Model elements - Desciptors and Parameters

[damskii9992]

General

A model is built upon many various parameters, some of which can be fitted and some of which are static. A model can additionally also be described by booleans and specific strings.
These different model elements behave differently and therefore needs to be treated differently. As such, they are split into two groups, the static parameters, booleans and strings are called "Descriptors", whereas only those model parameters which can be fitted to match the experimental data to the model prediction are called Parameter.

The Descriptors are then further split into 3 groups based on the type of value that can be assigned to them, DescriptorNumber for static numbers, DescriptorStr for strings and DescriptorBool for booleans. Functionality shared between all types of Descriptors live in an DescriptorBase object which all Descriptors inherit from. The inheritance graph of the model objects therefore has the following form:

graph LR
DescriptorBase --> DescriptorNumber
DescriptorBase --> DescriptorStr
DescriptorBase --> DescriptorBool
DescriptorNumber --> Parameter
subgraph Non-fittable
   DescriptorNumber
   DescriptorStr
   DescriptorBool
end
subgraph Fittable
   Parameter
end

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Descriptors

The purpose of a "Descriptor" is to handle model elements that can be considered "static" (can't be fitted to match model to experimental data). The types of descriptors currently implemented have bool, string, or number values, which all share some base functionality contained in a base class.

DescriptorBase

All type specific descriptors inherit from this base class. The main properties of the base class are:

• name, name of this object (decorated with undo/redo functionality)
• display_name, optional pretty name for the object (decorated with undo/redo functionality)
• description, optional summary of what this object is for
• url, optional lookup url for documentation/information
• parent, optional link to the object which this descriptor is attached to

DescriptorBool

The bool descriptor holds the value of a builtin bool type. In addition to the DescriptorBase properties, it has the properties:

• value, utilized to hold the value (decorated with undo/redo functionality)

DescriptorStr

The str descriptor holds the value of a builtin string type. In addition to the DescriptorBase properties, it has the properties:

• value, utilized to hold the value (decorated with undo/redo functionality)

DescriptorNumber

The number descriptor is different from the two former descriptors as it is continuous. Furthermore it can be assigned a physical unit and a variance for the value. To provide this functionally the value is kept internally in a [scipp_scalar] (https://scipp.github.io/generated/functions/scipp.scalar.html). In addition to the DescriptorBase properties, the DescriptorNumber has the following properties:

• value, the numerical value of the variable (decorated with undo/redo functionality)
• unit, optional physical unit for the numerical value (decorated with undo/redo functionality)
• variance, optional variance for the value (decorated with undo/redo functionality)
• full_value, the full Scipp scalar holding all the above mentioned properties (decorated with undo/redo functionality)

To minimize user mistakes and simplify constraints, the unit (and therefore also full_value) cannot be changed after initialization, except between allowed types, such as from "m" to "cm" or "eV" to "J". This unit conversion is done through the convert_unit method.

DescriptorNumbers can be created from the value and optionally, the variance and unit, as well as directly from a predefined Scipp scalar through the DescriptorNumber.fromScipp(scipp_scalar) constructor.

Parameter

The Parameter class inherits from DescriptorNumber and serves to hold model parameters that can be fitted. To facilitate this, it contains the additional properties:

• min, optional minimum which the value can't go below (decorated with undo/redo functionality)
• max, optional maximum which the value can't go above (decorated with undo/redo functionality)
• fixed, optional sets if the parameter is allowed to vary while fitting (decorated with undo/redo functionality)
• enabled, optional sets if the objects value can be set or if constraints are applied (decorated with undo/redo functionality)
• callback, optional callback that serves as a link between the object and a potential Calculator

Link to the ADR suggestion:
#20