[
Debug(),
RandomGaussian(),
RandomBinary(),
RandomSymmetricDirichlet(),
BinaryMarkovChain(0.1, 0.1),
Constant(1),
LinearTrend(),
RandomCat([10]),
Lag("foo", 1),
ForEachCat(RandomGaussian()),
Eval("np.random.rand(length)"),
SmoothSeasonality(Constant(12), Constant(0)),
Add(["foo", "foo"]),
Mul(["foo", "foo"]),
NanWhere("foo", "foo"),
Stack([Ref("foo"), Ref("foo")]),
RandomGaussian() + RandomGaussian(),
RandomGaussian() * RandomGaussian(),
RandomGaussian() / RandomGaussian(),
],
)
def test_call_and_repr(func) -> None:
global_state = {}
x = evaluate(BASE_RECIPE, length=10, global_state=global_state)
kwargs = dict(foo=42, bar=23)
np.random.seed(0)
ret = func(
x,
field_name="bar",
length=10,
[
Debug(),
RandomGaussian(),
RandomBinary(),
RandomSymmetricDirichlet(),
BinaryMarkovChain(0.1, 0.1),
Constant(1),
LinearTrend(),
RandomCat([10]),
Lag("foo", 1),
ForEachCat(RandomGaussian()),
Expr("np.random.rand(length)"),
SmoothSeasonality(Constant(12), Constant(0)),
Add(['foo', 'foo']),
Mul(['foo', 'foo']),
NanWhere('foo', 'foo'),
NanWhereNot('foo', 'foo'),
Stack(['foo', 'foo']),
RandomGaussian() + RandomGaussian(),
RandomGaussian() * RandomGaussian(),
RandomGaussian() / RandomGaussian(),
],
)
def test_call_and_repr(func) -> None:
global_state = {}
x = evaluate_recipe(BASE_RECIPE, length=10, global_state=global_state)
kwargs = dict(foo=42, bar=23)
np.random.seed(0)
ret = func(
x,
field_name='bar',