:py:mod:`causal_testing.specification.scenario`
===============================================

.. py:module:: causal_testing.specification.scenario

.. autoapi-nested-parse::

   This module holds the Scenario Class



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

Classes
~~~~~~~

.. autoapisummary::

   causal_testing.specification.scenario.Scenario




.. py:class:: Scenario(variables: collections.abc.Iterable[causal_testing.specification.variable.Variable], constraints: set[str] = None)


   A scenario defines the setting by listing the endogenous variables, their
   datatypes, distributions, and any constraints over them. This is a common
   practice in CI and is analogous to an investigator specifying “we are
   interested in individuals over 40 who regularly eat cheese” or whatever. A
   scenario, here, is not a specific test case; it just defines the population
   of interest, in our case “runs of the model with parameters meeting the
   constraints”. The model may have other inputs/outputs which the investigator
   may choose to leave out. These are then exogenous variables and behave
   accordingly.

   :param {Variable} variables: The set of endogenous variables.
   :param {str} constraints: The set of constraints relating the endogenous variables.
   :attr variables:
   :attr constraints:

   .. py:method:: hidden_variables() -> set[causal_testing.specification.variable.Variable]

      Get the set of hidden variables

      :return The variables marked as hidden.
      :rtype: {Variable}