LayOpt 0.0.1a1

Adaptive topology optimization of fail-safe trusses

LayOpt

LayOpt is a Python package for topology optimisation of fail-safe trusses developed by the Integrated Civil and Infrastructure Research Centre at The University of Sheffield. For more detailed information about the software please see our website.

Installation

Virtual Environment

It is recommended that you use a Python Virtual Environment to install LayOpt. There are many options available but a good choice, used in the development of LayOpt, is uv. Create a directory for your work and after installing uv create a virtual environment.

# Create a directory
mkdir LayOpt
# Change directory
cd LayOpt
# Create a virtual Environment
uv venv

PyPI

Layopt is available on PyPI. Ideally you should use a Python Virtual Environment (see above).

# Plain virtual environment
pip install layopt
# uv virtual environment
uv pip install layopt

Pre-releases

If you wish to try pre-releases, denoted by suffixes of the form a# for alpha releases, b# for beta and rc# for release candidates you should include the specific version when calling pip. For example to install the 0.1.0a1 (first alpha release of version 0.1.0) you would use...

# Plain virtual environment
pip install layopt==0.1.0a1
# uv virtual environment
uv pip install layopt==0.1.0a1

GitHub

You can use pip to install the package directly from GitHub. This allows you to install a specific branch or commit to test out new functionality that is under development. In your Virtual Environment run...

# Install from HEAD of main branch
pip install git@https://github.com/ICAIR-Sheffield/LayOpt
# Install a specific <branch>
pip install git@https://github.com/ICAIR-Sheffield/LayOpt.git@<branch>

Development

Contributions are welcome. If you are considering contributing to the development of LayOpt and are not a collaborator of the repository then you should fork to your account first and then clone from there.

To find out how to contribute please see our Contributing page

Documentation

We use the Material for Mkdocs static site generator to build a website. This is deployed on GitHub Pages.

• GitHub Pages

Citing

To cite this software please refer to the CITATION.cff included in this repository.

Publications

• Fairclough H.E., He L., Asfaha T.B., Rigby S. (2023) Adaptive topology optimization of fail-safe truss structures Structural and Multidisciplinary Optimization 66(7)148 doi:10.1007/s00158-023-03585-x
• He L., Gilbert M., Song X. (2019) A Python script for adaptive layout optimization of trusses Structural and Multidisciplinary Optimization 60(2) 835-847 doi:10.1007/s00158-019-02226-6