DataReal

class aixd.data.DataReal(name: str, dim: int = 1, domain: Interval | None = None, unit: str = None, position: int = None, position_index: int = None, transformations: List[str] | List[DataObjectTransform] = None, dtype: str = 'float64', flag_split_perdim: bool = False)

Bases: DataObject

Real data type.

Parameters:

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

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

• domain (Interval, optional, default=None) – Domain of the data object.

• 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).

• position (int, optional, default=None) – Position of the data object in the vector.

• position_index (int, optional, default=None) – Index of the data object in the vector.

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

• dtype (str, optional, default=”float64”) – 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.

Methods

from_range	Class method to initialization a DataReal from a range defined by vmin and vmax.
get_activation_outhead	Tries to interfere the activation function for the output head, based on the last transformation.
get_loss_evaluation	Returns the evaluation loss function for this feature.
get_ml_heads	Returns a fully-connected head for encoding and decoding this feature.
get_objective	Returns the loss function for approximating this feature.