ksuit.data.wrappers.property_subset_wrapper
===========================================

.. py:module:: ksuit.data.wrappers.property_subset_wrapper


Classes
-------

.. autoapisummary::

   ksuit.data.wrappers.property_subset_wrapper.PropertySubsetWrapper


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

.. py:class:: PropertySubsetWrapper(dataset, properties)

   Bases: :py:obj:`ksuit.data.base.DatasetWrapper`


   Wrapper around arbitrary ksuit.data.Dataset instances to make __getitem__ load the properties that are defined
   in the `properties` attribute of this wrapper. For example, if we have a dataset that contains three kinds of items: "x", "y", and "z"
   (i.e., the dataset implements `getitem_x`, `getitem_y`, and `getitem_z` methods), we can create a PropertySubsetWrapper around that dataset with `properties={"x", "y"}`.
   to only load "x" and "y" when __getitem__ is called. This is useful to avoid loading unnecessary data from disk. For example, it might be that you need different items from the same dataset
   during training and validation. During training you might only need "x" and "y", while during validation you might need "x", "y", and "z".
   By using a PropertySubsetWrapper, you can create two different datasets for training and validation that only load the necessary items.

   .. rubric:: Example

   >>> class DummyDataset(Dataset):
   >>>     def __init__(self):
   >>>         self.data  = torch.arange(10)
   >>>     def getitem_x(self, idx):
   >>>         return self.data[idx] * 2
   >>>     def getitem_y(self, idx):
   >>>         return self.data[idx] + 3
   >>>     def getitem_z(self, idx):
   >>>         return self.data[idx] - 5
   >>>     def __len__(self):
   >>>         return len(self.data)
   >>> dataset = DummyDataset()
   >>> wrapper = PropertySubsetWrapper(dataset=dataset, modes={"x", "y"})
   >>> sample = wrapper[4]  # calls dataset.getitem_x(4) and dataset.getitem_y(4), getitem_z is not called
   >>> sample  # {"x": 8, "y": 7}
   >>> wrapper.properties  # {"x", "y"}

   :param dataset: Base dataset to be wrapped.
   :param properties: Which properties to load from the wrapped dataset when __getitem__ is called.

   :raises TypeError: If modes is not a set.
   :raises ValueError: If modes is empty or if any mode does not correspond to a getitem


   .. py:attribute:: properties


   .. py:method:: from_included_excluded(dataset, included_properties, excluded_properties)
      :classmethod:


      Creates a PropertySubsetWrapper from included and excluded properties.

      :param dataset: Base dataset to be wrapped.
      :param included_properties: If defined, only these properties are included.
      :param excluded_properties: If defined, these properties are excluded.

      :returns: The created PropertySubsetWrapper.
      :rtype: PropertySubsetWrapper