RT Journal Article
T1 UTypes: a library for uncertain datatypes in Python
A1 Fernández-Candel, Carlos Javier
A1 Muñoz, Paula
A1 Troya-Castilla, Javier
A1 Vallecillo-Moreno, Antonio Jesús
K1 Bases de datos
K1 Informática
AB Existing Python uncertainty packages support the expression and propagation of uncertainty in numeric types, such as float or int. However, they do not cover the rest of the built-in types which can also be affected by uncertainty when representing physical systems. The Uncertain Datatypes (UTypes) library provides extensions of Python built-in datatypes bool, int, float, enum and str to seamlessly incorporate the data uncertainty coming from physical measurements or user estimations into Python programs, along with the set of operations defined for the values of these types. The library implements in a natural and efficient manner linear error propagation theory in Python and performs uncertainty calculations analytically.
PB Elsevier
YR 2024
FD 2024-03-05
LK https://hdl.handle.net/10630/30795
UL https://hdl.handle.net/10630/30795
LA eng
NO Carlos Javier Fernández-Candel, Paula Muñoz, Javier Troya, Antonio Vallecillo, UTypes: A library for uncertain datatypes in Python, SoftwareX, Volume 26, 2024, 101676, ISSN 2352-7110, https://doi.org/10.1016/j.softx.2024.101676
NO Partial funding for open access charge: Universidad de Málaga/CBUA.This work was partially supported by the Spanish Government (FEDER/Ministerio de Ciencia e Innovación – Agencia Estatal de Investigación) under projects SoCUS [TED2021-130523B-I00] and IPSCA [PID2021-125527NB-I00], and by the Junta de Andalucia, Spain, under contract QUAL21 010UMA.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026