def benchmark_ask_tell_100k(benchmark, fake_archive_fixture):
archive, x0 = fake_archive_fixture
batch_size = 32
emitter = IsoLineEmitter(archive, x0, batch_size=batch_size)
n = 100_000
np.random.seed(0)
objective_values = np.random.rand(batch_size)
behavior_values = np.random.rand(batch_size, 2)
# Let numba compile.
temp_sol = emitter.ask()
emitter.tell(temp_sol, objective_values, behavior_values)
obj_vals = np.random.rand(n, batch_size)
behavior_vals = np.random.rand(n, batch_size, 2)
def ask_and_tell():
for i in range(n):
solutions = emitter.ask()
objective_values = obj_vals[i]
behavior_values = behavior_vals[i]
emitter.tell(solutions, objective_values, behavior_values)
benchmark(ask_and_tell)
def test_degenerate_gauss_emits_parent(archive_fixture):
archive, x0 = archive_fixture
emitter = IsoLineEmitter(archive, x0, iso_sigma=0, batch_size=2)
archive.add(x0, 1, np.array([0, 0]))
solutions = emitter.ask()
assert (solutions == np.expand_dims(x0, axis=0)).all()
def test_lower_bounds_enforced(archive_fixture):
archive, _ = archive_fixture
emitter = IsoLineEmitter(archive, [-2, -2],
iso_sigma=0,
line_sigma=0,
bounds=[(-1, 1)] * 2)
sols = emitter.ask()
assert np.all(sols >= -1)
def test_degenerate_gauss_emits_along_line(archive_fixture):
archive, x0 = archive_fixture
emitter = IsoLineEmitter(archive, x0, iso_sigma=0, batch_size=100)
archive.add(np.array([0, 0, 0, 0]), 1, np.array([0, 0]))
archive.add(np.array([10, 0, 0, 0]), 1, np.array([1, 1]))
solutions = emitter.ask()
# All solutions should either come from a degenerate distribution around
# [0,0,0,0], a degenerate distribution around [10,0,0,0], or the "iso line
# distribution" between [0,0,0,0] and [10,0,0,0] (i.e. a line between those
# two points). By having a large batch size, we should be able to cover all
# cases. In any case, this assertion should hold for all solutions
# generated.
assert (solutions[:, 1:] == 0).all()
def test_degenerate_gauss_emits_x0(archive_fixture):
archive, x0 = archive_fixture
emitter = IsoLineEmitter(archive, x0, iso_sigma=0, batch_size=2)
solutions = emitter.ask()
assert (solutions == np.expand_dims(x0, axis=0)).all()