Skip to main content

Generic Engine for Multi-disciplinary Scenarios, Exploration and Optimization

Project description

PyPI - License PyPI - Python Version PyPI Conda (channel only) Code Style Codecov branch Paper

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

  • Selime Gürol

  • Reda El Amri

  • Simone Coniglio

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-4.0.0.tar.gz (26.2 MB view details)

Uploaded Source

Built Distribution

gemseo-4.0.0-py2.py3-none-any.whl (1.4 MB view details)

Uploaded Python 2 Python 3

File details

Details for the file gemseo-4.0.0.tar.gz.

File metadata

  • Download URL: gemseo-4.0.0.tar.gz
  • Upload date:
  • Size: 26.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.5

File hashes

Hashes for gemseo-4.0.0.tar.gz
Algorithm Hash digest
SHA256 1eb39bb42f55cb439423a0b46a91b7f179d9823c2164bae9c8e917a417a319e4
MD5 37013e8e298066c80fc99c8458c1bb3e
BLAKE2b-256 17a1a51e296eb78829872efe0dfb0918c3bd635ac171a6a41e900787f1465434

See more details on using hashes here.

File details

Details for the file gemseo-4.0.0-py2.py3-none-any.whl.

File metadata

  • Download URL: gemseo-4.0.0-py2.py3-none-any.whl
  • Upload date:
  • Size: 1.4 MB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.5

File hashes

Hashes for gemseo-4.0.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 f2251a96f67e7ddea74361c4338c82d692322b435a532e80a429bab60a71dc2b
MD5 6e6758f249e826709748f45519e8d434
BLAKE2b-256 115c3af6007cba67b95bb3fa31793c998cd0193abdb02e702f55c96f4465d740

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