Punpy: Propagating Uncertainties with PYthon

The punpy module is a Python software package to propagate random, structured and systematic uncertainties through a given measurement function.

punpy can be used as a standalone tool, where the input uncertainties are inputted manually. Alternatively, punpy can also be used in combination with digital effects tables created with obsarray. This documentation provides general information on how to use the module (with some examples), as well as a detailed API of the included classes and function.

Quickstart Guide

New to punpy? Check out the quickstart guide for an introduction.

User Guide

The user guide provides a documentation and examples how to use punpy either standalone or in combination with obsarray digital effects tables.

ATBD

ATBD mathematical description of punpy (under development).

API Reference

The API Reference contains a description of each of the punpy classes and functions.

Acknowledgements

punpy has been developed by Pieter De Vis.

The development has been funded by:

• The UK’s Department for Business, Energy and Industrial Strategy’s (BEIS) National Measurement System (NMS) programme

• The IDEAS-QA4EO project funded by the European Space Agency.

Project status

punpy is under active development. It is beta software.