Add more tests

Author: ymtoo

test/runtests.jl

@@ -3,34 +3,37 @@ using Test, Random, Distributions
 
 @testset "AlphaStableDistributions.jl" begin
 
-    for α in 0.6:0.1:2
-        d1 = AlphaStable(α=α)
-        s = rand(d1, 100000)
+    stabletypes = [AlphaStable,SymmetricAlphaStable]
+    αs = [0.6:0.1:2,1:0.1:2]
+    for (i, stabletype) in enumerate(stabletypes)
+        for α in αs[i]
+            d1 = AlphaStable(α=α)
+            s = rand(d1, 100000)
 
-        d2 = fit(AlphaStable, s)
+            d2 = fit(stabletype, s)
 
-        @test d1.α ≈ d2.α rtol=0.1
-        @test d1.β ≈ d2.β atol=0.2
-        @test d1.scale ≈ d2.scale rtol=0.1
-        @test d1.location ≈ d2.location atol=0.1
-    end
+            @test d1.α ≈ d2.α rtol=0.1
+            stabletype != SymmetricAlphaStable && @test d1.β ≈ d2.β atol=0.2
+            @test d1.scale ≈ d2.scale rtol=0.1
+            @test d1.location ≈ d2.location atol=0.1
+        end
 
-    xnormal = rand(Normal(3.0, 4.0), 96000)
-    d = fit(AlphaStable, xnormal)
-    @test d.α ≈ 2 rtol=0.2
-    @test d.β ≈ 0 atol=0.2
-    @test d.scale ≈ 4/√2 rtol=0.2
-    @test d.location ≈ 3 rtol=0.1
+        xnormal = rand(Normal(3.0, 4.0), 96000)
+        d = fit(stabletype, xnormal)
+        @test d.α ≈ 2 rtol=0.2
+        stabletype != SymmetricAlphaStable && @test d.β ≈ 0 atol=0.2
+        @test d.scale ≈ 4/√2 rtol=0.2
+        @test d.location ≈ 3 rtol=0.1
 
-    xcauchy = rand(Cauchy(3.0, 4.0), 96000)
-    d = fit(AlphaStable, xcauchy)
-    @test d.α ≈ 1 rtol=0.2
-    @test d.β ≈ 0 atol=0.2
-    @test d.scale ≈ 4 rtol=0.2
-    @test d.location ≈ 3 rtol=0.1
+        xcauchy = rand(Cauchy(3.0, 4.0), 96000)
+        d = fit(stabletype, xcauchy)
+        @test d.α ≈ 1 rtol=0.2
+        @test d.β ≈ 0 atol=0.2
+        @test d.scale ≈ 4 rtol=0.2
+        @test d.location ≈ 3 rtol=0.1
+    end
 
     for α in 1.1:0.1:1.9
-
         d = AlphaSubGaussian(n=96000, α=α)
         x = rand(d)
         x2 = copy(x)