Bump compat to TensorAlgebra 0.22 and GradedArrays 0.16.6

Project.toml

@@ -1,6 +1,6 @@
 name = "ITensorBase"
 uuid = "4795dd04-0d67-49bb-8f44-b89c448a1dc7"
-version = "0.15.0"
+version = "0.15.1"
 authors = ["ITensor developers <support@itensor.org> and contributors"]
 
 [workspace]
@@ -44,14 +44,14 @@ Adapt = "4.1.1"
 ArrayLayouts = "1.11"
 Combinatorics = "1"
 ConstructionBase = "1.6"
-GradedArrays = "0.16.5"
+GradedArrays = "0.16.6"
 LinearAlgebra = "1.10"
 MatrixAlgebraKit = "0.2, 0.3, 0.4, 0.5, 0.6"
 Mooncake = "0.4.202, 0.5"
 OMEinsumContractionOrders = "1.3"
 Random = "1.10"
 SimpleTraits = "0.9.4"
-TensorAlgebra = "0.21.1"
+TensorAlgebra = "0.22"
 TensorKit = "0.17"
 TensorKitSectors = "0.3.9"
 TermInterface = "2"

docs/Project.toml

@@ -16,5 +16,5 @@ ITensorBase = "0.15"
 ITensorFormatter = "0.2.27"
 Literate = "2"
 MatrixAlgebraKit = "0.2, 0.3, 0.4, 0.5, 0.6"
-TensorAlgebra = "0.21.1"
+TensorAlgebra = "0.22"
 Test = "1.10"

ext/ITensorBaseGradedArraysExt.jl

@@ -1,12 +1,42 @@
 module ITensorBaseGradedArraysExt
 
-using GradedArrays: SectorRange
+using GradedArrays: FusedGradedDiagonal, FusedGradedMatrix, SectorRange
 using ITensorBase: ITensorBase, NamedTensor, name, uniquename, unnamed
 using Random: AbstractRNG, default_rng
+using TensorAlgebra: TensorAlgebra as TA
 using TensorKitSectors: Sector
 
 const NamedUnitRange = ITensorBase.NamedUnitRange
 
+# GradedArrays defines `unmatricize` for its fused matrices with untyped axes, which ties with
+# ITensorBase's methods on named axes. Restate those for each fused matrix type so the named
+# unmatricize of a graded matrix has a unique most-specific method.
+for M in (:FusedGradedMatrix, :FusedGradedDiagonal)
+    @eval begin
+        function TA.unmatricize(
+                m::$M,
+                codomain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}},
+                domain::Tuple{Vararg{NamedUnitRange}}
+            )
+            return ITensorBase.unmatricize_namedtensor(m, codomain, domain)
+        end
+        function TA.unmatricize(
+                m::$M,
+                codomain::Tuple{Vararg{NamedUnitRange}},
+                domain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}}
+            )
+            return ITensorBase.unmatricize_namedtensor(m, codomain, domain)
+        end
+        function TA.unmatricize(
+                m::$M,
+                codomain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}},
+                domain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}}
+            )
+            return ITensorBase.unmatricize_namedtensor(m, codomain, domain)
+        end
+    end
+end
+
 # Flux-canceling constructors at the `Index` level: delegate to the GradedArrays flux backend on
 # the unnamed axes, then reattach names, so the flux convention lives only in the backend. The
 # sector may be a bare `TensorKitSectors.Sector` or a `SectorRange`; this is an extension because

ext/ITensorBaseTensorKitExt.jl

@@ -1,7 +1,33 @@
 module ITensorBaseTensorKitExt
 
 using ITensorBase: ITensorBase, NamedUnitRange
-using TensorKit: ElementarySpace, dim
+using TensorAlgebra: TensorAlgebra as TA
+using TensorKit: AbstractTensorMap, ElementarySpace, dim
+
+# TensorAlgebra's TensorKit extension defines `unmatricize` for `AbstractTensorMap` with untyped
+# axes, and a `TensorMap` is not an `AbstractMatrix`, so ITensorBase's named-axes methods do not
+# reach it. Restate them for `AbstractTensorMap`.
+function TA.unmatricize(
+        m::AbstractTensorMap,
+        codomain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}},
+        domain::Tuple{Vararg{NamedUnitRange}}
+    )
+    return ITensorBase.unmatricize_namedtensor(m, codomain, domain)
+end
+function TA.unmatricize(
+        m::AbstractTensorMap,
+        codomain::Tuple{Vararg{NamedUnitRange}},
+        domain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}}
+    )
+    return ITensorBase.unmatricize_namedtensor(m, codomain, domain)
+end
+function TA.unmatricize(
+        m::AbstractTensorMap,
+        codomain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}},
+        domain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}}
+    )
+    return ITensorBase.unmatricize_namedtensor(m, codomain, domain)
+end
 
 # ================================  Index over a native space  ==============================
 # A native TensorKit space is stored directly as the axis value of a `NamedUnitRange`, so

src/tensoralgebra.jl

@@ -108,23 +108,24 @@ end
 # Unmatricize an unnamed matrix into the named `codomain`/`domain` axes, giving a named tensor.
 # `Tuple{Vararg{NamedUnitRange}}` also matches an empty tuple, so demanding at least one named
 # axis across the two groups takes three methods: one per group, plus the both-nonempty case
-# that resolves the ambiguity between them.
+# that resolves the ambiguity between them. `m::AbstractMatrix` keeps these more specific than
+# TensorAlgebra's `unmatricize(::AbstractMatrix, axes_codomain, axes_domain)`.
 function TA.unmatricize(
-        m,
+        m::AbstractMatrix,
         codomain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}},
         domain::Tuple{Vararg{NamedUnitRange}}
     )
     return unmatricize_namedtensor(m, codomain, domain)
 end
 function TA.unmatricize(
-        m,
+        m::AbstractMatrix,
         codomain::Tuple{Vararg{NamedUnitRange}},
         domain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}}
     )
     return unmatricize_namedtensor(m, codomain, domain)
 end
 function TA.unmatricize(
-        m,
+        m::AbstractMatrix,
         codomain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}},
         domain::Tuple{NamedUnitRange, Vararg{NamedUnitRange}}
     )

test/Project.toml

@@ -32,7 +32,7 @@ AbstractTrees = "0.4.5"
 Adapt = "4"
 Aqua = "0.8.9"
 Combinatorics = "1"
-GradedArrays = "0.16.5"
+GradedArrays = "0.16.6"
 ITensorBase = "0.15"
 ITensorPkgSkeleton = "0.3.42"
 JLArrays = "0.2, 0.3"
@@ -44,7 +44,7 @@ Random = "1.10"
 SafeTestsets = "0.1"
 StableRNGs = "1"
 Suppressor = "0.2"
-TensorAlgebra = "0.21.1"
+TensorAlgebra = "0.22"
 TensorKit = "0.17"
 TensorKitSectors = "0.3.9"
 TermInterface = "2"