PyElastica is the python implementation of Elastica, which is a free and open-source software project for the simulation of assemblies of slender, one-dimensional structures using Cosserat Rod theory. More information about Elastica and Cosserat rod theory is available at the Elastica project website
The current version of PyElastica released here is the educational version. This version is a straight forward Python implementation of the Elastica code making heavy use of numpy. As such, it is very slow. We are working on a significantly accelerated Python version of the code that we hope to release soon.
PyElastica is compatible with Python 3.5 - 3.8. The easiest way to install PyElastica is with PIP.
$ pip install pyelastica Documentation of PyElastica is available at docs.cosseratrods.org
PyElastica is developed by the Gazzola Lab at the University of Illinois at Urbana-Champaign.
We have created several Jupyter notebooks and Python scripts to help get users started with using PyElastica. The Jupyter notebooks are available on Binder, allowing you to try out some of the tutorials without having to install PyElastica.
We ask that any publications which use Elastica cite the following papers:
Zhang, Chan, Parthasarathy, Gazzola, Modeling and simulation of complex dynamic musculoskeletal architectures, Nature Communications, 2019. doi: 10.1038/s41467-019-12759-5
Gazzola, Dudte, McCormick, Mahadevan, Forward and inverse problems in the mechanics of soft filaments, Royal Society Open Science, 2018. doi: 10.1098/rsos.171628
@article{gazzola2018forward,
title={Forward and inverse problems in the mechanics of soft filaments},
author={Gazzola, M and Dudte, LH and McCormick, AG and Mahadevan, L},
journal={Royal Society open science},
volume={5},
number={6},
pages={171628},
year={2018},
publisher={The Royal Society Publishing},
doi = {10.1098/rsos.171628},
url = {https://doi.org/10.1098/rsos.171628},
}
@article{zhang2019modeling,
title={Modeling and simulation of complex dynamic musculoskeletal architectures},
author={Zhang, X and Chan, FK and Parthasarathy, T and Gazzola, M},
journal={Nature Communications},
volume={10},
number={1},
pages={1--12},
year={2019},
publisher={Nature Publishing Group},
doi = {10.1038/s41467-019-12759-5},
url = {https://doi.org/10.1038/s41467-019-12759-5},
}