Simplified truncated SVD with logical indexing

Project.toml

@@ -1,7 +1,7 @@
 name = "BlockSparseArrays"
 uuid = "2c9a651f-6452-4ace-a6ac-809f4280fbb4"
 authors = ["ITensor developers <[email protected]> and contributors"]
-version = "0.6.9"
+version = "0.7.0"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"

docs/Project.toml

@@ -6,6 +6,6 @@ Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
 
 [compat]
 BlockArrays = "1"
-BlockSparseArrays = "0.6"
+BlockSparseArrays = "0.7"
 Documenter = "1"
 Literate = "2"

examples/Project.toml

@@ -5,5 +5,5 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
 BlockArrays = "1"
-BlockSparseArrays = "0.6"
+BlockSparseArrays = "0.7"
 Test = "1"

src/blocksparsearrayinterface/blocksparsearrayinterface.jl

@@ -432,9 +432,11 @@ function Base.isassigned(a::SparseSubArrayBlocks{<:Any,N}, I::Vararg{Int,N}) whe
 end
 
 function SparseArraysBase.eachstoredindex(::IndexCartesian, a::SparseSubArrayBlocks)
-  return filter(eachindex(a)) do I
+  isempty(a) && return CartesianIndex{ndims(a)}[]
+  inds = filter(eachindex(a)) do I
     return isstored(a, I)
   end
+  return inds
 
   ## # TODO: This only works for blockwise slices, i.e. slices using
   ## # `BlockSliceCollection`.

src/factorizations/truncation.jl

@@ -45,69 +45,11 @@ function MatrixAlgebraKit.findtruncated(
   return indexmask
 end
 
-function similar_truncate(
-  ::typeof(svd_trunc!),
-  (U, S, Vᴴ)::TBlockUSVᴴ,
-  strategy::BlockPermutedDiagonalTruncationStrategy,
-  indexmask=MatrixAlgebraKit.findtruncated(diagview(S), strategy),
-)
-  ax = axes(S, 1)
-  counter = Base.Fix1(count, Base.Fix1(getindex, indexmask))
-  s_lengths = filter!(>(0), map(counter, blocks(ax)))
-  s_axis = blockedrange(s_lengths)
-  Ũ = similar(U, axes(U, 1), s_axis)
-  S̃ = similar(S, s_axis, s_axis)
-  Ṽᴴ = similar(Vᴴ, s_axis, axes(Vᴴ, 2))
-  return Ũ, S̃, Ṽᴴ
-end
-
 function MatrixAlgebraKit.truncate!(
   ::typeof(svd_trunc!),
   (U, S, Vᴴ)::TBlockUSVᴴ,
   strategy::BlockPermutedDiagonalTruncationStrategy,
 )
-  indexmask = MatrixAlgebraKit.findtruncated(diagview(S), strategy)
-
-  # first determine the block structure of the output to avoid having assumptions on the
-  # data structures
-  Ũ, S̃, Ṽᴴ = similar_truncate(svd_trunc!, (U, S, Vᴴ), strategy, indexmask)
-
-  # then loop over the blocks and assign the data
-  # TODO: figure out if we can presort and loop over the blocks -
-  # for now this has issues with missing blocks
-  bI_Us = collect(eachblockstoredindex(U))
-  bI_Ss = collect(eachblockstoredindex(S))
-  bI_Vᴴs = collect(eachblockstoredindex(Vᴴ))
-
-  I′ = 0 # number of skipped blocks that got fully truncated
-  ax = axes(S, 1)
-  for I in 1:blocksize(ax, 1)
-    b = ax[Block(I)]
-    mask = indexmask[b]
-
-    if !any(mask)
-      I′ += 1
-      continue
-    end
-
-    bU_id = @something findfirst(x -> last(Tuple(x)) == Block(I), bI_Us) error(
-      "No U-block found for $I"
-    )
-    bU = Tuple(bI_Us[bU_id])
-    Ũ[bU[1], bU[2] - Block(I′)] = view(U, bU...)[:, mask]
-
-    bVᴴ_id = @something findfirst(x -> first(Tuple(x)) == Block(I), bI_Vᴴs) error(
-      "No Vᴴ-block found for $I"
-    )
-    bVᴴ = Tuple(bI_Vᴴs[bVᴴ_id])
-    Ṽᴴ[bVᴴ[1] - Block(I′), bVᴴ[2]] = view(Vᴴ, bVᴴ...)[mask, :]
-
-    bS_id = findfirst(x -> last(Tuple(x)) == Block(I), bI_Ss)
-    if !isnothing(bS_id)
-      bS = Tuple(bI_Ss[bS_id])
-      S̃[(bS .- Block(I′))...] = Diagonal(diagview(view(S, bS...))[mask])
-    end
-  end
-
-  return Ũ, S̃, Ṽᴴ
+  I = MatrixAlgebraKit.findtruncated(diagview(S), strategy)
+  return (U[:, I], S[I, I], Vᴴ[I, :])
 end

test/Project.toml

@@ -23,7 +23,7 @@ Adapt = "4"
 Aqua = "0.8"
 ArrayLayouts = "1"
 BlockArrays = "1"
-BlockSparseArrays = "0.6"
+BlockSparseArrays = "0.7"
 DiagonalArrays = "0.3"
 GPUArraysCore = "0.2"
 JLArrays = "0.2"