def test_opytimizer_build():
def square(x):
return np.sum(x**2)
assert square(2) == 4
new_function = function.Function(pointer=square)
lb = [0, 0]
ub = [10, 10]
new_space = search.SearchSpace(lower_bound=lb, upper_bound=ub)
new_pso = pso.PSO()
try:
new_pso.built = False
new_opytimizer = opytimizer.Opytimizer(space=new_space,
optimizer=new_pso,
function=new_function)
except:
new_pso.built = True
new_opytimizer = opytimizer.Opytimizer(space=new_space,
optimizer=new_pso,
function=new_function)
def test_opytimizer_start():
space = search.SearchSpace(1, 1, 0, 1)
func = function.Function(callable)
optimizer = pso.PSO()
new_opytimizer = opytimizer.Opytimizer(space, optimizer, func)
new_opytimizer.start(n_iterations=1)
def test_opytimizer_history():
space = search.SearchSpace(1, 1, 0, 1)
func = function.Function(callable)
optimizer = pso.PSO()
new_opytimizer = opytimizer.Opytimizer(space, optimizer, func)
assert type(new_opytimizer.history).__name__ == 'History'
def test_opytimizer_save():
space = search.SearchSpace(1, 1, 0, 1)
func = function.Function(callable)
optimizer = pso.PSO()
new_opytimizer = opytimizer.Opytimizer(space, optimizer, func)
new_opytimizer.save('out.pkl')
def test_opytimizer_update_args():
space = search.SearchSpace(1, 1, 0, 1)
func = function.Function(callable)
optimizer = pso.PSO()
new_opytimizer = opytimizer.Opytimizer(space, optimizer, func)
assert len(new_opytimizer.update_args) == 1
def test_opytimizer_total_iterations():
space = search.SearchSpace(1, 1, 0, 1)
func = function.Function(callable)
optimizer = pso.PSO()
new_opytimizer = opytimizer.Opytimizer(space, optimizer, func)
assert new_opytimizer.total_iterations == 0
def test_opytimizer_update():
space = search.SearchSpace(1, 1, 0, 1)
func = function.Function(callable)
optimizer = pso.PSO()
callbacks = callback.CallbackVessel([])
new_opytimizer = opytimizer.Opytimizer(space, optimizer, func)
new_opytimizer.update(callbacks)
def test_opytimizer_history_setter():
space = search.SearchSpace(1, 1, 0, 1)
func = function.Function(callable)
optimizer = pso.PSO()
hist = history.History()
new_opytimizer = opytimizer.Opytimizer(space, optimizer, func)
try:
new_opytimizer.history = 1
except:
new_opytimizer.history = hist
assert type(new_opytimizer.history).__name__ == 'History'
def test_opytimizer_function_setter():
space = search.SearchSpace(1, 1, 0, 1)
func = function.Function(callable)
optimizer = pso.PSO()
new_opytimizer = opytimizer.Opytimizer(space, optimizer, func)
try:
func.built = False
new_opytimizer.function = func
except:
func.built = True
new_opytimizer.function = func
assert type(new_opytimizer.function).__name__ == 'Function'
def test_opytimizer_space_setter():
space = search.SearchSpace(1, 1, 0, 1)
func = function.Function(callable)
optimizer = pso.PSO()
new_opytimizer = opytimizer.Opytimizer(space, optimizer, func)
try:
space.built = False
new_opytimizer.space = space
except:
space.built = True
new_opytimizer.space = space
assert type(new_opytimizer.space).__name__ == 'SearchSpace'
def test_opytimizer_start():
def square(x):
return np.sum(x**2)
new_function = function.Function(pointer=square)
lb = [0, 0]
ub = [10, 10]
new_space = search.SearchSpace(lower_bound=lb, upper_bound=ub)
new_pso = pso.PSO()
new_opytimizer = opytimizer.Opytimizer(space=new_space,
optimizer=new_pso,
function=new_function)
new_opytimizer.start(history=True)
def test_opytimizer_start():
def square(x):
return np.sum(x**2)
new_function = function.Function(pointer=square)
lb = [0]
ub = [10]
new_space = search.SearchSpace(lower_bound=lb, upper_bound=ub)
new_pso = pso.PSO()
new_opytimizer = opytimizer.Opytimizer(space=new_space,
optimizer=new_pso,
function=new_function)
history = new_opytimizer.start()
assert isinstance(history, opytimizer.utils.history.History)
def test_opytimizer_total_iterations_setter():
space = search.SearchSpace(1, 1, 0, 1)
func = function.Function(callable)
optimizer = pso.PSO()
new_opytimizer = opytimizer.Opytimizer(space, optimizer, func)
try:
new_opytimizer.total_iterations = 'a'
except:
new_opytimizer.total_iterations = 0
assert new_opytimizer.total_iterations == 0
try:
new_opytimizer.total_iterations = -1
except:
new_opytimizer.total_iterations = 0
assert new_opytimizer.total_iterations == 0