pdstools.infinity.resources.prediction_studio.v24_2.prediction
==============================================================

.. py:module:: pdstools.infinity.resources.prediction_studio.v24_2.prediction


Classes
-------

.. autoapisummary::

   pdstools.infinity.resources.prediction_studio.v24_2.prediction.Prediction
   pdstools.infinity.resources.prediction_studio.v24_2.prediction.AsyncPrediction


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

.. py:class:: Prediction(client, *, predictionId: str, label: str, status: str, lastUpdateTime: str, objective: str | None = None, subject: str | None = None)

   Bases: :py:obj:`_PredictionV24_2Mixin`, :py:obj:`pdstools.infinity.resources.prediction_studio.v24_1.prediction.Prediction`


   The ``Prediction`` class provide functionality including retrieving
   notifications, models, adding conditional models, getting champion
   challengers, metrics, and plotting metrics.


   .. py:method:: get_notifications(category: pdstools.infinity.resources.prediction_studio.types.NotificationCategory | None = None, return_df: Literal[False] = False) -> pdstools.infinity.internal._pagination.PaginatedList[pdstools.infinity.resources.prediction_studio.base.Notification]
                  get_notifications(category: pdstools.infinity.resources.prediction_studio.types.NotificationCategory | None = None, return_df: Literal[True] = True) -> polars.DataFrame

      Fetches a list of notifications for a specific prediction.

      This function retrieves notifications related to a prediction. You
      can filter these notifications by their category.  Optionally, the
      notifications can be returned as a DataFrame for easier analysis
      and visualization.

      :param category: The category of notifications to retrieve. If not specified,
                       all notifications are fetched.
      :type category: {"All", "Responses", "Performance", "Model approval", "Output", "Predictors", "Prediction deployment", "Generic"} or None
      :param return_df: If True, returns the notifications as a DataFrame. Otherwise,
                        returns a list.
      :type return_df: bool, default False

      :returns: A list of notifications or a DataFrame containing the
                notifications, depending on the value of ``return_df``.
      :rtype: PaginatedList[Notification] or polars.DataFrame



   .. py:method:: get_champion_challengers()

      Fetches list of ChampionChallenger objects linked to the prediction.

      This function fetches Champion-challenger pairs from a prediction.
      In cases where a challenger model is absent, it returns a
      ChampionChallenger object containing only the champion model.

      :returns: A list of entries, each pairing a primary model with its
                challenger across various segments of the prediction.
      :rtype: list of ChampionChallenger



   .. py:method:: add_conditional_model(new_model, category: str, context: str | None = None)

      Incorporates a new model into a prediction for a specified category
      and context.

      :param new_model: Identifier of the model to be added.
      :type new_model: str or Model
      :param category: The category under which the model will be classified.
      :type category: str
      :param context: The specific context or scenario in which the model will be
                      utilized.
      :type context: str, optional

      :returns: An object detailing the updated configuration with the newly
                added model.
      :rtype: ChampionChallenger



.. py:class:: AsyncPrediction(client, *, predictionId: str, label: str, status: str, lastUpdateTime: str, objective: str | None = None, subject: str | None = None)

   Bases: :py:obj:`_PredictionV24_2Mixin`, :py:obj:`pdstools.infinity.resources.prediction_studio.v24_1.prediction.AsyncPrediction`


   Async variant of the v24.2 Prediction.


   .. py:method:: get_notifications(category: pdstools.infinity.resources.prediction_studio.types.NotificationCategory | None = None, return_df: bool = False) -> pdstools.infinity.internal._pagination.AsyncPaginatedList[pdstools.infinity.resources.prediction_studio.base.AsyncNotification] | polars.DataFrame
      :async:


      Fetches a list of notifications for a specific prediction.

      :param category: The category of notifications to retrieve.
      :type category: {"All", "Responses", "Performance", "Model approval", "Output", "Predictors", "Prediction deployment", "Generic"} or None
      :param return_df: If True, returns the notifications as a DataFrame.
      :type return_df: bool, default False

      :returns: A list of notifications or a DataFrame.
      :rtype: AsyncPaginatedList[AsyncNotification] or polars.DataFrame



   .. py:method:: get_champion_challengers()
      :async:


      Fetches list of ChampionChallenger objects linked to the prediction.

      :returns: Champion-challenger pairs from a prediction.
      :rtype: list of AsyncChampionChallenger



   .. py:method:: add_conditional_model(new_model, category: str, context: str | None = None)
      :async:


      Incorporates a new model into a prediction for a specified category
      and context.

      :param new_model: Identifier of the model to be added.
      :type new_model: str or AsyncModel
      :param category: The category under which the model will be classified.
      :type category: str
      :param context: The specific context or scenario.
      :type context: str, optional

      :returns: An object detailing the updated configuration.
      :rtype: AsyncChampionChallenger