czbenchmarks.tasks.single_cell.perturbation
===========================================

.. py:module:: czbenchmarks.tasks.single_cell.perturbation


Attributes
----------

.. autoapisummary::

   czbenchmarks.tasks.single_cell.perturbation.logger


Classes
-------

.. autoapisummary::

   czbenchmarks.tasks.single_cell.perturbation.PerturbationTask


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

.. py:data:: logger

.. py:class:: PerturbationTask

   Bases: :py:obj:`czbenchmarks.tasks.base.BaseTask`


   Task for evaluating perturbation prediction quality.

   This task computes metrics to assess how well a model predicts gene expression
   changes in response to perturbations. Compares predicted vs ground truth
   perturbation effects using MSE and correlation metrics.


   .. py:property:: display_name
      :type: str


      A pretty name to use when displaying task results


   .. py:property:: required_inputs
      :type: Set[czbenchmarks.datasets.DataType]


      Required input data types.

      :returns: Set of required input DataTypes (ground truth perturbation effects)


   .. py:property:: required_outputs
      :type: Set[czbenchmarks.datasets.DataType]


      Required output data types.

      :returns: required output types from models this task to run
                (predicted perturbation effects)


   .. py:method:: set_baseline(data: czbenchmarks.datasets.PerturbationSingleCellDataset, gene_pert: str, baseline_type: Literal['median', 'mean'] = 'median', **kwargs)

      Set a baseline embedding for perturbation prediction.

      Creates baseline predictions using simple statistical methods (median and mean)
      applied to the control data, and evaluates these predictions against ground
      truth.

      :param data: PerturbationSingleCellDataset containing control and perturbed data
      :param gene_pert: The perturbation gene to evaluate
      :param baseline_type: The statistical method to use for baseline prediction
                            (median or mean)
      :param \*\*kwargs: Additional arguments passed to the evaluation

      :returns: List of MetricResult objects containing baseline performance metrics
                for different statistical methods (median, mean)