src.pydasa.elements.specs.conceptual
====================================

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

.. autoapi-nested-parse::

   Module conceptual.py
   ===========================================

   Conceptual perspective for variable representation.

   This module defines the ConceptualSpecs class representing the abstract
   identity and classification of a variable.

   Classes:
       **ConceptualSpecs**: Conceptual variable specifications

   *IMPORTANT:* Based on the theory from:

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



Classes
-------

.. autoapisummary::

   src.pydasa.elements.specs.conceptual.ConceptualSpecs


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

.. py:class:: ConceptualSpecs

   Bases: :py:obj:`pydasa.core.basic.Foundation`


   Conceptual perspective: variable identity and classification.

   Answers the fundamental question: "What IS this variable?". This perspective focuses on:
       - What category does it belong to? (INPUT, OUTPUT, CONTROL)
       - Which framework is it part of? (PHYSICAL, COMPUTATION, SOFTWARE, CUSTOM)
       - Is it relevant for the current analysis?
       - What dimensional framework does it use?

   .. attribute:: # From Foundation

      _name (str): User-friendly name of the variable.
      description (str): Brief summary of the variable.
      _idx (int): Index/precedence in the dimensional matrix.
      _sym (str): Symbol representation (LaTeX or alphanumeric).
      _alias (str): Python-compatible alias for use in code.
      _fwk (str): Frameworks context (PHYSICAL, COMPUTATION, SOFTWARE, CUSTOM).

   .. attribute:: # From ConceptualSpecs

      _schema (Optional[Schema]): Reference to the dimensional framework schema.
      _cat (str): Category of the variable (INPUT, OUTPUT, CONTROL).
      relevant (bool): Flag indicating if variable is relevant for analysis.


   .. py:attribute:: _schema
      :type:  Optional[pydasa.dimensional.vaschy.Schema]
      :value: None


      Reference to the dimensional framework schema.


   .. py:attribute:: _cat
      :type:  str
      :value: 'IN'


      Category of the variable (INPUT, OUT, CTRL).


   .. py:attribute:: relevant
      :type:  bool
      :value: False


      Flag indicating if variable is relevant for analysis.


   .. py:method:: _validate_in_list(value, prec_lt)

      *_validate_in_list()* Validates if a value exists in a list of allowed values.

      :param value: Value to validate.
      :type value: str
      :param prec_lt: List of allowed values.
      :type prec_lt: List[str]

      :returns: True if the value is in the list, False otherwise.
      :rtype: bool



   .. py:property:: cat
      :type: str


      *cat* Get the category of the variable.

      :returns: Category (INPUT, OUT, CTRL).
      :rtype: str


   .. py:property:: schema
      :type: Optional[pydasa.dimensional.vaschy.Schema]


      *schema* Get the dimensional schema reference.

      :returns: The dimensional framework schema.
      :rtype: Optional[Schema]


   .. py:method:: clear()

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

      Resets category, schema, and relevance flag.