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.

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:

Building the book and running code

The book is built using jupyterbook. The following environment variables should be set if you want to build the book

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="html"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you run the tutorial using jupyter-lab, for instance through conda, one should set the following environment variables

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="trame"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you use docker to run your code, you should set the following variables:

docker run -ti -e DISPLAY=$DISPLAY -e LIBGL_ALWAYS_SOFTWARE=1 -e PYVISTA_OFF_SCREEN=false -e PYVISTA_JUPYTER_BACKEND="trame" -e JUPYTER_EXTENSION_ENABLED=true --network=host -v $(pwd):/root/shared -w /root/shared ....

To run python scripts, either choose PYVISTA_OFF_SCREEN=True to get screenshots, or render interactive plots with PYVISTA_OFF_SCREEN=False

python3 -m jupytext --sync */*.ipynb --set-formats ipynb,py:light

or

python3 -m jupytext --sync */*.py --set-formats ipynb,py:light

Any code added to the tutorial should work in parallel.

To strip notebook output, one can use pre-commit.

pre-commit run --all-files

Dependencies

It is advised 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 --no-build-isolation -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:

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.

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.

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:

Building the book and running code

The book is built using jupyterbook. The following environment variables should be set if you want to build the book

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="html"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you run the tutorial using jupyter-lab, for instance through conda, one should set the following environment variables

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="trame"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you use docker to run your code, you should set the following variables:

docker run -ti -e DISPLAY=$DISPLAY -e LIBGL_ALWAYS_SOFTWARE=1 -e PYVISTA_OFF_SCREEN=false -e PYVISTA_JUPYTER_BACKEND="trame" -e JUPYTER_EXTENSION_ENABLED=true --network=host -v $(pwd):/root/shared -w /root/shared ....

To run python scripts, either choose PYVISTA_OFF_SCREEN=True to get screenshots, or render interactive plots with PYVISTA_OFF_SCREEN=False

python3 -m jupytext --sync */*.ipynb --set-formats ipynb,py:light

or

python3 -m jupytext --sync */*.py --set-formats ipynb,py:light

Any code added to the tutorial should work in parallel.

To strip notebook output, one can use pre-commit.

pre-commit run --all-files

Dependencies

It is advised 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 --no-build-isolation -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:

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.

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.

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:

Building the book and running code

The book is built using jupyterbook. The following environment variables should be set if you want to build the book

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="html"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you run the tutorial using jupyter-lab, for instance through conda, one should set the following environment variables

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="trame"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you use docker to run your code, you should set the following variables:

docker run -ti -e DISPLAY=$DISPLAY -e LIBGL_ALWAYS_SOFTWARE=1 -e PYVISTA_OFF_SCREEN=false -e PYVISTA_JUPYTER_BACKEND="trame" -e JUPYTER_EXTENSION_ENABLED=true --network=host -v $(pwd):/root/shared -w /root/shared ....

To run python scripts, either choose PYVISTA_OFF_SCREEN=True to get screenshots, or render interactive plots with PYVISTA_OFF_SCREEN=False

python3 -m jupytext --sync */*.ipynb --set-formats ipynb,py:light

or

python3 -m jupytext --sync */*.py --set-formats ipynb,py:light

Any code added to the tutorial should work in parallel.

To strip notebook output, one can use pre-commit.

pre-commit run --all-files

Dependencies

It is advised 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 --no-build-isolation -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:

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.

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.

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:

Building the book and running code

The book is built using jupyterbook. The following environment variables should be set if you want to build the book

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="html"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you run the tutorial using jupyter-lab, for instance through conda, one should set the following environment variables

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="trame"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you use docker to run your code, you should set the following variables:

docker run -ti -e DISPLAY=$DISPLAY -e LIBGL_ALWAYS_SOFTWARE=1 -e PYVISTA_OFF_SCREEN=false -e PYVISTA_JUPYTER_BACKEND="trame" -e JUPYTER_EXTENSION_ENABLED=true --network=host -v $(pwd):/root/shared -w /root/shared ....

To run python scripts, either choose PYVISTA_OFF_SCREEN=True to get screenshots, or render interactive plots with PYVISTA_OFF_SCREEN=False

python3 -m jupytext --sync */*.ipynb --set-formats ipynb,py:light

or

python3 -m jupytext --sync */*.py --set-formats ipynb,py:light

Any code added to the tutorial should work in parallel.

To strip notebook output, one can use pre-commit.

pre-commit run --all-files

Dependencies

It is advised 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 --no-build-isolation -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:

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.

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.

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:

Building the book and running code

The book is built using jupyterbook. The following environment variables should be set if you want to build the book

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="html"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you run the tutorial using jupyter-lab, for instance through conda, one should set the following environment variables

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="trame"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you use docker to run your code, you should set the following variables:

docker run -ti -e DISPLAY=$DISPLAY -e LIBGL_ALWAYS_SOFTWARE=1 -e PYVISTA_OFF_SCREEN=false -e PYVISTA_JUPYTER_BACKEND="trame" -e JUPYTER_EXTENSION_ENABLED=true --network=host -v $(pwd):/root/shared -w /root/shared ....

To run python scripts, either choose PYVISTA_OFF_SCREEN=True to get screenshots, or render interactive plots with PYVISTA_OFF_SCREEN=False

python3 -m jupytext --sync */*.ipynb --set-formats ipynb,py:light

or

python3 -m jupytext --sync */*.py --set-formats ipynb,py:light

Any code added to the tutorial should work in parallel.

To strip notebook output, one can use pre-commit.

pre-commit run --all-files

Dependencies

It is advised 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 --no-build-isolation -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:

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.

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.

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:

Building the book and running code

The book is built using jupyterbook. The following environment variables should be set if you want to build the book

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="html"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you run the tutorial using jupyter-lab, for instance through conda, one should set the following environment variables

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="trame"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you use docker to run your code, you should set the following variables:

docker run -ti -e DISPLAY=$DISPLAY -e LIBGL_ALWAYS_SOFTWARE=1 -e PYVISTA_OFF_SCREEN=false -e PYVISTA_JUPYTER_BACKEND="trame" -e JUPYTER_EXTENSION_ENABLED=true --network=host -v $(pwd):/root/shared -w /root/shared ....

To run python scripts, either choose PYVISTA_OFF_SCREEN=True to get screenshots, or render interactive plots with PYVISTA_OFF_SCREEN=False

python3 -m jupytext --sync */*.ipynb --set-formats ipynb,py:light

or

python3 -m jupytext --sync */*.py --set-formats ipynb,py:light

Any code added to the tutorial should work in parallel.

To strip notebook output, one can use pre-commit.

pre-commit run --all-files

Dependencies

It is advised 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 --no-build-isolation -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:

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.

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.

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:

Building the book and running code

The book is built using jupyterbook. The following environment variables should be set if you want to build the book

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="html"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you run the tutorial using jupyter-lab, for instance through conda, one should set the following environment variables

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="trame"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you use docker to run your code, you should set the following variables:

docker run -ti -e DISPLAY=$DISPLAY -e LIBGL_ALWAYS_SOFTWARE=1 -e PYVISTA_OFF_SCREEN=false -e PYVISTA_JUPYTER_BACKEND="trame" -e JUPYTER_EXTENSION_ENABLED=true --network=host -v $(pwd):/root/shared -w /root/shared ....

To run python scripts, either choose PYVISTA_OFF_SCREEN=True to get screenshots, or render interactive plots with PYVISTA_OFF_SCREEN=False

python3 -m jupytext --sync */*.ipynb --set-formats ipynb,py:light

or

python3 -m jupytext --sync */*.py --set-formats ipynb,py:light

Any code added to the tutorial should work in parallel.

To strip notebook output, one can use pre-commit.

pre-commit run --all-files

Dependencies

It is advised 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 --no-build-isolation -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:

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.

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.

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:

Building the book and running code

The book is built using jupyterbook. The following environment variables should be set if you want to build the book

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="html"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you run the tutorial using jupyter-lab, for instance through conda, one should set the following environment variables

PYVISTA_OFF_SCREEN=false
PYVISTA_JUPYTER_BACKEND="trame"
JUPYTER_EXTENSION_ENABLED=true
LIBGL_ALWAYS_SOFTWARE=1

If you use docker to run your code, you should set the following variables:

docker run -ti -e DISPLAY=$DISPLAY -e LIBGL_ALWAYS_SOFTWARE=1 -e PYVISTA_OFF_SCREEN=false -e PYVISTA_JUPYTER_BACKEND="trame" -e JUPYTER_EXTENSION_ENABLED=true --network=host -v $(pwd):/root/shared -w /root/shared ....

To run python scripts, either choose PYVISTA_OFF_SCREEN=True to get screenshots, or render interactive plots with PYVISTA_OFF_SCREEN=False

python3 -m jupytext --sync */*.ipynb --set-formats ipynb,py:light

or

python3 -m jupytext --sync */*.py --set-formats ipynb,py:light

Any code added to the tutorial should work in parallel.

To strip notebook output, one can use pre-commit.

pre-commit run --all-files

Dependencies

It is advised 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 --no-build-isolation -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:

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.

Name		Name	Last commit message	Last commit date
.github		.github
.vscode		.vscode
chapter1		chapter1
chapter2		chapter2
chapter3		chapter3
chapter4		chapter4
docker		docker
.dockerignore		.dockerignore
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
Changelog.md		Changelog.md
Dockerfile		Dockerfile
README.md		README.md
_config.yml		_config.yml
_toc.yml		_toc.yml
binder.png		binder.png
fem.md		fem.md
fenics_logo.png		fenics_logo.png
git.png		git.png
index.ipynb		index.ipynb
jupyter_book.code-workspace		jupyter_book.code-workspace
pyproject.toml		pyproject.toml
references.bib		references.bib
save.png		save.png
tox.ini		tox.ini

Name		Name	Last commit message	Last commit date
.github		.github
.vscode		.vscode
chapter1		chapter1
chapter2		chapter2
chapter3		chapter3
chapter4		chapter4
docker		docker
.dockerignore		.dockerignore
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
Changelog.md		Changelog.md
Dockerfile		Dockerfile
README.md		README.md
_config.yml		_config.yml
_toc.yml		_toc.yml
binder.png		binder.png
fem.md		fem.md
fenics_logo.png		fenics_logo.png
git.png		git.png
index.ipynb		index.ipynb
jupyter_book.code-workspace		jupyter_book.code-workspace
pyproject.toml		pyproject.toml
references.bib		references.bib
save.png		save.png
tox.ini		tox.ini

Name		Name	Last commit message	Last commit date
.github		.github
.vscode		.vscode
chapter1		chapter1
chapter2		chapter2
chapter3		chapter3
chapter4		chapter4
docker		docker
.dockerignore		.dockerignore
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
Changelog.md		Changelog.md
Dockerfile		Dockerfile
README.md		README.md
_config.yml		_config.yml
_toc.yml		_toc.yml
binder.png		binder.png
fem.md		fem.md
fenics_logo.png		fenics_logo.png
git.png		git.png
index.ipynb		index.ipynb
jupyter_book.code-workspace		jupyter_book.code-workspace
pyproject.toml		pyproject.toml
references.bib		references.bib
save.png		save.png
tox.ini		tox.ini

Name		Name	Last commit message	Last commit date
.github		.github
.vscode		.vscode
chapter1		chapter1
chapter2		chapter2
chapter3		chapter3
chapter4		chapter4
docker		docker
.dockerignore		.dockerignore
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
Changelog.md		Changelog.md
Dockerfile		Dockerfile
README.md		README.md
_config.yml		_config.yml
_toc.yml		_toc.yml
binder.png		binder.png
fem.md		fem.md
fenics_logo.png		fenics_logo.png
git.png		git.png
index.ipynb		index.ipynb
jupyter_book.code-workspace		jupyter_book.code-workspace
pyproject.toml		pyproject.toml
references.bib		references.bib
save.png		save.png
tox.ini		tox.ini

Name		Name	Last commit message	Last commit date
.github		.github
.vscode		.vscode
chapter1		chapter1
chapter2		chapter2
chapter3		chapter3
chapter4		chapter4
docker		docker
.dockerignore		.dockerignore
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
Changelog.md		Changelog.md
Dockerfile		Dockerfile
README.md		README.md
_config.yml		_config.yml
_toc.yml		_toc.yml
binder.png		binder.png
fem.md		fem.md
fenics_logo.png		fenics_logo.png
git.png		git.png
index.ipynb		index.ipynb
jupyter_book.code-workspace		jupyter_book.code-workspace
pyproject.toml		pyproject.toml
references.bib		references.bib
save.png		save.png
tox.ini		tox.ini

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The DOLFINx tutorial

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