src.pydasa.elements.parameter
=============================

.. py:module:: src.pydasa.elements.parameter

.. autoapi-nested-parse::

   Module parameter.py
   ===========================================

   Module for representing **Variable** entities in Dimensional Analysis for *PyDASA*.

   Classes:
       **Variable**: Represents a Variable with dimensional properties, value ranges, and validation.

   *IMPORTANT:* Based on the theory from:

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



Classes
-------

.. autoapisummary::

   src.pydasa.elements.parameter.Variable


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

.. py:class:: Variable

   Bases: :py:obj:`pydasa.elements.specs.ConceptualSpecs`, :py:obj:`pydasa.elements.specs.SymbolicSpecs`, :py:obj:`pydasa.elements.specs.NumericalSpecs`, :py:obj:`pydasa.elements.specs.StatisticalSpecs`


   **Variable** class for Dimensional Analysis in *PyDASA*.

   A comprehensive implementation that combines Parameter and Variable functionality for use in dimensional analysis calculations, simulations, and sensitivity analysis.

   This class composes four philosophical perspectives through multiple inheritance:
   - **ConceptualSpecs**: Identity and classification (what IS this variable?)
   - **SymbolicSpecs**: Mathematical representation (how do we WRITE it?)
   - **NumericalSpecs**: Computational values (what VALUES can it take?)
   - **StatisticalSpecs**: Probabilistic modeling (how do we MODEL uncertainty?)

   All attributes, properties, and methods are inherited from the spec classes.

   This class only provides integration logic and utility methods.

   .. attribute:: # From Foundation

      

      :type: via ConceptualSpecs

   .. attribute:: _name

      User-friendly name of the variable.

      :type: str

   .. attribute:: description

      Brief summary of the variable.

      :type: str

   .. attribute:: _idx

      Index/precedence in the dimensional matrix.

      :type: int

   .. attribute:: _sym

      Symbol representation (LaTeX or alphanumeric).

      :type: str

   .. attribute:: _alias

      Python-compatible alias for use in code.

      :type: str

   .. attribute:: _fwk

      Frameworks context (PHYSICAL, COMPUTATION, SOFTWARE, CUSTOM).

      :type: str

   .. attribute:: # From ConceptualSpecs - Identity and Classification

      

   .. attribute:: _cat

      Category (INPUT, OUT, CTRL).

      :type: str

   .. attribute:: _schema

      Reference to the dimensional framework or FDUs list.

      :type: Schema

   .. attribute:: relevant

      Flag indicating if variable is relevant for analysis.

      :type: bool

   .. attribute:: # From SymbolicSpecs - Dimensional Properties

      

   .. attribute:: _dims

      Dimensional expression (e.g., "L*T^-1").

      :type: str

   .. attribute:: _units

      Units of measure (e.g., "m/s").

      :type: str

   .. attribute:: _sym_exp

      Sympy-compatible expression.

      :type: str

   .. attribute:: _dim_col

      Dimensional column for matrix operations.

      :type: List[int]

   .. attribute:: # From SymbolicSpecs - Standardized Dimensional Properties

      

   .. attribute:: _std_dims

      Standardized dimensional expression.

      :type: str

   .. attribute:: _std_units

      Standardized units of measure.

      :type: str

   .. attribute:: # From NumericalSpecs - Value Ranges

      

      :type: Original Units

   .. attribute:: _min

      Minimum value in original units.

      :type: float

   .. attribute:: _max

      Maximum value in original units.

      :type: float

   .. attribute:: _mean

      Mean value in original units.

      :type: float

   .. attribute:: _dev

      Standard deviation in original units.

      :type: float

   .. attribute:: # From NumericalSpecs - Value Ranges

      

      :type: Standardized Units

   .. attribute:: _std_min

      Minimum value in standard units.

      :type: float

   .. attribute:: _std_max

      Maximum value in standard units.

      :type: float

   .. attribute:: _std_mean

      Mean value in standard units.

      :type: float

   .. attribute:: _std_dev

      Standard deviation in standard units.

      :type: float

   .. attribute:: _step

      Step size for simulations.

      :type: float

   .. attribute:: _std_range

      Range array for analysis.

      :type: np.ndarray

   .. attribute:: # From StatisticalSpecs - Distribution Specifications

      

   .. attribute:: _dist_type

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

      :type: str

   .. attribute:: _dist_params

      Parameters for the distribution.

      :type: Dict[str, Any]

   .. attribute:: _depends

      List of variable names that this variable depends on.

      :type: List[str]

   .. attribute:: _dist_func

      Callable representing the distribution function.

      :type: Callable


   .. py:method:: __post_init__()

      *__post_init__()* Initializes the variable and validates its properties.

      Performs validation of core properties and processes dimensional expressions.
      Sets up range arrays if all required values are provided.

      :raises ValueError: If dimensional expression is invalid.



   .. py:method:: clear()

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

      Resets all variable properties to their initial state by calling
      clear() on all composed perspective classes.



   .. py:method:: to_dict()

      *to_dict()* Convert variable to dictionary representation.

      :returns: Dictionary representation of variable.
      :rtype: Dict[str, Any]



   .. py:method:: from_dict(data)
      :classmethod:


      *from_dict()* Create variable from dictionary representation.

      :param data: Dictionary representation of variable.
      :type data: Dict[str, Any]

      :returns: New variable instance.
      :rtype: Variable