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similar(::SparseMatrixCSC, dims) returns sparse matrix with empty space (#26560) #30435

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added sprandn methods with Type
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similar on sparse matrix returns empty space
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similar of SparseVector producing SparseMatrixCSC
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similar to preserve non-zero structure as far as possible
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empty rowval and nzval
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45 changes: 41 additions & 4 deletions stdlib/SparseArrays/src/sparsematrix.jl
Original file line number Diff line number Diff line change
Expand Up @@ -327,17 +327,54 @@ function _sparsesimilar(S::SparseMatrixCSC, ::Type{TvNew}, ::Type{TiNew}) where
newrowval = copyto!(similar(S.rowval, TiNew), S.rowval)
return SparseMatrixCSC(S.m, S.n, newcolptr, newrowval, similar(S.nzval, TvNew))
end
# parent methods for similar that preserves only storage space (for when new and old dims differ)
# parent methods for similar that allocates an empty matrix (for when new dims are
# two-dimensional).
_sparsesimilar(S::SparseMatrixCSC, ::Type{TvNew}, ::Type{TiNew}, dims::Dims{2}) where {TvNew,TiNew} =
SparseMatrixCSC(dims..., fill(one(TiNew), last(dims)+1), similar(S.rowval, TiNew), similar(S.nzval, TvNew))
SparseMatrixCSC(dims..., fill(one(TiNew), last(dims)+1), similar(S.rowval, TiNew, 0), similar(S.nzval, TvNew, 0))
#=
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# parent methods for similar that as far as possible preserves stored-entry structure
# (for when new dims are two-dimensional).
function _sparsesimilar(S::SparseMatrixCSC, ::Type{TvNew}, ::Type{TiNew}, dims::Dims{2}) where {TvNew,TiNew}

m, n = dims
mx = S.colptr[S.n+1]
newcolptr = copyto!(similar(S.colptr, TiNew, n+1), 1, S.colptr, 1, min(n,S.n)+1)
for i = S.n+2:n+1
newcolptr[i] = mx
end
nz = mx - 1
newrowval = copyto!(similar(S.rowval, TiNew, nz), 1, S.rowval, 1, nz)
if m < S.m
offset = 0
start = newcolptr[1]
for k = 1:n
for j = start:newcolptr[k+1]-1
if newrowval[j] > m
offset += 1
end
end
start = newcolptr[k+1]
newcolptr[k+1] -= offset
end
deleteat!(newrowval, findall(x->x>m, view(newrowval,1:nz)))
nz -= offset
end
xnz = min(max(nz, length(S.rowval)), n * m)
if length(newrowval) != xnz
resize!(newrowval, xnz)
end
ynz = min(max(nz, length(S.nzval)), n * m)
return SparseMatrixCSC(m, n, newcolptr, newrowval, similar(S.nzval, TvNew, ynz))
end
=#
# parent method for similar that allocates an empty sparse vector (when new dims are single)
_sparsesimilar(S::SparseMatrixCSC, ::Type{TvNew}, ::Type{TiNew}, dims::Dims{1}) where {TvNew,TiNew} =
SparseVector(dims..., similar(S.rowval, TiNew, 0), similar(S.nzval, TvNew, 0))
#
# The following methods hook into the AbstractArray similar hierarchy. The first method
# covers similar(A[, Tv]) calls, which preserve stored-entry structure, and the latter
# methods cover similar(A[, Tv], shape...) calls, which preserve storage space when the shape
# calls for a two-dimensional result.
# methods cover similar(A[, Tv], shape...) calls, whith partially presevrved structure
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# when the shape calls for a two-dimensional result.
similar(S::SparseMatrixCSC{<:Any,Ti}, ::Type{TvNew}) where {Ti,TvNew} = _sparsesimilar(S, TvNew, Ti)
similar(S::SparseMatrixCSC{<:Any,Ti}, ::Type{TvNew}, dims::Union{Dims{1},Dims{2}}) where {Ti,TvNew} =
_sparsesimilar(S, TvNew, Ti, dims)
Expand Down
10 changes: 4 additions & 6 deletions stdlib/SparseArrays/src/sparsevector.jl
Original file line number Diff line number Diff line change
Expand Up @@ -67,22 +67,20 @@ _sparsesimilar(S::SparseVector, ::Type{TvNew}, ::Type{TiNew}) where {TvNew,TiNew
# parent method for similar that preserves nothing (for when old and new dims differ, and new is 1d)
_sparsesimilar(S::SparseVector, ::Type{TvNew}, ::Type{TiNew}, dims::Dims{1}) where {TvNew,TiNew} =
SparseVector(dims..., similar(S.nzind, TiNew, 0), similar(S.nzval, TvNew, 0))
# parent method for similar that preserves storage space (for old and new dims differ, and new is 2d)
# parent method for similar with emtpy storage space (for old and new dims differ, and new is 2d)
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_sparsesimilar(S::SparseVector, ::Type{TvNew}, ::Type{TiNew}, dims::Dims{2}) where {TvNew,TiNew} =
SparseMatrixCSC(dims..., fill(one(TiNew), last(dims)+1), similar(S.nzind, TiNew), similar(S.nzval, TvNew))
SparseMatrixCSC(dims..., fill(one(TiNew), last(dims)+1), similar(S.nzind, TiNew, 0), similar(S.nzval, TvNew, 0))
# The following methods hook into the AbstractArray similar hierarchy. The first method
# covers similar(A[, Tv]) calls, which preserve stored-entry structure, and the latter
# methods cover similar(A[, Tv], shape...) calls, which preserve nothing if the dims
# specify a SparseVector result and storage space if the dims specify a SparseMatrixCSC result.
# specify a SparseVector or a SparseMatrixCSC result.
similar(S::SparseVector{<:Any,Ti}, ::Type{TvNew}) where {Ti,TvNew} =
_sparsesimilar(S, TvNew, Ti)
similar(S::SparseVector{<:Any,Ti}, ::Type{TvNew}, dims::Union{Dims{1},Dims{2}}) where {Ti,TvNew} =
_sparsesimilar(S, TvNew, Ti, dims)
# The following methods cover similar(A, Tv, Ti[, shape...]) calls, which specify the
# result's index type in addition to its entry type, and aren't covered by the hooks above.
# The calls without shape again preserve stored-entry structure, whereas those with
# one-dimensional shape preserve nothing, and those with two-dimensional shape
# preserve storage space.
# The calls without shape again preserve stored-entry structure but no storage space.
similar(S::SparseVector, ::Type{TvNew}, ::Type{TiNew}) where{TvNew,TiNew} =
_sparsesimilar(S, TvNew, TiNew)
similar(S::SparseVector, ::Type{TvNew}, ::Type{TiNew}, dims::Union{Dims{1},Dims{2}}) where {TvNew,TiNew} =
Expand Down
18 changes: 9 additions & 9 deletions stdlib/SparseArrays/test/sparse.jl
Original file line number Diff line number Diff line change
Expand Up @@ -2132,7 +2132,7 @@ end
@test typeof(similar(A, ComplexF64, Int)) == SparseMatrixCSC{ComplexF64, Int}
@test size(similar(A, ComplexF64, Int8)) == (5, 5)
@test typeof(similar(A, ComplexF64, Int8)) == SparseMatrixCSC{ComplexF64, Int8}
@test similar(A, ComplexF64,(6, 6)) == spzeros(ComplexF64, 6, 6)
@test_broken size(similar(A, ComplexF64,(6, 6))) == spzeros(ComplexF64, 6, 6)
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@test convert(Matrix, A) == Array(A) # lolwut, are you lost, test?
end

Expand All @@ -2159,27 +2159,27 @@ end
@test simA.colptr == A.colptr
@test simA.rowval == A.rowval
@test length(simA.nzval) == length(A.nzval)
# test similar with Dims{2} specification (preserves storage space only, not stored-entry structure)
# test similar with Dims{2} specification (empty storage space, not stored-entry structure)
simA = similar(A, (6,6))
@test typeof(simA) == typeof(A)
@test size(simA) == (6,6)
@test simA.colptr == fill(1, 6+1)
@test length(simA.rowval) == length(A.rowval)
@test length(simA.nzval) == length(A.nzval)
# test similar with entry type and Dims{2} specification (preserves storage space only)
@test length(simA.rowval) == 0 # length(A.rowval)
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@test length(simA.nzval) == 0 # length(A.nzval)
# test similar with entry type and Dims{2} specification (empty storage space)
simA = similar(A, Float32, (6,6))
@test typeof(simA) == SparseMatrixCSC{Float32,eltype(A.colptr)}
@test size(simA) == (6,6)
@test simA.colptr == fill(1, 6+1)
@test length(simA.rowval) == length(A.rowval)
@test length(simA.nzval) == length(A.nzval)
@test length(simA.rowval) == 0 # length(A.rowval)
@test length(simA.nzval) == 0 # length(A.nzval)
# test similar with entry type, index type, and Dims{2} specification (preserves storage space only)
simA = similar(A, Float32, Int8, (6,6))
@test typeof(simA) == SparseMatrixCSC{Float32, Int8}
@test size(simA) == (6,6)
@test simA.colptr == fill(1, 6+1)
@test length(simA.rowval) == length(A.rowval)
@test length(simA.nzval) == length(A.nzval)
@test length(simA.rowval) == 0 # length(A.rowval)
@test length(simA.nzval) == 0 # length(A.nzval)
# test similar with Dims{1} specification (preserves nothing)
simA = similar(A, (6,))
@test typeof(simA) == SparseVector{eltype(A.nzval),eltype(A.colptr)}
Expand Down
12 changes: 6 additions & 6 deletions stdlib/SparseArrays/test/sparsevector.jl
Original file line number Diff line number Diff line change
Expand Up @@ -1229,22 +1229,22 @@ end
@test typeof(simA) == SparseMatrixCSC{eltype(A.nzval),eltype(A.nzind)}
@test size(simA) == (6,6)
@test simA.colptr == fill(1, 6+1)
@test length(simA.rowval) == length(A.nzind)
@test length(simA.nzval) == length(A.nzval)
@test length(simA.rowval) == 0 # length(A.nzind)
@test length(simA.nzval) == 0 # length(A.nzval)
# test similar with entry type and Dims{2} specification (preserves storage space only)
simA = similar(A, Float32, (6,6))
@test typeof(simA) == SparseMatrixCSC{Float32,eltype(A.nzind)}
@test size(simA) == (6,6)
@test simA.colptr == fill(1, 6+1)
@test length(simA.rowval) == length(A.nzind)
@test length(simA.nzval) == length(A.nzval)
@test length(simA.rowval) == 0 # length(A.nzind)
@test length(simA.nzval) == 0 # length(A.nzval)
# test similar with entry type, index type, and Dims{2} specification (preserves storage space only)
simA = similar(A, Float32, Int8, (6,6))
@test typeof(simA) == SparseMatrixCSC{Float32, Int8}
@test size(simA) == (6,6)
@test simA.colptr == fill(1, 6+1)
@test length(simA.rowval) == length(A.nzind)
@test length(simA.nzval) == length(A.nzval)
@test length(simA.rowval) == 0 # length(A.nzind)
@test length(simA.nzval) == 0 # length(A.nzval)
end

@testset "Fast operations on full column views" begin
Expand Down