czbenchmarks.tasks.single_cell.cross_species_integration
========================================================

.. py:module:: czbenchmarks.tasks.single_cell.cross_species_integration


Classes
-------

.. autoapisummary::

   czbenchmarks.tasks.single_cell.cross_species_integration.CrossSpeciesIntegrationTaskInput
   czbenchmarks.tasks.single_cell.cross_species_integration.CrossSpeciesIntegrationOutput
   czbenchmarks.tasks.single_cell.cross_species_integration.CrossSpeciesIntegrationTask


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

.. py:class:: CrossSpeciesIntegrationTaskInput(/, **data: Any)

   Bases: :py:obj:`czbenchmarks.tasks.task.TaskInput`


   Pydantic model for CrossSpeciesIntegrationTask inputs.

   Create a new model by parsing and validating input data from keyword arguments.

   Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
   validated to form a valid model.

   `self` is explicitly positional-only to allow `self` as a field name.


   .. py:attribute:: labels
      :type:  List[czbenchmarks.types.ListLike]


   .. py:attribute:: organism_list
      :type:  List[czbenchmarks.datasets.types.Organism]


.. py:class:: CrossSpeciesIntegrationOutput(/, **data: Any)

   Bases: :py:obj:`czbenchmarks.tasks.task.TaskOutput`


   Output for cross-species integration task.

   Create a new model by parsing and validating input data from keyword arguments.

   Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
   validated to form a valid model.

   `self` is explicitly positional-only to allow `self` as a field name.


   .. py:attribute:: cell_representation
      :type:  czbenchmarks.tasks.types.CellRepresentation


   .. py:attribute:: labels
      :type:  czbenchmarks.types.ListLike


   .. py:attribute:: species
      :type:  czbenchmarks.types.ListLike


.. py:class:: CrossSpeciesIntegrationTask(*, random_seed: int = RANDOM_SEED)

   Bases: :py:obj:`czbenchmarks.tasks.task.Task`


   Task for evaluating cross-species integration quality.

   This task computes metrics to assess how well different species' data are integrated
   in the embedding space while preserving biological signals. It operates on multiple
   datasets from different species.

   :param random_seed: Random seed for reproducibility
   :type random_seed: int


   .. py:attribute:: display_name
      :value: 'Cross-species Integration'



   .. py:attribute:: description
      :value: 'Evaluate cross-species integration quality using various integration metrics.'



   .. py:attribute:: input_model


   .. py:attribute:: requires_multiple_datasets
      :value: True



   .. py:method:: compute_baseline(**kwargs)
      :abstractmethod:


      Set a baseline embedding for cross-species integration.

      This method is not implemented for cross-species integration tasks
      as standard preprocessing workflows are not directly applicable
      across different species.

      :raises NotImplementedError: Always raised as baseline is not implemented