Make sparsearrays an ext

Fixes #447
JuliaArrays · Jul 27, 2024 · cb614b5 · cb614b5
1 parent ac0b31a
commit cb614b5
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Showing 3 changed files with 42 additions and 35 deletions.
diff --git a/Project.toml b/Project.toml
@@ -5,8 +5,6 @@ version = "7.12.0"
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
-SuiteSparse = "4607b0f0-06f3-5cda-b6b1-a6196a1729e9"
 
 [weakdeps]
 BandedMatrices = "aae01518-5342-5314-be14-df237901396f"
@@ -16,6 +14,7 @@ CUDSS = "45b445bb-4962-46a0-9369-b4df9d0f772e"
 ChainRules = "082447d4-558c-5d27-93f4-14fc19e9eca2"
 GPUArraysCore = "46192b85-c4d5-4398-a991-12ede77f4527"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
+SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 StaticArraysCore = "1e83bf80-4336-4d27-bf5d-d5a4f845583c"
 Tracker = "9f7883ad-71c0-57eb-9f7f-b5c9e6d3789c"
 
@@ -27,6 +26,7 @@ ArrayInterfaceCUDSSExt = "CUDSS"
 ArrayInterfaceChainRulesExt = "ChainRules"
 ArrayInterfaceGPUArraysCoreExt = "GPUArraysCore"
 ArrayInterfaceReverseDiffExt = "ReverseDiff"
+ArrayInterfaceSparseArraysExt = "SparseArrays"
 ArrayInterfaceStaticArraysCoreExt = "StaticArraysCore"
 ArrayInterfaceTrackerExt = "Tracker"
 
@@ -42,7 +42,6 @@ LinearAlgebra = "1.10"
 ReverseDiff = "1"
 SparseArrays = "1.10"
 StaticArraysCore = "1"
-SuiteSparse = "1.10"
 Tracker = "0.2"
 julia = "1.10"
 

diff --git a/ext/ArrayInterfaceSparseArraysExt.jl b/ext/ArrayInterfaceSparseArraysExt.jl
@@ -0,0 +1,38 @@
+module ArrayInterfaceSparseArraysExt
+
+import ArrayInterface: buffer, has_sparsestruct, issingular, findstructralnz, bunchkaufman_instance, DEFAULT_CHOLESKY_PIVOT, cholesky_instance, ldlt_instance, lu_instance, qr_instance
+using ArrayInterface.LinearAlgebra
+using SparseArrays
+
+buffer(x::SparseMatrixCSC) = getfield(x, :nzval)
+buffer(x::SparseVector) = getfield(x, :nzval)
+has_sparsestruct(::Type{<:SparseMatrixCSC}) = true
+issingular(A::AbstractSparseMatrix) = !issuccess(lu(A, check = false))
+
+function findstructralnz(x::SparseMatrixCSC)
+    rowind, colind, _ = findnz(x)
+    (rowind, colind)
+end
+
+function bunchkaufman_instance(A::SparseMatrixCSC)
+    bunchkaufman(sparse(similar(A, 1, 1)), check = false)
+end
+
+function cholesky_instance(A::Union{SparseMatrixCSC,Symmetric{<:Number,<:SparseMatrixCSC}}, pivot = DEFAULT_CHOLESKY_PIVOT)
+    cholesky(sparse(similar(A, 1, 1)), check = false)
+end
+
+function ldlt_instance(A::SparseMatrixCSC)
+    ldlt(sparse(similar(A, 1, 1)), check=false)
+end
+
+# Could be optimized but this should work for any real case.
+function lu_instance(jac_prototype::SparseMatrixCSC, pivot = DEFAULT_CHOLESKY_PIVOT)
+    lu(sparse(rand(1,1)))
+end
+
+function qr_instance(jac_prototype::SparseMatrixCSC, pivot = DEFAULT_CHOLESKY_PIVOT)
+    qr(sparse(rand(1,1)))
+end
+
+end
diff --git a/src/ArrayInterface.jl b/src/ArrayInterface.jl
@@ -1,8 +1,6 @@
 module ArrayInterface
 
 using LinearAlgebra
-using SparseArrays
-using SuiteSparse
 
 @static if isdefined(Base, Symbol("@assume_effects"))
     using Base: @assume_effects
@@ -121,8 +119,6 @@ Return the buffer data that `x` points to. Unlike `parent(x::AbstractArray)`, `b
 may not return another array type.
 """
 buffer(x) = parent(x)
-buffer(x::SparseMatrixCSC) = getfield(x, :nzval)
-buffer(x::SparseVector) = getfield(x, :nzval)
 buffer(@nospecialize x::Union{Base.Slice, Base.IdentityUnitRange}) = getfield(x, :indices)
 
 """
@@ -308,7 +304,6 @@ Determine whether `findstructralnz` accepts the parameter `x`.
 has_sparsestruct(x) = has_sparsestruct(typeof(x))
 has_sparsestruct(::Type) = false
 has_sparsestruct(::Type{<:AbstractArray}) = false
-has_sparsestruct(::Type{<:SparseMatrixCSC}) = true
 has_sparsestruct(::Type{<:Diagonal}) = true
 has_sparsestruct(::Type{<:Bidiagonal}) = true
 has_sparsestruct(::Type{<:Tridiagonal}) = true
@@ -320,7 +315,6 @@ has_sparsestruct(::Type{<:SymTridiagonal}) = true
 Determine whether a given abstract matrix is singular.
 """
 issingular(A::AbstractMatrix) = issingular(Matrix(A))
-issingular(A::AbstractSparseMatrix) = !issuccess(lu(A, check = false))
 issingular(A::Matrix) = !issuccess(lu(A, check = false))
 issingular(A::UniformScaling) = A.λ == 0
 issingular(A::Diagonal) = any(iszero, A.diag)
@@ -359,11 +353,6 @@ function findstructralnz(x::Union{Tridiagonal, SymTridiagonal})
     (rowind, colind)
 end
 
-function findstructralnz(x::SparseMatrixCSC)
-    rowind, colind, _ = findnz(x)
-    (rowind, colind)
-end
-
 abstract type ColoringAlgorithm end
 
 """
@@ -403,9 +392,6 @@ cheaply.
 function bunchkaufman_instance(A::Matrix{T}) where T
     return bunchkaufman(similar(A, 0, 0), check = false)
 end
-function bunchkaufman_instance(A::SparseMatrixCSC)
-    bunchkaufman(sparse(similar(A, 1, 1)), check = false)
-end
 
 """
 bunchkaufman_instance(a::Number) -> a
@@ -429,14 +415,10 @@ cholesky_instance(A, pivot = LinearAlgebra.RowMaximum()) -> cholesky_factorizati
 Returns an instance of the Cholesky factorization object with the correct type
 cheaply.
 """
-function cholesky_instance(A::Matrix{T}, pivot = DEFAULT_CHOLESKY_PIVOT) where {T}  
+function cholesky_instance(A::Matrix{T}, pivot = DEFAULT_CHOLESKY_PIVOT) where {T}
     return cholesky(similar(A, 0, 0), pivot, check = false)
 end
 
-function cholesky_instance(A::Union{SparseMatrixCSC,Symmetric{<:Number,<:SparseMatrixCSC}}, pivot = DEFAULT_CHOLESKY_PIVOT)
-    cholesky(sparse(similar(A, 1, 1)), check = false)
-end
-
 """
 cholesky_instance(a::Number, pivot = LinearAlgebra.RowMaximum()) -> a
 
@@ -458,14 +440,10 @@ ldlt_instance(A) -> ldlt_factorization_instance
 Returns an instance of the LDLT factorization object with the correct type
 cheaply.
 """
-function ldlt_instance(A::Matrix{T}) where {T}  
+function ldlt_instance(A::Matrix{T}) where {T}
     return ldlt_instance(SymTridiagonal(similar(A, 0, 0)))
 end
 
-function ldlt_instance(A::SparseMatrixCSC)
-    ldlt(sparse(similar(A, 1, 1)), check=false)
-end
-
 function ldlt_instance(A::SymTridiagonal{T,V}) where {T,V}
     return LinearAlgebra.LDLt{T,SymTridiagonal{T,V}}(A)
 end
@@ -498,9 +476,6 @@ function lu_instance(A::Matrix{T}) where {T}
     info = zero(LinearAlgebra.BlasInt)
     return LU{luT}(similar(A, 0, 0), ipiv, info)
 end
-function lu_instance(jac_prototype::SparseMatrixCSC)
-    SuiteSparse.UMFPACK.UmfpackLU(similar(jac_prototype, 1, 1))
-end
 
 function lu_instance(A::Symmetric{T}) where {T}
     noUnitT = typeof(zero(T))
@@ -557,11 +532,6 @@ function qr_instance(A::Matrix{BigFloat},pivot = DEFAULT_CHOLESKY_PIVOT)
     LinearAlgebra.QR(zeros(BigFloat,0,0),zeros(BigFloat,0))
 end
 
-# Could be optimized but this should work for any real case.
-function qr_instance(jac_prototype::SparseMatrixCSC, pivot = DEFAULT_CHOLESKY_PIVOT)
-    qr(sparse(rand(1,1)))
-end
-
 """
   qr_instance(a::Number) -> a