def validate_input_observation_space(
self, input_observation_space: ObservationSpace):
crop_high = self._replace_negative_one_in_crop_size(
self.crop_high, input_observation_space.shape)
crop_low = self._replace_negative_one_in_crop_size(
self.crop_low, input_observation_space.shape)
if np.any(crop_high > input_observation_space.shape) or \
np.any(crop_low > input_observation_space.shape):
raise ValueError(
"The cropping values are outside of the observation space")
if not input_observation_space.is_point_in_space_shape(crop_low) or \
not input_observation_space.is_point_in_space_shape(crop_high - 1):
raise ValueError(
"The cropping indices are outside of the observation space")
def test_observation_space():
observation_space = ObservationSpace(np.array([1, 10]), -10, 10)
# testing that val_matches_space_definition works
assert observation_space.val_matches_space_definition(np.ones([1, 10]))
assert not observation_space.val_matches_space_definition(np.ones([2, 10]))
assert not observation_space.val_matches_space_definition(
np.ones([1, 10]) * 100)
assert not observation_space.val_matches_space_definition(
np.ones([1, 1, 10]))
# is_point_in_space_shape
assert observation_space.is_point_in_space_shape(np.array([0, 9]))
assert observation_space.is_point_in_space_shape(np.array([0, 0]))
assert not observation_space.is_point_in_space_shape(np.array([1, 8]))
assert not observation_space.is_point_in_space_shape(np.array([0, 10]))
assert not observation_space.is_point_in_space_shape(np.array([-1, 6]))
