def test_learnerND_curvature_inits_loss_depends_on_neighbors_correctly():
loss = curvature_loss_function()
assert loss.nth_neighbors == 1
learner = LearnerND(ring_of_fire,
bounds=[(-1, 1), (-1, 1)],
loss_per_simplex=loss)
assert learner.nth_neighbors == 1
def test_learnerND_raises_if_too_many_neigbors():
@uses_nth_neighbors(2)
def loss(*args):
return 0
assert loss.nth_neighbors == 2
with pytest.raises(NotImplementedError):
LearnerND(ring_of_fire, bounds=[(-1, 1), (-1, 1)], loss_per_simplex=loss)
def test_learnerND_accepts_ConvexHull_as_input():
triangle = ConvexHull([(0, 1), (2, 0), (0, 0)])
learner = LearnerND(ring_of_fire, bounds=triangle)
assert learner.nth_neighbors == 0
assert np.allclose(learner._bbox, [(0, 2), (0, 1)])
def test_learnerND_inits_loss_depends_on_neighbors_correctly():
learner = LearnerND(ring_of_fire, bounds=[(-1, 1), (-1, 1)])
assert learner.nth_neighbors == 0