def __post_init__(self) -> None:
if isinstance(self.target, list) and len(self.target) == 1:
self.target = self.target[0]
self.one_dim_target = not isinstance(self.target, list)
self.process = ProcessDataEntry(self.freq,
one_dim_target=self.one_dim_target)
# store data internally as List[Tuple[str, pandas.DataFrame]]
# if str is not empty it will be set in ``DataEntry`` as ``item_id``.
if isinstance(self.dataframes, dict):
self._dataframes = list(self.dataframes.items())
elif isinstance(self.dataframes, list):
self._dataframes = [("", df) for df in self.dataframes]
else: # case single dataframe
self._dataframes = [("", self.dataframes)]
def test_timeseries_item_serialization() -> None:
ts_item = TimeSeriesItem(
item="1",
start="2014-09-07 00:00:00",
target=[1, 2],
feat_static_cat=[1],
)
metadata = MetaData(
freq="1H",
feat_static_cat=[{"name": "feat_static_cat_000", "cardinality": 1}],
)
process = ProcessDataEntry(freq=metadata.freq)
data_entry = process(ts_item.gluontsify(metadata))
serialized_data = serialize_data_entry(data_entry)
deserialized_ts_item = TimeSeriesItem(**serialized_data)
assert deserialized_ts_item == ts_item