def test_loa_params():
params = {
"N": 0.2,
"P": 4,
"S": 0.8,
"R": 0.2,
"I": 0.4,
"Ma": 0.3,
"Mu": 0.2
}
new_loa = loa.LOA(params=params)
assert new_loa.N == 0.2
assert new_loa.P == 4
assert new_loa.S == 0.8
assert new_loa.R == 0.2
assert new_loa.I == 0.4
assert new_loa.Ma == 0.3
assert new_loa.Mu == 0.2
def test_loa_compile():
search_space = search.SearchSpace(n_agents=10,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_loa = loa.LOA()
new_loa.compile(search_space)
def test_loa_moving_safe_place():
search_space = search.SearchSpace(n_agents=100,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_loa = loa.LOA()
new_loa.compile(search_space)
prides = new_loa._get_pride_lions(search_space.agents)
new_loa._moving_safe_place(prides)
def test_loa_update():
def square(x):
return np.sum(x**2)
search_space = search.SearchSpace(n_agents=100,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_loa = loa.LOA()
new_loa.compile(search_space)
new_loa.update(search_space, square)
def test_loa_migrating():
search_space = search.SearchSpace(n_agents=100,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_loa = loa.LOA()
new_loa.compile(search_space)
nomads = new_loa._get_nomad_lions(search_space.agents)
prides = new_loa._get_pride_lions(search_space.agents)
new_nomads, new_prides = new_loa._migrating(nomads, prides)
def test_loa_equilibrium():
search_space = search.SearchSpace(n_agents=100,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_loa = loa.LOA()
new_loa.compile(search_space)
nomads = new_loa._get_nomad_lions(search_space.agents)
prides = new_loa._get_pride_lions(search_space.agents)
prides[0] = prides[0] + prides[0]
new_nomads, new_prides = new_loa._equilibrium(nomads, prides, 100)
def test_loa_check_prides_for_males():
search_space = search.SearchSpace(n_agents=100,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_loa = loa.LOA()
new_loa.compile(search_space)
prides = new_loa._get_pride_lions(search_space.agents)
for agent in prides[0]:
agent.female = True
new_loa._check_prides_for_males(prides)
def test_loa_nomad_mating():
def square(x):
return np.sum(x**2)
search_space = search.SearchSpace(n_agents=100,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_loa = loa.LOA()
new_loa.compile(search_space)
nomads = new_loa._get_nomad_lions(search_space.agents)
new_loa._nomad_mating(nomads, square)
def test_loa_mating_operator():
def square(x):
return np.sum(x**2)
search_space = search.SearchSpace(n_agents=100,
n_variables=2,
lower_bound=[0, 0],
upper_bound=[10, 10])
new_loa = loa.LOA()
new_loa.compile(search_space)
new_loa.Mu = 1
nomads = new_loa._get_nomad_lions(search_space.agents)
males_nomads = [nomad for nomad in nomads if not nomad.female]
a1, a2 = new_loa._mating_operator(search_space.agents[0], males_nomads,
square)
assert type(a1).__name__ == "Lion"
assert type(a2).__name__ == "Lion"
def test_loa_params_setter():
new_loa = loa.LOA()
try:
new_loa.N = "a"
except:
new_loa.N = 0.2
assert new_loa.N == 0.2
try:
new_loa.N = -1
except:
new_loa.N = 0.2
assert new_loa.N == 0.2
try:
new_loa.P = "b"
except:
new_loa.P = 4
assert new_loa.P == 4
try:
new_loa.P = -1
except:
new_loa.P = 4
assert new_loa.P == 4
try:
new_loa.S = "c"
except:
new_loa.S = 0.8
assert new_loa.S == 0.8
try:
new_loa.S = -1
except:
new_loa.S = 0.8
assert new_loa.S == 0.8
try:
new_loa.R = "d"
except:
new_loa.R = 0.2
assert new_loa.R == 0.2
try:
new_loa.R = -1
except:
new_loa.R = 0.2
assert new_loa.R == 0.2
try:
new_loa.I = "e"
except:
new_loa.I = 0.4
assert new_loa.I == 0.4
try:
new_loa.I = -1
except:
new_loa.I = 0.4
assert new_loa.I == 0.4
try:
new_loa.Ma = "f"
except:
new_loa.Ma = 0.3
assert new_loa.Ma == 0.3
try:
new_loa.Ma = -1
except:
new_loa.Ma = 0.3
assert new_loa.Ma == 0.3
try:
new_loa.Mu = "g"
except:
new_loa.Mu = 0.2
assert new_loa.Mu == 0.2
try:
new_loa.Mu = -1
except:
new_loa.Mu = 0.2
assert new_loa.Mu == 0.2
