timesead.data.transforms.transform_base
=======================================

.. py:module:: timesead.data.transforms.transform_base


Classes
-------

.. autoapisummary::

   timesead.data.transforms.transform_base.Transform


Module Contents
---------------

.. py:class:: Transform(parent: Optional[Transform])

   Bases: :py:obj:`abc.ABC`


   Base class for all transforms.
   A Transform processes one (or several) data points and outputs them. Transforms can be chained in a pull-based
   pipeline.

   :param parent: Another :class:`~timesead.data.transforms.Transform` which is used as the data source for this
       :class:`~timesead.data.transforms.Transform`.
       Can be `None` in the case of a source.


   .. py:attribute:: parent


   .. py:method:: get_datapoint(item: int) -> Tuple[Tuple[torch.Tensor, Ellipsis], Tuple[torch.Tensor, Ellipsis]]

      Returns a datapoint (in our case this is a sequence) from this transform.

      :param item: Must be `0<=item<len(self)`
      :return: A datapoint of the form `(inputs, targets)`, where `inputs` and `targets` are tuples of tensors.



   .. py:method:: __len__() -> Optional[int]

      This should return the number of available sequences after the transformation.



   .. py:property:: seq_len
      :type: Union[int, List[int]]


      This should return the length of each time series. If the time series have different lengths, the return
      value should be a list that contains the length of each sequence. If all sequences are of equal length,
      this should return an `int`.


   .. py:property:: num_features
      :type: Union[int, Tuple[int, Ellipsis]]


      Number of features of each datapoint. This can also be a tuple if the data has more than one feature dimension.