The DOLFINx tutorial

Author: Jørgen S. Dokken

This is the source code for the dolfinx-tutorial webpage. If you have any comments, corrections or questions, please submit an issue in the issue tracker.

Contributing

If you want to contribute to this tutorial, please make a fork of the repository, make your changes, and test that the CI passes. You can do this locally by downloading act and call

act -j test-nightly

Alternatively, if you want to add a separate chapter, a Jupyter notebook can be added to a pull request, without integrating it into the tutorial. If so, the notebook will be reviewed and modified to be included in the tutorial.

Any code added to the tutorial should work in parallel. If any changes are made to ipynb files, please ensure that these changes are reflected in the corresponding py files by using jupytext:

python3 -m jupytext --sync  */*.ipynb

Any code added to the tutorial should work in parallel.

Dependencies

It is adviced to use a pre-installed version of DOLFINx, for instance through conda or docker. Remaining dependencies can be installed with

python3 -m pip install --no-binary=h5py -e .

Docker images

Docker images for this tutorial can be found in the packages tab

Additional requirements on top of the dolfinx/lab:nightly images can be found at Dockerfile and pyproject.toml

An image building DOLFINx, Basix, UFL and FFCx from source can be built using:

cd docker
docker build -f ./docker/Dockerfile -t local_lab_env .

from the root of this repository, and run

 docker run --rm -ti -v $(pwd):/root/shared -w /root/shared  --init -p 8888:8888 local_lab_env

from the main directory.