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.github/workflows/book_stable.yml

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jobs:
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build-book:
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runs-on: ubuntu-latest
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container: ghcr.io/fenics/dolfinx/lab:v0.8.0
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container: ghcr.io/fenics/dolfinx/lab:stable
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env:
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PYVISTA_TRAME_SERVER_PROXY_PREFIX: "/proxy/"

.github/workflows/test_nightly.yml

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- name: Test building the book
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run: PYVISTA_OFF_SCREEN=false jupyter-book build -W .
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- name: Test building the book
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run: PYVISTA_OFF_SCREEN=false jupyter-book build -W .
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- name: Test complex notebooks in parallel
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working-directory: chapter1
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run: |
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mpirun -n 2 python3 nonlinpoisson_code.py
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mpirun -n 2 python3 ns_code1.py
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mpirun -n 2 python3 ns_code2.py
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- name: Test chapter 3
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working-directory: chapter3
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run: |
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mpirun -n 2 python3 robin_neumann_dirichlet.py
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mpirun -n 2 python3 component_bc.py
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mpirun -n 2 python3 em.py
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- name: Test chapter 4
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working-directory: chapter4
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run: |

.github/workflows/test_stable.yml

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jobs:
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test:
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runs-on: ubuntu-latest
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container: ghcr.io/fenics/dolfinx/lab:v0.8.0
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container: ghcr.io/fenics/dolfinx/lab:stable
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env:
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PYVISTA_OFF_SCREEN: true
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run: |
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export PKG_CONFIG_PATH=/usr/local/dolfinx-complex/lib/pkgconfig:$PKG_CONFIG_PATH
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export PETSC_ARCH=linux-gnu-complex128-32
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export PYTHONPATH=/usr/local/dolfinx-complex/lib/python3.10/dist-packages:$PYTHONPATH
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export PYTHONPATH=/usr/local/dolfinx-complex/lib/python3.12/dist-packages:$PYTHONPATH
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export LD_LIBRARY_PATH=/usr/local/dolfinx-complex/lib:$LD_LIBRARY_PATH
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python3 complex_mode.py
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mpirun -n 2 python3 complex_mode.py

Changelog.md

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# Changelog
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## v0.9.0
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- `scale` in `apply_lifting` has been renamed to `alpha`
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- Use `dolfinx.fem.Function.x.petsc_vec` as opposed to `dolfinx.fem.Function.vector`
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## v0.8.0
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- Replace all `ufl.FiniteElement` and `ufl.VectorElement` with the appropriate `basix.ufl.element`

chapter4/compiler_parameters.ipynb

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"id": "3f832e78",
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"metadata": {},
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"source": [
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"Next we generate a general function to assemble the mass matrix for a unit cube. Note that we use `dolfinx.fem.Form` to compile the variational form. For codes using `dolfinx.LinearProblem`, you can supply `jit_options` as a keyword argument."
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"Next we generate a general function to assemble the mass matrix for a unit cube. Note that we use `dolfinx.fem.form` to compile the variational form. For codes using `dolfinx.fem.petsc.LinearProblem`, you can supply `jit_options` as a keyword argument."
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]
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},
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{

chapter4/compiler_parameters.py

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print(f"Directory to put C files in: {cache_dir}")
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# -
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# Next we generate a general function to assemble the mass matrix for a unit cube. Note that we use `dolfinx.fem.Form` to compile the variational form. For codes using `dolfinx.LinearProblem`, you can supply `jit_options` as a keyword argument.
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# Next we generate a general function to assemble the mass matrix for a unit cube. Note that we use `dolfinx.fem.form` to compile the variational form. For codes using `dolfinx.fem.petsc.LinearProblem`, you can supply `jit_options` as a keyword argument.
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# +
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chapter4/newton-solver.ipynb

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fem.md

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To use the notebooks in this tutorial with DOLFINx on your own computer, you should use the docker image obtained using the following command:
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```bash
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docker run --init -p 8888:8888 -v "$(pwd)":/root/shared ghcr.io/jorgensd/dolfinx-tutorial:v0.7.2
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docker run --init -p 8888:8888 -v "$(pwd)":/root/shared ghcr.io/jorgensd/dolfinx-tutorial:release
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```
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This image can also be used as a normal docker container by adding:
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```bash
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docker run --ti -v "$(pwd)":/root/shared --entrypoint="/bin/bash" ghcr.io/jorgensd/dolfinx-tutorial:v0.7.2
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docker run --ti -v "$(pwd)":/root/shared --entrypoint="/bin/bash" ghcr.io/jorgensd/dolfinx-tutorial:release
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```
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The tutorials can also be exported as an IPython notebook or PDF by clicking the ![Download](save.png)-symbol in the top right corner of the relevant tutorial. The notebook can in turn be used with a Python kernel which has DOLFINx.
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provides a definitive build recipe. As the DOLFINx docker images are hosted at Docker-hub, one can directly access the image using:
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```bash
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docker run dolfinx/dolfinx:v0.8.0
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docker run dolfinx/dolfinx:stable
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```
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There are several ways of customizing a docker container, such as mounting volumes/sharing folder, setting a working directory, sharing graphical interfaces etc. See `docker run --help` for an extensive list.

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