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An open-source, object-oriented Python package for surrogate-assisted Bayesain Validation of computational models.

Project description

BayesValidRox

bayesvalidrox logo

An open-source, object-oriented Python package for surrogate-assisted Bayesain Validation of computational models. This framework provides an automated workflow for surrogate-based sensitivity analysis, Bayesian calibration, and validation of computational models with a modular structure.

Project Status: Active – The project has reached a stable, usable state and is being actively developed.

Features

  • Surrogate modeling with Polynomial Chaos Expansion, Gaussian Process Emulator, mixed surrogate types
  • Global sensitivity analysis using Sobol Indices
  • Bayesian calibration and validation with Rejection sampling or MCMC using emcee package
  • Bayesian model comparison with model weights or confusion matrix for multi-model setting

Resources

The following resources are useful to get started on working with BayesValidRox:

Important links:

Authors

Installation

The best practive is to create a virtual environment and install the package inside it.

To create and activate the virtual environment run the following command in the terminal:

  python3 -m venv bayes_env
  cd bayes_env
  source bin/activate

You can replace bayes_env with your preferred name. For more information on virtual environments see this link.

Now, you can install the latest release of the package on PyPI inside the venv with:

  pip install bayesvalidrox

and installing the version on the master branch can be done by cloning this repo and installing:

  git clone https://git.iws.uni-stuttgart.de/inversemodeling/bayesvalidrox.git
  cd bayesvalidrox
  pip install .

Requirements

python 3.10:

  • numpy>=1.23.5
  • pandas==1.4.4
  • joblib==1.1.1
  • matplotlib==3.7.3
  • seaborn==0.11.1
  • scipy>=1.11.1
  • scikit-learn==1.3.1
  • tqdm>=4.61.1
  • chaospy==4.3.3
  • emcee==3.0.2
  • corner==2.2.1
  • h5py==3.9.0
  • statsmodels==0.14.2
  • multiprocess==0.70.16
  • datasets==2.20.0
  • umbridge==1.2.4

TexLive for Plotting with matplotlib

Here you need super user rights

sudo apt-get install dvipng texlive-latex-extra texlive-fonts-recommended cm-super

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