remove Random.defaultRNG() (JuliaLang#25650)

This function is an artifact of an intermediate state of PR JuliaLang#24874, but is not needed anymore.
tekverkp · Jan 21, 2018 · c546f03 · c546f03
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commit c546f03
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Showing 4 changed files with 11 additions and 13 deletions.
diff --git a/stdlib/Random/src/Random.jl b/stdlib/Random/src/Random.jl
@@ -27,15 +27,13 @@ export srand,
  randperm, randperm!,
  randcycle, randcycle!,
  AbstractRNG, MersenneTwister, RandomDevice,
- defaultRNG, randjump
+ randjump
 
 
 ## general definitions
 
 abstract type AbstractRNG end
 
-defaultRNG() = GLOBAL_RNG
-
 
 ### integers
 

diff --git a/stdlib/SparseArrays/src/SparseArrays.jl b/stdlib/SparseArrays/src/SparseArrays.jl
@@ -30,7 +30,7 @@ import Base: @get!, acos, acosd, acot, acotd, acsch, asech, asin, asind, asinh,
  rotl90, rotr90, round, setindex!, similar, size, transpose,
  vec, permute!, map, map!, Array
 
-using Random: defaultRNG, AbstractRNG, randsubseq, randsubseq!
+using Random: GLOBAL_RNG, AbstractRNG, randsubseq, randsubseq!
 
 export AbstractSparseArray, AbstractSparseMatrix, AbstractSparseVector,
  SparseMatrixCSC, SparseVector, blkdiag, droptol!, dropzeros!, dropzeros,

diff --git a/stdlib/SparseArrays/src/sparsematrix.jl b/stdlib/SparseArrays/src/sparsematrix.jl
@@ -1417,18 +1417,18 @@ function sprand(m::Integer, n::Integer, density::AbstractFloat,
  N == 0 && return spzeros(T,m,n)
  N == 1 && return rand() <= density ? sparse([1], [1], rfn(1)) : spzeros(T,1,1)
 
- I,J = sprand_IJ(defaultRNG(), m, n, density)
+ I,J = sprand_IJ(GLOBAL_RNG, m, n, density)
  sparse_IJ_sorted!(I, J, rfn(length(I)), m, n, +) # it will never need to combine
 end
 
 truebools(r::AbstractRNG, n::Integer) = fill(true, n)
 
-sprand(m::Integer, n::Integer, density::AbstractFloat) = sprand(defaultRNG(),m,n,density)
+sprand(m::Integer, n::Integer, density::AbstractFloat) = sprand(GLOBAL_RNG,m,n,density)
 
 sprand(r::AbstractRNG, m::Integer, n::Integer, density::AbstractFloat) = sprand(r,m,n,density,rand,Float64)
 sprand(r::AbstractRNG, ::Type{T}, m::Integer, n::Integer, density::AbstractFloat) where {T} = sprand(r,m,n,density,(r, i) -> rand(r, T, i), T)
 sprand(r::AbstractRNG, ::Type{Bool}, m::Integer, n::Integer, density::AbstractFloat) = sprand(r,m,n,density, truebools, Bool)
-sprand(::Type{T}, m::Integer, n::Integer, density::AbstractFloat) where {T} = sprand(defaultRNG(), T, m, n, density)
+sprand(::Type{T}, m::Integer, n::Integer, density::AbstractFloat) where {T} = sprand(GLOBAL_RNG, T, m, n, density)
 
 """
  sprandn([rng], m[,n],p::AbstractFloat)
@@ -1450,7 +1450,7 @@ julia> sprandn(rng, 2, 2, 0.75)
 ```
 """
 sprandn(r::AbstractRNG, m::Integer, n::Integer, density::AbstractFloat) = sprand(r,m,n,density,randn,Float64)
-sprandn(m::Integer, n::Integer, density::AbstractFloat) = sprandn(defaultRNG(),m,n,density)
+sprandn(m::Integer, n::Integer, density::AbstractFloat) = sprandn(GLOBAL_RNG,m,n,density)
 
 LinearAlgebra.fillstored!(S::SparseMatrixCSC, x) = (fill!(view(S.nzval, 1:(S.colptr[S.n + 1] - 1)), x); S)
 

diff --git a/stdlib/SparseArrays/src/sparsevector.jl b/stdlib/SparseArrays/src/sparsevector.jl
@@ -472,28 +472,28 @@ copyto!(A::SparseMatrixCSC, B::SparseVector{TvB,TiB}) where {TvB,TiB} =
 
 
 ### Rand Construction
-sprand(n::Integer, p::AbstractFloat, rfn::Function, ::Type{T}) where {T} = sprand(defaultRNG(), n, p, rfn, T)
+sprand(n::Integer, p::AbstractFloat, rfn::Function, ::Type{T}) where {T} = sprand(GLOBAL_RNG, n, p, rfn, T)
 function sprand(r::AbstractRNG, n::Integer, p::AbstractFloat, rfn::Function, ::Type{T}) where T
  I = randsubseq(r, 1:convert(Int, n), p)
  V = rfn(r, T, length(I))
  SparseVector(n, I, V)
 end
 
-sprand(n::Integer, p::AbstractFloat, rfn::Function) = sprand(defaultRNG(), n, p, rfn)
+sprand(n::Integer, p::AbstractFloat, rfn::Function) = sprand(GLOBAL_RNG, n, p, rfn)
 function sprand(r::AbstractRNG, n::Integer, p::AbstractFloat, rfn::Function)
  I = randsubseq(r, 1:convert(Int, n), p)
  V = rfn(r, length(I))
  SparseVector(n, I, V)
 end
 
-sprand(n::Integer, p::AbstractFloat) = sprand(defaultRNG(), n, p, rand)
+sprand(n::Integer, p::AbstractFloat) = sprand(GLOBAL_RNG, n, p, rand)
 
 sprand(r::AbstractRNG, n::Integer, p::AbstractFloat) = sprand(r, n, p, rand)
 sprand(r::AbstractRNG, ::Type{T}, n::Integer, p::AbstractFloat) where {T} = sprand(r, n, p, (r, i) -> rand(r, T, i))
 sprand(r::AbstractRNG, ::Type{Bool}, n::Integer, p::AbstractFloat) = sprand(r, n, p, truebools)
-sprand(::Type{T}, n::Integer, p::AbstractFloat) where {T} = sprand(defaultRNG(), T, n, p)
+sprand(::Type{T}, n::Integer, p::AbstractFloat) where {T} = sprand(GLOBAL_RNG, T, n, p)
 
-sprandn(n::Integer, p::AbstractFloat) = sprand(defaultRNG(), n, p, randn)
+sprandn(n::Integer, p::AbstractFloat) = sprand(GLOBAL_RNG, n, p, randn)
 sprandn(r::AbstractRNG, n::Integer, p::AbstractFloat) = sprand(r, n, p, randn)
 
 ## Indexing into Matrices can return SparseVectors