Automatic Runic.jl run

Project.toml

@@ -1,7 +1,7 @@
 name = "BlockSparseArrays"
 uuid = "2c9a651f-6452-4ace-a6ac-809f4280fbb4"
+version = "0.10.4"
 authors = ["ITensor developers <[email protected]> and contributors"]
-version = "0.10.3"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"

docs/make.jl

@@ -2,26 +2,26 @@ using BlockSparseArrays: BlockSparseArrays
 using Documenter: Documenter, DocMeta, deploydocs, makedocs
 
 DocMeta.setdocmeta!(
-  BlockSparseArrays, :DocTestSetup, quote
-    using BlockSparseArrays
-    using LinearAlgebra: Diagonal
-  end; recursive=true
+    BlockSparseArrays, :DocTestSetup, quote
+        using BlockSparseArrays
+        using LinearAlgebra: Diagonal
+    end; recursive = true
 )
 
 include("make_index.jl")
 
 makedocs(;
-  modules=[BlockSparseArrays],
-  authors="ITensor developers <[email protected]> and contributors",
-  sitename="BlockSparseArrays.jl",
-  format=Documenter.HTML(;
-    canonical="https://ITensor.github.io/BlockSparseArrays.jl",
-    edit_link="main",
-    assets=["assets/favicon.ico", "assets/extras.css"],
-  ),
-  pages=["Home" => "index.md", "Reference" => "reference.md"],
+    modules = [BlockSparseArrays],
+    authors = "ITensor developers <[email protected]> and contributors",
+    sitename = "BlockSparseArrays.jl",
+    format = Documenter.HTML(;
+        canonical = "https://ITensor.github.io/BlockSparseArrays.jl",
+        edit_link = "main",
+        assets = ["assets/favicon.ico", "assets/extras.css"],
+    ),
+    pages = ["Home" => "index.md", "Reference" => "reference.md"],
 )
 
 deploydocs(;
-  repo="github.com/ITensor/BlockSparseArrays.jl", devbranch="main", push_preview=true
+    repo = "github.com/ITensor/BlockSparseArrays.jl", devbranch = "main", push_preview = true
 )

docs/make_index.jl

@@ -2,20 +2,20 @@ using Literate: Literate
 using BlockSparseArrays: BlockSparseArrays
 
 function ccq_logo(content)
-  include_ccq_logo = """
+    include_ccq_logo = """
     ```@raw html
     <img class="display-light-only" src="assets/CCQ.png" width="20%" alt="Flatiron Center for Computational Quantum Physics logo."/>
     <img class="display-dark-only" src="assets/CCQ-dark.png" width="20%" alt="Flatiron Center for Computational Quantum Physics logo."/>
     ```
     """
-  content = replace(content, "{CCQ_LOGO}" => include_ccq_logo)
-  return content
+    content = replace(content, "{CCQ_LOGO}" => include_ccq_logo)
+    return content
 end
 
 Literate.markdown(
-  joinpath(pkgdir(BlockSparseArrays), "examples", "README.jl"),
-  joinpath(pkgdir(BlockSparseArrays), "docs", "src");
-  flavor=Literate.DocumenterFlavor(),
-  name="index",
-  postprocess=ccq_logo,
+    joinpath(pkgdir(BlockSparseArrays), "examples", "README.jl"),
+    joinpath(pkgdir(BlockSparseArrays), "docs", "src");
+    flavor = Literate.DocumenterFlavor(),
+    name = "index",
+    postprocess = ccq_logo,
 )

docs/make_readme.jl

@@ -2,20 +2,20 @@ using Literate: Literate
 using BlockSparseArrays: BlockSparseArrays
 
 function ccq_logo(content)
-  include_ccq_logo = """
+    include_ccq_logo = """
     <picture>
       <source media="(prefers-color-scheme: dark)" width="20%" srcset="docs/src/assets/CCQ-dark.png">
       <img alt="Flatiron Center for Computational Quantum Physics logo." width="20%" src="docs/src/assets/CCQ.png">
     </picture>
     """
-  content = replace(content, "{CCQ_LOGO}" => include_ccq_logo)
-  return content
+    content = replace(content, "{CCQ_LOGO}" => include_ccq_logo)
+    return content
 end
 
 Literate.markdown(
-  joinpath(pkgdir(BlockSparseArrays), "examples", "README.jl"),
-  joinpath(pkgdir(BlockSparseArrays));
-  flavor=Literate.CommonMarkFlavor(),
-  name="README",
-  postprocess=ccq_logo,
+    joinpath(pkgdir(BlockSparseArrays), "examples", "README.jl"),
+    joinpath(pkgdir(BlockSparseArrays));
+    flavor = Literate.CommonMarkFlavor(),
+    name = "README",
+    postprocess = ccq_logo,
 )

examples/README.jl

@@ -1,5 +1,5 @@
 # # BlockSparseArrays.jl
-# 
+#
 # [![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://itensor.github.io/BlockSparseArrays.jl/stable/)
 # [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://itensor.github.io/BlockSparseArrays.jl/dev/)
 # [![Build Status](https://github.com/ITensor/BlockSparseArrays.jl/actions/workflows/Tests.yml/badge.svg?branch=main)](https://github.com/ITensor/BlockSparseArrays.jl/actions/workflows/Tests.yml?query=branch%3Amain)

ext/BlockSparseArraysTensorAlgebraExt/BlockSparseArraysTensorAlgebraExt.jl

@@ -2,64 +2,64 @@ module BlockSparseArraysTensorAlgebraExt
 
 using BlockSparseArrays: AbstractBlockSparseArray, blockreshape
 using TensorAlgebra:
-  TensorAlgebra,
-  BlockedTrivialPermutation,
-  BlockedTuple,
-  FusionStyle,
-  ReshapeFusion,
-  fuseaxes
+    TensorAlgebra,
+    BlockedTrivialPermutation,
+    BlockedTuple,
+    FusionStyle,
+    ReshapeFusion,
+    fuseaxes
 
 struct BlockReshapeFusion <: FusionStyle end
 
 function TensorAlgebra.FusionStyle(::Type{<:AbstractBlockSparseArray})
-  return BlockReshapeFusion()
+    return BlockReshapeFusion()
 end
 
 using BlockArrays: Block, blocklength, blocks
 using BlockSparseArrays: blocksparse
 using SparseArraysBase: eachstoredindex
 using TensorAlgebra: TensorAlgebra, matricize, unmatricize
 function TensorAlgebra.matricize(
-  ::BlockReshapeFusion, a::AbstractArray, biperm::BlockedTrivialPermutation{2}
-)
-  ax = fuseaxes(axes(a), biperm)
-  reshaped_blocks_a = reshape(blocks(a), map(blocklength, ax))
-  key(I) = Block(Tuple(I))
-  value(I) = matricize(reshaped_blocks_a[I], biperm)
-  Is = eachstoredindex(reshaped_blocks_a)
-  bs = if isempty(Is)
-    # Catch empty case and make sure the type is constrained properly.
-    # This seems to only be necessary in Julia versions below v1.11,
-    # try removing it when we drop support for those versions.
-    keytype = Base.promote_op(key, eltype(Is))
-    valtype = Base.promote_op(value, eltype(Is))
-    valtype′ = !isconcretetype(valtype) ? AbstractMatrix{eltype(a)} : valtype
-    Dict{keytype,valtype′}()
-  else
-    Dict(key(I) => value(I) for I in Is)
-  end
-  return blocksparse(bs, ax)
+        ::BlockReshapeFusion, a::AbstractArray, biperm::BlockedTrivialPermutation{2}
+    )
+    ax = fuseaxes(axes(a), biperm)
+    reshaped_blocks_a = reshape(blocks(a), map(blocklength, ax))
+    key(I) = Block(Tuple(I))
+    value(I) = matricize(reshaped_blocks_a[I], biperm)
+    Is = eachstoredindex(reshaped_blocks_a)
+    bs = if isempty(Is)
+        # Catch empty case and make sure the type is constrained properly.
+        # This seems to only be necessary in Julia versions below v1.11,
+        # try removing it when we drop support for those versions.
+        keytype = Base.promote_op(key, eltype(Is))
+        valtype = Base.promote_op(value, eltype(Is))
+        valtype′ = !isconcretetype(valtype) ? AbstractMatrix{eltype(a)} : valtype
+        Dict{keytype, valtype′}()
+    else
+        Dict(key(I) => value(I) for I in Is)
+    end
+    return blocksparse(bs, ax)
 end
 
 using BlockArrays: blocklengths
 function TensorAlgebra.unmatricize(
-  ::BlockReshapeFusion,
-  m::AbstractMatrix,
-  blocked_ax::BlockedTuple{2,<:Any,<:Tuple{Vararg{AbstractUnitRange}}},
-)
-  ax = Tuple(blocked_ax)
-  reshaped_blocks_m = reshape(blocks(m), map(blocklength, ax))
-  function f(I)
-    block_axes_I = BlockedTuple(
-      map(ntuple(identity, length(ax))) do i
-        return Base.axes1(ax[i][Block(I[i])])
-      end,
-      blocklengths(blocked_ax),
+        ::BlockReshapeFusion,
+        m::AbstractMatrix,
+        blocked_ax::BlockedTuple{2, <:Any, <:Tuple{Vararg{AbstractUnitRange}}},
     )
-    return unmatricize(reshaped_blocks_m[I], block_axes_I)
-  end
-  bs = Dict(Block(Tuple(I)) => f(I) for I in eachstoredindex(reshaped_blocks_m))
-  return blocksparse(bs, ax)
+    ax = Tuple(blocked_ax)
+    reshaped_blocks_m = reshape(blocks(m), map(blocklength, ax))
+    function f(I)
+        block_axes_I = BlockedTuple(
+            map(ntuple(identity, length(ax))) do i
+                return Base.axes1(ax[i][Block(I[i])])
+            end,
+            blocklengths(blocked_ax),
+        )
+        return unmatricize(reshaped_blocks_m[I], block_axes_I)
+    end
+    bs = Dict(Block(Tuple(I)) => f(I) for I in eachstoredindex(reshaped_blocks_m))
+    return blocksparse(bs, ax)
 end
 
 end

ext/BlockSparseArraysTensorProductsExt/BlockSparseArraysTensorProductsExt.jl

@@ -5,10 +5,10 @@ using TensorProducts: TensorProducts, tensor_product
 # TODO: Dispatch on `FusionStyle` to allow different kinds of products,
 # for example to allow merging common symmetry sectors.
 function TensorProducts.tensor_product(a1::BlockUnitRange, a2::BlockUnitRange)
-  new_blockaxes = vec(
-    map(splat(tensor_product), Iterators.product(eachblockaxis(a1), eachblockaxis(a2)))
-  )
-  return blockrange(new_blockaxes)
+    new_blockaxes = vec(
+        map(splat(tensor_product), Iterators.product(eachblockaxis(a1), eachblockaxis(a2)))
+    )
+    return blockrange(new_blockaxes)
 end
 
 end