remove the global test option and use it locally instead

ReactiveBayes · Nov 24, 2023 · c72bd8b · c72bd8b
1 parent 94a7f7e
commit c72bd8b
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Showing 2 changed files with 6 additions and 5 deletions.
diff --git a/test/distributions/distributions_setuptests.jl b/test/distributions/distributions_setuptests.jl
@@ -58,7 +58,6 @@ function test_exponentialfamily_interface(distribution;
     test_fisherinformation_against_hessian = true,
     test_fisherinformation_against_jacobian = true,
     option_assume_no_allocations = false,
-    option_test_samples_logpdf = true
 )
     T = ExponentialFamily.exponential_family_typetag(distribution)
 
@@ -71,7 +70,7 @@ function test_exponentialfamily_interface(distribution;
     test_distribution_conversion && run_test_distribution_conversion(distribution; assume_no_allocations = option_assume_no_allocations)
     test_packing_unpacking && run_test_packing_unpacking(distribution)
     test_isproper && run_test_isproper(distribution; assume_no_allocations = option_assume_no_allocations)
-    test_basic_functions && run_test_basic_functions(distribution; assume_no_allocations = option_assume_no_allocations, test_samples_logpdf = option_test_samples_logpdf)
+    test_basic_functions && run_test_basic_functions(distribution; assume_no_allocations = option_assume_no_allocations)
     test_fisherinformation_properties && run_test_fisherinformation_properties(distribution)
     test_fisherinformation_against_hessian && run_test_fisherinformation_against_hessian(distribution; assume_no_allocations = option_assume_no_allocations)
     test_fisherinformation_against_jacobian && run_test_fisherinformation_against_jacobian(distribution; assume_no_allocations = option_assume_no_allocations)
@@ -193,7 +192,7 @@ function run_test_isproper(distribution; assume_no_allocations = true)
     end
 end
 
-function run_test_basic_functions(distribution; nsamples = 10, test_gradients = true, assume_no_allocations = true, test_samples_logpdf = true)
+function run_test_basic_functions(distribution; nsamples = 10, test_gradients = true, test_samples_logpdf = true, assume_no_allocations = true)
     T = ExponentialFamily.exponential_family_typetag(distribution)
 
     ef = @inferred(convert(ExponentialFamilyDistribution, distribution))

diff --git a/test/distributions/mv_normal_wishart_tests.jl b/test/distributions/mv_normal_wishart_tests.jl
@@ -19,11 +19,13 @@ end
         @testset let (d = MvNormalWishart(rand(dim), invS, rand(), ν))
             ef = test_exponentialfamily_interface(
                 d;
-                option_test_samples_logpdf = false, 
                 option_assume_no_allocations = false,
+                test_basic_functions = false,
                 test_fisherinformation_against_hessian = false,
-                test_fisherinformation_against_jacobian = false,
+                test_fisherinformation_against_jacobian = false
             )
+
+            run_test_basic_functions(ef; assume_no_allocations = false, test_samples_logpdf = false)
         end
     end
 end