Rename srand to Random.seed! (JuliaLang#28295)

Author: Olivier Thill

NEWS.md

@@ -1323,6 +1323,8 @@ Deprecated or removed
 
   * `squeeze` is deprecated in favor of `dropdims`.
 
+  * `srand` is deprecated in favor of the unexported `Random.seed!` ([#27726]).
+
   * `realmin`/`realmax` are deprecated in favor of `floatmin`/`floatmax` ([#28302]).
 
 Command-line option changes
@@ -1674,6 +1676,7 @@ Command-line option changes
 [#27635]: https://github.com/JuliaLang/julia/issues/27635
 [#27641]: https://github.com/JuliaLang/julia/issues/27641
 [#27711]: https://github.com/JuliaLang/julia/issues/27711
+[#27726]: https://github.com/JuliaLang/julia/issues/27726
 [#27746]: https://github.com/JuliaLang/julia/issues/27746
 [#27859]: https://github.com/JuliaLang/julia/issues/27859
 [#27908]: https://github.com/JuliaLang/julia/issues/27908

doc/src/devdocs/subarrays.md

@@ -37,7 +37,7 @@ cartesian, rather than linear, indexing.
 Consider making 2d slices of a 3d array:
 
 ```@meta
-DocTestSetup = :(import Random; Random.srand(1234))
+DocTestSetup = :(import Random; Random.seed!(1234))
 ```
 ```jldoctest subarray
 julia> A = rand(2,3,4);

doc/src/manual/parallel-computing.md

@@ -418,7 +418,7 @@ julia> function g()
        end
 g (generic function with 1 method)
 
-julia> srand(1); g() # the result for a single thread is 1000
+julia> Random.seed!(1); g() # the result for a single thread is 1000
 781
 ```
 

doc/src/manual/performance-tips.md

@@ -58,7 +58,7 @@ so all the performance issues discussed previously apply.
 A useful tool for measuring performance is the [`@time`](@ref) macro. We here repeat the example
 with the global variable above, but this time with the type annotation removed:
 
-```jldoctest; setup = :(using Random; srand(1234)), filter = r"[0-9\.]+ seconds \(.*?\)"
+```jldoctest; setup = :(using Random; Random.seed!(1234)), filter = r"[0-9\.]+ seconds \(.*?\)"
 julia> x = rand(1000);
 
 julia> function sum_global()
@@ -94,7 +94,7 @@ If we instead pass `x` as an argument to the function it no longer allocates mem
 (the allocation reported below is due to running the `@time` macro in global scope)
 and is significantly faster after the first call:
 
-```jldoctest sumarg; setup = :(using Random; srand(1234)), filter = r"[0-9\.]+ seconds \(.*?\)"
+```jldoctest sumarg; setup = :(using Random; Random.seed!(1234)), filter = r"[0-9\.]+ seconds \(.*?\)"
 julia> x = rand(1000);
 
 julia> function sum_arg(x)
@@ -583,7 +583,7 @@ to perform a core computation. Where possible, it is a good idea to put these co
 in separate functions. For example, the following contrived function returns an array of a randomly-chosen
 type:
 
-```jldoctest; setup = :(using Random; srand(1234))
+```jldoctest; setup = :(using Random; Random.seed!(1234))
 julia> function strange_twos(n)
            a = Vector{rand(Bool) ? Int64 : Float64}(undef, n)
            for i = 1:n
@@ -601,7 +601,7 @@ julia> strange_twos(3)
 
 This should be written as:
 
-```jldoctest; setup = :(using Random; srand(1234))
+```jldoctest; setup = :(using Random; Random.seed!(1234))
 julia> function fill_twos!(a)
            for i = eachindex(a)
                a[i] = 2

stdlib/LinearAlgebra/test/bidiag.jl

@@ -8,7 +8,7 @@ using LinearAlgebra: BlasReal, BlasFloat
 include("testutils.jl") # test_approx_eq_modphase
 
 n = 10 #Size of test matrix
-srand(1)
+Random.seed!(1)
 
 @testset for relty in (Int, Float32, Float64, BigFloat), elty in (relty, Complex{relty})
     if relty <: AbstractFloat

stdlib/LinearAlgebra/test/blas.jl

@@ -5,7 +5,7 @@ module TestBLAS
 using Test, LinearAlgebra, Random
 using LinearAlgebra: BlasReal, BlasComplex
 
-srand(100)
+Random.seed!(100)
 ## BLAS tests - testing the interface code to BLAS routines
 @testset for elty in [Float32, Float64, ComplexF32, ComplexF64]
     @testset "syr2k!" begin

stdlib/LinearAlgebra/test/bunchkaufman.jl

@@ -12,7 +12,7 @@ n = 10
 n1 = div(n, 2)
 n2 = 2*n1
 
-srand(1234321)
+Random.seed!(1234321)
 
 areal = randn(n,n)/2
 aimg  = randn(n,n)/2

stdlib/LinearAlgebra/test/cholesky.jl

@@ -39,7 +39,7 @@ end
     n1 = div(n, 2)
     n2 = 2*n1
 
-    srand(1234321)
+    Random.seed!(1234321)
 
     areal = randn(n,n)/2
     aimg  = randn(n,n)/2
@@ -73,7 +73,7 @@ end
 
         #these tests were failing on 64-bit linux when inside the inner loop
         #for eltya = ComplexF32 and eltyb = Int. The E[i,j] had NaN32 elements
-        #but only with srand(1234321) set before the loops.
+        #but only with Random.seed!(1234321) set before the loops.
         E = abs.(apd - r'*r)
         for i=1:n, j=1:n
             @test E[i,j] <= (n+1)ε/(1-(n+1)ε)*real(sqrt(apd[i,i]*apd[j,j]))

stdlib/LinearAlgebra/test/dense.jl

@@ -15,7 +15,7 @@ n = 10
 n1 = div(n, 2)
 n2 = 2*n1
 
-srand(1234321)
+Random.seed!(1234321)
 
 @testset "Matrix condition number" begin
     ainit = rand(n,n)

stdlib/LinearAlgebra/test/diagonal.jl

@@ -6,7 +6,7 @@ using Test, LinearAlgebra, SparseArrays, Random
 using LinearAlgebra: mul!, rmul!, lmul!, ldiv!, rdiv!, BlasFloat, BlasComplex, SingularException
 
 n=12 #Size of matrix problem to test
-srand(1)
+Random.seed!(1)
 
 @testset for relty in (Float32, Float64, BigFloat), elty in (relty, Complex{relty})
     dd=convert(Vector{elty}, randn(n))

stdlib/LinearAlgebra/test/eigen.jl

@@ -11,7 +11,7 @@ n = 10
 n1 = div(n, 2)
 n2 = 2*n1
 
-srand(1234321)
+Random.seed!(1234321)
 
 areal = randn(n,n)/2
 aimg  = randn(n,n)/2

stdlib/LinearAlgebra/test/generic.jl

@@ -31,7 +31,7 @@ Base.isfinite(q::Quaternion) = isfinite(q.s) & isfinite(q.v1) & isfinite(q.v2) &
 (/)(q::Quaternion, w::Quaternion) = q * conj(w) * (1.0 / abs2(w))
 (\)(q::Quaternion, w::Quaternion) = conj(q) * w * (1.0 / abs2(q))
 
-srand(123)
+Random.seed!(123)
 
 n = 5 # should be odd
 

stdlib/LinearAlgebra/test/hessenberg.jl

@@ -5,7 +5,7 @@ module TestHessenberg
 using Test, LinearAlgebra, Random
 
 let n = 10
-    srand(1234321)
+    Random.seed!(1234321)
 
     Areal  = randn(n,n)/2
     Aimg   = randn(n,n)/2

stdlib/LinearAlgebra/test/lapack.jl

@@ -11,7 +11,7 @@ using LinearAlgebra: BlasInt
 @test_throws ArgumentError LinearAlgebra.LAPACK.chktrans('Z')
 
 @testset "syevr" begin
-    srand(123)
+    Random.seed!(123)
     Ainit = randn(5,5)
     @testset for elty in (Float32, Float64, ComplexF32, ComplexF64)
         if elty == ComplexF32 || elty == ComplexF64
@@ -208,7 +208,7 @@ end
 
 @testset "gels" begin
     @testset for elty in (Float32, Float64, ComplexF32, ComplexF64)
-        srand(913)
+        Random.seed!(913)
         A = rand(elty,10,10)
         X = rand(elty,10)
         B,Y,z = LAPACK.gels!('N',copy(A),copy(X))
@@ -443,7 +443,7 @@ end
 
 @testset "sysv" begin
     @testset for elty in (Float32, Float64, ComplexF32, ComplexF64)
-        srand(123)
+        Random.seed!(123)
         A = rand(elty,10,10)
         A = A + transpose(A) #symmetric!
         b = rand(elty,10)
@@ -456,7 +456,7 @@ end
 
 @testset "hesv" begin
     @testset for elty in (ComplexF32, ComplexF64)
-        srand(935)
+        Random.seed!(935)
         A = rand(elty,10,10)
         A = A + A' #hermitian!
         b = rand(elty,10)

stdlib/LinearAlgebra/test/lq.jl

@@ -11,7 +11,7 @@ n = 10
 n1 = div(n, 2)
 n2 = 2*n1
 
-srand(1234321)
+Random.seed!(1234321)
 
 areal = randn(n,n)/2
 aimg  = randn(n,n)/2

stdlib/LinearAlgebra/test/lu.jl

@@ -11,7 +11,7 @@ n = 10
 n1 = div(n, 2)
 n2 = 2*n1
 
-srand(1234321)
+Random.seed!(1234321)
 
 areal = randn(n,n)/2
 aimg  = randn(n,n)/2
@@ -208,7 +208,7 @@ end
 end
 
 @testset "conversion" begin
-    srand(3)
+    Random.seed!(3)
     a = Tridiagonal(rand(9),rand(10),rand(9))
     fa = Array(a)
     falu = lu(fa)

stdlib/LinearAlgebra/test/pinv.jl

@@ -4,7 +4,7 @@ module TestPinv
 
 using Test, LinearAlgebra, Random
 
-srand(12345)
+Random.seed!(12345)
 
 function hilb(T::Type, n::Integer)
     a = Matrix{T}(undef, n, n)

stdlib/LinearAlgebra/test/qr.jl

@@ -11,7 +11,7 @@ n = 10
 n1 = div(n, 2)
 n2 = 2*n1
 
-srand(1234321)
+Random.seed!(1234321)
 
 areal = randn(n,n)/2
 aimg  = randn(n,n)/2

stdlib/LinearAlgebra/test/schur.jl

@@ -11,7 +11,7 @@ n = 10
 n1 = div(n, 2)
 n2 = 2*n1
 
-srand(1234321)
+Random.seed!(1234321)
 
 areal = randn(n,n)/2
 aimg  = randn(n,n)/2

stdlib/LinearAlgebra/test/special.jl

@@ -6,7 +6,7 @@ using Test, LinearAlgebra, SparseArrays, Random
 using LinearAlgebra: rmul!
 
 n= 10 #Size of matrix to test
-srand(1)
+Random.seed!(1)
 
 @testset "Interconversion between special matrix types" begin
     a = [1.0:n;]

stdlib/LinearAlgebra/test/svd.jl

@@ -37,7 +37,7 @@ n = 10
 n1 = div(n, 2)
 n2 = 2*n1
 
-srand(1234321)
+Random.seed!(1234321)
 
 areal = randn(n,n)/2
 aimg  = randn(n,n)/2

stdlib/LinearAlgebra/test/symmetric.jl

@@ -4,7 +4,7 @@ module TestSymmetric
 
 using Test, LinearAlgebra, SparseArrays, Random
 
-srand(101)
+Random.seed!(101)
 
 @testset "Pauli σ-matrices: $σ" for σ in map(Hermitian,
         Any[ [1 0; 0 1], [0 1; 1 0], [0 -im; im 0], [1 0; 0 -1] ])

stdlib/LinearAlgebra/test/triangular.jl

@@ -11,7 +11,7 @@ using LinearAlgebra: BlasFloat, errorbounds, full!, naivesub!, transpose!,
 debug && println("Triangular matrices")
 
 n = 9
-srand(123)
+Random.seed!(123)
 
 debug && println("Test basic type functionality")
 @test_throws DimensionMismatch LowerTriangular(randn(5, 4))

stdlib/LinearAlgebra/test/tridiag.jl

@@ -22,9 +22,9 @@ end
 
 @testset for elty in (Float32, Float64, ComplexF32, ComplexF64, Int)
     n = 12 #Size of matrix problem to test
-    srand(123)
+    Random.seed!(123)
     if elty == Int
-        srand(61516384)
+        Random.seed!(61516384)
         d = rand(1:100, n)
         dl = -rand(0:10, n-1)
         du = -rand(0:10, n-1)

stdlib/LinearAlgebra/test/uniformscaling.jl

@@ -4,7 +4,7 @@ module TestUniformscaling
 
 using Test, LinearAlgebra, Random, SparseArrays
 
-srand(123)
+Random.seed!(123)
 
 @testset "basic functions" begin
     @test I[1,1] == 1 # getindex

stdlib/Pkg/test/NastyGenerator.jl

@@ -40,7 +40,7 @@ function generate_nasty(n::Int,             # size of planted solutions
     @assert m ≥ n
     d ≤ m-1 || @warn "d=$d, should be ≤ m-1=$(m-1)"
 
-    srand(seed)
+    Random.seed!(seed)
 
     allvers = [sort(unique(randvers(k) for j = 1:q)) for i = 1:m]
 

stdlib/Random/docs/src/index.md

@@ -56,7 +56,7 @@ Random.shuffle!
 ## Generators (creation and seeding)
 
 ```@docs
-Random.srand
+Random.seed!
 Random.MersenneTwister
 Random.RandomDevice
 ```

stdlib/Random/src/RNGs.jl

@@ -65,7 +65,7 @@ The entropy is obtained from the operating system.
 RandomDevice
 
 RandomDevice(::Nothing) = RandomDevice()
-srand(rng::RandomDevice) = rng
+seed!(rng::RandomDevice) = rng
 
 
 ## MersenneTwister
@@ -110,7 +110,7 @@ of random numbers.
 The `seed` may be a non-negative integer or a vector of
 `UInt32` integers. If no seed is provided, a randomly generated one
 is created (using entropy from the system).
-See the [`srand`](@ref) function for reseeding an already existing
+See the [`seed!`](@ref) function for reseeding an already existing
 `MersenneTwister` object.
 
 
@@ -135,7 +135,7 @@ true
 ```
 """
 MersenneTwister(seed=nothing) =
-    srand(MersenneTwister(Vector{UInt32}(), DSFMT_state()), seed)
+    seed!(MersenneTwister(Vector{UInt32}(), DSFMT_state()), seed)
 
 
 function copy!(dst::MersenneTwister, src::MersenneTwister)
@@ -274,9 +274,9 @@ function make_seed(n::Integer)
     end
 end
 
-#### srand()
+#### seed!()
 
-function srand(r::MersenneTwister, seed::Vector{UInt32})
+function seed!(r::MersenneTwister, seed::Vector{UInt32})
     copyto!(resize!(r.seed, length(seed)), seed)
     dsfmt_init_by_array(r.state, r.seed)
     mt_setempty!(r)
@@ -285,12 +285,12 @@ function srand(r::MersenneTwister, seed::Vector{UInt32})
     return r
 end
 
-srand(r::MersenneTwister=GLOBAL_RNG) = srand(r, make_seed())
-srand(r::MersenneTwister, n::Integer) = srand(r, make_seed(n))
-srand(seed::Union{Integer,Vector{UInt32}}) = srand(GLOBAL_RNG, seed)
+seed!(r::MersenneTwister=GLOBAL_RNG) = seed!(r, make_seed())
+seed!(r::MersenneTwister, n::Integer) = seed!(r, make_seed(n))
+seed!(seed::Union{Integer,Vector{UInt32}}) = seed!(GLOBAL_RNG, seed)
 
 
-### Global RNG (must be defined after srand)
+### Global RNG (must be defined after seed!)
 
 const GLOBAL_RNG = MersenneTwister(0)