OpenTURNS

An Open source initiative to Treat Uncertainties, Risks’N Statistics in a structured industrial approach
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OpenTURNS Ranking & Summary

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  • Rating:
  • License:
  • GPL
  • Price:
  • FREE
  • Publisher Name:
  • OpenTURNS Team
  • Publisher web site:
  • Operating Systems:
  • Mac OS X
  • File Size:
  • 4.1 MB

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OpenTURNS Description

An Open source initiative to Treat Uncertainties, Risks’N Statistics in a structured industrial approach OpenTURNS is an Open source initiative to Treat Uncertainties, Risks’N Statistics in a structured industrial approach. OpenTURNS is a Unix/Linux software that has three main components :· a scientific C++ library including an internal data model and algorithms dedicated to the treatment of uncertainties. The main function of that library is giving to specific applications all the functionalities needed to treat uncertainties in studies. Targeted users are all engineers who want to introduce the probabilistic dimension in their so far deterministic studies. · an independent application with a graphical user interface. This application was built to become the work environment for the specialist of the treatment of uncertainties. Targeted users are once again industrial practitioners: those who identify the treatment of uncertainties as a full task, which can be spread to multiple engineering domains. · a python module with high level operators in the probabilistic and statistical field. The interest of this language is to be both a powerful scientific language (capable of using C++ libraries), and a user friendly interpreted language like Matlab’s one. This python module was designed to make the development of prototypes easier (in order to test new algorithms and methods for example), to become an easy-to-use support for educational works.This module intends to become a natural environment capable of integrating new developments within the field of uncertainty and sensitivity analysis. The targeted users are here research centres and the academic community. What's New in This Release: · Fix bugs. · Add polynomial chaos facilities · Add some pretty print · Delete SVMRegression implementation


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