def test_interior_vs_bbox_gives_same_result():
f = generate_random_parametrization(ring_of_fire)
control = LearnerND(f, bounds=[(-1, 1), (-1, 1)])
hull = scipy.spatial.ConvexHull(control._bounds_points)
learner = LearnerND(f, bounds=hull)
simple(control, goal=lambda l: l.loss() < 0.1)
simple(learner, goal=lambda l: l.loss() < 0.1)
assert learner.data == control.data
def test_learnerND_curvature_runs_to_10_points_Blocking(execution_number):
loss = curvature_loss_function()
learner = LearnerND(ring_of_fire,
bounds=[(-1, 1), (-1, 1)],
loss_per_simplex=loss)
BlockingRunner(learner, goal=lambda l: l.npoints >= 10)
assert learner.npoints >= 10
def test_learnerND_curvature_runs_to_10_points():
loss = curvature_loss_function()
learner = LearnerND(ring_of_fire,
bounds=[(-1, 1), (-1, 1)],
loss_per_simplex=loss)
SimpleRunner(learner, goal=lambda l: l.npoints >= 10)
assert learner.npoints == 10
def test_vector_return_with_a_flat_layer():
f = generate_random_parametrization(ring_of_fire)
g = generate_random_parametrization(ring_of_fire)
h1 = lambda xy: np.array([f(xy), g(xy)]) # noqa: E731
h2 = lambda xy: np.array([f(xy), 0 * g(xy)]) # noqa: E731
h3 = lambda xy: np.array([0 * f(xy), g(xy)]) # noqa: E731
for function in [h1, h2, h3]:
learner = LearnerND(function, bounds=[(-1, 1), (-1, 1)])
simple(learner, goal=lambda l: l.loss() < 0.1)
def test_faiure_case_LearnerND():
log = [('ask', 4), ('tell', (-1, -1, -1), 1.607873907219222e-101),
('tell', (-1, -1, 1), 1.607873907219222e-101), ('ask', 2),
('tell', (-1, 1, -1), 1.607873907219222e-101),
('tell', (-1, 1, 1), 1.607873907219222e-101), ('ask', 2),
('tell', (1, -1, 1), 2.0), ('tell', (1, -1, -1), 2.0), ('ask', 2),
('tell', (0.0, 0.0, 0.0), 4.288304431237686e-06),
('tell', (1, 1, -1), 2.0)]
learner = LearnerND(lambda *x: x, bounds=[(-1, 1), (-1, 1), (-1, 1)])
replay_log(learner, log)
def test_learnerND_log_works():
loss = curvature_loss_function()
learner = LearnerND(ring_of_fire,
bounds=[(-1, 1), (-1, 1)],
loss_per_simplex=loss)
learner.ask(4)
learner.tell((-1, -1), -1.0)
learner.ask(1)
learner.tell((-1, 1), -1.0)
learner.tell((1, -1), 1.0)
learner.ask(2)
def test_learnerND_runs_to_10_points_Blocking(execution_number):
learner = LearnerND(ring_of_fire, bounds=[(-1, 1), (-1, 1)])
BlockingRunner(learner, goal=lambda l: l.npoints >= 10)
assert learner.npoints >= 10
def test_learnerND_runs_to_10_points():
learner = LearnerND(ring_of_fire, bounds=[(-1, 1), (-1, 1)])
SimpleRunner(learner, goal=lambda l: l.npoints >= 10)
assert learner.npoints == 10