Simplest TypeQL Units Model

authors: @modeller and @bradeneliason

date: September 2021

Overview

This repo is the simplest TypeQL model of a units library. It contains the code and data needed to load a minimum example. It imports data froma series of csv, making it easy to add your own units.

How it's used

Units are defined by their string value, for example "kN.m", or "m2". This "unit" attribute, is also owned as a key by the unit_details relation, which contains all of the details for that particular unit. These details include conversion attributes, to enable conversion to the metric base unit.

To create a measure, one needs to simply have a quantity and connect the unit to it in the schema measure isa attribute, value long, has unit

Then, on import one just uses the simple syntax insert $m isa measure; $m 103.25; $m has unit "kPa";

How its built

Units are of different types:

• core units are the ones all others break down to used in dimensional analysis, but also including non-SI dimensions like radians, composition, currency, bits, threads etc.
• derived units are those created out of the core ones through combination of core units, without any scaling, and represent the base means of describing that quantity kind
• scaled units are ones created out of core or derived through scaling, and they link back to their base for conversion purposes (implemented as a rule)
• imperial units are just a form of scaling

The unit is also connected to the dimensions, which define that measure. These dimensions also have the base unit name, attached to them. In addition to the usual SI dimensions (time, length, mass, current, temperature, moles, luminosity), there are two extra ones added for non-dimensional measures (radians, composition). The non-dimensional composition measures also connect to the unit they are compared on, for example m3/m3 has acomposition dimension of 1, and a length dimension of 3.

Non-base units, like "in2", are automatically connected to their base unit, "m2", so that conversions can be set up. At the moment, conversions are not implemented, as we are waiting for calculations before implementing them.

Tolerances

For this schema all tolerance types are converted into bilateral form with an upper and a lower tolernace value. How the upper and lower tolerance values are interpreted depends on two boolean values is_absolute and is_offset:

• If is_absolute is true the upper and lower tolerance value have the same units as the nominal value, otherwise the upper and lower tolerances are interpreted as a scaling factor of the nominal value.
• If is_offset is true, the limits of the tolernace is computed by adding the upper and lower tolernace to the nominal value, otherwise, the upper and lower tolerance stand alone as the limits.

The table below shows how the tolerance 10±1 can be represented in four ways.

	is_absolute true	is_absolute false
is_offset true	+1 -1	(×) +0.1 -0.1
is_offset false	11 9	(×) 1.10 0.90

Installing the Repo

Prerequisites

To install the repo make sure that pipenv is installed in your Python.

The implementation is tested on Python 3.8.

TypeDB must be running, and the system is setup to use the localhost. If you are using a different server, then its address need to be inserted in the clean_and_load.py.

Installation

1. Run Pipenv shell pipenv shell
2. Run pipenv install pipenv install
3. Run clean_and_load.py python clean_and_load.py

The installation implements some example measures, and these can be easily extended by adjusting the csv files from the spreadsheet