Named changes

Project.toml

@@ -1,7 +1,7 @@
 name = "ITensorNetworks"
 uuid = "2919e153-833c-4bdc-8836-1ea460a35fc7"
 authors = ["Matthew Fishman <[email protected]> and contributors"]
-version = "0.5"
+version = "0.6"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"

src/approx_itensornetwork/ttn_svd.jl

@@ -2,7 +2,7 @@ using IterTools: partition
 """
 Approximate a `partition` into an output ITensorNetwork
 with the binary tree structure defined by `out_tree` by
-first transforming the partition into a TTN, then truncating
+first transforming the partition into a ttn, then truncating
 the ttn using a sequence of SVDs.
 """
 function _approx_itensornetwork_ttn_svd!(
@@ -22,7 +22,7 @@ function _approx_itensornetwork_ttn_svd!(
       contraction_sequence_kwargs=contraction_sequence_kwargs,
     )
   end
-  truncate_ttn = truncate(TTN(tn); cutoff=cutoff, maxdim=maxdim, root_vertex=root)
+  truncate_ttn = truncate(ttn(tn); cutoff=cutoff, maxdim=maxdim, root_vertex=root)
   out_tn = ITensorNetwork(truncate_ttn)
   root_tensor = out_tn[root]
   root_norm = norm(root_tensor)

src/solvers/contract.jl

@@ -22,7 +22,7 @@ function sum_contract(
   )
   any(ns .!= n) &&
     throw(DimensionMismatch("Number of sites in different operators ($n) do not match"))
-  # ToDo: Write test for single-vertex TTN, this implementation has not been tested.
+  # ToDo: Write test for single-vertex ttn, this implementation has not been tested.
   if n == 1
     res = 0
     for (tn1, tn2) in zip(tn1s, tn2s)

src/specialitensornetworks.jl

@@ -101,41 +101,41 @@ end
 """
 Build an ITensor network on a graph specified by the inds network s. Bond_dim is given by link_space and entries are randomised (normal distribution, mean 0 std 1)
 """
-function randomITensorNetwork(eltype::Type, s::IndsNetwork; link_space=nothing)
+function random_itensornetwork(eltype::Type, s::IndsNetwork; link_space=nothing)
   return ITensorNetwork(s; link_space) do v, inds...
     itensor(randn(eltype, dim(inds)...), inds...)
   end
 end
 
-function randomITensorNetwork(s::IndsNetwork; link_space=nothing)
-  return randomITensorNetwork(Float64, s; link_space)
+function random_itensornetwork(s::IndsNetwork; link_space=nothing)
+  return random_itensornetwork(Float64, s; link_space)
 end
 
-@traitfn function randomITensorNetwork(
+@traitfn function random_itensornetwork(
   eltype::Type, g::::IsUnderlyingGraph; link_space=nothing
 )
-  return randomITensorNetwork(eltype, IndsNetwork(g); link_space)
+  return random_itensornetwork(eltype, IndsNetwork(g); link_space)
 end
 
-@traitfn function randomITensorNetwork(g::::IsUnderlyingGraph; link_space=nothing)
-  return randomITensorNetwork(Float64, IndsNetwork(g); link_space)
+@traitfn function random_itensornetwork(g::::IsUnderlyingGraph; link_space=nothing)
+  return random_itensornetwork(Float64, IndsNetwork(g); link_space)
 end
 
 """
 Build an ITensor network on a graph specified by the inds network s.
 Bond_dim is given by link_space and entries are randomized.
 The random distribution is based on the input argument `distribution`.
 """
-function randomITensorNetwork(
+function random_itensornetwork(
   distribution::Distribution, s::IndsNetwork; link_space=nothing
 )
   return ITensorNetwork(s; link_space) do v, inds...
     itensor(rand(distribution, dim(inds)...), inds...)
   end
 end
 
-@traitfn function randomITensorNetwork(
+@traitfn function random_itensornetwork(
   distribution::Distribution, g::::IsUnderlyingGraph; link_space=nothing
 )
-  return randomITensorNetwork(distribution, IndsNetwork(g); link_space)
+  return random_itensornetwork(distribution, IndsNetwork(g); link_space)
 end

src/treetensornetworks/abstracttreetensornetwork.jl

@@ -295,7 +295,7 @@ function Base.:+(
   @assert all(ψ -> nv(first(ψs)) == nv(ψ), ψs)
 
   # Output state
-  ϕ = TTN(siteinds(ψs[1]))
+  ϕ = ttn(siteinds(ψs[1]))
 
   vs = post_order_dfs_vertices(ϕ, root_vertex)
   es = post_order_dfs_edges(ϕ, root_vertex)

src/treetensornetworks/opsum_to_ttn.jl

@@ -252,7 +252,7 @@ function ttn_svd(
     link_space[e] = Index(qi...; tags=edge_tag(e), dir=linkdir_ref)
   end
 
-  H = TTN(sites0)   # initialize TTN without the dummy indices added
+  H = ttn(sites0)   # initialize TTN without the dummy indices added
   function qnblock(i::Index, q::QN)
     for b in 2:(nblocks(i) - 1)
       flux(i, Block(b)) == q && return b
@@ -496,12 +496,12 @@ function sorteachterm(os::OpSum, sites::IndsNetwork{V,<:Index}, root_vertex::V)
 end
 
 """
-    TTN(os::OpSum, sites::IndsNetwork{<:Index}; kwargs...)
-    TTN(eltype::Type{<:Number}, os::OpSum, sites::IndsNetwork{<:Index}; kwargs...)
+    ttn(os::OpSum, sites::IndsNetwork{<:Index}; kwargs...)
+    ttn(eltype::Type{<:Number}, os::OpSum, sites::IndsNetwork{<:Index}; kwargs...)
        
 Convert an OpSum object `os` to a TreeTensorNetwork, with indices given by `sites`.
 """
-function TTN(
+function ttn(
   os::OpSum,
   sites::IndsNetwork;
   root_vertex=default_root_vertex(sites),
@@ -530,37 +530,37 @@ function TTN(
 end
 
 function mpo(os::OpSum, external_inds::Vector; kwargs...)
-  return TTN(os, path_indsnetwork(external_inds); kwargs...)
+  return ttn(os, path_indsnetwork(external_inds); kwargs...)
 end
 
 # Conversion from other formats
-function TTN(o::Op, s::IndsNetwork; kwargs...)
-  return TTN(OpSum{Float64}() + o, s; kwargs...)
+function ttn(o::Op, s::IndsNetwork; kwargs...)
+  return ttn(OpSum{Float64}() + o, s; kwargs...)
 end
 
-function TTN(o::Scaled{C,Op}, s::IndsNetwork; kwargs...) where {C}
-  return TTN(OpSum{C}() + o, s; kwargs...)
+function ttn(o::Scaled{C,Op}, s::IndsNetwork; kwargs...) where {C}
+  return ttn(OpSum{C}() + o, s; kwargs...)
 end
 
-function TTN(o::Sum{Op}, s::IndsNetwork; kwargs...)
-  return TTN(OpSum{Float64}() + o, s; kwargs...)
+function ttn(o::Sum{Op}, s::IndsNetwork; kwargs...)
+  return ttn(OpSum{Float64}() + o, s; kwargs...)
 end
 
-function TTN(o::Prod{Op}, s::IndsNetwork; kwargs...)
-  return TTN(OpSum{Float64}() + o, s; kwargs...)
+function ttn(o::Prod{Op}, s::IndsNetwork; kwargs...)
+  return ttn(OpSum{Float64}() + o, s; kwargs...)
 end
 
-function TTN(o::Scaled{C,Prod{Op}}, s::IndsNetwork; kwargs...) where {C}
-  return TTN(OpSum{C}() + o, s; kwargs...)
+function ttn(o::Scaled{C,Prod{Op}}, s::IndsNetwork; kwargs...) where {C}
+  return ttn(OpSum{C}() + o, s; kwargs...)
 end
 
-function TTN(o::Sum{Scaled{C,Op}}, s::IndsNetwork; kwargs...) where {C}
-  return TTN(OpSum{C}() + o, s; kwargs...)
+function ttn(o::Sum{Scaled{C,Op}}, s::IndsNetwork; kwargs...) where {C}
+  return ttn(OpSum{C}() + o, s; kwargs...)
 end
 
 # Catch-all for leaf eltype specification
-function TTN(eltype::Type{<:Number}, os, sites::IndsNetwork; kwargs...)
-  return NDTensors.convert_scalartype(eltype, TTN(os, sites; kwargs...))
+function ttn(eltype::Type{<:Number}, os, sites::IndsNetwork; kwargs...)
+  return NDTensors.convert_scalartype(eltype, ttn(os, sites; kwargs...))
 end
 
 # 

src/treetensornetworks/ttn.jl

@@ -26,12 +26,16 @@ end
 
 const TTN = TreeTensorNetwork
 
+function ttn(itensor_network::ITensorNetwork, ortho_center::Vector)
+  return ttn(itensor_network, ortho_center)
+end
+
 function data_graph_type(G::Type{<:TTN})
   return data_graph_type(fieldtype(G, :itensor_network))
 end
 
 function Base.copy(ψ::TTN)
-  return TTN(copy(ψ.itensor_network), copy(ψ.ortho_center))
+  return ttn(copy(ψ.itensor_network), copy(ψ.ortho_center))
 end
 
 # Field access
@@ -44,36 +48,36 @@ data_graph(ψ::TTN) = data_graph(itensor_network(ψ))
 # Constructor
 # 
 
-TTN(tn::ITensorNetwork, args...) = TTN{vertextype(tn)}(tn, args...)
+ttn(tn::ITensorNetwork, args...) = TTN{vertextype(tn)}(tn, args...)
 
 # catch-all for default ElType
-function TTN(g::AbstractGraph, args...; kwargs...)
-  return TTN(Float64, g, args...; kwargs...)
+function ttn(g::AbstractGraph, args...; kwargs...)
+  return ttn(Float64, g, args...; kwargs...)
 end
 
-function TTN(eltype::Type{<:Number}, graph::AbstractGraph, args...; kwargs...)
+function ttn(eltype::Type{<:Number}, graph::AbstractGraph, args...; kwargs...)
   itensor_network = ITensorNetwork(eltype, graph; kwargs...)
-  return TTN(itensor_network, args...)
+  return ttn(itensor_network, args...)
 end
 
 # construct from given state (map)
-function TTN(::Type{ElT}, is::AbstractIndsNetwork, initstate, args...) where {ElT<:Number}
+function ttn(::Type{ElT}, is::AbstractIndsNetwork, initstate, args...) where {ElT<:Number}
   itensor_network = ITensorNetwork(ElT, is, initstate)
-  return TTN(itensor_network, args...)
+  return ttn(itensor_network, args...)
 end
 
 # Constructor from a collection of ITensors.
 # TODO: Support other collections like `Dictionary`,
 # interface for custom vertex names.
-function TTN(ts::ITensorCollection)
-  return TTN(ITensorNetwork(ts))
+function ttn(ts::ITensorCollection)
+  return ttn(ITensorNetwork(ts))
 end
 
 # TODO: Implement `random_circuit_ttn` for non-trivial
 # bond dimensions and correlations.
 # TODO: Implement random_ttn for QN-Index
 function random_ttn(args...; kwargs...)
-  T = TTN(args...; kwargs...)
+  T = ttn(args...; kwargs...)
   randn!.(vertex_data(T))
   normalize!.(vertex_data(T))
   return T
@@ -91,14 +95,14 @@ function random_mps(
   else
     randomMPS(external_inds, states; linkdims=internal_inds_space)
   end
-  return TTN([tn_mps[v] for v in eachindex(tn_mps)])
+  return ttn([tn_mps[v] for v in eachindex(tn_mps)])
 end
 
 #
 # Construction from operator (map)
 #
 
-function TTN(
+function ttn(
   ::Type{ElT},
   sites_map::Pair{<:AbstractIndsNetwork,<:AbstractIndsNetwork},
   ops::Dictionary;
@@ -110,7 +114,7 @@ function TTN(
   for v in vertices(sites)
     os *= Op(ops[v], v)
   end
-  T = TTN(ElT, os, sites; kwargs...)
+  T = ttn(ElT, os, sites; kwargs...)
   # see https://github.com/ITensor/ITensors.jl/issues/526
   lognormT = lognorm(T)
   T /= exp(lognormT / N) # TODO: fix broadcasting for in-place assignment
@@ -119,26 +123,26 @@ function TTN(
   return T
 end
 
-function TTN(
+function ttn(
   ::Type{ElT},
   sites_map::Pair{<:AbstractIndsNetwork,<:AbstractIndsNetwork},
   fops::Function;
   kwargs...,
 ) where {ElT<:Number}
   sites = first(sites_map) # TODO: Use the sites_map
   ops = Dictionary(vertices(sites), map(v -> fops(v), vertices(sites)))
-  return TTN(ElT, sites, ops; kwargs...)
+  return ttn(ElT, sites, ops; kwargs...)
 end
 
-function TTN(
+function ttn(
   ::Type{ElT},
   sites_map::Pair{<:AbstractIndsNetwork,<:AbstractIndsNetwork},
   op::String;
   kwargs...,
 ) where {ElT<:Number}
   sites = first(sites_map) # TODO: Use the sites_map
   ops = Dictionary(vertices(sites), fill(op, nv(sites)))
-  return TTN(ElT, sites, ops; kwargs...)
+  return ttn(ElT, sites, ops; kwargs...)
 end
 
 # Special constructors
@@ -156,25 +160,8 @@ function mps(external_inds::Vector{<:Vector{<:Index}}; states)
   tn = insert_missing_internal_inds(
     tn, edges(g); internal_inds_space=trivial_space(indtype(external_inds))
   )
-  return TTN(tn)
-end
-
-## function mps(external_inds::Vector{<:Index}; states)
-##   is = path_indsnetwork(external_inds)
-##   tn = TTN(underlying_graph(is))
-##   tn = insert_missing_internal_inds(tn, trivial_space(indtype(is)))
-##   for v in vertices(tn)
-##     @show v
-##     @show tn[v]
-##     tn[v] *= state(only(is[v]), states(v))
-##     @show tn[v]
-##   end
-##   return tn
-## end
-
-## function productTTN(args...; kwargs...)
-##   return TTN(args...; link_space=1, kwargs...)
-## end
+  return ttn(tn)
+end
 
 # 
 # Utility

test/test_additensornetworks.jl

@@ -1,7 +1,7 @@
 @eval module $(gensym())
 using Graphs: rem_edge!, vertices
 using NamedGraphs: NamedEdge, hexagonal_lattice_graph, named_grid
-using ITensorNetworks: ITensorNetwork, inner_network, randomITensorNetwork, siteinds
+using ITensorNetworks: ITensorNetwork, inner_network, random_itensornetwork, siteinds
 using ITensors: ITensors, apply, op
 using Random: Random
 using Test: @test, @testset
@@ -32,8 +32,8 @@ using Test: @test, @testset
   rem_edge!(s2, NamedEdge((1, 1) => (1, 2)))
 
   v = rand(vertices(g))
-  ψ1 = randomITensorNetwork(s1; link_space=χ)
-  ψ2 = randomITensorNetwork(s2; link_space=χ)
+  ψ1 = random_itensornetwork(s1; link_space=χ)
+  ψ2 = random_itensornetwork(s2; link_space=χ)
 
   ψ12 = ψ1 + ψ2
 

test/test_apply.jl

@@ -9,7 +9,7 @@ using ITensorNetworks:
   contract_inner,
   environment,
   norm_network,
-  randomITensorNetwork,
+  random_itensornetwork,
   siteinds,
   update
 using ITensors: ITensors
@@ -25,7 +25,7 @@ using Test: @test, @testset
   g = named_grid(g_dims)
   s = siteinds("S=1/2", g)
   χ = 2
-  ψ = randomITensorNetwork(s; link_space=χ)
+  ψ = random_itensornetwork(s; link_space=χ)
   v1, v2 = (2, 2), (1, 2)
   ψψ = norm_network(ψ)