def test_to_interval_size_format(
transform, target, expected, convert_to_np, is_train
):
if convert_to_np:
target = np.array(target)
data_set = ListDataset(
[{"target": target, "start": "2010-01-01"}], freq="1m"
)
if transform.drop_empty:
try:
next(transform(data_set, is_train=is_train))
except StopIteration:
return
transformed = next(transform(data_set, is_train=is_train))
assert np.allclose(transformed["target"], expected)
def test_count_trailing_zeros(target, expected, convert_to_np, is_train):
if convert_to_np:
target = np.array(target)
data_set = ListDataset(
[{"target": target, "start": "2010-01-01"}], freq="1m"
)
transform = CountTrailingZeros(new_field="time_remaining")
transformed = next(transform(data_set, is_train=is_train))
if len(target) == 0:
assert "time_remaining" not in transformed
return
assert "time_remaining" in transformed
assert transformed["time_remaining"] == expected
