Package: ot-batman
BatmanBatmanstands 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).batmanseamlessly 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 (OpenTURNSandscikit-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 inn-dimensions (HDR, Kiviat, PDF),PODfor database optimization or data reduction,Automatically manage code computations in parallel.Full documentation is available at:http://batman.readthedocs.ioGetting startedA detailled example can be found intutorial. The foldertest_casescontains examples that you can adapt to you needs. You can find more information
about the cases within the respectivesREADME.rstfile.Shoud you be interested by batman’s implementation, consider
reading thetechnical documentation.If you encounter a bug (or have a feature request), please report it viaGitLab. 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-outcontributing.Happy batman.How to install BATMAN?The sources are located onGitLab:https://gitlab.com/cerfacs/batmanLatest releaseInstall and update usingpip:pip install -U ot-batmanbatman is also distributed throughconda, on theconda-forgechannel.To install conda:wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.shTo create a new environment and install batman throughconda:conda create -n bat_env -c conda-forge batmanAll the above dependencies are automatically handled byconda,
exceptAntares. For more information, refer
to itsdocumentation.From sourcesUsing the latest python version is prefered! Then to install:git clone git@gitlab.com:cerfacs/batman.git
cd batman
python setup.py install
python setup.py test
python setup.py build_sphinxThe latter is optionnal as it build the documentation. The testing part is also
optionnal but is recommanded. (<30mins depending on your configuration).NoteIf you don’t have install priviledge, add--useroption after install.
But the simplest way might be to use pip or a conda environment.If batman has been correctly installed, you should be able to call it simply:batman -hWarningDepending on your configuration, you might have to export your local path:exportPATH=$PATH:~/.local/bin. Care to be taken with both yourPATHandPYTHONPATHenvironment variables. Make sure you do not call different
installation folders. It is recommanded that you leave yourPYTHONPATHempty.DependenciesThe required dependencies are:Python>= 2.7 or >= 3.4OpenTURNS>= 1.10scikit-learn>= 0.18numpy>= 1.13scipy>= 0.15pathos>= 0.2matplotlib>= 2.1Paramiko>= 2.4jsonschemaAppart from OpenTURNS, required dependencies are satisfied by the installer.
Optionnal dependencies are:Antaresfor extra IO optionssphinx>= 1.4 for documentationffmpegfor movie visualizations (n_features> 2)Testing dependencies are:pytest>= 2.8mock>= 2.0Extra testing flavours:coverage>= 4.4pylint>= 1.6.0NoteOpenTURNS and ffmpeg are available oncondathrough
theconda-forgechannel.Help and SupportAbout usSee authors and project history at:about us.CommunityIf you use batman, come and say hi athttps://batman-cerfacs.zulipchat.com.
Or send us an email. We would really appreciate that as we keep record of the users!CitationIf you use batman in a scientific publication, we would appreciatecitations.