def test_split_by_type():
domain = Domain({"x": [1, 2], "y": {-3, 2, 5}, "z": {"small", 1, 0.1}})
discr, cat, cont = domain.split_by_type()
assert sum(domain.split_by_type(), Domain({})) == domain
assert discr == Domain({"y": {-3, 2, 5}})
assert cat == Domain({"z": {"small", 1, 0.1}})
assert cont == Domain({"x": [1, 2]})
def __init__(self,
domain: Domain,
sample_continuous: bool = False,
seed: int = None):
"""Initialise the :class:`GridSearch` optimiser from a discrete domain.
If the domain contains continuous subspaces, then they could be sampled
if `sample_continuous` is enabled.
Args:
domain: :class:`Domain`. The domain to iterate over.
sample_continuous: (optional) :obj:`bool`. Whether to sample the
continuous subspaces of the domain.
seed: (optional) :obj:`int`. Seed for the sampling of the continuous
subspace if necessary.
"""
if domain.is_continuous and not sample_continuous:
raise DomainNotIterableError(
"Cannot perform grid search on (partially) continuous domain. "
"To enable grid search in this case, set the argument "
"'sample_continuous' to True.")
super(GridSearch, self).__init__(domain)
(discrete_domain, categorical_domain,
continuous_domain) = domain.split_by_type()
# unify the discrete and the categorical into one,
# as they can be iterated:
self.discrete_domain = discrete_domain + categorical_domain
if seed is not None:
self.continuous_domain = Domain(continuous_domain.as_dict(),
seed=seed)
else:
self.continuous_domain = continuous_domain
self._discrete_domain_iter = iter(self.discrete_domain)
self._is_exhausted = len(self.discrete_domain) == 0
self.__exhausted_err = ExhaustedSearchSpaceError(
"The domain has been exhausted. Reset the optimiser to start again."
)
