def test_to_dict(self):
operator = OnePointStrictLeafBiasedRecombinator()
variator = CrossoverVariator(operator, 10)
result = variator.to_dict()
self.assertIsInstance(result, dict)
self.assertEqual(operator.to_dict(), result["operator"])
self.assertEqual(variator.n_offspring, result["n_offspring"])
self.assertEqual(variator.n_way, result["n_way"])
self.assertEqual(variator.c_prob, result["c_prob"])
def test_from_dict(self):
test_cases = (CrossoverVariator, Variator, Serializable)
for cls in test_cases:
with self.subTest(name=cls.__name__):
operator = OnePointStrictLeafBiasedRecombinator()
variator = CrossoverVariator(operator, 3)
result = cls.from_dict(variator.to_dict())
self.assertIsInstance(result, CrossoverVariator)
self.assertEqual(variator.operator.__class__,
result.operator.__class__)
self.assertEqual(variator.n_offspring, result.n_offspring)
self.assertEqual(variator.n_way, result.n_way)
self.assertEqual(variator.c_prob, result.c_prob)
def test_to_dict(self):
cx_variator = CrossoverVariator(Recombinator(), 2)
pop_operator = CrossoverPopOperator([cx_variator])
result = pop_operator.to_dict()
self.assertIsInstance(result, dict)
self.assertEqual([v.to_dict() for v in pop_operator.variators],
result["variators"])
def test_variators(self):
cx_variator = CrossoverVariator(Recombinator(), 2)
mut_variator = MutationVariator(Mutator())
operator = CrossoverPopOperator([cx_variator, mut_variator])
with self.assertRaises(ValueError):
operator.variators = [cx_variator, mut_variator]
with self.assertRaises(TypeError):
operator.crossover_variator = mut_variator
def test_from_dict(self):
test_cases = (CrossoverPopOperator, PopulationOperator, Serializable)
for cls in test_cases:
with self.subTest(name=cls.__name__):
cx_variator = CrossoverVariator(Recombinator(), 2)
pop_operator = CrossoverPopOperator([cx_variator])
result = cls.from_dict(pop_operator.to_dict())
self.assertIsInstance(result, CrossoverPopOperator)
self.assertEqual(pop_operator.variators[0].__class__,
result.variators[0].__class__)
def _create_default_grammar(n_offspring: int,
cx_prob: float,
m_prob: float,
base_kernel_names: Optional[List[str]] = None,
hyperpriors: Optional[HyperpriorMap] = None):
mutator = HalfAndHalfMutator(binary_tree_node_cls=KernelNode, max_depth=1)
recombinator = SubtreeExchangeRecombinator() # OnePointStrictRecombinator()
cx_variator = CrossoverVariator(recombinator, n_offspring=n_offspring, c_prob=cx_prob)
mut_variator = MutationVariator(mutator, m_prob=m_prob)
variators = [cx_variator, mut_variator]
pop_operator = CrossMutPopOperator(variators)
return EvolutionaryGrammar(population_operator=pop_operator, base_kernel_names=base_kernel_names,
hyperpriors=hyperpriors)