Backports for Julia v1.8.x

.github/workflows/ci.yml

@@ -4,6 +4,7 @@ on:
     branches:
       - 'main'
       - 'release-*'
+      - 'backports-release-*'
   push:
     branches:
       - 'main'
@@ -22,8 +23,8 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          # - '1.6'
-          - 'nightly'
+          - '1.8'
+          # - 'nightly'
         os:
           - ubuntu-latest
           - macOS-latest
@@ -63,8 +64,8 @@ jobs:
       - uses: actions/checkout@v2
       - uses: julia-actions/setup-julia@latest
         with:
-          # version: '1.6'
-          version: 'nightly'
+          version: '1.8'
+          # version: 'nightly'
       - name: Generate docs
         run: |
           julia --color=yes -e 'write("Project.toml", replace(read("Project.toml", String), r"uuid = .*?\n" =>"uuid = \"3f01184e-e22b-5df5-ae63-d93ebab69eaf\"\n"));'

src/SparseArrays.jl

@@ -11,6 +11,11 @@ using Base.Sort: Forward
 using LinearAlgebra
 using LinearAlgebra: AdjOrTrans, matprod
 
+# Temporary workaround for simplifying SparseArrays.jl upgrade in JuliaLang/julia
+# to workaround circshift! bug, see https://github.com/JuliaLang/julia/pull/46759
+const CIRCSHIFT_WRONG_DIRECTION = circshift!([1, 2, 3], 1) != circshift([1, 2, 3], 1)
+
+
 import Base: +, -, *, \, /, &, |, xor, ==, zero
 import LinearAlgebra: mul!, ldiv!, rdiv!, cholesky, adjoint!, diag, eigen, dot,
     issymmetric, istril, istriu, lu, tr, transpose!, tril!, triu!, isbanded,

src/sparsematrix.jl

@@ -3938,16 +3938,16 @@ function Base.swaprows!(A::AbstractSparseMatrixCSC, i, j)
             rows[rr[iidx]] = j
             jidx == 0 && continue
             rotate_range = rr[iidx]:jrange[jidx]
-            circshift!(@view(vals[rotate_range]), -1)
-            circshift!(@view(rows[rotate_range]), -1)
+            circshift!(@view(vals[rotate_range]), CIRCSHIFT_WRONG_DIRECTION ? -1 : 1)
+            circshift!(@view(rows[rotate_range]), CIRCSHIFT_WRONG_DIRECTION ? -1 : 1)
         else
             # Same as i, but in the opposite direction
             @assert has_j
             rows[jrange[jidx]] = i
             iidx > length(rr) && continue
             rotate_range = rr[iidx]:jrange[jidx]
-            circshift!(@view(vals[rotate_range]), 1)
-            circshift!(@view(rows[rotate_range]), 1)
+            circshift!(@view(vals[rotate_range]), CIRCSHIFT_WRONG_DIRECTION ? 1 : -1)
+            circshift!(@view(rows[rotate_range]), CIRCSHIFT_WRONG_DIRECTION ? 1 : -1)
         end
     end
     return nothing

src/sparsevector.jl

@@ -40,6 +40,7 @@ const AdjOrTransSparseVectorUnion{Tv,Ti} = LinearAlgebra.AdjOrTrans{Tv, <:Sparse
 
 ### Basic properties
 
+length(x::SparseVector)   = getfield(x, :n)
 size(x::SparseVector)     = (getfield(x, :n),)
 count(f, x::SparseVector) = count(f, nonzeros(x)) + f(zero(eltype(x)))*(length(x) - nnz(x))
 
@@ -1075,20 +1076,27 @@ const _Annotated_SparseConcatArrays = Union{_Triangular_SparseConcatArrays, _Sym
 const _SparseConcatGroup = Union{_DenseConcatGroup, _SparseConcatArrays, _Annotated_SparseConcatArrays}
 
 # Concatenations involving un/annotated sparse/special matrices/vectors should yield sparse arrays
+
+# the output array type is determined by the first element of the to be concatenated objects
+# if this is a Number, the output would be dense by the fallback abstractarray.jl code (see cat_similar)
+# so make sure that if that happens, the "array" is sparse (if more sparse arrays are involved, of course)
+_sparse(x::Number) = sparsevec([1], [x], 1)
+_sparse(A) = _makesparse(A)
 _makesparse(x::Number) = x
-_makesparse(x::AbstractArray) = SparseMatrixCSC(issparse(x) ? x : sparse(x))
+_makesparse(x::AbstractVector) = convert(SparseVector, issparse(x) ? x : sparse(x))::SparseVector
+_makesparse(x::AbstractMatrix) = convert(SparseMatrixCSC, issparse(x) ? x : sparse(x))::SparseMatrixCSC
 
 function Base._cat(dims, Xin::_SparseConcatGroup...)
-    X = map(_makesparse, Xin)
+    X = (_sparse(first(Xin)), map(_makesparse, Base.tail(Xin))...)
     T = promote_eltype(Xin...)
     Base.cat_t(T, X...; dims=dims)
 end
 function hcat(Xin::_SparseConcatGroup...)
-    X = map(_makesparse, Xin)
+    X = (_sparse(first(Xin)), map(_makesparse, Base.tail(Xin))...)
     return cat(X..., dims=Val(2))
 end
 function vcat(Xin::_SparseConcatGroup...)
-    X = map(_makesparse, Xin)
+    X = (_sparse(first(Xin)), map(_makesparse, Base.tail(Xin))...)
     return cat(X..., dims=Val(1))
 end
 hvcat(rows::Tuple{Vararg{Int}}, X::_SparseConcatGroup...) =
@@ -1122,9 +1130,9 @@ Concatenate along dimension 2. Return a SparseMatrixCSC object.
     the concatenation with specialized "sparse" matrix types from LinearAlgebra.jl
     automatically yielded sparse output even in the absence of any SparseArray argument.
 """
-sparse_hcat(Xin::Union{AbstractVecOrMat,Number}...) = cat(map(_makesparse, Xin)..., dims=Val(2))
+sparse_hcat(Xin::Union{AbstractVecOrMat,Number}...) = cat(_sparse(first(Xin)), map(_makesparse, Base.tail(Xin))..., dims=Val(2))
 function sparse_hcat(X::Union{AbstractVecOrMat,UniformScaling,Number}...)
-    LinearAlgebra._hcat(X...; array_type = SparseMatrixCSC)
+    LinearAlgebra._hcat(_sparse(first(X)), map(_makesparse, Base.tail(X))...; array_type = SparseMatrixCSC)
 end
 
 """
@@ -1137,9 +1145,9 @@ Concatenate along dimension 1. Return a SparseMatrixCSC object.
     the concatenation with specialized "sparse" matrix types from LinearAlgebra.jl
     automatically yielded sparse output even in the absence of any SparseArray argument.
 """
-sparse_vcat(Xin::Union{AbstractVecOrMat,Number}...) = cat(map(_makesparse, Xin)..., dims=Val(1))
+sparse_vcat(Xin::Union{AbstractVecOrMat,Number}...) = cat(_sparse(first(Xin)), map(_makesparse, Base.tail(Xin))..., dims=Val(1))
 function sparse_vcat(X::Union{AbstractVecOrMat,UniformScaling,Number}...)
-    LinearAlgebra._vcat(X...; array_type = SparseMatrixCSC)
+    LinearAlgebra._vcat(_sparse(first(X)), map(_makesparse, Base.tail(X))...; array_type = SparseMatrixCSC)
 end
 
 """
@@ -1155,10 +1163,10 @@ arguments to concatenate in each block row.
     automatically yielded sparse output even in the absence of any SparseArray argument.
 """
 function sparse_hvcat(rows::Tuple{Vararg{Int}}, Xin::Union{AbstractVecOrMat,Number}...)
-    hvcat(rows, map(_makesparse, Xin)...)
+    hvcat(rows, _sparse(first(Xin)), map(_makesparse, Base.tail(Xin))...)
 end
 function sparse_hvcat(rows::Tuple{Vararg{Int}}, X::Union{AbstractVecOrMat,UniformScaling,Number}...)
-    LinearAlgebra._hvcat(rows, X...; array_type = SparseMatrixCSC)
+    LinearAlgebra._hvcat(rows, _sparse(first(X)), map(_makesparse, Base.tail(X))...; array_type = SparseMatrixCSC)
 end
 
 ### math functions
@@ -1434,7 +1442,12 @@ for (fun, comp, word) in ((:findmin, :(<), "minimum"), (:findmax, :(>), "maximum
         # we try to avoid findfirst(iszero, x)
         sindex = findfirst(iszero, nzvals) # first stored zero, if any
         zindex = findfirst(i -> i < nzinds[i], eachindex(nzinds)) # first non-stored zero
-        index = isnothing(sindex) ? zindex : min(sindex, zindex)
+        index = if isnothing(sindex)
+            # non-stored zero are contiguous and at the end
+            isnothing(zindex) && last(nzinds) < lastindex(x) ? last(nzinds) + 1 : zindex
+        else
+            min(sindex, zindex)
+        end
         return zeroval, index
     end
 end
@@ -2120,8 +2133,8 @@ function subvector_shifter!(R::AbstractVector, V::AbstractVector, start::Integer
         end
     end
     # ...but rowval should be sorted within columns
-    circshift!(@view(R[start:fin]), split-start+1)
-    circshift!(@view(V[start:fin]), split-start+1)
+    circshift!(@view(R[start:fin]), (CIRCSHIFT_WRONG_DIRECTION ? (+) : (-))(split-start+1))
+    circshift!(@view(V[start:fin]), (CIRCSHIFT_WRONG_DIRECTION ? (+) : (-))(split-start+1))
 end
 
 function circshift!(O::SparseVector, X::SparseVector, (r,)::Base.DimsInteger{1})

test/sparsevector.jl

@@ -33,9 +33,12 @@ x1_full[SparseArrays.nonzeroinds(spv_x1)] = nonzeros(spv_x1)
     @test SparseArrays.nonzeroinds(x) == [2, 5, 6]
     @test nonzeros(x) == [1.25, -0.75, 3.5]
     @test count(SparseVector(8, [2, 5, 6], [true,false,true])) == 2
-    y = SparseVector(typemax(Int128), Int128[4], [5])
+    y = SparseVector(8, Int128[4], [5])
     @test y isa SparseVector{Int,Int128}
-    @test @inferred size(y) == (@inferred(length(y)),)
+    @test @inferred size(y) == (@inferred(length(y))::Int128,)
+    y = SparseVector(8, Int8[4], [5.0])
+    @test y isa SparseVector{Float64,Int8}
+    @test @inferred size(y) == (@inferred(length(y))::Int8,)
 end
 
 @testset "isstored" begin
@@ -537,6 +540,22 @@ end
         @test length(V) == m * n
         Vr = vec(Hr)
         @test Array(V) == Vr
+        Vnum = vcat(A..., zero(Float64))
+        Vnum2 = sparse_vcat(map(Array, A)..., zero(Float64))
+        @test Vnum isa SparseVector{Float64,Int}
+        @test Vnum2 isa SparseVector{Float64,Int}
+        @test length(Vnum) == length(Vnum2) == m*n + 1
+        @test Array(Vnum) == Array(Vnum2) == [Vr; 0]
+        Vnum = vcat(zero(Float64), A...)
+        Vnum2 = sparse_vcat(zero(Float64), map(Array, A)...)
+        @test Vnum isa SparseVector{Float64,Int}
+        @test Vnum2 isa SparseVector{Float64,Int}
+        @test length(Vnum) == length(Vnum2) == m*n + 1
+        @test Array(Vnum) == Array(Vnum2) == [0; Vr]
+        # case with rowwise a Number as first element, should still yield a sparse matrix
+        x = sparsevec([1], [3.0], 1)
+        X = [3.0 x; 3.0 x]
+        @test issparse(X)
     end
 
     @testset "concatenation of sparse vectors with other types" begin
@@ -898,6 +917,24 @@ end
         @test_throws ArgumentError findmin(x)
         @test_throws ArgumentError findmax(x)
     end
+
+    let v = spzeros(3) #Julia #44978
+        v[1] = 2
+        @test argmin(v) == 2
+        @test argmax(v) == 1
+        v[2] = 2
+        @test argmin(v) == 3
+        v[1] = 0
+        v[2] = 0
+        v[3] = 2
+        @test argmin(v) == 1
+        @test argmax(v) == 3
+    end
+
+    let v = spzeros(3) #Julia #44978
+        v[3] = 2
+        @test argmax(v) == 3
+    end
 end
 
 ### linalg