Remove usage of GradedUnitRanges

Project.toml

@@ -1,7 +1,7 @@
 name = "BlockSparseArrays"
 uuid = "2c9a651f-6452-4ace-a6ac-809f4280fbb4"
 authors = ["ITensor developers <[email protected]> and contributors"]
-version = "0.3.9"
+version = "0.4.0"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
@@ -12,7 +12,6 @@ DiagonalArrays = "74fd4be6-21e2-4f6f-823a-4360d37c7a77"
 Dictionaries = "85a47980-9c8c-11e8-2b9f-f7ca1fa99fb4"
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 GPUArraysCore = "46192b85-c4d5-4398-a991-12ede77f4527"
-GradedUnitRanges = "e2de450a-8a67-46c7-b59c-01d5a3d041c5"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 MapBroadcast = "ebd9b9da-f48d-417c-9660-449667d60261"
@@ -22,11 +21,9 @@ TypeParameterAccessors = "7e5a90cf-f82e-492e-a09b-e3e26432c138"
 
 [weakdeps]
 TensorAlgebra = "68bd88dc-f39d-4e12-b2ca-f046b68fcc6a"
-TensorProducts = "decf83d6-1968-43f4-96dc-fdb3fe15fc6d"
 
 [extensions]
-BlockSparseArraysGradedUnitRangesExt = "GradedUnitRanges"
-BlockSparseArraysTensorAlgebraExt = ["TensorProducts", "TensorAlgebra"]
+BlockSparseArraysTensorAlgebraExt = "TensorAlgebra"
 
 [compat]
 Adapt = "4.1.1"
@@ -38,14 +35,12 @@ DiagonalArrays = "0.3"
 Dictionaries = "0.4.3"
 FillArrays = "1.13.0"
 GPUArraysCore = "0.1.0, 0.2"
-GradedUnitRanges = "0.2.2"
 LinearAlgebra = "1.10"
 MacroTools = "0.5.13"
 MapBroadcast = "0.1.5"
 SparseArraysBase = "0.5"
 SplitApplyCombine = "1.2.3"
 TensorAlgebra = "0.2.4"
-TensorProducts = "0.1.2"
 Test = "1.10"
 TypeParameterAccessors = "0.2.0, 0.3"
 julia = "1.10"

docs/Project.toml

@@ -6,6 +6,6 @@ Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
 
 [compat]
 BlockArrays = "1"
-BlockSparseArrays = "0.3"
+BlockSparseArrays = "0.4"
 Documenter = "1"
 Literate = "2"

examples/Project.toml

@@ -5,5 +5,5 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
 BlockArrays = "1"
-BlockSparseArrays = "0.3"
+BlockSparseArrays = "0.4"
 Test = "1"

ext/BlockSparseArraysTensorAlgebraExt/BlockSparseArraysTensorAlgebraExt.jl

@@ -1,10 +1,8 @@
 module BlockSparseArraysTensorAlgebraExt
-using BlockArrays: AbstractBlockedUnitRange
-
-using TensorAlgebra: TensorAlgebra, FusionStyle, BlockReshapeFusion
-using TensorProducts: OneToOne
 
+using BlockArrays: AbstractBlockedUnitRange
 using BlockSparseArrays: AbstractBlockSparseArray, blockreshape
+using TensorAlgebra: TensorAlgebra, FusionStyle, BlockReshapeFusion
 
 TensorAlgebra.FusionStyle(::AbstractBlockedUnitRange) = BlockReshapeFusion()
 
@@ -20,99 +18,4 @@ function TensorAlgebra.splitdims(
   return blockreshape(a, axes)
 end
 
-using BlockArrays:
-  AbstractBlockVector,
-  AbstractBlockedUnitRange,
-  Block,
-  BlockIndexRange,
-  blockedrange,
-  blocks
-using BlockSparseArrays:
-  BlockSparseArrays,
-  AbstractBlockSparseArray,
-  AbstractBlockSparseArrayInterface,
-  AbstractBlockSparseMatrix,
-  BlockSparseArray,
-  BlockSparseArrayInterface,
-  BlockSparseMatrix,
-  BlockSparseVector,
-  block_merge
-using DerivableInterfaces: @interface
-using GradedUnitRanges:
-  GradedUnitRanges,
-  AbstractGradedUnitRange,
-  blockmergesortperm,
-  blocksortperm,
-  dual,
-  invblockperm,
-  nondual,
-  unmerged_tensor_product
-using LinearAlgebra: Adjoint, Transpose
-using TensorAlgebra:
-  TensorAlgebra, FusionStyle, BlockReshapeFusion, SectorFusion, fusedims, splitdims
-
-# TODO: Make a `ReduceWhile` library.
-include("reducewhile.jl")
-
-TensorAlgebra.FusionStyle(::AbstractGradedUnitRange) = SectorFusion()
-
-# TODO: Need to implement this! Will require implementing
-# `block_merge(a::AbstractUnitRange, blockmerger::BlockedUnitRange)`.
-function BlockSparseArrays.block_merge(
-  a::AbstractGradedUnitRange, blockmerger::AbstractBlockedUnitRange
-)
-  return a
-end
-
-# Sort the blocks by sector and then merge the common sectors.
-function block_mergesort(a::AbstractArray)
-  I = blockmergesortperm.(axes(a))
-  return a[I...]
-end
-
-function TensorAlgebra.fusedims(
-  ::SectorFusion, a::AbstractArray, merged_axes::AbstractUnitRange...
-)
-  # First perform a fusion using a block reshape.
-  # TODO avoid groupreducewhile. Require refactor of fusedims.
-  unmerged_axes = groupreducewhile(
-    unmerged_tensor_product, axes(a), length(merged_axes); init=OneToOne()
-  ) do i, axis
-    return length(axis) ≤ length(merged_axes[i])
-  end
-
-  a_reshaped = fusedims(BlockReshapeFusion(), a, unmerged_axes...)
-  # Sort the blocks by sector and merge the equivalent sectors.
-  return block_mergesort(a_reshaped)
-end
-
-function TensorAlgebra.splitdims(
-  ::SectorFusion, a::AbstractArray, split_axes::AbstractUnitRange...
-)
-  # First, fuse axes to get `blockmergesortperm`.
-  # Then unpermute the blocks.
-  axes_prod = groupreducewhile(
-    unmerged_tensor_product, split_axes, ndims(a); init=OneToOne()
-  ) do i, axis
-    return length(axis) ≤ length(axes(a, i))
-  end
-  blockperms = blocksortperm.(axes_prod)
-  sorted_axes = map((r, I) -> only(axes(r[I])), axes_prod, blockperms)
-
-  # TODO: This is doing extra copies of the blocks,
-  # use `@view a[axes_prod...]` instead.
-  # That will require implementing some reindexing logic
-  # for this combination of slicing.
-  a_unblocked = a[sorted_axes...]
-  a_blockpermed = a_unblocked[invblockperm.(blockperms)...]
-  return splitdims(BlockReshapeFusion(), a_blockpermed, split_axes...)
-end
-
-# TODO: Handle this through some kind of trait dispatch, maybe
-# a `SymmetryStyle`-like trait to check if the block sparse
-# matrix has graded axes.
-function Base.axes(a::Adjoint{<:Any,<:AbstractBlockSparseMatrix})
-  return dual.(reverse(axes(a')))
-end
-
 end

src/BlockArraysExtensions/BlockArraysExtensions.jl

@@ -20,7 +20,6 @@ using BlockArrays:
   findblock,
   findblockindex
 using Dictionaries: Dictionary, Indices
-using GradedUnitRanges: blockedunitrange_getindices, to_blockindices
 using SparseArraysBase:
   SparseArraysBase,
   eachstoredindex,