TransformMixIn#

class pytorch_forecasting.data.encoders.TransformMixIn[source]#

Bases: object

Mixin for providing pre- and post-processing capabilities to encoders.

Class should have a transformation attribute to indicate how to preprocess data.

Inherited-members

Methods

`get_transform`(transformation)	Return transformation functions.
`inverse_preprocess`(y)	Inverse preprocess re-scaled data (e.g.
`preprocess`(y)	Preprocess input data (e.g.

Attributes

TRANSFORMATIONS

classmethod get_transform(transformation: Union[str, Dict[str, Callable]]) → Dict[str, Callable][source]#

Return transformation functions.

Parameters: transformation (Union[str, Dict[str, Callable]]) – name of transformation or dictionary with transformation information.
Returns: dictionary with transformation functions (forward, reverse, inverse and inverse_torch)
Return type: Dict[str, Callable]

inverse_preprocess(y: Union[pandas.core.series.Series, numpy.ndarray, torch.Tensor]) → Union[numpy.ndarray, torch.Tensor][source]#

Inverse preprocess re-scaled data (e.g. take exp).

Uses transform attribute to determine how to apply inverse transform.

Returns: return rescaled series with type depending on input type
Return type: Union[np.ndarray, torch.Tensor]

preprocess(y: Union[pandas.core.series.Series, pandas.core.frame.DataFrame, numpy.ndarray, torch.Tensor]) → Union[numpy.ndarray, torch.Tensor][source]#

Preprocess input data (e.g. take log).

Uses transform attribute to determine how to apply transform.

Returns: return rescaled series with type depending on input type
Return type: Union[np.ndarray, torch.Tensor]

SoftplusTransform

examples