define randn(::RNG)

Author: ogauthe

src/fusiontensor/base_interface.jl

@@ -1,7 +1,6 @@
 # This files defines Base functions for FusionTensor
 
 using Accessors: @set
-using Random: randn!
 using BlockSparseArrays: @view!, eachstoredblock
 using TensorAlgebra: BlockedTuple, tuplemortar
 

src/fusiontensor/fusiontensor.jl

@@ -20,6 +20,7 @@ using GradedArrays:
   sectors,
   space_isequal
 using LinearAlgebra: UniformScaling
+using Random: Random, AbstractRNG, randn!
 using TensorAlgebra: BlockedTuple, trivial_axis, tuplemortar
 using TensorProducts: tensor_product
 using TypeParameterAccessors: type_parameters
@@ -214,25 +215,32 @@ end
 Base.zeros(::Type{T}, fta::FusionTensorAxes) where {T} = FusionTensor(T, fta)
 Base.zeros(fta::FusionTensorAxes) = zeros(Float64, fta)
 
-function Base.randn(::Type{T}, fta::FusionTensorAxes) where {T}
+function Base.randn(rng::AbstractRNG, ::Type{T}, fta::FusionTensorAxes) where {T}
   ft = FusionTensor(T, fta)
   for m in eachstoredblock(data_matrix(ft))
-    randn!(m)
+    randn!(rng, m)
   end
   return ft
 end
+Base.randn(rng::AbstractRNG, fta::FusionTensorAxes) = randn(rng, Float64, fta)
+Base.randn(::Type{T}, fta::FusionTensorAxes) where {T} = randn(Random.default_rng(), T, fta)
 Base.randn(fta::FusionTensorAxes) = randn(Float64, fta)
 
-function FusionTensor(
-  ::UniformScaling, codomain_legs::Tuple{Vararg{AbstractGradedUnitRange}}
-)
+function FusionTensor{T}(
+  s::UniformScaling, codomain_legs::Tuple{Vararg{AbstractGradedUnitRange}}
+) where {T}
   fta = FusionTensorAxes(codomain_legs, dual.(codomain_legs))
-  ft = FusionTensor(Float64, fta)
+  ft = FusionTensor(T, fta)
   for m in eachstoredblock(data_matrix(ft))
-    m .= LinearAlgebra.I(size(m, 1))
+    m .= s(size(m, 1))
   end
   return ft
 end
+function FusionTensor(
+  s::UniformScaling, codomain_legs::Tuple{Vararg{AbstractGradedUnitRange}}
+)
+  return FusionTensor{Float64}(s, codomain_legs)
+end
 
 # ================================  BlockArrays interface  =================================
 

test/Project.toml

@@ -5,6 +5,7 @@ BlockSparseArrays = "2c9a651f-6452-4ace-a6ac-809f4280fbb4"
 FusionTensors = "e16ca583-1f51-4df0-8e12-57d32947d33e"
 GradedArrays = "bc96ca6e-b7c8-4bb6-888e-c93f838762c2"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
 Suppressor = "fd094767-a336-5f1f-9728-57cf17d0bbfb"
 TensorAlgebra = "68bd88dc-f39d-4e12-b2ca-f046b68fcc6a"
@@ -18,6 +19,7 @@ BlockSparseArrays = "0.7"
 FusionTensors = "0.4"
 GradedArrays = "0.4"
 LinearAlgebra = "1.10.0"
+Random = "1.10"
 SafeTestsets = "0.1.0"
 Suppressor = "0.2.8"
 TensorAlgebra = "0.3"

test/test_basics.jl

@@ -29,6 +29,7 @@ using GradedArrays:
 using TensorAlgebra: tuplemortar
 using TensorProducts: tensor_product
 using LinearAlgebra: LinearAlgebra
+using Random: Random
 
 include("setup.jl")
 
@@ -282,9 +283,13 @@ end
   fta = FusionTensorAxes((g1,), (g2, g3))
   @test zeros(fta) isa FusionTensor{Float64,3}
   @test zeros(ComplexF64, fta) isa FusionTensor{ComplexF64,3}
-  ft1 = randn(ComplexF64, fta)
+
+  rng = Random.default_rng()
+  ft1 = randn(rng, ComplexF64, fta)
   @test ft1 isa FusionTensor{ComplexF64,3}
   @test all(!=(0), data_matrix(ft1)[Block(1, 5)])
+  @test randn(rng, fta) isa FusionTensor{Float64,3}
+  @test randn(ComplexF64, fta) isa FusionTensor{ComplexF64,3}
   @test randn(fta) isa FusionTensor{Float64,3}
 
   ft2 = FusionTensor(LinearAlgebra.I, (g1, g2))
@@ -295,6 +300,15 @@ end
     m = data_matrix(ft2)[Block(i, i)]
     @test m == LinearAlgebra.I(size(m, 1))
   end
+
+  ft2 = FusionTensor(3 * LinearAlgebra.I, (g1, g2))
+  @test ft2 isa FusionTensor{Float64,4}
+  @test axes(ft2) == FusionTensorAxes((g1, g2), dual.((g1, g2)))
+  @test collect(eachblockstoredindex(data_matrix(ft2))) == map(i -> Block(i, i), 1:6)
+  for i in 1:6
+    m = data_matrix(ft2)[Block(i, i)]
+    @test m == 3 * LinearAlgebra.I(size(m, 1))
+  end
 end
 
 @testset "missing SectorProduct" begin