improve coverage

Author: BatyLeo

src/DecisionFocusedLearningBenchmarks.jl

@@ -79,6 +79,7 @@ export generate_statistical_model
 export generate_maximizer
 export generate_anticipative_solver, generate_parametric_anticipative_solver
 export is_exogenous, is_endogenous
+export is_minimization_problem
 
 export objective_value
 export has_visualization, plot_instance, plot_solution, plot_trajectory, animate_trajectory

src/Ranking/Ranking.jl

@@ -32,6 +32,7 @@ function Base.show(io::IO, bench::RankingBenchmark)
 end
 
 Utils.objective_value(::RankingBenchmark, sample::DataSample, y) = dot(sample.θ, y)
+Utils.is_minimization_problem(::RankingBenchmark) = false
 
 """
 $TYPEDSIGNATURES

src/SubsetSelection/SubsetSelection.jl

@@ -33,6 +33,7 @@ function Base.show(io::IO, bench::SubsetSelectionBenchmark)
 end
 
 Utils.objective_value(::SubsetSelectionBenchmark, sample::DataSample, y) = dot(sample.θ, y)
+Utils.is_minimization_problem(::SubsetSelectionBenchmark) = false
 
 function SubsetSelectionBenchmark(; n::Int=25, k::Int=5, identity_mapping::Bool=true)
     @assert n >= k "number of items n must be greater than k"

src/Utils/Utils.jl

@@ -36,6 +36,7 @@ export generate_environment, generate_environments
 export SampleAverageApproximation
 export generate_baseline_policies
 export generate_anticipative_solver, generate_parametric_anticipative_solver
+export is_minimization_problem
 
 export has_visualization, plot_instance, plot_solution, plot_trajectory, animate_trajectory
 export compute_gap

test/contextual_stochastic_argmax.jl

@@ -78,3 +78,13 @@ end
     gap = compute_gap(saa, labeled, model, maximizer)
     @test isfinite(gap)
 end
+
+@testset "csa_objective_value_error" begin
+    using DecisionFocusedLearningBenchmarks
+
+    b = ContextualStochasticArgmaxBenchmark(; n=5, d=3, seed=0)
+    maximizer = generate_maximizer(b)
+    # Sample with neither :scenario nor :scenarios in extra → objective_value should error
+    s = DataSample(; x=randn(Float32, 8), y=maximizer(randn(Float32, 5)))
+    @test_throws Exception objective_value(b, s, s.y)
+end

test/portfolio_optimization.jl

@@ -26,4 +26,7 @@
         @test length(y) == d
         @test sum(y) <= 1 + 1e-6
     end
+
+    gap = compute_gap(b, dataset[1:5], model, maximizer)
+    @test isfinite(gap)
 end

test/ranking.jl

@@ -30,4 +30,8 @@
         y = maximizer(θ)
         @test length(y) == instance_dim
     end
+
+    gap = compute_gap(b, dataset[1:5], model, maximizer)
+    @test isfinite(gap)
+    @test gap >= 0
 end

test/subset_selection.jl

@@ -36,4 +36,8 @@
         @test length(y) == n
         @test sum(y) == k
     end
+
+    gap = compute_gap(b, dataset[1:5], model, maximizer)
+    @test isfinite(gap)
+    @test gap >= 0
 end

test/utils.jl

@@ -117,6 +117,16 @@ end
     for i in 1:N
         @test dataset_zt[i].x ≈ dataset[i].x atol = 1e-10
     end
+
+    # Error: overlap between context and extra
+    @test_throws Exception DataSample(x=[1], foo=1, extra=(; foo=2))
+    # Error: reserved name used as context kwarg
+    @test_throws Exception DataSample(x=[1], context=[2])
+    # Error: reserved name in extra
+    @test_throws Exception DataSample(x=[1], extra=(; x=[2]))
+
+    # is_minimization_problem: maximization benchmarks override to false
+    @test is_minimization_problem(ArgmaxBenchmark()) == false
 end
 
 @testset "Maximizers" begin