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Modules
josephmure edited this page Jul 25, 2024
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- otagrum: create a distribution from a Bayesian Network using aGrUM
- otfftw: Fast Fourier Transform algorithm (e.g. for stochastic processes) using FFTW
- otfmi: FMI models manipulation using PyFMI
- otmixmod: build mixtures of a multivariate Normal distribution from a sample
- otmorris: Morris screening method module
- otpmml: manages PMML files for meta-modeling exchanges
- otpod: A module to build Probability of Detection for Non Destructive Testing
- otrobopt: robust optimization
- otsvm: Support Vector regression and classification with libsvm
- otwrapy: Python wrapper tools
- otbenchmark: benchmark problems for reliability and sensitivity analysis
- From an existing conda installation, refer to https://openturns.github.io/openturns/latest/install.html#conda:
conda install otrobopt
- From pip (except osx, otagrum):
pip install otmixmod
- From otconda
- On Linux, you can install modules either from our Debian or RPM repositories, see instructions
- On Linux, from sources:
- You will need to install the development packages first, check the required dependencies
- Launch installation, for example the robopt module:
git clone https://github.com/openturns/otrobopt.git
cd otrobopt
cmake -DCMAKE_INSTALL_PREFIX=~/.local .
make install
- othdrplot: high density region algorithm for functional outlier detection
- otsurrogate: surrogate metamodels
- otsklearn: metamodels with the scikit-learn estimator API (fit/predict)
- ottensap: reuse tensor metamodels from tensap as ot.Function
- otusecases: use cases suitable for OpenTURNS (functions and datasets)
- otmarkov: simulates Markov chains (experimental)
- otsensitivity: sensitivity analysis with density based measures
- otshapley: compute Shapley effects (fork of shapley-effects which is compatible with python 3.9+)
- batman: Statistical analysis for expensive computer codes made easy.
- otak: Active learning Kriging methods for reliability analysis.
- otsmt: Surrogate models from SMT into OpenTURNS PythonFunctions.
- otkerneldesign: Kernel Herding-based designs of experiments.
- otchaoskriging: Chaos/Kriging metamodels (experimental)
- otsliced: SIR method (experimental)
Some of these modules are available on pypi:
pip install otbenchmark
pip install othdrplot
A tutorial to create a Python package with OpenTURNS Python modules is provided at:
otquickmodule : Easy Python Packaging (7 steps to publish on PyPI).
A tutorial to create a Python module is provided at: