Use OrdinaryDiffEqRosenbrock.jl (#108)

* use OrdinaryDiffEqRosenbrock * add compat bound for OrdinaryDiffEqRosenbrock * bump compat of SciMLBase * also use OrdinaryDiffEqNonlinearSolve * document need of OrdinaryDiffEqNonlinearSolve.jl * fix typo * import OrdinaryDiffEqNonlinearSolve in tests * bump compat bounds of OrdinaryDiffEq* * run Downgrade on Julia 1.11
JoshuaLampert · Dec 4, 2024 · 52afbf6 · 52afbf6
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diff --git a/.github/workflows/Downgrade.yml b/.github/workflows/Downgrade.yml
@@ -33,7 +33,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.10'
+          - '1.11'
           # - '~1.9.0-0' # including development versions
           # - 'nightly'
         os:

diff --git a/Project.toml b/Project.toml
@@ -37,7 +37,7 @@ Random = "1"
 ReadVTK = "0.2"
 RecipesBase = "1.3.4"
 Reexport = "1.2"
-SciMLBase = "2.26"
+SciMLBase = "2.56"
 SimpleUnPack = "1.1"
 SpecialFunctions = "2"
 StaticArrays = "1.9"

diff --git a/README.md b/README.md
@@ -38,7 +38,8 @@ julia> Pkg.add("Plots")
 
 To create special node sets, you might also want to install [QuasiMonteCarlo.jl](https://github.com/SciML/QuasiMonteCarlo.jl) or
 [Meshes.jl](https://github.com/JuliaGeometry/Meshes.jl) and for solving time-dependent partial differential equations
-[OrdinaryDiffEq.jl](https://github.com/SciML/OrdinaryDiffEq.jl) in a similar way as above for Plots.jl. See the documentation for more
+[OrdinaryDiffEq.jl](https://github.com/SciML/OrdinaryDiffEq.jl) in a similar way as above for Plots.jl. Consider using the subpackage
+OrdinaryDiffEqRosenbrock.jl as it contains the most relevant time integration schemes for this package. See the documentation for more
 examples on how to use these packages in combination with KernelInterpolation.jl.
 
 ## Usage

diff --git a/docs/src/development.md b/docs/src/development.md
@@ -19,7 +19,7 @@ cd KernelInterpolation.jl
 mkdir run
 cd run
 julia --project=. -e 'using Pkg; Pkg.develop(PackageSpec(path=".."))' # Install local KernelInterpolation.jl clone
-julia --project=. -e 'using Pkg; Pkg.add(["Plots", "QuasiMonteCarlo", "Meshes", "OrdinaryDiffEq"])' # Install additional packages
+julia --project=. -e 'using Pkg; Pkg.add(["Plots", "QuasiMonteCarlo", "Meshes", "OrdinaryDiffEqRosenbrock", "OrdinaryDiffEqNonlinearSolve"])' # Install additional packages
 ```
 
 If you use other packages for executing KernelInterpolation.jl, you can add them to the project in the `run`

diff --git a/docs/src/index.md b/docs/src/index.md
@@ -38,7 +38,8 @@ julia> Pkg.add("Plots")
 
 To create special node sets, you might also want to install [QuasiMonteCarlo.jl](https://github.com/SciML/QuasiMonteCarlo.jl) or
 [Meshes.jl](https://github.com/JuliaGeometry/Meshes.jl) and for solving time-dependent partial differential equations
-[OrdinaryDiffEq.jl](https://github.com/SciML/OrdinaryDiffEq.jl) in a similar way as above for Plots.jl. See the documentation for more
+[OrdinaryDiffEq.jl](https://github.com/SciML/OrdinaryDiffEq.jl) in a similar way as above for Plots.jl. Consider using the subpackage
+OrdinaryDiffEqRosenbrock.jl as it contains the most relevant time integration schemes for this package. See the documentation for more
 examples on how to use these packages in combination with KernelInterpolation.jl.
 
 ## Usage

diff --git a/docs/src/pdes.md b/docs/src/pdes.md
@@ -226,6 +226,9 @@ which already provides a wide range of time integration methods. Note that this
 system, which is more difficult to solve than a simple ODE system. Thus, we are restricted to specialized time integration
 methods, which can handle DAEs. We recommend using the `Rodas5P` method, which is a Rosenbrock method for stiff DAEs. See
 also the [documentation of OrdinaryDiffEq.jl](https://docs.sciml.ai/DiffEqDocs/latest/tutorials/dae_example/) for more information.
+`Rodas5P` along with other Rosenbrock methods are implemented in the subpackage OrdinaryDiffEqRosenbrock.jl. Therefore, we
+recommend using this package in combination with KernelInterpolation.jl to reduce precompile time. In order to solve DAEs with
+OrdinaryDiffEqRosenbrock.jl, we also need to import the subpackage OrdinaryDiffEqNonlinearSolve.jl.
 
 In KernelInterpolation.jl, you can use the constructor of a [`Semidiscretization`](@ref) in a very similar way as
 [`SpatialDiscretization`](@ref), but with the additional initial condition. This can be turned into an `ODEProblem` object

diff --git a/examples/PDEs/advection_1d_basic.jl b/examples/PDEs/advection_1d_basic.jl
@@ -1,5 +1,5 @@
 using KernelInterpolation
-using OrdinaryDiffEq
+using OrdinaryDiffEqRosenbrock, OrdinaryDiffEqNonlinearSolve
 using Plots
 
 # source term of advection equation

diff --git a/examples/PDEs/advection_3d_basic.jl b/examples/PDEs/advection_3d_basic.jl
@@ -1,5 +1,5 @@
 using KernelInterpolation
-using OrdinaryDiffEq
+using OrdinaryDiffEqRosenbrock, OrdinaryDiffEqNonlinearSolve
 using LinearAlgebra: norm
 using WriteVTK: WriteVTK, paraview_collection
 

diff --git a/examples/PDEs/advection_diffusion_2d_basic.jl b/examples/PDEs/advection_diffusion_2d_basic.jl
@@ -1,5 +1,5 @@
 using KernelInterpolation
-using OrdinaryDiffEq
+using OrdinaryDiffEqRosenbrock, OrdinaryDiffEqNonlinearSolve
 using LinearAlgebra: norm
 using Plots
 

diff --git a/examples/PDEs/heat_2d_basic.jl b/examples/PDEs/heat_2d_basic.jl
@@ -1,5 +1,5 @@
 using KernelInterpolation
-using OrdinaryDiffEq
+using OrdinaryDiffEqRosenbrock, OrdinaryDiffEqNonlinearSolve
 using Plots
 
 # right-hand-side of Heat equation

diff --git a/examples/PDEs/heat_2d_manufactured.jl b/examples/PDEs/heat_2d_manufactured.jl
@@ -1,5 +1,5 @@
 using KernelInterpolation
-using OrdinaryDiffEq
+using OrdinaryDiffEqRosenbrock, OrdinaryDiffEqNonlinearSolve
 using Plots
 
 # right-hand-side of heat equation

diff --git a/test/Project.toml b/test/Project.toml
@@ -3,7 +3,8 @@ Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 ExplicitImports = "7d51a73a-1435-4ff3-83d9-f097790105c7"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Meshes = "eacbb407-ea5a-433e-ab97-5258b1ca43fa"
-OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+OrdinaryDiffEqNonlinearSolve = "127b3ac7-2247-4354-8eb6-78cf4e7c58e8"
+OrdinaryDiffEqRosenbrock = "43230ef6-c299-4910-a778-202eb28ce4ce"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 QuasiMonteCarlo = "8a4e6c94-4038-4cdc-81c3-7e6ffdb2a71b"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
@@ -18,7 +19,8 @@ Aqua = "0.8.3"
 ExplicitImports = "1.0.1"
 LinearAlgebra = "1"
 Meshes = "0.52.1"
-OrdinaryDiffEq = "6.68"
+OrdinaryDiffEqNonlinearSolve = "1.3"
+OrdinaryDiffEqRosenbrock = "1.3"
 Plots = "1.25.11"
 QuasiMonteCarlo = "0.3.1"
 Random = "1"

diff --git a/test/runtests.jl b/test/runtests.jl
@@ -9,7 +9,8 @@ end
 
 @testsnippet AdditionalImports begin
     using LinearAlgebra: norm, Symmetric, I
-    using OrdinaryDiffEq: solve, Rodas5P
+    using OrdinaryDiffEqRosenbrock: solve, Rodas5P
+    import OrdinaryDiffEqNonlinearSolve
     using StaticArrays: MVector
     using Meshes: Meshes, Sphere, Point, PointSet, RegularSampling
 end