Package: easyvvuq
EasyVVUQThe aim of EasyVVUQ is to facilitate verification, validation and
uncertainty quantification (VVUQ) for a wide variety of
simulations. While very convenient for simple cases, EasyVVUQ is particularly well suited in situations where the simulations are computationally expensive,
heterogeneous computing resources are necessary, the sampling space is very large or book-keeping is prohibitively
complex. It coordinates execution using an efficient database, it is fault tolerant and all progress can be saved.Here are some examples of questions EasyVVUQ can answer about your code:Given the uncertainties in input parameters, what is the distribution of the output?What percentage of the output variance each input parameter contributes?It also lets you construct surrogate models that are cheaper to evaluate than the complete simulation.The high-level overview of the library is avalable at ourreadthedocs.Getting StartedFor the quick start with EasyVVUQ we reccommend to check our basic interactive tutorial availablehere.FunctionalityAvailable analysis and sampling methods:Polynomial Chaos ExpansionStochastic CollocationDimension-adaptive Stochastic Collocation for high-dimensional inputsSimplex Stochastic Collocation for irregular outputsMonte Carlo Sensitivity AnalysisMarkov-Chain Monte CarloEasyVVUQ also supports building surrogate models using:Polynomial Chaos ExpansionStochastic CollocationGaussian ProcessesSupported computing resources:Traditional clustersKubernetes clustersThe easiest way to get familiar with the provided functionality is to follow the tutorials (*.ipynbfiles) in ourBinder.Installation instructionsRequirementsTo use the library you will need Python 3.7+.Installation using pipIf you are unsure of the version of python your defaultpipworks for type:pip --versionIf the output ends with(python 2.7)you should replacepipwithpip3in the following commands.The following should fully install the library:pip install easyvvuqTo upgrade the library use:pip install easyvvuq --upgradeManual installation from repositoryAlternatively, you can manually install EasyVVUQ.
First clone the repository to your computer:git clone https://github.com/UCL-CCS/EasyVVUQ.gitNote: As above, you need to be sure you are installing for Python 3 - if necessary replacepipwithpip3andpythonwithpython3in the commands below.We are trying to keep dependencies at a minimum but a few are inevitable, to install them use:cd EasyVVUQ/

pip install --use-feature=2020-resolver -r requirements.txtThen the library can be installed using:python setup.py installAPIYou can find the EasyVVUQ API documentation on ourGitHub Pages.Citing EasyVVUQRichardson, R A, Wright, D W, Edeling, W, Jancauskas, V, Lakhlili, J and Coveney, P V.
2020 EasyVVUQ: A Library for Verification, Validation and Uncertainty Quantification in High Performance Computing.
Journal of Open Research Software, 8: 11.DOI: 10.5334/jors.303.Wright, D.W., Richardson, R.A., Edeling, W., Lakhlili, J., Sinclair, R.C., Jancauskas, V., Suleimenova, D., Bosak, B., Kulczewski, M., Piontek, T., Kopta, P., Chirca, I., Arabnejad, H., Luk, O.O., Hoenen, O., Weglarz, J., Crommelin, D., Groen, D. and Coveney, P.V. (2020), Building Confidence in Simulation: Applications of EasyVVUQ. Adv. Theory Simul., 3: 1900246.DOI: 10.1002/adts.201900246.AcknowledgmentsDevelopment was funded by the EU Horizon 2020 projectVECMA.