Add initial fileloading

Author: lkdvos

Artifacts.toml

@@ -0,0 +1,6 @@
+[fusiondata]
+git-tree-sha1 = "78815c991b175f649504b29f6d52101bc7ee8ead"
+
+    [[fusiondata.download]]
+    sha256 = "95de3103709cdf08e25f098ead80eb9bec9965568720ddbec80d83e52f9102a5"
+    url = "https://github.com/QuantumKitHub/MultiTensorKit.jl/archive/refs/tags/data-v0.1.0.tar.gz"

Project.toml

@@ -3,5 +3,13 @@ uuid = "f0555a46-f681-4ef1-bed5-d64870568636"
 authors = ["Boris De Vos, Laurens Lootens and Lukas Devos"]
 version = "0.1.0"
 
+[deps]
+Artifacts = "56f22d72-fd6d-98f1-02f0-08ddc0907c33"
+JSON3 = "0f8b85d8-7281-11e9-16c2-39a750bddbf1"
+TensorKitSectors = "13a9c161-d5da-41f0-bcbd-e1a08ae0647f"
+
 [compat]
+Artifacts = "1.11.0"
+JSON3 = "1.14.1"
+TensorKitSectors = "0.1.2"
 julia = "1.10"

src/MultiTensorKit.jl

@@ -1,5 +1,11 @@
 module MultiTensorKit
 
-# Write your package code here.
+export BimoduleSector, A4Object
+
+using JSON3
+using Artifacts
+using TensorKitSectors
+
+include("bimodulesector.jl")
 
 end

src/bimodulesector.jl

@@ -0,0 +1,69 @@
+struct BimoduleSector{Name} <: Sector
+    i::Int
+    j::Int
+    label::Int
+end
+
+const A4Object = BimoduleSector{:A4}
+
+# Data from files
+# ---------------
+const artifact_path = joinpath(artifact"fusiondata", "MultiTensorKit.jl-data-v0.1.0")
+
+function extract_Nsymbol(::Type{A4Object})
+    filename = joinpath(artifact_path, "A4", "Nsymbol.json")
+    isfile(filename) || throw(LoadError(filename, 0, "Nsymbol file not found for $Name"))
+    json_string = read(filename, String)
+    Narray = copy(JSON3.read(json_string))
+    return map(reshape(Narray, 12, 12, 12)) do x
+        y = Dict{NTuple{3,Int},Int}()
+        for (k, v) in x
+            a, b, c = parse.(Int, split(string(k)[2:(end - 1)], ", "))
+            y[(a, b, c)] = v
+        end
+    end
+end
+
+let Ncache = extract_Nsymbol(A4Object)
+    function TensorKitSectors.Nsymbol(a::I, b::I, c::I) where {I<:A4Object}
+        # TODO: should this error or return 0?
+        (a.j == b.i && a.i == c.i && b.j == c.j) ||
+            throw(ArgumentError("invalid fusion channel"))
+        i, j, k = a.i, a.j, b.j
+        return get(Ncache[i, j, k], (a.label, b.label, c.label), 0)
+    end
+end
+
+function extract_Fsymbol(::Type{A4Object})
+    return mapreduce(vcat, 1:12) do i
+        filename = joinpath(artifact_path, "A4", "Fsymbol$i.json")
+        @assert isfile(filename)
+        json_string = read(filename, String)
+        Farray_part = copy(JSON3.read(json_string))
+        return map(reshape(Farray_part, 12, 12, 12, 12)) do x
+            y = Dict{NTuple{6,Int},ComplexF64}()
+            for (k, v) in x
+                a, b, c, d, e, f = parse.(Int, split(string(k)[2:(end - 1)], ", "))
+                y[(a, b, c, d, e, f)] = v
+            end
+        end
+    end
+end
+
+let Fcache = extract_Fsymbol(A4Object)
+    function TensorKitSectors.Fsymbol(a::I, b::I, c::I, d::I, e::I,
+                                      f::I) where {I<:A4Object}
+        # TODO: should this error or return 0?
+        (a.j == b.i && b.j == c.i && a.i == d.i && c.j == d.j &&
+         a.i == e.i && b.j == e.j && f.i == a.j && f.j == c.j) ||
+            throw(ArgumentError("invalid fusion channel"))
+
+        i, j, k, l = a.i, a.j, b.j, c.j
+        return get(Fcache[i, j, k, l],
+                   (a.label, b.label, c.label, d.label, e.label, f.label)) do
+            return zeros(sectorscalartype(A4Object),
+                         (Nsymbol(a, b, e), Nsymbol(e, c, d), Nsymbol(b, c, f),
+                          Nsymbol(a, f, d)))
+        end
+    end
+end