Surrogate-assisted Bayesian validation of computational models

BayesValidRox is an open-source python package that provides methods for surrogate modeling, Bayesian inference and model comparison.

Weighting model results against data with associated uncertainty, costs and sparsity

An introductory tutorial to the overall workflow with bayesvalidrox is provided in TUTORIAL and descriptions of the available examples can be found in EXAMPLES. The functionality and options for the different classes is described more in-depth in USER GUIDE and a list of all the classes and functions is provided in API.

Installation

This package runs under Python 3.9 for versions <1.0.0 and 3.9+ from version 1.0.0 on, use pip to install:

pip install bayesvalidrox

Quickstart

#TODO A minimal example to get people started

License

#TODO Note the License under which BVR is released

Contribution

We would be happy for you to contribute to BayesValidRox. This can include e.g. reporting issues, proposing new features, working on features, or support with the documentation. If you want to contibute, check out our contribution guidelines. You can contact us on the gitlab page.

Further contents

Indices and tables