src.pydasa.elements.specs.statistical
=====================================

.. py:module:: src.pydasa.elements.specs.statistical

.. autoapi-nested-parse::

   Module statistical.py
   ===========================================

   Statistical perspective for variable representation.

   This module defines the StatisticalSpecs class representing the probabilistic
   distribution and sampling properties of a variable.

   Classes:
       **StatisticalSpecs**: Statistical variable specifications

   *IMPORTANT:* Based on the theory from:

       # H.Gorter, *Dimensionalanalyse: Eine Theoririe der physikalischen Dimensionen mit Anwendungen*



Classes
-------

.. autoapisummary::

   src.pydasa.elements.specs.statistical.StatisticalSpecs


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

.. py:class:: StatisticalSpecs

   Statistical perspective: probabilistic distributions. Answers the question: "How do we MODEL uncertainty?"

   This perspective focuses on:
       - Probability distribution types (uniform, normal, beta, custom)
       - Distribution parameters
       - Random sampling mechanisms
       - Monte Carlo simulation support
       - Uncertainty quantification


   .. py:attribute:: _sym
      :type:  str


   .. py:attribute:: _dist_type
      :type:  str
      :value: 'uniform'


      Type of distribution (e.g., 'uniform', 'normal'). By default is 'uniform'.


   .. py:attribute:: _dist_params
      :type:  Optional[Dict[str, Any]]

      1} for uniform).

      :type: Parameters for the distribution (e.g., {'min'

      :type: 0, 'max'


   .. py:attribute:: _depends
      :type:  List[str]
      :value: []


      List of variable names that this variable depends on. (e.g., for calculated variables like F = m*a).


   .. py:attribute:: _dist_func
      :type:  Optional[Callable[Ellipsis, float]]
      :value: None


      Callable representing the distribution function defined externally by the user.


   .. py:method:: sample(*args)

      *sample()* Generate a random sample.

      :param \*args: Additional arguments for the distribution function.

      :returns: Random sample from distribution.
      :rtype: float

      :raises ValueError: If no distribution has been set.



   .. py:method:: has_function()

      *has_function()* Check if distribution is set.

      :returns: True if distribution is configured.
      :rtype: bool



   .. py:property:: dist_type
      :type: str


      *dist_type* Get the distribution type.

      :returns: Distribution type (e.g., 'uniform', 'normal').
      :rtype: str


   .. py:property:: dist_params
      :type: Optional[Dict[str, Any]]


      *dist_params* Get the distribution parameters.

      :returns: Distribution parameters.
      :rtype: Optional[Dict[str, Any]


   .. py:property:: dist_func
      :type: Optional[Callable[Ellipsis, float]]


      *dist_func* Get the distribution function.

      :returns: Distribution function.
      :rtype: Optional[Callable]


   .. py:property:: depends
      :type: List[str]


      *depends* Get the list of variable dependencies.

      :returns: List of variable names that this variable depends on.
      :rtype: List[str]


   .. py:method:: clear()

      *clear()* Reset statistical attributes to default values.

      Resets distribution type, parameters, and function.