Skip to main content

Generic Engine for Multi-disciplinary Scenarios, Exploration and Optimization

Project description

GEMSEO stands for “Generic Engine for Multi-disciplinary Scenarios, Exploration and Optimization”, it features:

  • Automatic creation and execution of MDO processes based on MDO formulations

  • Integration of numerical techniques in MDO processes: multidisciplinary coupling, optimization, design of experiments, visualization, surrogate models, machine learning, uncertainty, …

  • Various ways of interfacing software and models: Python, Matlab, Excel, scilab, executables, …

  • A Python library, standalone and easy to embed in simulation platforms

  • Built on NumPy, SciPy and matplotlib

  • Open-source LGPL-3.0 license

Documentation

The full documentation of GEMSEO, including installation and tutorials, can be found at https://gemseo.readthedocs.io.

Bugs/Questions

Please use the gitlab issue tracker at https://gitlab.com/gemseo/dev/gemseo/-/issues to submit bugs or questions.

License

The GEMSEO source code is distributed under the GNU LGPL v3.0 license. A copy of it can be found in the LICENSE.txt file. The GNU LGPL v3.0 license is an exception to the GNU GPL v3.0 license. A copy of the GNU GPL v3.0 license can be found in the LICENSES folder.

The GEMSEO examples are distributed under the BSD 0-Clause, a permissive license that allows to copy paste the code of examples without preserving the copyright mentions.

The GEMSEO documentation is distributed under the CC BY-SA 4.0 license.

The GEMSEO product depends on other software which have various licenses. The list of dependencies with their licenses is given in the CREDITS.rst file.

Contributors

  • Francois Gallard

  • Damien Guenot

  • Vincent Gachelin

  • Charlie Vanaret

  • Remi Lafage

  • Pierre-Jean Barjhoux

  • Benoit Pauwels

  • Matthias De Lozzo

  • Jean-Christophe Giret

  • Syver Doving Agdestein

  • Antoine Dechaume

  • Anne Gazaix

  • Nicolas Roussouly

  • Gilberto Ruiz Jimenez

  • Arthur Piat

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gemseo-3.2.1.tar.gz (21.7 MB view details)

Uploaded Source

Built Distribution

gemseo-3.2.1-py2.py3-none-any.whl (1.2 MB view details)

Uploaded Python 2 Python 3

File details

Details for the file gemseo-3.2.1.tar.gz.

File metadata

  • Download URL: gemseo-3.2.1.tar.gz
  • Upload date:
  • Size: 21.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

File hashes

Hashes for gemseo-3.2.1.tar.gz
Algorithm Hash digest
SHA256 7c4b0e362ac118eda8e0f3c8b1e98fce20065a1015770c2740dfe115b344243e
MD5 9579c15d79a49af87028b5d8586f4787
BLAKE2b-256 7e41829248c73958e7af0747983898417b74a365198300b0d5a4458af6ce2deb

See more details on using hashes here.

File details

Details for the file gemseo-3.2.1-py2.py3-none-any.whl.

File metadata

  • Download URL: gemseo-3.2.1-py2.py3-none-any.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

File hashes

Hashes for gemseo-3.2.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 6d0935032f0e5e504f10b7d612185ef12e4c0969ddc283363190bd874dd30ad1
MD5 3fd5a10cc561e755ca39004d15bbfc93
BLAKE2b-256 60fb7e309e03d3ca9a9dba4ba4a179be3f77cb224312d53aca89ee3d9e864271

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page