ot-batman 1.9.1

Batman

Batman stands for Bayesian Analysis Tool for Modelling and uncertAinty quaNtification. It is a Python module distributed under the open-source CECILL-B license (MIT/BSD compatible).

batman seamlessly allows to do statistical analysis (sensitivity analysis, Uncertainty Quantification, moments) based on non-intrusive ensemble experiment using any computer solver. It relies on open source python packages dedicated to statistics (OpenTURNS and scikit-learn).

Main features are:

• Design of Experiment (LHS, low discrepancy sequences, MC),

• Resample the parameter space based on the physic and the sample,

• Surrogate Models (Gaussian process, Polynomial Chaos, RBF, scikit-learn’s regressors),

• Optimization (Expected Improvement),

• Sensitivity/Uncertainty Analysis (SA, UA) and Uncertainty Quantification (UQ),

• Visualization in n-dimensions (HDR, Kiviat, PDF),

• POD for database optimization or data reduction,

• Automatically manage code computations in parallel.

Full documentation is available at:

http://batman.readthedocs.io

Getting started

A detailled example can be found in tutorial. The folder test_cases contains examples that you can adapt to you needs. You can find more information about the cases within the respectives README.rst file.

Shoud you be interested by batman’s implementation, consider reading the technical documentation.

If you encounter a bug (or have a feature request), please report it via GitLab. Or it might be you falling but “Why do we fall sir? So we can learn to pick ourselves up”.

Last but not least, if you consider contributing check-out contributing.

Happy batman.

pip install -U ot-batman

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

conda create -n bat_env -c conda-forge batman

git clone git@gitlab.com:cerfacs/batman.git
cd batman
python setup.py install
python setup.py test
python setup.py build_sphinx

batman -h