Bert Debusschere, Cosmin Safta, Khachik Sargsyan, Katherine Johnston, Prashant Rai, Mohammad Khalil, Tiernan Casey, Xiaoshu Zeng, Kenny Chowdhary
The UQ Toolkit (UQTk) is a collection of libraries and tools for the quantification of uncertainty in numerical model predictions. Version 3.1.0 offers Polynomial Chaos Expansions to represent random variables, intrusive and non-intrusive methods for propagating uncertainties through computational models, tools for sensitivity analysis, methods for sparse surrogate construction, and Bayesian inference tools for inferring parameters and model uncertainties from experimental data.
For documentation on how to install and use UQTk, please refer to the manual, which is included as a PDF file in the directory doc/UQTk_manual.pdf. For more detailed documentation on the actual source code for development purposes, please refer to the doxygen documentation in the directory doc/doxy or online at https://www.sandia.gov/UQToolkit/doc/. If you are familiar with UQTk and would like just a high level overview of where to find everything and how to install, see the sections on Directory Structure and Installation below.
On a high level UQTk is organized as follows:
- config: Example CMake configuration scripts
- cpp/lib: Core C++ libraries
- cpp/app: Standalone apps that make UQTk functionality available to the command line
- cpp/tests: CMake Unit Tests
- dep: Third party libraries that UQTk depends on
- examples: short tutorial style examples that illustrate key UQTk capabilities
- PyUQTk: Python wrappers for the core C++ libraries as well as additional Python tools
In many key directories, README files have been included to further lay out the contents of their subdirectories.
Below is a list of key UQTk capabilities, along with examples that illustrate those capabilities:
- Intrusive Forward UQ: examples/ops (C++), examples/surf_rxn/SurfRxnISP.cpp (C++)
- Non-Intrusive Forward UQ: examples/surf_rxn/SurfRxnNISP.cpp (C++), examples/fwd_prop (Python), examples/window (Python), examples/uqpc (Command Line/Python)
- Non-Intrusive Surrogate Construction: examples/uqpc (Command Line/Python)
- Bayesian Compressive Sensing (BCS): examples/pce_bcs (C++)
- Global Sensitivity Analysis: examples/uqpc (Command Line/Python), examples/pce_bcs (C++), examples/sensMC (Command Line)
- Bayesian Inference: examples/line_infer (C++), examples/iuq (Command Line/Python), examples/polynomial (Python)
- Bayesian model selection: examples/polynomial (Python)
- Transitional Markov chain Monte Carlo (TMCMC): examples/tmcmc_bimodal (C++/Python/Command Line)
- Karhunen-Loève decompositions: examples/kle_ex1 (C++)
- Data Free Inference (Inference based on summary statistics): examples/dfi (C++)
- Forward Propagation with Basis Adaptation: examples/d_spring_series (Python)
- Numerical Integration (Quadrature): examples/num_integ (Python)
For more details on these capabilities, please refer to the UQTk manual in PDF format.
To install UQTk, first create a build directory outside of the UQTk repository.
From within the build directory, configure the distribution via CMake. See example
CMake configuration scripts in the directory config
Then build via make
, and test with ctest
. Install with make install
For example:
% mkdir build
% cd build
% ../UQTk/config/config-gcc-Python.sh
% make -j 8
% ctest
% make install
For more details, please refer to the UQTk manual in PDF format.
To cite UQTk, please use the following publications:
@ARTICLE{DebusscherePCE:2004,
author = {B.J. Debusschere and H.N. Najm and P.P. P\'ebay and O.M. Knio
and R.G. Ghanem and O.P. {Le Ma{\^\i}tre}},
title = {Numerical challenges in the use of polynomial chaos representations
for stochastic processes},
journal = {{SIAM} Journal on Scientific Computing},
year = {2004},
volume = {26},
pages = {698-719},
number = {2}
url = {http://dx.doi.org/10.1137/S1064827503427741}
}
@InCollection{DebusschereUQTk:2017,
author = {B. Debusschere and K. Sargsyan and C. Safta and K. Chowdhary},
title = {The Uncertainty Quantification Toolkit (UQTk)},
booktitle = {Handbook of Uncertainty Quantification},
editor = {R. Ghanem and D. Higdon and H. Owhadi},
year = {2017},
pages = {1807--1827},
publisher = {Springer}
url = {http://www.springer.com/us/book/9783319123844}
}
For more information, visit the UQTk website at https://www.sandia.gov/UQToolkit/ or contact the UQTk Developers at uqtk-developers@software.sandia.gov Sandia National Laboratories, Livermore, CA, USA.