Update tests

Author: lhnguyen-vn

test/parameters.jl

@@ -8,7 +8,7 @@
     r4 = range(Float32, :r4; lower=-Inf, upper=Inf, origin=0, unit=1)
     rs = (r1, r2, r3, r4)
     # Test distribution types
-    Ds = (Dirichlet, Uniform, Gamma, Normal)
+    Ds = (Uniform, Gamma, Normal)
     # Manually fitted distributions for test ranges
     d1 = Dirichlet(ones(3))
     d2 = Uniform(1, 3)
@@ -28,14 +28,15 @@
     Xs = (X1, X2, X3, X4)
 
     @testset "Initializer" begin
-        for (r, D) in zip(rs, Ds)
-            @test PSO._initializer(r) === D
+        for (r, D) in zip(rs[2:end], Ds)
+            @test PSO._initializer(MLJTuning.boundedness(r)) === D
         end
     end
 
     @testset "Initialize with distribution types" begin
         rng = StableRNG(1234)
-        for (r, D, l, X) in zip(rs, Ds, lengths, Xs)
+        PSO._initialize(rng, r1, n)
+        for (r, D, l, X) in zip(rs[2:end], Ds, lengths[2:end], Xs[2:end])
             r̂, l̂, X̂ = PSO._initialize(rng, r, D, n)[[1,3,4]]
             @test r̂ === r
             @test l̂ == l
@@ -60,6 +61,7 @@
     @testset "Unsupported distributions" begin
         rng = StableRNG(1234)
         @test_throws ArgumentError PSO._initialize(rng, r1, Uniform, n)
+        @test_throws ArgumentError PSO._initialize(rng, r1, Dirichlet, n)
         @test_throws ArgumentError PSO._initialize(rng, r1, d2, n)
         @test_throws ArgumentError PSO._initialize(rng, r1, Dirichlet(ones(4)), n)
         @test_throws ArgumentError PSO._initialize(rng, r2, Dirichlet, n)

test/strategies/basic.jl

@@ -38,7 +38,7 @@ for acceleration in (CPU1(), CPUProcesses(), CPUThreads())
             acceleration=acceleration
         )
         baseline_mach = machine(baseline_self_tuning_tree, X, y)
-        fit!(baseline_mach, verbosity=2)
+        fit!(baseline_mach, verbosity=0)
         baseline_rep = report(baseline_mach)
         baseline_best_loss = baseline_rep.best_history_entry.measurement[1]
 
@@ -52,7 +52,7 @@ for acceleration in (CPU1(), CPUProcesses(), CPUThreads())
             acceleration=acceleration
         )
         mach = machine(self_tuning_tree, X, y)
-        fit!(mach, verbosity=2)
+        fit!(mach, verbosity=0)
         rep = report(mach)
         best_loss = rep.best_history_entry.measurement[1]
 

test/update.jl

@@ -30,9 +30,9 @@
         @test all(r2.lower .<= X[:, 4] .<= r2.upper)
         @test all(r3.lower .<= X[:, 5] .<= r3.upper)
         @test all(r4.lower .<= X[:, 6] .<= r4.upper)
-        @test X == [1.4861521012405697e-16 0.3306965950637089  0.6693034049362909    2.426443736254841  9.889381738850881  -0.8067647083847199;
-                    0.6561834218566733     0.17876621097030176 0.16505036717302488   3.0                3.6569395920512977 -40.736143561117814;
-                    0.11411862296972314    0.8858813770302767  1.967051803731305e-16 2.5742724788985445 1.0                 73.175744055348   ]
+        @test X ≈ [1.4861521012405697e-16 0.3306965950637089  0.6693034049362909    2.426443736254841  9.889381738850881  -0.8067647083847199;
+                   0.6561834218566733     0.17876621097030176 0.16505036717302488   3.0                3.6569395920512977 -40.736143561117814;
+                   0.11411862296972314    0.8858813770302767  1.967051803731305e-16 2.5742724788985445 1.0                 73.175744055348   ]
     end
 
     ps = ParticleSwarm(n_particles=3, rng=StableRNG(1234))
@@ -44,9 +44,9 @@
 
     @testset "Update personal best" begin
         @test state.pbest == measurements
-        @test state.pbest_X == [0.35710007620140427 0.37056803307520936 0.2723318907233864  2.7429797605672808 3.9372495283243105 -0.8067647083847199;
-                                0.471258004384426   0.3400938657534834  0.18864812986209056 2.3976392099947    3.6569395920512977  0.420991611378423 ;
-                                0.09661447846912713 0.19630556211862715 0.7070799594122457  2.5742724788985445 3.6354556967115146  0.6736019046580138]
+        @test state.pbest_X ≈ [0.35710007620140427 0.37056803307520936 0.2723318907233864  2.7429797605672808 3.9372495283243105 -0.8067647083847199;
+                               0.471258004384426   0.3400938657534834  0.18864812986209056 2.3976392099947    3.6569395920512977  0.420991611378423 ;
+                               0.09661447846912713 0.19630556211862715 0.7070799594122457  2.5742724788985445 3.6354556967115146  0.6736019046580138]
     end
 
     @testset "Update global best" begin