def test_filter():
filter = BoxMasking(10, 20)
# passing an output space that is wrong
with pytest.raises(ValueError):
filter.validate_output_action_space(DiscreteActionSpace(10))
# 1 dimensional box
output_space = BoxActionSpace(1, 5, 30)
input_space = filter.get_unfiltered_action_space(output_space)
action = np.array([2])
result = filter.filter(action)
assert result == np.array([12])
assert output_space.val_matches_space_definition(result)
def test_filter():
filter = BoxDiscretization(9)
# passing an output space that is wrong
with pytest.raises(ValueError):
filter.validate_output_action_space(DiscreteActionSpace(10))
# 1 dimensional box
output_space = BoxActionSpace(1, 5, 15)
input_space = filter.get_unfiltered_action_space(output_space)
assert filter.target_actions == [[5.], [6.25], [7.5], [8.75], [10.],
[11.25], [12.5], [13.75], [15.]]
assert input_space.actions == list(range(9))
action = 2
result = filter.filter(action)
assert result == [7.5]
assert output_space.val_matches_space_definition(result)
# 2 dimensional box
filter = BoxDiscretization(3)
output_space = BoxActionSpace(2, 5, 15)
input_space = filter.get_unfiltered_action_space(output_space)
assert filter.target_actions == [[5., 5.], [5., 10.], [5., 15.], [10., 5.],
[10., 10.], [10., 15.], [15., 5.],
[15., 10.], [15., 15.]]
assert input_space.actions == list(range(9))
action = 2
result = filter.filter(action)
assert result == [5., 15.]
assert output_space.val_matches_space_definition(result)