Upgrade to TensorAlgebra.jl v0.7, NamedDimsArrays.jl v0.14

Project.toml

@@ -1,7 +1,7 @@
 name = "SparseArraysBase"
 uuid = "0d5efcca-f356-4864-8770-e1ed8d78f208"
 authors = ["ITensor developers <support@itensor.org> and contributors"]
-version = "0.9.0"
+version = "0.9.1"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"
@@ -35,10 +35,10 @@ FunctionImplementations = "0.4"
 GPUArraysCore = "0.2"
 LinearAlgebra = "1.10"
 MapBroadcast = "0.1.5"
-NamedDimsArrays = "0.13"
+NamedDimsArrays = "0.13, 0.14"
 Random = "1.10"
 SparseArrays = "1.10"
-TensorAlgebra = "0.6.2"
+TensorAlgebra = "0.6.2, 0.7"
 TypeParameterAccessors = "0.4.3"
 julia = "1.10"
 

ext/SparseArraysBaseNamedDimsArraysExt/SparseArraysBaseNamedDimsArraysExt.jl

@@ -1,7 +1,7 @@
 module SparseArraysBaseNamedDimsArraysExt
 
 using NamedDimsArrays: AbstractNamedDimsArray, AbstractNamedUnitRange, denamed, inds,
-    nameddims, nameddimsof
+    name, nameddims, nameddimsof
 using SparseArraysBase: SparseArraysBase, dense, oneelement
 
 function SparseArraysBase.dense(a::AbstractNamedDimsArray)
@@ -13,7 +13,7 @@ end
 function SparseArraysBase.oneelement(
         value, index::NTuple{N, Int}, ax::NTuple{N, AbstractNamedUnitRange}
     ) where {N}
-    return nameddims(oneelement(value, index, only.(axes.(denamed.(ax)))), ax)
+    return nameddims(oneelement(value, index, denamed.(ax)), name.(ax))
 end
 
 end

test/Project.toml

@@ -29,12 +29,12 @@ FillArrays = "1.13.0"
 FunctionImplementations = "0.4"
 JLArrays = "0.2.0, 0.3"
 LinearAlgebra = "<0.0.1, 1"
-NamedDimsArrays = "0.13"
+NamedDimsArrays = "0.13, 0.14"
 Random = "<0.0.1, 1"
 SafeTestsets = "0.1.0"
 SparseArrays = "1.10"
 SparseArraysBase = "0.9"
 StableRNGs = "1.0.2"
 Suppressor = "0.2.8"
-TensorAlgebra = "0.6"
+TensorAlgebra = "0.6, 0.7"
 Test = "<0.0.1, 1"

test/test_dense.jl

@@ -3,6 +3,21 @@ using JLArrays: JLArray
 using SparseArraysBase: dense, sparsezeros
 using Test: @test, @testset
 
+module TestDenseUtils
+    struct MySparseArrayDOK{T, N, S <: AbstractVector{T}} <: AbstractArray{T, N}
+        storedvalues::S
+        storedindices::Dict{CartesianIndex{N}, Int}
+        size::NTuple{N, Int}
+    end
+    Base.size(a::MySparseArrayDOK) = a.size
+    function Base.getindex(a::MySparseArrayDOK{<:Any, N}, I::Vararg{Int, N}) where {N}
+        storageindex = get(a.storedindices, CartesianIndex(I), nothing)
+        isnothing(storageindex) && return zero(eltype(a))
+        return a.storedvalues[storageindex]
+    end
+    Base.parent(a::MySparseArrayDOK) = a.storedvalues
+end
+
 elts = (Float32, ComplexF64)
 arrayts = (Array, JLArray)
 @testset "dense (arraytype=$arrayt, eltype=$elt)" for arrayt in arrayts, elt in elts
@@ -17,20 +32,7 @@ arrayts = (Array, JLArray)
     end
 
     @testset "Custom sparse array" begin
-        struct MySparseArrayDOK{T, N, S <: AbstractVector{T}} <: AbstractArray{T, N}
-            storedvalues::S
-            storedindices::Dict{CartesianIndex{N}, Int}
-            size::NTuple{N, Int}
-        end
-        Base.size(a::MySparseArrayDOK) = a.size
-        function Base.getindex(a::MySparseArrayDOK{<:Any, N}, I::Vararg{Int, N}) where {N}
-            storageindex = get(a.storedindices, CartesianIndex(I), nothing)
-            isnothing(storageindex) && return zero(eltype(a))
-            return a.storedvalues[storageindex]
-        end
-        Base.parent(a::MySparseArrayDOK) = a.storedvalues
-
-        s = MySparseArrayDOK(
+        s = TestDenseUtils.MySparseArrayDOK(
             dev(elt[2, 4]), Dict([CartesianIndex(1, 2) => 1, CartesianIndex(3, 4) => 2]), (3, 4)
         )
         d = dense(s)