def test_ci_compile():
search_space = search.SearchSpace(n_agents=10,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_ci = ci.CI()
new_ci.compile(search_space)
try:
new_ci.lower = 1
except:
new_ci.lower = np.array([1])
assert new_ci.lower == 1
try:
new_ci.upper = 1
except:
new_ci.upper = np.array([1])
assert new_ci.upper == 1
def test_gco_compile():
search_space = search.SearchSpace(n_agents=4,
n_variables=2,
lower_bound=[1, 1],
upper_bound=[10, 10])
new_gco = gco.GCO()
new_gco.compile(search_space)
try:
new_gco.life = 1
except:
new_gco.life = np.array([1])
assert new_gco.life == np.array([1])
try:
new_gco.counter = 1
except:
new_gco.counter = np.array([1])
assert new_gco.counter == np.array([1])
def test_hho_run():
def square(x):
return np.sum(x**2)
def hook(optimizer, space, function):
return
new_function = function.Function(pointer=square)
new_hho = hho.HHO()
search_space = search.SearchSpace(n_agents=10, n_iterations=100,
n_variables=2, lower_bound=[0, 0],
upper_bound=[10, 10])
history = new_hho.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 hho failed to converge.'
def test_hs_run():
def square(x):
return np.sum(x**2)
new_function = function.Function(pointer=square)
hyperparams = {
'HMCR': 0.7,
'PAR': 0.7,
'bw': 10
}
new_hs = hs.HS(hyperparams=hyperparams)
search_space = search.SearchSpace(n_agents=2, n_iterations=100,
n_variables=2, lower_bound=[0, 0],
upper_bound=[10, 10])
history = new_hs.run(search_space, new_function)
assert len(history.agents) > 0
assert len(history.best_agent) > 0
def test_wwo_compile():
search_space = search.SearchSpace(n_agents=50,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_wwo = wwo.WWO()
new_wwo.compile(search_space)
try:
new_wwo.height = 1
except:
new_wwo.height = np.array([1])
assert new_wwo.height == np.array([1])
try:
new_wwo.length = 1
except:
new_wwo.length = np.array([1])
assert new_wwo.length == np.array([1])
def test_ssd_compile():
search_space = search.SearchSpace(n_agents=10,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_ssd = ssd.SSD()
new_ssd.compile(search_space)
try:
new_ssd.local_position = 1
except:
new_ssd.local_position = np.array([1])
assert new_ssd.local_position == 1
try:
new_ssd.velocity = 1
except:
new_ssd.velocity = np.array([1])
assert new_ssd.velocity == 1
def test_gsa_update_velocity():
new_gsa = gsa.GSA()
search_space = search.SearchSpace(n_agents=10,
n_iterations=100,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
search_space.agents[0].fit = 1
search_space.agents.sort(key=lambda x: x.fit)
mass = new_gsa._calculate_mass(search_space.agents)
gravity = 1
force = new_gsa._calculate_force(search_space.agents, mass, gravity)
velocity = new_gsa._update_velocity(force[0], mass[0], 1)
assert velocity[0] != 0
def test_sghs_run():
def square(x):
return np.sum(x**2)
def hook(optimizer, space, function):
return
new_function = function.Function(pointer=square)
new_sghs = hs.SGHS(hyperparams={'LP': 10})
search_space = search.SearchSpace(n_agents=20, n_iterations=50,
n_variables=2, lower_bound=[0, 0],
upper_bound=[5, 5])
history = new_sghs.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 ihs failed to converge.'
def test_coa_compile():
search_space = search.SearchSpace(n_agents=10,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_coa = coa.COA()
new_coa.compile(search_space)
try:
new_coa.n_c = 'a'
except:
new_coa.n_c = 1
assert new_coa.n_c == 1
try:
new_coa.n_c = -1
except:
new_coa.n_c = 1
assert new_coa.n_c == 1
def test_af_compile():
search_space = search.SearchSpace(n_agents=10,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_af = af.AF()
new_af.compile(search_space)
try:
new_af.p_distance = 1
except:
new_af.p_distance = np.array([1])
assert new_af.p_distance == np.array([1])
try:
new_af.g_distance = 1
except:
new_af.g_distance = np.array([1])
assert new_af.g_distance == np.array([1])
def test_kh_local_alpha():
search_space = search.SearchSpace(n_agents=5,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_kh = kh.KH()
new_kh.compile(search_space)
distance, eucl_distance = new_kh._sensing_distance(search_space.agents, 0)
neighbours = new_kh._get_neighbours(search_space.agents, 0, distance,
eucl_distance)
alpha = new_kh._local_alpha(
search_space.agents[0],
search_space.agents[-1],
search_space.agents[0],
neighbours,
)
assert alpha.shape == (2, 1) or alpha == 0
def test_kh_compile():
search_space = search.SearchSpace(n_agents=5,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_kh = kh.KH()
new_kh.compile(search_space)
try:
new_kh.motion = 1
except:
new_kh.motion = np.array([1])
assert new_kh.motion == np.array([1])
try:
new_kh.foraging = 1
except:
new_kh.foraging = np.array([1])
assert new_kh.foraging == np.array([1])
def test_rfo_compile():
search_space = search.SearchSpace(n_agents=10,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_rfo = rfo.RFO()
new_rfo.compile(search_space)
try:
new_rfo.n_replacement = "a"
except:
new_rfo.n_replacement = 1
assert new_rfo.n_replacement == 1
try:
new_rfo.n_replacement = -1
except:
new_rfo.n_replacement = 1
assert new_rfo.n_replacement == 1
def test_eho_compile():
search_space = search.SearchSpace(n_agents=20,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_eho = eho.EHO()
new_eho.compile(search_space)
try:
new_eho.n_ci = 'a'
except:
new_eho.n_ci = 1
assert new_eho.n_ci == 1
try:
new_eho.n_ci = -1
except:
new_eho.n_ci = 1
assert new_eho.n_ci == 1
def test_ba_compile():
search_space = search.SearchSpace(n_agents=10,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_ba = ba.BA()
new_ba.compile(search_space)
try:
new_ba.frequency = 1
except:
new_ba.frequency = np.array([1])
assert new_ba.frequency == np.array([1])
try:
new_ba.velocity = 1
except:
new_ba.velocity = np.array([1])
assert new_ba.velocity == np.array([1])
try:
new_ba.loudness = 1
except:
new_ba.loudness = np.array([1])
assert new_ba.loudness == np.array([1])
try:
new_ba.pulse_rate = 1
except:
new_ba.pulse_rate = np.array([1])
assert new_ba.pulse_rate == np.array([1])
def test_search_initialize_agents():
new_search_space = search.SearchSpace()
assert new_search_space.agents[0].position[0] != 0
