default_parameters now dispatches on Val types (#379)

docs/Project.toml

@@ -2,6 +2,7 @@
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 MetaGraphsNext = "fa8bd995-216d-47f1-8a91-f3b68fbeb377"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"

src/solve-model.jl

@@ -1,13 +1,68 @@
-export solve_model!, solve_model
+export solve_model!, solve_model, default_parameters
 
 """
+    default_parameters(Val(optimizer_name_symbol))
     default_parameters(optimizer)
+    default_parameters(optimizer_name_symbol)
+    default_parameters(optimizer_name_string)
 
 Returns the default parameters for a given JuMP optimizer.
 Falls back to `Dict()` for undefined solvers.
+
+## Arguments
+
+There are four ways to use this function:
+
+  - `Val(optimizer_name_symbol)`: This uses type dispatch with the special `Val` type.
+    Just give the solver name as a Symbol (e.g., `Val(:HiGHS)`).
+  - `optimizer`: The JuMP optimizer type (e.g., `HiGHS.Optimizer`).
+  - `optimizer_name_symbol` or `optimizer_name_string`: Just give the name in Symbol
+    or String format and we will convert to `Val`.
+
+Using `Val` is necessary for the dispatch.
+All other cases will convert the argument and call the `Val` version, which might lead to some type instability.
+
+## Examples
+
+```jldoctest
+using HiGHS
+default_parameters(HiGHS.Optimizer)
+
+# output
+
+Dict{String, Any} with 1 entry:
+  "output_flag" => false
+```
+
+This also
+
+```jldoctest
+default_parameters(Val(:SCIP))
+
+# output
+
+Dict{String, Any} with 1 entry:
+  "display/verblevel" => 0
+```
+
+```jldoctest
+default_parameters(:SCIP) == default_parameters("SCIP") == default_parameters(Val(:SCIP))
+
+# output
+
+true
+```
 """
-default_parameters(::Type{T}) where {T<:MathOptInterface.AbstractOptimizer} = Dict{String,Any}()
-default_parameters(::Type{HiGHS.Optimizer}) = Dict{String,Any}("output_flag" => false)
+default_parameters(::Any) = Dict{String,Any}()
+default_parameters(::Val{:HiGHS}) = Dict{String,Any}("output_flag" => false)
+default_parameters(::Val{:SCIP}) = Dict{String,Any}("display/verblevel" => 0)
+
+function default_parameters(::Type{T}) where {T<:MathOptInterface.AbstractOptimizer}
+    solver_name = split(string(T), ".")[1]
+    return default_parameters(Val(Symbol(solver_name)))
+end
+
+default_parameters(optimizer::Union{String,Symbol}) = default_parameters(Val(Symbol(optimizer)))
 
 """
     solution = solve_model!(energy_problem[, optimizer; parameters])

test/runtests.jl

@@ -8,9 +8,6 @@ using SCIP
 using Test
 using TulipaEnergyModel
 
-TulipaEnergyModel.default_parameters(::Type{SCIP.Optimizer}) =
-    Dict{String,Any}("display/verblevel" => 0)
-
 # Folders names
 const INPUT_FOLDER = joinpath(@__DIR__, "inputs")
 const OUTPUT_FOLDER = joinpath(@__DIR__, "outputs")

test/test-options.jl

@@ -15,9 +15,32 @@
     )
 end
 
-@testset "Test dummy solver" begin
-    struct DummySolver <: MathOptInterface.AbstractOptimizer end
-    @test TulipaEnergyModel.default_parameters(DummySolver) == Dict{String,Any}()
+@testset "Test default_parameters usage" begin
+    @testset "HiGHS" begin
+        expected = Dict{String,Any}("output_flag" => false)
+        @test default_parameters(Val(:HiGHS)) == expected
+        @test default_parameters(HiGHS.Optimizer) == expected
+        @test default_parameters(:HiGHS) == expected
+        @test default_parameters("HiGHS") == expected
+    end
+
+    @testset "Undefined values" begin
+        expected = Dict{String,Any}()
+        @test default_parameters(Val(:blah)) == expected
+        @test default_parameters(:blah) == expected
+        @test default_parameters("blah") == expected
+        struct DummySolver <: MathOptInterface.AbstractOptimizer end
+        @test default_parameters(Val(:DummySolver)) == expected
+    end
+
+    @testset "New definition" begin
+        expected = Dict{String,Any}("dummy" => true, "use" => :testing)
+        struct NewSolver <: MathOptInterface.AbstractOptimizer end
+        TulipaEnergyModel.default_parameters(::Val{:NewSolver}) = expected
+        @test TulipaEnergyModel.default_parameters(NewSolver) == expected
+        @test TulipaEnergyModel.default_parameters(:NewSolver) == expected
+        @test TulipaEnergyModel.default_parameters("NewSolver") == expected
+    end
 end
 
 @testset "Test that bad options throw errors" begin