CoMet Toolkit overview

Presented here is the Python CoMet Toolkit, which stands for Community Metrology toolkit, which has been developed to enable easy handling and processing of dataset error-covariance information. This toolkit aims to abstract away the complexity of dealing with uncertainties. There are a number of tools included in this toolkit (listed below), which are available on github and are installable via pip. More modules are planned to extend the toolkit capabilities.

The current included tools are:

comet_maths
comet_maths is a python module with useful mathematical algorithms for general use as well as for the other tools in the comet toolkit. The comet_maths documentation is available here. There are also jupyter notebooks available in the example section.
Last updated on Jul 26, 2022
obsarray
obsarray is an extension to xarray for defining, storing and interfacing with uncertainty and measurement error-covariance information in NetCDF files using standardised metadata. These datasets that include standardised uncertainty and error-covariance information are dubbed `digital effects tables’.
Last updated on May 24, 2022
punpy
punpy is a tool for “Propagation of UNcertainties in Python”. It propagates uncertainties on input quantities through any python function, evaluating the uncertainty on the output. These input data uncertainties can be defined using obsarray.
Last updated on May 24, 2022