ci: standardize workflows using SciML's reusable workflows

.github/workflows/Documentation.yml

@@ -1,4 +1,4 @@
-name: Documentation
+name: "Documentation"
 
 on:
   push:
@@ -7,22 +7,12 @@ on:
     tags: '*'
   pull_request:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: ${{ github.ref_name != github.event.repository.default_branch || github.ref != 'refs/tags/v*' }}
+
 jobs:
-  build:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@latest
-        with:
-          version: '1'
-      - name: Install dependencies
-        run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
-      - name: Build and deploy
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # For authentication with GitHub Actions token
-          DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} # For authentication with SSH deploy key
-        run: julia --project=docs/ --code-coverage=user docs/make.jl
-      - uses: julia-actions/julia-processcoverage@v1
-      - uses: codecov/codecov-action@v4
-        with:
-          file: lcov.info
+  build-and-deploy-docs:
+    name: "Documentation"
+    uses: "SciML/.github/.github/workflows/documentation.yml@v1"
+    secrets: "inherit"

.github/workflows/FormatCheck.yml

@@ -1,42 +1,13 @@
-name: format-check
+name: "Format Check"
 
 on:
   push:
     branches:
       - 'master'
-      - 'release-'
     tags: '*'
   pull_request:
 
 jobs:
-  build:
-    runs-on: ${{ matrix.os }}
-    strategy:
-      matrix:
-        julia-version: [1]
-        julia-arch: [x86]
-        os: [ubuntu-latest]
-    steps:
-      - uses: julia-actions/setup-julia@latest
-        with:
-          version: ${{ matrix.julia-version }}
-
-      - uses: actions/checkout@v4
-      - name: Install JuliaFormatter and format
-        # This will use the latest version by default but you can set the version like so:
-        #
-        # julia  -e 'using Pkg; Pkg.add(PackageSpec(name="JuliaFormatter", version="0.13.0"))'
-        run: |
-          julia  -e 'using Pkg; Pkg.add(PackageSpec(name="JuliaFormatter"))'
-          julia  -e 'using JuliaFormatter; format(".", verbose=true)'
-      - name: Format check
-        run: |
-          julia -e '
-          out = Cmd(`git diff --name-only`) |> read |> String
-          if out == ""
-              exit(0)
-          else
-              @error "Some files have not been formatted !!!"
-              write(stdout, out)
-              exit(1)
-          end'
+  format-check:
+    name: "Format Check"
+    uses: "SciML/.github/.github/workflows/format-suggestions-on-pr.yml@v1"

.github/workflows/Invalidations.yml

@@ -1,4 +1,4 @@
-name: Invalidations
+name: "Invalidations"
 
 on:
   pull_request:
@@ -10,31 +10,6 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
-  evaluate:
-    # Only run on PRs to the default branch.
-    # In the PR trigger above branches can be specified only explicitly whereas this check should work for master, main, or any other default branch
-    if: github.base_ref == github.event.repository.default_branch
-    runs-on: ubuntu-latest
-    steps:
-    - uses: julia-actions/setup-julia@v2
-      with:
-        version: '1'
-    - uses: actions/checkout@v4
-    - uses: julia-actions/julia-buildpkg@v1
-    - uses: julia-actions/julia-invalidations@v1
-      id: invs_pr
-
-    - uses: actions/checkout@v4
-      with:
-        ref: ${{ github.event.repository.default_branch }}
-    - uses: julia-actions/julia-buildpkg@v1
-    - uses: julia-actions/julia-invalidations@v1
-      id: invs_default
-
-    - name: Report invalidation counts
-      run: |
-        echo "Invalidations on default branch: ${{ steps.invs_default.outputs.total }} (${{ steps.invs_default.outputs.deps }} via deps)" >> $GITHUB_STEP_SUMMARY
-        echo "This branch: ${{ steps.invs_pr.outputs.total }} (${{ steps.invs_pr.outputs.deps }} via deps)" >> $GITHUB_STEP_SUMMARY
-    - name: Check if the PR does increase number of invalidations
-      if: steps.invs_pr.outputs.total > steps.invs_default.outputs.total
-      run: exit 1
+  evaluate-invalidations:
+    name: "Evaluate Invalidations"
+    uses: "SciML/.github/.github/workflows/invalidations.yml@v1"

.github/workflows/Tests.yml

@@ -0,0 +1,31 @@
+name: "Tests"
+
+on:
+  pull_request:
+    branches:
+      - master
+    paths-ignore:
+      - 'docs/**'
+  push:
+    branches:
+      - master
+    paths-ignore:
+      - 'docs/**'
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: ${{ github.ref_name != github.event.repository.default_branch || github.ref != 'refs/tags/v*' }}
+
+jobs:
+  tests:
+    name: "Tests"
+    strategy:
+      fail-fast: false
+      matrix:
+        version:
+          - "1"
+          - "1.6"
+    uses: "SciML/.github/.github/workflows/tests.yml@v1"
+    with:
+      julia-version: "${{ matrix.version }}"
+    secrets: "inherit"

src/cost_functions.jl

@@ -50,14 +50,14 @@ function (f::L2Loss)(sol::DiffEqBase.AbstractNoTimeSolution)
 
     if weight == nothing
         @inbounds for i in 1:length(sol)
-            sumsq += (data[i] - sol[i])^2
+            sumsq += (data[i] - sol.u[i])^2
         end
     else
         @inbounds for i in 1:length(sol)
             if weight isa Real
-                sumsq = sumsq + ((data[i] - sol[i])^2) * weight
+                sumsq = sumsq + ((data[i] - sol.u[i])^2) * weight
             else
-                sumsq = sumsq + ((data[i] - sol[i])^2) * weight[i]
+                sumsq = sumsq + ((data[i] - sol.u[i])^2) * weight[i]
             end
         end
     end
@@ -82,11 +82,11 @@ function (f::L2Loss)(sol::SciMLBase.AbstractSciMLSolution)
 
     if weight == nothing
         @inbounds for i in 1:length(sol)
-            for j in 1:length(sol[i])
+            for j in 1:length(sol.u[i])
                 sumsq += (data[j, i] - sol[j, i])^2
             end
             if diff_weight != nothing && i != 1
-                for j in 1:length(sol[i])
+                for j in 1:length(sol.u[i])
                     if diff_weight isa Real
                         sumsq += diff_weight *
                                  ((data[j, i] - data[j, i - 1] - sol[j, i] +
@@ -102,16 +102,16 @@ function (f::L2Loss)(sol::SciMLBase.AbstractSciMLSolution)
     else
         @inbounds for i in 1:length(sol)
             if weight isa Real
-                for j in 1:length(sol[i])
+                for j in 1:length(sol.u[i])
                     sumsq = sumsq + ((data[j, i] - sol[j, i])^2) * weight
                 end
             else
-                for j in 1:length(sol[i])
+                for j in 1:length(sol.u[i])
                     sumsq = sumsq + ((data[j, i] - sol[j, i])^2) * weight[j, i]
                 end
             end
             if diff_weight != nothing && i != 1
-                for j in 1:length(sol[i])
+                for j in 1:length(sol.u[i])
                     if diff_weight isa Real
                         sumsq += diff_weight *
                                  ((data[j, i] - data[j, i - 1] - sol[j, i] +
@@ -194,7 +194,7 @@ function (f::LogLikeLoss)(sol::SciMLBase.AbstractSciMLSolution)
             # i is the number of time points
             # j is the size of the system
             # corresponds to distributions[i,j]
-            ll -= logpdf(distributions[i], sol[i])
+            ll -= logpdf(distributions[i], sol.u[i])
         end
     end
 

test/tests_on_odes/regularization_test.jl

@@ -26,8 +26,8 @@ result = solve(optprob, Optim.BFGS())
 
 optprob = Optimization.OptimizationProblem(cost_function_2, [1.2, 2.7])
 result = solve(optprob, Optim.BFGS())
-@test result.minimizer≈[1.5; 3.0] atol=3e-1
+@test result.u≈[1.5; 3.0] atol=3e-1
 
 optprob = Optimization.OptimizationProblem(cost_function_3, [1.3, 0.8, 2.8, 1.2])
 result = solve(optprob, Optim.BFGS())
-@test result.minimizer≈[1.5; 1.0; 3.0; 1.0] atol=5e-1
+@test result.u≈[1.5; 1.0; 3.0; 1.0] atol=5e-1

test/tests_on_odes/two_stage_method_test.jl

@@ -4,18 +4,18 @@ println("Use Two Stage Method to fit the parameter")
 
 cost_function = two_stage_objective(prob1, t, data)
 result = Optim.optimize(cost_function, 0.0, 10.0)
-@test result.minimizer[1]≈1.5 atol=3e-1
+@test result.u[1]≈1.5 atol=3e-1
 cost_function = two_stage_objective(prob2, t, data)
 result = Optim.optimize(cost_function, [1.0, 2.5], Optim.BFGS())
-@test result.minimizer≈[1.5; 3.0] atol=3e-1
+@test result.u≈[1.5; 3.0] atol=3e-1
 cost_function = two_stage_objective(prob3, t, data)
 result = Optim.optimize(cost_function, [1.3, 0.8, 2.8, 1.2], Optim.BFGS())
-@test result.minimizer≈[1.5; 1.0; 3.0; 1.0] atol=5e-1
+@test result.u≈[1.5; 1.0; 3.0; 1.0] atol=5e-1
 # test differentiation
 obj = two_stage_objective(prob2, t, data, Optimization.AutoForwardDiff())
 optprob = OptimizationNLopt.OptimizationProblem(obj, [1.3, 0.8])
 result = solve(optprob, Optim.ConjugateGradient())
-@test result.minimizer≈[1.5; 3.0] atol=3e-1
+@test result.u≈[1.5; 3.0] atol=3e-1
 
 obj = two_stage_objective(prob2, t, data, Optimization.AutoForwardDiff())
 opt = Opt(:LD_LBFGS, 2)