optimus

The official repository of OptimUS: a Python library for solving 3D acoustic wave propagation.

https://github.com/optimuslib/optimus

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 17 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (19.9%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

The official repository of OptimUS: a Python library for solving 3D acoustic wave propagation.

Basic Info
  • Host: GitHub
  • Owner: optimuslib
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 39.3 MB
Statistics
  • Stars: 20
  • Watchers: 2
  • Forks: 8
  • Open Issues: 2
  • Releases: 4
Created over 4 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

OptimUS

Documentation Status

An open-source Python library for solving 3D acoustic wave propagation.

The OptimUS library provides functionality to simulate acoustic wave propagation in an unbounded domain with multiple scatterers. OptimUS solves the Helmholtz equation in multiple domains with homogeneous material parameters, using a boundary element method (BEM). The library targets general acoustical simulation and has functionality for focused ultrasound in biomedical engineering.

Installation

The OptimUS library and all dependencies are installed and tested in a Docker container. First, install the docker engine on your machine following the instruction on the docker website. Then, pull the docker container by running:

bash docker pull optimuslib/optimus:latest

Downloading and installing the OptimUS' Docker image takes several minutes and requires a stable internet connection. This step can be skipped next time you use the Docker image and is only necessary to update with a new release.

To start the container on your machine, run:

bash docker run -it -v $(pwd):/home/optimus/localwork --workdir /home/optimus/localwork -p 8888:8888 optimuslib/optimus:latest The output will provide the URL and token to access the Jupyter notebook interface from a web browser.

Upon accessing Jupyter, you can execute the notebooks available in the notebook directory on this GitHub page.

If you want to get a bash terminal within the container, you can either launch one through the Jupyter notebook interface or via Docker as:

bash docker run -it --rm -v $(pwd):/home/optimus/localwork --workdir /home/optimus/localwork optimuslib/optimus:latest

In the terminal, you can execute your Python files by running:

bash python3 <file_name.py>

Troubleshooting

Depending on the configuration of your machine's OS, you may need to adapt the above Docker commands. - Some systems require running the above Docker commands as a super user. In a bash terminal use: sudo docker instead of docker. - On Windows, PowerShell works best. Other shell environments may not detect $(pwd) as the current working directory and one needs to provide the full path, for example, C:\Users\myname:/home/optimus/localwork with the first part adapted to the path of your local folder to be detected in the Docker container.

Documentation

Examples are available in the notebook directory on this GitHub page. Automatically generated documentation of the Python API can be found in Read the Docs optimus project.

Getting help

Enquiries about the library and questions should be asked on the GitHub discussion page. Errors in the library should be added to the GitHub issue tracker.

Citation

If you use OptimUS in your work, please cite it as follows:

APA Gélat, P., Haqshenas, S. R., and van 't Wout, E. (2022), OptimUS: A Python library for solving 3D acoustic wave propagation, https://github.com/optimuslib/optimus

BibTeX @software{optimuslib, author = {Gélat, Pierre and Haqshenas, Reza and van 't Wout, Elwin}, title = {OptimUS}, url = {https://github.com/optimuslib/optimus}, version = {0.2.1} }

DOI

https://doi.org/10.5281/zenodo.15039756

Acknowledgement

Licence

OptimUS is licensed under an MIT licence. Full text of the licence can be found here.

References

The main references describing the BEM formulations and preconditioners implemented in OptimUS are as follows:

Haqshenas, S. R., Gélat, P., van 't Wout, E., Betcke, T., & Saffari, N. (2021). A fast full-wave solver for calculating ultrasound propagation in the body. Ultrasonics, 110, 106240. doi:10.1016/j.ultras.2020.106240

van 't Wout, E., Haqshenas, S. R., Gélat, P., Betcke, T., & Saffari, N. (2021). Benchmarking preconditioned boundary integral formulations for acoustics. International Journal for Numerical Methods in Engineering, nme.6777. doi:10.1002/nme.6777

van 't Wout, E., Haqshenas, S. R., Gélat, P., Betcke, T., & Saffari, N. (2022). Boundary integral formulations for acoustic modelling of high-contrast media. Computers & Mathematics with Applications, 105, 136-149. doi:10.1016/j.camwa.2021.11.021

van 't Wout, E., Haqshenas, S. R., Gélat, P., Betcke, T., & Saffari, N. (2022). Frequency-robust preconditioning of boundary integral equations for acoustic transmission. Journal of Computational Physics, 111229. doi:10.1016/j.jcp.2022.111229

Owner

  • Name: optimuslib
  • Login: optimuslib
  • Kind: organization
  • Email: optimusproject2017@gmail.com

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use OptimUS in your work, please cite it as below."
authors:
- family-names: "Gélat"
  given-names: "Pierre"
  orcid: "https://orcid.org/0000-0002-4462-2421"
- family-names: "Haqshenas"
  given-names: "Reza"
  orcid: "https://orcid.org/0000-0002-3082-0232"
- family-names: "van't Wout"
  given-names: "Elwin"
  orcid: "https://orcid.org/0000-0002-9096-5054"
title: "optimuslib"
version: 0.1.0
doi: 
url: "hhttps://github.com/optimuslib/optimus"
preferred-citation:
  type: software-code
  title: "optimuslib"
  authors:
  - family-names: "Gélat"
    given-names: "Pierre"
    orcid: "https://orcid.org/0000-0002-4462-2421"
  - family-names: "Haqshenas"
    given-names: "Reza"
    orcid: "https://orcid.org/0000-0002-3082-0232"
  - family-names: "van't Wout"
    given-names: "Elwin"
    orcid: "https://orcid.org/0000-0002-9096-5054"
  doi:
  year: 2022

GitHub Events

Total
  • Release event: 2
  • Watch event: 7
  • Delete event: 5
  • Issue comment event: 2
  • Push event: 12
  • Pull request review event: 6
  • Pull request event: 10
  • Fork event: 1
  • Create event: 6
Last Year
  • Release event: 2
  • Watch event: 7
  • Delete event: 5
  • Issue comment event: 2
  • Push event: 12
  • Pull request review event: 6
  • Pull request event: 10
  • Fork event: 1
  • Create event: 6

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 0
  • Total pull requests: 4
  • Average time to close issues: N/A
  • Average time to close pull requests: about 1 month
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.5
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 4
  • Average time to close issues: N/A
  • Average time to close pull requests: about 1 month
  • Issue authors: 0
  • Pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.5
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • pgelat (1)
Pull Request Authors
  • pgelat (3)
  • evantwout (3)
  • gato1108 (1)
  • SRHaqshenas (1)
  • ShescBlank (1)
  • javisanh (1)
Top Labels
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Dependencies

Dockerfile docker
  • optimuslib/optimus notebook build
docs/requirements.txt pypi
  • alabaster ==0.7.12
  • babel ==2.10.3
  • certifi ==2022.6.15
  • charset-normalizer ==2.1.0
  • docutils ==0.17.1
  • idna ==3.3
  • imagesize ==1.4.1
  • jinja2 ==3.1.2
  • markupsafe ==2.1.1
  • numpydoc *
  • packaging ==21.3
  • pydata-sphinx-theme *
  • pygments ==2.12.0
  • pyparsing ==3.0.9
  • pytz ==2022.1
  • requests ==2.28.1
  • snowballstemmer ==2.2.0
  • sphinx ==5.0.2
  • sphinx-autoapi *
  • sphinx-rtd-theme ==1.0.0
  • sphinxcontrib-applehelp ==1.0.2
  • sphinxcontrib-devhelp ==1.0.2
  • sphinxcontrib-htmlhelp ==2.0.0
  • sphinxcontrib-jsmath ==1.0.1
  • sphinxcontrib-qthelp ==1.0.3
  • sphinxcontrib-serializinghtml ==1.1.5
  • urllib3 ==1.26.9
pyproject.toml pypi
setup.py pypi