Detail publikace

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.

Originální název

UQpy v4.1: Uncertainty quantification with Python

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Uncertainty quantification

Autoři

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

Vydáno

12. 12. 2023

Nakladatel

Elsevier

ISSN

2352-7110

Periodikum

SoftwareX

Ročník

24

Číslo

1

Stát

Nizozemsko

Strany od

1

Strany do

7

Strany počet

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"
}