Publication detail

UQpy v4.1: Uncertainty quantification with Python

TSAPETIS, D. SHIELDS, M. GIOVANIS, D. OLIVIER, A. NOVÁK, L. CHAKROBORTY, P. SHARMA, H. CHAUHAN, M. KONTOLATI, K. VANDANAPU, L. LOUKREZIS, D. GARDNER, M.

Original Title

UQpy v4.1: Uncertainty quantification with Python

Type

journal article in Web of Science

Language

English

Original Abstract

This paper presents the latest improvements introduced in Version 4 of the UQpy, Uncertainty Quantification with Python, library. In the latest version, the code was restructured to conform with the latest Python coding conventions, refactored to simplify previous tightly coupled features, and improve its extensibility and modularity. To improve the robustness of UQpy, software engineering best practices were adopted. A new software development workflow significantly improved collaboration between team members, and continuous integration and automated testing ensured the robustness and reliability of software performance. Continuous deployment of UQpy allowed its automated packaging and distribution in system agnostic format via multiple channels, while a Docker image enables the use of the toolbox regardless of operating system limitations.

Keywords

Uncertainty quantification

Authors

TSAPETIS, D.; SHIELDS, M.; GIOVANIS, D.; OLIVIER, A.; NOVÁK, L.; CHAKROBORTY, P.; SHARMA, H.; CHAUHAN, M.; KONTOLATI, K.; VANDANAPU, L.; LOUKREZIS, D.; GARDNER, M.

Released

12. 12. 2023

Publisher

Elsevier

ISBN

2352-7110

Periodical

SoftwareX

Year of study

24

Number

1

State

Kingdom of the Netherlands

Pages from

1

Pages to

7

Pages count

7

URL

https://www.sciencedirect.com/science/article/pii/S2352711023002571?ref=cra_js_challenge&fr=RR-1

BibTex

@article{BUT187079,
  author="TSAPETIS, D. and SHIELDS, M. and GIOVANIS, D. and OLIVIER, A. and NOVÁK, L. and CHAKROBORTY, P. and SHARMA, H. and CHAUHAN, M. and KONTOLATI, K. and VANDANAPU, L. and LOUKREZIS, D. and GARDNER, M.",
  title="UQpy v4.1: Uncertainty quantification with Python",
  journal="SoftwareX",
  year="2023",
  volume="24",
  number="1",
  pages="1--7",
  doi="10.1016/j.softx.2023.101561",
  issn="2352-7110",
  url="https://www.sciencedirect.com/science/article/pii/S2352711023002571?ref=cra_js_challenge&fr=RR-1"
}