def test_sso_update():
search_space = search.SearchSpace(
n_agents=10, n_variables=2, lower_bound=[0, 0], upper_bound=[10, 10]
)
new_sso = sso.SSO()
new_sso.compile(search_space)
new_sso.update(search_space)
def test_sso_params():
params = {"C_w": 0.1, "C_p": 0.4, "C_g": 0.9}
new_sso = sso.SSO(params=params)
assert new_sso.C_w == 0.1
assert new_sso.C_p == 0.4
assert new_sso.C_g == 0.9
def test_sso_params():
params = {'C_w': 0.1, 'C_p': 0.4, 'C_g': 0.9}
new_sso = sso.SSO(params=params)
assert new_sso.C_w == 0.1
assert new_sso.C_p == 0.4
assert new_sso.C_g == 0.9
def test_sso_hyperparams():
hyperparams = {'C_w': 0.1, 'C_p': 0.4, 'C_g': 0.9}
new_sso = sso.SSO(hyperparams=hyperparams)
assert new_sso.C_w == 0.1
assert new_sso.C_p == 0.4
assert new_sso.C_g == 0.9
def test_sso_evaluate():
def square(x):
return np.sum(x**2)
search_space = search.SearchSpace(
n_agents=10, n_variables=2, lower_bound=[0, 0], upper_bound=[10, 10]
)
new_sso = sso.SSO()
new_sso.compile(search_space)
new_sso.evaluate(search_space, square)
def test_sso_compile():
search_space = search.SearchSpace(
n_agents=10, n_variables=2, lower_bound=[0, 0], upper_bound=[10, 10]
)
new_sso = sso.SSO()
new_sso.compile(search_space)
try:
new_sso.local_position = 1
except:
new_sso.local_position = np.array([1])
assert new_sso.local_position == np.array([1])
def test_sso_params_setter():
new_sso = sso.SSO()
try:
new_sso.C_w = "a"
except:
new_sso.C_w = 0.1
try:
new_sso.C_w = -1
except:
new_sso.C_w = 0.1
assert new_sso.C_w == 0.1
try:
new_sso.C_p = "b"
except:
new_sso.C_p = 0.4
try:
new_sso.C_p = 0.05
except:
new_sso.C_p = 0.4
assert new_sso.C_p == 0.4
try:
new_sso.C_g = "c"
except:
new_sso.C_g = 0.9
try:
new_sso.C_g = 0.35
except:
new_sso.C_g = 0.9
assert new_sso.C_g == 0.9
def test_sso_params_setter():
new_sso = sso.SSO()
try:
new_sso.C_w = 'a'
except:
new_sso.C_w = 0.1
try:
new_sso.C_w = -1
except:
new_sso.C_w = 0.1
assert new_sso.C_w == 0.1
try:
new_sso.C_p = 'b'
except:
new_sso.C_p = 0.4
try:
new_sso.C_p = 0.05
except:
new_sso.C_p = 0.4
assert new_sso.C_p == 0.4
try:
new_sso.C_g = 'c'
except:
new_sso.C_g = 0.9
try:
new_sso.C_g = 0.35
except:
new_sso.C_g = 0.9
assert new_sso.C_g == 0.9
def test_sso_run():
def square(x):
return np.sum(x**2)
def hook(optimizer, space, function):
return
new_function = function.Function(pointer=square)
new_sso = sso.SSO()
search_space = search.SearchSpace(n_agents=10,
n_iterations=100,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
history = new_sso.run(search_space, new_function, pre_evaluation=hook)
assert len(history.agents) > 0
assert len(history.best_agent) > 0
best_fitness = history.best_agent[-1][1]
assert best_fitness <= constants.TEST_EPSILON, 'The algorithm sso failed to converge.'
def test_sso_build():
new_sso = sso.SSO()
assert new_sso.built == True
