def test_grid_space_terminals_setter():
try:
new_grid_space = grid.GridSpace()
new_grid_space.grid = 'a'
except:
new_grid_space = grid.GridSpace()
new_grid_space.grid = np.array((1, 1))
assert len(new_grid_space.grid) == 2
def test_grid_space_step_setter():
new_grid_space = grid.GridSpace(1, 0.1, 0, 1)
try:
new_grid_space.step = "a"
except:
new_grid_space.step = np.array([0.1])
assert new_grid_space.step == 0.1
try:
new_grid_space.step = np.array([0.1, 0.1])
except:
new_grid_space.step = np.array([0.1])
assert new_grid_space.step == 0.1
def test_grid_space_step_setter():
new_grid_space = grid.GridSpace()
try:
new_grid_space.step = 'a'
except:
new_grid_space.step = 0.1
assert new_grid_space.step == 0.1
try:
new_grid_space.step = 0
except:
new_grid_space.step = 0.1
assert new_grid_space.step == 0.1
def test_gs_run():
def square(x):
return np.sum(x)
def hook(optimizer, space, function):
return
new_function = function.Function(pointer=square)
new_gs = gs.GS()
grid_space = grid.GridSpace(n_variables=2,
step=0.1,
lower_bound=[0, 0],
upper_bound=[5, 5])
history = new_gs.run(grid_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 gs failed to converge.'
def test_grid_initialize_agents():
new_grid_space = grid.GridSpace(1, 0.1, 0, 1)
assert new_grid_space.agents[0].position[0] != 1
def test_grid_space_step():
new_grid_space = grid.GridSpace(1, 0.1, 0, 1)
assert new_grid_space.step == 0.1
def test_grid_create_grid():
new_grid_space = grid.GridSpace(1, 0.1, 0, 1)
new_grid_space._create_grid()
assert len(new_grid_space.grid) == 11
def test_grid_create_grid():
new_grid_space = grid.GridSpace()
new_grid_space._create_grid(0.1, [1, 1], [2, 2])
assert len(new_grid_space.grid) == 100
def test_grid_space_grid():
new_grid_space = grid.GridSpace()
assert len(new_grid_space.grid) == 10
