Add findnz for adjoint/transpose of sparse matrices and vectors

src/abstractsparse.jl

@@ -114,6 +114,8 @@ end
 
 Return a tuple `(I, J, V)` where `I` and `J` are the row and column indices of the stored
 ("structurally non-zero") values in sparse matrix `A`, and `V` is a vector of the values.
+`A` may also be the adjoint or transpose of a sparse matrix or vector, in which case the
+values in `V` are correspondingly adjointed or transposed.
 
 # Examples
 ```jldoctest

src/sparsematrix.jl

@@ -1958,6 +1958,11 @@ function findnz(S::AbstractSparseMatrixCSC{Tv,Ti}) where {Tv,Ti}
     return (I, J, V)
 end
 
+# Materializing the (conjugate) transpose is linear in `nnz` and yields the
+# indices in column-major order of the wrapped matrix, consistent with the
+# `AbstractSparseMatrixCSC` method above.
+findnz(S::AdjOrTrans{<:Any,<:AbstractSparseMatrixCSC}) = findnz(copy(S))
+
 function _sparse_findnextnz(m::AbstractSparseMatrixCSC, ij::CartesianIndex{2})
     row, col = Tuple(ij)
     col > size(m, 2) && return nothing

src/sparsevector.jl

@@ -924,6 +924,25 @@ function findnz(x::SparseVectorUnion)
     return (I, V)
 end
 
+function findnz(x::AdjOrTransSparseVectorUnion)
+    p = parent(x)
+    numnz = nnz(p)
+    I = ones(indtype(p), numnz)
+    J = Vector{indtype(p)}(undef, numnz)
+    V = Vector{eltype(x)}(undef, numnz)
+
+    nzind = nonzeroinds(p)
+    nzval = nonzeros(p)
+    f = wrapperop(x)
+
+    @inbounds for i = 1 : numnz
+        J[i] = nzind[i]
+        V[i] = f(nzval[i])
+    end
+
+    return (I, J, V)
+end
+
 function _sparse_findnextnz(v::AbstractCompressedVector, i::Integer)
     n = searchsortedfirst(nonzeroinds(v), i)
     if n > length(nonzeroinds(v))

test/sparsematrix_ops.jl

@@ -29,6 +29,27 @@ end
     @test nnz(zero(sparse(fill(1,5,5)))) == 0
 end
 
+@testset "findnz for adjoint/transpose (issue #632)" begin
+    A = sparse([1, 1, 2, 3], [1, 2, 3, 2], [1.0+2.0im, 3.0, 4.0-1.0im, 0.0], 3, 4)
+    for T in (Float64, ComplexF64), op in (adjoint, transpose)
+        B = op(T == Float64 ? real(A) : A)
+        I, J, V = findnz(B)
+        @test (I, J, V) == findnz(SparseMatrixCSC(B))
+        @test issorted(collect(zip(J, I)))  # column-major order of the wrapper
+        @test all(B[i, j] == v for (i, j, v) in zip(I, J, V))
+        @test length(I) == nnz(B)
+        @test typeof(I) == typeof(J) == Vector{Int} && eltype(V) == T
+        @test all(isempty, findnz(op(spzeros(T, 2, 3))))
+    end
+    x = sparsevec([2, 4], [1.0+im, 0.0], 5)
+    for op in (adjoint, transpose)
+        I, J, V = findnz(op(x))
+        @test I == [1, 1] && J == [2, 4] && V == op.([1.0+im, 0.0])
+        @test (I, J, V) == findnz(sparse(op(x)))
+        @test all(isempty, findnz(op(spzeros(3))))
+    end
+end
+
 @testset "iszero specialization for SparseMatrixCSC" begin
     @test !iszero(sparse(I, 3, 3))                  # test failure
     @test iszero(spzeros(3, 3))                     # test success with no stored entries