timesead.data.transforms.dataset_source
=======================================

.. py:module:: timesead.data.transforms.dataset_source


Classes
-------

.. autoapisummary::

   timesead.data.transforms.dataset_source.DatasetSource


Functions
---------

.. autoapisummary::

   timesead.data.transforms.dataset_source.make_dataset_split


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

.. py:class:: DatasetSource(dataset: timesead.data.dataset.BaseTSDataset, start: Union[int, List[int]] = None, end: Union[int, List[int]] = None, axis: str = 'batch')

   Bases: :py:obj:`timesead.data.transforms.transform_base.Transform`


   This acts as a source :class:`~timesead.data.transforms.Transform` (meaning it has no parent) that simply returns
   sequences from a given dataset.
   It can be constrained to return only a specific part of the data.

   :param dataset: The dataset from which to take points.
   :param start: Start index for this dataset. Please see below for a more detailed explanation.
   :param end: End index for this dataset (exclusive). Please see below for a more detailed explanation.
   :param axis: Can be either 'batch' or 'time'. In 'batch' mode, this simply returns only the sequences indexed
       from `start` to `end`. 'time' mode is used for datasets that contain only one long time series. That time
       series will be cut according to `start` and `end`.


   .. py:attribute:: dataset


   .. py:attribute:: axis
      :value: 'batch'



   .. py:method:: __len__()

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



   .. py:property:: seq_len

      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

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


.. py:function:: make_dataset_split(dataset: timesead.data.dataset.BaseTSDataset, *splits: float, axis: str = 'batch')

   Create :class:`DatasetSource`\s for different parts of a given dataset.

   :param dataset: The dataset, for which the split should be done.
   :param splits: This should be the percentages of the dataset in each split. Will be normalized to 100%.
   :param axis: The axis along which to split the dataset. Please see :class:`DatasetSource` for a more detailed
       explanation.
   :return: This will return a generator that yields :class:`DatasetSource`\s according to the specified splits.