diff --git a/Project.toml b/Project.toml
index 2ce895f0..2f82e3a0 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "ITensorNetworks"
 uuid = "2919e153-833c-4bdc-8836-1ea460a35fc7"
 authors = ["Matthew Fishman <mfishman@flatironinstitute.org> and contributors"]
-version = "0.7"
+version = "0.8.0"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
@@ -19,6 +19,7 @@ IsApprox = "28f27b66-4bd8-47e7-9110-e2746eb8bed7"
 IterTools = "c8e1da08-722c-5040-9ed9-7db0dc04731e"
 KrylovKit = "0b1a1467-8014-51b9-945f-bf0ae24f4b77"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+NDTensors = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
 NamedGraphs = "678767b0-92e7-4007-89e4-4527a8725b19"
 Observers = "338f10d5-c7f1-4033-a7d1-f9dec39bcaa0"
 PackageExtensionCompat = "65ce6f38-6b18-4e1d-a461-8949797d7930"
diff --git a/README.md b/README.md
index fe933ec8..2f86bee0 100644
--- a/README.md
+++ b/README.md
@@ -39,7 +39,7 @@ julia> using ITensorNetworks: ITensorNetwork, siteinds
 julia> using NamedGraphs: named_grid, subgraph
 
 julia> tn = ITensorNetwork(named_grid(4); link_space=2)
-ITensorNetwork{Int64} with 4 vertices:
+ITensorNetworks.ITensorNetwork{Int64} with 4 vertices:
 4-element Vector{Int64}:
  1
  2
@@ -90,7 +90,7 @@ and here is a similar example for making a tensor network on a grid (a tensor pr
 
 ```julia
 julia> tn = ITensorNetwork(named_grid((2, 2)); link_space=2)
-ITensorNetwork{Tuple{Int64, Int64}} with 4 vertices:
+ITensorNetworks.ITensorNetwork{Tuple{Int64, Int64}} with 4 vertices:
 4-element Vector{Tuple{Int64, Int64}}:
  (1, 1)
  (2, 1)
@@ -125,7 +125,7 @@ julia> neighbors(tn, (1, 2))
  (2, 2)
 
 julia> tn_1 = subgraph(v -> v[1] == 1, tn)
-ITensorNetwork{Tuple{Int64, Int64}} with 2 vertices:
+ITensorNetworks.ITensorNetwork{Tuple{Int64, Int64}} with 2 vertices:
 2-element Vector{Tuple{Int64, Int64}}:
  (1, 1)
  (1, 2)
@@ -139,7 +139,7 @@ with vertex data:
  (1, 2) │ ((dim=2|id=723|"1×1,1×2"), (dim=2|id=712|"1×2,2×2"))
 
 julia> tn_2 = subgraph(v -> v[1] == 2, tn)
-ITensorNetwork{Tuple{Int64, Int64}} with 2 vertices:
+ITensorNetworks.ITensorNetwork{Tuple{Int64, Int64}} with 2 vertices:
 2-element Vector{Tuple{Int64, Int64}}:
  (2, 1)
  (2, 2)
@@ -184,7 +184,7 @@ and edge data:
 0-element Dictionaries.Dictionary{NamedGraphs.NamedEdge{Int64}, Vector{ITensors.Index}}
 
 julia> tn1 = ITensorNetwork(s; link_space=2)
-ITensorNetwork{Int64} with 3 vertices:
+ITensorNetworks.ITensorNetwork{Int64} with 3 vertices:
 3-element Vector{Int64}:
  1
  2
@@ -201,7 +201,7 @@ with vertex data:
  3 │ ((dim=2|id=656|"S=1/2,Site,n=3"), (dim=2|id=190|"2,3"))
 
 julia> tn2 = ITensorNetwork(s; link_space=2)
-ITensorNetwork{Int64} with 3 vertices:
+ITensorNetworks.ITensorNetwork{Int64} with 3 vertices:
 3-element Vector{Int64}:
  1
  2
diff --git a/src/ITensorNetworks.jl b/src/ITensorNetworks.jl
index bfe4b8a2..7e69dd39 100644
--- a/src/ITensorNetworks.jl
+++ b/src/ITensorNetworks.jl
@@ -36,7 +36,6 @@ include("caches/beliefpropagationcache.jl")
 include("contraction_tree_to_graph.jl")
 include("gauging.jl")
 include("utils.jl")
-include("tensornetworkoperators.jl")
 include("ITensorsExt/itensorutils.jl")
 include("solvers/local_solvers/eigsolve.jl")
 include("solvers/local_solvers/exponentiate.jl")
diff --git a/src/abstractitensornetwork.jl b/src/abstractitensornetwork.jl
index 3e044abe..958a5845 100644
--- a/src/abstractitensornetwork.jl
+++ b/src/abstractitensornetwork.jl
@@ -23,7 +23,6 @@ using ITensors:
   commoninds,
   commontags,
   contract,
-  convert_eltype,
   dag,
   hascommoninds,
   noprime,
@@ -39,18 +38,18 @@ using ITensors:
   swaptags
 using ITensors.ITensorMPS: ITensorMPS, add, linkdim, linkinds, siteinds
 using ITensors.ITensorVisualizationCore: ITensorVisualizationCore, visualize
-using ITensors.NDTensors: NDTensors, dim
-using LinearAlgebra: LinearAlgebra
+using LinearAlgebra: LinearAlgebra, factorize
 using NamedGraphs:
   NamedGraphs,
   NamedGraph,
   ⊔,
+  directed_graph,
   incident_edges,
   not_implemented,
   rename_vertices,
   vertex_to_parent_vertex,
   vertextype
-using NamedGraphs: directed_graph
+using NDTensors: NDTensors, dim
 using SplitApplyCombine: flatten
 
 abstract type AbstractITensorNetwork{V} <: AbstractDataGraph{V,ITensor,ITensor} end
@@ -174,41 +173,26 @@ function Base.Vector{ITensor}(tn::AbstractITensorNetwork)
 end
 
 # Convenience wrapper
-# TODO: Delete this and just use `Vector{ITensor}`, or maybe
-# it should output a dictionary or be called `eachtensor`?
-itensors(tn::AbstractITensorNetwork) = Vector{ITensor}(tn)
+function tensors(tn::AbstractITensorNetwork, vertices=vertices(tn))
+  return map(v -> tn[v], Indices(vertices))
+end
 
 #
 # Promotion and conversion
 #
 
-function LinearAlgebra.promote_leaf_eltypes(tn::AbstractITensorNetwork)
-  return LinearAlgebra.promote_leaf_eltypes(itensors(tn))
-end
-
 function promote_indtypeof(tn::AbstractITensorNetwork)
-  return mapreduce(promote_indtype, vertices(tn)) do v
-    return indtype(tn[v])
+  return mapreduce(promote_indtype, tensors(tn)) do t
+    return indtype(t)
   end
 end
 
-# TODO: Delete in favor of `scalartype`.
-function ITensors.promote_itensor_eltype(tn::AbstractITensorNetwork)
-  return LinearAlgebra.promote_leaf_eltypes(tn)
+function NDTensors.scalartype(tn::AbstractITensorNetwork)
+  return mapreduce(eltype, promote_type, tensors(tn); init=Bool)
 end
 
-NDTensors.scalartype(tn::AbstractITensorNetwork) = LinearAlgebra.promote_leaf_eltypes(tn)
-
-# TODO: eltype(::AbstractITensorNetwork) (cannot behave the same as eltype(::ITensors.AbstractMPS))
-
-# TODO: mimic ITensors.AbstractMPS implementation using map
-function ITensors.convert_leaf_eltype(eltype::Type, tn::AbstractITensorNetwork)
-  tn = copy(tn)
-  vertex_data(tn) .= convert_eltype.(Ref(eltype), vertex_data(tn))
-  return tn
-end
+# TODO: Define `eltype(::AbstractITensorNetwork)` as `ITensor`?
 
-# TODO: Mimic ITensors.AbstractMPS implementation using map
 # TODO: Implement using `adapt`
 function NDTensors.convert_scalartype(eltype::Type{<:Number}, tn::AbstractITensorNetwork)
   tn = copy(tn)
@@ -217,7 +201,7 @@ function NDTensors.convert_scalartype(eltype::Type{<:Number}, tn::AbstractITenso
 end
 
 function Base.complex(tn::AbstractITensorNetwork)
-  return NDTensors.convert_scalartype(complex(LinearAlgebra.promote_leaf_eltypes(tn)), tn)
+  return NDTensors.convert_scalartype(complex(scalartype(tn)), tn)
 end
 
 #
@@ -251,7 +235,9 @@ end
 # Alias
 indsnetwork(tn::AbstractITensorNetwork) = IndsNetwork(tn)
 
-function external_indsnetwork(tn::AbstractITensorNetwork)
+# TODO: Output a `VertexDataGraph`? Unfortunately
+# `IndsNetwork` doesn't allow iterating over vertex data.
+function ITensorMPS.siteinds(tn::AbstractITensorNetwork)
   is = IndsNetwork(underlying_graph(tn))
   for v in vertices(tn)
     is[v] = uniqueinds(tn, v)
@@ -259,25 +245,12 @@ function external_indsnetwork(tn::AbstractITensorNetwork)
   return is
 end
 
-# For backwards compatibility
-# TODO: Delete this
-ITensorMPS.siteinds(tn::AbstractITensorNetwork) = external_indsnetwork(tn)
-
-# External indsnetwork of the flattened network, with vertices
-# mapped back to `tn1`.
-function flatten_external_indsnetwork(
-  tn1::AbstractITensorNetwork, tn2::AbstractITensorNetwork
-)
-  is = external_indsnetwork(sim(tn1; sites=[]) ⊗ tn2)
-  flattened_is = IndsNetwork(underlying_graph(tn1))
-  for v in vertices(flattened_is)
-    # setindex_preserve_graph!(flattened_is, unioninds(is[v, 1], is[v, 2]), v)
-    flattened_is[v] = unioninds(is[v, 1], is[v, 2])
-  end
-  return flattened_is
+function flatten_siteinds(tn::AbstractITensorNetwork)
+  # reduce(noncommoninds, tensors(tn))
+  return unique(flatten([uniqueinds(tn, v) for v in vertices(tn)]))
 end
 
-function internal_indsnetwork(tn::AbstractITensorNetwork)
+function ITensorMPS.linkinds(tn::AbstractITensorNetwork)
   is = IndsNetwork(underlying_graph(tn))
   for e in edges(tn)
     is[e] = commoninds(tn, e)
@@ -285,20 +258,22 @@ function internal_indsnetwork(tn::AbstractITensorNetwork)
   return is
 end
 
-# For backwards compatibility
-# TODO: Delete this
-ITensorMPS.linkinds(tn::AbstractITensorNetwork) = internal_indsnetwork(tn)
+function flatten_linkinds(tn::AbstractITensorNetwork)
+  return unique(flatten([commoninds(tn, e) for e in edges(tn)]))
+end
 
 #
 # Index access
 #
 
-function neighbor_itensors(tn::AbstractITensorNetwork, vertex)
-  return [tn[vn] for vn in neighbors(tn, vertex)]
+function neighbor_tensors(tn::AbstractITensorNetwork, vertex)
+  return tensors(tn, neighbors(tn, vertex))
 end
 
 function ITensors.uniqueinds(tn::AbstractITensorNetwork, vertex)
-  return uniqueinds(tn[vertex], neighbor_itensors(tn, vertex)...)
+  # TODO: Splatting here isn't good, make a version that works for
+  # collections of ITensors.
+  return reduce(uniqueinds, Iterators.flatten(([tn[vertex]], neighbor_tensors(tn, vertex))))
 end
 
 function ITensors.uniqueinds(tn::AbstractITensorNetwork, edge::AbstractEdge)
@@ -322,14 +297,6 @@ function ITensorMPS.linkinds(tn::AbstractITensorNetwork, edge)
   return commoninds(tn, edge)
 end
 
-function internalinds(tn::AbstractITensorNetwork)
-  return unique(flatten([commoninds(tn, e) for e in edges(tn)]))
-end
-
-function externalinds(tn::AbstractITensorNetwork)
-  return unique(flatten([uniqueinds(tn, v) for v in vertices(tn)]))
-end
-
 # Priming and tagging (changing Index identifiers)
 function ITensors.replaceinds(
   tn::AbstractITensorNetwork, is_is′::Pair{<:IndsNetwork,<:IndsNetwork}
@@ -439,9 +406,7 @@ function Base.isapprox(
   x::AbstractITensorNetwork,
   y::AbstractITensorNetwork;
   atol::Real=0,
-  rtol::Real=Base.rtoldefault(
-    LinearAlgebra.promote_leaf_eltypes(x), LinearAlgebra.promote_leaf_eltypes(y), atol
-  ),
+  rtol::Real=Base.rtoldefault(scalartype(x), scalartype(y), atol),
 )
   error("Not implemented")
   d = norm(x - y)
diff --git a/src/apply.jl b/src/apply.jl
index 559438e2..948ccb7c 100644
--- a/src/apply.jl
+++ b/src/apply.jl
@@ -1,3 +1,4 @@
+using Graphs: has_edge
 using LinearAlgebra: qr
 using ITensors: Ops
 using ITensors:
diff --git a/src/approx_itensornetwork/partition.jl b/src/approx_itensornetwork/partition.jl
index 9f89d063..7dd994f5 100644
--- a/src/approx_itensornetwork/partition.jl
+++ b/src/approx_itensornetwork/partition.jl
@@ -1,3 +1,9 @@
+using DataGraphs: AbstractDataGraph, DataGraph, edge_data, vertex_data
+using Dictionaries: Dictionary
+using Graphs: AbstractGraph, add_edge!, has_edge, dst, edges, edgetype, src, vertices
+using ITensors: ITensor, noncommoninds
+using NamedGraphs: NamedGraph, subgraph
+
 function _partition(g::AbstractGraph, subgraph_vertices)
   partitioned_graph = DataGraph(
     NamedGraph(eachindex(subgraph_vertices)),
diff --git a/src/formnetworks/bilinearformnetwork.jl b/src/formnetworks/bilinearformnetwork.jl
index bcb59704..14d21114 100644
--- a/src/formnetworks/bilinearformnetwork.jl
+++ b/src/formnetworks/bilinearformnetwork.jl
@@ -57,7 +57,7 @@ function BilinearFormNetwork(
   dual_site_index_map=default_dual_site_index_map,
   kwargs...,
 )
-  @assert issetequal(externalinds(bra), externalinds(ket))
+  @assert issetequal(flatten_siteinds(bra), flatten_siteinds(ket))
   operator_inds = union_all_inds(siteinds(ket), dual_site_index_map(siteinds(ket)))
   O = ITensorNetwork(Op("I"), operator_inds)
   return BilinearFormNetwork(O, bra, ket; dual_site_index_map, kwargs...)
diff --git a/src/solvers/contract.jl b/src/solvers/contract.jl
index cfc90fd6..1e6ddeec 100644
--- a/src/solvers/contract.jl
+++ b/src/solvers/contract.jl
@@ -72,11 +72,6 @@ end
 Overload of `ITensors.apply`.
 """
 function ITensors.apply(tn1::AbstractTTN, tn2::AbstractTTN; init, kwargs...)
-  if !isone(plev_diff(flatten_external_indsnetwork(tn1, tn2), external_indsnetwork(init)))
-    error(
-      "Initial guess `init` needs to primelevel one less than the contraction tn1 and tn2."
-    )
-  end
   init = init'
   tn12 = contract(tn1, tn2; init, kwargs...)
   return replaceprime(tn12, 1 => 0)
@@ -85,24 +80,7 @@ end
 function sum_apply(
   tns::Vector{<:Tuple{<:AbstractTTN,<:AbstractTTN}}; alg="fit", init, kwargs...
 )
-  if !isone(
-    plev_diff(
-      flatten_external_indsnetwork(first(first(tns)), last(first(tns))),
-      external_indsnetwork(init),
-    ),
-  )
-    error(
-      "Initial guess `init` needs to primelevel one less than the contraction tn1 and tn2."
-    )
-  end
-
   init = init'
   tn12 = sum_contract(Algorithm(alg), tns; init, kwargs...)
   return replaceprime(tn12, 1 => 0)
 end
-
-function plev_diff(a::IndsNetwork, b::IndsNetwork)
-  pla = plev(only(a[first(vertices(a))]))
-  plb = plev(only(b[first(vertices(b))]))
-  return pla - plb
-end
diff --git a/src/tensornetworkoperators.jl b/src/tensornetworkoperators.jl
deleted file mode 100644
index 080c723b..00000000
--- a/src/tensornetworkoperators.jl
+++ /dev/null
@@ -1,48 +0,0 @@
-using Graphs: has_edge
-using ITensors: ITensors, commoninds, product
-using LinearAlgebra: factorize
-
-"""
-Take a vector of gates which act on different edges/ vertices of an Inds network and construct the tno which represents prod(gates).
-"""
-function gate_group_to_tno(s::IndsNetwork, gates::Vector{ITensor})
-
-  #Construct indsnetwork for TNO
-  s_O = union_all_inds(s, prime(s; links=[]))
-
-  # Make a TNO with `I` on every site.
-  O = ITensorNetwork(Op("I"), s_O)
-
-  for gate in gates
-    v⃗ = vertices(s)[findall(i -> (length(commoninds(s[i], inds(gate))) != 0), vertices(s))]
-    if length(v⃗) == 1
-      O[v⃗[1]] = product(O[v⃗[1]], gate)
-    elseif length(v⃗) == 2
-      e = v⃗[1] => v⃗[2]
-      if !has_edge(s, e)
-        error("Vertices where the gates are being applied must be neighbors for now.")
-      end
-      Osrc, Odst = factorize(gate, commoninds(O[v⃗[1]], gate))
-      O[v⃗[1]] = product(O[v⃗[1]], Osrc)
-      O[v⃗[2]] = product(O[v⃗[2]], Odst)
-    else
-      error(
-        "Can only deal with gates acting on one or two sites for now. Physical indices of the gates must also match those in the IndsNetwork.",
-      )
-    end
-  end
-
-  return combine_linkinds(O)
-end
-
-"""Take a series of gates acting on the physical indices specified by IndsNetwork convert into a series of tnos
-whose product represents prod(gates). Useful for keeping the bond dimension of each tno low (as opposed to just building a single tno)"""
-function get_tnos(s::IndsNetwork, gates::Vector{ITensor})
-  tnos = ITensorNetwork[]
-  gate_groups = group_commuting_itensors(gates)
-  for group in gate_groups
-    push!(tnos, gate_group_to_tno(s, group))
-  end
-
-  return tnos
-end
diff --git a/src/treetensornetworks/abstracttreetensornetwork.jl b/src/treetensornetworks/abstracttreetensornetwork.jl
index 35cbd128..33146a70 100644
--- a/src/treetensornetworks/abstracttreetensornetwork.jl
+++ b/src/treetensornetworks/abstracttreetensornetwork.jl
@@ -285,9 +285,7 @@ function Base.isapprox(
   x::AbstractTTN,
   y::AbstractTTN;
   atol::Real=0,
-  rtol::Real=Base.rtoldefault(
-    LinearAlgebra.promote_leaf_eltypes(x), LinearAlgebra.promote_leaf_eltypes(y), atol
-  ),
+  rtol::Real=Base.rtoldefault(scalartype(x), scalartype(y), atol),
 )
   d = norm(x - y)
   if isfinite(d)
diff --git a/src/treetensornetworks/projttns/abstractprojttn.jl b/src/treetensornetworks/projttns/abstractprojttn.jl
index 63ff4bf7..d86cc48a 100644
--- a/src/treetensornetworks/projttns/abstractprojttn.jl
+++ b/src/treetensornetworks/projttns/abstractprojttn.jl
@@ -1,6 +1,6 @@
 using DataGraphs: DataGraphs, underlying_graph
 using Graphs: neighbors
-using ITensors: ITensor, contract, order
+using ITensors: ITensor, contract, order, product
 using ITensors.ITensorMPS: ITensorMPS, nsite
 using NamedGraphs: NamedGraphs, NamedEdge, incident_edges, vertextype
 
diff --git a/src/treetensornetworks/projttns/projttnsum.jl b/src/treetensornetworks/projttns/projttnsum.jl
index 4abb8965..73b87af8 100644
--- a/src/treetensornetworks/projttns/projttnsum.jl
+++ b/src/treetensornetworks/projttns/projttnsum.jl
@@ -1,4 +1,4 @@
-using ITensors: ITensors, contract
+using ITensors: ITensors, contract, product
 using ITensors.LazyApply: LazyApply, terms
 using NamedGraphs: NamedGraphs, incident_edges
 
diff --git a/src/treetensornetworks/ttn.jl b/src/treetensornetworks/ttn.jl
index 31bc9770..a30c0776 100644
--- a/src/treetensornetworks/ttn.jl
+++ b/src/treetensornetworks/ttn.jl
@@ -1,6 +1,6 @@
 using Graphs: path_graph
 using ITensors: ITensor
-using LinearAlgebra: normalize
+using LinearAlgebra: factorize, normalize
 using NamedGraphs: vertextype
 
 """
diff --git a/test/Project.toml b/test/Project.toml
index 8ac3670c..9e02c3ef 100644
--- a/test/Project.toml
+++ b/test/Project.toml
@@ -16,6 +16,7 @@ KaHyPar = "2a6221f6-aa48-11e9-3542-2d9e0ef01880"
 KrylovKit = "0b1a1467-8014-51b9-945f-bf0ae24f4b77"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Metis = "2679e427-3c69-5b7f-982b-ece356f1e94b"
+NDTensors = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
 NamedGraphs = "678767b0-92e7-4007-89e4-4527a8725b19"
 OMEinsumContractionOrders = "6f22d1fd-8eed-4bb7-9776-e7d684900715"
 Observers = "338f10d5-c7f1-4033-a7d1-f9dec39bcaa0"
diff --git a/test/test_forms.jl b/test/test_forms.jl
index a9a0e453..e6cda5cd 100644
--- a/test/test_forms.jl
+++ b/test/test_forms.jl
@@ -10,7 +10,7 @@ using ITensorNetworks:
   bra_vertex,
   dual_index_map,
   environment,
-  externalinds,
+  flatten_siteinds,
   ket_network,
   ket_vertex,
   operator_network,
@@ -36,7 +36,7 @@ using Random: Random
 
   blf = BilinearFormNetwork(A, ψbra, ψket)
   @test nv(blf) == nv(ψket) + nv(ψbra) + nv(A)
-  @test isempty(externalinds(blf))
+  @test isempty(flatten_siteinds(blf))
 
   @test underlying_graph(ket_network(blf)) == underlying_graph(ψket)
   @test underlying_graph(operator_network(blf)) == underlying_graph(A)
@@ -44,7 +44,7 @@ using Random: Random
 
   qf = QuadraticFormNetwork(A, ψket)
   @test nv(qf) == 2 * nv(ψbra) + nv(A)
-  @test isempty(externalinds(qf))
+  @test isempty(flatten_siteinds(qf))
 
   v = (1, 1)
   new_tensor = randomITensor(inds(ψket[v]))
diff --git a/test/test_itensornetwork.jl b/test/test_itensornetwork.jl
index 18845dd5..cc5c6217 100644
--- a/test/test_itensornetwork.jl
+++ b/test/test_itensornetwork.jl
@@ -34,18 +34,17 @@ using ITensors:
   scalartype,
   sim,
   uniqueinds
-using ITensors.NDTensors: dim
 using ITensorNetworks:
   ITensorNetworks,
   ⊗,
   IndsNetwork,
   ITensorNetwork,
   contraction_sequence,
-  externalinds,
+  flatten_linkinds,
+  flatten_siteinds,
   inner_network,
-  internalinds,
   linkinds,
-  neighbor_itensors,
+  neighbor_tensors,
   norm_sqr,
   norm_sqr_network,
   orthogonalize,
@@ -54,6 +53,7 @@ using ITensorNetworks:
   ttn
 using LinearAlgebra: factorize
 using NamedGraphs: NamedEdge, incident_edges, named_comb_tree, named_grid
+using NDTensors: NDTensors, dim
 using Random: Random, randn!
 using Test: @test, @test_broken, @testset
 
@@ -323,7 +323,7 @@ const elts = (Float32, Float64, Complex{Float32}, Complex{Float64})
     s = siteinds("S=1/2", g)
     ψ = ITensorNetwork(s; link_space=2)
 
-    nt = neighbor_itensors(ψ, (1, 1))
+    nt = neighbor_tensors(ψ, (1, 1))
     @test length(nt) == 2
     @test all(map(hascommoninds(ψ[1, 1]), nt))
 
@@ -342,8 +342,8 @@ const elts = (Float32, Float64, Complex{Float32}, Complex{Float64})
 
     @test linkinds(ψ, e) == commoninds(ψ[1, 1], ψ[2, 1])
 
-    @test length(externalinds(ψ)) == length(vertices(g))
-    @test length(internalinds(ψ)) == length(edges(g))
+    @test length(flatten_siteinds(ψ)) == length(vertices(g))
+    @test length(flatten_linkinds(ψ)) == length(edges(g))
   end
 
   @testset "eltype conversion, $new_eltype" for new_eltype in (Float32, ComplexF64)
@@ -351,10 +351,10 @@ const elts = (Float32, Float64, Complex{Float32}, Complex{Float64})
     g = named_grid(dims)
     s = siteinds("S=1/2", g)
     ψ = random_tensornetwork(s; link_space=2)
-    @test ITensors.scalartype(ψ) == Float64
+    @test scalartype(ψ) == Float64
 
-    ϕ = ITensors.convert_leaf_eltype(new_eltype, ψ)
-    @test ITensors.scalartype(ϕ) == new_eltype
+    ϕ = NDTensors.convert_scalartype(new_eltype, ψ)
+    @test scalartype(ϕ) == new_eltype
   end
 
   @testset "Construction from state map" for elt in (Float32, ComplexF64)
diff --git a/test/test_tno.jl b/test/test_tno.jl
deleted file mode 100644
index 30811130..00000000
--- a/test/test_tno.jl
+++ /dev/null
@@ -1,65 +0,0 @@
-@eval module $(gensym())
-using Graphs: vertices
-using ITensorNetworks:
-  apply,
-  flatten_networks,
-  group_commuting_itensors,
-  gate_group_to_tno,
-  get_tnos,
-  random_tensornetwork,
-  siteinds
-using ITensors: ITensor, inner, noprime
-using ITensorNetworks.ModelHamiltonians: ModelHamiltonians
-using NamedGraphs: named_grid
-using Test: @test, @testset
-
-@testset "TN operator Basics" begin
-  L = 3
-  g = named_grid((L, L))
-  s = siteinds("S=1/2", g)
-
-  ℋ = ModelHamiltonians.ising(g; h=1.5)
-  gates = Vector{ITensor}(ℋ, s)
-  gate_groups = group_commuting_itensors(gates)
-
-  @test typeof(gate_groups) == Vector{Vector{ITensor}}
-
-  #Construct a number of tnos whose product is prod(gates)
-  tnos = get_tnos(s, gates)
-  @test length(tnos) == length(gate_groups)
-
-  #Construct a single tno which represents prod(gates)
-  single_tno = gate_group_to_tno(s, gates)
-
-  ψ = random_tensornetwork(s; link_space=2)
-
-  ψ_gated = copy(ψ)
-
-  for gate in gates
-    ψ_gated = apply(gate, ψ_gated)
-  end
-  ψ_tnod = copy(ψ)
-
-  for tno in tnos
-    ψ_tnod = flatten_networks(ψ_tnod, tno)
-    for v in vertices(ψ_tnod)
-      ψ_tnod[v] = noprime(ψ_tnod[v])
-    end
-  end
-  ψ_tno = copy(ψ)
-  ψ_tno = flatten_networks(ψ_tno, single_tno)
-  for v in vertices(ψ_tno)
-    ψ_tno[v] = noprime(ψ_tno[v])
-  end
-
-  z1 = inner(ψ_gated, ψ_gated)
-  z2 = inner(ψ_tnod, ψ_tnod)
-  z3 = inner(ψ_tno, ψ_tno)
-  f12 = inner(ψ_tnod, ψ_gated) / sqrt(z1 * z2)
-  f13 = inner(ψ_tno, ψ_gated) / sqrt(z1 * z3)
-  f23 = inner(ψ_tno, ψ_tnod) / sqrt(z2 * z3)
-  @test f12 * conj(f12) ≈ 1.0
-  @test f13 * conj(f13) ≈ 1.0
-  @test f23 * conj(f23) ≈ 1.0
-end
-end