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import numpy as np
from hyperactive.base import BaseExperiment
class AckleyFunction(BaseExperiment):
r"""Ackley function, common benchmark for optimization algorithms.
The Ackley function is a non-convex function used to test optimization algorithms.
It is defined as:
.. math::
f(x, y) = -A \cdot \exp(-0.2 \sqrt{0.5 (x^2 + y^2)}) - \exp(0.5 (\cos(2 \pi x) + \cos(2 \pi y))) + \exp(1) + A
where A is a constant.
Parameters
----------
A : float
Amplitude constant used in the calculation of the Ackley function.
""" # noqa: E501
def __init__(self, A):
self.A = A
super().__init__()
def _paramnames(self):
return ["x0", "x1"]
def _score(self, params):
x = params["x0"]
y = params["x1"]
loss1 = -self.A * np.exp(-0.2 * np.sqrt(0.5 * (x * x + y * y)))
loss2 = -np.exp(0.5 * (np.cos(2 * np.pi * x) + np.cos(2 * np.pi * y)))
loss3 = np.exp(1)
loss4 = self.A
return -(loss1 + loss2 + loss3 + loss4)
SimonBlanke /
Hyperactive
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