Fix -, conj, and conj! for sparse matrices with invalid entries…

… in `nzval` (JuliaLang#31187)

stdlib/SparseArrays/src/sparsematrix.jl

@@ -1503,12 +1503,22 @@ sparse(s::UniformScaling, dims::Dims{2}) = SparseMatrixCSC(s, dims)
 sparse(s::UniformScaling, m::Integer, n::Integer) = sparse(s, Dims((m, n)))
 
 # TODO: More appropriate location?
-conj!(A::SparseMatrixCSC) = (@inbounds broadcast!(conj, A.nzval, A.nzval); A)
-(-)(A::SparseMatrixCSC) = SparseMatrixCSC(A.m, A.n, copy(A.colptr), copy(A.rowval), map(-, A.nzval))
+function conj!(A::SparseMatrixCSC)
+    map!(conj, nzvalview(A), nzvalview(A))
+    return A
+end
+function (-)(A::SparseMatrixCSC)
+    nzval = similar(A.nzval)
+    map!(-, view(nzval, 1:nnz(A)), nzvalview(A))
+    return SparseMatrixCSC(A.m, A.n, copy(A.colptr), copy(A.rowval), nzval)
+end
 
 # the rest of real, conj, imag are handled correctly via AbstractArray methods
-conj(A::SparseMatrixCSC{<:Complex}) =
-    SparseMatrixCSC(A.m, A.n, copy(A.colptr), copy(A.rowval), conj(A.nzval))
+function conj(A::SparseMatrixCSC{<:Complex})
+    nzval = similar(A.nzval)
+    map!(conj, view(nzval, 1:nnz(A)), nzvalview(A))
+    return SparseMatrixCSC(A.m, A.n, copy(A.colptr), copy(A.rowval), nzval)
+end
 imag(A::SparseMatrixCSC{Tv,Ti}) where {Tv<:Real,Ti} = spzeros(Tv, Ti, A.m, A.n)
 
 ## Binary arithmetic and boolean operators

stdlib/SparseArrays/test/sparse.jl

@@ -2518,4 +2518,16 @@ end
     @test_throws ArgumentError sparse(I1, J1, zero(length(I1)zero(length(I1))))
 end
 
+@testset "unary operations on matrices where length(nzval)>nnz" begin
+    # this should create a sparse matrix with length(nzval)>nnz
+    A = SparseMatrixCSC(Complex{BigInt}[1+im 2+2im]')'[1:1, 2:2]
+    # ...ensure it does! If necessary, the test needs to be updated to use
+    # another mechanism to create a suitable A.
+    @assert length(A.nzval) > nnz(A)
+    @test -A == fill(-2-2im, 1, 1)
+    @test conj(A) == fill(2-2im, 1, 1)
+    conj!(A)
+    @test A == fill(2-2im, 1, 1)
+end
+
 end # module