Allow more customization in ITensorNetwork constructor

src/itensornetwork.jl

@@ -1,5 +1,5 @@
 using DataGraphs: DataGraphs, DataGraph
-using Dictionaries: dictionary
+using Dictionaries: Indices, dictionary
 using ITensors: ITensors, ITensor
 using NamedGraphs: NamedGraphs, NamedEdge, NamedGraph, vertextype
 
@@ -153,20 +153,26 @@ function ITensorNetwork(inds_network::IndsNetwork; kwargs...)
 end
 
 # TODO: Handle `eltype` and `undef` through `generic_state`.
-function generic_state(f, inds...)
-  return f(inds...)
+# `inds` are stored in a `NamedTuple`
+function generic_state(f, inds::NamedTuple)
+  return generic_state(f, reduce(vcat, inds.linkinds; init=inds.siteinds))
 end
-function generic_state(a::AbstractArray, inds...)
-  return itensor(a, inds...)
+
+function generic_state(f, inds::Vector)
+  return f(inds)
+end
+function generic_state(a::AbstractArray, inds::Vector)
+  return itensor(a, inds)
 end
-function generic_state(s::AbstractString, inds...)
-  tensor = state(s, inds[1])
-  # TODO: Remove this and handle with `insert_missing_linkinds`.
-  return contract(tensor, onehot.(vcat(inds[2:end]...) .=> 1)...)
+function generic_state(s::AbstractString, inds::NamedTuple)
+  # TODO: Handle the case of multiple site indices.
+  site_tensors = [state(s, only(inds.siteinds))]
+  link_tensors = [[onehot(i => 1) for i in inds.linkinds[e]] for e in keys(inds.linkinds)]
+  return contract(reduce(vcat, link_tensors; init=site_tensors))
 end
 
-# TODO: This is repeated from `ModelHamiltonians`, put into a
-# single location (such as a `MakeCallable` submodule).
+# TODO: This is similar to `ModelHamiltonians.to_callable`,
+# try merging the two.
 to_callable(value::Type) = value
 to_callable(value::Function) = value
 to_callable(value::AbstractDict) = Base.Fix1(getindex, value)
@@ -194,7 +200,7 @@ function ITensorNetwork(
   itensor_constructor::Function, inds_network::IndsNetwork; link_space=1, kwargs...
 )
   if isnothing(link_space)
-    # Make the the link space is set
+    # Make sure the link space is set
     link_space = 1
   end
   # Graphs.jl uses `zero` to create a graph of the same type
@@ -212,15 +218,9 @@ function ITensorNetwork(
   end
   for v in vertices(tn)
     siteinds = get(inds_network, v, indtype(inds_network)[])
-    linkinds = [
-      get(inds_network, edgetype(inds_network)(v, nv), indtype(inds_network)[]) for
-      nv in neighbors(inds_network, v)
-    ]
-    # TODO: Come up with a better interface besides flattening the indices.
-    # Maybe a namedtuple or dictionary, which indicates which indices
-    # are site and links, which edges the links are associated with, etc.
-    tensor_v = generic_state(itensor_constructor(v), siteinds..., vcat(linkinds...)...)
-    # TODO: Call `insert_missing_linkinds` instead.
+    edges = [edgetype(inds_network)(v, nv) for nv in neighbors(inds_network, v)]
+    linkinds = map(e -> get(inds_network, e, indtype(inds_network)[]), Indices(edges))
+    tensor_v = generic_state(itensor_constructor(v), (; siteinds, linkinds))
     setindex_preserve_graph!(tn, tensor_v, v)
   end
   return tn

src/specialitensornetworks.jl

@@ -9,7 +9,7 @@ Note that passing a link_space will mean the indices of the resulting network do
 """
 function delta_network(eltype::Type, s::IndsNetwork; link_space=nothing)
   return ITensorNetwork(s; link_space) do v
-    return (inds...) -> delta(eltype, inds...)
+    return inds -> delta(eltype, inds)
   end
 end
 
@@ -30,7 +30,7 @@ Build an ITensor network on a graph specified by the inds network s. Bond_dim is
 """
 function random_tensornetwork(eltype::Type, s::IndsNetwork; link_space=nothing)
   return ITensorNetwork(s; link_space) do v
-    return (inds...) -> itensor(randn(eltype, dim(inds)...), inds...)
+    return inds -> itensor(randn(eltype, dim.(inds)...), inds)
   end
 end
 
@@ -57,7 +57,7 @@ function random_tensornetwork(
   distribution::Distribution, s::IndsNetwork; link_space=nothing
 )
   return ITensorNetwork(s; link_space) do v
-    return (inds...) -> itensor(rand(distribution, dim(inds)...), inds...)
+    return inds -> itensor(rand(distribution, dim.(inds)...), inds)
   end
 end
 

test/test_itensornetwork.jl

@@ -29,7 +29,7 @@ using ITensors:
   order,
   sim,
   uniqueinds
-using ITensors.NDTensors: dims
+using ITensors.NDTensors: dim
 using ITensorNetworks:
   ITensorNetworks,
   ⊗,
@@ -160,11 +160,11 @@ using Test: @test, @test_broken, @testset
     )
 
     ψ = ITensorNetwork(g; link_space) do v
-      return (inds...) -> itensor(randn(elt, dims(inds)...), inds...)
+      return inds -> itensor(randn(elt, dim.(inds)...), inds)
     end
     @test eltype(ψ[first(vertices(ψ))]) == elt
     ψ = ITensorNetwork(g; link_space) do v
-      return (inds...) -> itensor(randn(dims(inds)...), inds...)
+      return inds -> itensor(randn(dim.(inds)...), inds)
     end
     @test eltype(ψ[first(vertices(ψ))]) == Float64
     ψ = random_tensornetwork(elt, g; link_space)