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BATMAN

swMATH ID: 29121
Software Authors:
Description: 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.
Homepage: https://www.theoj.org/joss-papers/joss.00493/10.21105.joss.00493.pdf
Source Code:  https://gitlab.com/cerfacs/batman
Dependencies: Python
Keywords: JOSS; Journal Open Source Software; Bayesian Analysis Tool; Python; HPC; uncertainty quantification; Modelling
Related Software: OpenTURNS; Python; Scikit; PiXIE; PyCharm; MASCARET; DAPPER; Smurf; Open TURNS; AQUASIM; iDynoR; ElemStatLearn; WRF-SFIRE; Prometheus; FlamMap; FARSITE; fireLib; Multivac; LSMLIB; SciPy
Cited in: 2 Documents

Standard Articles

1 Publication describing the Software Year
BATMAN: Statistical analysis for expensive computer codes made easy Link
Pamphile T. Roy; Sophie Ricci; Romain Dupuis; Robin Campet; Jean-Christophe Jouhaud; Cyril Fournier
2018

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