def test_hill_climb_continuous_min():
"""Test hill_climb function for a continuous minimization problem"""
problem = ContinuousOpt(5, OneMax(), maximize=False)
best_state, best_fitness, _ = hill_climb(problem, restarts=20)
x = np.array([0, 0, 0, 0, 0])
assert (np.array_equal(best_state, x) and best_fitness == 0)
def test_hill_climb_discrete_max():
"""Test hill_climb function for a discrete maximization problem"""
problem = DiscreteOpt(5, OneMax(), maximize=True)
best_state, best_fitness, _ = hill_climb(problem, restarts=20)
x = np.array([1, 1, 1, 1, 1])
assert (np.array_equal(best_state, x) and best_fitness == 5)
def test_hill_climb_max_iters():
"""Test hill_climb function with max_iters less than infinite"""
problem = DiscreteOpt(5, OneMax(), maximize=True)
x = np.array([0, 0, 0, 0, 0])
best_state, best_fitness, _ = hill_climb(problem,
max_iters=1,
restarts=0,
init_state=x)
assert best_fitness == 1