def test_rfo_rellocation():
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_rfo = rfo.RFO()
new_rfo.compile(search_space)
new_rfo._rellocation(search_space.agents[0], search_space.best_agent,
square)
def test_rfo_params():
params = {
"phi": r.generate_uniform_random_number(0, 2 * np.pi)[0],
"theta": r.generate_uniform_random_number()[0],
"p_replacement": 0.05,
}
new_rfo = rfo.RFO(params=params)
assert 0 <= new_rfo.phi <= 2 * np.pi
assert 0 <= new_rfo.theta <= 1
assert new_rfo.p_replacement == 0.05
def test_rfo_update():
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_rfo = rfo.RFO()
new_rfo.compile(search_space)
new_rfo.update(search_space, square)
new_rfo.n_replacement = 10
new_rfo.update(search_space, square)
def test_rfo_noticing():
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_rfo = rfo.RFO()
new_rfo.compile(search_space)
new_rfo._noticing(search_space.agents[0], square, 0.1)
new_rfo.phi = 0
new_rfo._noticing(search_space.agents[0], square, 0.1)
def test_rfo_params_setter():
new_rfo = rfo.RFO()
try:
new_rfo.phi = "a"
except:
new_rfo.phi = r.generate_uniform_random_number(0, 2 * np.pi)[0]
assert 0 <= new_rfo.phi <= 2 * np.pi
try:
new_rfo.phi = -1
except:
new_rfo.phi = r.generate_uniform_random_number(0, 2 * np.pi)[0]
assert 0 <= new_rfo.phi <= 2 * np.pi
try:
new_rfo.theta = "b"
except:
new_rfo.theta = r.generate_uniform_random_number()[0]
assert 0 <= new_rfo.theta <= 1
try:
new_rfo.theta = -1
except:
new_rfo.theta = r.generate_uniform_random_number()[0]
assert 0 <= new_rfo.theta <= 1
try:
new_rfo.p_replacement = "c"
except:
new_rfo.p_replacement = 0.05
assert new_rfo.p_replacement == 0.05
try:
new_rfo.p_replacement = -1
except:
new_rfo.p_replacement = 0.05
assert new_rfo.p_replacement == 0.05
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