Remove ITensorMPS from tests

Author: mtfishman

test/test_binary_tree_partition.jl

@@ -4,7 +4,6 @@ using Graphs: add_vertex!, vertices
 # Trigger package extension.
 using GraphsFlows: GraphsFlows
 using ITensors: Index, ITensor, contract, noncommoninds, random_itensor
-using ITensorMPS: MPS
 using ITensorNetworks:
   _DensityMartrixAlgGraph,
   _contract_deltas_ignore_leaf_partitions,
@@ -27,38 +26,6 @@ using StableRNGs: StableRNG
 using TensorOperations: TensorOperations
 using Test: @test, @testset
 
-@testset "test mincut functions on top of MPS" begin
-  i = Index(2, "i")
-  j = Index(2, "j")
-  k = Index(2, "k")
-  l = Index(2, "l")
-  m = Index(2, "m")
-  n = Index(2, "n")
-  o = Index(2, "o")
-  p = Index(2, "p")
-
-  T = random_itensor(i, j, k, l, m, n, o, p)
-  M = MPS(T, (i, j, k, l, m, n, o, p); cutoff=1e-5, maxdim=500)
-  tn = ITensorNetwork(M[:])
-  for out in [binary_tree_structure(tn), path_graph_structure(tn)]
-    @test out isa DataGraph
-    @test is_binary_arborescence(out)
-    @test length(vertex_data(out).values) == 8
-  end
-  out = _mps_partition_inds_order(tn, [o, p, i, j, k, l, m, n])
-  @test out in [[i, j, k, l, m, n, o, p], [p, o, n, m, l, k, j, i]]
-  p1, p2 = _mincut_partitions(tn, [k, l], [m, n])
-  # When MPS bond dimensions are large, the partition will not across internal inds
-  @test (length(p1) == 0) || (length(p2) == 0)
-
-  M = MPS(T, (i, j, k, l, m, n, o, p); cutoff=1e-5, maxdim=2)
-  tn = ITensorNetwork(M[:])
-  p1, p2 = _mincut_partitions(tn, [k, l], [m, n])
-  # When MPS bond dimensions are small, the partition will across internal inds
-  @test sort(p1) == [1, 2, 3, 4]
-  @test sort(p2) == [5, 6, 7, 8]
-end
-
 @testset "test _binary_tree_partition_inds of a 2D network" begin
   N = (3, 3, 3)
   linkdim = 2
@@ -83,77 +50,4 @@ end
   network = mapreduce(v -> collect(eachtensor(par[v])), vcat, vertices(par))
   @test isapprox(contract(tn), contract(network))
 end
-
-@testset "test partition with mincut_recursive_bisection alg and approx_itensornetwork" begin
-  i = Index(2, "i")
-  j = Index(2, "j")
-  k = Index(2, "k")
-  l = Index(2, "l")
-  m = Index(2, "m")
-  for dtype in (Float64, Complex{Float64})
-    T = random_itensor(dtype, i, j, k, l, m)
-    M = MPS(T, (i, j, k, l, m); cutoff=1e-5, maxdim=5)
-    network = M[:]
-    out1 = contract(network...)
-    tn = ITensorNetwork(network)
-    inds_btree = binary_tree_structure(tn)
-    par = _partition(tn, inds_btree; alg="mincut_recursive_bisection")
-    par = _contract_deltas_ignore_leaf_partitions(par; root=root_vertex(inds_btree))
-    networks = map(v -> par[v], vertices(par))
-    network2 = reduce(union, networks)
-    out2 = contract(network2)
-    @test isapprox(out1, out2)
-    # test approx_itensornetwork (here we call `contract` to test the interface)
-    for structure in [path_graph_structure, binary_tree_structure]
-      for alg in ["density_matrix", "ttn_svd"]
-        approx_tn, lognorm = contract(
-          tn;
-          alg,
-          output_structure=structure,
-          contraction_sequence_kwargs=(; alg="sa_bipartite"),
-        )
-        network3 = collect(eachtensor(approx_tn))
-        out3 = contract(network3...) * exp(lognorm)
-        i1 = noncommoninds(network...)
-        i3 = noncommoninds(network3...)
-        @test (length(i1) == length(i3))
-        @test isapprox(out1, out3)
-      end
-    end
-  end
-end
-
-@testset "test caching in approx_itensornetwork" begin
-  i = Index(2, "i")
-  j = Index(2, "j")
-  k = Index(2, "k")
-  l = Index(2, "l")
-  m = Index(2, "m")
-  T = random_itensor(i, j, k, l, m)
-  M = MPS(T, (i, j, k, l, m); cutoff=1e-5, maxdim=5)
-  tn = ITensorNetwork(M[:])
-  out_tree = path_graph_structure(tn)
-  input_partition = _partition(tn, out_tree; alg="mincut_recursive_bisection")
-  underlying_tree = underlying_graph(input_partition)
-  # Change type of each partition[v] since they will be updated
-  # with potential data type chage.
-  p = DataGraph(NamedGraph())
-  for v in vertices(input_partition)
-    add_vertex!(p, v)
-    p[v] = ITensorNetwork{Any}(input_partition[v])
-  end
-  alg_graph = _DensityMartrixAlgGraph(p, underlying_tree, root_vertex(out_tree))
-  path = post_order_dfs_vertices(underlying_tree, root_vertex(out_tree))
-  for v in path[1:2]
-    _rem_vertex!(
-      alg_graph,
-      v;
-      cutoff=1e-15,
-      maxdim=10000,
-      contraction_sequence_kwargs=(; alg="optimal"),
-    )
-  end
-  # Check that a specific density matrix info has been cached
-  @test haskey(alg_graph.caches.es_to_pdm, Set([NamedEdge(nothing, path[3])]))
-end
 end

test/test_opsum_to_ttn.jl

@@ -13,7 +13,6 @@ using ITensors:
   dag,
   inds,
   removeqns
-using ITensorMPS: ITensorMPS
 using ITensors.NDTensors: matrix
 using ITensorGaussianMPS: ITensorGaussianMPS
 using ITensorNetworks: ITensorNetworks, OpSum, ttn, siteinds
@@ -61,26 +60,6 @@ end
     # root_vertex = (1, 2)
     # println(leaf_vertices(is))
 
-    @testset "Svd approach" for root_vertex in leaf_vertices(is)
-      # get TTN Hamiltonian directly
-      Hsvd = ttn(H, is; root_vertex, cutoff=1e-10)
-      # get corresponding MPO Hamiltonian
-      Hline = ITensorMPS.MPO(replace_vertices(v -> vmap[v], H), sites)
-      # compare resulting dense Hamiltonians
-      @disable_warn_order begin
-        Tttno = prod(Hline)
-        Tmpo = contract(Hsvd)
-      end
-      @test Tttno ≈ Tmpo rtol = 1e-6
-
-      Hsvd_lr = ttn(Hlr, is; root_vertex, cutoff=1e-10)
-      Hline_lr = ITensorMPS.MPO(replace_vertices(v -> vmap[v], Hlr), sites)
-      @disable_warn_order begin
-        Tttno_lr = prod(Hline_lr)
-        Tmpo_lr = contract(Hsvd_lr)
-      end
-      @test Tttno_lr ≈ Tmpo_lr rtol = 1e-6
-    end
     if auto_fermion_enabled
       ITensors.enable_auto_fermion()
     end
@@ -138,28 +117,6 @@ end
 
     # root_vertex = (1, 2)
     # println(leaf_vertices(is))
-
-    @testset "Svd approach" for root_vertex in leaf_vertices(is)
-      # get TTN Hamiltonian directly
-      Hsvd = ttn(H, is; root_vertex, cutoff=1e-10)
-      # get corresponding MPO Hamiltonian
-      Hline = ITensorMPS.MPO(replace_vertices(v -> vmap[v], H), sites)
-      # compare resulting sparse Hamiltonians
-
-      @disable_warn_order begin
-        Tmpo = prod(Hline)
-        Tttno = contract(Hsvd)
-      end
-      @test Tttno ≈ Tmpo rtol = 1e-6
-
-      Hsvd_lr = ttn(Hlr, is; root_vertex, cutoff=1e-10)
-      Hline_lr = ITensorMPS.MPO(replace_vertices(v -> vmap[v], Hlr), sites)
-      @disable_warn_order begin
-        Tttno_lr = prod(Hline_lr)
-        Tmpo_lr = contract(Hsvd_lr)
-      end
-      @test Tttno_lr ≈ Tmpo_lr rtol = 1e-6
-    end
   end
 
   @testset "OpSum to TTN Fermions" begin
@@ -182,37 +139,6 @@ end
     # add combination of longer range interactions
     Hlr = copy(H)
 
-    @testset "Svd approach" for root_vertex in leaf_vertices(is)
-      # get TTN Hamiltonian directly
-      Hsvd = ttn(H, is; root_vertex, cutoff=1e-10)
-      # get corresponding MPO Hamiltonian
-      sites = [only(is[v]) for v in reverse(post_order_dfs_vertices(c, root_vertex))]
-      vmap = Dictionary(reverse(post_order_dfs_vertices(c, root_vertex)), 1:length(sites))
-      Hline = ITensorMPS.MPO(replace_vertices(v -> vmap[v], H), sites)
-      # compare resulting sparse Hamiltonians
-      Hmat_sp = ITensorGaussianMPS.hopping_hamiltonian(replace_vertices(v -> vmap[v], H))
-      @disable_warn_order begin
-        Tmpo = prod(Hline)
-        Tttno = contract(Hsvd)
-      end
-
-      # verify that the norm isn't 0 and thus the same (which would indicate a problem with the autofermion system
-      @test norm(Tmpo) > 0
-      @test norm(Tttno) > 0
-      @test norm(Tmpo) ≈ norm(Tttno) rtol = 1e-6
-
-      # TODO: fix comparison for fermionic tensors
-      @test_broken Tmpo ≈ Tttno
-      # In the meantime: matricize tensors and convert to dense Matrix to compare element by element
-      dTmm = to_matrix(Tmpo)
-      dTtm = to_matrix(Tttno)
-      @test any(>(1e-14), dTmm - dTtm)
-
-      # also compare with energies obtained from single-particle Hamiltonian
-      GS_mb, _, _ = eigsolve(dTtm, 1, :SR, eltype(dTtm))
-      spectrum_sp = eigvals(Hmat_sp)
-      @test minimum(cumsum(spectrum_sp)) ≈ GS_mb[1] atol = 1e-8
-    end
     if !auto_fermion_enabled
       ITensors.disable_auto_fermion()
     end
@@ -252,28 +178,6 @@ end
     Hlr += -4, "Z", (1, 1), "Z", (2, 2)
     Hlr += 2.0, "Z", (2, 2), "Z", (3, 2)
     Hlr += -1.0, "Z", (1, 2), "Z", (3, 1)
-
-    @testset "Svd approach" for root_vertex in leaf_vertices(is)
-      # get TTN Hamiltonian directly
-      Hsvd = ttn(H, is_missing_site; root_vertex, cutoff=1e-10)
-      # get corresponding MPO Hamiltonian
-      Hline = ITensorMPS.MPO(replace_vertices(v -> vmap[v], H), sites)
-
-      # compare resulting sparse Hamiltonians
-      @disable_warn_order begin
-        Tmpo = prod(Hline)
-        Tttno = contract(Hsvd)
-      end
-      @test Tttno ≈ Tmpo rtol = 1e-6
-
-      Hsvd_lr = ttn(Hlr, is_missing_site; root_vertex, cutoff=1e-10)
-      Hline_lr = ITensorMPS.MPO(replace_vertices(v -> vmap[v], Hlr), sites)
-      @disable_warn_order begin
-        Tttno_lr = prod(Hline_lr)
-        Tmpo_lr = contract(Hsvd_lr)
-      end
-      @test Tttno_lr ≈ Tmpo_lr rtol = 1e-6
-    end
   end
 end
 end

test/test_tebd.jl

@@ -1,7 +1,6 @@
 @eval module $(gensym())
 using Graphs: vertices
 using ITensors: ITensors
-using ITensorMPS: ITensorMPS
 using ITensorNetworks: ITensorNetwork, cartesian_to_linear, dmrg, expect, siteinds, tebd
 using ITensorNetworks.ITensorsExtensions: group_terms
 using ITensorNetworks.ModelHamiltonians: ModelHamiltonians
@@ -20,18 +19,6 @@ ITensors.disable_warn_order()
 
   s = siteinds("S=1/2", g)
 
-  #
-  # DMRG comparison
-  #
-  g_dmrg = rename_vertices(v -> cartesian_to_linear(dims)[v], g)
-  ℋ_dmrg = ModelHamiltonians.ising(g_dmrg; h)
-  s_dmrg = [only(s[v]) for v in vertices(s)]
-  H_dmrg = ITensorMPS.MPO(ℋ_dmrg, s_dmrg)
-  ψ_dmrg_init = ITensorMPS.MPS(s_dmrg, j -> "↑")
-  E_dmrg, ψ_dmrg = dmrg(
-    H_dmrg, ψ_dmrg_init; nsweeps=20, maxdim=[fill(10, 10); 20], cutoff=1e-8, outputlevel=0
-  )
-
   #
   # PEPS TEBD optimization
   #
@@ -66,6 +53,5 @@ ITensors.disable_warn_order()
   #E2 = expect(ℋ, ψ)
   #@show E0, E1, E2, E_dmrg
   @test_broken (((abs((E2 - E1) / E2) < 1e-3) && (E1 < E0)) || (E2 < E1 < E0))
-  @test_broken E2 ≈ E_dmrg rtol = 1e-3
 end
 end

test/test_ttn_contract.jl

@@ -17,7 +17,6 @@ using ITensorNetworks:
   siteinds
 using ITensorNetworks.ModelHamiltonians: ModelHamiltonians
 using ITensors: prime, replaceinds, replaceprime
-using ITensorMPS: ITensorMPS
 using LinearAlgebra: norm, normalize
 using NamedGraphs.NamedGraphGenerators: named_comb_tree
 using StableRNGs: StableRNG
@@ -150,23 +149,4 @@ end
   Hpsi = contract(H, psi; alg="fit", nsites=1, nsweeps=10, init=Hpsi_guess)
   @test inner(psit, Hpsi) ≈ inner(psit, H, psi) rtol = 1e-2
 end
-
-@testset "Contract TTN with dangling inds" begin
-  nbit = 3
-  sites = siteinds("Qubit", nbit)
-
-  # random_mpo does not support linkdims keyword.
-  M1 = replaceprime(
-    ITensorMPS.random_mpo(sites) + ITensorMPS.random_mpo(sites), 1 => 2, 0 => 1
-  )
-  M2 = ITensorMPS.random_mpo(sites) + ITensorMPS.random_mpo(sites)
-  M12_ref = contract(M1, M2; alg="naive")
-  t12_ref = ttn([M12_ref[v] for v in eachindex(M12_ref)])
-
-  t1 = ttn([M1[v] for v in eachindex(M1)])
-  t2 = ttn([M2[v] for v in eachindex(M2)])
-
-  # Test with good initial guess
-  @test contract(t1, t2; alg="fit", init=t12_ref, nsweeps=1) ≈ t12_ref rtol = 1e-7
-end
 end

test/test_ttn_dmrg.jl

@@ -2,7 +2,6 @@
 using DataGraphs: edge_data, vertex_data
 using Dictionaries: Dictionary
 using Graphs: nv, vertices, uniform_tree
-using ITensorMPS: ITensorMPS
 using ITensorNetworks:
   ITensorNetworks,
   OpSum,
@@ -52,16 +51,10 @@ ITensors.disable_auto_fermion()
   nsweeps = 10
   maxdim = [10, 20, 40, 100]
 
-  # Compare to `ITensors.MPO` version of `dmrg`
-  H_mpo = ITensorMPS.MPO([H[v] for v in 1:nv(H)])
-  psi_mps = ITensorMPS.MPS([psi[v] for v in 1:nv(psi)])
-  e2, psi2 = dmrg(H_mpo, psi_mps; nsweeps, maxdim, outputlevel=0)
-
   e, psi = dmrg(
     H, psi; nsweeps, maxdim, cutoff, nsites, updater_kwargs=(; krylovdim=3, maxiter=1)
   )
   @test inner(psi', H, psi) ≈ e
-  @test inner(psi', H, psi) ≈ inner(psi2', H_mpo, psi2)
 
   # Alias for `ITensorNetworks.dmrg`
   e, psi = eigsolve(
@@ -235,17 +228,6 @@ end
       H, psi; nsweeps, maxdim, cutoff, nsites, updater_kwargs=(; krylovdim=3, maxiter=1)
     )
 
-    # Compare to `ITensors.MPO` version of `dmrg`
-    linear_order = [4, 1, 2, 5, 3, 6]
-    vmap = Dictionary(collect(vertices(s))[linear_order], 1:length(linear_order))
-    sline = only.(collect(vertex_data(s)))[linear_order]
-    Hline = ITensorMPS.MPO(replace_vertices(v -> vmap[v], os), sline)
-    rng = StableRNG(1234)
-    psiline = ITensorMPS.random_mps(rng, sline, i -> isodd(i) ? "Up" : "Dn"; linkdims=20)
-    e2, psi2 = dmrg(Hline, psiline; nsweeps, maxdim, cutoff, outputlevel=0)
-
-    @test inner(psi', H, psi) ≈ inner(psi2', Hline, psi2) atol = 1e-5
-
     if !auto_fermion_enabled
       ITensors.disable_auto_fermion()
     end
@@ -273,14 +255,6 @@ end
   vmap = Dictionary(collect(vertices(s))[linear_order], 1:length(linear_order))
   sline = only.(collect(vertex_data(s)))[linear_order]
 
-  # get MPS / MPO with JW string result
-  ITensors.disable_auto_fermion()
-  Hline = ITensorMPS.MPO(replace_vertices(v -> vmap[v], os), sline)
-  rng = StableRNG(1234)
-  psiline = ITensorMPS.random_mps(rng, sline, i -> isodd(i) ? "Up" : "Dn"; linkdims=20)
-  e_jw, psi_jw = dmrg(Hline, psiline; nsweeps, maxdim, cutoff, outputlevel=0)
-  ITensors.enable_auto_fermion()
-
   # now get auto-fermion results 
   H = ttn(os, s)
   # make init_state
@@ -294,16 +268,6 @@ end
     H, psi; nsweeps, maxdim, cutoff, nsites, updater_kwargs=(; krylovdim=3, maxiter=1)
   )
 
-  # Compare to `ITensors.MPO` version of `dmrg`
-  Hline = ITensorMPS.MPO(replace_vertices(v -> vmap[v], os), sline)
-  rng = StableRNG(1234)
-  psiline = ITensorMPS.random_mps(rng, sline, i -> isodd(i) ? "Up" : "Dn"; linkdims=20)
-  e2, psi2 = dmrg(Hline, psiline; nsweeps, maxdim, cutoff, outputlevel=0)
-
-  @test inner(psi', H, psi) ≈ inner(psi2', Hline, psi2) atol = 1e-5
-  @test e2 ≈ e_jw atol = 1e-5
-  @test inner(psi2', Hline, psi2) ≈ e_jw atol = 1e-5
-
   if !auto_fermion_enabled
     ITensors.disable_auto_fermion()
   end