v1.0

.github/workflows/CompatHelper.yml

@@ -15,7 +15,7 @@ jobs:
         run: which julia
         continue-on-error: true
       - name: Install Julia, but only if it is not already available in the PATH
-        uses: julia-actions/setup-julia@v1
+        uses: julia-actions/setup-julia@v2
         with:
           version: '1'
           arch: ${{ runner.arch }}

.github/workflows/ci.yml

@@ -46,7 +46,7 @@ jobs:
           - x64
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}

.github/workflows/docs.yml

@@ -26,12 +26,12 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: '1.10'
-      - uses: julia-actions/cache@v1
+      - uses: julia-actions/cache@v2
       - name: Install dependencies
-        run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
+        run: julia --project=docs/ -e 'using Pkg; Pkg.update(); Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
       - name: Build and deploy
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # If authenticating with GitHub Actions token

.github/workflows/downstream.yml

@@ -41,7 +41,7 @@ jobs:
 
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.julia-version }}
           arch: x64

.gitignore

@@ -9,4 +9,5 @@ src/.DS_Store
 Manifest.toml
 Manifest-v*.*.toml
 .DS_Store
+.*.swp
 build

Project.toml

@@ -1,19 +1,27 @@
 name = "BlockArrays"
 uuid = "8e7c35d0-a365-5155-bbbb-fb81a777f24e"
-version = "0.16.44-dev"
+version = "1.0.0"
 
 [deps]
 ArrayLayouts = "4c555306-a7a7-4459-81d9-ec55ddd5c99a"
+BandedMatrices = "aae01518-5342-5314-be14-df237901396f"
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 
+[weakdeps]
+BandedMatrices = "aae01518-5342-5314-be14-df237901396f"
+
+[extensions]
+BlockArraysBandedMatricesExt = "BandedMatrices"
+
 [compat]
 Aqua = "0.8"
 ArrayLayouts = "1.0.8"
-Documenter = "1"
-FillArrays = "1"
+BandedMatrices = "1.0"
+Documenter = "1.0"
+FillArrays = "1.11"
 LinearAlgebra = "1.6"
-OffsetArrays = "1"
+OffsetArrays = "1.0"
 Random = "1.6"
 SparseArrays = "1.6"
 StaticArrays = "1.6"
@@ -22,6 +30,7 @@ julia = "1.6"
 
 [extras]
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
+BandedMatrices = "aae01518-5342-5314-be14-df237901396f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
@@ -30,4 +39,4 @@ StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Aqua", "Documenter", "OffsetArrays", "SparseArrays", "StaticArrays", "Test", "Random"]
+test = ["Aqua", "BandedMatrices", "Documenter", "OffsetArrays", "SparseArrays", "StaticArrays", "Test", "Random"]

README.md

@@ -10,10 +10,12 @@
 
 A block array is a partition of an array into blocks or subarrays, see [wikipedia](https://en.wikipedia.org/wiki/Block_matrix) for a more extensive description. This package has two purposes. Firstly, it defines an interface for an `AbstractBlockArray` block arrays that can be shared among types representing different types of block arrays. The advantage to this is that it provides a consistent API for block arrays.
 
-Secondly, it also implements two different type of block arrays that follow the `AbstractBlockArray` interface. The type `BlockArray` stores each block contiguously while the type `PseudoBlockArray` stores the full matrix contiguously. This means that `BlockArray` supports fast non copying extraction and insertion of blocks while `PseudoBlockArray` supports fast access to the full matrix to use in in for example a linear solver.
+Secondly, it also implements two different type of block arrays that follow the `AbstractBlockArray` interface. The type `BlockArray` stores each block contiguously while the type `BlockedArray` stores the full matrix contiguously. This means that `BlockArray` supports fast non copying extraction and insertion of blocks while `BlockedArray` supports fast access to the full matrix to use in in for example a linear solver.
 
 A simple way to produce `BlockArray`s is via `mortar`, which combines an array of arrays into a `BlockArray`:
 ```julia
+julia> using BlockArrays
+
 julia> mortar([randn(3), randn(4)])
 2-blocked 7-element BlockVector{Float64}:
  -0.19808699390960527
@@ -33,11 +35,41 @@ julia> mortar(reshape([randn(2,2), randn(1,2), randn(2,3), randn(1,3)],2,2))
   0.430093  -0.0263753  │  -1.31275     0.278447  -0.139579
 ```
 
+Alternatively, one can add block structure on top of an existing array by wrapping the array in  `BlockedArray`, where the extra arguments give the sizes of the blocks:
+```julia
+julia> BlockedArray(randn(7), [3,4])
+2-blocked 7-element BlockedVector{Float64}:
+ -0.17348560551451797
+ -0.5680124317024628
+  1.699007590285868
+ ─────────────────────
+ -0.7437814954416642
+ -0.018198226033108045
+  1.3335354818213445
+ -0.03512135185007728
+
+julia> BlockedArray(randn(3,5), [2,1], [2,3])
+2×2-blocked 3×5 BlockedMatrix{Float64}:
+  0.444186   0.788823  │   0.743428  -0.815026   0.715779
+ -0.721074  -0.43783   │   1.07413   -0.336926   0.539873
+ ──────────────────────┼─────────────────────────────────
+  0.128836  -0.350202  │  -2.71365    1.67605   -0.25611
+```
+
+
 ## Documentation
 
 - [**STABLE**][docs-stable-url] — **most recently tagged version of the documentation.**
 - [**LATEST**][docs-dev-url] — *in-development version of the documentation.*
 
+## Changes in v1.0
+
+We are excited to release v1.0! There are some important breaking changes from previous versions of BlockArrays.jl:
+
+- `BlockedArray` replaces `PseudoBlockArray`.
+- Axes are now typically `BlockedOneTo` instead of `BlockUnitRange`.
+- Support for some simple block-banded matrices has been moved here from BlockBandedMatrices.jl
+
 ## Contributing
 
 Possible ways of contributing to this package include:

benchmark/runbenchmarks.jl

@@ -12,7 +12,7 @@ g = addgroup!(SUITE, "indexing")
 g_size = addgroup!(SUITE, "size")
 
 for n = (5,)
-    for BT in (BlockArray, PseudoBlockArray)
+    for BT in (BlockArray, BlockedArray)
         block_vec = BT(rand(n),       [1,3,1])
         block_mat = BT(rand(n,n),     [1,3,1], [4,1])
         block_arr = BT(rand(n,n,n),   [1,3,1], [4,1], [3, 2])

docs/make.jl

@@ -13,7 +13,7 @@ makedocs(
         "Manual" => [
             "man/abstractblockarrayinterface.md",
             "man/blockarrays.md",
-            "man/pseudoblockarrays.md",
+            "man/blockedarrays.md",
         ],
         "API" => [
             "lib/public.md",

docs/src/index.md

@@ -6,7 +6,7 @@
 
 A block array is a partition of an array into multiple blocks or subarrays, see [wikipedia](https://en.wikipedia.org/wiki/Block_matrix) for a more extensive description. This package has two purposes. Firstly, it defines an interface for an `AbstractBlockArray` block arrays that can be shared among types representing different types of block arrays. The advantage to this is that it provides a consistent API for block arrays.
 
-Secondly, it also implements two concrete types of block arrays that follow the `AbstractBlockArray` interface.  The type `BlockArray` stores each single block contiguously, by wrapping an `AbstractArray{<:AbstractArray{T,N},N}` to concatenate all blocks – the complete array is thus not stored contiguously.  Conversely, a `PseudoBlockArray` stores the full matrix contiguously (by wrapping only one `AbstractArray{T, N}`) and only superimposes a block structure.  This means that `BlockArray` supports fast non copying extraction and insertion of blocks, while `PseudoBlockArray` supports fast access to the full matrix to use in, for example, a linear solver.
+Secondly, it also implements two concrete types of block arrays that follow the `AbstractBlockArray` interface.  The type `BlockArray` stores each single block contiguously, by wrapping an `AbstractArray{<:AbstractArray{T,N},N}` to concatenate all blocks – the complete array is thus not stored contiguously.  Conversely, a `BlockedArray` stores the full matrix contiguously (by wrapping only one `AbstractArray{T, N}`) and only superimposes a block structure.  This means that `BlockArray` supports fast non copying extraction and insertion of blocks, while `BlockedArray` supports fast access to the full matrix to use in, for example, a linear solver.
 
 
 ## Terminology
@@ -39,7 +39,7 @@ A block array layout is specified its _block sizes_ – a tuple of `AbstractArra
 ## Manual Outline
 
 ```@contents
-Pages = ["man/abstractblockarrayinterface.md", "man/blockarrays.md", "man/pseudoblockarrays.md"]
+Pages = ["man/abstractblockarrayinterface.md", "man/blockarrays.md", "man/blockedarrays.md"]
 Depth = 2
 ```
 

docs/src/lib/internals.md

@@ -21,6 +21,8 @@ Pages = ["internals.md"]
 ```@docs
 blockcolsupport
 blockrowsupport
+blockedrange
+BlockedOneTo
 BlockedUnitRange
 BlockRange
 BlockIndexRange

docs/src/lib/public.md

@@ -65,12 +65,12 @@ Base.popfirst!
 ```
 
 
-## PseudoBlockArray
+## BlockedArray
 
 ```@docs
-PseudoBlockArray
-PseudoBlockVector
-PseudoBlockMatrix
+BlockedArray
+BlockedVector
+BlockedMatrix
 Base.resize!
 ```
 

docs/src/man/abstractblockarrayinterface.md

@@ -1,8 +1,8 @@
 # The block axis interface
 
-A block array's block structure is dictated by its axes, which
-are typically a `BlockedUnitRange` but may also be a `UnitRange`, 
-which is assumed to be a single block, or other type that implements
+A block array's block structure is dictated by its axes. These
+are typically `BlockedOneTo`s, but may also be standard and non-blocked `AbstractUnitRange`s
+(which are assumed to correspond to a single block), or other type that implements
 the block axis interface.
 
 

docs/src/man/blockarrays.md

@@ -22,7 +22,7 @@ julia> BlockArray(Array(reshape(1:16, 4, 4)), [2,2], [1,1,2])
 julia> S = spzeros(4,5); S[1,2] = S[4,3] = 1;
 
 julia> block_array_sparse = BlockArray(S, [1,3], [2,3])
-2×2-blocked 4×5 BlockMatrix{Float64, Matrix{SparseMatrixCSC{Float64, Int64}}, Tuple{BlockedUnitRange{Vector{Int64}}, BlockedUnitRange{Vector{Int64}}}}:
+2×2-blocked 4×5 BlockMatrix{Float64, Matrix{SparseMatrixCSC{Float64, Int64}}, Tuple{BlockedOneTo{Int64, Vector{Int64}}, BlockedOneTo{Int64, Vector{Int64}}}}:
   ⋅   1.0  │   ⋅    ⋅    ⋅ 
  ──────────┼───────────────
   ⋅    ⋅   │   ⋅    ⋅    ⋅ 
@@ -67,7 +67,7 @@ The `block_type` should be an array type.  It specifies the internal block type,
 
 ```jldoctest
 julia> BlockArray(undef_blocks, SparseVector{Float64, Int}, [1,2])
-2-blocked 3-element BlockVector{Float64, Vector{SparseVector{Float64, Int64}}, Tuple{BlockedUnitRange{Vector{Int64}}}}:
+2-blocked 3-element BlockVector{Float64, Vector{SparseVector{Float64, Int64}}, Tuple{BlockedOneTo{Int64, Vector{Int64}}}}:
  #undef
  ──────
  #undef
@@ -151,7 +151,7 @@ julia> view(A, Block(2)) .= [3,4]; A[Block(2)]
  4.0
 
 julia> view(A, Block.(1:2))
-3-element view(::BlockVector{Float64, Vector{Vector{Float64}}, Tuple{BlockedUnitRange{ArrayLayouts.RangeCumsum{Int64, UnitRange{Int64}}}}}, BlockSlice(BlockRange(1:2),1:1:3)) with eltype Float64 with indices 1:1:3:
+3-element view(::BlockVector{Float64, Vector{Vector{Float64}}, Tuple{BlockedOneTo{Int64, ArrayLayouts.RangeCumsum{Int64, UnitRange{Int64}}}}}, BlockSlice(BlockRange(1:2),1:1:3)) with eltype Float64 with indices BlockedOneTo([1, 3]):
  1.0
  3.0
  4.0
@@ -167,7 +167,7 @@ An array can be repacked into a `BlockArray` with `BlockArray(array, block_sizes
 julia> S = spzeros(4,5); S[1,2] = S[4,3] = 1;
 
 julia> block_array_sparse = BlockArray(S, [1,3], [2,3])
-2×2-blocked 4×5 BlockMatrix{Float64, Matrix{SparseMatrixCSC{Float64, Int64}}, Tuple{BlockedUnitRange{Vector{Int64}}, BlockedUnitRange{Vector{Int64}}}}:
+2×2-blocked 4×5 BlockMatrix{Float64, Matrix{SparseMatrixCSC{Float64, Int64}}, Tuple{BlockedOneTo{Int64, Vector{Int64}}, BlockedOneTo{Int64, Vector{Int64}}}}:
   ⋅   1.0  │   ⋅    ⋅    ⋅ 
  ──────────┼───────────────
   ⋅    ⋅   │   ⋅    ⋅    ⋅ 

docs/src/man/pseudoblockarrays.md → docs/src/man/blockedarrays.md

@@ -1,4 +1,4 @@
-# PseudoBlockArrays
+# BlockedArrays
 
 ```@meta
 DocTestSetup = quote
@@ -8,22 +8,22 @@ DocTestSetup = quote
 end
 ```
 
-A `PseudoBlockArray` is similar to a [`BlockArray`](@ref) except the full array is stored
+A `BlockedArray` is similar to a [`BlockArray`](@ref) except the full array is stored
 contiguously instead of block by block. This means that is not possible to insert and retrieve
-blocks without copying data. On the other hand, converting a `PseudoBlockArray` to the "full" underlying array is instead instant since
+blocks without copying data. On the other hand, converting a `BlockedArray` to the "full" underlying array is instead instant since
 it can just return the wrapped array.
 
 When iteratively solving a set of equations with a gradient method the Jacobian typically has a block structure. It can be convenient
-to use a `PseudoBlockArray` to build up the Jacobian block by block and then pass the resulting matrix to
+to use a `BlockedArray` to build up the Jacobian block by block and then pass the resulting matrix to
 a direct solver using `Matrix`.
 
-## Creating PseudoBlockArrays
+## Creating BlockedArrays
 
-Creating a `PseudoBlockArray` works in the same way as a `BlockArray`.
+Creating a `BlockedArray` works in the same way as a `BlockArray`.
 
 ```jldoctest A
-julia> pseudo = PseudoBlockArray(reshape([1:9;], 3, 3), [1,2], [2,1])
-2×2-blocked 3×3 PseudoBlockMatrix{Int64}:
+julia> pseudo = BlockedArray(reshape([1:9;], 3, 3), [1,2], [2,1])
+2×2-blocked 3×3 BlockedMatrix{Int64}:
  1  4  │  7
  ──────┼───
  2  5  │  8
@@ -38,8 +38,8 @@ This "takes ownership" of the passed in array so no copy of the array is made.
 A block array can be created with uninitialized entries using the `BlockArray{T}(undef, block_sizes...)`
 function. The block_sizes are each an `AbstractVector{Int}` which determines the size of the blocks in that dimension. We here create a `[1,2]×[3,2]` block matrix of `Float32`s:
 ```julia
-julia> PseudoBlockArray{Float32}(undef, [1,2], [3,2])
-2×2-blocked 3×5 PseudoBlockMatrix{Float32}:
+julia> BlockedArray{Float32}(undef, [1,2], [3,2])
+2×2-blocked 3×5 BlockedMatrix{Float32}:
  1.02295e-43  0.0          1.09301e-43  │  0.0          1.17709e-43
  ───────────────────────────────────────┼──────────────────────────
  0.0          1.06499e-43  0.0          │  1.14906e-43  0.0
@@ -79,9 +79,9 @@ The underlying array is accessed with `Array` just like for `BlockArray`.
 
 ## Views of blocks
 
-We can also view and modify views of blocks of `PseudoBlockArray` using the `view` syntax:
+We can also view and modify views of blocks of `BlockedArray` using the `view` syntax:
 ```jldoctest
-julia> A = PseudoBlockArray(ones(6), 1:3);
+julia> A = BlockedArray(ones(6), 1:3);
 
 julia> view(A, Block(2))
 2-element view(::Vector{Float64}, 2:3) with eltype Float64:

ext/BlockArraysBandedMatricesExt.jl

@@ -0,0 +1,30 @@
+module BlockArraysBandedMatricesExt
+
+using BandedMatrices, BlockArrays
+using BlockArrays.ArrayLayouts
+import BandedMatrices: isbanded, AbstractBandedLayout, bandeddata, bandwidths
+import BlockArrays: blockcolsupport, blockrowsupport, AbstractBlockedUnitRange
+import ArrayLayouts: sub_materialize
+
+
+bandeddata(P::BlockedMatrix) = bandeddata(P.blocks)
+bandwidths(P::BlockedMatrix) = bandwidths(P.blocks)
+
+function blockcolsupport(::AbstractBandedLayout, B, j)
+    m,n = axes(B)
+    cs = colsupport(B,n[j])
+    findblock(m,first(cs)):findblock(m,last(cs))
+end
+
+function blockrowsupport(::AbstractBandedLayout, B, k)
+    m,n = axes(B)
+    rs = rowsupport(B,m[k])
+    findblock(n,first(rs)):findblock(n,last(rs))
+end
+
+# ambiguity
+sub_materialize(::AbstractBandedLayout, V, ::Tuple{AbstractBlockedUnitRange,Base.OneTo{Int}}) = BandedMatrix(V)
+sub_materialize(::AbstractBandedLayout, V, ::Tuple{Base.OneTo{Int},AbstractBlockedUnitRange}) = BandedMatrix(V)
+
+
+end