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# Author: Simon Blanke
# Email: [email protected]
# License: MIT License
import pytest
import numpy as np
from gradient_free_optimizers import SimulatedAnnealingOptimizer
from .test_stochastic_hill_climbing_para_init import (
stochastic_hill_climbing_para,
)
from ._base_para_test import _base_para_test_func
def objective_function(para):
score = -para["x1"] * para["x1"]
return score
search_space = {"x1": np.arange(-100, 101, 1)}
simulated_annealing_para = [
({"annealing_rate": 0.9}),
({"annealing_rate": 0.8}),
({"annealing_rate": 0.5}),
({"annealing_rate": 1}),
({"start_temp": 1}),
({"start_temp": 0.5}),
({"start_temp": 3}),
({"start_temp": 10}),
]
pytest_wrapper = ("opt_para", simulated_annealing_para)
@pytest.mark.parametrize(*pytest_wrapper)
def test_hill_climbing_para(opt_para):
_base_para_test_func(opt_para, SimulatedAnnealingOptimizer)
SimonBlanke /
Gradient-Free-Optimizers
