def test_primitive_sequence_to_expression_string_wrong_length(self):
primitive_sequence = [
gp.Primitive('add', args=(int, int), ret=int),
gp.Terminal('x', symbolic=True, ret=None),
]
with self.assertRaisesRegex(
ValueError,
r'The length of sequence should be 1 \+ 2 \* n, but got 2'):
evolutionary.primitive_sequence_to_expression_string(
primitive_sequence)
def test_primitive_sequence_to_expression_string(self):
# add
# / \
# x mul
# / \
# sub y
# / \
# a b
primitive_sequence = [
gp.Primitive('add', args=(int, int), ret=int),
gp.Terminal('x', symbolic=True, ret=None),
gp.Primitive('mul', args=(int, int), ret=int),
gp.Primitive('sub', args=(int, int), ret=int),
# Whether symbolic is True or False does not matter.
gp.Terminal(1, symbolic=True, ret=None),
gp.Terminal(2, symbolic=False, ret=None),
gp.Terminal('y', symbolic=True, ret=None),
]
self.assertEqual(
evolutionary.primitive_sequence_to_expression_string(
primitive_sequence), '( x + ( ( 1 - 2 ) * y ) )')
def _call(fun):
return gp.Primitive(f'{fun.name}/{fun.arity}', fun.params, fun.ret)
def _return():
name = f'{RET}/1'
fun = FUN[name]
return gp.Primitive(name, fun.params, fun.ret)
def _if():
name = f'{IF}/3'
fun = FUN[name]
return gp.Primitive(name, fun.params, fun.ret)
def _assign():
name = f'{ASSIGN}/2'
fun = FUN[name]
return gp.Primitive(name, fun.params, fun.ret)
def _sequence(arity):
name = f'{SEQ}/{arity}'
fun = FUN[name]
return gp.Primitive(name, fun.params, fun.ret)
class EvolutionaryTest(parameterized.TestCase):
def setUp(self):
super(EvolutionaryTest, self).setUp()
self.pset = evolutionary.get_univariate_one_constant_primitives_set()
@parameterized.parameters(
('( 1 + x )', True),
(gp.Terminal('x', symbolic=True, ret=None), True),
(gp.Primitive('c', args=(), ret=None), True),
(gp.Primitive('add', args=(int, int), ret=int), False),
)
def test_is_terminal(self, node, expected):
self.assertEqual(evolutionary.is_terminal(node), expected)
@parameterized.parameters(
(gp.Primitive('add', args=(int, int),
ret=int), gp.Terminal('x', symbolic=True, ret=None),
gp.Terminal('y', symbolic=True, ret=None), '( x + y )'),
(gp.Primitive('add', args=(int, int),
ret=int), gp.Primitive('add', args=(int, int), ret=int),
gp.Terminal('y', symbolic=True, ret=None), None),
(gp.Primitive('add', args=(int, int),
ret=int), gp.Terminal('x', symbolic=True, ret=None),
gp.Primitive('add', args=(int, int), ret=int), None),
)
def test_combine_nodes(self, node0, node1, node2, expected):
self.assertEqual(evolutionary.combine_nodes(node0, node1, node2),
expected)
def test_primitive_sequence_to_expression_string(self):
# add
# / \
# x mul
# / \
# sub y
# / \
# a b
primitive_sequence = [
gp.Primitive('add', args=(int, int), ret=int),
gp.Terminal('x', symbolic=True, ret=None),
gp.Primitive('mul', args=(int, int), ret=int),
gp.Primitive('sub', args=(int, int), ret=int),
# Whether symbolic is True or False does not matter.
gp.Terminal(1, symbolic=True, ret=None),
gp.Terminal(2, symbolic=False, ret=None),
gp.Terminal('y', symbolic=True, ret=None),
]
self.assertEqual(
evolutionary.primitive_sequence_to_expression_string(
primitive_sequence), '( x + ( ( 1 - 2 ) * y ) )')
def test_primitive_sequence_to_expression_string_constant(self):
primitive_sequence = [gp.Terminal('ARG0', symbolic=True, ret=None)]
self.assertEqual(
evolutionary.primitive_sequence_to_expression_string(
primitive_sequence), 'x')
def test_primitive_sequence_to_expression_string_wrong_length(self):
primitive_sequence = [
gp.Primitive('add', args=(int, int), ret=int),
gp.Terminal('x', symbolic=True, ret=None),
]
with self.assertRaisesRegex(
ValueError,
r'The length of sequence should be 1 \+ 2 \* n, but got 2'):
evolutionary.primitive_sequence_to_expression_string(
primitive_sequence)
def test_evolutionary_algorithm_with_num_evals_limit(self):
evolutionary.set_creator()
toolbox = evolutionary.get_toolbox(pset=self.pset, max_height=50)
toolbox.register('evaluate',
evolutionary.evaluate_individual,
input_values=np.array([1., 2., 3.]),
output_values=np.array([2., 3., 4.]),
toolbox=toolbox)
population = toolbox.population(n=10)
halloffame = tools.HallOfFame(1)
evolutionary.evolutionary_algorithm_with_num_evals_limit(
population=population,
toolbox=toolbox,
cxpb=0.5,
mutpb=0.1,
num_evals_limit=500,
halloffame=halloffame)
func = toolbox.compile(expr=halloffame[0])
np.testing.assert_allclose(func(np.array([5., 6., 7.])), [6., 7., 8.])
@parameterized.parameters(
(None, None, None, False),
(0, 1, None, True),
(0, 1, 50., True),
)
def test_search_expression(self, leading_at_0, leading_at_inf,
hard_penalty_default_value,
include_leading_powers):
# Test search several expressions.
evolutionary.set_creator()
evolutionary.search_expression(
input_values=np.array([1., 2., 3.]),
output_values=np.array([2., 3., 4.]),
pset=self.pset,
max_height=50,
population_size=10,
cxpb=0.5,
mutpb=0.1,
num_evals_limit=30,
leading_at_0=leading_at_0,
leading_at_inf=leading_at_inf,
hard_penalty_default_value=hard_penalty_default_value,
include_leading_powers=include_leading_powers,
default_value=50.)
evolutionary.search_expression(
input_values=np.array([1., 2., 3.]),
output_values=np.array([1., 4., 9.]),
pset=self.pset,
max_height=50,
population_size=10,
cxpb=0.5,
mutpb=0.1,
num_evals_limit=30,
leading_at_0=leading_at_0,
leading_at_inf=leading_at_inf,
hard_penalty_default_value=hard_penalty_default_value,
include_leading_powers=include_leading_powers,
default_value=50.)
