Use StableRNGs.jl in tests (#294)

Author: eliascarv

test/Project.toml

@@ -11,6 +11,7 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 PairPlots = "43a3c2be-4208-490b-832a-a21dcd55d7da"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ReferenceTests = "324d217c-45ce-50fc-942e-d289b448e8cf"
+StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"

test/data/eigenanalysis-1.png

@@ -10,9 +10,9 @@ using StatsBase
 using Statistics
 using DelimitedFiles
 using ReferenceTests
+using StableRNGs
 using PairPlots
 using ImageIO
-using Random
 using Test
 
 import CairoMakie as Mke
@@ -30,9 +30,8 @@ islinux = Sys.islinux()
 visualtests = !isCI || (isCI && islinux)
 datadir = joinpath(@__DIR__, "data")
 
-# using MersenneTwister for backward
-# compatibility with old Julia versions
-rng = MersenneTwister(42)
+# using StableRNG for compatibility between Julia versions
+rng = StableRNG(42)
 
 # for functor tests in Functional testset
 struct Polynomial{T<:Real}

test/data/eigenanalysis-2.png

@@ -143,7 +143,7 @@
     ├─ weights: nothing
     ├─ replace: false
     ├─ ordered: true
-    └─ rng: TaskLocalRNG()"""
+    └─ rng: Random.TaskLocalRNG()"""
   end
 
   @testset "Filter" begin

test/data/projectionpursuit-1.png

@@ -2,8 +2,8 @@
   @test TT.parameters(EigenAnalysis(:V)) == (proj=:V, maxdim=nothing, pratio=1.0)
 
   # PCA test
-  x = rand(Normal(0, 10), 1500)
-  y = x + rand(Normal(0, 2), 1500)
+  x = rand(rng, Normal(0, 10), 1500)
+  y = x + rand(rng, Normal(0, 2), 1500)
   t = Table(; x, y)
   T = EigenAnalysis(:V)
   n, c = apply(T, t)
@@ -16,8 +16,8 @@
   @test Tables.matrix(t) ≈ Tables.matrix(tₒ)
 
   # DRS test
-  x = rand(Normal(0, 10), 1500)
-  y = x + rand(Normal(0, 2), 1500)
+  x = rand(rng, Normal(0, 10), 1500)
+  y = x + rand(rng, Normal(0, 2), 1500)
   t = Table(; x, y)
   T = EigenAnalysis(:VD)
   n, c = apply(T, t)
@@ -30,8 +30,8 @@
   @test Tables.matrix(t) ≈ Tables.matrix(tₒ)
 
   # SDS test
-  x = rand(Normal(0, 10), 1500)
-  y = x + rand(Normal(0, 2), 1500)
+  x = rand(rng, Normal(0, 10), 1500)
+  y = x + rand(rng, Normal(0, 2), 1500)
   t = Table(; x, y)
   T = EigenAnalysis(:VDV)
   n, c = apply(T, t)
@@ -73,8 +73,8 @@
   end
 
   # row table
-  x = rand(Normal(0, 10), 1500)
-  y = x + rand(Normal(0, 2), 1500)
+  x = rand(rng, Normal(0, 10), 1500)
+  y = x + rand(rng, Normal(0, 2), 1500)
   t = Table(; x, y)
   rt = Tables.rowtable(t)
   T = EigenAnalysis(:V)
@@ -84,9 +84,9 @@
   @test Tables.matrix(rt) ≈ Tables.matrix(rtₒ)
 
   # maxdim
-  x = randn(1000)
-  y = x + randn(1000)
-  z = 2x - y + randn(1000)
+  x = randn(rng, 1000)
+  y = x + randn(rng, 1000)
+  z = 2x - y + randn(rng, 1000)
   t = Table(; x, y, z)
 
   # PCA

test/data/projectionpursuit-2.png

@@ -104,7 +104,7 @@
   @test Tables.isrowtable(n)
 
   # performance tests
-  trng = MersenneTwister(2) # test rng
+  trng = StableRNG(2) # test rng
   x = rand(trng, 100_000)
   y = rand(trng, 100_000)
   c = CoDaArray((a=rand(trng, 100_000), b=rand(trng, 100_000), c=rand(trng, 100_000)))