Revise convert methods involving SparseMatrixCSCs, leveraging multipl…

…e dispatch to displace some type computations. (#17515)
JuliaLang · Jul 21, 2016 · 0ae8a95 · 0ae8a95
1 parent 188db66
commit 0ae8a95
Showing 1 changed file with 17 additions and 30 deletions.
diff --git a/base/sparse/sparsematrix.jl b/base/sparse/sparsematrix.jl
@@ -253,39 +253,26 @@ similar(S::SparseMatrixCSC, Tv::Type=eltype(S)) = SparseMatrixCSC(S.m, S.n, copy
 similar{Tv,Ti,TvNew,TiNew}(S::SparseMatrixCSC{Tv,Ti}, ::Type{TvNew}, ::Type{TiNew}) = SparseMatrixCSC(S.m, S.n, convert(Array{TiNew},S.colptr), convert(Array{TiNew}, S.rowval), Array{TvNew}(length(S.nzval)))
 @inline similar{Tv}(S::SparseMatrixCSC, ::Type{Tv}, d::Dims) = spzeros(Tv, d...)
 
-function convert{Tv,Ti,TvS,TiS}(::Type{SparseMatrixCSC{Tv,Ti}}, S::SparseMatrixCSC{TvS,TiS})
- if Tv == TvS && Ti == TiS
- return S
- else
- return SparseMatrixCSC(S.m, S.n,
- convert(Vector{Ti},S.colptr),
- convert(Vector{Ti},S.rowval),
- convert(Vector{Tv},S.nzval))
- end
-end
-
-function convert{Tv,TvS,TiS}(::Type{SparseMatrixCSC{Tv}}, S::SparseMatrixCSC{TvS,TiS})
- if Tv == TvS
- return S
- else
- return SparseMatrixCSC(S.m, S.n,
- S.colptr,
- S.rowval,
- convert(Vector{Tv},S.nzval))
- end
-end
-
+# convert'ing between SparseMatrixCSC types
+convert{Tv}(::Type{AbstractMatrix{Tv}}, A::SparseMatrixCSC) = convert(SparseMatrixCSC{Tv}, A)
+convert{Tv}(::Type{SparseMatrixCSC{Tv}}, S::SparseMatrixCSC) = convert(SparseMatrixCSC{Tv,eltype(S.colptr)}, S)
+convert{Tv,Ti}(::Type{SparseMatrixCSC{Tv,Ti}}, S::SparseMatrixCSC{Tv,Ti}) = S
+function convert{Tv,Ti}(::Type{SparseMatrixCSC{Tv,Ti}}, S::SparseMatrixCSC)
+ eltypeTicolptr = convert(Vector{Ti}, S.colptr)
+ eltypeTirowval = convert(Vector{Ti}, S.rowval)
+ eltypeTvnzval = convert(Vector{Tv}, S.nzval)
+ return SparseMatrixCSC(S.m, S.n, eltypeTicolptr, eltypeTirowval, eltypeTvnzval)
+end
+# convert'ing from other matrix types to SparseMatrixCSC (also see sparse())
+convert(::Type{SparseMatrixCSC}, M::Matrix) = sparse(M)
 function convert{Tv,Ti}(::Type{SparseMatrixCSC{Tv,Ti}}, M::AbstractMatrix)
- m, n = size(M)
  (I, J, V) = findnz(M)
- return sparse_IJ_sorted!(convert(Vector{Ti},I),
-  convert(Vector{Ti},J),
-  convert(Vector{Tv},V),
-  m, n)
+ eltypeTiI = convert(Vector{Ti}, I)
+ eltypeTiJ = convert(Vector{Ti}, J)
+ eltypeTvV = convert(Vector{Tv}, V)
+ return sparse_IJ_sorted!(eltypeTiI, eltypeTiJ, eltypeTvV, size(M)...)
 end
-convert{T}(::Type{AbstractMatrix{T}}, A::SparseMatrixCSC) = convert(SparseMatrixCSC{T}, A)
-convert(::Type{SparseMatrixCSC}, M::Matrix) = sparse(M)
-
+# convert'ing from SparseMatrixCSC to other matrix types
 function convert{Tv}(::Type{Matrix}, S::SparseMatrixCSC{Tv})
  # Handle cases where zero(Tv) is not defined but the array is dense.
  A = length(S) == nnz(S) ? Array{Tv}(S.m, S.n) : zeros(Tv, S.m, S.n)