def test_get_random_seed_rng():
def make_mock_random_state(return_value):
class MockRandomState(np.random.RandomState):
def __init__(self):
self.min_bound = None
self.max_bound = None
super().__init__()
def randint(self, min_bound, max_bound):
self.min_bound = min_bound
self.max_bound = max_bound
return return_value
return MockRandomState()
rng = make_mock_random_state(42)
assert get_random_seed(rng) == 42
assert rng.min_bound == SEED_BOUNDS.min_bound
assert rng.max_bound == SEED_BOUNDS.max_bound
def test_get_random_seed_int():
# ensure the invariant "min_bound < max_bound" is enforced
with pytest.raises(ValueError):
get_random_seed(0, min_bound=0, max_bound=0)
with pytest.raises(ValueError):
get_random_seed(0, min_bound=0, max_bound=-1)
# test default boundaries to show the provided value should modulate within the default range
assert get_random_seed(SEED_BOUNDS.max_bound - 2) == SEED_BOUNDS.max_bound - 2
assert get_random_seed(SEED_BOUNDS.max_bound - 1) == SEED_BOUNDS.max_bound - 1
assert get_random_seed(SEED_BOUNDS.max_bound) == SEED_BOUNDS.min_bound
assert get_random_seed(SEED_BOUNDS.max_bound + 1) == SEED_BOUNDS.min_bound + 1
assert get_random_seed(SEED_BOUNDS.max_bound + 2) == SEED_BOUNDS.min_bound + 2
assert get_random_seed(SEED_BOUNDS.min_bound - 2) == SEED_BOUNDS.max_bound - 2
assert get_random_seed(SEED_BOUNDS.min_bound - 1) == SEED_BOUNDS.max_bound - 1
assert get_random_seed(SEED_BOUNDS.min_bound) == SEED_BOUNDS.min_bound
assert get_random_seed(SEED_BOUNDS.min_bound + 1) == SEED_BOUNDS.min_bound + 1
assert get_random_seed(SEED_BOUNDS.min_bound + 2) == SEED_BOUNDS.min_bound + 2
# vectorize get_random_seed via a wrapper for easy evaluation
default_min_bound = inspect.signature(get_random_seed).parameters['min_bound'].default
default_max_bound = inspect.signature(get_random_seed).parameters['max_bound'].default
assert default_min_bound == SEED_BOUNDS.min_bound
assert default_max_bound == SEED_BOUNDS.max_bound
def get_random_seed_vec(min_bound=None, max_bound=None): # passing None for either means no value is provided to get_random_seed
def get_random_seed_wrapper(random_seed):
return get_random_seed(random_seed,
min_bound=min_bound if min_bound is not None else default_min_bound,
max_bound=max_bound if max_bound is not None else default_max_bound)
return np.vectorize(get_random_seed_wrapper)
# ensure that regardless of the setting of min_bound and max_bound, the output of get_random_seed always stays
# between the min_bound (inclusive) and max_bound (exclusive), and wraps neatly around that range using modular arithmetic.
vals = np.arange(-100, 100)
def make_expected_values(vals, min_bound, max_bound):
return np.array([i if (min_bound <= i and i < max_bound) else ((i - min_bound) % (max_bound - min_bound)) + min_bound
for i in vals])
np.testing.assert_equal(get_random_seed_vec(min_bound=None, max_bound=None)(vals),
make_expected_values(vals, min_bound=SEED_BOUNDS.min_bound, max_bound=SEED_BOUNDS.max_bound))
np.testing.assert_equal(get_random_seed_vec(min_bound=None, max_bound=10)(vals),
make_expected_values(vals, min_bound=SEED_BOUNDS.min_bound, max_bound=10))
np.testing.assert_equal(get_random_seed_vec(min_bound=-10, max_bound=None)(vals),
make_expected_values(vals, min_bound=-10, max_bound=SEED_BOUNDS.max_bound))
np.testing.assert_equal(get_random_seed_vec(min_bound=0, max_bound=5)(vals),
make_expected_values(vals, min_bound=0, max_bound=5))
np.testing.assert_equal(get_random_seed_vec(min_bound=-5, max_bound=0)(vals),
make_expected_values(vals, min_bound=-5, max_bound=0))
np.testing.assert_equal(get_random_seed_vec(min_bound=-5, max_bound=5)(vals),
make_expected_values(vals, min_bound=-5, max_bound=5))
np.testing.assert_equal(get_random_seed_vec(min_bound=5, max_bound=10)(vals),
make_expected_values(vals, min_bound=5, max_bound=10))
np.testing.assert_equal(get_random_seed_vec(min_bound=-10, max_bound=-5)(vals),
make_expected_values(vals, min_bound=-10, max_bound=-5))
def get_random_seed_wrapper(random_seed):
return get_random_seed(random_seed,
min_bound=min_bound if min_bound is not None else default_min_bound,
max_bound=max_bound if max_bound is not None else default_max_bound)