{"id":19863935,"url":"https://github.com/sandialabs/uqtk","last_synced_at":"2026-01-27T17:38:23.784Z","repository":{"id":36322999,"uuid":"193990601","full_name":"sandialabs/UQTk","owner":"sandialabs","description":"Sandia Uncertainty Quantification Toolkit","archived":false,"fork":false,"pushed_at":"2024-12-21T02:22:41.000Z","size":51282,"stargazers_count":76,"open_issues_count":1,"forks_count":27,"subscribers_count":9,"default_branch":"master","last_synced_at":"2025-01-11T15:32:43.953Z","etag":null,"topics":["bayesian-inference","mcmc","mcmc-methods","mcmc-sampler","scr-1380","snl-data-analysis","snl-science-libs","surrogate-models","uncertainty","uncertainty-estimation","uncertainty-propagation","uncertainty-quantification","uq"],"latest_commit_sha":null,"homepage":"","language":"Fortran","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sandialabs.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-06-26T23:26:47.000Z","updated_at":"2024-12-21T02:22:47.000Z","dependencies_parsed_at":"2023-01-17T01:17:19.296Z","dependency_job_id":"e547889a-8c64-4b1c-b34f-e607e95b7f77","html_url":"https://github.com/sandialabs/UQTk","commit_stats":null,"previous_names":[],"tags_count":7,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2FUQTk","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2FUQTk/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2FUQTk/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2FUQTk/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sandialabs","download_url":"https://codeload.github.com/sandialabs/UQTk/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241272628,"owners_count":19937092,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bayesian-inference","mcmc","mcmc-methods","mcmc-sampler","scr-1380","snl-data-analysis","snl-science-libs","surrogate-models","uncertainty","uncertainty-estimation","uncertainty-propagation","uncertainty-quantification","uq"],"created_at":"2024-11-12T15:16:42.189Z","updated_at":"2026-01-27T17:38:23.562Z","avatar_url":"https://github.com/sandialabs.png","language":"Fortran","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Sandia National Labs\n# Uncertainty Quantification Toolkit (UQTk) version 3.1.5\n\n#### Bert Debusschere, Caitlin Curry, Cosmin Safta, Katherine Johnston, Kenny Chowdhary, Khachik Sargsyan, Luke Boll, Mohammad Khalil, Prashant Rai, Tiernan Casey, Xiaoshu Zeng\n\n## Overview\nThe UQ Toolkit (UQTk) is a collection of libraries and tools for the\nquantification of uncertainty in numerical model predictions. Version\n3.1.5 offers Polynomial Chaos Expansions to represent random variables,\nintrusive and non-intrusive methods for propagating uncertainties through\ncomputational models, tools for sensitivity analysis, methods for sparse\nsurrogate construction, and Bayesian inference tools for inferring parameters\nand model uncertainties from experimental data.\n\n## Documentation\nFor documentation on how to install and use UQTk, please refer to the manual,\nwhich is included as a PDF file in the directory docs/UQTk_manual.pdf. For more\ndetailed documentation on the actual source code for development purposes,\nplease refer to the [C++ doxygen documentation](https://sandialabs.github.io/UQTk/).\nIf you are familiar with UQTk and would like just a high level overview of where to find\neverything and how to install, see the sections on Directory Structure and\nInstallation below.\n\n## Directory Structure\nOn a high level UQTk is organized as follows:\n* config: Example CMake configuration scripts\n* cpp/lib: Core C++ libraries\n* cpp/app: Standalone apps that make UQTk functionality available to the command line\n* cpp/tests: CMake Unit Tests\n* dep: Third party libraries that UQTk depends on\n* examples: short tutorial style examples that illustrate key UQTk capabilities\n* PyUQTk: Python wrappers for the core C++ libraries as well as additional Python tools\n\nIn many key directories, README files have been included to further lay out the\ncontents of their subdirectories.\n\n## Capabilities\nBelow is a list of key UQTk capabilities, along with examples that illustrate those\ncapabilities:\n* Intrusive Forward UQ: examples/ops (C++), examples/surf_rxn/SurfRxnISP.cpp (C++)\n* Non-Intrusive Forward UQ: examples/surf_rxn/SurfRxnNISP.cpp (C++), examples/fwd_prop (Python),\n  examples/window (Python), examples/uqpc (Command Line/Python)\n* Non-Intrusive Surrogate Construction: examples/uqpc (Command Line/Python)\n* Bayesian Compressive Sensing (BCS): examples/pce_bcs (C++)\n* Global Sensitivity Analysis: examples/uqpc (Command Line/Python), examples/pce_bcs (C++), examples/sensMC (Command Line)\n* Bayesian Inference: examples/line_infer (C++), examples/iuq (Command Line/Python), examples/polynomial (Python)\n* Bayesian model selection: examples/polynomial (Python)\n* Transitional Markov chain Monte Carlo (TMCMC): examples/tmcmc_bimodal (C++/Python/Command Line)\n* Karhunen-Loève decompositions: examples/kle_ex1 (C++)\n* Data Free Inference (Inference based on summary statistics): examples/dfi (C++)\n* Forward Propagation with Basis Adaptation: examples/d_spring_series (Python)\n* Numerical Integration (Quadrature): examples/num_integ (Python)\n\nFor more details on these capabilities, please refer to the UQTk manual in PDF format.\n\n## Installation\nTo install UQTk, first create a build directory outside of the UQTk repository.\nFrom within the build directory, configure the distribution via CMake. See example\nCMake configuration scripts in the directory config\nThen build via ``make``, and test with ``ctest``. Install with ``make install``\nFor example:\n```\n% mkdir build\n% cd build\n% ../UQTk/config/config-gcc-Python.sh\n% make -j 8\n% ctest\n% make install\n```\n\nFor more details, please refer to the UQTk manual in PDF format.\n\n\n## How to Cite\nTo cite UQTk, please use the following publications:\n\n```\n@ARTICLE{DebusscherePCE:2004,\n  author   =  {B.J. Debusschere and H.N. Najm and P.P. P\\'ebay and O.M. Knio\n               and R.G. Ghanem and O.P. {Le Ma{\\^\\i}tre}},\n  title    =  {Numerical challenges in the use of polynomial chaos representations\n               for stochastic processes},\n  journal  =  {{SIAM} Journal on Scientific Computing},\n  year     =  {2004},\n  volume   =  {26},\n  pages    =  {698-719},\n  number   =  {2},\n  url      =  {http://dx.doi.org/10.1137/S1064827503427741}\n}\n\n@InCollection{DebusschereUQTk:2017,\n  author    = {B. Debusschere and K. Sargsyan and C. Safta and K. Chowdhary},\n  title     = {The Uncertainty Quantification Toolkit (UQTk)},\n  booktitle = {Handbook of Uncertainty Quantification},\n  editor    = {R. Ghanem and D. Higdon and H. Owhadi},\n  year      = {2017},\n  pages     = {1807--1827},\n  publisher = {Springer},\n  url       = {http://www.springer.com/us/book/9783319123844}\n}\n```\n\n## Contact Us\nFor more information, visit the [UQTk website at https://www.sandia.gov/UQToolkit/](https://www.sandia.gov/UQToolkit/) or contact the UQTk developers through the [github discussions site](https://github.com/sandialabs/UQTk/discussions)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsandialabs%2Fuqtk","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsandialabs%2Fuqtk","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsandialabs%2Fuqtk/lists"}