remove isnothing

TuringLang · Apr 30, 2020 · c440dfd · c440dfd
1 parent 6aafa94
commit c440dfd
Show file tree

Hide file tree

Showing 2 changed files with 8 additions and 8 deletions.
diff --git a/test/sampler-vec.jl b/test/sampler-vec.jl
@@ -30,9 +30,9 @@ include("common.jl")
         n_chains = n_chains_list[i_test]
         metric = metricT((D, n_chains))
         h = Hamiltonian(metric, ℓπ, ∂ℓπ∂θ)
-        @test isnothing(show(metric))
-        @test isnothing(show(h))
-        @test isnothing(show(τ))
+        @test show(metric) == nothing
+        @test show(h) == nothing
+        @test show(τ) == nothing
         # NoAdaptation
         samples, stats = sample(h, τ, θ_init_list[i_test], n_samples; verbose=false)
         @test mean(samples) ≈ zeros(D, n_chains) atol=RNDATOL * n_chains
@@ -50,7 +50,7 @@ include("common.jl")
             ),
         ]
             τ isa HMCDA && continue
-            @test isnothing(show(adaptor))
+            @test show(adaptor) == nothing
             samples, stats = sample(h, τ, θ_init_list[i_test], n_samples, adaptor, n_adapts; verbose=false, progress=false)
             @test mean(samples) ≈ zeros(D, n_chains) atol=RNDATOL * n_chains
         end

diff --git a/test/sampler.jl b/test/sampler.jl
@@ -36,7 +36,7 @@ end
         :DiagEuclideanMetric => DiagEuclideanMetric(D),
         :DenseEuclideanMetric => DenseEuclideanMetric(D),
     )
-        @test isnothing(show(metric))
+        @test show(metric) == nothing
         h = Hamiltonian(metric, ℓπ, ∂ℓπ∂θ)
         @testset "$lfsym" for (lfsym, lf) in Dict(
             :Leapfrog => Leapfrog(ϵ),
@@ -53,8 +53,8 @@ end
                 :(NUTS{MultinomialTS,Original}) => NUTS{MultinomialTS,ClassicNoUTurn}(lf),
                 :(NUTS{MultinomialTS,Generalised}) => NUTS{MultinomialTS,GeneralisedNoUTurn}(lf),
             )
-                @test isnothing(show(h))
-                @test isnothing(show(τ))
+                @test show(h) == nothing
+                @test show(τ) == nothing
                 @testset  "NoAdaptation" begin
                     Random.seed!(1)
                     samples, stats = sample(h, τ, θ_init, n_samples; verbose=false, progress=PROGRESS)
@@ -79,7 +79,7 @@ end
                         StepSizeAdaptor(0.8, τ.integrator),
                     ),
                 )
-                    @test isnothing(show(adaptor))
+                    @test show(adaptor) == nothing
                     Random.seed!(1)
                     # For `MassMatrixAdaptor`, we use the pre-defined step size as the method cannot adapt the step size.
                     # For other adapatation methods that are able to adpat the step size, we use `find_good_stepsize`.