openturns/openturns

Probabilistic modelling and uncertainty quantification library

What it solves

OpenTURNS provides a scientific library for treating uncertainties, risks, and statistics in industrial applications. It allows engineers to transition from deterministic studies to probabilistic ones by providing the necessary mathematical tools to model and analyze uncertainty.

How it works

It is implemented as a C++ and Python library featuring an internal data model and a suite of algorithms specifically designed for uncertainty treatment. It also incorporates symbolic differentiation capabilities via a modified version of the Ev3 library.

Who it’s for

Engineers who want to introduce a probabilistic dimension into their previously deterministic industrial studies.

Highlights

  • Scientific C++ and Python library
  • Dedicated internal data model for uncertainty treatment
  • Support for symbolic differentiation
  • Focused on industrial applications

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