def test_duplicate_with_ignored_and_pending(self):
space = [{
'name': 'var_1',
'type': 'continuous',
'domain': (-3, 1),
'dimensionality': 1
}, {
'name': 'var_2',
'type': 'discrete',
'domain': (0, 1, 2, 3)
}, {
'name': 'var_3',
'type': 'categorical',
'domain': (0, 1)
}]
design_space = Design_space(space)
np.random.seed(666)
number_points = 5
zipped_X = initial_design("random", design_space, number_points)
pending_zipped_X = initial_design("random", design_space,
number_points)
ignored_zipped_X = initial_design("random", design_space,
number_points)
d = DuplicateManager(design_space, zipped_X, pending_zipped_X,
ignored_zipped_X)
duplicate_in_pending_state = np.atleast_2d(
pending_zipped_X[0, :].copy())
assert d.is_zipped_x_duplicate(duplicate_in_pending_state)
assert d.is_unzipped_x_duplicate(
design_space.unzip_inputs(duplicate_in_pending_state))
duplicate_in_ignored_state = np.atleast_2d(
ignored_zipped_X[0, :].copy())
assert d.is_zipped_x_duplicate(duplicate_in_ignored_state)
assert d.is_unzipped_x_duplicate(
design_space.unzip_inputs(duplicate_in_ignored_state))
def test_duplicate(self):
space = [{
'name': 'var_1',
'type': 'continuous',
'domain': (-3, 1),
'dimensionality': 1
}, {
'name': 'var_2',
'type': 'discrete',
'domain': (0, 1, 2, 3)
}, {
'name': 'var_3',
'type': 'categorical',
'domain': (0, 1)
}]
design_space = Design_space(space)
np.random.seed(666)
number_points = 5
zipped_X = initial_design("random", design_space, number_points)
d = DuplicateManager(design_space, zipped_X)
duplicate = np.atleast_2d(zipped_X[0, :].copy())
assert d.is_zipped_x_duplicate(duplicate)
assert d.is_unzipped_x_duplicate(design_space.unzip_inputs(duplicate))
non_duplicate = np.array([[-2.5, 2., 0.]])
for x in zipped_X:
assert not np.all(non_duplicate == x)
assert not d.is_zipped_x_duplicate(non_duplicate)
assert not d.is_unzipped_x_duplicate(
design_space.unzip_inputs(non_duplicate))