Use stable RNG for tests

Author: avik-pal

Project.toml

@@ -75,6 +75,7 @@ SciMLOperators = "0.3"
 SimpleNonlinearSolve = "0.1.23"
 SparseArrays = "<0.0.1, 1"
 SparseDiffTools = "2.14"
+StableRNGs = "1"
 StaticArrays = "1"
 Symbolics = "5"
 Test = "1"
@@ -98,11 +99,12 @@ NonlinearProblemLibrary = "b7050fa9-e91f-4b37-bcee-a89a063da141"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
+StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 SparseDiffTools = "47a9eef4-7e08-11e9-0b38-333d64bd3804"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["Aqua", "Enzyme", "BenchmarkTools", "SafeTestsets", "Pkg", "Test", "ForwardDiff", "StaticArrays", "Symbolics", "LinearSolve", "Random", "LinearAlgebra", "Zygote", "SparseDiffTools", "NonlinearProblemLibrary", "LeastSquaresOptim", "FastLevenbergMarquardt", "NaNMath", "BandedMatrices", "DiffEqBase"]
+test = ["Aqua", "Enzyme", "BenchmarkTools", "SafeTestsets", "Pkg", "Test", "ForwardDiff", "StaticArrays", "Symbolics", "LinearSolve", "Random", "LinearAlgebra", "Zygote", "SparseDiffTools", "NonlinearProblemLibrary", "LeastSquaresOptim", "FastLevenbergMarquardt", "NaNMath", "BandedMatrices", "DiffEqBase", "StableRNGs"]

docs/Project.toml

@@ -30,7 +30,7 @@ NonlinearSolve = "1, 2"
 NonlinearSolveMINPACK = "0.1"
 SciMLBase = "2.4"
 SciMLNLSolve = "0.1"
-SimpleNonlinearSolve = "0.1.5"
+SimpleNonlinearSolve = "0.1.5, 1"
 StaticArrays = "1"
 SteadyStateDiffEq = "1.10, 2"
 Sundials = "4.11"

test/nonlinear_least_squares.jl

@@ -1,4 +1,5 @@
-using NonlinearSolve, LinearSolve, LinearAlgebra, Test, Random, ForwardDiff, Zygote
+using NonlinearSolve,
+    LinearSolve, LinearAlgebra, Test, StableRNGs, Random, ForwardDiff, Zygote
 import FastLevenbergMarquardt, LeastSquaresOptim
 
 true_function(x, θ) = @. θ[1] * exp(θ[2] * x) * cos(θ[3] * x + θ[4])
@@ -21,7 +22,7 @@ function loss_function(resid, θ, p)
     return resid
 end
 
-θ_init = θ_true .+ randn!(similar(θ_true)) * 0.1
+θ_init = θ_true .+ randn!(StableRNG(0), similar(θ_true)) * 0.1
 prob_oop = NonlinearLeastSquaresProblem{false}(loss_function, θ_init, x)
 prob_iip = NonlinearLeastSquaresProblem(NonlinearFunction(loss_function;
         resid_prototype = zero(y_target)), θ_init, x)

test/runtests.jl

@@ -14,11 +14,11 @@ end
 @time begin
     if GROUP == "All" || GROUP == "Core"
         @time @safetestset "Quality Assurance" include("qa.jl")
+        @time @safetestset "Nonlinear Least Squares" include("nonlinear_least_squares.jl")
         @time @safetestset "Basic Tests + Some AD" include("basictests.jl")
         @time @safetestset "Sparsity Tests" include("sparse.jl")
         @time @safetestset "Polyalgs" include("polyalgs.jl")
         @time @safetestset "Matrix Resizing" include("matrix_resizing.jl")
-        @time @safetestset "Nonlinear Least Squares" include("nonlinear_least_squares.jl")
         @time @safetestset "Infeasible Problems" include("infeasible.jl")
     end