diff --git a/test/1_test_sim_model.jl b/test/1_test_sim_model.jl index d054a3a02..a976595da 100644 --- a/test/1_test_sim_model.jl +++ b/test/1_test_sim_model.jl @@ -108,11 +108,11 @@ end u, d = [10, 50], Float64[] @test updatestate!(linmodel1, u) ≈ zeros(2) @test updatestate!(linmodel1, u, d) ≈ zeros(2) - @test_skip @allocations(updatestate!(linmodel1, u)) == 0 + @test @allocations(updatestate!(linmodel1, u)) == 0 @test linmodel1.x0 ≈ zeros(2) @test evaloutput(linmodel1) ≈ linmodel1() ≈ [50,30] @test evaloutput(linmodel1, Float64[]) ≈ linmodel1(Float64[]) ≈ [50,30] - @test_skip @allocations(evaloutput(linmodel1)) == 0 + @test @allocations(evaloutput(linmodel1)) == 0 x = initstate!(linmodel1, [10, 60]) @test evaloutput(linmodel1) ≈ [50 + 19.0, 30 + 7.4] @test preparestate!(linmodel1) ≈ x # new method @@ -283,11 +283,11 @@ end u, d = zeros(2), Float64[] @test updatestate!(nonlinmodel, u) ≈ zeros(2) @test updatestate!(nonlinmodel, u, d) ≈ zeros(2) - @test_skip @allocations(updatestate!(nonlinmodel, u)) == 0 + @test @allocations(updatestate!(nonlinmodel, u)) == 0 @test nonlinmodel.x0 ≈ zeros(2) @test evaloutput(nonlinmodel) ≈ nonlinmodel() ≈ zeros(2) @test evaloutput(nonlinmodel, d) ≈ nonlinmodel(Float64[]) ≈ zeros(2) - @test_skip @allocations(evaloutput(nonlinmodel)) == 0 + @test @allocations(evaloutput(nonlinmodel)) == 0 x = initstate!(nonlinmodel, [0, 10]) # do nothing for NonLinModel @test evaloutput(nonlinmodel) ≈ [0, 0] @@ -387,7 +387,7 @@ end # return nothing (see this issue : https://github.com/JuliaLang/julia/issues/51112): linearize2!(linmodel, model) = (linearize!(linmodel, model); nothing) linearize2!(linmodel4, nonlinmodel4) - @test_skip @allocations(linearize2!(linmodel4, nonlinmodel4)) == 0 + @test @allocations(linearize2!(linmodel4, nonlinmodel4)) == 0 end @testitem "NonLinModel real time simulations" setup=[SetupMPCtests] begin diff --git a/test/2_test_state_estim.jl b/test/2_test_state_estim.jl index 995d96781..c1b42f42c 100644 --- a/test/2_test_state_estim.jl +++ b/test/2_test_state_estim.jl @@ -71,12 +71,12 @@ end preparestate!(manual1, y) @test updatestate!(manual1, u, y, d) ≈ zeros(4) @test manual1.x̂0 ≈ zeros(4) - @test_skip @allocations(preparestate!(manual1, y)) == 0 - @test_skip @allocations(updatestate!(manual1, u, y)) == 0 + @test @allocations(preparestate!(manual1, y)) == 0 + @test @allocations(updatestate!(manual1, u, y)) == 0 preparestate!(manual1, y) @test evaloutput(manual1) ≈ manual1() ≈ [50, 30] @test evaloutput(manual1, d) ≈ manual1(d) ≈ [50, 30] - @test_skip @allocations(evaloutput(manual1, d)) == 0 + @test @allocations(evaloutput(manual1, d)) == 0 @test initstate!(manual1, [10, 50], [50, 30+1]) ≈ [zeros(3); [1]] linmodel2 = LinModel(append(tf(1, [1, 0]), tf(2, [10, 1])), 1.0) manual2 = SteadyKalmanFilter(linmodel2, nint_u=[1, 1], direct=false) @@ -205,12 +205,12 @@ end preparestate!(kalmanfilter1, y) @test updatestate!(kalmanfilter1, u, y, d) ≈ zeros(4) @test kalmanfilter1.x̂0 ≈ zeros(4) - @test_skip @allocations(preparestate!(kalmanfilter1, y)) == 0 - @test_skip @allocations(updatestate!(kalmanfilter1, u, y)) == 0 + @test @allocations(preparestate!(kalmanfilter1, y)) == 0 + @test @allocations(updatestate!(kalmanfilter1, u, y)) == 0 preparestate!(kalmanfilter1, y) @test evaloutput(kalmanfilter1) ≈ kalmanfilter1() ≈ [50, 30] @test evaloutput(kalmanfilter1, d) ≈ kalmanfilter1(d) ≈ [50, 30] - @test_skip @allocations(evaloutput(kalmanfilter1, d)) == 0 + @test @allocations(evaloutput(kalmanfilter1, d)) == 0 @test initstate!(kalmanfilter1, [10, 50], [50, 30+1]) ≈ [zeros(3); [1]] setstate!(kalmanfilter1, [1,2,3,4], diagm(.1:.1:.4)) @test kalmanfilter1.x̂0 ≈ [1,2,3,4] @@ -326,12 +326,12 @@ end preparestate!(lo1, y) @test updatestate!(lo1, u, y, d) ≈ zeros(4) @test lo1.x̂0 ≈ zeros(4) - @test_skip @allocations(preparestate!(lo1, y)) == 0 - @test_skip @allocations(updatestate!(lo1, u, y)) == 0 + @test @allocations(preparestate!(lo1, y)) == 0 + @test @allocations(updatestate!(lo1, u, y)) == 0 preparestate!(lo1, y) @test evaloutput(lo1) ≈ lo1() ≈ [50, 30] @test evaloutput(lo1, d) ≈ lo1(d) ≈ [50, 30] - @test_skip @allocations(evaloutput(lo1, d)) == 0 + @test @allocations(evaloutput(lo1, d)) == 0 @test initstate!(lo1, [10, 50], [50, 30+1]) ≈ [zeros(3); [1]] setstate!(lo1, [1,2,3,4]) @test lo1.x̂0 ≈ [1,2,3,4] @@ -457,11 +457,11 @@ end @test updatestate!(internalmodel1, u, y, d) ≈ zeros(2) @test internalmodel1.x̂d ≈ internalmodel1.x̂0 ≈ zeros(2) @test internalmodel1.x̂s ≈ ones(2) - @test_skip @allocations(preparestate!(internalmodel1, y)) == 0 - @test_skip @allocations(updatestate!(internalmodel1, u, y)) == 0 + @test @allocations(preparestate!(internalmodel1, y)) == 0 + @test @allocations(updatestate!(internalmodel1, u, y)) == 0 preparestate!(internalmodel1, y) @test evaloutput(internalmodel1, d) ≈ [51,31] - @test_skip @allocations(evaloutput(internalmodel1, d)) == 0 + @test @allocations(evaloutput(internalmodel1, d)) == 0 @test initstate!(internalmodel1, [10, 50], [50, 30]) ≈ zeros(2) @test internalmodel1.x̂s ≈ zeros(2) setstate!(internalmodel1, [1,2]) @@ -593,12 +593,12 @@ end preparestate!(ukf1, y) @test updatestate!(ukf1, u, y, d) ≈ zeros(4) atol=1e-9 @test ukf1.x̂0 ≈ zeros(4) atol=1e-9 - @test_skip @allocations(preparestate!(ukf1, y)) == 0 - @test_skip @allocations(updatestate!(ukf1, u, y)) == 0 + @test @allocations(preparestate!(ukf1, y)) == 0 + @test @allocations(updatestate!(ukf1, u, y)) == 0 preparestate!(ukf1, y) @test evaloutput(ukf1) ≈ ukf1() ≈ [50, 30] @test evaloutput(ukf1, d) ≈ ukf1(d) ≈ [50, 30] - @test_skip @allocations(evaloutput(ukf1, d)) == 0 + @test @allocations(evaloutput(ukf1, d)) == 0 @test initstate!(ukf1, [10, 50], [50, 30+1]) ≈ zeros(4) atol=1e-9 setstate!(ukf1, [1,2,3,4], diagm(.1:.1:.4)) @test ukf1.x̂0 ≈ [1,2,3,4] @@ -752,12 +752,12 @@ end preparestate!(ekf1, y) @test updatestate!(ekf1, u, y, d) ≈ zeros(4) atol=1e-9 @test ekf1.x̂0 ≈ zeros(4) atol=1e-9 - @test_skip @allocations(preparestate!(ekf1, y)) == 0 - @test_skip @allocations(updatestate!(ekf1, u, y)) == 0 + @test @allocations(preparestate!(ekf1, y)) == 0 + @test @allocations(updatestate!(ekf1, u, y)) == 0 preparestate!(ekf1, y) @test evaloutput(ekf1) ≈ ekf1() ≈ [50, 30] @test evaloutput(ekf1, d) ≈ ekf1(d) ≈ [50, 30] - @test_skip @allocations(evaloutput(ekf1, d)) == 0 + @test @allocations(evaloutput(ekf1, d)) == 0 @test initstate!(ekf1, [10, 50], [50, 30+1]) ≈ zeros(4); setstate!(ekf1, [1,2,3,4], diagm(.1:.1:.4)) @test ekf1.x̂0 ≈ [1,2,3,4] diff --git a/test/3_test_predictive_control.jl b/test/3_test_predictive_control.jl index a24d7d088..c353017d1 100644 --- a/test/3_test_predictive_control.jl +++ b/test/3_test_predictive_control.jl @@ -496,7 +496,7 @@ end @test u ≈ [1] atol=1e-2 u = mpc1(r) @test u ≈ [1] atol=1e-2 - @test_skip @allocations(moveinput!(mpc1, r)) == 0 + @test @allocations(moveinput!(mpc1, r)) == 0 info = getinfo(mpc1) @test info[:u] ≈ u @test info[:Ŷ][end] ≈ r[1] atol=1e-2