src.pydasa.elements.specs.numerical =================================== .. py:module:: src.pydasa.elements.specs.numerical .. autoapi-nested-parse:: Module numerical.py =========================================== Numerical perspective for variable representation. This module defines the NumericalSpecs class representing the computational value ranges and discretization properties of a variable. Classes: **BoundsSpecs**: Value bounds in original units **StandardizedSpecs**: Standardized value specifications with discretization **NumericalSpecs**: Numerical variable specifications (combines BoundsSpecs and StandardizedSpecs) *IMPORTANT:* Based on the theory from: # H.Gorter, *Dimensionalanalyse: Eine Theoririe der physikalischen Dimensionen mit Anwendungen* Classes ------- .. autoapisummary:: src.pydasa.elements.specs.numerical.BoundsSpecs src.pydasa.elements.specs.numerical.StandardizedSpecs src.pydasa.elements.specs.numerical.NumericalSpecs Module Contents --------------- .. py:class:: BoundsSpecs Value bounds in original units: min, max, mean, deviation, setpoint. This class represents the value ranges and statistical measures in the original (non-standardized) units of a variable. .. attribute:: _setpoint Specific value/point in original units. :type: Optional[float] .. attribute:: _min Minimum value in original units. :type: Optional[float] .. attribute:: _max Maximum value in original units. :type: Optional[float] .. attribute:: _mean Mean value in original units. :type: Optional[float] .. attribute:: _median Median value in original units. :type: Optional[float] .. attribute:: _dev Standard deviation in original units. :type: Optional[float] .. py:property:: setpoint :type: Optional[float] *setpoint* Get specific value/point system for original units. :returns: Specific value/point system for original units. :rtype: Optional[str] .. py:property:: min :type: Optional[float] *min* Get minimum range value. :returns: Minimum range value. :rtype: Optional[float] .. py:property:: max :type: Optional[float] *max* Get the maximum range value. :returns: Maximum range value. :rtype: Optional[float] .. py:property:: mean :type: Optional[float] *mean* Get the Variable average value. :returns: Variable average value. :rtype: Optional[float] .. py:property:: median :type: Optional[float] *median* Get the median value. :returns: Median value. :rtype: Optional[float] .. py:property:: dev :type: Optional[float] *dev* Get the Variable standardized deviation. :returns: Variable standardized deviation. :rtype: Optional[float] .. py:method:: clear() *clear()* Reset bounds attributes to default values. Resets all value ranges in original units. .. py:class:: StandardizedSpecs Standardized value specifications: ranges, statistics, and discretization. This class represents value ranges and statistical measures in standardized units, plus discretization properties for numerical analysis (step size, range array). .. attribute:: _std_setpoint Specific value/point in standardized units. :type: Optional[float] .. attribute:: _std_min Minimum value in standardized units. :type: Optional[float] .. attribute:: _std_max Maximum value in standardized units. :type: Optional[float] .. attribute:: _std_mean Mean value in standardized units. :type: Optional[float] .. attribute:: _std_median Median value in standardized units. :type: Optional[float] .. attribute:: _std_dev Standard deviation in standardized units. :type: Optional[float] .. py:property:: std_setpoint :type: Optional[float] *std_setpoint* Get specific value/point system for standardized units. :returns: Specific value/point system for standardized units. :rtype: Optional[str] .. py:property:: std_min :type: Optional[float] *std_min* Get the standardized minimum range value. :returns: standardized minimum range value. :rtype: Optional[float] .. py:property:: std_max :type: Optional[float] *std_max* Get the standardized maximum range value. :returns: standardized maximum range value. :rtype: Optional[float] .. py:property:: std_mean :type: Optional[float] *std_mean* Get standardized mean value. :returns: standardized mean. :rtype: Optional[float] .. py:property:: std_median :type: Optional[float] *std_median* Get standardized median value. :returns: Standardized median. :rtype: Optional[float] .. py:property:: std_dev :type: Optional[float] *std_dev* Get standardized standardized deviation. :returns: Standardized standardized deviation. :rtype: Optional[float] .. py:method:: clear() *clear()* Reset standardized attributes to default values. Resets all value ranges in standardized units. .. py:class:: NumericalSpecs Bases: :py:obj:`BoundsSpecs`, :py:obj:`StandardizedSpecs` Numerical perspective: computational value ranges. Answers the question: "What VALUES can this variable take?" This perspective combines: - BoundsSpecs: Value ranges in original units (min, max, mean, deviation, setpoint) - StandardizedSpecs: Value ranges in standardized units - Discretization properties (step, range array) This perspective focuses on: - Concrete bounds (minimum, maximum) - Central tendency (mean value) - Variation (standard deviation) - Discretization for simulations (step size, range arrays) - Unit conversions (original <-> standardized) - Variable dependencies (calculated variables) .. attribute:: # From BoundsSpecs _setpoint (Optional[float]): Specific value/point in original units. _min (Optional[float]): Minimum value in original units. _max (Optional[float]): Maximum value in original units. _mean (Optional[float]): Mean value in original units. _median (Optional[float]): Median value in original units. _dev (Optional[float]): Standard deviation in original units. :type: original units .. attribute:: # From StandardizedSpecs _std_setpoint (Optional[float]): Specific value/point in standardized units. _std_min (Optional[float]): Minimum value in standardized units. _std_max (Optional[float]): Maximum value in standardized units. _std_mean (Optional[float]): Mean value in standardized units. _std_median (Optional[float]): Median value in standardized units. _std_dev (Optional[float]): Standard deviation in standardized units. :type: standardized units .. attribute:: # Discretization properties _step (Optional[float]): Step size for simulations. _data (NDArray[np.float64]): Range for numerical analysis in standardized units. .. py:property:: step :type: Optional[float] *step* Get standardized step size. :returns: Step size (always standardized). :rtype: Optional[float] .. py:property:: data :type: numpy.typing.NDArray[numpy.float64] *data* Get standardized data array. :returns: Data array for range (always standardized). :rtype: NDArray[np.float64] .. py:method:: generate_data() *generate_data()* Generate standardized data array from min, max, using step value. :raises ValueError: If needed values are missing. .. py:method:: clear() *clear()* Reset numerical attributes to default values. Resets all value ranges, discretization, and step size by calling parent clear() methods.