def test_botorch_ackley(self):
ackley = FromBotorch(botorch_synthetic_function=botorch_synthetic.Ackley())
self.assertEqual(ackley.name, "FromBotorch_Ackley")
self.assertAlmostEqual(ackley(1.0, 2.0), 5.422131717799505)
self.assertAlmostEqual(ackley(x1=1.0, x2=2.0), 5.422131717799505)
self.assertAlmostEqual(ackley(np.array([1, 2])), 5.422131717799505)
self.assertAlmostEqual(ackley(np.array([[1, 2], [1, 2]]))[0], 5.422131717799505)
self.assertAlmostEqual(ackley.domain[0], (-32.768, 32.768), places=3)
self.assertEqual(ackley.required_dimensionality, 2)
self.assertEqual(ackley.fmin, 0.0)
with self.assertRaisesRegex(NotImplementedError, "Ackley does not specify"):
ackley.maximums
with self.assertRaisesRegex(NotImplementedError, "Ackley does not specify"):
ackley.minimums
with self.assertRaisesRegex(NotImplementedError, "Ackley does not specify"):
ackley.fmax
(4 * np.pi**2) * x_1**2 + 5.0 / np.pi * x_1 - 6.0)**2 +
10 * (1 - 1.0 / (8 * np.pi)) * np.cos(x_1) + 10)
class Aug_Branin(SyntheticFunction):
"""Augmented Branin function (3-dimensional with infinitely many global minima)."""
_required_dimensionality = 3
_domain = [(-5, 10), (0, 15), (0, 1)]
_minimums = [(-np.pi, 12.275, 1), (np.pi, 2.275, 1), (9.42478, 2.475, 1)]
_fmin = 0.397887
_fmax = 308.129
@copy_doc(SyntheticFunction._f)
def _f(self, X: np.ndarray) -> float:
x_1 = X[0]
x_2 = X[1]
return float((x_2 -
(5.1 / (4 * np.pi**2) - 0.1 *
(1 - X[-1])) * x_1**2 + 5.0 / np.pi * x_1 - 6.0)**2 +
10 * (1 - 1.0 / (8 * np.pi)) * np.cos(x_1) + 10)
hartmann6 = Hartmann6()
aug_hartmann6 = Aug_Hartmann6()
branin = Branin()
aug_branin = Aug_Branin()
# Synthetic functions constructed from BoTorch.
ackley = from_botorch(botorch_synthetic_function=botorch_synthetic.Ackley())
# pyre-fixme[15]: `_required_dimensionality` overrides attribute defined in
# `SyntheticFunction` inconsistently.
_required_dimensionality = 3
# pyre-fixme[15]: `_domain` overrides attribute defined in `SyntheticFunction`
# inconsistently.
_domain = [(-5, 10), (0, 15), (0, 1)]
_minimums = [(-np.pi, 12.275, 1), (np.pi, 2.275, 1), (9.42478, 2.475, 1)]
# pyre-fixme[15]: `_fmin` overrides attribute defined in `SyntheticFunction`
# inconsistently.
_fmin = 0.397887
# pyre-fixme[15]: `_fmax` overrides attribute defined in `SyntheticFunction`
# inconsistently.
_fmax = 294.0
@copy_doc(SyntheticFunction._f)
def _f(self, X: np.ndarray) -> float:
x_1 = X[0]
x_2 = X[1]
return float((x_2 -
(5.1 / (4 * np.pi**2) - 0.1 *
(1 - X[-1])) * x_1**2 + 5.0 / np.pi * x_1 - 6.0)**2 +
10 * (1 - 1.0 / (8 * np.pi)) * np.cos(x_1) + 10)
hartmann6 = Hartmann6()
aug_hartmann6 = Aug_Hartmann6()
branin = Branin()
aug_branin = Aug_Branin()
ackley = FromBotorch(botorch_synthetic_function=botorch_synthetic.Ackley())
AlignedAugHartmann6(),
# Ax support.
"hartmann6":
Hartmann6(), # d: 6; [(0, 1) for i in range(6)]
"AugHartmann6":
Aug_Hartmann6(), # d: 7; [(0, 1) for i in range(7)]
"branin":
Branin(), # d: 2; [(-5, 10), (0, 15)]
"AugBranin":
Aug_Branin(), # d: 3; [(-5, 10), (0, 15), (0, 1)]
# From Botorch
# # dim; _optimal_value; _bounds; _optimizers;
# (2); 0.0; [(-32.768, 32.768),(-32.768, 32.768)]; [(0.0, 0.0)]
"ackley2":
from_botorch(botorch_synthetic_function=botorch_synthetic.Ackley(dim=2)),
"ackley3":
from_botorch(botorch_synthetic_function=botorch_synthetic.Ackley(dim=3)),
"ackley4":
from_botorch(botorch_synthetic_function=botorch_synthetic.Ackley(dim=4)),
"ackley7":
from_botorch(botorch_synthetic_function=botorch_synthetic.Ackley(dim=7)),
# 2; 0.0; [(-4.5, 4.5), (-4.5, 4.5)]; [(3.0, 0.5)]
"beale":
from_botorch(botorch_synthetic_function=botorch_synthetic.Beale()),
# 2; 0.0; [(-15.0, -5.0), (-3.0, 3.0)]; [(-10.0, 1.0)]
"bukin":
from_botorch(botorch_synthetic_function=botorch_synthetic.Bukin()),
# 8; 0.8; [(-1.0, 1.0) for _ in range(8)]; [tuple(0.0 for _ in range(8))]
"cosine8":
from_botorch(botorch_synthetic_function=botorch_synthetic.Cosine8()),