Make sure scalartype variants are properly defined

Project.toml

@@ -1,7 +1,7 @@
 name = "SUNRepresentations"
 uuid = "1a50b95c-7aac-476d-a9ce-2bfc675fc617"
 authors = ["Maarten Van Damme <Maarten.VanDamme@UGent.be>, Jutho Haegeman <jutho.haegeman@ugent.be> and Lukas Devos <lukas.devos@UGent.be>"]
-version = "0.3.4"
+version = "0.3.5"
 
 [deps]
 JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
@@ -35,7 +35,7 @@ RationalRoots = "0.1 - 0.2"
 Scratch = "1"
 SparseArrayKit = "0.4"
 TensorKit = "0.15, 0.16"
-TensorKitSectors = "0.3"
+TensorKitSectors = "0.3.5"
 TensorOperations = "5"
 Test = "1"
 TestExtras = "0.3"

src/clebschgordan.jl

@@ -16,7 +16,7 @@ function weightmap(basis)
     return weights
 end
 
-CGC(s1::I, s2::I, s3::I) where {I <: SUNIrrep} = CGC(Float64, s1, s2, s3)
+CGC(s1::I, s2::I, s3::I) where {I <: SUNIrrep} = CGC(sectorscalartype(I), s1, s2, s3)
 function CGC(::Type{T}, s1::SUNIrrep{N}, s2::SUNIrrep{N}, s3::SUNIrrep{N}) where {T, N}
     return _get_CGC(T, (s1, s2, s3))
 end

src/sector.jl

@@ -46,20 +46,24 @@ function TensorKitSectors.Nsymbol(
     return get(directproduct(s1, s2), s3, 0)
 end
 
+TensorKitSectors.sectorscalartype(::Type{<:SUNIrrep}) = Float64
 function TensorKitSectors.fusiontensor(
         s1::SUNIrrep{N}, s2::SUNIrrep{N}, s3::SUNIrrep{N}
     ) where {N}
-    return CGC(Float64, s1, s2, s3)
+    return CGC(s1, s2, s3)
 end
 
 const FCACHE = LRU{Int, Any}(; maxsize = 10)
+
+TensorKitSectors.fusionscalartype(::Type{<:SUNIrrep}) = Float64
+
 function TensorKitSectors.Fsymbol(
         a::SUNIrrep{N}, b::SUNIrrep{N}, c::SUNIrrep{N},
         d::SUNIrrep{N}, e::SUNIrrep{N}, f::SUNIrrep{N}
     ) where {N}
     key = (a, b, c, d, e, f)
     K = typeof(key)
-    V = Array{Float64, 4}
+    V = Array{fusionscalartype(typeof(a)), 4}
     cache::LRU{K, V} = get!(FCACHE, N) do
         return LRU{K, V}(; maxsize = 10^5)
     end
@@ -76,7 +80,8 @@ function _Fsymbol(
     N3 = Nsymbol(b, c, f)
     N4 = Nsymbol(a, f, d)
 
-    (N1 == 0 || N2 == 0 || N3 == 0 || N4 == 0) && return fill(0.0, N1, N2, N3, N4)
+    (N1 == 0 || N2 == 0 || N3 == 0 || N4 == 0) &&
+        return fill(zero(fusionscalartype(typeof(a))), N1, N2, N3, N4)
 
     # computing first diagonal element
     A = fusiontensor(a, b, e)
@@ -90,10 +95,11 @@ function _Fsymbol(
 end
 
 const RCACHE = LRU{Int, Any}(; maxsize = 10)
+TensorKitSectors.braidingscalartype(::Type{<:SUNIrrep}) = Float64
 function TensorKitSectors.Rsymbol(a::SUNIrrep{N}, b::SUNIrrep{N}, c::SUNIrrep{N}) where {N}
     key = (a, b, c)
     K = typeof(key)
-    V = Array{Float64, 2}
+    V = Array{braidingscalartype(typeof(a)), 2}
     cache::LRU{K, V} = get!(RCACHE, N) do
         return LRU{K, V}(; maxsize = 10^5)
     end
@@ -105,7 +111,8 @@ function _Rsymbol(a::SUNIrrep{N}, b::SUNIrrep{N}, c::SUNIrrep{N}) where {N}
     N1 = Nsymbol(a, b, c)
     N2 = Nsymbol(b, a, c)
 
-    (N1 == 0 || N2 == 0) && return fill(0.0, N1, N2)
+    (N1 == 0 || N2 == 0) &&
+        return fill(zero(braidingscalartype(typeof(a))), N1, N2)
 
     A = fusiontensor(a, b, c)[:, :, 1, :]
     B = fusiontensor(b, a, c)[:, :, 1, :]