Test BlockSparseArrays

Project.toml

@@ -1,7 +1,7 @@
 name = "TensorAlgebra"
 uuid = "68bd88dc-f39d-4e12-b2ca-f046b68fcc6a"
 authors = ["ITensor developers <[email protected]> and contributors"]
-version = "0.1.9"
+version = "0.1.10"
 
 [deps]
 ArrayLayouts = "4c555306-a7a7-4459-81d9-ec55ddd5c99a"

test/Project.toml

@@ -1,13 +1,16 @@
 [deps]
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 BlockArrays = "8e7c35d0-a365-5155-bbbb-fb81a777f24e"
+BlockSparseArrays = "2c9a651f-6452-4ace-a6ac-809f4280fbb4"
 EllipsisNotation = "da5c29d0-fa7d-589e-88eb-ea29b0a81949"
 GradedUnitRanges = "e2de450a-8a67-46c7-b59c-01d5a3d041c5"
 JLArrays = "27aeb0d3-9eb9-45fb-866b-73c2ecf80fcb"
 LabelledNumbers = "f856a3a6-4152-4ec4-b2a7-02c1a55d7993"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
+SparseArraysBase = "0d5efcca-f356-4864-8770-e1ed8d78f208"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 Suppressor = "fd094767-a336-5f1f-9728-57cf17d0bbfb"
 SymmetrySectors = "f8a8ad64-adbc-4fce-92f7-ffe2bb36a86e"
@@ -18,7 +21,10 @@ TestExtras = "5ed8adda-3752-4e41-b88a-e8b09835ee3a"
 
 [compat]
 Aqua = "0.8.9"
+BlockSparseArrays = "0.2"
+Random = "1.10"
 SafeTestsets = "0.1"
+SparseArraysBase = "0.2.11"
 Suppressor = "0.2"
 SymmetrySectors = "0.1"
 TensorOperations = "5.1.3"

test/test_gradedunitrangesext_contract.jl

@@ -1,37 +1,33 @@
-using Test: @test_skip
-# TODO: Add this back once `BlockSparseArrays` is set up.
-@test_skip begin
-  using BlockArrays: Block, blocksize
-  using BlockSparseArrays: BlockSparseArray
-  using GradedUnitRanges: gradedrange
-  using SparseArraysBase: densearray
-  using SymmetrySectors: U1
-  using TensorAlgebra: contract
-  using Random: randn!
-  using Test: @test, @testset
+using BlockArrays: Block, blocksize
+using BlockSparseArrays: BlockSparseArray
+using GradedUnitRanges: dual, gradedrange
+using SparseArraysBase: densearray
+using SymmetrySectors: U1
+using TensorAlgebra: contract
+using Random: randn!
+using Test: @test, @testset
 
-  function randn_blockdiagonal(elt::Type, axes::Tuple)
-    a = BlockSparseArray{elt}(axes)
-    blockdiaglength = minimum(blocksize(a))
-    for i in 1:blockdiaglength
-      b = Block(ntuple(Returns(i), ndims(a)))
-      a[b] = randn!(a[b])
-    end
-    return a
+function randn_blockdiagonal(elt::Type, axes::Tuple)
+  a = BlockSparseArray{elt}(axes)
+  blockdiaglength = minimum(blocksize(a))
+  for i in 1:blockdiaglength
+    b = Block(ntuple(Returns(i), ndims(a)))
+    a[b] = randn!(a[b])
   end
+  return a
+end
 
-  const elts = (Float32, Float64, Complex{Float32}, Complex{Float64})
-  @testset "`contract` `BlockSparseArray` (eltype=$elt)" for elt in elts
-    d = gradedrange([U1(0) => 2, U1(1) => 3])
-    a1 = randn_blockdiagonal(elt, (d, d, d))
-    a2 = randn_blockdiagonal(elt, (d, d, d))
-    a_dest, dimnames_dest = contract(a1, (-1, 1, -2), a2, (-1, -2, 2))
-    a1_dense = densearray(a1)
-    a2_dense = densearray(a2)
-    a_dest_dense, dimnames_dest_dense = contract(
-      a1_dense, (-1, 1, -2), a2_dense, (-1, -2, 2)
-    )
-    @test dimnames_dest == dimnames_dest_dense
-    @test a_dest ≈ a_dest_dense
-  end
+const elts = (Float32, Float64, Complex{Float32}, Complex{Float64})
+@testset "`contract` `BlockSparseArray` (eltype=$elt)" for elt in elts
+  d = gradedrange([U1(0) => 2, U1(1) => 3])
+  a1 = randn_blockdiagonal(elt, (d, d, dual(d), dual(d)))
+  a2 = randn_blockdiagonal(elt, (d, d, dual(d), dual(d)))
+  a_dest, dimnames_dest = contract(a1, (1, -1, 2, -2), a2, (2, -3, 1, -4))
+  a1_dense = densearray(a1)
+  a2_dense = densearray(a2)
+  a_dest_dense, dimnames_dest_dense = contract(
+    a1_dense, (1, -1, 2, -2), a2_dense, (2, -3, 1, -4)
+  )
+  @test dimnames_dest == dimnames_dest_dense
+  @test a_dest ≈ a_dest_dense
 end