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Add method for sparsecsr() that takes an AbstractMatrix #31

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Merged
JordiManyer merged 1 commit into from
Aug 6, 2025
Merged

Add method for sparsecsr() that takes an AbstractMatrix #31

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2 changes: 2 additions & 0 deletions src/SparseMatrixCSR.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -93,9 +93,11 @@ Create a `SparseMatrixCSR` with `Bi`-based indexing (1 by default)
from the same `args...` as one constructs a `SparseMatrixCSC`
with the [`SparseArrays.sparse`](@extref) function.
"""
sparsecsr(A::AbstractMatrix{T}) where T = convert(SparseMatrixCSR{1,T,Int64}, A)
sparsecsr(I,J,V) = SparseMatrixCSR(transpose(sparse(J,I,V,dimlub(J),dimlub(I))))
sparsecsr(I,J,V,m,n) = SparseMatrixCSR(transpose(sparse(J,I,V,n,m)))
sparsecsr(I,J,V,m,n,combine) = SparseMatrixCSR(transpose(sparse(J,I,V,n,m,combine)))
sparsecsr(::Val{Bi},A::AbstractMatrix{T}) where {Bi,T} = convert(SparseMatrixCSR{Bi,T,Int64}, A)
sparsecsr(::Val{Bi},I,J,V) where Bi = SparseMatrixCSR{Bi}(transpose(sparse(J,I,V,dimlub(J),dimlub(I))))
sparsecsr(::Val{Bi},I,J,V,m,n) where Bi = SparseMatrixCSR{Bi}(transpose(sparse(J,I,V,n,m)))
sparsecsr(::Val{Bi},I,J,V,m,n,combine) where Bi = SparseMatrixCSR{Bi}(transpose(sparse(J,I,V,n,m,combine)))
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12 changes: 12 additions & 0 deletions test/SparseMatrixCSR.jl
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Expand Up @@ -47,6 +47,18 @@ function test_csr(Bi,Tv,Ti)
end
end

if Ti == Int64
dense = rand(Tv, maxrows,maxcols)
CSR = sparsecsr(Val(Bi), dense)
@test isa(CSR,SparseMatrixCSR{Bi,Tv,Ti})
@test CSR == dense
if Bi == 1
CSR = sparsecsr(dense)
@test CSR == dense
@test isa(CSR,SparseMatrixCSR{Bi,Tv,Ti})
end
end

CSC = sparse(I,J,V,maxrows,maxcols)
if Bi == 1
CSR = sparsecsr(I,J,V,maxrows,maxcols)
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