def test_one_point(): pbounds = {'p1': (0, 1), 'p2': (1, 100)} space = TargetSpace(target_func, pbounds) x = space.random_points(1)[0] space.observe_point(x) space._assert_internal_invariants(fast=False) assert space._n_alloc_rows > len(space)
def test_observe_m_nd_points(m, n): pbounds = {'p{}'.format(i): (0, i) for i in range(n)} space = TargetSpace(target_func, pbounds) for x in space.random_points(m): space.observe_point(x) space._assert_internal_invariants(fast=False) space._assert_internal_invariants(fast=False)
def test_two_points(): """ pytest tests/test_target_space.py::test_two_points """ pbounds = {'p1': (0, 1), 'p2': (1, 100)} space = TargetSpace(target_func, pbounds) for x in space.random_points(2): space.observe_point(x) space._assert_internal_invariants(fast=False) space._assert_internal_invariants(fast=False) assert space._n_alloc_rows == len(space)
def test_contains(): # Simply re-observing a non-unique values returns the cached result pbounds = {'p1': (0, 1), 'p2': (1, 100)} space = TargetSpace(target_func, pbounds) # add 1000 random points for x in space.random_points(1000): space.observe_point(x) # now all points should be unique, so test contains space2 = TargetSpace(target_func, pbounds) for x in space.X: assert x not in space2 y = space2.observe_point(x) assert x in space2 assert y == space2.observe_point(x) space2._assert_internal_invariants(fast=False)