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add: [CartesianIndex...] sparse method #600

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35eb302
add: [CartesianIndex...] sparse method
kunzaatko Feb 22, 2025
0021a71
fix: Only allow 2D Cartesian indices in constructor
kunzaatko Feb 25, 2025
42e29b6
docs: Document the CartesianIndex method of `sparse`
kunzaatko Jan 8, 2026
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17 changes: 17 additions & 0 deletions src/sparsematrix.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -1041,6 +1041,7 @@ sparse(D::Diagonal) = SparseMatrixCSC(D)

"""
sparse(I, J, V,[ m, n, combine])
sparse(IJ, V,[ m, n, combine])

Create a sparse matrix `S` of dimensions `m x n` such that `S[I[k], J[k]] = V[k]`. The
`combine` function is used to combine duplicates. If `m` and `n` are not specified, they
Expand All @@ -1061,6 +1062,12 @@ julia> Js = [1; 2; 3];
julia> Vs = [1; 2; 3];

julia> sparse(Is, Js, Vs)
3×3 SparseMatrixCSC{Int64, Int64} with 3 stored entries:
1 ⋅ ⋅
⋅ 2 ⋅
⋅ ⋅ 3

julia> sparse([CartesianIndex(i,i) for i in 1:3], Vs)
3×3 SparseMatrixCSC{Int64, Int64} with 3 stored entries:
1 ⋅ ⋅
⋅ 2 ⋅
Expand Down Expand Up @@ -1331,17 +1338,27 @@ end

dimlub(I) = isempty(I) ? 0 : Int(maximum(I)) #least upper bound on required sparse matrix dimension

function reinterpret_cartesian(IJ::AbstractVector{CartesianIndex{2}})
IJ′ = reinterpret(Int, reshape(IJ, 1, :))
return (view(IJ′, 1, :), view(IJ′, 2, :))
end

sparse(I,J,v::Number) = sparse(I, J, fill(v,length(I)))
sparse(IJ::AbstractVector{<:CartesianIndex{2}},v::Number) = sparse(reinterpret_cartesian(IJ)..., v)

sparse(I,J,V::AbstractVector) = sparse(I, J, V, dimlub(I), dimlub(J))
sparse(IJ::AbstractVector{<:CartesianIndex{2}},V::AbstractVector) = sparse(reinterpret_cartesian(IJ)..., V)

sparse(I,J,v::Number,m,n) = sparse(I, J, fill(v,length(I)), Int(m), Int(n))
sparse(IJ::AbstractVector{<:CartesianIndex{2}},v::Number,m,n) = sparse(reinterpret_cartesian(IJ)..., v, m, n)

sparse(I,J,V::AbstractVector,m,n) = sparse(I, J, V, Int(m), Int(n), +)
sparse(IJ::AbstractVector{<:CartesianIndex{2}},V::AbstractVector,m,n) = sparse(reinterpret_cartesian(IJ)..., V, m, n)

sparse(I,J,V::AbstractVector{Bool},m,n) = sparse(I, J, V, Int(m), Int(n), |)

sparse(I,J,v::Number,m,n,combine::Function) = sparse(I, J, fill(v,length(I)), Int(m), Int(n), combine)
sparse(IJ::AbstractVector{<:CartesianIndex{2}},v::Number,m,n,combine::Function) = sparse(reinterpret_cartesian(IJ)..., v, m, n, combine)

## Transposition and permutation methods

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3 changes: 3 additions & 0 deletions test/sparsematrix_constructors_indexing.jl
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Expand Up @@ -52,6 +52,9 @@ end
SparseMatrixCSC(6, 6, big.([1,2,4,7,8,9,9]), big.([1,1,2,1,2,3,4,5]), big.([1,2,3,4,5,6,7,8])))
@test sparse(Any[1,2,3], Any[1,2,3], Any[1,1,1]) == sparse([1,2,3], [1,2,3], [1,1,1])
@test sparse(Any[1,2,3], Any[1,2,3], Any[1,1,1], 5, 4) == sparse([1,2,3], [1,2,3], [1,1,1], 5, 4)
@test_throws MethodError sparse([CartesianIndex(1, 1, 1), CartesianIndex(2, 2, 2), CartesianIndex(3, 3, 3)], [1, 2, 4], [1, 2, 3], 3, 3) # Only 2D indices should work
@test isequal(sparse([CartesianIndex(1, 1), CartesianIndex(2, 2), CartesianIndex(3, 3)], [1.0, 2.0, 3.0], 3, 3), sparse([1, 2, 3], [1, 2, 3], [1.0, 2.0, 3.0], 3, 3))
@test sparse([CartesianIndex(1, 1), CartesianIndex(2, 2), CartesianIndex(3, 3)], [1, 2, 3]) == sparse([1, 2, 3], [1, 2, 3], [1, 2, 3])
# with combine
@test sparse([1, 1, 2, 2, 2], [1, 2, 1, 2, 2], 1.0, 2, 2, +) == sparse([1, 1, 2, 2], [1, 2, 1, 2], [1.0, 1.0, 1.0, 2.0], 2, 2)
@test sparse([1, 1, 2, 2, 2], [1, 2, 1, 2, 2], -1.0, 2, 2, *) == sparse([1, 1, 2, 2], [1, 2, 1, 2], [-1.0, -1.0, -1.0, 1.0], 2, 2)
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