An open-source, object-oriented Python package for surrogate-assisted Bayesain Validation of computational models.
Project description
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
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 my project with pip inside the venv with:
pip install bayesvalidrox
Features
- Surrogate modeling with Polynomial Chaos Expansion
- Global sensitivity analysis using Sobol Indices
- Bayesian calibration with MCMC using
emceepackage - Bayesian validation with model weights for multi-model setting
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
- statsmodels==0.13.2
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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