DataInt.from_options

classmethod DataInt.from_options(name: str, option_list: List[int], dim: int = 1, unit: str | None = None, transformations: List[str] | List[DataObjectTransform] | None = None, normalization: str | DataObjectNormalization | None = None, norm_arg_dict: Dict | None = None, dtype: str = 'int64', flag_split_perdim: bool = False) → DataInt

Class method to initialization a DataInt from a list of integers.

Parameters:

• name (str) – Name of the data object.

• option_list (List[int]) – List of integers to be used as domain.

• dim (int, optional, default=1) – Dimensionality of the data object, or different columns to perform the split on.

• unit (str, optional, default=None) – Unit of the data object (e.g. m, kg. m^2, m/s^2 etc.). Use ^ to indicate powers (e.g. m^2), and _ to indicate subscripts (e.g. m_1).

• transformations (Union[List[str], List[DataObjectTransform]], optional, default=None) – List of transformations to be applied to the data object.

• normalization (Union[str, DataObjectNormalization], optional, default=None) – Normalization to be applied to the data object, by default ‘norm_0to1’ is applied.

• norm_arg_dict (Dict, optional, default=None) – Arguments passed to the normalization, if it was specified by a string.

• dtype (str, optional, default=”int64”) – The dtype of the numpy are of the expected data matrix.

• flag_split_perdim (bool, optional, default=False) – If True, object is split across dimensions in a DataBlock.

Returns:

DataInt – A DataInt object.