example-paper-fenics

Example paper using FEniCS

https://github.com/scientificcomputing/example-paper-fenics

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 1 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 (15.9%) to scientific vocabulary

Keywords

fenics paper
Last synced: 6 months ago · JSON representation ·

Repository

Example paper using FEniCS

Basic Info
Statistics
  • Stars: 2
  • Watchers: 2
  • Forks: 2
  • Open Issues: 0
  • Releases: 4
Topics
fenics paper
Created over 3 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License Citation

README.md

Supplementary code for the paper: Title of paper

Binder

This repository contains supplementary code for the paper

Finsberg, H., Dokken, J. 2022. Title of paper, Journal of ..., volume, page, url

Abstract

Provide the abstract of the paper

Getting started

We provide a pre-build Docker image which can be used to run the the code in this repository. First thing you need to do is in ensure that you have docker installed.

To start an interactive docker container you can execute the following command

bash docker run --rm -it ghcr.io/scientificcomputing/example-paper-fenics:latest

Data

Data is available in a dropbox folder. Use the script download_data.sh in the data folder to download the data.

The data folder should have the following structure after the data is downloaded. ├── README.md ├── data.tar ├── download_data.sh └── mesh ├── heart01.msh └── heart02.msh These meshes are originally taken from https://ora.ox.ac.uk/objects/uuid:951b086c-c4ba-41ef-b967-c2106d87ee06, but since the original data is about 26GB we decided to make a smaller dataset for this example.

Eventually when you publish a paper you could put this data on e.g Zenodo. That will make sure the data gets it's own DOI.

Scripts

All the scripts are located in the folder called code in the repository. Is is assumed that you run the script from within this folder.

Pre-processing

In order to reproduce the results you need to first run the pre-processing script python3 pre_processing.py This will convert the meshes from Gmsh to a dolfin format.

Fiber generation

The next step is to run the fiber generation. You can do this by running the script python3 run_fiber_generation.py This will create a new folder code/results containing files called microstructure_<heart_nr>.h5.

Postprocessing

The final step is to postprocess the results by running the script python3 postprocess.py This will generate a file for visualizing the fibers in the Paraview (inside code/results called fiber_<heart_nr>.xdmf). This script will also compare some features computed from the fibers with the results published in the (artificial) paper. If the results differ, then the program will raise an error.

Citation

@software{Lisa_My_Research_Software_2017, author = {Lisa, Mona and Bot, Hew}, doi = {10.5281/zenodo.1234}, month = {12}, title = {{My Research Software}}, url = {https://github.com/scientificcomputing/example-paper}, version = {2.0.4}, year = {2017} }

Having issues

If you have any troubles please file and issue in the GitHub repository.

License

MIT

Owner

  • Name: Scientific Computing at Simula Research Laboratory
  • Login: scientificcomputing
  • Kind: organization

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Lisa"
  given-names: "Mona"
  orcid: "https://orcid.org/0000-0000-0000-0000"
- family-names: "Bot"
  given-names: "Hew"
  orcid: "https://orcid.org/0000-0000-0000-0000"
title: "My Research Software"
version: 0.3.0
doi: 10.5281/zenodo.1234
date-released: 2017-12-18
url: "https://github.com/scientificcomputing/example-paper"

GitHub Events

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Dependencies

requirements-docs.txt pypi
  • jupyter-book *
  • sphinxcontrib-bibtex *
.github/workflows/build_docs.yml actions
  • actions/cache v3 composite
  • actions/checkout v4 composite
  • actions/configure-pages v3 composite
  • actions/deploy-pages v2 composite
  • actions/upload-pages-artifact v2 composite
.github/workflows/docker-image.yml actions
  • actions/checkout v3 composite
  • docker/build-push-action v3 composite
  • docker/login-action v2 composite
  • docker/metadata-action 98669ae865ea3cffbcbaa878cf57c20bbf1c6c38 composite
  • docker/setup-buildx-action v2 composite
  • docker/setup-qemu-action v2 composite
.github/workflows/reproduce_results.yml actions
  • actions/cache v3 composite
  • actions/checkout v4 composite
  • actions/upload-artifact v3 composite
Dockerfile docker
  • ghcr.io/scientificcomputing/example-paper-fenics v0.1.6 build
docker/Dockerfile docker
  • ghcr.io/scientificcomputing/fenics-gmsh 2023-08-16 build
pyproject.toml pypi
  • cardiac-geometries >=0.11.0
  • h5py ==3.9.0
  • ldrb *
  • requests *
  • tqdm *
requirements.txt pypi
  • cardiac-geometries ==0.11.0
  • certifi ==2023.7.22
  • charset-normalizer ==3.3.2
  • click ==8.1.3
  • commonmark ==0.9.1
  • h5py ==3.9.0
  • idna ==3.4
  • ldrb ==2023.4.0
  • llvmlite ==0.40.1
  • meshio ==5.3.4
  • numba ==0.57.1
  • numpy ==1.21.6
  • pygments ==2.13.0
  • requests ==2.31.0
  • rich ==12.6.0
  • rich-click ==1.5.2
  • tqdm ==4.66.1
  • urllib3 ==2.0.7