add dedicated constructors

Project.toml

@@ -1,7 +1,7 @@
 name = "FusionTensors"
 uuid = "e16ca583-1f51-4df0-8e12-57d32947d33e"
 authors = ["ITensor developers <[email protected]> and contributors"]
-version = "0.4.1"
+version = "0.4.3"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"
@@ -11,6 +11,7 @@ GradedArrays = "bc96ca6e-b7c8-4bb6-888e-c93f838762c2"
 HalfIntegers = "f0d1745a-41c9-11e9-1dd9-e5d34d218721"
 LRUCache = "8ac3fa9e-de4c-5943-b1dc-09c6b5f20637"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Strided = "5e0ebb24-38b0-5f93-81fe-25c709ecae67"
 TensorAlgebra = "68bd88dc-f39d-4e12-b2ca-f046b68fcc6a"
 TensorProducts = "decf83d6-1968-43f4-96dc-fdb3fe15fc6d"
@@ -25,6 +26,7 @@ GradedArrays = "0.4.13"
 HalfIntegers = "1.6"
 LRUCache = "1.6"
 LinearAlgebra = "1.10"
+Random = "1.11.0"
 Strided = "2.3"
 TensorAlgebra = "0.3.8"
 TensorProducts = "0.1.7"

src/fusiontensor/base_interface.jl

@@ -1,8 +1,8 @@
 # This files defines Base functions for FusionTensor
 
 using Accessors: @set
-
-using BlockSparseArrays: @view!
+using Random: randn!
+using BlockSparseArrays: @view!, eachstoredblock
 using TensorAlgebra: BlockedTuple, tuplemortar
 
 set_data_matrix(ft::FusionTensor, data_matrix) = @set ft.data_matrix = data_matrix

src/fusiontensor/fusiontensor.jl

@@ -19,6 +19,7 @@ using GradedArrays:
   sectormergesort,
   sectors,
   space_isequal
+using LinearAlgebra: UniformScaling
 using TensorAlgebra: BlockedTuple, trivial_axis, tuplemortar
 using TensorProducts: tensor_product
 using TypeParameterAccessors: type_parameters
@@ -209,6 +210,30 @@ function FusionTensor(
   return FusionTensor(x, tuplemortar((codomain_legs, domain_legs)))
 end
 
+# specific constructors
+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}
+  ft = FusionTensor(T, fta)
+  for m in eachstoredblock(data_matrix(ft))
+    m = randn!(m)
+  end
+  return ft
+end
+Base.randn(fta::FusionTensorAxes) = randn(Float64, fta)
+
+function FusionTensor(
+  ::UniformScaling, codomain_legs::Tuple{Vararg{AbstractGradedUnitRange}}
+)
+  fta = FusionTensorAxes(codomain_legs, dual.(codomain_legs))
+  ft = FusionTensor(Float64, fta)
+  for m in eachstoredblock(data_matrix(ft))
+    m .= LinearAlgebra.I(size(m, 1))
+  end
+  return ft
+end
+
 # ================================  BlockArrays interface  =================================
 
 function BlockArrays.findblock(ft::FusionTensor, f1::SectorFusionTree, f2::SectorFusionTree)

test/test_basics.jl

@@ -1,7 +1,7 @@
 using Test: @test, @test_throws, @testset
 
 using BlockArrays: Block
-using BlockSparseArrays: BlockSparseArray
+using BlockSparseArrays: BlockSparseArray, eachblockstoredindex
 using FusionTensors:
   FusionTensor,
   FusionTensorAxes,
@@ -28,13 +28,20 @@ using GradedArrays:
   space_isequal
 using TensorAlgebra: tuplemortar
 using TensorProducts: tensor_product
+using LinearAlgebra: LinearAlgebra
 
 include("setup.jl")
 
 @testset "Fusion matrix" begin
   g1 = gradedrange([U1(0) => 1, U1(1) => 2, U1(2) => 3])
   g2 = dual(gradedrange([U1(0) => 2, U1(1) => 2, U1(3) => 1]))
 
+  fta = FusionTensorAxes((g1,), (g2,))
+  ft0 = FusionTensor(Float64, fta)
+  @test ft0 isa FusionTensor
+  @test space_isequal(codomain_axis(ft0), g1)
+  @test space_isequal(domain_axis(ft0), g2)
+
   # check dual convention when initializing data_matrix
   ft0 = FusionTensor(Float64, (g1,), (g2,))
   @test ft0 isa FusionTensor
@@ -266,6 +273,30 @@ end
   @test_throws DimensionMismatch ft7 * ft3
 end
 
+@testset "specific constructors" begin
+  g1 = gradedrange([U1(0) => 1, U1(1) => 2, U1(2) => 3])
+  g2 = gradedrange([U1(0) => 2, U1(1) => 2, U1(3) => 1])
+  g3 = gradedrange([U1(-1) => 1, U1(0) => 2, U1(1) => 1])
+  g4 = gradedrange([U1(-1) => 1, U1(0) => 1, U1(1) => 1])
+
+  fta = FusionTensorAxes((g1,), (g2, g3))
+  @test zeros(fta) isa FusionTensor{Float64,3}
+  @test zeros(ComplexF64, fta) isa FusionTensor{ComplexF64,3}
+  ft1 = randn(ComplexF64, fta)
+  @test ft1 isa FusionTensor{ComplexF64,3}
+  @test all(data_matrix(ft1)[Block(1, 5)] .!= 0)
+  @test randn(fta) isa FusionTensor{Float64,3}
+
+  ft2 = FusionTensor(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 == LinearAlgebra.I(size(m, 1))
+  end
+end
+
 @testset "missing SectorProduct" begin
   g1 = gradedrange([SectorProduct(U1(1)) => 1])
   g2 = gradedrange([SectorProduct(U1(1), SU2(1//2)) => 1])