Update navierstokes.md

.github/workflows/book_stable.yml

@@ -12,11 +12,12 @@ env:
   HDF5_DIR: "/usr/local/"
   DISPLAY: ":99.0"
   DEB_PYTHON_INSTALL_LAYOUT: deb_system
+  LIBGL_ALWAYS_SOFTWARE: 1
 
 jobs:
   build-book:
     runs-on: ubuntu-latest
-    container: ghcr.io/fenics/dolfinx/lab:v0.8.0
+    container: ghcr.io/fenics/dolfinx/lab:stable
 
     env:
       PYVISTA_TRAME_SERVER_PROXY_PREFIX: "/proxy/"
@@ -37,7 +38,7 @@ jobs:
         run: jupyter-book build . -W
 
       - uses: actions/upload-artifact@v4
-        if : always()
+        if: always()
         with:
           name: webpage
           path: ./_build/html

.github/workflows/deploy.yml

@@ -38,7 +38,7 @@ jobs:
         uses: actions/checkout@v4
 
       - name: Setup Pages
-        uses: actions/configure-pages@v4
+        uses: actions/configure-pages@v5
 
       - name: Download docs artifact
         uses: actions/download-artifact@v4

.github/workflows/publish_docker.yml

@@ -45,7 +45,7 @@ jobs:
           images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
 
       - name: Build Docker image
-        uses: docker/build-push-action@v5
+        uses: docker/build-push-action@v6
         with:
           context: .
           load: true
@@ -56,7 +56,7 @@ jobs:
           labels: ${{ steps.meta.outputs.labels }}
 
       - name: Build (arm) and push (amd/arm) Docker image
-        uses: docker/build-push-action@v5
+        uses: docker/build-push-action@v6
         if: github.event_name == 'push'
         with:
           context: .

.github/workflows/test_nightly.yml

@@ -24,6 +24,7 @@ jobs:
       PYVISTA_OFF_SCREEN: true
       DISPLAY: ":99.0"
       PYVISTA_JUPYTER_BACKEND: html
+      LIBGL_ALWAYS_SOFTWARE: 1
 
     steps:
       - uses: actions/checkout@v4
@@ -39,6 +40,9 @@ jobs:
       - name: Test building the book
         run: PYVISTA_OFF_SCREEN=false jupyter-book build  -W .
 
+      - name: Test building the book
+        run: PYVISTA_OFF_SCREEN=false jupyter-book build  -W .
+
       - name: Test complex notebooks in parallel
         working-directory: chapter1
         run: |
@@ -67,7 +71,6 @@ jobs:
           mpirun -n 2 python3 nonlinpoisson_code.py
           mpirun -n 2 python3 ns_code1.py
           mpirun -n 2 python3 ns_code2.py
-
       - name: Test chapter 3
         working-directory: chapter3
         run: |
@@ -77,7 +80,6 @@ jobs:
           mpirun -n 2 python3 robin_neumann_dirichlet.py
           mpirun -n 2 python3 component_bc.py
           mpirun -n 2 python3 em.py
-
       - name: Test chapter 4
         working-directory: chapter4
         run: |

.github/workflows/test_stable.yml

@@ -10,17 +10,20 @@ env:
   HDF5_DIR: "/usr/local/"
   DISPLAY: ":99.0"
   DEB_PYTHON_INSTALL_LAYOUT: deb_system
+  LIBGL_ALWAYS_SOFTWARE: 1
 
 jobs:
   test:
     runs-on: ubuntu-latest
-    container: ghcr.io/fenics/dolfinx/lab:v0.8.0
+    container: ghcr.io/fenics/dolfinx/lab:stable
     env:
       PYVISTA_OFF_SCREEN: true
 
     # Steps represent a sequence of tasks that will be executed as part of the job
     steps:
       - uses: actions/checkout@v4
+        with:
+          ref: release
 
       - uses: ./.github/actions/install-dependencies
 
@@ -33,30 +36,30 @@ jobs:
         run: |
           export PKG_CONFIG_PATH=/usr/local/dolfinx-complex/lib/pkgconfig:$PKG_CONFIG_PATH
           export PETSC_ARCH=linux-gnu-complex128-32
-          export PYTHONPATH=/usr/local/dolfinx-complex/lib/python3.10/dist-packages:$PYTHONPATH
+          export PYTHONPATH=/usr/local/dolfinx-complex/lib/python3.12/dist-packages:$PYTHONPATH
           export LD_LIBRARY_PATH=/usr/local/dolfinx-complex/lib:$LD_LIBRARY_PATH
           python3 complex_mode.py
           mpirun -n 2 python3 complex_mode.py
-  
+
       - name: Test chapter 1
         working-directory: chapter1
         run: |
-            python3 -c "from pyvista import start_xvfb; start_xvfb(0.1)"
-            mpirun -n 2 python3 fundamentals_code.py
-            mpirun -n 2 python3 nitsche.py
-            mpirun -n 2 python3 membrane_code.py
+          python3 -c "from pyvista import start_xvfb; start_xvfb(0.1)"
+          mpirun -n 2 python3 fundamentals_code.py
+          mpirun -n 2 python3 nitsche.py
+          mpirun -n 2 python3 membrane_code.py
 
       - name: Test chapter 2
         working-directory: chapter2
-        run: |    
+        run: |
           mpirun -n 2 python3 diffusion_code.py
           mpirun -n 2 python3 heat_code.py
           mpirun -n 2 python3 linearelasticity_code.py
           mpirun -n 2 python3 hyperelasticity.py
           mpirun -n 2 python3 nonlinpoisson_code.py
           mpirun -n 2 python3 ns_code1.py
           mpirun -n 2 python3 ns_code2.py
-        
+
       - name: Test chapter 3
         working-directory: chapter3
         run: |
@@ -66,7 +69,7 @@ jobs:
           mpirun -n 2 python3 robin_neumann_dirichlet.py
           mpirun -n 2 python3 component_bc.py
           mpirun -n 2 python3 em.py
-  
+
       - name: Test chapter 4
         working-directory: chapter4
         run: |

Changelog.md

@@ -1,5 +1,10 @@
 # Changelog
 
+## v0.9.0
+
+- `scale` in `apply_lifting` has been renamed to `alpha`
+- Use `dolfinx.fem.Function.x.petsc_vec` as opposed to `dolfinx.fem.Function.vector`
+
 ## v0.8.0
 
 - Replace all `ufl.FiniteElement` and `ufl.VectorElement` with the appropriate `basix.ufl.element`

chapter2/navierstokes.md

@@ -59,7 +59,7 @@ $\langle -\nabla \cdot \sigma, v\rangle$. Just as for the [linear elasticity pro
 where $T=\sigma \cdot n$ is the boundary traction. If we solve a problem with a free boundary, we can take $T=0$ on the boundary. However, if we compute the flow through a channel or a pipe and want to model flow that continues into an "imaginary channel" at the outflow, we need to treat this term with some care. 
 The assumption we then can make is that the derivative of the velocity in the direction of the channel is zero at the outflow, corresponding to that the flow is "fully developed" or doesn't change significantly downstream at the outflow.
 Doing so, the remaining boundary term at the outflow becomes 
-$pn - \mu \nabla u \cdot n$, which is the term appearing in the variational problem [](ipcs-one). Note that this argument and the implementation depends exact on the definition of $\nabla u$, as either the  matrix with components $\frac{\partial u_i}{\partial x_j}$ or $\frac{\partial u_j}{\partial x_i}$.
+$pn - \mu \nabla u \cdot n$, which is the term appearing in the variational problem [](ipcs-one). Note that this argument and the implementation depend exactly on the definition of $\nabla u$, as either the  matrix with components $\frac{\partial u_i}{\partial x_j}$ or $\frac{\partial u_j}{\partial x_i}$.
 We here choose the  latter, $\frac{\partial u_j}{\partial x_i}$,
 which means that we must use the UFL-operator `nabla_grad`. If we use the operator `grad` and the definition $\frac{\partial u_i}{\partial x_j}$, we must instead keep the terms $pn-\mu(\nabla u)^T \cdot n$.
 

chapter2/ns_code2.ipynb

@@ -651,6 +651,7 @@
     "            if pressure is not None:\n",
     "                p_diff[i] -= pressure[0]\n",
     "                break\n",
+    "progress.close()\n",
     "vtx_u.close()\n",
     "vtx_p.close()"
    ]

chapter2/ns_code2.py

@@ -478,6 +478,7 @@ def __call__(self, x):
             if pressure is not None:
                 p_diff[i] -= pressure[0]
                 break
+progress.close()
 vtx_u.close()
 vtx_p.close()
 

chapter4/compiler_parameters.ipynb

@@ -50,7 +50,7 @@
    "id": "2",
    "metadata": {},
    "source": [
-    "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."
+    "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."
    ]
   },
   {

chapter4/compiler_parameters.py

@@ -46,7 +46,7 @@
 print(f"Directory to put C files in: {cache_dir}")
 # -
 
-# 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.
+# 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.
 
 # +
 

fem.md

@@ -40,13 +40,13 @@ The tutorial uses several dependencies for meshing, plotting and timings. A comp
 To use the notebooks in this tutorial with DOLFINx on your own computer, you should use the docker image obtained using the following command:
 
 ```bash
-  docker run --init -p 8888:8888 -v "$(pwd)":/root/shared ghcr.io/jorgensd/dolfinx-tutorial:v0.7.2
+  docker run --init -p 8888:8888 -v "$(pwd)":/root/shared ghcr.io/jorgensd/dolfinx-tutorial:release
 ```
 
 This image can also be used as a normal docker container by adding:
 
 ```bash
-  docker run --ti -v "$(pwd)":/root/shared  --entrypoint="/bin/bash" ghcr.io/jorgensd/dolfinx-tutorial:v0.7.2
+  docker run --ti -v "$(pwd)":/root/shared  --entrypoint="/bin/bash" ghcr.io/jorgensd/dolfinx-tutorial:release
 ```
 
 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.
@@ -58,7 +58,7 @@ 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 using:
 
 ```bash
-docker run dolfinx/dolfinx:v0.8.0
+docker run dolfinx/dolfinx:stable
 ```
 
 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.