Release version compatible with 0.5.0 (#92)

* Bump version

* Try fixing weird formatting

* Try fixing pyvista ci

.github/workflows/build-publish.yml

@@ -20,7 +20,7 @@ jobs:
   build-publish:
     # The type of runner that the job will run on
     runs-on: ubuntu-latest
-    container: dokken92/dolfinx_custom:10082022
+    container: dokken92/dolfinx_custom:v0.5.0
 
     env:
       HDF5_MPI: "ON"

.github/workflows/nightly.yml

@@ -38,7 +38,7 @@ jobs:
           pip3 install --upgrade pip setuptools
           CC=mpicc HDF_MPI="ON" HDF5_DIR="/usr/local/" pip3 install --no-cache-dir -r docker/requirements.txt
           pip3 uninstall pyvista -y
-          pip3 install pyvista --upgrade
+          pip3 install pyvista --upgrade --user
           apt-get -qq update
           apt-get install -y libgl1-mesa-dev xvfb nodejs
 

Changelog.md

@@ -1,6 +1,9 @@
 # Changelog
 
 ## Dev
+- No Changes
+
+## v0.5.0
 - Using new GMSH interface in DOLFINx (`dolfinx.io.gmshio`) in all demos using GMSH
 - Added a section on custom Newton-solvers, see [chapter4/newton-solver].
 - Various minor DOLFINx API updates. `dolfinx.mesh.compute_boundary_facets` -> `dolfinx.mesh.exterior_facet_indices` with slightly different functionality. Use `dolfinx.mesh.MeshTagsMetaClass.find` instead of `mt.indices[mt.values==value]`.

Dockerfile

@@ -1,4 +1,4 @@
-FROM dokken92/dolfinx_custom:10082022
+FROM dokken92/dolfinx_custom:v0.5.0
 
 # create user with a home directory
 ARG NB_USER

chapter3/neumann_dirichlet_code.ipynb

@@ -11,9 +11,11 @@
     "\n",
     "Let's return to the Poisson problem from the [Fundamentals chapter](./../chapter1/fundamentals.md) and see how to extend the mathematics and the implementation to handle Dirichlet condition in combination with a Neumann condition.\n",
     "The domain is still the unit square, but now we set the Dirichlet condition $u=u_D$ at the left and right sides, while the Neumann condition \n",
+    "\n",
     "$$\n",
     "-\\frac{\\partial u}{\\partial n}=g\n",
     "$$\n",
+    "\n",
     "is applied to the  remaining sides $y=0$ and $y=1$.\n",
     "\n",
     "## The PDE problem\n",

chapter3/neumann_dirichlet_code.py

@@ -19,9 +19,11 @@
 #
 # Let's return to the Poisson problem from the [Fundamentals chapter](./../chapter1/fundamentals.md) and see how to extend the mathematics and the implementation to handle Dirichlet condition in combination with a Neumann condition.
 # The domain is still the unit square, but now we set the Dirichlet condition $u=u_D$ at the left and right sides, while the Neumann condition 
+#
 # $$
 # -\frac{\partial u}{\partial n}=g
 # $$
+#
 # is applied to the  remaining sides $y=0$ and $y=1$.
 #
 # ## The PDE problem

docker/Dockerfile

@@ -1,4 +1,4 @@
-FROM dolfinx/lab:nightly
+FROM dolfinx/lab:v0.5.0
 
 WORKDIR /tmp/
 

docker/LocalDockerfile

@@ -16,14 +16,6 @@ ARG HDF5_MPI="ON"
 # Can be set to "notebook"
 ARG JUPYTER_TYPE="lab" 
 
-# Reinstall HDF5
-RUN export HDF5_SERIES=1.12 && \
-    export HDF5_PATCH=2 && \
-    wget -nc --quiet https://support.hdfgroup.org/ftp/HDF5/releases/hdf5-${HDF5_SERIES}/hdf5-${HDF5_SERIES}.${HDF5_PATCH}/src/hdf5-${HDF5_SERIES}.${HDF5_PATCH}.tar.gz && \
-    tar xfz hdf5-${HDF5_SERIES}.${HDF5_PATCH}.tar.gz && \
-    cmake -G Ninja -DCMAKE_INSTALL_PREFIX=/usr/local -DCMAKE_BUILD_TYPE=Release -DHDF5_ENABLE_PARALLEL=on -DHDF5_ENABLE_Z_LIB_SUPPORT=on -B build-dir -S hdf5-${HDF5_SERIES}.${HDF5_PATCH} && \
-    cmake --build build-dir && \
-    cmake --install build-dir
 
 # Install python dependencies
 RUN pip3 install --upgrade pip 

fem.md

@@ -27,18 +27,23 @@ As this book has been published as a Jupyter Book, we provide interactive notebo
 ## Obtaining the software
 
 If you would like to work with DOLFINx outside of the binder-notebooks, you need to install the FEniCS software. 
-The recommended way of installing DOLFINx for new usesers is by using Docker. 
+The recommended way of installing DOLFINx for new users is by using Docker. 
 Docker is a software that uses *containers* to supply software across different kinds of operating systems (Linux, Mac, Windows). The first step is to install docker, following the instructions at their [webpage](https://docs.docker.com/get-started/).
 
 All notebooks can be converted to python files using [nbconvert](https://nbconvert.readthedocs.io/en/latest/).
 
 ### Tutorial compatible docker images
-The tutorial uses several dependencies for meshing, plotting and timings. A compatible `JupyterLab` image is available at [DockerHub/dokken92/dolfinx_custom:10082022](https://hub.docker.com/r/dokken92/dolfinx_custom/tags)
+The tutorial uses several dependencies for meshing, plotting and timings. A compatible `JupyterLab` image is available at [DockerHub/dokken92/dolfinx_custom:v0.5.0](https://hub.docker.com/r/dokken92/dolfinx_custom/tags)
 
-To use the notebookes in this tutorial with DOLFINx on your own computer, you should use the docker image using the following command
+To use the notebooks in this tutorial with DOLFINx on your own computer, you should use the docker image using the following command
+```bash
+  docker run --init -p 8888:8888 -v "$(pwd)":/root/shared dokken92/dolfinx_custom:v0.5.0
 ```
-  docker run --init -p 8888:8888 -v "$(pwd)":/root/shared dokken92/dolfinx_custom:10082022
+This image can also be used as a normal docker container by adding:
+```bash
+  docker run --ti -v "$(pwd)":/root/shared  --entrypoint="/bin/bash" dokken92/dolfinx_custom:v0.5.0
 ```
+
 The tutorials can also be exported as a notebook or PDF by clicking the ![Download](save.png)-symbol in the top right corner of the relevant tutorialThe notebook can in turn be used with a Python kernel which has DOLFINx.
 
 ### Official images
@@ -47,7 +52,7 @@ The FEniCS project supplies pre-built docker images at [https://hub.docker.com/r
 The [Dockerfile](https://github.com/FEniCS/dolfinx/blob/main/docker/Dockerfile)
 provides a definitive build recipe. As the DOLFINx docker images are hosted at Docker-hub, one can directly access the image
 ```
-docker run dolfinx/dolfinx
+docker run dolfinx/dolfinx:v0.5.0
 ```
 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.