def test_choice():
p = choice(partial(int, 15.5), (15, 4), (3, 2))
assert evaluate(p) == 4
p = choice(variable('x', value_type=['a', 'b', 'c']), ('a', 'b'),
('b', 'c'))
assert evaluate(p, x='a') == 'b'
assert evaluate(p, x='b') == 'c'
def test_choice_raises():
raised = False
try:
choice(5, (5, 4), (3, 2, 1))
except ValueError:
raised = True
assert raised
raised = False
try:
choice(5, (5, 4), [3, 4])
except ValueError:
raised = True
assert raised
def test_uniform_choice():
p = as_pyll(choice(variable('foo', value_type=[7, 9, 11]),
(7, 'rst'),
(9, 'uvw'),
(11, 'xyz')))
assert p.name == 'switch'
assert p.pos_args[0].name == 'hyperopt_param'
assert p.pos_args[0].pos_args[0].obj == 'foo'
assert p.pos_args[0].pos_args[1].name == 'randint'
assert p.pos_args[0].pos_args[1].arg['upper'].obj == 3
# Make sure this executes and yields a value in the right domain.
recursive_set_rng_kwarg(p, np.random)
try:
values = [rec_eval(p) for _ in xrange(10)]
except Exception:
assert False
assert all(v in ['rst', 'uvw', 'xyz'] for v in values)
def test_nonuniform_choice():
var = variable('blu', value_type=[2, 4, 8], distribution='categorical',
p=[0.2, 0.7, 0.1])
p = as_pyll(choice(var,
(2, 'abc'),
(4, 'def'),
(8, 'ghi')))
assert p.name == 'switch'
assert p.pos_args[0].name == 'hyperopt_param'
assert p.pos_args[0].pos_args[0].obj == 'blu'
assert p.pos_args[0].pos_args[1].name == 'categorical'
assert p.pos_args[0].pos_args[1].arg['p'].name == 'pos_args'
assert p.pos_args[0].pos_args[1].arg['p'].pos_args[0].obj == 0.2
assert p.pos_args[0].pos_args[1].arg['p'].pos_args[1].obj == 0.7
assert p.pos_args[0].pos_args[1].arg['p'].pos_args[2].obj == 0.1
# Make sure this executes and yields a value in the right domain.
recursive_set_rng_kwarg(p, np.random)
try:
values = [rec_eval(p) for _ in xrange(10)]
except Exception:
assert False
assert all(v in ['abc', 'def', 'ghi'] for v in values)
