:
Klemen Berkovič
Attributes:
seed (int): Starting seed of random generator.
rng (numpy.random.Generator): Random generator.
a (Algorithm): Algorithm to use for testing.
See Also:
* :class:`niapy.algorithms.Individual`
"""
def setUp(self):
self.seed = 1
self.rng = default_rng(self.seed)
self.a = Algorithm(seed=self.seed)
def test_algorithm_info(self):
r"""Check if method works fine."""
i = Algorithm.info()
self.assertIsNotNone(i)
def test_algorithm_getParameters(self):
r"""Check if method works fine."""
algo = Algorithm()
params = algo.get_parameters()
self.assertIsNotNone(params)
def test_init_population_numpy(self):
r"""Test if custom generation initialization works ok."""
a = Algorithm(population_size=10, initialization_function=init_pop_numpy)
t = Task(problem=MyProblem(dimension=20))
self.assertTrue(np.array_equal(np.zeros((10, t.dimension)), a.init_population(t)[0]))
def test_init_population_individual(self):
r"""Test if custom generation initialization works ok."""
a = Algorithm(population_size=10, initialization_function=init_pop_individual, individual_type=Individual)
t = Task(problem=MyProblem(dimension=20))
i = Individual(x=np.zeros(t.dimension), task=t)
pop, fpop, d = a.init_population(t)
for e in pop:
self.assertEqual(i, e)
def test_set_parameters(self):
self.a.set_parameters(t=None, a=20)
self.assertRaises(AttributeError, lambda: self.assertEqual(self.a.a, None))
def test_integers(self):
o = self.a.integers(low=10, high=20, size=[10, 10])
self.assertEqual(o.shape, (10, 10))
self.assertTrue(np.array_equal(self.rng.integers(10, 20, (10, 10)), o))
o = self.a.integers(low=10, high=20, size=(10, 5))
self.assertEqual(o.shape, (10, 5))
self.assertTrue(np.array_equal(self.rng.integers(10, 20, (10, 5)), o))
o = self.a.integers(low=10, high=20, size=10)
self.assertEqual(o.shape, (10,))
self.assertTrue(np.array_equal(self.rng.integers(10, 20, 10), o))
def test_standard_normal(self):
a = self.a.standard_normal([1, 2])
self.assertEqual(a.shape, (1, 2))
self.assertTrue(np.array_equal(self.rng.standard_normal((1, 2)), a))
a = self.a.standard_normal(1)
self.assertEqual(len(a), 1)
self.assertTrue(np.array_equal(self.rng.standard_normal(1), a))
a = self.a.standard_normal(2)
self.assertEqual(len(a), 2)
self.assertTrue(np.array_equal(self.rng.standard_normal(2), a))
a = self.a.standard_normal()
self.assertIsInstance(a, float)
self.assertTrue(np.array_equal(self.rng.standard_normal(), a))
def test_uniform(self):
a = self.a.uniform(-10, 10, [10, 10])
self.assertEqual(a.shape, (10, 10))
self.assertTrue(np.array_equal(self.rng.uniform(-10, 10, (10, 10)), a))
a = self.a.uniform(4, 10, (4, 10))
self.assertEqual(len(a), 4)
self.assertEqual(len(a[0]), 10)
self.assertTrue(np.array_equal(self.rng.uniform(4, 10, (4, 10)), a))
a = self.a.uniform(1, 4, 2)
self.assertEqual(len(a), 2)
self.assertTrue(np.array_equal(self.rng.uniform(1, 4, 2), a))
a = self.a.uniform(10, 100)
self.assertIsInstance(a, float)
self.assertEqual(self.rng.uniform(10, 100), a)
def test_normal(self):
a = self.a.normal(-10, 10, [10, 10])
self.assertEqual(a.shape, (10, 10))
self.assertTrue(np.array_equal(self.rng.normal(-10, 10, (10, 10)), a))
a = self.a.normal(4, 10, (4, 10))
self.assertEqual(len(a), 4)
self.assertEqual(len(a[0]), 10)
self.assertTrue(np.array_equal(self.rng.normal(4, 10, (4, 10)), a))
a = self.a.normal(1, 4, 2)
self.assertEqual(len(a), 2)
self.assertTrue(np.array_equal(self.rng.normal(1, 4, 2), a))
a = self.a.normal(10, 100)
self.assertIsInstance(a, float)
self.assertEqual(self.rng.normal(10, 100), a)
