diff --git a/test/LMO_test.jl b/test/LMO_test.jl index d2064d7bd..35005e0fd 100644 --- a/test/LMO_test.jl +++ b/test/LMO_test.jl @@ -77,7 +77,7 @@ diffi = Random.rand(Bool, n) * 0.6 .+ 0.3 branching_strategy = Boscia.PartialStrongBranching(10, 1e-3, blmo) x, _, result = - Boscia.solve(f, grad!, blmo, verbose=true, branching_strategy=branching_strategy) + Boscia.solve(f, grad!, blmo, branching_strategy=branching_strategy) @test x == round.(diffi) @test isapprox(f(x), f(result[:raw_solution]), atol=1e-6, rtol=1e-3) @@ -95,10 +95,8 @@ diffi = Random.rand(Bool, n) * 0.6 .+ 0.3 end branching_strategy = Boscia.HybridStrongBranching(10, 1e-3, blmo, perform_strong_branch) - branching_strategy = Boscia.PartialStrongBranching(10, 1e-3, blmo, branching_strategy=branching_strategy) - x, _, result = - Boscia.solve(f, grad!, blmo, verbose=true) + Boscia.solve(f, grad!, blmo, branching_strategy=branching_strategy) @test x == round.(diffi) @test isapprox(f(x), f(result[:raw_solution]), atol=1e-6, rtol=1e-3) diff --git a/test/interface_test.jl b/test/interface_test.jl index bd1c108a0..f97fe14a3 100644 --- a/test/interface_test.jl +++ b/test/interface_test.jl @@ -97,7 +97,7 @@ end sblmo = Boscia.CubeSimpleBLMO(lbs, ubs, int_vars) x, _, result = - Boscia.solve(f, grad!, sblmo, lbs[int_vars], ubs[int_vars], int_vars, n, verbose=true) + Boscia.solve(f, grad!, sblmo, lbs[int_vars], ubs[int_vars], int_vars, n) @test x == round.(diffi) @test isapprox(f(x), f(result[:raw_solution]), atol=1e-6, rtol=1e-3) @@ -110,7 +110,7 @@ end sblmo = Boscia.CubeSimpleBLMO(lbs, ubs, int_vars) x, _, result = - Boscia.solve(f, grad!, sblmo, lbs[int_vars], ubs[int_vars], int_vars, n, verbose=true, use_shadow_set=false) + Boscia.solve(f, grad!, sblmo, lbs[int_vars], ubs[int_vars], int_vars, n, use_shadow_set=false) @test x == round.(diffi) @test isapprox(f(x), f(result[:raw_solution]), atol=1e-6, rtol=1e-3)