@pytest.mark.parametrize( "func", [ 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,
@pytest.mark.parametrize( "func", [ 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(