move SparseArrays to stdlib

NEWS.md

@@ -872,6 +872,8 @@ Deprecated or removed
   * The functions `eigs` and `svds` have been moved to the `IterativeEigensolvers` standard
     library module ([#24714]).
 
+  * Sparse array functionality has moved to the `SparseArrays` standard library ([#25249]).
+
   * `@printf` and `@sprintf` have been moved to the `Printf` standard library ([#23929],[#25056]).
 
   * `isnumber` has been deprecated in favor of `isnumeric`, `is_assigned_char`

base/asyncmap.jl

@@ -260,13 +260,6 @@ function asyncmap(f, b::BitArray; kwargs...)
     return b2
 end
 
-# TODO: Optimize for sparse arrays
-# For now process as regular arrays and convert back
-function asyncmap(f, s::AbstractSparseArray...; kwargs...)
-    sa = map(Array, s)
-    return sparse(asyncmap(f, sa...; kwargs...))
-end
-
 mutable struct AsyncCollector
     f
     results

base/exports.jl

@@ -434,15 +434,13 @@ export
     minimum,
     minmax,
     ndims,
-    nonzeros,
     ones,
     parent,
     parentindices,
     partialsort,
     partialsort!,
     partialsortperm,
     partialsortperm!,
-    permute,
     permute!,
     permutedims,
     permutedims!,
@@ -513,7 +511,6 @@ export
 # linear algebra
     bkfact!,
     bkfact,
-    blkdiag,
     chol,
     cholfact!,
     cholfact,
@@ -594,10 +591,6 @@ export
     ⋅,
     ×,
 
-# sparse
-    dropzeros,
-    dropzeros!,
-
 # bitarrays
     falses,
     flipbits!,
@@ -1183,22 +1176,4 @@ export
     @goto,
     @view,
     @views,
-    @static,
-
-# SparseArrays module re-exports
-    SparseArrays,
-    AbstractSparseArray,
-    AbstractSparseMatrix,
-    AbstractSparseVector,
-    SparseMatrixCSC,
-    SparseVector,
-    issparse,
-    sparse,
-    sparsevec,
-    spdiagm,
-    sprand,
-    sprandn,
-    spzeros,
-    rowvals,
-    nzrange,
-    nnz
+    @static

base/linalg/bidiag.jl

@@ -178,7 +178,8 @@ broadcast(::typeof(big), B::Bidiagonal) = Bidiagonal(big.(B.dv), big.(B.ev), B.u
 # On the other hand, similar(B, [neweltype,] shape...) should yield a sparse matrix.
 # The first method below effects the former, and the second the latter.
 similar(B::Bidiagonal, ::Type{T}) where {T} = Bidiagonal(similar(B.dv, T), similar(B.ev, T), B.uplo)
-similar(B::Bidiagonal, ::Type{T}, dims::Union{Dims{1},Dims{2}}) where {T} = spzeros(T, dims...)
+# The method below is moved to SparseArrays for now
+# similar(B::Bidiagonal, ::Type{T}, dims::Union{Dims{1},Dims{2}}) where {T} = spzeros(T, dims...)
 
 
 ###################

base/linalg/dense.jl

@@ -303,8 +303,6 @@ Vector `kv.second` will be placed on the `kv.first` diagonal.
 versions with fast arithmetic, see [`Diagonal`](@ref), [`Bidiagonal`](@ref)
 [`Tridiagonal`](@ref) and [`SymTridiagonal`](@ref).
 
-See also: [`spdiagm`](@ref)
-
 # Examples
 ```jldoctest
 julia> diagm(1 => [1,2,3])

base/linalg/diagonal.jl

@@ -59,7 +59,8 @@ Array(D::Diagonal) = Matrix(D)
 # On the other hand, similar(D, [neweltype,] shape...) should yield a sparse matrix.
 # The first method below effects the former, and the second the latter.
 similar(D::Diagonal, ::Type{T}) where {T} = Diagonal(similar(D.diag, T))
-similar(D::Diagonal, ::Type{T}, dims::Union{Dims{1},Dims{2}}) where {T} = spzeros(T, dims...)
+# The method below is moved to SparseArrays for now
+# similar(D::Diagonal, ::Type{T}, dims::Union{Dims{1},Dims{2}}) where {T} = spzeros(T, dims...)
 
 copyto!(D1::Diagonal, D2::Diagonal) = (copyto!(D1.diag, D2.diag); D1)
 

base/linalg/lapack.jl

@@ -3759,7 +3759,7 @@ for (stev, stebz, stegr, stein, elty) in
             chklapackerror(info[])
             if any(ifail .!= 0)
                 # TODO: better error message / type
-                error("failed to converge eigenvectors:\n$(nonzeros(ifail))")
+                error("failed to converge eigenvectors:\n$(find(x->x != 0, ifail))")
             end
             z
         end

base/linalg/tridiag.jl

@@ -111,7 +111,8 @@ end
 # On the other hand, similar(S, [neweltype,] shape...) should yield a sparse matrix.
 # The first method below effects the former, and the second the latter.
 similar(S::SymTridiagonal, ::Type{T}) where {T} = SymTridiagonal(similar(S.dv, T), similar(S.ev, T))
-similar(S::SymTridiagonal, ::Type{T}, dims::Union{Dims{1},Dims{2}}) where {T} = spzeros(T, dims...)
+# The method below is moved to SparseArrays for now
+# similar(S::SymTridiagonal, ::Type{T}, dims::Union{Dims{1},Dims{2}}) where {T} = spzeros(T, dims...)
 
 #Elementary operations
 broadcast(::typeof(abs), M::SymTridiagonal) = SymTridiagonal(abs.(M.dv), abs.(M.ev))
@@ -497,7 +498,8 @@ Array(M::Tridiagonal) = Matrix(M)
 # On the other hand, similar(M, [neweltype,] shape...) should yield a sparse matrix.
 # The first method below effects the former, and the second the latter.
 similar(M::Tridiagonal, ::Type{T}) where {T} = Tridiagonal(similar(M.dl, T), similar(M.d, T), similar(M.du, T))
-similar(M::Tridiagonal, ::Type{T}, dims::Union{Dims{1},Dims{2}}) where {T} = spzeros(T, dims...)
+# The method below is moved to SparseArrays for now
+# similar(M::Tridiagonal, ::Type{T}, dims::Union{Dims{1},Dims{2}}) where {T} = spzeros(T, dims...)
 
 # Operations on Tridiagonal matrices
 copyto!(dest::Tridiagonal, src::Tridiagonal) = (copyto!(dest.dl, src.dl); copyto!(dest.d, src.d); copyto!(dest.du, src.du); dest)

base/sysimg.jl

@@ -427,10 +427,6 @@ include("libgit2/libgit2.jl")
 # package manager
 include("pkg/pkg.jl")
 
-# sparse matrices, vectors, and sparse linear algebra
-include("sparse/sparse.jl")
-using .SparseArrays
-
 include("asyncmap.jl")
 
 # worker threads
@@ -499,6 +495,7 @@ Base.require(:IterativeEigensolvers)
 Base.require(:Mmap)
 Base.require(:Profile)
 Base.require(:SharedArrays)
+Base.require(:SparseArrays)
 Base.require(:SuiteSparse)
 Base.require(:Test)
 Base.require(:Unicode)
@@ -512,6 +509,19 @@ Base.require(:Future)
     @deprecate_binding Profile root_module(:Profile) true ", run `using Profile` instead"
     @deprecate_binding Dates root_module(:Dates) true ", run `using Dates` instead"
     @deprecate_binding Distributed root_module(:Distributed) true ", run `using Distributed` instead"
+
+    # PR #25249
+    @deprecate_binding SparseArrays root_module(:SparseArrays) true ", run `using SparseArrays` instead"
+    @deprecate_binding(AbstractSparseArray, root_module(:SparseArrays).AbstractSparseArray, true,
+        ", run `using SparseArrays` to load sparse array functionality")
+    @deprecate_binding(AbstractSparseMatrix, root_module(:SparseArrays).AbstractSparseMatrix, true,
+        ", run `using SparseArrays` to load sparse array functionality")
+    @deprecate_binding(AbstractSparseVector, root_module(:SparseArrays).AbstractSparseVector, true,
+        ", run `using SparseArrays` to load sparse array functionality")
+    @deprecate_binding(SparseMatrixCSC, root_module(:SparseArrays).SparseMatrixCSC, true,
+        ", run `using SparseArrays` to load sparse array functionality")
+    @deprecate_binding(SparseVector, root_module(:SparseArrays).SparseVector, true,
+        ", run `using SparseArrays` to load sparse array functionality")
 end
 
 empty!(LOAD_PATH)

doc/src/base/arrays.md

@@ -188,30 +188,3 @@ and can be converted to/from the latter via `Array(bitarray)` and `BitArray(arra
 ```@docs
 Base.flipbits!
 ```
-
-## [Sparse Vectors and Matrices](@id stdlib-sparse-arrays)
-
-Sparse vectors and matrices largely support the same set of operations as their dense counterparts.
-The following functions are specific to sparse arrays.
-
-```@docs
-Base.SparseArrays.SparseVector
-Base.SparseArrays.SparseMatrixCSC
-Base.SparseArrays.sparse
-Base.SparseArrays.sparsevec
-Base.SparseArrays.issparse
-Base.SparseArrays.nnz
-Base.SparseArrays.spzeros
-Base.SparseArrays.spdiagm
-Base.SparseArrays.sprand
-Base.SparseArrays.sprandn
-Base.SparseArrays.nonzeros
-Base.SparseArrays.rowvals
-Base.SparseArrays.nzrange
-Base.SparseArrays.dropzeros!(::SparseMatrixCSC, ::Bool)
-Base.SparseArrays.dropzeros(::SparseMatrixCSC, ::Bool)
-Base.SparseArrays.dropzeros!(::SparseVector, ::Bool)
-Base.SparseArrays.dropzeros(::SparseVector, ::Bool)
-Base.SparseArrays.permute
-Base.permute!{Tv, Ti, Tp <: Integer, Tq <: Integer}(::SparseMatrixCSC{Tv,Ti}, ::SparseMatrixCSC{Tv,Ti}, ::AbstractArray{Tp,1}, ::AbstractArray{Tq,1})
-```

doc/src/base/base.md

@@ -98,7 +98,6 @@ Base.Markdown
 Base.Meta
 Base.Pkg
 Base.Serializer
-Base.SparseArrays
 Base.StackTraces
 Base.Sys
 Base.Threads

doc/src/base/index.md

@@ -31,5 +31,6 @@
   * [Memory-mapped I/O](@ref)
   * [Base64](@ref)
   * [File Events](@ref lib-filewatching)
+  * [Sparse Arrays](@ref)
   * [Iterative Eigensolvers](@ref lib-itereigen)
   * [Printf](@ref)

doc/src/base/linalg.md

@@ -91,7 +91,6 @@ Base.LinAlg.pinv
 Base.LinAlg.nullspace
 Base.repmat
 Base.kron
-Base.SparseArrays.blkdiag
 Base.LinAlg.linreg
 Base.LinAlg.exp(::StridedMatrix{<:Base.LinAlg.BlasFloat})
 Base.LinAlg.log(::StridedMatrix)

doc/src/index.md

@@ -81,6 +81,7 @@
   * [Delimited Files](@ref)
   * [Distributed Computing](@ref)
   * [File Events](@ref lib-filewatching)
+  * [Sparse Arrays](@ref)
   * [Iterative Eigensolvers](@ref lib-itereigen)
   * [Memory-mapped I/O](@ref)
   * [Printf](@ref)