carg-io 1.0b0

Parametrization made easy

Ir. E. van Vliet

24-07-2023

Carg-io

cargi-io supports defining, setting and bookkeeping when working with sets of parameters. cargi-io originated as an alternative to using the python-native dataclass, since dataclasses did not really offer the functionality needed for parametric analyses.

Features

• Unit conversion
• Assigning default values
• Linting and autocompletion
• Hashing
• Iteration
• Representations for pandas.dataframe and tkinter

Examples:

Independent parameters

Below an example of how to organize the input parameters for a box object.

from carg_io import ParameterSet, Parameter, units

class Box(ParameterSet):
    Length:Parameter = 1 * units.meter
    Width:Parameter = 1 * units.meter
    Height:Parameter = 1 * units.meter
    Density:Parameter = 2 * units.kilogram / units.meter**3


if __name__ == "__main__":
    box = Box()
    box.Length['m'] = 2
    assert box.Length['mm'] == 2000

Dependent parameter

In the example below, Box.Volume is a dependent parameter that uses the length, width and height of the box.

from carg_io import ParameterSet, Parameter, units

class Box(ParameterSet):
    Length:Parameter = 1 * units.meter
    Width:Parameter = 1 * units.meter
    Height:Parameter = 1 * units.meter
    Density:Parameter = 2 * units.kilogram / units.meter**3

    def Volume(self) -> Parameter:
        l = self.Length['m']
        w = self.Width['m']
        h = self.Height['m']
        return Parameter('Volume', l*w*h*units.meter**3)

No categorical data

Categorical data, such as as choice between GREEN, BLUE, YELLOW, is deliberately not supported. The reason for this is that carg-io focusses on numerical values only, since only numerical values can be shown in a graph.

Typically, digging deeper into categorical values, one will eventually find numerical values again. E.g. the colors GREEN, BLUE and YELLOW are actually wave lenghts 550, 450 and 580 nm.