Fix typo in testing of infeasible parameters

test/runtests.jl

@@ -15,7 +15,7 @@ using FiniteDiff: FiniteDiff
     lower_bounds = [-Inf, -Inf, 0, 0]
     upper_bounds = [Inf, Inf, Inf, Inf]
     problem = ParametricMCPs.ParametricMCP(f, lower_bounds, upper_bounds, parameter_dimension)
-    problem_no_jacobian = ParametricMCPs.ParametricMCP(f, lower_bounds, upper_bounds, parameter_dimension; compute_sensitivities = false)
+    problem_no_jacobian = ParametricMCPs.ParametricMCP(f, lower_bounds, upper_bounds, parameter_dimension; compute_sensitivities=false)
 
     feasible_parameters = [[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [rand(rng, 2) for _ in 1:10]...]
     infeasible_parameters = -feasible_parameters
@@ -26,7 +26,7 @@ using FiniteDiff: FiniteDiff
             @test solution.z[1:2] ≈ θ
         end
 
-        for θ in feasible_parameters
+        for θ in infeasible_parameters
             solution = ParametricMCPs.solve(problem, θ)
             @test norm(solution.z[1:2] - θ) <= norm(θ)
         end
@@ -42,17 +42,17 @@ using FiniteDiff: FiniteDiff
             ∇_autodiff_reverse = only(Zygote.gradient(dummy_pipeline, θ))
             ∇_autodiff_forward = only(Zygote.gradient(θ -> Zygote.forwarddiff(dummy_pipeline, θ), θ))
             ∇_finitediff = FiniteDiff.finite_difference_gradient(dummy_pipeline, θ)
-            @test isapprox(∇_autodiff_reverse, ∇_finitediff; atol = 1e-4)
-            @test isapprox(∇_autodiff_reverse, ∇_autodiff_forward; atol = 1e-4)
+            @test isapprox(∇_autodiff_reverse, ∇_finitediff; atol=1e-4)
+            @test isapprox(∇_autodiff_reverse, ∇_autodiff_forward; atol=1e-4)
         end
-    end   
-    
+    end
+
     @testset "missing jacobian" begin
         function dummy_pipeline(θ, problem)
             solution = ParametricMCPs.solve(problem, θ)
             sum(solution.z .^ 2)
         end
 
         @test_throws ArgumentError Zygote.gradient(θ -> dummy_pipeline(θ, problem_no_jacobian), feasible_parameters[1])
-    end 
+    end
 end