Fixate dependency versions

.github/workflows/check_and_test_package.yml

@@ -11,15 +11,15 @@ on:
     - cron: '0 8 * * *'
 
 env:
-  CACHE_NUMBER: 11 # Increase to reset cache
+  CACHE_NUMBER: 12 # Increase to reset cache
 
 jobs:
   check-code:
     name: Check code
     runs-on: ubuntu-latest
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v3
       - uses: actions/setup-python@v5
         with:
           python-version: '3.8'
@@ -48,11 +48,13 @@ jobs:
     defaults:
       run: # https://github.com/marketplace/actions/setup-miniconda#use-a-default-shell
         shell: bash -l {0}
+
     steps:
       - uses: actions/checkout@v3
       - uses: actions/setup-python@v5
         with:
           python-version: '3.8'
+
       - name: Setup and install with Mambaforge
         uses: conda-incubator/setup-miniconda@v2
         with:
@@ -63,19 +65,20 @@ jobs:
           use-mamba: true
           environment-file: environment-test.yml
         id: mamba
-      - uses: actions/cache@v2
+
+      - uses: actions/cache@v3
         with:
           path: ${{ matrix.prefix }}
-          key: ${{ matrix.label }}-${{ github.run_id }}-${{ env.CACHE_NUMBER }}
-          restore-keys: ${{ matrix.label }}-
+          key: ${{ matrix.label }}-${{ env.CACHE_NUMBER }}-${{ hashFiles('environment-test.yml') }}
+          restore-keys: ${{ matrix.label }}-${{ env.CACHE_NUMBER }}-
+
       - run: mamba env update -n vampy -f environment-test.yml
-        if: steps.cache.outputs.cache-hit != 'true'
 
       - name: Install VaMPy
-        run: python -m pip install .[test]
+        run: mamba run -n vampy python -m pip install '.[test]'
 
       - name: Run tests
-        run: python -m pytest tests
+        run: mamba run -n vampy python -m pytest tests
 
       - name: Upload coverage report to Codecov
         if: matrix.os == 'ubuntu-latest'

.github/workflows/deploy_pages.yml

@@ -62,7 +62,7 @@ jobs:
         run: pip install -r requirements.txt
 
       - name: Install VaMPy
-        run: python3 -m pip install .[test]
+        run: python3 -m pip install '.[test]'
 
         # Build the book
       - name: Build the book

environment-test.yml

@@ -6,13 +6,12 @@ channels:
 dependencies:
   - fenics
   - morphman
-  - paramiko
-  - pip
-  - git
   - python >=3.8
-  - expat==2.5 # Hotfix for https://gitlab.archlinux.org/archlinux/packaging/packages/paraview/-/issues/4
+  - pip==24.2
   - pip:
       - matplotlib
-      - scipy
-      - cppimport
+      - scipy==1.14.1
+      - numpy==1.24.4
+      - cppimport==22.8.2
+      - paramiko==3.4.1
       - git+https://github.com/KVSlab/OasisMove

environment.yml

@@ -6,12 +6,12 @@ channels:
 dependencies:
   - fenics
   - morphman
-  - paramiko
-  - pip
-  - git
   - python >=3.8
-  - expat==2.5 # Hotfix for https://gitlab.archlinux.org/archlinux/packaging/packages/paraview/-/issues/4
+  - pip==24.2
   - pip:
-      - scipy
-      - cppimport
+      - matplotlib
+      - scipy==1.14.1
+      - numpy==1.24.4
+      - cppimport==22.8.2
+      - paramiko==3.4.1
       - git+https://github.com/mikaem/Oasis

requirements.txt

@@ -1,8 +1,8 @@
 jupyter-book
-matplotlib
-numpy
 ghp-import
-cppimport
-scipy
 sphinx==5.3.0
 docutils==0.17.1
+matplotlib==3.9.2
+numpy==1.24.4
+cppimport==3.4.1
+scipy==1.14.1

src/vampy/automatedPostprocessing/compute_flow_and_simulation_metrics.py

@@ -334,6 +334,7 @@ def define_functions_and_iterate_dataset(time_to_average, dataset, dataset_avg,
         print("=" * 10, "Starting post processing", "=" * 10)
 
     counter = 0
+    tolerance = 1E-12
     for data, data_avg in zip(dataset, dataset_avg):
         counter += 1
 
@@ -402,14 +403,14 @@ def define_functions_and_iterate_dataset(time_to_average, dataset, dataset_avg,
 
         # Compute length scale
         t0 = Timer("Length scale")
-        length_scale.vector().set_local((nu ** 3 / eps) ** (1. / 4))
+        length_scale.vector().set_local((nu ** 3 / (eps + tolerance)) ** (1. / 4))
         length_scale.vector().apply("insert")
         length_scale_cycle_avg.vector().axpy(1, length_scale.vector())
         t0.stop()
 
         # Compute time scale
         t0 = Timer("Time scale")
-        time_scale.vector().set_local((nu / eps) ** 0.5)
+        time_scale.vector().set_local((nu / (eps + tolerance)) ** 0.5)
         time_scale.vector().apply("insert")
         time_scale_cycle_avg.vector().axpy(1, time_scale.vector())
         t0.stop()