.. image:: /docs/img/gefest_logo.png
:alt: Logo of GEFEST framework
.. start-badges
.. list-table::
:stub-columns: 1
* - tests
- | |build|
* - docs
- |docs|
* - license
- | |license|
* - support
- | |tg|
* - gitlab
- | |gitlab|
* - funding
- | |ITMO| |NCCR|
.. end-badges
**GEFEST** (**G**\enerative **E**\volution **F**\or **E**\ncoded **ST**\ructures) is a toolbox for the generative design of
physical objects.
In core it uses:
1. Numerical modelling to simulate the interaction between object and environment
2. Evolutionary optimization to produce new variants of geometrically-encoded structures
The basic abstractions in GEFEST are Point, Polygon, Structure and Domain. Architecture of the GEFEST can be described as:
.. figure:: /docs/img/workflow.png
:figwidth: image
:align: center
The evolutionary workflow of the generative design is the following:
.. figure:: /docs/img/evo.png
:figwidth: image
:align: center
The dynamics of the optimisation can be visualized as (breakwaters optimisation case):
.. image:: /docs/img/breakwaters.gif
How to use
==========
All details about first steps with GEFEST might be found in the `quick start guide <https://gefest.readthedocs.io/en/latest/gefest/quickstart.html>`__.
Tutorals for more spicific use cases can be found `tutorial section of docs <https://gefest.readthedocs.io/en/latest/tutorials/index.html>`__.
Project Structure
=================
The latest stable release of GEFEST is on the `main branch <https://github.com/ITMO-NSS-team/GEFEST/tree/main>`__.
The repository includes the following directories:
* Package `core <https://github.com/ITMO-NSS-team/GEFEST/tree/main/gefest/core>`__ contains the main classes and scripts. It is the *core* of GEFEST framework;
* Package `cases <https://github.com/ITMO-NSS-team/GEFEST/tree/main/cases>`__ includes several *how-to-use-cases* where you can start to discover how GEFEST works;
* All *unit and integration tests* can be observed in the `test <https://github.com/ITMO-NSS-team/GEFEST/tree/main/test>`__ directory;
* The sources of the documentation are in the `docs <https://github.com/ITMO-NSS-team/GEFEST/tree/main/docs>`__.
* Weights of pretrained DL models can be downloaded from `this repository <https://gitlab.actcognitive.org/itmo-nss-team/gefest-models>`__.
Cases and examples
==================
**Note**: To run the examples below, the old kernel gefest version, which can be installed on python 3.7 with:
.. code-block:: bash
pip install git+https://github.com/aimclub/GEFEST.git@4f9c34c449c0eb65d264476e5145f09b4839cd70
- `Experiments <https://github.com/ITMO-NSS-team/GEFEST-paper-experiments>`__ with various real and synthetic cases
- `Case <https://github.com/ITMO-NSS-team/rbc-traps-generative-design>`__ devoted to the red blood cell traps design.
Migrated examples can be found in cases folder of the main branch.
Current R&D and future plans
============================
Currently, we are working on integration of new types of physical objects with consideration of their internal structure.\n
The major ongoing tasks:
* to integrate three dimensional physical objects
* to implement gradient based approaches for optimization of physical objects
Documentation
=============
Detailed information and description of GEFEST framework is available in the `Read the Docs <https://gefest.readthedocs.io/en/latest/>`__
Contribution guide
==================
The contribution guide is available in the `page <https://gefest.readthedocs.io/en/latest/contribution.html>`__
Acknowledgments
===============
We acknowledge the contributors for their important impact and the participants of the numerous scientific conferences
and workshops for their valuable advice and suggestions.
Contacts
========
* `Telegram channel for solving problems and answering questions on GEFEST <https://t.me/gefest_helpdesk>`_
* `Natural System Simulation Team <https://itmo-nss-team.github.io/>`_
* `Newsfeed <https://t.me/NSS_group>`_
* `Youtube channel <https://www.youtube.com/channel/UC4K9QWaEUpT_p3R4FeDp5jA>`_
Supported by
============
`National Center for Cognitive Research of ITMO University <https://actcognitive.org/>`_
Citation
========
@article{starodubcev2023generative,
title={Generative design of physical objects using modular framework},
author={Starodubcev, Nikita O and Nikitin, Nikolay O and Andronova, Elizaveta A and Gavaza, Konstantin G and Sidorenko, Denis O and Kalyuzhnaya, Anna V},
journal={Engineering Applications of Artificial Intelligence},
volume={119},
pages={105715},
year={2023},
publisher={Elsevier}}
@inproceedings{solovev2023ai,
title={AI Framework for Generative Design of Computational Experiments with Structures in Physical Environment},
author={Solovev, Gleb Vitalevich and Kalyuzhnaya, Anna and Hvatov, Alexander and Starodubcev, Nikita and Petrov, Oleg and Nikitin, Nikolay},
booktitle={NeurIPS 2023 AI for Science Workshop},
year={2023}}
.. |build| image:: https://github.com/aimclub/GEFEST/workflows/unit%20tests/badge.svg?branch=main
:alt: Build Status
:target: https://github.com/aimclub/GEFEST/actions
.. |docs| image:: https://readthedocs.org/projects/gefest/badge/?version=latest
:target: https://gefest.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. |license| image:: https://img.shields.io/github/license/ITMO-NSS-team/GEFEST
:alt: Supported Python Versions
:target: ./LICENSE.md
.. |tg| image:: https://img.shields.io/badge/Telegram-Group-blue.svg
:target: https://t.me/gefest_helpdesk
:alt: Telegram Chat
.. |ITMO| image:: https://github.com/ITMO-NSS-team/open-source-ops/blob/add_badge/badges/ITMO_badge_rus.svg
:alt: Acknowledgement to ITMO
:target: https://itmo.ru
.. |NCCR| image:: https://github.com/ITMO-NSS-team/open-source-ops/blob/add_badge/badges/NCCR_badge.svg
:alt: Acknowledgement to NCCR
:target: https://actcognitive.org/
.. |gitlab| image:: https://camo.githubusercontent.com/9bd7b8c5b418f1364e72110a83629772729b29e8f3393b6c86bff237a6b784f6/68747470733a2f2f62616467656e2e6e65742f62616467652f6769746c61622f6d6972726f722f6f72616e67653f69636f6e3d6769746c6162
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:target: https://gitlab.actcognitive.org/itmo-nss-team/GEFEST
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"download_url": "https://files.pythonhosted.org/packages/56/d1/5dc1956de5e41cd60104f3a5c4747e845690d45c1ec42f9c6b422970fe24/gefest-0.1.0.tar.gz",
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