Add more solvers (#1868)

Support most of the ones listen in https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/#Stiff-Problems
Deltares · Oct 7, 2024 · 67205d5 · 67205d5
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commit 67205d5
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diff --git a/core/src/config.jl b/core/src/config.jl
@@ -18,8 +18,8 @@ using OrdinaryDiffEqNonlinearSolve: NLNewton
 using OrdinaryDiffEqLowOrderRK: Euler, RK4
 using OrdinaryDiffEqTsit5: Tsit5
 using OrdinaryDiffEqSDIRK: ImplicitEuler, KenCarp4, TRBDF2
-using OrdinaryDiffEqBDF: QNDF
-using OrdinaryDiffEqRosenbrock: Rodas5, Rosenbrock23
+using OrdinaryDiffEqBDF: FBDF, QNDF
+using OrdinaryDiffEqRosenbrock: Rosenbrock23, Rodas4P, Rodas5P
 
 export Config, Solver, Results, Logging, Toml
 export algorithm,
@@ -213,9 +213,11 @@ Map from config string to a supported algorithm type from [OrdinaryDiffEq](https
 Supported algorithms:
 
 - `QNDF`
+- `FBDF`
 - `Rosenbrock23`
 - `TRBDF2`
-- `Rodas5`
+- `Rodas4P`
+- `Rodas5P`
 - `KenCarp4`
 - `Tsit5`
 - `RK4`
@@ -224,9 +226,11 @@ Supported algorithms:
 """
 const algorithms = Dict{String, Type}(
  "QNDF" => QNDF,
+ "FBDF" => FBDF,
  "Rosenbrock23" => Rosenbrock23,
  "TRBDF2" => TRBDF2,
- "Rodas5" => Rodas5,
+ "Rodas4P" => Rodas4P,
+ "Rodas5P" => Rodas5P,
  "KenCarp4" => KenCarp4,
  "Tsit5" => Tsit5,
  "RK4" => RK4,

diff --git a/core/test/run_models_test.jl b/core/test/run_models_test.jl
@@ -280,7 +280,7 @@ end
  @test sparse_fdm.integrator.u ≈ sparse_ad.integrator.u atol = 4
  @test dense_fdm.integrator.u ≈ sparse_ad.integrator.u atol = 4
 
- config = Ribasim.Config(toml_path; solver_algorithm = "Rodas5", solver_autodiff = true)
+ config = Ribasim.Config(toml_path; solver_algorithm = "Rodas5P", solver_autodiff = true)
  time_ad = Ribasim.run(config)
  @test successful_retcode(time_ad)
  @test time_ad.integrator.u ≈ sparse_ad.integrator.u atol = 10

diff --git a/docs/reference/usage.qmd b/docs/reference/usage.qmd
@@ -21,7 +21,7 @@ If your model does not converge, or your performance is lower than expected, it
 
 The default solver `algorithm = "QNDF"`, which is a multistep method similar to Matlab's `ode15s` [@shampine1997matlab].
 It is an implicit method that supports the default adaptive timestepping.
-The full list of available solvers is: `QNDF`, `Rosenbrock23`, `TRBDF2`, `Rodas5`, `KenCarp4`, `Tsit5`, `RK4`, `ImplicitEuler`, `Euler`.
+The full list of available solvers is: `QNDF`, `FBDF`, `Rosenbrock23`, `Rodas4P`, `Rodas5P`, `TRBDF2`, `KenCarp4`, `Tsit5`, `RK4`, `ImplicitEuler`, `Euler`.
 Information on the solver algorithms can be found on the [ODE solvers page](https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/).
 
 By default Ribasim uses adaptive timestepping, though not all algorithms support adaptive timestepping.