openturns

Probabilistic modelling and uncertainty quantification library

https://github.com/openturns/openturns

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (15.5%) to scientific vocabulary

Keywords

data-analysis metamodel optimization probability-distribution python reliability sensitivity stochastic-process uncertainty-quantification
Last synced: 6 months ago · JSON representation ·

Repository

Probabilistic modelling and uncertainty quantification library

Basic Info
Statistics
  • Stars: 276
  • Watchers: 20
  • Forks: 97
  • Open Issues: 281
  • Releases: 33
Topics
data-analysis metamodel optimization probability-distribution python reliability sensitivity stochastic-process uncertainty-quantification
Created over 10 years ago · Last pushed 8 months ago
Metadata Files
Readme Changelog License Citation

README.rst

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=============================================================================
OpenTURNS (Open source initiative to Treat Uncertainties, Risks'N Statistics)
=============================================================================

OpenTURNS is a scientific C++ and Python library featuring an internal data model and algorithms
dedicated to the treatment of uncertainties. The main goal of this library is to provide
all functionalities needed to treat uncertainties in studies with industrial applications.
Targeted users are all engineers who want to introduce the probabilistic dimension
in their so far deterministic studies. 

Up-to-date information can be found at http://www.openturns.org

License
=======
OpenTURNS is free software distributed under the GNU Lesser General Public License version 3 or, at your option, any later version.
The terms of the GNU LGPL version 3 can be found in the files ``COPYING`` and ``COPYING.LESSER``.
Additional licenses apply to some parts of the library:
please see the ``LICENSE`` file and the other ``COPYING.*`` files.

Release Notes
=============
Please see the ``ChangeLog`` file for a summary of bug fixes and
new features of the current release.

Backwards Compatibility
=======================
The developers strive to preserve backwards compatibility
between releases, but this is not always possible. Where backwards
compatibility is known to be broken, it is clearly marked as an
incompatibility in the ``ChangeLog`` file.

Installation
============
Instructions on how to install
OpenTURNS from binaries and from sources are available `here
`_.

Documentation
=============
The link http://openturns.github.io/openturns/latest/contents.html will take you to
the documentation of the current release.

In the URL above, replace "latest" with "master" to view the documentation of the current master branch,
or with a version number to view the documentation of that specific version.

Contributing
============
There are many ways you can contribute,
and not all of them involve developer skills.
Please visit `this page
`_ for more information.

Acknowledgements
================

Symbolic differentiation is powered in OpenTURNS by a `modified version
`_ of Leo Liberti's `Ev3
`_ library.

-- The OpenTURNS team

Owner

  • Name: OpenTURNS
  • Login: openturns
  • Kind: organization
  • Location: Standard Space

Citation (CITATION.cff)

cff-version: 1.2.0
title: OpenTURNS
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - name: Airbus
  - name: EDF
  - name: IMACS
  - name: ONERA
  - name: Phimeca
repository-code: 'https://github.com/openturns/openturns'
url: 'https://openturns.github.io/www/'
abstract: Uncertainty treatment library
keywords:
  - probability
  - uncertainty
  - reliability
license: LGPL-3.0-or-later
doi: 10.1007/978-3-319-11259-6_64-1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 103
  • Total pull requests: 52
  • Average time to close issues: 9 months
  • Average time to close pull requests: 2 months
  • Total issue authors: 17
  • Total pull request authors: 10
  • Average comments per issue: 0.98
  • Average comments per pull request: 2.15
  • Merged pull requests: 27
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 88
  • Pull requests: 49
  • Average time to close issues: about 2 months
  • Average time to close pull requests: 29 days
  • Issue authors: 16
  • Pull request authors: 9
  • Average comments per issue: 0.78
  • Average comments per pull request: 1.76
  • Merged pull requests: 26
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • mbaudin47 (117)
  • jschueller (41)
  • josephmure (24)
  • adutfoy (24)
  • regislebrun (21)
  • m-balesdent (14)
  • pgrt (7)
  • sofianehaddad (7)
  • mdelozzo (5)
  • JPelamatti (4)
  • nitawa (4)
  • adumasphi (3)
  • yurivict (3)
  • mwestphal (3)
  • vchabri (3)
Pull Request Authors
  • mbaudin47 (51)
  • jschueller (49)
  • adutfoy (27)
  • m-balesdent (25)
  • josephmure (19)
  • regislebrun (16)
  • sofianehaddad (7)
  • JPelamatti (6)
  • ariste-sarl (4)
  • l-brevault (2)
  • arkinn2 (2)
  • ArashPartow (1)
  • mwestphal (1)
  • mdelozzo (1)
  • AnnikaSchultheiss (1)
Top Labels
Issue Labels
bug (149) enhancement (83) doc (60) graph (19) API (17) probas (13) question (10) optimization (9) difficulty:easy (8) hackathon 25.04 (5) metamodel (5) calibration (5) reliability (4) Performance (4) difficulty:medium (3) help wanted (3) sensitivity (3) data (2) build (2) needs review (2) testing (1) upstream (1) swig (1) invalid (1) difficulty:hard (1) service support (1)
Pull Request Labels
doc (44) enhancement (21) metamodel (20) probas (20) graph (15) API (14) service support (12) optimization (7) needs review (6) bug (6) sensitivity (6) reliability (4) Performance (4) calibration (3) swig (3) build (2) testing (2) difficulty:easy (2) hackathon 25.04 (2) regression (1) geometry (1)

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