PyTUQ
Library for tools and workflows for uncertainty quantification in computational models
Area: Mathematical libraries
CASS member: FASTMath
Description
The Python Toolkit for Uncertainty Quantification (PyTUQ) is a lightweight Python library for a range of uncertainty quantification tasks and workflows. Features include conventional tools such as polynomial chaos machinery with mixed bases, global sensitivity analysis, quadrature point generation, linear regression, Bayesian inference with various flavors of Markov chain Monte Carlo. PyTUQ also includes advanced methods such as Bayesian compressed sensing, sampling-based Rosenblatt transformation and embedded model error calibration.
Target audience
Computational scientists for any domain should be able to use PyTUQ’s functionalities for various UQ-related activities relevant to their computational models.
License: BSD-3-Clause
Package links
- Spack: py-pytuq