tests: explicit random seed

Project.toml

@@ -12,7 +12,8 @@ julia = "1.6"
 MKL_jll = "2022.2.0, 2023.0.0"
 
 [extras]
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test"]
+test = ["Test", "Random"]

test/test_BLAS.jl

@@ -1,5 +1,5 @@
 using MKLSparse
-using Test, SparseArrays, LinearAlgebra
+using Test, Random, SparseArrays, LinearAlgebra
 
 # evaluates ex and checks whether it has called any SparseBLAS MKL method
 macro blas(ex)
@@ -24,6 +24,8 @@ matrix_classes = [
 ]
 
 @testset "MKLSparse.matdescra()" begin
+    Random.seed!(100500)
+
     sA = sprand(5, 5, 0.01)
     sS = sA'sA
     sTl = tril(sS)
@@ -60,6 +62,8 @@ end
 local atol::real(T) = 100*eps(real(one(T))) # absolute tolerance for SparseBLAS results
 
 @testset "SparseMatrixCSC{$T} * Vector{$T}" begin
+    Random.seed!(100500)
+
     for _ in 1:10
         spA = sprand(T, 10, 5, 0.5)
         a = Array(spA)
@@ -77,6 +81,8 @@ local atol::real(T) = 100*eps(real(one(T))) # absolute tolerance for SparseBLAS
 end
 
 @testset "Vector{$T} * SparseMatrixCSC{$T}" begin
+    Random.seed!(100500)
+
     for _ in 1:10
         spA = sprand(T, 10, 5, 0.5)
         a = Array(spA)
@@ -101,6 +107,8 @@ end
 end
 
 @testset "SparseMatrixCSC{$T} * Matrix{$T}" begin
+    Random.seed!(100500)
+
     for _ in 1:10
         spA = sprand(T, 10, 5, 0.5)
         a = Array(spA)
@@ -135,6 +143,8 @@ end
 
 @testset "$Aclass{SparseMatrixCSC{$T}} * $(ifelse(Bdim == 2, "Matrix", "Vector")){$T}" for Bdim in 1:2,
         (Aclass, transform_to_class) in matrix_classes
+    Random.seed!(100500)
+
     for _ in 1:10
         n = rand(50:150)
         spA = transform_to_class(sprand(T, n, n, 0.5) + convert(real(T), sqrt(n))*I)
@@ -154,6 +164,8 @@ end
 
     (Aclass == Symmetric) && continue # not implemented in MKLSparse
 
+    Random.seed!(100500)
+
     for _ in 1:10
         n = rand(50:150)
         spA = transform_to_class(sprand(T, n, n, 0.5) + convert(real(T), sqrt(n))*I)