Runic formatting

.github/PULL_REQUEST_TEMPLATE.md

@@ -11,13 +11,15 @@ If practical and applicable, please include a minimal demonstration of the previ
 ```julia
 [YOUR MINIMAL DEMONSTRATION OF PREVIOUS BEHAVIOR]
 ```
+
 </p></details>
 
 <details><summary>Minimal demonstration of new behavior</summary><p>
 
 ```julia
 [YOUR MINIMAL DEMONSTRATION OF NEW BEHAVIOR]
 ```
+
 </p></details>
 
 # How Has This Been Tested?

.github/workflows/FormatCheck.yml

@@ -1,11 +1,14 @@
 name: "Format Check"
 
 on:
-  push:
-    branches:
-      - 'main'
-    tags: '*'
-  pull_request:
+  pull_request_target:
+    paths: ['**/*.jl']
+    types: [opened, synchronize, reopened, ready_for_review]
+
+permissions:
+  contents: read
+  actions: write
+  pull-requests: write
 
 jobs:
   format-check:

.github/workflows/FormatPullRequest.yml

@@ -0,0 +1,14 @@
+name: "Format Pull Request"
+
+on:
+  schedule:
+    - cron: '0 0 * * *'
+  workflow_dispatch:
+permissions:
+  contents: write
+  pull-requests: write
+
+jobs:
+  format-pull-request:
+    name: "Format Pull Request"
+    uses: "ITensor/ITensorActions/.github/workflows/FormatPullRequest.yml@main"

.github/workflows/VersionCheck.yml

@@ -0,0 +1,11 @@
+name: "Version Check"
+
+on:
+  pull_request:
+
+jobs:
+  version-check:
+    name: "Version Check"
+    uses: "ITensor/ITensorActions/.github/workflows/VersionCheck.yml@main"
+    with:
+      localregistry: https://github.com/ITensor/ITensorRegistry.git

.pre-commit-config.yaml

@@ -1,5 +1,5 @@
 ci:
-  skip: [julia-formatter]
+  skip: [runic]
 
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
@@ -11,10 +11,8 @@ repos:
   - id: end-of-file-fixer
     exclude: '.*references/.*\.txt$'  # do not check reference TN images
     exclude_types: [markdown]  # incompatible with Literate.jl
-  - id: trailing-whitespace
-    exclude: '.*references/.*\.txt$'  # do not check reference TN images
 
-- repo: "https://github.com/domluna/JuliaFormatter.jl"
-  rev: v2.1.6
+- repo: https://github.com/fredrikekre/runic-pre-commit
+  rev: v2.0.1
   hooks:
-  - id: "julia-formatter"
+    - id: runic

NDTensors/Project.toml

@@ -1,7 +1,7 @@
 name = "NDTensors"
 uuid = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
 authors = ["Matthew Fishman <[email protected]>"]
-version = "0.4.11"
+version = "0.4.12"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"

NDTensors/ext/NDTensorsHDF5Ext/blocksparse.jl

@@ -3,66 +3,66 @@ using NDTensors: data, Block, blockoffsets, BlockOffsets, BlockSparse
 
 # Helper function for HDF5 write/read of BlockSparse
 function offsets_to_array(boff::BlockOffsets{N}) where {N}
-  nblocks = length(boff)
-  asize = (N + 1) * nblocks
-  n = 1
-  a = Vector{Int}(undef, asize)
-  for bo in pairs(boff)
-    for j in 1:N
-      a[n] = bo[1][j]
-      n += 1
+    nblocks = length(boff)
+    asize = (N + 1) * nblocks
+    n = 1
+    a = Vector{Int}(undef, asize)
+    for bo in pairs(boff)
+        for j in 1:N
+            a[n] = bo[1][j]
+            n += 1
+        end
+        a[n] = bo[2]
+        n += 1
     end
-    a[n] = bo[2]
-    n += 1
-  end
-  return a
+    return a
 end
 
 # Helper function for HDF5 write/read of BlockSparse
 function array_to_offsets(a, N::Int)
-  asize = length(a)
-  nblocks = div(asize, N + 1)
-  boff = BlockOffsets{N}()
-  j = 0
-  for b in 1:nblocks
-    insert!(boff, Block(ntuple(i -> (a[j + i]), N)), a[j + N + 1])
-    j += (N + 1)
-  end
-  return boff
+    asize = length(a)
+    nblocks = div(asize, N + 1)
+    boff = BlockOffsets{N}()
+    j = 0
+    for b in 1:nblocks
+        insert!(boff, Block(ntuple(i -> (a[j + i]), N)), a[j + N + 1])
+        j += (N + 1)
+    end
+    return boff
 end
 
-function HDF5.write(parent::Union{HDF5.File,HDF5.Group}, name::String, B::BlockSparse)
-  g = create_group(parent, name)
-  attributes(g)["type"] = "BlockSparse{$(eltype(B))}"
-  attributes(g)["version"] = 1
-  if eltype(B) != Nothing
-    write(g, "ndims", ndims(B))
-    write(g, "data", data(B))
-    off_array = offsets_to_array(blockoffsets(B))
-    write(g, "offsets", off_array)
-  end
+function HDF5.write(parent::Union{HDF5.File, HDF5.Group}, name::String, B::BlockSparse)
+    g = create_group(parent, name)
+    attributes(g)["type"] = "BlockSparse{$(eltype(B))}"
+    attributes(g)["version"] = 1
+    return if eltype(B) != Nothing
+        write(g, "ndims", ndims(B))
+        write(g, "data", data(B))
+        off_array = offsets_to_array(blockoffsets(B))
+        write(g, "offsets", off_array)
+    end
 end
 
 function HDF5.read(
-  parent::Union{HDF5.File,HDF5.Group}, name::AbstractString, ::Type{Store}
-) where {Store<:BlockSparse}
-  g = open_group(parent, name)
-  ElT = eltype(Store)
-  typestr = "BlockSparse{$ElT}"
-  if read(attributes(g)["type"]) != typestr
-    error("HDF5 group or file does not contain $typestr data")
-  end
-  N = read(g, "ndims")
-  off_array = read(g, "offsets")
-  boff = array_to_offsets(off_array, N)
-  # Attribute __complex__ is attached to the "data" dataset
-  # by the h5 library used by C++ version of ITensor:
-  if haskey(attributes(g["data"]), "__complex__")
-    M = read(g, "data")
-    nelt = size(M, 1) * size(M, 2)
-    data = Vector(reinterpret(ComplexF64, reshape(M, nelt)))
-  else
-    data = read(g, "data")
-  end
-  return BlockSparse(data, boff)
+        parent::Union{HDF5.File, HDF5.Group}, name::AbstractString, ::Type{Store}
+    ) where {Store <: BlockSparse}
+    g = open_group(parent, name)
+    ElT = eltype(Store)
+    typestr = "BlockSparse{$ElT}"
+    if read(attributes(g)["type"]) != typestr
+        error("HDF5 group or file does not contain $typestr data")
+    end
+    N = read(g, "ndims")
+    off_array = read(g, "offsets")
+    boff = array_to_offsets(off_array, N)
+    # Attribute __complex__ is attached to the "data" dataset
+    # by the h5 library used by C++ version of ITensor:
+    if haskey(attributes(g["data"]), "__complex__")
+        M = read(g, "data")
+        nelt = size(M, 1) * size(M, 2)
+        data = Vector(reinterpret(ComplexF64, reshape(M, nelt)))
+    else
+        data = read(g, "data")
+    end
+    return BlockSparse(data, boff)
 end

NDTensors/ext/NDTensorsHDF5Ext/dense.jl

@@ -2,36 +2,36 @@ using HDF5: HDF5, attributes, create_group, open_group, read, write
 using NDTensors: Dense
 
 function HDF5.write(
-  parent::Union{HDF5.File,HDF5.Group}, name::String, D::Store
-) where {Store<:Dense}
-  g = create_group(parent, name)
-  attributes(g)["type"] = "Dense{$(eltype(Store))}"
-  attributes(g)["version"] = 1
-  if eltype(D) != Nothing
-    write(g, "data", D.data)
-  end
+        parent::Union{HDF5.File, HDF5.Group}, name::String, D::Store
+    ) where {Store <: Dense}
+    g = create_group(parent, name)
+    attributes(g)["type"] = "Dense{$(eltype(Store))}"
+    attributes(g)["version"] = 1
+    return if eltype(D) != Nothing
+        write(g, "data", D.data)
+    end
 end
 
 function HDF5.read(
-  parent::Union{HDF5.File,HDF5.Group}, name::AbstractString, ::Type{Store}
-) where {Store<:Dense}
-  g = open_group(parent, name)
-  ElT = eltype(Store)
-  typestr = "Dense{$ElT}"
-  if read(attributes(g)["type"]) != typestr
-    error("HDF5 group or file does not contain $typestr data")
-  end
-  if ElT == Nothing
-    return Dense{Nothing}()
-  end
-  # Attribute __complex__ is attached to the "data" dataset
-  # by the h5 library used by C++ version of ITensor:
-  if haskey(attributes(g["data"]), "__complex__")
-    M = read(g, "data")
-    nelt = size(M, 1) * size(M, 2)
-    data = Vector(reinterpret(ComplexF64, reshape(M, nelt)))
-  else
-    data = read(g, "data")
-  end
-  return Dense{ElT}(data)
+        parent::Union{HDF5.File, HDF5.Group}, name::AbstractString, ::Type{Store}
+    ) where {Store <: Dense}
+    g = open_group(parent, name)
+    ElT = eltype(Store)
+    typestr = "Dense{$ElT}"
+    if read(attributes(g)["type"]) != typestr
+        error("HDF5 group or file does not contain $typestr data")
+    end
+    if ElT == Nothing
+        return Dense{Nothing}()
+    end
+    # Attribute __complex__ is attached to the "data" dataset
+    # by the h5 library used by C++ version of ITensor:
+    if haskey(attributes(g["data"]), "__complex__")
+        M = read(g, "data")
+        nelt = size(M, 1) * size(M, 2)
+        data = Vector(reinterpret(ComplexF64, reshape(M, nelt)))
+    else
+        data = read(g, "data")
+    end
+    return Dense{ElT}(data)
 end

NDTensors/ext/NDTensorsHDF5Ext/diag.jl

@@ -2,37 +2,37 @@ using HDF5: HDF5, attributes, create_group, open_group, read, write
 using NDTensors: datatype, Dense, Diag
 
 function HDF5.write(
-  parent::Union{HDF5.File,HDF5.Group}, name::String, D::Store
-) where {Store<:Diag}
-  g = create_group(parent, name)
-  attributes(g)["type"] = "Diag{$(eltype(Store)),$(datatype(Store))}"
-  attributes(g)["version"] = 1
-  if eltype(D) != Nothing
-    write(g, "data", D.data)
-  end
+        parent::Union{HDF5.File, HDF5.Group}, name::String, D::Store
+    ) where {Store <: Diag}
+    g = create_group(parent, name)
+    attributes(g)["type"] = "Diag{$(eltype(Store)),$(datatype(Store))}"
+    attributes(g)["version"] = 1
+    return if eltype(D) != Nothing
+        write(g, "data", D.data)
+    end
 end
 
 function HDF5.read(
-  parent::Union{HDF5.File,HDF5.Group}, name::AbstractString, ::Type{Store}
-) where {Store<:Diag}
-  g = open_group(parent, name)
-  ElT = eltype(Store)
-  DataT = datatype(Store)
-  typestr = "Diag{$ElT,$DataT}"
-  if read(attributes(g)["type"]) != typestr
-    error("HDF5 group or file does not contain $typestr data")
-  end
-  if ElT == Nothing
-    return Dense{Nothing}()
-  end
-  # Attribute __complex__ is attached to the "data" dataset
-  # by the h5 library used by C++ version of ITensor:
-  if haskey(attributes(g["data"]), "__complex__")
-    M = read(g, "data")
-    nelt = size(M, 1) * size(M, 2)
-    data = Vector(reinterpret(ComplexF64, reshape(M, nelt)))
-  else
-    data = read(g, "data")
-  end
-  return Diag{ElT,DataT}(data)
+        parent::Union{HDF5.File, HDF5.Group}, name::AbstractString, ::Type{Store}
+    ) where {Store <: Diag}
+    g = open_group(parent, name)
+    ElT = eltype(Store)
+    DataT = datatype(Store)
+    typestr = "Diag{$ElT,$DataT}"
+    if read(attributes(g)["type"]) != typestr
+        error("HDF5 group or file does not contain $typestr data")
+    end
+    if ElT == Nothing
+        return Dense{Nothing}()
+    end
+    # Attribute __complex__ is attached to the "data" dataset
+    # by the h5 library used by C++ version of ITensor:
+    if haskey(attributes(g["data"]), "__complex__")
+        M = read(g, "data")
+        nelt = size(M, 1) * size(M, 2)
+        data = Vector(reinterpret(ComplexF64, reshape(M, nelt)))
+    else
+        data = read(g, "data")
+    end
+    return Diag{ElT, DataT}(data)
 end