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BayesValidRox

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.

Authors

Installation

Install my project with pip

  pip install bayesvalidrox

Features

  • Surrogate modeling with Polynomial Chaos Expansion
  • Global sensitivity analysis using Sobol Indices
  • Bayesian calibration with MCMC using emcee package
  • Bayesian validation with model weights for multi-model setting

Examples

Requirements

  • numpy==1.22.1
  • pandas==1.2.4
  • joblib==1.0.1
  • matplotlib==3.4.2
  • seaborn==0.11.1
  • scikit-learn==0.24.2
  • tqdm==4.61.1
  • chaospy==4.3.3
  • emcee==3.0.2
  • tables==3.6.1
  • corner==2.2.1
  • h5py==3.2.1