Support TensorAlgebra 0.14 graded contraction and add!

Project.toml

@@ -1,6 +1,6 @@
 name = "GradedArrays"
 uuid = "bc96ca6e-b7c8-4bb6-888e-c93f838762c2"
-version = "0.13.1"
+version = "0.13.2"
 authors = ["ITensor developers <support@itensor.org> and contributors"]
 
 [workspace]
@@ -18,6 +18,7 @@ MatrixAlgebraKit = "6c742aac-3347-4629-af66-fc926824e5e4"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SparseArraysBase = "0d5efcca-f356-4864-8770-e1ed8d78f208"
 SplitApplyCombine = "03a91e81-4c3e-53e1-a0a4-9c0c8f19dd66"
+StridedViews = "4db3bf67-4bd7-4b4e-b153-31dc3fb37143"
 TensorAlgebra = "68bd88dc-f39d-4e12-b2ca-f046b68fcc6a"
 TensorKitSectors = "13a9c161-d5da-41f0-bcbd-e1a08ae0647f"
 
@@ -40,6 +41,7 @@ Random = "1.10"
 SUNRepresentations = "0.3, 0.4"
 SparseArraysBase = "0.10"
 SplitApplyCombine = "1.2.3"
-TensorAlgebra = "0.12.4, 0.13"
+StridedViews = "0.5"
+TensorAlgebra = "0.14"
 TensorKitSectors = "0.3"
 julia = "1.10"

src/fusion.jl

@@ -159,8 +159,10 @@ function TensorAlgebra.unmatricize(
     if isempty(codomain_axes) && isempty(domain_axes)
         # Scalar (rank-0) result: only the trivial-sector block contributes, and
         # `cod ∩ dom = {trivial}` for a fused scalar means `m.blocks` is at most
-        # one 1×1 entry. Return a 0-D `Array` matching the eltype.
-        a = fill(zero(eltype(m)))
+        # one 1×1 entry. Return a graded rank-0 array, like the result at every other
+        # rank, so the permute-add back into the destination dispatches to the graded
+        # `bipermutedimsopadd!` overload rather than the generic strided path.
+        a = zero!(similar(m, ()))
         triv = trivial(sectortype(m))
         haskey(m.blocks, triv) && (a[] = m.blocks[triv][1, 1])
         return a

src/tensoralgebra.jl

@@ -1,4 +1,5 @@
 using SplitApplyCombine: groupcount
+using StridedViews: StridedViews
 
 function tensor_product(r1, r2, r3, rs...)
     return tensor_product(tensor_product(r1, r2), r3, rs...)
@@ -173,6 +174,12 @@ function TensorAlgebra.bipermutedimsopadd!(
     return y
 end
 
+# An abelian sector array's dense form is its data block (each abelian sector is
+# one-dimensional, so the structural sector-delta factor is an identity selection).
+# Wrapping it as a `StridedView` of its data lets it flow through the generic strided
+# permute-add path when the other operand is a plain dense array.
+StridedViews.StridedView(a::AbelianSectorArray) = StridedViews.StridedView(data(a))
+
 function TensorAlgebra.bipermutedimsopadd!(
         y::AbstractGradedArray{<:Any, <:Any, N}, op, x::AbstractGradedArray{<:Any, <:Any, N},
         perm_codomain, perm_domain,

test/Project.toml

@@ -32,7 +32,7 @@ SUNRepresentations = "0.3, 0.4"
 SafeTestsets = "0.1"
 SparseArraysBase = "0.10"
 Suppressor = "0.2.8"
-TensorAlgebra = "0.12.4, 0.13"
+TensorAlgebra = "0.14"
 TensorKitSectors = "0.3"
 Test = "1.10"
 TestExtras = "0.3.1"

test/test_tensoralgebra.jl

@@ -338,7 +338,7 @@ end
     @test isdual(col)
 
     # A rank-0 graded array matricizes to a 1×1 trivial-sector `FusedGradedMatrix`,
-    # and unmatricizing back recovers the scalar.
+    # and unmatricizing back recovers the scalar as a rank-0 graded array.
     a = AbelianGradedArray{Float64, U1, 0, Array{Float64, 0}}(undef, ())
     a[] = 4.0
     m = matricize(GradedArrays.SectorFusion(), a, Val(0))
@@ -347,7 +347,7 @@ end
     @test data(m[Block(1, 1)]) == fill(4.0, 1, 1)
 
     back = unmatricize(GradedArrays.SectorFusion(), m, (), ())
-    @test back isa Array{Float64, 0}
+    @test back isa AbelianGradedArray{Float64, <:Any, 0}
     @test back[] == 4.0
 end