From 6e19de05fc1eb717048344a2d46e1506ef6e5d76 Mon Sep 17 00:00:00 2001 From: Ryan Anselm <31040739+ryboselm@users.noreply.github.com> Date: Mon, 3 Jun 2024 21:37:30 -0400 Subject: [PATCH 01/31] Gridpoint improvement (#1) * Add support for rng and eltype in rand_itn * Bump ITN version * added error catching for gridpoints and function for random gridpoint sampling * change to overload Random.rand * Rename to prevent dimension overload * Rename calculate_fx(yz) to evaluate * Rename calculate_x(yz) to calculate_p * Rename delta_x(yz) to delta_p * created improved grid_points() * grid_points can take arbitrary ranges * Return dimension_indices * Changed instances of dimension in grid_points() and rand() to use d instead * updated grid_points() and rand() to incorporate feedback * grid_points() uses simpler method when span is default * changed to rand_p() and added enforced points * fix minor edge case * Formatting --------- Co-authored-by: Ryan Levy Co-authored-by: Joseph Tindall <51231103+JoeyT1994@users.noreply.github.com> --- Project.toml | 2 +- examples/2d_laplace_solver.jl | 4 +- examples/boundary_conditions.jl | 6 +- .../construct_multi_dimensional_function.jl | 8 +- examples/fredholm_solver.jl | 8 +- src/ITensorNumericalAnalysis.jl | 11 +- src/elementary_functions.jl | 69 +++--- src/elementary_operators.jl | 62 +++--- src/indexmap.jl | 173 +++++++++++---- src/indsnetworkmap.jl | 8 +- src/itensornetworkfunction.jl | 17 +- test/test_indexmaps.jl | 67 +++++- test/test_integration.jl | 4 +- test/test_itensorfunction.jl | 60 ++--- test/test_operators.jl | 205 +++++++++--------- 15 files changed, 422 insertions(+), 282 deletions(-) diff --git a/Project.toml b/Project.toml index f03a38e..afd7bf0 100644 --- a/Project.toml +++ b/Project.toml @@ -17,7 +17,7 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40" Dictionaries = "0.4.2" Glob = "1.3.1" Graphs = "1.8" -ITensorNetworks = "0.11.8" +ITensorNetworks = "0.11.10" ITensors = "0.5, 0.6" NamedGraphs = "0.6" Random = "1.8" diff --git a/examples/2d_laplace_solver.jl b/examples/2d_laplace_solver.jl index ed51cd6..e0250cc 100644 --- a/examples/2d_laplace_solver.jl +++ b/examples/2d_laplace_solver.jl @@ -48,7 +48,7 @@ x_vals, y_vals = grid_points(s, n_grid, 1), grid_points(s, n_grid, 2) vals = zeros((length(x_vals), length(y_vals))) for (i, x) in enumerate(x_vals) for (j, y) in enumerate(y_vals) - vals[i, j] = real(calculate_fxyz(ϕ_fxy, [x, y])) + vals[i, j] = real(evaluate(ϕ_fxy, [x, y])) end end @@ -60,7 +60,7 @@ x_vals = grid_points(s, n_grid, 1) y = 0.5 vals = zeros(length(x_vals)) for (i, x) in enumerate(x_vals) - vals[i] = real(calculate_fxyz(ϕ_fxy, [x, y])) + vals[i] = real(evaluate(ϕ_fxy, [x, y])) end println("Here is a cut of the function at y = $y") diff --git a/examples/boundary_conditions.jl b/examples/boundary_conditions.jl index 0a9e83a..5422b25 100644 --- a/examples/boundary_conditions.jl +++ b/examples/boundary_conditions.jl @@ -39,7 +39,7 @@ end vals = zeros((length(x_vals), length(y_vals))) for (i, x) in enumerate(x_vals) for (j, y) in enumerate(y_vals) - vals[i, j] = real(calculate_fxyz(ϕ_fxy, [x, y]; alg="exact")) + vals[i, j] = real(evaluate(ϕ_fxy, [x, y]; alg="exact")) end end @@ -49,7 +49,7 @@ display(heatmap(vals; xfact=1 / 32, yfact=1 / 32, xoffset=0, yoffset=0, colormap y = 0.5 vals2 = zeros(length(x_vals)) for (i, x) in enumerate(x_vals) - vals2[i] = real(calculate_fxyz(ϕ_fxy, [x, y]; alg="exact")) + vals2[i] = real(evaluate(ϕ_fxy, [x, y]; alg="exact")) end lp = lineplot(x_vals, vals2; name="cut y=$y") @@ -57,7 +57,7 @@ lp = lineplot(x_vals, vals2; name="cut y=$y") x = 0.5 vals3 = zeros(length(y_vals)) for (i, y) in enumerate(y_vals) - vals3[i] = real(calculate_fxyz(ϕ_fxy, [x, y]; alg="exact")) + vals3[i] = real(evaluate(ϕ_fxy, [x, y]; alg="exact")) end println("Here is a cut of the function at x = $x or y = $y") diff --git a/examples/construct_multi_dimensional_function.jl b/examples/construct_multi_dimensional_function.jl index 502ba95..1e36a7c 100644 --- a/examples/construct_multi_dimensional_function.jl +++ b/examples/construct_multi_dimensional_function.jl @@ -14,16 +14,16 @@ s = continuous_siteinds(g; map_dimension=3) println( "Constructing the 3D function f(x,y,z) = x³(y + y²) + cosh(πz) as a tensor network on a randomly chosen tree with $L vertices", ) -ψ_fx = poly_itn(s, [0.0, 0.0, 0.0, 1.0]; dimension=1) -ψ_fy = poly_itn(s, [0.0, 1.0, 1.0, 0.0]; dimension=2) -ψ_fz = cosh_itn(s; k=Number(pi), dimension=3) +ψ_fx = poly_itn(s, [0.0, 0.0, 0.0, 1.0]; dim=1) +ψ_fy = poly_itn(s, [0.0, 1.0, 1.0, 0.0]; dim=2) +ψ_fz = cosh_itn(s; k=Number(pi), dim=3) ψxyz = ψ_fx * ψ_fy + ψ_fz ψxyz = truncate(ψxyz; cutoff=1e-12) println("Maximum bond dimension of the network is $(maxlinkdim(ψxyz))") x, y, z = 0.125, 0.625, 0.5 -fxyz_xyz = calculate_fxyz(ψxyz, [x, y, z]) +fxyz_xyz = evaluate(ψxyz, [x, y, z]) println( "Tensor network evaluates the function as $fxyz_xyz at the co-ordinate: (x,y,z) = ($x, $y, $z)", ) diff --git a/examples/fredholm_solver.jl b/examples/fredholm_solver.jl index aa26623..8dd7293 100644 --- a/examples/fredholm_solver.jl +++ b/examples/fredholm_solver.jl @@ -47,13 +47,13 @@ println("solve f(x) = eˣ + ∫₀¹ (xy) f(y) dy") s = continuous_siteinds(g; map_dimension=2) ψ = const_itn(s) # f(x) = 1_x⊗1_y # make g(x,y) = x*y -g = poly_itn(s, [0, 1]; dimension=1) * poly_itn(s, [0, 1]; dimension=2) +g = poly_itn(s, [0, 1]; dim=1) * poly_itn(s, [0, 1]; dim=2) sU = union_all_inds(s.indsnetwork, s.indsnetwork') ∫_odd = ITensorNetwork(v -> v ∈ dimension_vertices(s, 1) ? Op("I") : Op("HalfInt"), sU) ∫_even = ITensorNetwork(v -> v ∈ dimension_vertices(s, 1) ? Op("HalfInt") : Op("I"), sU) -const_exp_odd = exp_itn(s; dimension=1) -const_exp_even = exp_itn(s; dimension=2) +const_exp_odd = exp_itn(s; dim=1) +const_exp_even = exp_itn(s; dim=2) niter = 20 for iter in 1:niter @@ -71,7 +71,7 @@ x_vals = grid_points(s, n_grid, 1) y = 0.5 # arbitrary cutvals = zeros(length(x_vals)) for (i, x) in enumerate(x_vals) - cutvals[i] = real(calculate_fxyz(ψ, [x, y]; alg="bp")) # alg="exact" if you encounter NaNs + cutvals[i] = real(evaluate(ψ, [x, y]; alg="bp")) # alg="exact" if you encounter NaNs end correct = (3 / 2 * x_vals) .+ exp.(x_vals) diff --git a/src/ITensorNumericalAnalysis.jl b/src/ITensorNumericalAnalysis.jl index 758caf9..35af0ec 100644 --- a/src/ITensorNumericalAnalysis.jl +++ b/src/ITensorNumericalAnalysis.jl @@ -14,12 +14,12 @@ export ITensorNetworkFunction, itensornetwork, dimension_vertices export IndexMap, default_dimension_map, dimension_inds, - calculate_xyz, - calculate_x, + calculate_p, calculate_ind_values, dimension, dimensions, - grid_points + grid_points, + rand_p export IndsNetworkMap, continuous_siteinds, indsnetwork, @@ -44,14 +44,13 @@ export const_itensornetwork, third_derivative_operator, fourth_derivative_operator, identity_operator, - delta_x, - delta_xyz, + delta_p, map_to_zero_operator, map_to_zeros, const_plane_op export const_itn, poly_itn, cosh_itn, sinh_itn, tanh_itn, exp_itn, sin_itn, cos_itn, rand_itn -export calculate_fx, calculate_fxyz +export evaluate export operate, operator_proj, multiply end diff --git a/src/elementary_functions.jl b/src/elementary_functions.jl index 4c89d86..3eb1c5a 100644 --- a/src/elementary_functions.jl +++ b/src/elementary_functions.jl @@ -4,6 +4,7 @@ using NamedGraphs.GraphsExtensions: random_bfs_tree, rem_edges, add_edges, leaf_vertices, undirected_graph using ITensors: dim, commoninds using ITensorNetworks: IndsNetwork, underlying_graph +using Random: AbstractRNG default_c_value() = 1.0 default_a_value() = 0.0 @@ -31,16 +32,16 @@ function exp_itensornetwork( k=default_k_value(), a=default_a_value(), c=default_c_value(), - dimension::Int=default_dimension(), + dim::Int=default_dimension(), ) ψ = const_itensornetwork(s) - Lx = length(dimension_vertices(ψ, dimension)) - for v in dimension_vertices(ψ, dimension) + Lx = length(dimension_vertices(ψ, dim)) + for v in dimension_vertices(ψ, dim) sind = only(inds(s, v)) ψ[v] = ITensor(exp(a / Lx) * exp.(k * index_values_to_scalars(s, sind)), inds(ψ[v])) end - ψ[first(dimension_vertices(ψ, dimension))] *= c + ψ[first(dimension_vertices(ψ, dim))] *= c return ψ end @@ -52,10 +53,10 @@ function cosh_itensornetwork( k=default_k_value(), a=default_a_value(), c=default_c_value(), - dimension::Int=default_dimension(), + dim::Int=default_dimension(), ) - ψ1 = exp_itensornetwork(s; a, k, c=0.5 * c, dimension) - ψ2 = exp_itensornetwork(s; a=-a, k=-k, c=0.5 * c, dimension) + ψ1 = exp_itensornetwork(s; a, k, c=0.5 * c, dim) + ψ2 = exp_itensornetwork(s; a=-a, k=-k, c=0.5 * c, dim) return ψ1 + ψ2 end @@ -67,10 +68,10 @@ function sinh_itensornetwork( k=default_k_value(), a=default_a_value(), c=default_c_value(), - dimension::Int=default_dimension(), + dim::Int=default_dimension(), ) - ψ1 = exp_itensornetwork(s; a, k, c=0.5 * c, dimension) - ψ2 = exp_itensornetwork(s; a=-a, k=-k, c=-0.5 * c, dimension) + ψ1 = exp_itensornetwork(s; a, k, c=0.5 * c, dim) + ψ2 = exp_itensornetwork(s; a=-a, k=-k, c=-0.5 * c, dim) return ψ1 + ψ2 end @@ -83,16 +84,16 @@ function tanh_itensornetwork( a=default_a_value(), c=default_c_value(), nterms::Int=default_nterms(), - dimension::Int=default_dimension(), + dim::Int=default_dimension(), ) ψ = const_itensornetwork(s) for n in 1:nterms - ψt = exp_itensornetwork(s; a=-2 * n * a, k=-2 * k * n, dimension) - ψt[first(dimension_vertices(ψ, dimension))] *= 2 * ((-1)^n) + ψt = exp_itensornetwork(s; a=-2 * n * a, k=-2 * k * n, dim) + ψt[first(dimension_vertices(ψ, dim))] *= 2 * ((-1)^n) ψ = ψ + ψt end - ψ[first(dimension_vertices(ψ, dimension))] *= c + ψ[first(dimension_vertices(ψ, dim))] *= c return ψ end @@ -104,10 +105,10 @@ function cos_itensornetwork( k=default_k_value(), a=default_a_value(), c=default_c_value(), - dimension::Int=default_dimension(), + dim::Int=default_dimension(), ) - ψ1 = exp_itensornetwork(s; a=a * im, k=k * im, c=0.5 * c, dimension) - ψ2 = exp_itensornetwork(s; a=-a * im, k=-k * im, c=0.5 * c, dimension) + ψ1 = exp_itensornetwork(s; a=a * im, k=k * im, c=0.5 * c, dim) + ψ2 = exp_itensornetwork(s; a=-a * im, k=-k * im, c=0.5 * c, dim) return ψ1 + ψ2 end @@ -119,10 +120,10 @@ function sin_itensornetwork( k=default_k_value(), a=default_a_value(), c=default_c_value(), - dimension::Int=default_dimension(), + dim::Int=default_dimension(), ) - ψ1 = exp_itensornetwork(s; a=a * im, k=k * im, c=-0.5 * im * c, dimension) - ψ2 = exp_itensornetwork(s; a=-a * im, k=-k * im, c=0.5 * im * c, dimension) + ψ1 = exp_itensornetwork(s; a=a * im, k=k * im, c=-0.5 * im * c, dim) + ψ2 = exp_itensornetwork(s; a=-a * im, k=-k * im, c=0.5 * im * c, dim) return ψ1 + ψ2 end @@ -132,7 +133,7 @@ by indsnetwork""" function polynomial_itensornetwork( s::IndsNetworkMap, coeffs::Vector; - dimension::Int=default_dimension(), + dim::Int=default_dimension(), k=default_k_value(), c=default_c_value(), ) @@ -146,7 +147,7 @@ function polynomial_itensornetwork( s_tree = IndsNetworkMap(s_tree, indexmap(s)) ψ = const_itensornetwork(s_tree; linkdim=n) - dim_vertices = dimension_vertices(ψ, dimension) + dim_vertices = dimension_vertices(ψ, dim) source_vertex = first(dim_vertices) for v in dim_vertices @@ -191,12 +192,22 @@ function polynomial_itensornetwork( return ψ end +function random_itensornetwork(rng::AbstractRNG, eltype::Type, s::IndsNetworkMap; kwargs...) + return ITensorNetworkFunction( + random_tensornetwork(rng, eltype, indsnetwork(s); kwargs...), s + ) +end + +function random_itensornetwork(rng::AbstractRNG, s::IndsNetworkMap; kwargs...) + return ITensorNetworkFunction(random_tensornetwork(rng, indsnetwork(s); kwargs...), s) +end + function random_itensornetwork(s::IndsNetworkMap; kwargs...) return ITensorNetworkFunction(random_tensornetwork(indsnetwork(s); kwargs...), s) end "Create a product state of a given bit configuration. Will make planes if all dims not specificed" -function delta_xyz( +function delta_p( s::IndsNetworkMap, xs::Vector{<:Number}, dims::Vector{Int}=[i for i in 1:length(xs)]; @@ -211,12 +222,12 @@ function delta_xyz( end "Create a product state of a given bit configuration of a 1D function" -function delta_x(s::IndsNetworkMap, x::Number, kwargs...) +function delta_p(s::IndsNetworkMap, x::Number, kwargs...) @assert dimension(s) == 1 - return delta_xyz(s, [x], [1]; kwargs...) + return delta_p(s, [x], [1]; kwargs...) end -function delta_xyz( +function delta_p( s::IndsNetworkMap, points::Vector{<:Vector}, points_dims::Vector{<:Vector}=[[i for i in 1:length(xs)] for xs in points]; @@ -225,7 +236,7 @@ function delta_xyz( @assert length(points) != 0 @assert length(points) == length(points_dims) ψ = reduce( - +, [delta_xyz(s, xs, dims; kwargs...) for (xs, dims) in zip(points, points_dims)] + +, [delta_p(s, xs, dims; kwargs...) for (xs, dims) in zip(points, points_dims)] ) return ψ end @@ -240,7 +251,7 @@ function delta_kernel( include_identity=true, truncate_kwargs..., ) - ψ = coeff * delta_xyz(s, points, points_dims; truncate_kwargs...) + ψ = coeff * delta_p(s, points, points_dims; truncate_kwargs...) if include_identity ψ = const_itn(s) + ψ @@ -286,7 +297,7 @@ function delta_kernel( end end if length(overlap_points) != 0 - ψ = ψ + -coeff * delta_xyz(s, overlap_points, overlap_dims; truncate_kwargs...) + ψ = ψ + -coeff * delta_p(s, overlap_points, overlap_dims; truncate_kwargs...) end end diff --git a/src/elementary_operators.jl b/src/elementary_operators.jl index 9b82cdc..6a48d88 100644 --- a/src/elementary_operators.jl +++ b/src/elementary_operators.jl @@ -22,28 +22,26 @@ default_boundary() = "Dirichlet" ## TODO: turn this into a proper system ala sites which can be externally overloaded -function boundary_term( - s::IndsNetworkMap, boundary::String, dimension, isfwd::Bool, n::Int=0 -) +function boundary_term(s::IndsNetworkMap, boundary::String, dim, isfwd::Bool, n::Int=0) ttn_op = OpSum() - dim_vertices = dimension_vertices(s, dimension) + dim_vertices = dimension_vertices(s, dim) L = length(dim_vertices) if boundary == "Neumann" string_site = [ if j <= (L - n) - (isfwd ? "Dup" : "Ddn", vertex(s, dimension, j)) + (isfwd ? "Dup" : "Ddn", vertex(s, dim, j)) else - ("I", vertex(s, dimension, j)) + ("I", vertex(s, dim, j)) end for j in 1:L ] add!(ttn_op, 1.0, (string_site...)...) elseif boundary == "Periodic" string_site = [ if j <= (L - n) - (isfwd ? "D-" : "D+", vertex(s, dimension, j)) + (isfwd ? "D-" : "D+", vertex(s, dim, j)) else - ("I", vertex(s, dimension, j)) + ("I", vertex(s, dim, j)) end for j in 1:L ] add!(ttn_op, 1.0, (string_site...)...) @@ -52,47 +50,47 @@ function boundary_term( end function forward_shift_opsum( - s::IndsNetworkMap; dimension=default_dimension(), boundary=default_boundary(), n::Int=0 + s::IndsNetworkMap; dim=default_dimension(), boundary=default_boundary(), n::Int=0 ) @assert is_tree(s) @assert base(s) == 2 ttn_op = OpSum() - dim_vertices = dimension_vertices(s, dimension) + dim_vertices = dimension_vertices(s, dim) L = length(dim_vertices) - string_site = [("D+", vertex(s, dimension, L - n))] - add!(ttn_op, 1.0, "D+", vertex(s, dimension, L - n)) + string_site = [("D+", vertex(s, dim, L - n))] + add!(ttn_op, 1.0, "D+", vertex(s, dim, L - n)) for i in (L - n):-1:2 pop!(string_site) - push!(string_site, ("D-", vertex(s, dimension, i))) - push!(string_site, ("D+", vertex(s, dimension, i - 1))) + push!(string_site, ("D-", vertex(s, dim, i))) + push!(string_site, ("D+", vertex(s, dim, i - 1))) add!(ttn_op, 1.0, (string_site...)...) end - ttn_op += boundary_term(s, boundary, dimension, true, n) + ttn_op += boundary_term(s, boundary, dim, true, n) return ttn_op end function backward_shift_opsum( - s::IndsNetworkMap; dimension=default_dimension(), boundary=default_boundary(), n::Int=0 + s::IndsNetworkMap; dim=default_dimension(), boundary=default_boundary(), n::Int=0 ) @assert is_tree(s) @assert base(s) == 2 ttn_op = OpSum() - dim_vertices = dimension_vertices(s, dimension) + dim_vertices = dimension_vertices(s, dim) L = length(dim_vertices) - string_site = [("D-", vertex(s, dimension, L - n))] - add!(ttn_op, 1.0, "D-", vertex(s, dimension, L - n)) + string_site = [("D-", vertex(s, dim, L - n))] + add!(ttn_op, 1.0, "D-", vertex(s, dim, L - n)) for i in (L - n):-1:2 pop!(string_site) - push!(string_site, ("D+", vertex(s, dimension, i))) - push!(string_site, ("D-", vertex(s, dimension, i - 1))) + push!(string_site, ("D+", vertex(s, dim, i))) + push!(string_site, ("D-", vertex(s, dim, i - 1))) add!(ttn_op, 1.0, (string_site...)...) end - ttn_op += boundary_term(s, boundary, dimension, false, n) + ttn_op += boundary_term(s, boundary, dim, false, n) return ttn_op end @@ -118,7 +116,7 @@ function stencil( s::IndsNetworkMap, shifts::Vector, delta_power::Int; - dimension=default_dimension(), + dim=default_dimension(), left_boundary=default_boundary(), right_boundary=default_boundary(), scale=true, @@ -132,23 +130,21 @@ function stencil( for i in [1, 2] n = i == 1 ? 1 : 0 if !iszero(shifts[i]) - stencil_opsum += - shifts[i] * forward_shift_opsum(s; dimension, boundary=right_boundary, n) + stencil_opsum += shifts[i] * forward_shift_opsum(s; dim, boundary=right_boundary, n) end end for i in [4, 5] n = i == 5 ? 1 : 0 if !iszero(shifts[i]) - stencil_opsum += - shifts[i] * backward_shift_opsum(s; dimension, boundary=left_boundary, n) + stencil_opsum += shifts[i] * backward_shift_opsum(s; dim, boundary=left_boundary, n) end end stencil_op = ttn(stencil_opsum, indsnetwork(s); kwargs...) if scale - for v in dimension_vertices(s, dimension) + for v in dimension_vertices(s, dim) stencil_op[v] = (b^delta_power) * stencil_op[v] end end @@ -172,14 +168,12 @@ function fourth_derivative_operator(s::IndsNetworkMap; kwargs...) return stencil(s, [1.0, -4.0, 6.0, -4.0, 1.0], 4; kwargs...) end -function laplacian_operator( - s::IndsNetworkMap; dimensions=[i for i in 1:dimension(s)], kwargs... -) - remaining_dims = copy(dimensions) - ∇ = second_derivative_operator(s; dimension=first(remaining_dims), kwargs...) +function laplacian_operator(s::IndsNetworkMap; dims=[i for i in 1:dimension(s)], kwargs...) + remaining_dims = copy(dims) + ∇ = second_derivative_operator(s; dim=first(remaining_dims), kwargs...) popfirst!(remaining_dims) for rd in remaining_dims - ∇ += second_derivative_operator(s; dimension=rd, kwargs...) + ∇ += second_derivative_operator(s; dim=rd, kwargs...) end return ∇ end diff --git a/src/indexmap.jl b/src/indexmap.jl index 9a96c2b..cb6c284 100644 --- a/src/indexmap.jl +++ b/src/indexmap.jl @@ -2,6 +2,7 @@ using Base: Base using Dictionaries: Dictionary, set! using ITensors: ITensors, Index, dim using ITensorNetworks: IndsNetwork, vertex_data +using Random: rand struct IndexMap{VB,VD} index_digit::VB @@ -39,10 +40,10 @@ end function IndexMap(dimension_indices::Vector{Vector{V}}) where {V<:Index} index_digit = Dictionary() index_dimension = Dictionary() - for (dimension, indices) in enumerate(dimension_indices) + for (d, indices) in enumerate(dimension_indices) for (bit, ind) in enumerate(indices) set!(index_digit, ind, bit) - set!(index_dimension, ind, dimension) + set!(index_dimension, ind, d) end end return IndexMap(index_digit, index_dimension) @@ -68,28 +69,27 @@ function ITensors.inds(imap::IndexMap) @assert keys(index_dimension(imap)) == keys(index_digit(imap)) return collect(keys(index_dimension(imap))) end -function dimension_inds(imap::IndexMap, dimension::Int) - return collect( - filter(i -> index_dimension(imap)[i] == dimension, keys(index_dimension(imap))) - ) +function dimension_inds(imap::IndexMap, dim::Int) + return collect(filter(i -> index_dimension(imap)[i] == dim, keys(index_dimension(imap)))) +end +function dimension_indices(imap::IndexMap, dim::Int) + return filter(ind -> dimension(imap, ind) == dim, inds(imap)) end -function ind(imap::IndexMap, dimension::Int, digit::Int) +function ind(imap::IndexMap, dim::Int, digit::Int) return only( filter( - i -> index_dimension(imap)[i] == dimension && index_digit(imap)[i] == digit, + i -> index_dimension(imap)[i] == dim && index_digit(imap)[i] == digit, keys(index_dimension(imap)), ), ) end -function dimension_indices(imap::IndexMap, dimap::Int) - return filter(ind -> dimension(imap, ind) == dim, inds(imap)) -end - -function calculate_xyz(imap::IndexMap, ind_to_ind_value_map, dimensions::Vector{Int}) +function calculate_p( + imap::IndexMap, ind_to_ind_value_map, dims::Vector{Int}=[i for i in 1:dimension(imap)] +) out = Number[] - for dimension in dimensions - indices = dimension_inds(imap, dimension) + for d in dims + indices = dimension_inds(imap, d) push!( out, sum([index_value_to_scalar(imap, ind, ind_to_ind_value_map[ind]) for ind in indices]), @@ -98,25 +98,17 @@ function calculate_xyz(imap::IndexMap, ind_to_ind_value_map, dimensions::Vector{ return out end -function calculate_xyz(imap::IndexMap, ind_to_ind_value_map) - return calculate_xyz(imap, ind_to_ind_value_map, [i for i in 1:dimension(imap)]) -end -function calculate_x(imap::IndexMap, ind_to_ind_value_map, dimension::Int) - return only(calculate_xyz(imap, ind_to_ind_value_map, [dimension])) -end -function calculate_x(imap::IndexMap, ind_to_ind_value_map) - return calculate_x(imap, ind_to_ind_value_map, 1) +function calculate_p(imap::IndexMap, ind_to_ind_value_map, dim::Int) + return calculate_p(imap, ind_to_ind_value_map, [dim]) end -function calculate_ind_values( - imap::IndexMap, xs::Vector, dimensions::Vector{Int}; print_x=false -) - @assert length(xs) == length(dimensions) +function calculate_ind_values(imap::IndexMap, xs::Vector, dims::Vector{Int}; print_x=false) + @assert length(xs) == length(dims) ind_to_ind_value_map = Dictionary() for (i, x) in enumerate(xs) - dimension = dimensions[i] + d = dims[i] x_rn = x - indices = dimension_inds(imap, dimension) + indices = dimension_inds(imap, d) sorted_inds = sort(indices; by=indices -> digit(imap, indices)) for ind in sorted_inds ind_val = dim(ind) - 1 @@ -133,7 +125,7 @@ function calculate_ind_values( end if print_x - x_bitstring = calculate_x(imap, ind_to_ind_value_map, dimension) + x_bitstring = only(calculate_p(imap, ind_to_ind_value_map, d)) println( "Dimension $dimension. Actual value of x is $x but bitstring rep. is $x_bitstring" ) @@ -142,8 +134,8 @@ function calculate_ind_values( return ind_to_ind_value_map end -function calculate_ind_values(imap::IndexMap, x::Number, dimension::Int; kwargs...) - return calculate_ind_values(imap, [x], [dimension]; kwargs...) +function calculate_ind_values(imap::IndexMap, x::Number, dim::Int; kwargs...) + return calculate_ind_values(imap, [x], [dim]; kwargs...) end function calculate_ind_values(imap::IndexMap, xs::Vector; kwargs...) return calculate_ind_values(imap, xs, [i for i in 1:length(xs)]; kwargs...) @@ -152,21 +144,114 @@ function calculate_ind_values(imap::IndexMap, x::Number; kwargs...) return calculate_ind_values(imap, [x], [1]; kwargs...) end -function grid_points(imap::IndexMap, N::Int, dimension::Int) - dims = dim.(dimension_inds(imap, dimension)) +""" + grid_points(imap, N, d, range; exact_grid=true) + + Gives `N` grid points from a given dimension of `imap` within a specified range. + + # Arguments + - `imap::IndexMap`: An IndexMap specifying the structure of the TN being used + - `N::Int`: The number of grid points requested. + - `d::Int` The index of the dimension of `imap` requested + - `span::AbstractVector{<:Number}`: A two element number vector [a,b] with 0≤a= span[2] || span[1] < 0 || span[2] > 1 + throw( + "expected a two-element vector [a,b] with 0≤a y == first(dims), dims) base = first(dims) - L = length(dimension_inds(imap, dimension)) - a = round(base^L / N) - grid_points = [i * (a / base^L) for i in 0:(N + 1)] - return filter(x -> x <= 1, grid_points) + L = length(dimension_inds(imap, d)) + + if !exact_grid + grid_points = range(span[1], span[2] - (span[2] - span[1]) / N; length=N) + else #exact_grid = true + if span[1] == 0 && span[2] == 1 + inv_step = min(Int(floor(log(base, N))), L) + if !(log(base, N) ≈ inv_step) + @warn "rounding $N down to $(Int(base^inv_step)) exact gridpoints!" + end + # now 1/inv_step should provide the step + grid_points = collect(span[1]:(1 / base^inv_step):span[2])[1:(end - 1)] + + else + + #get a count of the number of gridpoints within the span + points_in_span = floor(span[end] * base^L) - ceil(span[1] * base^L) + 1 + #TODO: figure out a way to calculate this without exponentiating to the power of L + + #exclude the endpoint in the count + if floor(span[end] * base^L) == span[end] * base^L + points_in_span = points_in_span - 1 + end + + if points_in_span <= 0 + @warn "No exact gridpoints found in this span!" + grid_points = [] + else + oldN = N + stepsize = ceil(points_in_span / N) + N = Int(floor(points_in_span / stepsize)) + 1 + startval = ceil(span[1] * base^L) / base^L #startval is the smallest grid point ≥ span[1] + + if startval + (N - 1) * stepsize / base^L >= span[2] + N = N - 1 + end + + if N < oldN + @warn "rounding $oldN down to $N exact gridpoints to maintain equal spacing." + end + + grid_points = [startval + i * (stepsize / base^L) for i in 0:(N - 1)] + end + end + end + + #add enforced points in naively + for point in enforced + if point >= span[2] || point < span[1] + @warn "enforced point $point outside of span $span, not including it" + continue + end + nearest_idx = searchsortedfirst(grid_points, point) + if nearest_idx > length(grid_points) || grid_points[nearest_idx] != point + insert!(grid_points, nearest_idx, point) + end + end + + return grid_points +end + +function grid_points( + imap::IndexMap, d::Int, span::AbstractVector{<:Number}=[0, 1]; kwargs... +) + dims = dim.(dimension_inds(imap, d)) + @assert all(y -> y == first(dims), dims) + base = dims[d] + L = length(dimension_inds(imap, d)) + return grid_points(imap, base^L, d, span; kwargs...) end -" Obtain all grid points of a given dimension" -function grid_points(imap::IndexMap, dimension::Int) - dims = dim.(dimension_inds(imap, dimension)) +""" + Picks a random grid point from `imap` given a dimension +""" +function rand_p(imap::IndexMap, d::Integer) + dims = dim.(dimension_inds(imap, d)) @assert all(y -> y == first(dims), dims) - base = dims[dimension] - L = length(dimension_inds(imap, dimension)) - return grid_points(imap, base^L, dimension) + base = dims[d] + L = length(dimension_inds(imap, d)) + return rand(0:(base^L - 1)) / base^L +end + +function rand_p(imap::IndexMap) + return [rand_p(imap, i) for i in 1:dimension(imap)] end diff --git a/src/indsnetworkmap.jl b/src/indsnetworkmap.jl index ecb8e26..c69deed 100644 --- a/src/indsnetworkmap.jl +++ b/src/indsnetworkmap.jl @@ -58,9 +58,9 @@ for f in [ :digit, :digits, :calculate_ind_values, - :calculate_x, - :calculate_xyz, + :calculate_p, :grid_points, + :rand_p, :index_value_to_scalar, :index_values_to_scalars, ] @@ -102,7 +102,7 @@ function dimension_vertices(inm::IndsNetworkMap, dims::Vector{Int}) return filter(v -> vertex_dimension(inm, v) in dims, vertices(inm)) end -function vertex(inm::IndsNetworkMap, dimension::Int, digit::Int) - index = ind(inm, dimension, digit) +function vertex(inm::IndsNetworkMap, dim::Int, digit::Int) + index = ind(inm, dim, digit) return only(filter(v -> index ∈ inm[v], vertices(inm))) end diff --git a/src/itensornetworkfunction.jl b/src/itensornetworkfunction.jl index 69d566d..397ec73 100644 --- a/src/itensornetworkfunction.jl +++ b/src/itensornetworkfunction.jl @@ -50,8 +50,7 @@ for f in [ :digit, :digits, :calculate_ind_values, - :calculate_x, - :calculate_xyz, + :calculate_p, :grid_points, :vertices_dimensions, :vertices_digits, @@ -80,25 +79,21 @@ function project(fitn::ITensorNetworkFunction, ind_to_ind_value_map) return fitn end -function calculate_fxyz( +function evaluate( fitn::ITensorNetworkFunction, xs::Vector, - dimensions::Vector{Int}; + dims::Vector{<:Int}=[i for i in 1:length(xs)]; alg=default_contraction_alg(), kwargs..., ) - ind_to_ind_value_map = calculate_ind_values(fitn, xs, dimensions) + ind_to_ind_value_map = calculate_ind_values(fitn, xs, dims) fitn_xyz = project(fitn, ind_to_ind_value_map) return scalar(itensornetwork(fitn_xyz); alg, kwargs...) end -function calculate_fxyz(fitn::ITensorNetworkFunction, xs::Vector; kwargs...) - return calculate_fxyz(fitn, xs, [i for i in 1:length(xs)]; kwargs...) -end - -function calculate_fx(fitn::ITensorNetworkFunction, x::Number; kwargs...) +function evaluate(fitn::ITensorNetworkFunction, x::Number; kwargs...) @assert dimension(fitn) == 1 - return calculate_fxyz(fitn, [x], [1]; kwargs...) + return evaluate(fitn, [x], [1]; kwargs...) end function ITensorNetworks.truncate(fitn::ITensorNetworkFunction; kwargs...) diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 779b5df..8f62e93 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -2,7 +2,7 @@ using Test using ITensorNumericalAnalysis using NamedGraphs: vertices -using NamedGraphs.NamedGraphGenerators: named_grid +using NamedGraphs.NamedGraphGenerators: named_grid, named_comb_tree using ITensors: siteinds, inds using Dictionaries: Dictionary @@ -19,7 +19,7 @@ using Dictionaries: Dictionary x = 0.625 ind_to_ind_value_map = calculate_ind_values(s, x) @test Set(keys(ind_to_ind_value_map)) == Set(inds(s)) - @test calculate_x(s, ind_to_ind_value_map) == x + @test only(calculate_p(s, ind_to_ind_value_map)) == x end @testset "test multi dimensional index map" begin @@ -29,14 +29,73 @@ using Dictionaries: Dictionary x, y = 0.5, 0.75 ind_to_ind_value_map = calculate_ind_values(s, [x, y], [1, 2]) - xyz = calculate_xyz(s, ind_to_ind_value_map, [1, 2]) + xyz = calculate_p(s, ind_to_ind_value_map, [1, 2]) @test first(xyz) == x @test last(xyz) == y xyzvals = [rand() for i in 1:L] ind_to_ind_value_map = calculate_ind_values(s, xyzvals) - xyzvals_approx = calculate_xyz(s, ind_to_ind_value_map) + xyzvals_approx = calculate_p(s, ind_to_ind_value_map, [i for i in 1:dimension(s)]) xyzvals ≈ xyzvals_approx end + + @testset "test grid_points" begin + L = 16 + base = 2 + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + + #first set -- irregular span + N = 125 + a = 0.12 + b = 0.95 + test_gridpoints = grid_points(s, N, 1, [a, b]) + + points_in_span = floor(b * base^(L / 2)) - ceil(a * base^(L / 2)) + 1 + N_gridpoints = Int(floor(points_in_span / ceil(points_in_span / N))) + 1 + + @test length(test_gridpoints) == N_gridpoints + @test test_gridpoints[1] >= a + @test test_gridpoints[end] < b + internal = (test_gridpoints[2] - test_gridpoints[1]) + left = (test_gridpoints[1] - a) + right = (b - test_gridpoints[end]) + @test internal >= left && internal >= right + + #second set + N = 32 + a = 0.25 + b = 0.5 + test2 = grid_points(s, N, 1, [a, b]) + @test length(test2) == N + @test test2[1] >= a + @test test2[end] < b + internal = (test2[2] - test2[1]) + left = (test2[1] - a) + right = (b - test2[end]) + @test internal >= left && internal >= right + + #third set + test3 = grid_points(s, 1) + @test length(test3) == 256 + @test test3[1] >= 0 + @test test3[end] < 1 + internal = (test3[2] - test3[1]) + left = (test3[1] - a) + right = (b - test3[end]) + @test internal >= left && internal >= right + + #test the rand() function to see if it succeeds + rand_gridpoint1 = rand_p(s) + rand_gridpoint2 = rand_p(s, 1) + + #fourth set -- very large L + L = 140 + base = 2 + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + n_grid = 16 + @test length(grid_points(s, n_grid, 1)) == n_grid + end end diff --git a/test/test_integration.jl b/test/test_integration.jl index 1f6491f..e142a4d 100644 --- a/test/test_integration.jl +++ b/test/test_integration.jl @@ -17,7 +17,7 @@ seed!(42) g = named_comb_tree((2, L ÷ 2)) s = continuous_siteinds(g; map_dimension=1) - ψ_fx = exp_itn(s; dimension=1) + ψ_fx = exp_itn(s; dim=1) O = operator_proj(ψ_fx) correct = 1 / 2 * (-1 + exp(1)^2) ans = ITensorNumericalAnalysis.integrate(O, ψ_fx) @@ -29,7 +29,7 @@ seed!(42) L = 30 g = named_comb_tree((3, L ÷ 3)) s = continuous_siteinds(g; map_dimension=2) - ψ_fxy = exp_itn(s; dimension=1) * exp_itn(s; dimension=2) + ψ_fxy = exp_itn(s; dim=1) * exp_itn(s; dim=2) ans = ITensorNumericalAnalysis.integrate(ψ_fxy) correct = (exp(1) - 1)^2 diff --git a/test/test_itensorfunction.jl b/test/test_itensorfunction.jl index 71f4934..2cb07c8 100644 --- a/test/test_itensorfunction.jl +++ b/test/test_itensorfunction.jl @@ -44,14 +44,14 @@ Random.seed!(1234) ψ_fx = const_itn(s; c) x = 0.5 - fx_x = calculate_fx(ψ_fx, x; alg="exact") + fx_x = evaluate(ψ_fx, x; alg="exact") @test fx_x ≈ c # link dims section ψ_fx = const_itn(s; c, linkdim=4) x = 0.5 - fx_x = calculate_fx(ψ_fx, x; alg="exact") + fx_x = evaluate(ψ_fx, x; alg="exact") @test fx_x ≈ c end funcs = [ @@ -73,7 +73,7 @@ Random.seed!(1234) x = 0.625 ψ_fx = net_func(s; k, a, c) - fx_x = calculate_fx(ψ_fx, x) + fx_x = evaluate(ψ_fx, x) @test c * func(k * x + a) ≈ fx_x end end @@ -97,7 +97,7 @@ Random.seed!(1234) x = (5.0 / 9.0) ψ_fx = net_func(s; k, a, c) - fx_x = calculate_fx(ψ_fx, x) + fx_x = evaluate(ψ_fx, x) @test c * func(k * x + a) ≈ fx_x end end @@ -114,7 +114,7 @@ Random.seed!(1234) x = 0.625 ψ_fx = tanh_itn(s; k, a, c, nterms) - fx_x = calculate_fx(ψ_fx, x) + fx_x = evaluate(ψ_fx, x) @test c * tanh(k * x + a) ≈ fx_x end @@ -135,7 +135,7 @@ Random.seed!(1234) x = 0.875 ψ_fx = poly_itn(s, coeffs; k, c) - fx_x = calculate_fx(ψ_fx, x) + fx_x = evaluate(ψ_fx, x) fx_exact = c * sum([coeffs[i] * ((k * x)^(i - 1)) for i in 1:(deg + 1)]) @test fx_x ≈ fx_exact atol = 1e-4 @@ -155,7 +155,7 @@ Random.seed!(1234) x, y, z = 0.5, 0.25, 0.0 - fx_xyz = calculate_fxyz(ψ_fxyz, [x, y, z], [1, 2, 3]) + fx_xyz = evaluate(ψ_fxyz, [x, y, z], [1, 2, 3]) @test fx_xyz ≈ c end @@ -178,11 +178,11 @@ Random.seed!(1234) k = rand() c = rand() - ψ_fx = net_func(s; k, a, c, dimension=1) - ψ_fy = net_func(s; k, a, c, dimension=2) + ψ_fx = net_func(s; k, a, c, dim=1) + ψ_fy = net_func(s; k, a, c, dim=2) ψ_fxy = ψ_fx + ψ_fy - fxy_xy = calculate_fxyz(ψ_fxy, [x, y], [1, 2]) + fxy_xy = evaluate(ψ_fxy, [x, y], [1, 2]) @test c * func(k * x + a) + c * func(k * y + a) ≈ fxy_xy end end @@ -198,15 +198,15 @@ Random.seed!(1234) s = continuous_siteinds(g; map_dimension=2) x, y = 0.625, 0.875 - ψ_fx = tanh_itn(s; k, a, c, nterms, dimension=1) - ψ_fy = tanh_itn(s; k, a, c, nterms, dimension=2) + ψ_fx = tanh_itn(s; k, a, c, nterms, dim=1) + ψ_fy = tanh_itn(s; k, a, c, nterms, dim=2) ψ_fxy = ψ_fx + ψ_fy - fxy_xy = calculate_fxyz(ψ_fxy, [x, y], [1, 2]; alg="exact") + fxy_xy = evaluate(ψ_fxy, [x, y], [1, 2]; alg="exact") @test c * tanh(k * x + a) + c * tanh(k * y + a) ≈ fxy_xy end end - @testset "test delta_xyz" begin + @testset "test delta_p" begin L = 10 g = named_grid((L, 1)) s = continuous_siteinds(g; map_dimension=2) @@ -215,45 +215,45 @@ Random.seed!(1234) lastDigit = 1 - delta xs = [0.0, delta, 0.25, 0.5, 0.625, 0.875, lastDigit] @testset "test single point" begin - ψ = delta_xyz(s, [x0, y0]) - @test calculate_fxyz(ψ, [x0, y0], [1, 2]) ≈ 1 + ψ = delta_p(s, [x0, y0]) + @test evaluate(ψ, [x0, y0], [1, 2]) ≈ 1 # test another point - @test calculate_fxyz(ψ, [y0, x0], [1, 2]) ≈ 0 + @test evaluate(ψ, [y0, x0], [1, 2]) ≈ 0 end @testset "test plane" begin - ψ = delta_xyz(s, [y0], [2]) + ψ = delta_p(s, [y0], [2]) # should be 1 in the plane for x in xs - @test calculate_fxyz(ψ, [x, y0], [1, 2]) ≈ 1 + @test evaluate(ψ, [x, y0], [1, 2]) ≈ 1 end # test random points for x in xs - @test calculate_fxyz(ψ, [x, 0.5], [1, 2]) ≈ 0 + @test evaluate(ψ, [x, 0.5], [1, 2]) ≈ 0 end end @testset "test sums of points" begin points = [[x0, y0], [y0, x0]] - ψ = delta_xyz(s, points) - @test calculate_fxyz(ψ, [x0, y0], [1, 2]) ≈ 1 - @test calculate_fxyz(ψ, [y0, x0], [1, 2]) ≈ 1 + ψ = delta_p(s, points) + @test evaluate(ψ, [x0, y0], [1, 2]) ≈ 1 + @test evaluate(ψ, [y0, x0], [1, 2]) ≈ 1 # test other points - @test calculate_fxyz(ψ, [0, 0], [1, 2]) ≈ 0 - @test calculate_fxyz(ψ, [0, y0], [1, 2]) ≈ 0 + @test evaluate(ψ, [0, 0], [1, 2]) ≈ 0 + @test evaluate(ψ, [0, y0], [1, 2]) ≈ 0 end @testset "test sums of points and plane" begin p0 = 0.5 points = [[x0, y0], [p0]] dims = [[1, 2], [2]] - ψ = delta_xyz(s, points, dims) - @test calculate_fxyz(ψ, [x0, y0], [1, 2]) ≈ 1 + ψ = delta_p(s, points, dims) + @test evaluate(ψ, [x0, y0], [1, 2]) ≈ 1 for x in xs - @test calculate_fxyz(ψ, [x, p0], [1, 2]) ≈ 1 + @test evaluate(ψ, [x, p0], [1, 2]) ≈ 1 end ## test other points - @test calculate_fxyz(ψ, [0, 0], [1, 2]) ≈ 0 - @test calculate_fxyz(ψ, [0, y0], [1, 2]) ≈ 0 + @test evaluate(ψ, [0, 0], [1, 2]) ≈ 0 + @test evaluate(ψ, [0, y0], [1, 2]) ≈ 0 end end end diff --git a/test/test_operators.jl b/test/test_operators.jl index 9511b65..09605a6 100644 --- a/test/test_operators.jl +++ b/test/test_operators.jl @@ -33,13 +33,13 @@ using Dictionaries: Dictionary xs = [0.0, 0.25, 0.625, 0.875, 1.0 - delta] for x in xs - @test 1.0 + calculate_fx(ψ_fx, x; alg="exact") ≈ 1.0 + sin(2.0 * pi * x) rtol = 1e-3 - @test 1.0 + calculate_fx(ψ_f1x, x) ≈ 1.0 + 2.0 * pi * cos(2.0 * pi * x) rtol = 1e-3 - @test 1.0 + calculate_fx(ψ_f2x, x) ≈ 1.0 + -1.0 * (2.0 * pi)^2 * sin(2.0 * pi * x) rtol = + @test 1.0 + evaluate(ψ_fx, x; alg="exact") ≈ 1.0 + sin(2.0 * pi * x) rtol = 1e-3 + @test 1.0 + evaluate(ψ_f1x, x) ≈ 1.0 + 2.0 * pi * cos(2.0 * pi * x) rtol = 1e-3 + @test 1.0 + evaluate(ψ_f2x, x) ≈ 1.0 + -1.0 * (2.0 * pi)^2 * sin(2.0 * pi * x) rtol = 1e-3 - @test 1.0 + calculate_fx(ψ_f3x, x) ≈ 1.0 + -1.0 * (2.0 * pi)^3 * cos(2.0 * pi * x) rtol = + @test 1.0 + evaluate(ψ_f3x, x) ≈ 1.0 + -1.0 * (2.0 * pi)^3 * cos(2.0 * pi * x) rtol = 1e-3 - @test 1.0 + calculate_fx(ψ_f4x, x) ≈ 1.0 + 1.0 * (2.0 * pi)^4 * sin(2.0 * pi * x) rtol = + @test 1.0 + evaluate(ψ_f4x, x) ≈ 1.0 + 1.0 * (2.0 * pi)^4 * sin(2.0 * pi * x) rtol = 1e-3 end end @@ -57,7 +57,7 @@ using Dictionaries: Dictionary xs = [delta, 0.125, 0.25, 0.625, 0.875] for x in xs - ∂x_ψ_fx_x = real(calculate_fx(∂x_ψ_fx, x)) + ∂x_ψ_fx_x = real(evaluate(∂x_ψ_fx, x)) @test ∂x_ψ_fx_x ≈ pi * cos(pi * x) atol = 1e-3 end end @@ -68,14 +68,14 @@ using Dictionaries: Dictionary s = continuous_siteinds(g; map_dimension=3) - ψ_fx = poly_itn(s, [0.0, -1.0, 1.0]; dimension=1) - ψ_gy = sin_itn(s; k=Number(pi), dimension=2) - ψ_hz = sin_itn(s; k=Number(pi), dimension=3) + ψ_fx = poly_itn(s, [0.0, -1.0, 1.0]; dim=1) + ψ_gy = sin_itn(s; k=Number(pi), dim=2) + ψ_hz = sin_itn(s; k=Number(pi), dim=3) @assert dimension(ψ_fx) == dimension(ψ_gy) == dimension(ψ_hz) == 3 ψ_fxgyhz = ψ_fx * ψ_gy * ψ_hz - ∂_∂y = first_derivative_operator(s; dimension=2, cutoff=1e-10) + ∂_∂y = first_derivative_operator(s; dim=2, cutoff=1e-10) ∂_∂y_ψ_fxgyhz = operate([∂_∂y], ψ_fxgyhz; cutoff=1e-10) @@ -85,10 +85,10 @@ using Dictionaries: Dictionary for x in xs for y in ys for z in zs - ψ_fxgyhz_xyz = real(calculate_fxyz(ψ_fxgyhz, [x, y, z])) + ψ_fxgyhz_xyz = real(evaluate(ψ_fxgyhz, [x, y, z])) @test ψ_fxgyhz_xyz ≈ (x^2 - x) * sin(pi * y) * sin(pi * z) atol = 1e-3 - ∂_∂y_ψ_fxgyhz_xyz = real(calculate_fxyz(∂_∂y_ψ_fxgyhz, [x, y, z])) + ∂_∂y_ψ_fxgyhz_xyz = real(evaluate(∂_∂y_ψ_fxgyhz, [x, y, z])) @test ∂_∂y_ψ_fxgyhz_xyz ≈ pi * (x^2 - x) * cos(pi * y) * sin(pi * z) atol = 1e-3 end end @@ -106,7 +106,7 @@ using Dictionaries: Dictionary ψ_fxgx = ψ_gx * ψ_fx xs = [0.025, 0.1, 0.25, 0.625, 0.875] for x in xs - ψ_fxgx_x = real(calculate_fx(ψ_fxgx, x)) + ψ_fxgx_x = real(evaluate(ψ_fxgx, x)) @test ψ_fxgx_x ≈ sin(0.5 * pi * x) * cos(0.25 * pi * x) atol = 1e-3 end end @@ -118,8 +118,8 @@ using Dictionaries: Dictionary s = continuous_siteinds(g; map_dimension=2) - ψ_fx = cos_itn(s; k=0.25 * Number(pi), dimension=1) - ψ_gy = sin_itn(s; k=0.5 * Number(pi), dimension=2) + ψ_fx = cos_itn(s; k=0.25 * Number(pi), dim=1) + ψ_gy = sin_itn(s; k=0.5 * Number(pi), dim=2) @assert dimension(ψ_fx) == dimension(ψ_gy) == 2 ψ_fxgy = ψ_fx * ψ_gy @@ -128,11 +128,11 @@ using Dictionaries: Dictionary ys = [0.125, 0.25, 0.625, 0.875] for x in xs for y in ys - ψ_fx_x = real(calculate_fxyz(ψ_fx, [x, y])) - ψ_gy_y = real(calculate_fxyz(ψ_gy, [x, y])) + ψ_fx_x = real(evaluate(ψ_fx, [x, y])) + ψ_gy_y = real(evaluate(ψ_gy, [x, y])) @test ψ_fx_x ≈ cos(0.25 * pi * x) @test ψ_gy_y ≈ sin(0.5 * pi * y) - ψ_fxgy_xy = real(calculate_fxyz(ψ_fxgy, [x, y])) + ψ_fxgy_xy = real(evaluate(ψ_fxgy, [x, y])) @test ψ_fxgy_xy ≈ cos(0.25 * pi * x) * sin(0.5 * pi * y) atol = 1e-3 end end @@ -174,26 +174,25 @@ using Dictionaries: Dictionary for x in xs if x + delta < 1 - fx_xplus = calculate_fx(ψ_fx, x + delta) - @test fx_xplus ≈ calculate_fx(ψ_fx_pshift_dirichlet, x) atol = 1e-8 - @test fx_xplus ≈ calculate_fx(ψ_fx_pshift_pbc, x) atol = 1e-8 - @test fx_xplus ≈ calculate_fx(ψ_fx_pshift_neumann, x) atol = 1e-8 + fx_xplus = evaluate(ψ_fx, x + delta) + @test fx_xplus ≈ evaluate(ψ_fx_pshift_dirichlet, x) atol = 1e-8 + @test fx_xplus ≈ evaluate(ψ_fx_pshift_pbc, x) atol = 1e-8 + @test fx_xplus ≈ evaluate(ψ_fx_pshift_neumann, x) atol = 1e-8 elseif x == 1.0 - delta - @test calculate_fx(ψ_fx_pshift_dirichlet, x) ≈ 0.0 atol = 1e-8 - @test calculate_fx(ψ_fx_pshift_pbc, x) ≈ calculate_fx(ψ_fx, 0.0) atol = 1e-8 - @test calculate_fx(ψ_fx_pshift_neumann, x) ≈ calculate_fx(ψ_fx, 1.0 - delta) atol = - 1e-8 + @test evaluate(ψ_fx_pshift_dirichlet, x) ≈ 0.0 atol = 1e-8 + @test evaluate(ψ_fx_pshift_pbc, x) ≈ evaluate(ψ_fx, 0.0) atol = 1e-8 + @test evaluate(ψ_fx_pshift_neumann, x) ≈ evaluate(ψ_fx, 1.0 - delta) atol = 1e-8 end if x - delta >= 0.0 - fx_xminus = calculate_fx(ψ_fx, x - delta) - @test fx_xminus ≈ calculate_fx(ψ_fx_mshift_dirichlet, x) atol = 1e-8 - @test fx_xminus ≈ calculate_fx(ψ_fx_mshift_pbc, x) atol = 1e-8 - @test fx_xminus ≈ calculate_fx(ψ_fx_mshift_neumann, x) atol = 1e-8 + fx_xminus = evaluate(ψ_fx, x - delta) + @test fx_xminus ≈ evaluate(ψ_fx_mshift_dirichlet, x) atol = 1e-8 + @test fx_xminus ≈ evaluate(ψ_fx_mshift_pbc, x) atol = 1e-8 + @test fx_xminus ≈ evaluate(ψ_fx_mshift_neumann, x) atol = 1e-8 elseif x == 0.0 - @test calculate_fx(ψ_fx_mshift_dirichlet, x) ≈ 0.0 atol = 1e-8 - @test calculate_fx(ψ_fx_mshift_pbc, x) ≈ calculate_fx(ψ_fx, 1.0 - delta) atol = 1e-8 - @test calculate_fx(ψ_fx_mshift_neumann, x) ≈ calculate_fx(ψ_fx, 0.0) atol = 1e-8 + @test evaluate(ψ_fx_mshift_dirichlet, x) ≈ 0.0 atol = 1e-8 + @test evaluate(ψ_fx_mshift_pbc, x) ≈ evaluate(ψ_fx, 1.0 - delta) atol = 1e-8 + @test evaluate(ψ_fx_mshift_neumann, x) ≈ evaluate(ψ_fx, 0.0) atol = 1e-8 end end end @@ -235,27 +234,27 @@ using Dictionaries: Dictionary for x in xs if x + 2.0 * delta < 1 - fx_xplus = calculate_fx(ψ_fx, x + 2.0 * delta) - @test fx_xplus ≈ calculate_fx(ψ_fx_pshift_dirichlet, x) atol = 1e-8 - @test fx_xplus ≈ calculate_fx(ψ_fx_pshift_pbc, x) atol = 1e-8 - @test fx_xplus ≈ calculate_fx(ψ_fx_pshift_neumann, x) atol = 1e-8 + fx_xplus = evaluate(ψ_fx, x + 2.0 * delta) + @test fx_xplus ≈ evaluate(ψ_fx_pshift_dirichlet, x) atol = 1e-8 + @test fx_xplus ≈ evaluate(ψ_fx_pshift_pbc, x) atol = 1e-8 + @test fx_xplus ≈ evaluate(ψ_fx_pshift_neumann, x) atol = 1e-8 elseif x == 1.0 - 2.0 * delta || x == 1.0 - delta - @test calculate_fx(ψ_fx_pshift_dirichlet, x; alg="exact") ≈ 0.0 atol = 1e-8 - @test calculate_fx(ψ_fx_pshift_pbc, x) ≈ calculate_fx(ψ_fx, x + 2.0 * delta - 1.0) atol = + @test evaluate(ψ_fx_pshift_dirichlet, x; alg="exact") ≈ 0.0 atol = 1e-8 + @test evaluate(ψ_fx_pshift_pbc, x) ≈ evaluate(ψ_fx, x + 2.0 * delta - 1.0) atol = 1e-8 - @test calculate_fx(ψ_fx_pshift_neumann, x) ≈ calculate_fx(ψ_fx, x) atol = 1e-8 + @test evaluate(ψ_fx_pshift_neumann, x) ≈ evaluate(ψ_fx, x) atol = 1e-8 end if x - 2.0 * delta >= 0.0 - fx_xminus = calculate_fx(ψ_fx, x - 2.0 * delta) - @test fx_xminus ≈ calculate_fx(ψ_fx_mshift_dirichlet, x) atol = 1e-8 - @test fx_xminus ≈ calculate_fx(ψ_fx_mshift_pbc, x) atol = 1e-8 - @test fx_xminus ≈ calculate_fx(ψ_fx_mshift_neumann, x) atol = 1e-8 + fx_xminus = evaluate(ψ_fx, x - 2.0 * delta) + @test fx_xminus ≈ evaluate(ψ_fx_mshift_dirichlet, x) atol = 1e-8 + @test fx_xminus ≈ evaluate(ψ_fx_mshift_pbc, x) atol = 1e-8 + @test fx_xminus ≈ evaluate(ψ_fx_mshift_neumann, x) atol = 1e-8 else - @test calculate_fx(ψ_fx_mshift_dirichlet, x) ≈ 0.0 atol = 1e-8 - @test calculate_fx(ψ_fx_mshift_pbc, x) ≈ calculate_fx(ψ_fx, x - 2.0 * delta + 1.0) atol = + @test evaluate(ψ_fx_mshift_dirichlet, x) ≈ 0.0 atol = 1e-8 + @test evaluate(ψ_fx_mshift_pbc, x) ≈ evaluate(ψ_fx, x - 2.0 * delta + 1.0) atol = 1e-8 - @test calculate_fx(ψ_fx_mshift_neumann, x) ≈ calculate_fx(ψ_fx, x) atol = 1e-8 + @test evaluate(ψ_fx_mshift_neumann, x) ≈ evaluate(ψ_fx, x) atol = 1e-8 end end end @@ -267,27 +266,27 @@ using Dictionaries: Dictionary delta = 2.0^(-1.0 * L) x = 0.5 ys = [0.0, delta, 0.25, 0.5, 0.625, 0.875, 1.0 - delta] - ψ_fx = poly_itn(s, [1.0, 0.5, 0.25]; dimension=1) - ψ_fy = cos_itn(s; dimension=2) + ψ_fx = poly_itn(s, [1.0, 0.5, 0.25]; dim=1) + ψ_fy = cos_itn(s; dim=2) ψ_fxy = ψ_fx + ψ_fx forward_shift_dirichlet = forward_shift_op( - s; boundary="Dirichlet", dimension=2, truncate_kwargs=(; cutoff=1e-10) + s; boundary="Dirichlet", dim=2, truncate_kwargs=(; cutoff=1e-10) ) backward_shift_dirichlet = backward_shift_op( - s; boundary="Dirichlet", dimension=2, truncate_kwargs=(; cutoff=1e-10) + s; boundary="Dirichlet", dim=2, truncate_kwargs=(; cutoff=1e-10) ) forward_shift_pbc = forward_shift_op( - s; boundary="Periodic", dimension=2, truncate_kwargs=(; cutoff=1e-10) + s; boundary="Periodic", dim=2, truncate_kwargs=(; cutoff=1e-10) ) backward_shift_pbc = backward_shift_op( - s; boundary="Periodic", dimension=2, truncate_kwargs=(; cutoff=1e-10) + s; boundary="Periodic", dim=2, truncate_kwargs=(; cutoff=1e-10) ) forward_shift_neumann = forward_shift_op( - s; boundary="Neumann", dimension=2, truncate_kwargs=(; cutoff=1e-10) + s; boundary="Neumann", dim=2, truncate_kwargs=(; cutoff=1e-10) ) backward_shift_neumann = backward_shift_op( - s; boundary="Neumann", dimension=2, truncate_kwargs=(; cutoff=1e-10) + s; boundary="Neumann", dim=2, truncate_kwargs=(; cutoff=1e-10) ) ψ_fxy_pshift_dirichlet = operate(forward_shift_dirichlet, ψ_fxy; cutoff=1e-12) @@ -299,29 +298,27 @@ using Dictionaries: Dictionary for y in ys if y + delta < 1 - fxy_xyplus = calculate_fxyz(ψ_fxy, [x, y + delta]) - @test fxy_xyplus ≈ calculate_fxyz(ψ_fxy_pshift_dirichlet, [x, y]) atol = 1e-8 - @test fxy_xyplus ≈ calculate_fxyz(ψ_fxy_pshift_pbc, [x, y]) atol = 1e-8 - @test fxy_xyplus ≈ calculate_fxyz(ψ_fxy_pshift_neumann, [x, y]) atol = 1e-8 + fxy_xyplus = evaluate(ψ_fxy, [x, y + delta]) + @test fxy_xyplus ≈ evaluate(ψ_fxy_pshift_dirichlet, [x, y]) atol = 1e-8 + @test fxy_xyplus ≈ evaluate(ψ_fxy_pshift_pbc, [x, y]) atol = 1e-8 + @test fxy_xyplus ≈ evaluate(ψ_fxy_pshift_neumann, [x, y]) atol = 1e-8 elseif y == 1.0 - delta - @test calculate_fxyz(ψ_fxy_pshift_dirichlet, [x, y]) ≈ 0.0 atol = 1e-8 - @test calculate_fxyz(ψ_fxy_pshift_pbc, [x, y]) ≈ calculate_fxyz(ψ_fxy, [x, 0.0]) atol = + @test evaluate(ψ_fxy_pshift_dirichlet, [x, y]) ≈ 0.0 atol = 1e-8 + @test evaluate(ψ_fxy_pshift_pbc, [x, y]) ≈ evaluate(ψ_fxy, [x, 0.0]) atol = 1e-8 + @test evaluate(ψ_fxy_pshift_neumann, [x, y]) ≈ evaluate(ψ_fxy, [x, 1.0 - delta]) atol = 1e-8 - @test calculate_fxyz(ψ_fxy_pshift_neumann, [x, y]) ≈ - calculate_fxyz(ψ_fxy, [x, 1.0 - delta]) atol = 1e-8 end if y - delta >= 0.0 - fxy_xyminus = calculate_fxyz(ψ_fxy, [x, y - delta]) - @test fxy_xyminus ≈ calculate_fxyz(ψ_fxy_mshift_dirichlet, [x, y]) atol = 1e-8 - @test fxy_xyminus ≈ calculate_fxyz(ψ_fxy_mshift_pbc, [x, y]) atol = 1e-8 - @test fxy_xyminus ≈ calculate_fxyz(ψ_fxy_mshift_neumann, [x, y]) atol = 1e-8 + fxy_xyminus = evaluate(ψ_fxy, [x, y - delta]) + @test fxy_xyminus ≈ evaluate(ψ_fxy_mshift_dirichlet, [x, y]) atol = 1e-8 + @test fxy_xyminus ≈ evaluate(ψ_fxy_mshift_pbc, [x, y]) atol = 1e-8 + @test fxy_xyminus ≈ evaluate(ψ_fxy_mshift_neumann, [x, y]) atol = 1e-8 elseif y == 0.0 - @test calculate_fxyz(ψ_fxy_mshift_dirichlet, [x, y]) ≈ 0.0 atol = 1e-8 - @test calculate_fxyz(ψ_fxy_mshift_pbc, [x, y]) ≈ - calculate_fxyz(ψ_fxy, [x, 1.0 - delta]) atol = 1e-8 - @test calculate_fxyz(ψ_fxy_mshift_neumann, [x, y]) ≈ calculate_fxyz(ψ_fxy, [x, 0.0]) atol = + @test evaluate(ψ_fxy_mshift_dirichlet, [x, y]) ≈ 0.0 atol = 1e-8 + @test evaluate(ψ_fxy_mshift_pbc, [x, y]) ≈ evaluate(ψ_fxy, [x, 1.0 - delta]) atol = 1e-8 + @test evaluate(ψ_fxy_mshift_neumann, [x, y]) ≈ evaluate(ψ_fxy, [x, 0.0]) atol = 1e-8 end end end @@ -340,7 +337,7 @@ using Dictionaries: Dictionary @testset "corner boundary test" begin for p1 in [0, lastDigit] - p = (itensornetwork(delta_x(s, p1))) + p = (itensornetwork(delta_p(s, p1))) @test inner(p, Zo, p) ≈ 0.0 end end @@ -348,7 +345,7 @@ using Dictionaries: Dictionary maxdim, cutoff = 10, 1e-16 ϕ_fx = map_to_zeros(ψ_fx, [0, lastDigit]; cutoff, maxdim) for x in xs - val = real(calculate_fx(ϕ_fx, x)) + val = real(evaluate(ϕ_fx, x)) @test (x ∈ [0, lastDigit]) ? isapprox(val, 0.0; atol=1e-8) : !(val ≈ 0.0) end end @@ -362,15 +359,15 @@ using Dictionaries: Dictionary lastDigit = 1 - delta ys = [0.0, delta, 0.25, 0.5, 0.625, 0.875, lastDigit] - ψ_fx = poly_itn(s, [1.0, 0.5, 0.25]; dimension=1) - ψ_fy = cos_itn(s; dimension=2) + ψ_fx = poly_itn(s, [1.0, 0.5, 0.25]; dim=1) + ψ_fy = cos_itn(s; dim=2) ψ_fxy = ψ_fx + ψ_fy Zo = map_to_zero_operator(s, [0, lastDigit, 0, lastDigit], [1, 1, 2, 2]) @testset "corner boundary test" begin for p1 in [0, lastDigit] for p2 in [0, lastDigit] - p = itensornetwork(delta_xyz(s, [p1, p2])) + p = itensornetwork(delta_p(s, [p1, p2])) @test inner(p, Zo, p) ≈ 0.0 end end @@ -382,7 +379,7 @@ using Dictionaries: Dictionary for x in [0, lastDigit] vals = zeros(length(ys)) for (i, y) in enumerate(ys) - vals[i] = real(calculate_fxyz(ϕ_fxy, [x, y])) + vals[i] = real(evaluate(ϕ_fxy, [x, y])) end @test all(isapprox.(vals, 0.0, atol=1e-8)) end @@ -398,9 +395,9 @@ using Dictionaries: Dictionary xs = [0.0, delta, 0.25, 0.625, 0.875, lastDigit] ψ_fx = delta_kernel(s, [[0.5]]; coeff=-1, include_identity=true) - @test calculate_fxyz(ψ_fx, [0.5]) ≈ 0 + @test evaluate(ψ_fx, [0.5]) ≈ 0 for x in xs - @test calculate_fxyz(ψ_fx, [x]) ≈ 1 + @test evaluate(ψ_fx, [x]) ≈ 1 end end @testset "test delta-kernel in 2D" begin @@ -413,26 +410,26 @@ using Dictionaries: Dictionary xs = [0.0, delta, 0.25, 0.625, 0.875, lastDigit] @testset "insersecting lines" begin ψ_f = delta_kernel(s, [[0.5], [0.5]], [[1], [2]]; coeff=-1, include_identity=true) - @test calculate_fxyz(ψ_f, [0.5, 0.5]) ≈ 0 + @test evaluate(ψ_f, [0.5, 0.5]) ≈ 0 for x in xs - @test calculate_fxyz(ψ_f, [x, 0.5]) ≈ 0 - @test calculate_fxyz(ψ_f, [0.5, x], [1, 2]) ≈ 0 + @test evaluate(ψ_f, [x, 0.5]) ≈ 0 + @test evaluate(ψ_f, [0.5, x], [1, 2]) ≈ 0 - @test calculate_fxyz(ψ_f, [x, delta], [1, 2]) ≈ 1 - @test calculate_fxyz(ψ_f, [delta, x], [1, 2]) ≈ 1 + @test evaluate(ψ_f, [x, delta], [1, 2]) ≈ 1 + @test evaluate(ψ_f, [delta, x], [1, 2]) ≈ 1 end end @testset "line and point" begin ψ_f = delta_kernel( s, [[0.5], [0.5, 0.1]], [[1], [1, 2]]; coeff=-1, include_identity=true ) - @test calculate_fxyz(ψ_f, [0.5, 0.5]) ≈ 0 - @test calculate_fxyz(ψ_f, [0.5, 0.1]) ≈ 0 + @test evaluate(ψ_f, [0.5, 0.5]) ≈ 0 + @test evaluate(ψ_f, [0.5, 0.1]) ≈ 0 for x in xs - @test calculate_fxyz(ψ_f, [0.5, x], [1, 2]) ≈ 0 + @test evaluate(ψ_f, [0.5, x], [1, 2]) ≈ 0 - @test calculate_fxyz(ψ_f, [x, delta], [1, 2]) ≈ 1 - @test calculate_fxyz(ψ_f, [delta, x], [1, 2]) ≈ 1 + @test evaluate(ψ_f, [x, delta], [1, 2]) ≈ 1 + @test evaluate(ψ_f, [delta, x], [1, 2]) ≈ 1 end end end @@ -449,13 +446,13 @@ using Dictionaries: Dictionary @testset "insersecting planes" begin ψ_f = delta_kernel(s, [[0.5], [0.5]], [[1], [2]]; coeff=-1, include_identity=true) for z in zs - @test calculate_fxyz(ψ_f, [0.5, 0.5, z]) ≈ 0 + @test evaluate(ψ_f, [0.5, 0.5, z]) ≈ 0 for x in xs - @test calculate_fxyz(ψ_f, [x, 0.5, z]) ≈ 0 - @test calculate_fxyz(ψ_f, [0.5, x, z], [1, 2, 3]) ≈ 0 + @test evaluate(ψ_f, [x, 0.5, z]) ≈ 0 + @test evaluate(ψ_f, [0.5, x, z], [1, 2, 3]) ≈ 0 - @test calculate_fxyz(ψ_f, [x, delta, z], [1, 2, 3]) ≈ 1 - @test calculate_fxyz(ψ_f, [delta, x, z], [1, 2, 3]) ≈ 1 + @test evaluate(ψ_f, [x, delta, z], [1, 2, 3]) ≈ 1 + @test evaluate(ψ_f, [delta, x, z], [1, 2, 3]) ≈ 1 end end end @@ -464,13 +461,13 @@ using Dictionaries: Dictionary s, [[0.5], [0.5, 0]], [[1], [1, 2]]; coeff=-1, include_identity=true ) for z in zs - @test calculate_fxyz(ψ_f, [0.5, 0.5, z]) ≈ 0 - @test calculate_fxyz(ψ_f, [0.5, 0, z]) ≈ 0 + @test evaluate(ψ_f, [0.5, 0.5, z]) ≈ 0 + @test evaluate(ψ_f, [0.5, 0, z]) ≈ 0 for x in xs - @test calculate_fxyz(ψ_f, [0.5, x, z], [1, 2, 3]) ≈ 0 + @test evaluate(ψ_f, [0.5, x, z], [1, 2, 3]) ≈ 0 - @test calculate_fxyz(ψ_f, [x, delta, z], [1, 2, 3]) ≈ 1 - @test calculate_fxyz(ψ_f, [delta, x, z], [1, 2, 3]) ≈ 1 + @test evaluate(ψ_f, [x, delta, z], [1, 2, 3]) ≈ 1 + @test evaluate(ψ_f, [delta, x, z], [1, 2, 3]) ≈ 1 end end end @@ -478,14 +475,14 @@ using Dictionaries: Dictionary ψ_f = delta_kernel( s, [[0.5, 0], [0, 0.5]], [[2, 3], [1, 2]]; coeff=-1, include_identity=true ) - @test calculate_fxyz(ψ_f, [0.0, 0.5, 0.5]) ≈ 0 + @test evaluate(ψ_f, [0.0, 0.5, 0.5]) ≈ 0 for z in [0] - @test calculate_fxyz(ψ_f, [0.0, 0.5, z]) ≈ 0 + @test evaluate(ψ_f, [0.0, 0.5, z]) ≈ 0 for x in xs - @test calculate_fxyz(ψ_f, [x, 0.5, z], [1, 2, 3]) ≈ 0 + @test evaluate(ψ_f, [x, 0.5, z], [1, 2, 3]) ≈ 0 - @test calculate_fxyz(ψ_f, [x, delta, z], [1, 2, 3]) ≈ 1 - @test calculate_fxyz(ψ_f, [delta, x, z], [1, 2, 3]) ≈ 1 + @test evaluate(ψ_f, [x, delta, z], [1, 2, 3]) ≈ 1 + @test evaluate(ψ_f, [delta, x, z], [1, 2, 3]) ≈ 1 end end end From e87ea6db2800bda5c8089d6686f156631437f750 Mon Sep 17 00:00:00 2001 From: Ryan Levy Date: Wed, 5 Jun 2024 09:22:37 -0400 Subject: [PATCH 02/31] Add RNG passing to rand_p --- src/indexmap.jl | 12 +++++++----- src/indsnetworkmap.jl | 9 +++++++++ test/test_indexmaps.jl | 6 ++++-- 3 files changed, 20 insertions(+), 7 deletions(-) diff --git a/src/indexmap.jl b/src/indexmap.jl index cb6c284..1cd32a7 100644 --- a/src/indexmap.jl +++ b/src/indexmap.jl @@ -2,7 +2,7 @@ using Base: Base using Dictionaries: Dictionary, set! using ITensors: ITensors, Index, dim using ITensorNetworks: IndsNetwork, vertex_data -using Random: rand +using Random: Random, rand, AbstractRNG struct IndexMap{VB,VD} index_digit::VB @@ -244,14 +244,16 @@ end """ Picks a random grid point from `imap` given a dimension """ -function rand_p(imap::IndexMap, d::Integer) +function rand_p(rng::AbstractRNG, imap::IndexMap, d::Integer) dims = dim.(dimension_inds(imap, d)) @assert all(y -> y == first(dims), dims) base = dims[d] L = length(dimension_inds(imap, d)) - return rand(0:(base^L - 1)) / base^L + return rand(rng, 0:(base^L - 1)) / base^L end -function rand_p(imap::IndexMap) - return [rand_p(imap, i) for i in 1:dimension(imap)] +function rand_p(rng::AbstractRNG, imap::IndexMap) + return [rand_p(rng, imap, i) for i in 1:dimension(imap)] end + +rand_p(imap::IndexMap, args...) = rand_p(Random.default_rng(), imap, args...) diff --git a/src/indsnetworkmap.jl b/src/indsnetworkmap.jl index c69deed..71aea10 100644 --- a/src/indsnetworkmap.jl +++ b/src/indsnetworkmap.jl @@ -4,6 +4,7 @@ using NamedGraphs: NamedGraphs using ITensors: ITensors using ITensorNetworks: ITensorNetworks, AbstractIndsNetwork, IndsNetwork, data_graph, underlying_graph +using Random: AbstractRNG struct IndsNetworkMap{V,I,IN<:IndsNetwork{V,I},IM} <: AbstractIndsNetwork{V,I} indsnetwork::IN @@ -70,6 +71,14 @@ for f in [ end end end +# Forward RNG functionality +for f in [:rand_p] + @eval begin + function $f(rng::AbstractRNG, inm::IndsNetworkMap, args...; kwargs...) + return $f(rng, indexmap(inm), args...; kwargs...) + end + end +end #Functions on indsnetwork that don't seem to autoforward function ITensors.inds(inm::IndsNetworkMap, args...; kwargs...) diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 8f62e93..e1eb489 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -5,6 +5,7 @@ using NamedGraphs: vertices using NamedGraphs.NamedGraphGenerators: named_grid, named_comb_tree using ITensors: siteinds, inds using Dictionaries: Dictionary +using Random: Random @testset "indexmap tests" begin @testset "test single dimensional index map" begin @@ -87,8 +88,9 @@ using Dictionaries: Dictionary @test internal >= left && internal >= right #test the rand() function to see if it succeeds - rand_gridpoint1 = rand_p(s) - rand_gridpoint2 = rand_p(s, 1) + rng = Random.Xoshiro(42) + rand_gridpoint1 = rand_p(rng, s) + rand_gridpoint2 = rand_p(rng, s, 1) #fourth set -- very large L L = 140 From f4032a2084be7101e361cf1316bd1616d92cd15a Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Wed, 5 Jun 2024 10:09:38 -0400 Subject: [PATCH 03/31] add default rng tests --- test/test_indexmaps.jl | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index e1eb489..df998df 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -87,10 +87,12 @@ using Random: Random right = (b - test3[end]) @test internal >= left && internal >= right - #test the rand() function to see if it succeeds + #test the rand_p() function to see if it succeeds rng = Random.Xoshiro(42) rand_gridpoint1 = rand_p(rng, s) rand_gridpoint2 = rand_p(rng, s, 1) + default_rng_gridpoint1 = rand_p(s) + default_rng_gridpoint2 = rand_p(s,1) #fourth set -- very large L L = 140 From f85ab8323d50bf1aaac283a06b51d3e20280bb1c Mon Sep 17 00:00:00 2001 From: Ryan Anselm <31040739+ryboselm@users.noreply.github.com> Date: Thu, 20 Jun 2024 15:50:31 -0400 Subject: [PATCH 04/31] Methods to convert Data and Functions into QTT format (#3) * Add support for rng and eltype in rand_itn * Bump ITN version * Rename to prevent dimension overload * Rename calculate_fx(yz) to evaluate * Rename calculate_x(yz) to calculate_p * Rename delta_x(yz) to delta_p * Return dimension_indices * add 1d polynomial interpolation * added black box function ITNs for fourier/chebyshev * working chebyshev * experimenting with function_itn * add data_itensornetwork() * started 2D functions, expanded data into QTT * working 2D function TNs * 2D data to ITN * clean up code * rename examples and add image to ITN example * function/data itn now takes top coefficients by magnitude by default * formatting * add data_itn documentation * move interpolation functions to new file * add compat version info --------- Co-authored-by: Ryan Levy Co-authored-by: Joseph Tindall <51231103+JoeyT1994@users.noreply.github.com> --- .gitignore | 2 + .vscode/settings.json | 2 + Project.toml | 7 +- examples/1D_data_into_ITN.jl | 71 +++++++ examples/1D_function_into_ITN.jl | 178 ++++++++++++++++++ examples/2D_data_into_ITN.jl | 90 +++++++++ examples/2D_function_into_ITN.jl | 73 ++++++++ examples/Statue_Of_Liberty.png | Bin 0 -> 935673 bytes examples/image_into_ITN.jl | 98 ++++++++++ src/ITensorNumericalAnalysis.jl | 16 +- src/interpolation_functions.jl | 308 +++++++++++++++++++++++++++++++ test/test_indexmaps.jl | 2 +- 12 files changed, 844 insertions(+), 3 deletions(-) create mode 100644 .vscode/settings.json create mode 100644 examples/1D_data_into_ITN.jl create mode 100644 examples/1D_function_into_ITN.jl create mode 100644 examples/2D_data_into_ITN.jl create mode 100644 examples/2D_function_into_ITN.jl create mode 100644 examples/Statue_Of_Liberty.png create mode 100644 examples/image_into_ITN.jl create mode 100644 src/interpolation_functions.jl diff --git a/.gitignore b/.gitignore index 628ce42..b590bfe 100644 --- a/.gitignore +++ b/.gitignore @@ -41,3 +41,5 @@ Sessionx.vim tags # Persistent undo [._]*.un~ + +plots diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..7a73a41 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,2 @@ +{ +} \ No newline at end of file diff --git a/Project.toml b/Project.toml index afd7bf0..abecd90 100644 --- a/Project.toml +++ b/Project.toml @@ -4,21 +4,26 @@ authors = ["Joseph Tindall ", "Ryan Levy join(["$i," for i in v]), g) + +#random tree +# g = NamedGraph(SimpleGraph(uniform_tree(L))) +# g = rename_vertices(v -> (v, 1), g) + +s = continuous_siteinds(g; map_dimension=1) + +function eval_L1(s, ψ, f) + x_vals = grid_points(s, 1) + error = 0 + # (∑|ψ(x) - f(x)|) + for (i, x) in enumerate(x_vals) + error += abs(real(evaluate(ψ, [x])) - f(x)) + end + return error +end + +function eval_L2(s, ψ, f) + x_vals = grid_points(s, 1) + error = 0 + # (∑|ψ(x) - f(x)|^2) + for (i, x) in enumerate(x_vals) + error += (real(evaluate(ψ, [x])) - f(x))^2 + end + return error / length(x_vals) +end + +function L2_error(truth, est) + if length(truth) != length(est) + throw("not equal length!") + end + return sum((truth .- est) .^ 2) / length(truth) +end + +### Potential functions to choose from + +#piecewise function +#f(x) = x < 0.75 ? x < 0.25 ? 0 : sin(4π * (x - 0.25)) : 0 +#gaussian +#f(x) = exp(-(x - 0.5)^2 / 0.01) + +#almost 1/x function. this breaks it if the cutoff is not fairly large/max_coeffs fairly small +# f(x) = 1/(.01+x) + 5*x^2 + +#f(x) = sin(1/(.01+x)) +#f(x) = cos(π*x) + 5*x +#f(x) = sin(20*x^(1/7)) + +# +# Sum of random Gaussians +# +Ng = 40 +ω = 0.001 +ws = [ω * rand() for n in 1:Ng] +xs = [rand() for n in 1:Ng] +hs = [randn() for n in 1:Ng] +step_size = 2.5 * rand() +step_location = 0.4 +function f(x::Number) + val = sum(g -> hs[g] * exp(-(x[1] - xs[g])^2 / ws[g]), 1:Ng) + val += (x[1] > step_location) ? step_size : 0.0 + return val +end + +### Plotting f(x) vs ITN encodings using Fourier or Chebyshev decompositions + +cheb_max = 25 +fourier_max = 100 +cheb_cut = 1e-3 +fourier_cut = 1e-3 + +ψ_c, cc = function_itn( + s, f; cutoff=cheb_cut, max_coeffs=cheb_max, mode="chebyshev", by_mag=false +) +ψ_f, cf = function_itn(s, f; cutoff=fourier_cut, max_coeffs=fourier_max, mode="fourier") + +n_c = length(cc) +n_f = length(cf) + +println("truncating...") +ψ_c = truncate(ψ_c; cutoff=1e-10) +ψ_f = truncate(ψ_f; cutoff=1e-10) + +println("chebyshev maxlinkdim $(maxlinkdim(ψ_c))") +println("fourier maxlinkdim $(maxlinkdim(ψ_f))") + +fourier_L1 = eval_L1(s, ψ_f, f) +fourier_L2 = eval_L2(s, ψ_f, f) +cheb_L1 = eval_L1(s, ψ_c, f) +cheb_L2 = eval_L2(s, ψ_c, f) +println("Fourier L2: $fourier_L2") +println("Chebyshev L2: $cheb_L2") + +x_vals = grid_points(s, 1) +f_vals = [real(evaluate(ψ_f, [x])) for x in x_vals] +c_vals = [real(evaluate(ψ_c, [x])) for x in x_vals] +true_vals = [f(x) for x in x_vals] + +# println("Fourier L2 (second method): $(L2_error(true_vals,f_vals))") +# println("Cheb L2 (second method): $(L2_error(true_vals, c_vals))") + +println("Plotting f(x)") +plot(x_vals, true_vals; label="true function", title="f(x)") +plot!(x_vals, f_vals; label="Fourier w/ $n_f terms") +plot!(x_vals, c_vals; label="Chebyshev w/ $n_c terms") + +### Plots of Loss vs # terms and Maxlinkdim vs # terms + +# max_terms = 25 +# eval_range = 1:3:max_terms +# l = length(eval_range) + +# cheb_L1 = zeros(l) +# cheb_L2 = zeros(l) +# fourier_L1 = zeros(l) +# fourier_L2 = zeros(l) +# cheb_mld = zeros(l) +# fourier_mld = zeros(l) + +# for (j, i) in enumerate(eval_range) +# println("$i terms") + +# local ψ_c, n_c = function_itn(s, f; cutoff=1e-10, max_coeffs=i, mode="chebyshev") +# local ψ_f, n_f = function_itn(s, f; cutoff=1e-10, max_coeffs=i, mode="fourier") + +# ψ_c = truncate(ψ_c; cutoff=1e-10) +# ψ_f = truncate(ψ_f; cutoff=1e-10) + +# cheb_L1[j] = eval_L1(s, ψ_c, f) +# cheb_L2[j] = eval_L2(s, ψ_c, f) +# fourier_L1[j] = eval_L1(s, ψ_f, f) +# fourier_L2[j] = eval_L2(s, ψ_f, f) +# cheb_mld[j] = maxlinkdim(ψ_c) +# fourier_mld[j] = maxlinkdim(ψ_f) +# end + +# plot1 = plot( +# eval_range, +# cheb_L1; +# label="Cheb L1", +# title="f(x) = exp(-(x-0.5)^2/.01)", +# xlabel="number of terms", +# ylabel="loss", +# ) +# plot!(eval_range, cheb_L2; label="Cheb L2") +# plot!(eval_range, fourier_L1; label="Fourier L1") +# plot!(eval_range, fourier_L2; label="Fourier L2") + +# plot2 = plot( +# eval_range, +# cheb_mld; +# label="Chebyshev", +# title="f(x) = exp(-(x-0.5)^2/.01)", +# xlabel="number of terms", +# ylabel="max bond dimension", +# ) +# plot!(eval_range, fourier_mld; label="Fourier") + +# display(plot1, plot2, layout=(1,2)) diff --git a/examples/2D_data_into_ITN.jl b/examples/2D_data_into_ITN.jl new file mode 100644 index 0000000..d221344 --- /dev/null +++ b/examples/2D_data_into_ITN.jl @@ -0,0 +1,90 @@ +using ITensorNumericalAnalysis + +using Graphs: SimpleGraph, uniform_tree +using NamedGraphs: NamedGraph +using NamedGraphs.GraphsExtensions: rename_vertices +using NamedGraphs.NamedGraphGenerators: named_comb_tree, named_binary_tree +using Random +using ITensorNetworks: maxlinkdim +using Plots +using Interpolations + +Random.seed!(1234) + +function eval_L2(s, f, ψ_f) + x_vals = grid_points(s, 1) + y_vals = grid_points(s, 2) + error_sq = [ + (f(x, y) - real(ITensorNumericalAnalysis.evaluate(ψ_f, [x, y])))^2 for x in x_vals, + y in y_vals + ] + N = length(error_sq) + return sum(error_sq) / N +end + +L = 8 +g = named_comb_tree((2, L ÷ 2)) + +# g = NamedGraph(SimpleGraph(uniform_tree(L))) +# g = rename_vertices(v -> (v, 1), g) + +# g = named_binary_tree(3) +# g = rename_vertices(v -> join(["$i," for i in v]), g) + +s = continuous_siteinds(g; map_dimension=2) + +### Example Test Functions to generate data off of +#f(x, y) = exp( -( (x-0.5)^2 + (y-0.5)^2 )/.05) +f(x, y) = sin(2π * x) + sin(2π * y) + +xrange = 0:0.05:1 +yrange = 0:0.05:1 +noise_level = 0.0 +data = [f(x, y) + noise_level * randn() for x in xrange, y in yrange] + +elapsed_time = @elapsed begin + ψ_f, cf = data_itn(s, data, (xrange, yrange); mode="fourier", cutoff=1e-3, max_coeffs=20) +end +println("ψ_f time: ", elapsed_time) + +elapsed_time = @elapsed begin + ψ_c, cc = data_itn( + s, data, (xrange, yrange); mode="chebyshev", cutoff=1e-3, max_coeffs=20, by_mag=false + ) +end +println("ψ_c time: ", elapsed_time) + +ψ_f = truncate(ψ_f; cutoff=1e-10) +println("size of ψ_f coeffs: $(size(cf))") +println("maxlinkdim of ψ_f after truncation: $(maxlinkdim(ψ_f))") + +ψ_c = truncate(ψ_c; cutoff=1e-10) +println("size of ψ_c coeffs: $(size(cc))") +println("maxlinkdim of ψ_c after truncation: $(maxlinkdim(ψ_c))") + +x_vals = grid_points(s, 1) +y_vals = grid_points(s, length(x_vals), 2) +#f_eval = [f(x,y) for x in x_vals, y in y_vals] +ψ_f_eval = [ + real(ITensorNumericalAnalysis.evaluate(ψ_f, [x, y])) for x in x_vals, y in y_vals +] +ψ_c_eval = [ + real(ITensorNumericalAnalysis.evaluate(ψ_c, [x, y])) for x in x_vals, y in y_vals +] + +g = LinearInterpolation((xrange, yrange), data; extrapolation_bc=Interpolations.Line()) +fourier_loss = eval_L2(s, g, ψ_f) +chebyshev_loss = eval_L2(s, g, ψ_c) +println("fourier L2 error: $fourier_loss") +println("chebyshev L2 error: $chebyshev_loss") + +plot1 = heatmap(xrange, yrange, data; title="true data", xlabel="x", ylabel="y") #true data +plot2 = heatmap( + x_vals, y_vals, ψ_f_eval; title="fourier TN", xlabel="x", ylabel="y", zlabel="ψ(x,y)" +) #fourier TN approximation +plot3 = heatmap( + x_vals, y_vals, ψ_c_eval; title="chebyshev TN", xlabel="x", ylabel="y", zlabel="ψ(x,y)" +) #chebyshev TN approximation + +combined_plot = plot(plot1, plot2, plot3; layout=(1, 3), size=(1200, 280)) +display(combined_plot) diff --git a/examples/2D_function_into_ITN.jl b/examples/2D_function_into_ITN.jl new file mode 100644 index 0000000..a08666e --- /dev/null +++ b/examples/2D_function_into_ITN.jl @@ -0,0 +1,73 @@ +using ITensorNumericalAnalysis + +using Graphs: SimpleGraph, uniform_tree +using NamedGraphs: NamedGraph +using NamedGraphs.GraphsExtensions: rename_vertices +using NamedGraphs.NamedGraphGenerators: named_comb_tree, named_binary_tree +using Random +using ITensorNetworks: maxlinkdim +using Plots + +Random.seed!(1234) + +function eval_L2(f_eval, ψ_eval) + return sum((f_eval .- ψ_eval) .^ 2) +end + +L = 10 + +#comb tree +g = named_comb_tree((2, L ÷ 2)) + +#uniform tree +# g = NamedGraph(SimpleGraph(uniform_tree(L))) +# g = rename_vertices(v -> (v, 1), g) + +#binary tree +# g = named_binary_tree(4) +# g = rename_vertices(v -> join(["$i," for i in v]), g) + +s = continuous_siteinds(g; map_dimension=2) + +x_vals = grid_points(s, 1) +y_vals = grid_points(s, length(x_vals), 2) + +### Example Test Functions to use +f(x, y) = exp(-((x - 0.5)^2 + (y - 0.5)^2) / 0.05) +#f(x, y) = exp(x) - exp(y) +#f(x, y) = cos(20 * (x + y)) + sin(50 * (x - y)) + +ψ_f, cf = function_itn(s, f; mode="fourier", cutoff=1e-3, max_coeffs=100) +ψ_c, cc = function_itn(s, f; mode="chebyshev", cutoff=1e-2, max_coeffs=36, by_mag=false) + +println("maxlinkdim of ψ_f after truncation: $(maxlinkdim(ψ_f))") +println("maxlinkdim of ψ_c after truncation: $(maxlinkdim(ψ_c))") + +f_eval = [f(x, y) for x in x_vals, y in y_vals] +println("f_eval done") +ψ_f_eval = [ + real(ITensorNumericalAnalysis.evaluate(ψ_f, [x, y])) for x in x_vals, y in y_vals +] +println("ψ_f_eval done") +ψ_c_eval = [ + real(ITensorNumericalAnalysis.evaluate(ψ_c, [x, y])) for x in x_vals, y in y_vals +] +println("ψ_c_eval done") + +fourier_loss = eval_L2(f_eval, ψ_f_eval) +chebyshev_loss = eval_L2(f_eval, ψ_c_eval) +println("fourier L2 error: $fourier_loss") +println("chebyshev L2 error: $chebyshev_loss") + +plot1 = heatmap( + x_vals, y_vals, f_eval; title="true function", xlabel="x", ylabel="y", zlabel="f(x,y)" +) #true function +plot2 = heatmap( + x_vals, y_vals, ψ_f_eval; title="fourier TN", xlabel="x", ylabel="y", zlabel="ψ(x,y)" +) #fourier TN approximation +plot3 = heatmap( + x_vals, y_vals, ψ_c_eval; title="chebyshev TN", xlabel="x", ylabel="y", zlabel="ψ(x,y)" +) #chebyshev TN approximation + +combined_plot = plot(plot1, plot2, plot3; layout=(1, 3), size=(1200, 280)) +display(combined_plot) diff --git a/examples/Statue_Of_Liberty.png b/examples/Statue_Of_Liberty.png new file mode 100644 index 0000000000000000000000000000000000000000..adf867af901019428a11154d460abd98573da2c8 GIT binary patch literal 935673 zcmXVX1yCGa)Ai!+wm1ZLO>lPzP6!T*6B68Qao6DP5Q4h}cL^HY-Q8hff1daI&(zdZ z-I|)3>U(eZ>C=59)Kug!P)Se$004%9ytD=Y0H^)mjSTxf;v^a={QjUalh;rN0KDh{ z0RLbB;Q4*X{}2FhU5hND{Wf`PH zM089h8p`9g{`VmmdnXkwn8^b7jQ1}A6r?4zJeE&ib(73TJSmXhEZy%u-bY6d4~x_@ z+YTw_`S(it!^0qN7U0a`ODo`)73QQ!H^zoK|2y6TO$fW>9vx{v{3=U7pI3}5V2s2k z3V=rzhZq0;1%UdCt^T*u$<}OavbuDN*1%Kd%N2YW51Wv 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NamedGraphs.GraphsExtensions: rename_vertices +using NamedGraphs.NamedGraphGenerators: named_comb_tree +using Random +using ITensorNetworks: maxlinkdim +using Plots +using Images: imresize +using FileIO: load + +function eval_L2(f_eval, ψ_eval) + N = length(f_eval) + return sum((f_eval .- ψ_eval) .^ 2) / N +end + +L = 5 +g = named_comb_tree((2, L)) +s = continuous_siteinds(g; map_dimension=2) + +img = load("examples/Statue_Of_Liberty.png") +img_matrix = Array{Gray}(img) +img_float_matrix = (x -> float(x)).(Float32.(img_matrix)) +data = imresize(img_float_matrix, (2^L, 2^L)) +data = reverse(data; dims=1) + +println("size of matrix: $(size(data))") + +elapsed_time = @elapsed begin + ψ_f, cf = data_itn(s, data; mode="fourier", cutoff=1e-4, max_coeffs=100, by_mag=true) +end +println("constructing ψ_f: ", elapsed_time, " seconds") + +# elapsed_time = @elapsed begin +# ψ_c, cc = data_itn(s, data; mode="chebyshev", cutoff=1e-3, max_coeffs = 100) +# end +# println("constructing ψ_c: ", elapsed_time, " seconds") + +#### Plot Error vs Max Bond Dim + +# bondrange = 1:4:50 +# loss = zeros(length(bondrange)) +# x_vals = grid_points(s, 1) +# y_vals = grid_points(s, 2) +# for (i, bond) in enumerate(bondrange) +# ψ_bond = truncate(ψ_f; maxdim=bond) +# ψ_bond_eval = [ +# real(ITensorNumericalAnalysis.evaluate(ψ_bond, [x, y])) for x in x_vals, y in y_vals +# ] +# loss[i] = eval_L2(data, ψ_bond_eval) +# end + +# plot( +# bondrange, +# loss; +# xlabel="max bond dimension", +# ylabel="L2 error", +# title="64 x 64 statue of liberty image", +# ) + +### Compare images side by side + +ψ_f = truncate(ψ_f; cutoff=1e-16) +# ψ_c = truncate(ψ_c, cutoff=1e-16) + +println("size of coeffs of ψ_f: $(size(cf))") +println("maxlinkdim of ψ_f: $(maxlinkdim(ψ_f))") +# println("size of coeffs of ψ_c: $(size(cc))") +# println("maxlinkdim of ψ_c: $(maxlinkdim(ψ_c))") + +x_vals = grid_points(s, 1) +y_vals = grid_points(s, 2) + +elapsed_time = @elapsed begin + ψ_f_eval = [ + real(ITensorNumericalAnalysis.evaluate(ψ_f, [x, y])) for x in x_vals, y in y_vals + ] +end +println("ψ_f evaluation elapsed time: ", elapsed_time, " seconds") + +# elapsed_time = @elapsed begin +# ψ_c_eval = [ +# real(ITensorNumericalAnalysis.evaluate(ψ_c, [x, y])) for x in x_vals, y in y_vals +# ] +# end +# println("ψ_c evaluation elapsed time: ", elapsed_time, " seconds") + +fourier_loss = eval_L2(data, ψ_f_eval) +# chebyshev_loss = eval_L2(data, ψ_c_eval) +println("fourier L2 error: $fourier_loss") +# println("chebyshev L2 error: $chebyshev_loss") + +plot1 = heatmap(x_vals, y_vals, data; title="true image") +plot2 = heatmap(x_vals, y_vals, ψ_f_eval; title="fourier TN") #fourier TN approximation +# plot3 = heatmap(x_vals, y_vals, ψ_c_eval; title="chebyshev TN") + +combined = plot(plot1, plot2; layout=(1, 2), size=(700, 280)) diff --git a/src/ITensorNumericalAnalysis.jl b/src/ITensorNumericalAnalysis.jl index 35af0ec..9c48e4f 100644 --- a/src/ITensorNumericalAnalysis.jl +++ b/src/ITensorNumericalAnalysis.jl @@ -8,6 +8,7 @@ include("itensornetworkfunction.jl") include("elementary_functions.jl") include("elementary_operators.jl") include("integration.jl") +include("interpolation_functions.jl") export continuous_siteinds export ITensorNetworkFunction, itensornetwork, dimension_vertices @@ -48,8 +49,21 @@ export const_itensornetwork, map_to_zero_operator, map_to_zeros, const_plane_op +export fourier_itensornetwork, + chebyshev_itensornetwork, function_itensornetwork, data_itensornetwork export const_itn, - poly_itn, cosh_itn, sinh_itn, tanh_itn, exp_itn, sin_itn, cos_itn, rand_itn + poly_itn, + cosh_itn, + sinh_itn, + tanh_itn, + exp_itn, + sin_itn, + cos_itn, + rand_itn, + fourier_itn, + chebyshev_itn, + function_itn, + data_itn export evaluate export operate, operator_proj, multiply diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl new file mode 100644 index 0000000..4443b4b --- /dev/null +++ b/src/interpolation_functions.jl @@ -0,0 +1,308 @@ +using ApproxFun: + Interval, Fourier, Chebyshev, Fun, ProductFun, coefficients, chop, ncoefficients +using Interpolations: LinearInterpolation, Line + +default_dimension() = 1 + +""" Helper function for fourier_itensornetwork and fourier_2D_itensornetwork """ +function fourier_term(s::IndsNetworkMap, j::Integer, d::Integer) + if j == 1 + return const_itn(s) + elseif j % 2 == 0 + return sin_itn(s; k=j * π, dim=d) + else + return cos_itn(s; k=(j - 1) * π, dim=d) + end +end + +""" Build the function f(x) = coeffs[1] + ∑_{k=1}^{n} coeffs[2k]*sin(2kπx) + + ∑_{k=1}^{n} coeffs[2k+1]*cos(2kπx) """ +function fourier_itensornetwork( + s::IndsNetworkMap, + coeffs::Vector{Float64}; + dim::Int=default_dimension(), + min_threshold=1e-15, +) + n = length(coeffs) + if n < 1 + throw("coeffs must be nonempty") + end + + ψ = coeffs[1] * const_itn(s) + for i in 2:n + if abs(coeffs[i]) > min_threshold + ψ += coeffs[i] * fourier_term(s, i, dim) + ψ = truncate(ψ; cutoff=1e-16) + end + end + return ψ +end + +""" Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are sines/cosines. """ +function fourier_2D_itensornetwork( + s::IndsNetworkMap, coeffs::Matrix{Float64}; dims::Vector{Int}=[1, 2], min_threshold=1e-15 +) + n = size(coeffs)[1] + m = size(coeffs)[2] + if n < 1 || m < 1 + throw("coeffs must be nonempty") + end + + ψ = const_itn(s; c=0) + for j in 1:n + for k in 1:m + if abs(coeffs[j, k]) > min_threshold + ψ += coeffs[j, k] * fourier_term(s, j, dims[1]) * fourier_term(s, k, dims[2]) + ψ = truncate(ψ; cutoff=1e-16) + end + end + end + return ψ +end + +""" Build the function f(x) = ∑_{k=1}^n coeffs[k] * T_k(x) + where T_k(x) is the k-th Chebyshev polynomial """ +function chebyshev_itensornetwork( + s::IndsNetworkMap, coeffs::Vector{Float64}; dim::Int=default_dimension() +) + n = length(coeffs) + if n <= 0 + throw("coeffs must be nonempty") + elseif n == 1 + return coeffs[1] * const_itensornetwork(s) + end + + # Converts a polynomial in chebyshev basis to its standard polynomial form + Tn_minus_one = [1.0; zeros(n - 1)] # T_0 = 1 + Tn = [[-1.0, 2.0]; zeros(n - 2)] # T_1 = 2x-1 + std_coeffs = zeros(n) + std_coeffs += coeffs[1] * Tn_minus_one + std_coeffs += coeffs[2] * Tn + for i in 3:n + #recurrence relation: T_{n+1} = (4x-2)*T_n - T_{n-1} + Tn_plus_one = circshift(Tn, 1) * 4.0 - Tn * 2.0 - Tn_minus_one + Tn_minus_one = Tn + Tn = Tn_plus_one + std_coeffs += coeffs[i] * Tn + end + return polynomial_itensornetwork(s, std_coeffs; dim=dim) +end + +""" helper function for chebyshev_2D_itensornetwork """ +function cheb_term(s::IndsNetworkMap, k::Integer, d::Integer) + Tn_minus_one = [1.0] # T_0 = 1 + Tn = [-1.0, 2.0] # T_1 = 2x-1 + if k == 1 + return const_itensornetwork(s) + elseif k == 2 + return polynomial_itensornetwork(s, Tn; dim=d) + else + #generate the k-th chebyshev coefficients + for i in 3:k + Tn_plus_one = [0.0; Tn] * 4.0 + for j in 1:length(Tn_minus_one) + Tn_plus_one[j] -= Tn_minus_one[j] + end + for j in 1:length(Tn) + Tn_plus_one[j] -= 2 * Tn[j] + end + Tn_minus_one = Tn + Tn = Tn_plus_one + end + return polynomial_itensornetwork(s, Tn; dim=d) + end +end + +""" Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are chebyshev polynomials """ +function chebyshev_2D_itensornetwork( + s::IndsNetworkMap, coeffs::Matrix{Float64}; dims::Vector{Int}=[1, 2], min_threshold=1e-15 +) + n = size(coeffs)[1] + m = size(coeffs)[2] + if n < 1 || m < 1 + throw("coeffs must be nonempty") + end + + ψ = const_itn(s; c=0) + for j in 1:n + for k in 1:m + if abs(coeffs[j, k]) > min_threshold + ψ += coeffs[j, k] * cheb_term(s, j, dims[1]) * cheb_term(s, k, dims[2]) + ψ = truncate(ψ; cutoff=1e-16) + end + end + end + return ψ +end + +""" Helper function for function_itensornetwork (1D case) """ +function greatest_n(coeffs, n) + if n < 1 + throw("n must be greater than 0") + end + sorted_indices = sortperm(coeffs; by=abs, rev=true) + top_n_indices = sorted_indices[1:min(n, length(coeffs))] + output = zeros(eltype(coeffs), length(coeffs)) + output[top_n_indices] = coeffs[top_n_indices] + last_non_zero = findlast(output .!= 0) + if isempty(last_non_zero) + return [] + end + return output[1:last_non_zero] +end + +""" Helper function for function_itensornetwork (2D case) """ +function greatest_n_2d(coeffs_matrix, n) + if n < 1 + throw("n must be greater than 0") + end + dims = size(coeffs_matrix) + coeffs = vec(coeffs_matrix) + sorted_indices = sortperm(coeffs; by=abs, rev=true) + top_n_indices = sorted_indices[1:min(n, length(coeffs))] + output = zeros(eltype(coeffs), length(coeffs)) + output[top_n_indices] = coeffs[top_n_indices] + matrix = reshape(output, dims) + last_row, last_col = size(matrix) + while last_row > 0 && all(matrix[last_row, :] .== 0) + last_row -= 1 + end + while last_col > 0 && all(matrix[:, last_col] .== 0) + last_col -= 1 + end + return matrix[1:last_row, 1:last_col] +end + +""" + function_itensornetwork(s,f, cutoff=1e-3, max_coeffs=100, mode="fourier", by_mag=true) + Takes in a function `f` as a black box, outputs a tensor network approximation using Fourier or Chebyshev series. Supports 1D or 2D functions. + + #Arguments + - `s`: IndsNetworkMap + - `f`: a real-valued function on domain [0,1] or [0,1]⊗[0,1] which can be given as a black box + - `cutoff`: (default=1e-3) specifies at what value should the fourier/chebyshev coefficients be truncated below + - `max_coeffs`: the maximum number of coefficients allowed + - `mode`: ["fourier", "chebyshev"] "fourier" uses a fourier basis and "chebyshev" uses a chebyshev polynomial basis + - `by_mag`: boolean. if false, will use the `max_coeffs` coefficients of lowest degree. if true, will use the `max_coeffs` coefficients of greatest absolute magnitude. +""" +function function_itensornetwork( + s::IndsNetworkMap, + f::Function; + cutoff::Float64=1e-3, + max_coeffs::Integer=100, + mode="fourier", + by_mag=true, +) + + #get the number of inputs to f + method_list = methods(f).ms + arg_counts = [length(m.sig.parameters) - 1 for m in method_list] + num_inputs = arg_counts[1] + + """ 1D functions """ + if num_inputs == 1 + domain = Interval(0.0, 1.0) + if mode == "fourier" + S = Fourier(domain) + f_fourier = Fun(f, S) + a = chop(f_fourier, cutoff) + if by_mag + cf = greatest_n(coefficients(a), max_coeffs) + else + cf = ncoefficients(a) > max_coeffs ? coefficients(a)[1:max_coeffs] : coefficients(a) + end + ψ = fourier_itensornetwork(s, cf) + elseif mode == "chebyshev" + T = Chebyshev(domain) + f_chebyshev = Fun(f, T) + a = chop(f_chebyshev, cutoff) + if by_mag + cf = greatest_n(coefficients(a), max_coeffs) + else + cf = ncoefficients(a) > max_coeffs ? coefficients(a)[1:max_coeffs] : coefficients(a) + end + ψ = chebyshev_itensornetwork(s, cf) + else + throw("mode $mode not recognized") + end + return ψ, cf + + """ 2D functions """ + elseif num_inputs == 2 + domain = Interval(0.0, 1.0) + if mode == "fourier" + S = Fourier(domain)^2 + f_fourier = ProductFun(f, S; tol=cutoff) + if by_mag + cf = greatest_n_2d(coefficients(f_fourier), max_coeffs) + else + D = Int(floor(sqrt(max_coeffs))) + a = min(D, size(coefficients(f_fourier))[1]) + b = min(D, size(coefficients(f_fourier))[2]) + cf = coefficients(f_fourier)[1:a, 1:b] + end + ψ = fourier_2D_itensornetwork(s, cf; dims=[1, 2]) + elseif mode == "chebyshev" + T = Chebyshev(domain)^2 + f_chebyshev = ProductFun(f, T; tol=cutoff) + if by_mag + cf = greatest_n_2d(coefficients(f_chebyshev), max_coeffs) + else + D = Int(floor(sqrt(max_coeffs))) + a = min(D, size(coefficients(f_chebyshev))[1]) + b = min(D, size(coefficients(f_chebyshev))[2]) + cf = coefficients(f_chebyshev)[1:a, 1:b] + end + ψ = chebyshev_2D_itensornetwork(s, cf; dims=[1, 2]) + else + throw("mode $mode not recognized") + end + return ψ, cf + else + throw("functions with $num_inputs inputs not supported.") + end +end + +""" + data_itensornetwork converts a list of numerical datapoints into an ITN by first converting it into a function. Can be 1D or 2D data. + + #Arguments + - `s`: IndsNetworkMap + - `data`: a real-valued vector or matrix of data points + - `eval_pts`: optional, where the data is located. by default it will the data as evenly spaced over [0,1] or [0,1]⊗[0,1], depending on dimension of the data. + - other kwargs are inherited from `function_itensornetwork` + +""" +function data_itensornetwork(s::IndsNetworkMap, data, eval_pts=nothing; kwargs...) + dimensionality = length(size(data)) + + if dimensionality == 1 + #if no eval_pts are given, assumes that the data is evenly spaced across [0,1] + if eval_pts == nothing + eval_pts = grid_points(s, length(data), 1; exact_grid=false) + end + if length(eval_pts) != length(data) + throw("length of data and eval_pts do not match!") + end + f = LinearInterpolation(eval_pts, data; extrapolation_bc=Line()) + g = (x) -> f(x) #make a function g that is defined as f + return function_itensornetwork(s, g; kwargs...) + elseif dimensionality == 2 + if eval_pts == nothing + eval_pts_x = grid_points(s, size(data)[1], 1; exact_grid=false) + eval_pts_y = grid_points(s, size(data)[2], 2; exact_grid=false) + eval_pts = (eval_pts_x, eval_pts_y) + end + if length(eval_pts[1]) * length(eval_pts[2]) != length(data) + throw("length of data and eval_pts do not match!") + end + f = LinearInterpolation(eval_pts, data; extrapolation_bc=Line()) + g = (x, y) -> f(x, y) #make a function g that is defined identically to f + return function_itensornetwork(s, g; kwargs...) + end +end + +const fourier_itn = fourier_itensornetwork +const chebyshev_itn = chebyshev_itensornetwork +const function_itn = function_itensornetwork +const data_itn = data_itensornetwork diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index df998df..eb73a8f 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -92,7 +92,7 @@ using Random: Random rand_gridpoint1 = rand_p(rng, s) rand_gridpoint2 = rand_p(rng, s, 1) default_rng_gridpoint1 = rand_p(s) - default_rng_gridpoint2 = rand_p(s,1) + default_rng_gridpoint2 = rand_p(s, 1) #fourth set -- very large L L = 140 From ec1333a585a15d28c8daa8b455ce4cacdcba58f5 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Wed, 26 Jun 2024 10:17:15 -0400 Subject: [PATCH 05/31] get rid of warning about redefining default_dimension() --- src/interpolation_functions.jl | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl index 4443b4b..6e28d8c 100644 --- a/src/interpolation_functions.jl +++ b/src/interpolation_functions.jl @@ -2,8 +2,6 @@ using ApproxFun: Interval, Fourier, Chebyshev, Fun, ProductFun, coefficients, chop, ncoefficients using Interpolations: LinearInterpolation, Line -default_dimension() = 1 - """ Helper function for fourier_itensornetwork and fourier_2D_itensornetwork """ function fourier_term(s::IndsNetworkMap, j::Integer, d::Integer) if j == 1 @@ -20,7 +18,7 @@ end function fourier_itensornetwork( s::IndsNetworkMap, coeffs::Vector{Float64}; - dim::Int=default_dimension(), + dim::Int=1, min_threshold=1e-15, ) n = length(coeffs) @@ -63,7 +61,7 @@ end """ Build the function f(x) = ∑_{k=1}^n coeffs[k] * T_k(x) where T_k(x) is the k-th Chebyshev polynomial """ function chebyshev_itensornetwork( - s::IndsNetworkMap, coeffs::Vector{Float64}; dim::Int=default_dimension() + s::IndsNetworkMap, coeffs::Vector{Float64}; dim::Int=1 ) n = length(coeffs) if n <= 0 From 3a966d4368346410e26f83f0dbd9d8ec11edb803 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Thu, 18 Jul 2024 20:28:29 -0400 Subject: [PATCH 06/31] update interpolation functions to take complex coefficients --- src/interpolation_functions.jl | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl index 6e28d8c..ba51c6c 100644 --- a/src/interpolation_functions.jl +++ b/src/interpolation_functions.jl @@ -17,7 +17,7 @@ end + ∑_{k=1}^{n} coeffs[2k+1]*cos(2kπx) """ function fourier_itensornetwork( s::IndsNetworkMap, - coeffs::Vector{Float64}; + coeffs::Vector{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dim::Int=1, min_threshold=1e-15, ) @@ -38,7 +38,7 @@ end """ Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are sines/cosines. """ function fourier_2D_itensornetwork( - s::IndsNetworkMap, coeffs::Matrix{Float64}; dims::Vector{Int}=[1, 2], min_threshold=1e-15 + s::IndsNetworkMap, coeffs::Matrix{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dims::Vector{Int}=[1, 2], min_threshold=1e-15 ) n = size(coeffs)[1] m = size(coeffs)[2] @@ -61,7 +61,7 @@ end """ Build the function f(x) = ∑_{k=1}^n coeffs[k] * T_k(x) where T_k(x) is the k-th Chebyshev polynomial """ function chebyshev_itensornetwork( - s::IndsNetworkMap, coeffs::Vector{Float64}; dim::Int=1 + s::IndsNetworkMap, coeffs::Vector{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dim::Int=1 ) n = length(coeffs) if n <= 0 @@ -113,7 +113,7 @@ end """ Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are chebyshev polynomials """ function chebyshev_2D_itensornetwork( - s::IndsNetworkMap, coeffs::Matrix{Float64}; dims::Vector{Int}=[1, 2], min_threshold=1e-15 + s::IndsNetworkMap, coeffs::Matrix{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dims::Vector{Int}=[1, 2], min_threshold=1e-15 ) n = size(coeffs)[1] m = size(coeffs)[2] From e4504b9e9688bff068c52c849b1ecc09629555d5 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Fri, 19 Jul 2024 08:46:16 -0400 Subject: [PATCH 07/31] remove coeffs as an output of function_itn --- src/interpolation_functions.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl index ba51c6c..04b00a9 100644 --- a/src/interpolation_functions.jl +++ b/src/interpolation_functions.jl @@ -223,7 +223,7 @@ function function_itensornetwork( else throw("mode $mode not recognized") end - return ψ, cf + return ψ """ 2D functions """ elseif num_inputs == 2 @@ -255,7 +255,7 @@ function function_itensornetwork( else throw("mode $mode not recognized") end - return ψ, cf + return ψ else throw("functions with $num_inputs inputs not supported.") end From 78e4eeae7f7f16524db5524e7d850bc65f1899f8 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Fri, 19 Jul 2024 08:49:39 -0400 Subject: [PATCH 08/31] remove coefficients output from examples --- examples/1D_data_into_ITN.jl | 6 +----- examples/1D_function_into_ITN.jl | 15 +++++++-------- examples/2D_data_into_ITN.jl | 6 ++---- examples/2D_function_into_ITN.jl | 4 ++-- examples/image_into_ITN.jl | 5 ++--- 5 files changed, 14 insertions(+), 22 deletions(-) diff --git a/examples/1D_data_into_ITN.jl b/examples/1D_data_into_ITN.jl index d8f2d65..8dcce5f 100644 --- a/examples/1D_data_into_ITN.jl +++ b/examples/1D_data_into_ITN.jl @@ -30,7 +30,7 @@ x_vals = [collect(range(0.0, 0.5; length=50)); collect(range(0.51, 1.0; length=5 data = [f(x) + noise_level * randn() for x in x_vals] ### Plot one result -ψ_f, cf = data_itn(s, data, x_vals; mode="fourier", cutoff=1e-3, max_coeffs=300) +ψ_f = data_itn(s, data, x_vals; mode="fourier", cutoff=1e-3, max_coeffs=300) println("length of coeffs vector: $(length(cf))") ψ_f = truncate(ψ_f; cutoff=1e-10) x_vals_ψ = grid_points(s, 1) @@ -43,10 +43,6 @@ end plot1 = plot(x_vals, data; label="true data") plot!(x_vals_ψ, f_vals; label="fourier approx") -#""" Plotting Log of Fourier coefficient vs coefficient number """ -# plot2 = plot(1:length(cf), log10.(abs.(cf)), xlabel="k",ylabel="log|f_k|", title="fourier spectrum of noise") -# display(plot2) - ### Plot of error vs # terms # max_terms = 201 # eval_range = 1:10:max_terms diff --git a/examples/1D_function_into_ITN.jl b/examples/1D_function_into_ITN.jl index c9e41ac..b2dd8de 100644 --- a/examples/1D_function_into_ITN.jl +++ b/examples/1D_function_into_ITN.jl @@ -88,13 +88,12 @@ fourier_max = 100 cheb_cut = 1e-3 fourier_cut = 1e-3 -ψ_c, cc = function_itn( +ψ_c = function_itn( s, f; cutoff=cheb_cut, max_coeffs=cheb_max, mode="chebyshev", by_mag=false ) -ψ_f, cf = function_itn(s, f; cutoff=fourier_cut, max_coeffs=fourier_max, mode="fourier") +ψ_f = function_itn(s, f; cutoff=fourier_cut, max_coeffs=fourier_max, mode="fourier") + -n_c = length(cc) -n_f = length(cf) println("truncating...") ψ_c = truncate(ψ_c; cutoff=1e-10) @@ -120,8 +119,8 @@ true_vals = [f(x) for x in x_vals] println("Plotting f(x)") plot(x_vals, true_vals; label="true function", title="f(x)") -plot!(x_vals, f_vals; label="Fourier w/ $n_f terms") -plot!(x_vals, c_vals; label="Chebyshev w/ $n_c terms") +plot!(x_vals, f_vals; label="Fourier ") +plot!(x_vals, c_vals; label="Chebyshev") ### Plots of Loss vs # terms and Maxlinkdim vs # terms @@ -139,8 +138,8 @@ plot!(x_vals, c_vals; label="Chebyshev w/ $n_c terms") # for (j, i) in enumerate(eval_range) # println("$i terms") -# local ψ_c, n_c = function_itn(s, f; cutoff=1e-10, max_coeffs=i, mode="chebyshev") -# local ψ_f, n_f = function_itn(s, f; cutoff=1e-10, max_coeffs=i, mode="fourier") +# local ψ_c = function_itn(s, f; cutoff=1e-10, max_coeffs=i, mode="chebyshev") +# local ψ_f = function_itn(s, f; cutoff=1e-10, max_coeffs=i, mode="fourier") # ψ_c = truncate(ψ_c; cutoff=1e-10) # ψ_f = truncate(ψ_f; cutoff=1e-10) diff --git a/examples/2D_data_into_ITN.jl b/examples/2D_data_into_ITN.jl index d221344..715703b 100644 --- a/examples/2D_data_into_ITN.jl +++ b/examples/2D_data_into_ITN.jl @@ -43,23 +43,21 @@ noise_level = 0.0 data = [f(x, y) + noise_level * randn() for x in xrange, y in yrange] elapsed_time = @elapsed begin - ψ_f, cf = data_itn(s, data, (xrange, yrange); mode="fourier", cutoff=1e-3, max_coeffs=20) + ψ_f = data_itn(s, data, (xrange, yrange); mode="fourier", cutoff=1e-3, max_coeffs=20) end println("ψ_f time: ", elapsed_time) elapsed_time = @elapsed begin - ψ_c, cc = data_itn( + ψ_c = data_itn( s, data, (xrange, yrange); mode="chebyshev", cutoff=1e-3, max_coeffs=20, by_mag=false ) end println("ψ_c time: ", elapsed_time) ψ_f = truncate(ψ_f; cutoff=1e-10) -println("size of ψ_f coeffs: $(size(cf))") println("maxlinkdim of ψ_f after truncation: $(maxlinkdim(ψ_f))") ψ_c = truncate(ψ_c; cutoff=1e-10) -println("size of ψ_c coeffs: $(size(cc))") println("maxlinkdim of ψ_c after truncation: $(maxlinkdim(ψ_c))") x_vals = grid_points(s, 1) diff --git a/examples/2D_function_into_ITN.jl b/examples/2D_function_into_ITN.jl index a08666e..3958f37 100644 --- a/examples/2D_function_into_ITN.jl +++ b/examples/2D_function_into_ITN.jl @@ -37,8 +37,8 @@ f(x, y) = exp(-((x - 0.5)^2 + (y - 0.5)^2) / 0.05) #f(x, y) = exp(x) - exp(y) #f(x, y) = cos(20 * (x + y)) + sin(50 * (x - y)) -ψ_f, cf = function_itn(s, f; mode="fourier", cutoff=1e-3, max_coeffs=100) -ψ_c, cc = function_itn(s, f; mode="chebyshev", cutoff=1e-2, max_coeffs=36, by_mag=false) +ψ_f = function_itn(s, f; mode="fourier", cutoff=1e-3, max_coeffs=100) +ψ_c = function_itn(s, f; mode="chebyshev", cutoff=1e-2, max_coeffs=36, by_mag=false) println("maxlinkdim of ψ_f after truncation: $(maxlinkdim(ψ_f))") println("maxlinkdim of ψ_c after truncation: $(maxlinkdim(ψ_c))") diff --git a/examples/image_into_ITN.jl b/examples/image_into_ITN.jl index 6913484..2a5bbcc 100644 --- a/examples/image_into_ITN.jl +++ b/examples/image_into_ITN.jl @@ -28,12 +28,12 @@ data = reverse(data; dims=1) println("size of matrix: $(size(data))") elapsed_time = @elapsed begin - ψ_f, cf = data_itn(s, data; mode="fourier", cutoff=1e-4, max_coeffs=100, by_mag=true) + ψ_f = data_itn(s, data; mode="fourier", cutoff=1e-4, max_coeffs=100, by_mag=true) end println("constructing ψ_f: ", elapsed_time, " seconds") # elapsed_time = @elapsed begin -# ψ_c, cc = data_itn(s, data; mode="chebyshev", cutoff=1e-3, max_coeffs = 100) +# ψ_c = data_itn(s, data; mode="chebyshev", cutoff=1e-3, max_coeffs = 100) # end # println("constructing ψ_c: ", elapsed_time, " seconds") @@ -64,7 +64,6 @@ println("constructing ψ_f: ", elapsed_time, " seconds") ψ_f = truncate(ψ_f; cutoff=1e-16) # ψ_c = truncate(ψ_c, cutoff=1e-16) -println("size of coeffs of ψ_f: $(size(cf))") println("maxlinkdim of ψ_f: $(maxlinkdim(ψ_f))") # println("size of coeffs of ψ_c: $(size(cc))") # println("maxlinkdim of ψ_c: $(maxlinkdim(ψ_c))") From 58a789a11f5d64433f0e6312065d6517026c73cb Mon Sep 17 00:00:00 2001 From: Ryan Anselm <31040739+ryboselm@users.noreply.github.com> Date: Fri, 26 Jul 2024 10:02:04 -0400 Subject: [PATCH 09/31] added clenshaw interpolation (#5) * added clenshaw interpolation * update how max_coeffs works * add attribution and rename vars --- examples/1D_function_into_ITN.jl | 46 ++++++------ examples/2D_function_into_ITN.jl | 7 +- examples/image_into_ITN.jl | 7 +- src/interpolation_functions.jl | 125 ++++++++++++++----------------- 4 files changed, 85 insertions(+), 100 deletions(-) diff --git a/examples/1D_function_into_ITN.jl b/examples/1D_function_into_ITN.jl index b2dd8de..cdb6093 100644 --- a/examples/1D_function_into_ITN.jl +++ b/examples/1D_function_into_ITN.jl @@ -10,7 +10,7 @@ using Plots Random.seed!(1234) -L = 10 +L = 8 #comb tree g = named_comb_tree((1, L)) @@ -54,43 +54,41 @@ end ### Potential functions to choose from #piecewise function -#f(x) = x < 0.75 ? x < 0.25 ? 0 : sin(4π * (x - 0.25)) : 0 + f(x) = x < 0.75 ? x < 0.25 ? 0 : sin(4π * (x - 0.25)) : 0 #gaussian #f(x) = exp(-(x - 0.5)^2 / 0.01) #almost 1/x function. this breaks it if the cutoff is not fairly large/max_coeffs fairly small -# f(x) = 1/(.01+x) + 5*x^2 +#f(x) = 1/(.01+x) + 5*x^2 #f(x) = sin(1/(.01+x)) #f(x) = cos(π*x) + 5*x -#f(x) = sin(20*x^(1/7)) +# f(x) = sin(20*x^(1/7)) + -# # Sum of random Gaussians -# -Ng = 40 -ω = 0.001 -ws = [ω * rand() for n in 1:Ng] -xs = [rand() for n in 1:Ng] -hs = [randn() for n in 1:Ng] -step_size = 2.5 * rand() -step_location = 0.4 -function f(x::Number) - val = sum(g -> hs[g] * exp(-(x[1] - xs[g])^2 / ws[g]), 1:Ng) - val += (x[1] > step_location) ? step_size : 0.0 - return val -end + +# Ng = 40 +# ω = 0.001 +# ws = [ω * rand() for n in 1:Ng] +# xs = [rand() for n in 1:Ng] +# hs = [randn() for n in 1:Ng] +# step_size = 2.5 * rand() +# step_location = 0.4 +# function f(x::Number) +# val = sum(g -> hs[g] * exp(-(x[1] - xs[g])^2 / ws[g]), 1:Ng) +# val += (x[1] > step_location) ? step_size : 0.0 +# return val +# end ### Plotting f(x) vs ITN encodings using Fourier or Chebyshev decompositions -cheb_max = 25 +cheb_max = 100 fourier_max = 100 -cheb_cut = 1e-3 -fourier_cut = 1e-3 +cheb_cut = 1e-4 +fourier_cut = 1e-4 -ψ_c = function_itn( - s, f; cutoff=cheb_cut, max_coeffs=cheb_max, mode="chebyshev", by_mag=false -) +ψ_c = function_itn(s, f; cutoff=cheb_cut, max_coeffs=cheb_max, mode="chebyshev") ψ_f = function_itn(s, f; cutoff=fourier_cut, max_coeffs=fourier_max, mode="fourier") diff --git a/examples/2D_function_into_ITN.jl b/examples/2D_function_into_ITN.jl index 3958f37..51a87c0 100644 --- a/examples/2D_function_into_ITN.jl +++ b/examples/2D_function_into_ITN.jl @@ -37,8 +37,11 @@ f(x, y) = exp(-((x - 0.5)^2 + (y - 0.5)^2) / 0.05) #f(x, y) = exp(x) - exp(y) #f(x, y) = cos(20 * (x + y)) + sin(50 * (x - y)) -ψ_f = function_itn(s, f; mode="fourier", cutoff=1e-3, max_coeffs=100) -ψ_c = function_itn(s, f; mode="chebyshev", cutoff=1e-2, max_coeffs=36, by_mag=false) +ψ_f = function_itn(s, f; mode="fourier", cutoff=1e-3, max_coeffs=400, by_mag=true) +ψ_c = function_itn(s, f; mode="chebyshev", cutoff=1e-3, max_coeffs=400, by_mag=true) + +ψ_f = truncate(ψ_f; cutoff=1e-16) +ψ_c = truncate(ψ_c; cutoff=1e-16) println("maxlinkdim of ψ_f after truncation: $(maxlinkdim(ψ_f))") println("maxlinkdim of ψ_c after truncation: $(maxlinkdim(ψ_c))") diff --git a/examples/image_into_ITN.jl b/examples/image_into_ITN.jl index 2a5bbcc..d1911b8 100644 --- a/examples/image_into_ITN.jl +++ b/examples/image_into_ITN.jl @@ -28,12 +28,12 @@ data = reverse(data; dims=1) println("size of matrix: $(size(data))") elapsed_time = @elapsed begin - ψ_f = data_itn(s, data; mode="fourier", cutoff=1e-4, max_coeffs=100, by_mag=true) + ψ_f = data_itn(s, data; mode="fourier", cutoff=1e-4, max_coeffs=30) end println("constructing ψ_f: ", elapsed_time, " seconds") # elapsed_time = @elapsed begin -# ψ_c = data_itn(s, data; mode="chebyshev", cutoff=1e-3, max_coeffs = 100) +# ψ_c = data_itn(s, data; mode="chebyshev", cutoff=1e-3, max_coeffs = 30) # end # println("constructing ψ_c: ", elapsed_time, " seconds") @@ -65,7 +65,6 @@ println("constructing ψ_f: ", elapsed_time, " seconds") # ψ_c = truncate(ψ_c, cutoff=1e-16) println("maxlinkdim of ψ_f: $(maxlinkdim(ψ_f))") -# println("size of coeffs of ψ_c: $(size(cc))") # println("maxlinkdim of ψ_c: $(maxlinkdim(ψ_c))") x_vals = grid_points(s, 1) @@ -91,7 +90,7 @@ println("fourier L2 error: $fourier_loss") # println("chebyshev L2 error: $chebyshev_loss") plot1 = heatmap(x_vals, y_vals, data; title="true image") -plot2 = heatmap(x_vals, y_vals, ψ_f_eval; title="fourier TN") #fourier TN approximation +plot2 = heatmap(x_vals, y_vals, ψ_f_eval; title="cheb TN") #fourier TN approximation # plot3 = heatmap(x_vals, y_vals, ψ_c_eval; title="chebyshev TN") combined = plot(plot1, plot2; layout=(1, 2), size=(700, 280)) diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl index 04b00a9..b7bf709 100644 --- a/src/interpolation_functions.jl +++ b/src/interpolation_functions.jl @@ -20,6 +20,7 @@ function fourier_itensornetwork( coeffs::Vector{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dim::Int=1, min_threshold=1e-15, + cutoff=1e-16 ) n = length(coeffs) if n < 1 @@ -30,7 +31,7 @@ function fourier_itensornetwork( for i in 2:n if abs(coeffs[i]) > min_threshold ψ += coeffs[i] * fourier_term(s, i, dim) - ψ = truncate(ψ; cutoff=1e-16) + ψ = truncate(ψ; cutoff) end end return ψ @@ -38,7 +39,7 @@ end """ Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are sines/cosines. """ function fourier_2D_itensornetwork( - s::IndsNetworkMap, coeffs::Matrix{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dims::Vector{Int}=[1, 2], min_threshold=1e-15 + s::IndsNetworkMap, coeffs::Matrix{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dims::Vector{Int}=[1, 2], min_threshold=1e-15, cutoff=1e-16 ) n = size(coeffs)[1] m = size(coeffs)[2] @@ -51,7 +52,7 @@ function fourier_2D_itensornetwork( for k in 1:m if abs(coeffs[j, k]) > min_threshold ψ += coeffs[j, k] * fourier_term(s, j, dims[1]) * fourier_term(s, k, dims[2]) - ψ = truncate(ψ; cutoff=1e-16) + ψ = truncate(ψ; cutoff) end end end @@ -59,78 +60,64 @@ function fourier_2D_itensornetwork( end """ Build the function f(x) = ∑_{k=1}^n coeffs[k] * T_k(x) - where T_k(x) is the k-th Chebyshev polynomial """ + where T_k(x) is the k-th Chebyshev polynomial. """ function chebyshev_itensornetwork( - s::IndsNetworkMap, coeffs::Vector{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dim::Int=1 + s::IndsNetworkMap, coeffs::Vector{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dim::Int=1, cutoff=1e-16 ) n = length(coeffs) if n <= 0 throw("coeffs must be nonempty") elseif n == 1 - return coeffs[1] * const_itensornetwork(s) + return coeffs[1] * const_itn(s) end - # Converts a polynomial in chebyshev basis to its standard polynomial form - Tn_minus_one = [1.0; zeros(n - 1)] # T_0 = 1 - Tn = [[-1.0, 2.0]; zeros(n - 2)] # T_1 = 2x-1 - std_coeffs = zeros(n) - std_coeffs += coeffs[1] * Tn_minus_one - std_coeffs += coeffs[2] * Tn - for i in 3:n - #recurrence relation: T_{n+1} = (4x-2)*T_n - T_{n-1} - Tn_plus_one = circshift(Tn, 1) * 4.0 - Tn * 2.0 - Tn_minus_one - Tn_minus_one = Tn - Tn = Tn_plus_one - std_coeffs += coeffs[i] * Tn - end - return polynomial_itensornetwork(s, std_coeffs; dim=dim) -end + #Clenshaw Evaluation method - uses idea from https://arxiv.org/pdf/2407.09609 + y_n = const_itn(s; c = 0) + y_n1 = const_itn(s; c = 0) -""" helper function for chebyshev_2D_itensornetwork """ -function cheb_term(s::IndsNetworkMap, k::Integer, d::Integer) - Tn_minus_one = [1.0] # T_0 = 1 - Tn = [-1.0, 2.0] # T_1 = 2x-1 - if k == 1 - return const_itensornetwork(s) - elseif k == 2 - return polynomial_itensornetwork(s, Tn; dim=d) - else - #generate the k-th chebyshev coefficients - for i in 3:k - Tn_plus_one = [0.0; Tn] * 4.0 - for j in 1:length(Tn_minus_one) - Tn_plus_one[j] -= Tn_minus_one[j] - end - for j in 1:length(Tn) - Tn_plus_one[j] -= 2 * Tn[j] - end - Tn_minus_one = Tn - Tn = Tn_plus_one - end - return polynomial_itensornetwork(s, Tn; dim=d) + # y_n-1 = c_n-1 - y_n+1 + (4x-2) * y_n + for d in n:-1:1 + old_y_n = truncate(y_n; cutoff) + y_n = coeffs[d] * const_itn(s) + (-1) * y_n1 + poly_itn(s, [-2, 4]; dim) * old_y_n + y_n1 = old_y_n end + + return truncate(y_n + poly_itn(s, [1,-2]; dim) * y_n1; cutoff) end """ Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are chebyshev polynomials """ function chebyshev_2D_itensornetwork( - s::IndsNetworkMap, coeffs::Matrix{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dims::Vector{Int}=[1, 2], min_threshold=1e-15 + s::IndsNetworkMap, coeffs::Matrix{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dims::Vector{Int}=[1, 2], cutoff=1e-16 ) n = size(coeffs)[1] m = size(coeffs)[2] if n < 1 || m < 1 throw("coeffs must be nonempty") end + + #Clenshaw Evaluation method - uses idea from https://arxiv.org/pdf/2407.09609 + y_n = const_itn(s; c = 0) + y_n1 = const_itn(s; c = 0) - ψ = const_itn(s; c=0) - for j in 1:n - for k in 1:m - if abs(coeffs[j, k]) > min_threshold - ψ += coeffs[j, k] * cheb_term(s, j, dims[1]) * cheb_term(s, k, dims[2]) - ψ = truncate(ψ; cutoff=1e-16) - end + for j in m:-1:1 + #determine the weighted sum of chebyshev polynomials of x + x_n = const_itn(s; c = 0) + x_n1 = const_itn(s; c = 0) + for i in n:-1:1 + # x_n-1 = c_n-1 - x_n+1 + (4x-2) * x_n + old_x_n = truncate(x_n; cutoff) + x_n = coeffs[i,j] * const_itn(s) + (-1) * x_n1 + poly_itn(s, [-2, 4]; dim=dims[1]) * old_x_n + x_n1 = old_x_n end + coeff_j = truncate(x_n + poly_itn(s, [1,-2]; dim=dims[1]) * x_n1; cutoff) + + # y_n-1 = c_n-1 - y_n+1 + (4y-2) * y_n + old_y_n = truncate(y_n; cutoff) + y_n = coeff_j + (-1)*y_n1 + poly_itn(s, [-2, 4]; dim=dims[2]) * old_y_n + y_n1 = old_y_n end - return ψ + + return truncate(y_n + poly_itn(s, [1,-2]; dim=dims[2]) * y_n1; cutoff) end """ Helper function for function_itensornetwork (1D case) """ @@ -179,9 +166,10 @@ end - `s`: IndsNetworkMap - `f`: a real-valued function on domain [0,1] or [0,1]⊗[0,1] which can be given as a black box - `cutoff`: (default=1e-3) specifies at what value should the fourier/chebyshev coefficients be truncated below - - `max_coeffs`: the maximum number of coefficients allowed + - `max_coeffs`: the maximum number of coefficients allowed in 1D. In 2D, it is the maximum degree of a coefficient in each dimension - `mode`: ["fourier", "chebyshev"] "fourier" uses a fourier basis and "chebyshev" uses a chebyshev polynomial basis - `by_mag`: boolean. if false, will use the `max_coeffs` coefficients of lowest degree. if true, will use the `max_coeffs` coefficients of greatest absolute magnitude. + - `trunc_level`: what cutoff the periodic truncation is done at """ function function_itensornetwork( s::IndsNetworkMap, @@ -189,7 +177,8 @@ function function_itensornetwork( cutoff::Float64=1e-3, max_coeffs::Integer=100, mode="fourier", - by_mag=true, + by_mag=false, + trunc_level=1e-16 ) #get the number of inputs to f @@ -199,9 +188,8 @@ function function_itensornetwork( """ 1D functions """ if num_inputs == 1 - domain = Interval(0.0, 1.0) if mode == "fourier" - S = Fourier(domain) + S = Fourier(Interval(0.0, 1.0)) f_fourier = Fun(f, S) a = chop(f_fourier, cutoff) if by_mag @@ -209,9 +197,9 @@ function function_itensornetwork( else cf = ncoefficients(a) > max_coeffs ? coefficients(a)[1:max_coeffs] : coefficients(a) end - ψ = fourier_itensornetwork(s, cf) + ψ = fourier_itensornetwork(s, cf; cutoff=trunc_level) elseif mode == "chebyshev" - T = Chebyshev(domain) + T = Chebyshev(Interval(0.0, 1.0)) f_chebyshev = Fun(f, T) a = chop(f_chebyshev, cutoff) if by_mag @@ -219,7 +207,7 @@ function function_itensornetwork( else cf = ncoefficients(a) > max_coeffs ? coefficients(a)[1:max_coeffs] : coefficients(a) end - ψ = chebyshev_itensornetwork(s, cf) + ψ = chebyshev_itensornetwork(s, cf; cutoff=trunc_level) else throw("mode $mode not recognized") end @@ -227,31 +215,28 @@ function function_itensornetwork( """ 2D functions """ elseif num_inputs == 2 - domain = Interval(0.0, 1.0) if mode == "fourier" - S = Fourier(domain)^2 + S = Fourier(Interval(0.0, 1.0))^2 f_fourier = ProductFun(f, S; tol=cutoff) if by_mag cf = greatest_n_2d(coefficients(f_fourier), max_coeffs) else - D = Int(floor(sqrt(max_coeffs))) - a = min(D, size(coefficients(f_fourier))[1]) - b = min(D, size(coefficients(f_fourier))[2]) + a = min(max_coeffs, size(coefficients(f_fourier))[1]) + b = min(max_coeffs, size(coefficients(f_fourier))[2]) cf = coefficients(f_fourier)[1:a, 1:b] end - ψ = fourier_2D_itensornetwork(s, cf; dims=[1, 2]) + ψ = fourier_2D_itensornetwork(s, cf; dims=[1, 2], cutoff=trunc_level) elseif mode == "chebyshev" - T = Chebyshev(domain)^2 + T = Chebyshev(Interval(0.0, 1.0))^2 f_chebyshev = ProductFun(f, T; tol=cutoff) if by_mag cf = greatest_n_2d(coefficients(f_chebyshev), max_coeffs) else - D = Int(floor(sqrt(max_coeffs))) - a = min(D, size(coefficients(f_chebyshev))[1]) - b = min(D, size(coefficients(f_chebyshev))[2]) + a = min(max_coeffs, size(coefficients(f_chebyshev))[1]) + b = min(max_coeffs, size(coefficients(f_chebyshev))[2]) cf = coefficients(f_chebyshev)[1:a, 1:b] end - ψ = chebyshev_2D_itensornetwork(s, cf; dims=[1, 2]) + ψ = chebyshev_2D_itensornetwork(s, cf; dims=[1, 2], cutoff=trunc_level) else throw("mode $mode not recognized") end From 0cd8f576da4be6511237fb981cc69a9c6a6e16d3 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Thu, 31 Oct 2024 22:32:43 -0700 Subject: [PATCH 10/31] clean up old examples --- examples/1D_data_into_ITN.jl | 67 ------------ examples/1D_function_into_ITN.jl | 175 ------------------------------- examples/2D_data_into_ITN.jl | 88 ---------------- examples/2D_function_into_ITN.jl | 12 --- examples/Statue_Of_Liberty.png | Bin 935673 -> 0 bytes examples/image_into_ITN.jl | 96 ----------------- 6 files changed, 438 deletions(-) delete mode 100644 examples/1D_data_into_ITN.jl delete mode 100644 examples/1D_function_into_ITN.jl delete mode 100644 examples/2D_data_into_ITN.jl delete mode 100644 examples/Statue_Of_Liberty.png delete mode 100644 examples/image_into_ITN.jl diff --git a/examples/1D_data_into_ITN.jl b/examples/1D_data_into_ITN.jl deleted file mode 100644 index 8dcce5f..0000000 --- a/examples/1D_data_into_ITN.jl +++ /dev/null @@ -1,67 +0,0 @@ -using ITensorNumericalAnalysis - -using Graphs: SimpleGraph, uniform_tree -using NamedGraphs: NamedGraph -using NamedGraphs.NamedGraphGenerators: named_comb_tree -using Random: Random -using ITensorNetworks: maxlinkdim -using Plots - -function eval_L2(s, ψ, f) - x_vals = grid_points(s, 1) - error = 0 - # (∑|ψ(x) - f(x)|^2) - for (i, x) in enumerate(x_vals) - error += (real(evaluate(ψ, [x])) - f(x))^2 - end - return error -end - -Random.seed!(1234) - -L = 10 -g = named_comb_tree((1, L)) -s = continuous_siteinds(g; map_dimension=1) - -f(x) = 1 * exp(-(x - 0.5)^2 / 0.01) + 5 * x^2 -#f(x) = sin(30π*x) -noise_level = 0.0 -x_vals = [collect(range(0.0, 0.5; length=50)); collect(range(0.51, 1.0; length=50))] -data = [f(x) + noise_level * randn() for x in x_vals] - -### Plot one result -ψ_f = data_itn(s, data, x_vals; mode="fourier", cutoff=1e-3, max_coeffs=300) -println("length of coeffs vector: $(length(cf))") -ψ_f = truncate(ψ_f; cutoff=1e-10) -x_vals_ψ = grid_points(s, 1) -f_vals = zeros(length(x_vals_ψ)) -# c_vals = zeros(length(x_vals)) -for (i, x) in enumerate(x_vals_ψ) - f_vals[i] = real(evaluate(ψ_f, [x])) - #c_vals[i] = real(evaluate(ψ_c, [x])) -end -plot1 = plot(x_vals, data; label="true data") -plot!(x_vals_ψ, f_vals; label="fourier approx") - -### Plot of error vs # terms -# max_terms = 201 -# eval_range = 1:10:max_terms -# l = length(eval_range) - -# fourier_L2 = zeros(l) - -# for (j, i) in enumerate(eval_range) - -# println("$i terms") - -# #local ψ_c = function_itn(s, f, cutoff=1e-10, max_coeffs=i, mode="chebyshev") -# local ψ_f, n_f = data_itn(s, data; cutoff=0.0, max_coeffs=i, mode="fourier") - -# #ψ_c = truncate(ψ_c; cutoff=1e-10) -# ψ_f = truncate(ψ_f; cutoff=1e-10) - -# f = LinearInterpolation(x_vals, data, extrapolation_bc=Interpolations.Line()) -# fourier_L2[j] = eval_L2(s, ψ_f, f) -# end - -# plot(eval_range, fourier_L2, label="Fourier L2", title="noisy data", xlabel="number of terms", ylabel="loss") diff --git a/examples/1D_function_into_ITN.jl b/examples/1D_function_into_ITN.jl deleted file mode 100644 index cdb6093..0000000 --- a/examples/1D_function_into_ITN.jl +++ /dev/null @@ -1,175 +0,0 @@ -using ITensorNumericalAnalysis - -using Graphs: SimpleGraph, uniform_tree -using NamedGraphs: NamedGraph -using NamedGraphs.GraphsExtensions: rename_vertices -using NamedGraphs.NamedGraphGenerators: named_comb_tree, named_binary_tree -using Random -using ITensorNetworks: maxlinkdim -using Plots - -Random.seed!(1234) - -L = 8 -#comb tree -g = named_comb_tree((1, L)) - -#binary tree -# g = named_binary_tree(L) -# g = rename_vertices(v -> join(["$i," for i in v]), g) - -#random tree -# g = NamedGraph(SimpleGraph(uniform_tree(L))) -# g = rename_vertices(v -> (v, 1), g) - -s = continuous_siteinds(g; map_dimension=1) - -function eval_L1(s, ψ, f) - x_vals = grid_points(s, 1) - error = 0 - # (∑|ψ(x) - f(x)|) - for (i, x) in enumerate(x_vals) - error += abs(real(evaluate(ψ, [x])) - f(x)) - end - return error -end - -function eval_L2(s, ψ, f) - x_vals = grid_points(s, 1) - error = 0 - # (∑|ψ(x) - f(x)|^2) - for (i, x) in enumerate(x_vals) - error += (real(evaluate(ψ, [x])) - f(x))^2 - end - return error / length(x_vals) -end - -function L2_error(truth, est) - if length(truth) != length(est) - throw("not equal length!") - end - return sum((truth .- est) .^ 2) / length(truth) -end - -### Potential functions to choose from - -#piecewise function - f(x) = x < 0.75 ? x < 0.25 ? 0 : sin(4π * (x - 0.25)) : 0 -#gaussian -#f(x) = exp(-(x - 0.5)^2 / 0.01) - -#almost 1/x function. this breaks it if the cutoff is not fairly large/max_coeffs fairly small -#f(x) = 1/(.01+x) + 5*x^2 - -#f(x) = sin(1/(.01+x)) -#f(x) = cos(π*x) + 5*x -# f(x) = sin(20*x^(1/7)) - - -# Sum of random Gaussians - -# Ng = 40 -# ω = 0.001 -# ws = [ω * rand() for n in 1:Ng] -# xs = [rand() for n in 1:Ng] -# hs = [randn() for n in 1:Ng] -# step_size = 2.5 * rand() -# step_location = 0.4 -# function f(x::Number) -# val = sum(g -> hs[g] * exp(-(x[1] - xs[g])^2 / ws[g]), 1:Ng) -# val += (x[1] > step_location) ? step_size : 0.0 -# return val -# end - -### Plotting f(x) vs ITN encodings using Fourier or Chebyshev decompositions - -cheb_max = 100 -fourier_max = 100 -cheb_cut = 1e-4 -fourier_cut = 1e-4 - -ψ_c = function_itn(s, f; cutoff=cheb_cut, max_coeffs=cheb_max, mode="chebyshev") -ψ_f = function_itn(s, f; cutoff=fourier_cut, max_coeffs=fourier_max, mode="fourier") - - - -println("truncating...") -ψ_c = truncate(ψ_c; cutoff=1e-10) -ψ_f = truncate(ψ_f; cutoff=1e-10) - -println("chebyshev maxlinkdim $(maxlinkdim(ψ_c))") -println("fourier maxlinkdim $(maxlinkdim(ψ_f))") - -fourier_L1 = eval_L1(s, ψ_f, f) -fourier_L2 = eval_L2(s, ψ_f, f) -cheb_L1 = eval_L1(s, ψ_c, f) -cheb_L2 = eval_L2(s, ψ_c, f) -println("Fourier L2: $fourier_L2") -println("Chebyshev L2: $cheb_L2") - -x_vals = grid_points(s, 1) -f_vals = [real(evaluate(ψ_f, [x])) for x in x_vals] -c_vals = [real(evaluate(ψ_c, [x])) for x in x_vals] -true_vals = [f(x) for x in x_vals] - -# println("Fourier L2 (second method): $(L2_error(true_vals,f_vals))") -# println("Cheb L2 (second method): $(L2_error(true_vals, c_vals))") - -println("Plotting f(x)") -plot(x_vals, true_vals; label="true function", title="f(x)") -plot!(x_vals, f_vals; label="Fourier ") -plot!(x_vals, c_vals; label="Chebyshev") - -### Plots of Loss vs # terms and Maxlinkdim vs # terms - -# max_terms = 25 -# eval_range = 1:3:max_terms -# l = length(eval_range) - -# cheb_L1 = zeros(l) -# cheb_L2 = zeros(l) -# fourier_L1 = zeros(l) -# fourier_L2 = zeros(l) -# cheb_mld = zeros(l) -# fourier_mld = zeros(l) - -# for (j, i) in enumerate(eval_range) -# println("$i terms") - -# local ψ_c = function_itn(s, f; cutoff=1e-10, max_coeffs=i, mode="chebyshev") -# local ψ_f = function_itn(s, f; cutoff=1e-10, max_coeffs=i, mode="fourier") - -# ψ_c = truncate(ψ_c; cutoff=1e-10) -# ψ_f = truncate(ψ_f; cutoff=1e-10) - -# cheb_L1[j] = eval_L1(s, ψ_c, f) -# cheb_L2[j] = eval_L2(s, ψ_c, f) -# fourier_L1[j] = eval_L1(s, ψ_f, f) -# fourier_L2[j] = eval_L2(s, ψ_f, f) -# cheb_mld[j] = maxlinkdim(ψ_c) -# fourier_mld[j] = maxlinkdim(ψ_f) -# end - -# plot1 = plot( -# eval_range, -# cheb_L1; -# label="Cheb L1", -# title="f(x) = exp(-(x-0.5)^2/.01)", -# xlabel="number of terms", -# ylabel="loss", -# ) -# plot!(eval_range, cheb_L2; label="Cheb L2") -# plot!(eval_range, fourier_L1; label="Fourier L1") -# plot!(eval_range, fourier_L2; label="Fourier L2") - -# plot2 = plot( -# eval_range, -# cheb_mld; -# label="Chebyshev", -# title="f(x) = exp(-(x-0.5)^2/.01)", -# xlabel="number of terms", -# ylabel="max bond dimension", -# ) -# plot!(eval_range, fourier_mld; label="Fourier") - -# display(plot1, plot2, layout=(1,2)) diff --git a/examples/2D_data_into_ITN.jl b/examples/2D_data_into_ITN.jl deleted file mode 100644 index 715703b..0000000 --- a/examples/2D_data_into_ITN.jl +++ /dev/null @@ -1,88 +0,0 @@ -using ITensorNumericalAnalysis - -using Graphs: SimpleGraph, uniform_tree -using NamedGraphs: NamedGraph -using NamedGraphs.GraphsExtensions: rename_vertices -using NamedGraphs.NamedGraphGenerators: named_comb_tree, named_binary_tree -using Random -using ITensorNetworks: maxlinkdim -using Plots -using Interpolations - -Random.seed!(1234) - -function eval_L2(s, f, ψ_f) - x_vals = grid_points(s, 1) - y_vals = grid_points(s, 2) - error_sq = [ - (f(x, y) - real(ITensorNumericalAnalysis.evaluate(ψ_f, [x, y])))^2 for x in x_vals, - y in y_vals - ] - N = length(error_sq) - return sum(error_sq) / N -end - -L = 8 -g = named_comb_tree((2, L ÷ 2)) - -# g = NamedGraph(SimpleGraph(uniform_tree(L))) -# g = rename_vertices(v -> (v, 1), g) - -# g = named_binary_tree(3) -# g = rename_vertices(v -> join(["$i," for i in v]), g) - -s = continuous_siteinds(g; map_dimension=2) - -### Example Test Functions to generate data off of -#f(x, y) = exp( -( (x-0.5)^2 + (y-0.5)^2 )/.05) -f(x, y) = sin(2π * x) + sin(2π * y) - -xrange = 0:0.05:1 -yrange = 0:0.05:1 -noise_level = 0.0 -data = [f(x, y) + noise_level * randn() for x in xrange, y in yrange] - -elapsed_time = @elapsed begin - ψ_f = data_itn(s, data, (xrange, yrange); mode="fourier", cutoff=1e-3, max_coeffs=20) -end -println("ψ_f time: ", elapsed_time) - -elapsed_time = @elapsed begin - ψ_c = data_itn( - s, data, (xrange, yrange); mode="chebyshev", cutoff=1e-3, max_coeffs=20, by_mag=false - ) -end -println("ψ_c time: ", elapsed_time) - -ψ_f = truncate(ψ_f; cutoff=1e-10) -println("maxlinkdim of ψ_f after truncation: $(maxlinkdim(ψ_f))") - -ψ_c = truncate(ψ_c; cutoff=1e-10) -println("maxlinkdim of ψ_c after truncation: $(maxlinkdim(ψ_c))") - -x_vals = grid_points(s, 1) -y_vals = grid_points(s, length(x_vals), 2) -#f_eval = [f(x,y) for x in x_vals, y in y_vals] -ψ_f_eval = [ - real(ITensorNumericalAnalysis.evaluate(ψ_f, [x, y])) for x in x_vals, y in y_vals -] -ψ_c_eval = [ - real(ITensorNumericalAnalysis.evaluate(ψ_c, [x, y])) for x in x_vals, y in y_vals -] - -g = LinearInterpolation((xrange, yrange), data; extrapolation_bc=Interpolations.Line()) -fourier_loss = eval_L2(s, g, ψ_f) -chebyshev_loss = eval_L2(s, g, ψ_c) -println("fourier L2 error: $fourier_loss") -println("chebyshev L2 error: $chebyshev_loss") - -plot1 = heatmap(xrange, yrange, data; title="true data", xlabel="x", ylabel="y") #true data -plot2 = heatmap( - x_vals, y_vals, ψ_f_eval; title="fourier TN", xlabel="x", ylabel="y", zlabel="ψ(x,y)" -) #fourier TN approximation -plot3 = heatmap( - x_vals, y_vals, ψ_c_eval; title="chebyshev TN", xlabel="x", ylabel="y", zlabel="ψ(x,y)" -) #chebyshev TN approximation - -combined_plot = plot(plot1, plot2, plot3; layout=(1, 3), size=(1200, 280)) -display(combined_plot) diff --git a/examples/2D_function_into_ITN.jl b/examples/2D_function_into_ITN.jl index 51a87c0..fe11064 100644 --- a/examples/2D_function_into_ITN.jl +++ b/examples/2D_function_into_ITN.jl @@ -18,24 +18,12 @@ L = 10 #comb tree g = named_comb_tree((2, L ÷ 2)) - -#uniform tree -# g = NamedGraph(SimpleGraph(uniform_tree(L))) -# g = rename_vertices(v -> (v, 1), g) - -#binary tree -# g = named_binary_tree(4) -# g = rename_vertices(v -> join(["$i," for i in v]), g) - s = continuous_siteinds(g; map_dimension=2) x_vals = grid_points(s, 1) y_vals = grid_points(s, length(x_vals), 2) -### Example Test Functions to use f(x, y) = exp(-((x - 0.5)^2 + (y - 0.5)^2) / 0.05) -#f(x, y) = exp(x) - exp(y) -#f(x, y) = cos(20 * (x + y)) + sin(50 * (x - y)) ψ_f = function_itn(s, f; mode="fourier", cutoff=1e-3, max_coeffs=400, by_mag=true) ψ_c = function_itn(s, f; mode="chebyshev", cutoff=1e-3, max_coeffs=400, by_mag=true) diff --git a/examples/Statue_Of_Liberty.png b/examples/Statue_Of_Liberty.png deleted file mode 100644 index adf867af901019428a11154d460abd98573da2c8..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 935673 zcmXVX1yCGa)Ai!+wm1ZLO>lPzP6!T*6B68Qao6DP5Q4h}cL^HY-Q8hff1daI&(zdZ z-I|)3>U(eZ>C=59)Kug!P)Se$004%9ytD=Y0H^)mjSTxf;v^a={QjUalh;rN0KDh{ z0RLbB;Q4*X{}2FhU5hND{Wf`PH 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rename_vertices -using NamedGraphs.NamedGraphGenerators: named_comb_tree -using Random -using ITensorNetworks: maxlinkdim -using Plots -using Images: imresize -using FileIO: load - -function eval_L2(f_eval, ψ_eval) - N = length(f_eval) - return sum((f_eval .- ψ_eval) .^ 2) / N -end - -L = 5 -g = named_comb_tree((2, L)) -s = continuous_siteinds(g; map_dimension=2) - -img = load("examples/Statue_Of_Liberty.png") -img_matrix = Array{Gray}(img) -img_float_matrix = (x -> float(x)).(Float32.(img_matrix)) -data = imresize(img_float_matrix, (2^L, 2^L)) -data = reverse(data; dims=1) - -println("size of matrix: $(size(data))") - -elapsed_time = @elapsed begin - ψ_f = data_itn(s, data; mode="fourier", cutoff=1e-4, max_coeffs=30) -end -println("constructing ψ_f: ", elapsed_time, " seconds") - -# elapsed_time = @elapsed begin -# ψ_c = data_itn(s, data; mode="chebyshev", cutoff=1e-3, max_coeffs = 30) -# end -# println("constructing ψ_c: ", elapsed_time, " seconds") - -#### Plot Error vs Max Bond Dim - -# bondrange = 1:4:50 -# loss = zeros(length(bondrange)) -# x_vals = grid_points(s, 1) -# y_vals = grid_points(s, 2) -# for (i, bond) in enumerate(bondrange) -# ψ_bond = truncate(ψ_f; maxdim=bond) -# ψ_bond_eval = [ -# real(ITensorNumericalAnalysis.evaluate(ψ_bond, [x, y])) for x in x_vals, y in y_vals -# ] -# loss[i] = eval_L2(data, ψ_bond_eval) -# end - -# plot( -# bondrange, -# loss; -# xlabel="max bond dimension", -# ylabel="L2 error", -# title="64 x 64 statue of liberty image", -# ) - -### Compare images side by side - -ψ_f = truncate(ψ_f; cutoff=1e-16) -# ψ_c = truncate(ψ_c, cutoff=1e-16) - -println("maxlinkdim of ψ_f: $(maxlinkdim(ψ_f))") -# println("maxlinkdim of ψ_c: $(maxlinkdim(ψ_c))") - -x_vals = grid_points(s, 1) -y_vals = grid_points(s, 2) - -elapsed_time = @elapsed begin - ψ_f_eval = [ - real(ITensorNumericalAnalysis.evaluate(ψ_f, [x, y])) for x in x_vals, y in y_vals - ] -end -println("ψ_f evaluation elapsed time: ", elapsed_time, " seconds") - -# elapsed_time = @elapsed begin -# ψ_c_eval = [ -# real(ITensorNumericalAnalysis.evaluate(ψ_c, [x, y])) for x in x_vals, y in y_vals -# ] -# end -# println("ψ_c evaluation elapsed time: ", elapsed_time, " seconds") - -fourier_loss = eval_L2(data, ψ_f_eval) -# chebyshev_loss = eval_L2(data, ψ_c_eval) -println("fourier L2 error: $fourier_loss") -# println("chebyshev L2 error: $chebyshev_loss") - -plot1 = heatmap(x_vals, y_vals, data; title="true image") -plot2 = heatmap(x_vals, y_vals, ψ_f_eval; title="cheb TN") #fourier TN approximation -# plot3 = heatmap(x_vals, y_vals, ψ_c_eval; title="chebyshev TN") - -combined = plot(plot1, plot2; layout=(1, 2), size=(700, 280)) From 620d7cce14e2ffe7179f7262d96b2ef8d804c0cd Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Thu, 31 Oct 2024 22:41:58 -0700 Subject: [PATCH 11/31] stop tracking config files --- .gitignore | 45 ------------------------------------------- .vscode/settings.json | 2 -- 2 files changed, 47 deletions(-) delete mode 100644 .gitignore delete mode 100644 .vscode/settings.json diff --git a/.gitignore b/.gitignore deleted file mode 100644 index b590bfe..0000000 --- a/.gitignore +++ /dev/null @@ -1,45 +0,0 @@ -# Files generated by invoking Julia with --code-coverage -*.jl.cov -*.jl.*.cov - -# Files generated by invoking Julia with --track-allocation -*.jl.mem - -# System-specific files and directories generated by the BinaryProvider and BinDeps packages -# They contain absolute paths specific to the host computer, and so should not be committed -deps/deps.jl -deps/build.log -deps/downloads/ -deps/usr/ -deps/src/ - -# Build artifacts for creating documentation generated by the Documenter package -docs/build/ -docs/site/ - -# File generated by Pkg, the package manager, based on a corresponding Project.toml -# It records a fixed state of all packages used by the project. As such, it should not be -# committed for packages, but should be committed for applications that require a static -# environment. -Manifest.toml -# Swap -[._]*.s[a-v][a-z] -!*.svg # comment out if you don't need vector files -[._]*.sw[a-p] -[._]s[a-rt-v][a-z] -[._]ss[a-gi-z] -[._]sw[a-p] - -# Session -Session.vim -Sessionx.vim - -# Temporary -.netrwhist -*~ -# Auto-generated tag files -tags -# Persistent undo -[._]*.un~ - -plots diff --git a/.vscode/settings.json b/.vscode/settings.json deleted file mode 100644 index 7a73a41..0000000 --- a/.vscode/settings.json +++ /dev/null @@ -1,2 +0,0 @@ -{ -} \ No newline at end of file From 64c73ed75eb576215b8e25063713d044c73e1eb3 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Thu, 31 Oct 2024 22:43:42 -0700 Subject: [PATCH 12/31] oops add back .gitignore --- .gitignore | 43 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 43 insertions(+) create mode 100644 .gitignore diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..628ce42 --- /dev/null +++ b/.gitignore @@ -0,0 +1,43 @@ +# Files generated by invoking Julia with --code-coverage +*.jl.cov +*.jl.*.cov + +# Files generated by invoking Julia with --track-allocation +*.jl.mem + +# System-specific files and directories generated by the BinaryProvider and BinDeps packages +# They contain absolute paths specific to the host computer, and so should not be committed +deps/deps.jl +deps/build.log +deps/downloads/ +deps/usr/ +deps/src/ + +# Build artifacts for creating documentation generated by the Documenter package +docs/build/ +docs/site/ + +# File generated by Pkg, the package manager, based on a corresponding Project.toml +# It records a fixed state of all packages used by the project. As such, it should not be +# committed for packages, but should be committed for applications that require a static +# environment. +Manifest.toml +# Swap +[._]*.s[a-v][a-z] +!*.svg # comment out if you don't need vector files +[._]*.sw[a-p] +[._]s[a-rt-v][a-z] +[._]ss[a-gi-z] +[._]sw[a-p] + +# Session +Session.vim +Sessionx.vim + +# Temporary +.netrwhist +*~ +# Auto-generated tag files +tags +# Persistent undo +[._]*.un~ From 22c3707b5bafcdbcb7a549cb5d951f649ba7ce1a Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Thu, 31 Oct 2024 22:49:30 -0700 Subject: [PATCH 13/31] formatting --- src/interpolation_functions.jl | 51 +++++++++++++++++++++------------- 1 file changed, 32 insertions(+), 19 deletions(-) diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl index b7bf709..149c2f2 100644 --- a/src/interpolation_functions.jl +++ b/src/interpolation_functions.jl @@ -17,10 +17,10 @@ end + ∑_{k=1}^{n} coeffs[2k+1]*cos(2kπx) """ function fourier_itensornetwork( s::IndsNetworkMap, - coeffs::Vector{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; + coeffs::Vector{<:Union{AbstractFloat,Complex{<:AbstractFloat}}}; dim::Int=1, min_threshold=1e-15, - cutoff=1e-16 + cutoff=1e-16, ) n = length(coeffs) if n < 1 @@ -39,7 +39,11 @@ end """ Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are sines/cosines. """ function fourier_2D_itensornetwork( - s::IndsNetworkMap, coeffs::Matrix{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dims::Vector{Int}=[1, 2], min_threshold=1e-15, cutoff=1e-16 + s::IndsNetworkMap, + coeffs::Matrix{<:Union{AbstractFloat,Complex{<:AbstractFloat}}}; + dims::Vector{Int}=[1, 2], + min_threshold=1e-15, + cutoff=1e-16, ) n = size(coeffs)[1] m = size(coeffs)[2] @@ -62,7 +66,10 @@ end """ Build the function f(x) = ∑_{k=1}^n coeffs[k] * T_k(x) where T_k(x) is the k-th Chebyshev polynomial. """ function chebyshev_itensornetwork( - s::IndsNetworkMap, coeffs::Vector{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dim::Int=1, cutoff=1e-16 + s::IndsNetworkMap, + coeffs::Vector{<:Union{AbstractFloat,Complex{<:AbstractFloat}}}; + dim::Int=1, + cutoff=1e-16, ) n = length(coeffs) if n <= 0 @@ -72,8 +79,8 @@ function chebyshev_itensornetwork( end #Clenshaw Evaluation method - uses idea from https://arxiv.org/pdf/2407.09609 - y_n = const_itn(s; c = 0) - y_n1 = const_itn(s; c = 0) + y_n = const_itn(s; c=0) + y_n1 = const_itn(s; c=0) # y_n-1 = c_n-1 - y_n+1 + (4x-2) * y_n for d in n:-1:1 @@ -82,42 +89,48 @@ function chebyshev_itensornetwork( y_n1 = old_y_n end - return truncate(y_n + poly_itn(s, [1,-2]; dim) * y_n1; cutoff) + return truncate(y_n + poly_itn(s, [1, -2]; dim) * y_n1; cutoff) end """ Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are chebyshev polynomials """ function chebyshev_2D_itensornetwork( - s::IndsNetworkMap, coeffs::Matrix{<:Union{AbstractFloat, Complex{<:AbstractFloat}}}; dims::Vector{Int}=[1, 2], cutoff=1e-16 + s::IndsNetworkMap, + coeffs::Matrix{<:Union{AbstractFloat,Complex{<:AbstractFloat}}}; + dims::Vector{Int}=[1, 2], + cutoff=1e-16, ) n = size(coeffs)[1] m = size(coeffs)[2] if n < 1 || m < 1 throw("coeffs must be nonempty") end - + #Clenshaw Evaluation method - uses idea from https://arxiv.org/pdf/2407.09609 - y_n = const_itn(s; c = 0) - y_n1 = const_itn(s; c = 0) + y_n = const_itn(s; c=0) + y_n1 = const_itn(s; c=0) for j in m:-1:1 #determine the weighted sum of chebyshev polynomials of x - x_n = const_itn(s; c = 0) - x_n1 = const_itn(s; c = 0) + x_n = const_itn(s; c=0) + x_n1 = const_itn(s; c=0) for i in n:-1:1 - # x_n-1 = c_n-1 - x_n+1 + (4x-2) * x_n + # x_n-1 = c_n-1 - x_n+1 + (4x-2) * x_n old_x_n = truncate(x_n; cutoff) - x_n = coeffs[i,j] * const_itn(s) + (-1) * x_n1 + poly_itn(s, [-2, 4]; dim=dims[1]) * old_x_n + x_n = + coeffs[i, j] * const_itn(s) + + (-1) * x_n1 + + poly_itn(s, [-2, 4]; dim=dims[1]) * old_x_n x_n1 = old_x_n end - coeff_j = truncate(x_n + poly_itn(s, [1,-2]; dim=dims[1]) * x_n1; cutoff) + coeff_j = truncate(x_n + poly_itn(s, [1, -2]; dim=dims[1]) * x_n1; cutoff) # y_n-1 = c_n-1 - y_n+1 + (4y-2) * y_n old_y_n = truncate(y_n; cutoff) - y_n = coeff_j + (-1)*y_n1 + poly_itn(s, [-2, 4]; dim=dims[2]) * old_y_n + y_n = coeff_j + (-1) * y_n1 + poly_itn(s, [-2, 4]; dim=dims[2]) * old_y_n y_n1 = old_y_n end - return truncate(y_n + poly_itn(s, [1,-2]; dim=dims[2]) * y_n1; cutoff) + return truncate(y_n + poly_itn(s, [1, -2]; dim=dims[2]) * y_n1; cutoff) end """ Helper function for function_itensornetwork (1D case) """ @@ -178,7 +191,7 @@ function function_itensornetwork( max_coeffs::Integer=100, mode="fourier", by_mag=false, - trunc_level=1e-16 + trunc_level=1e-16, ) #get the number of inputs to f From 62d23f76fc7a6391cb1bcf0db25050bd4494f786 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Thu, 31 Oct 2024 23:46:08 -0700 Subject: [PATCH 14/31] test case --- test/test_indexmaps.jl | 61 ------------------------------------------ 1 file changed, 61 deletions(-) diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 9b3b077..f690c27 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -70,65 +70,4 @@ Random.seed!(1234) xyzvals ≈ xyzvals_approx end - @testset "test grid_points" begin - L = 16 - base = 2 - g = named_comb_tree((2, L ÷ 2)) - s = continuous_siteinds(g; map_dimension=2) - - #first set -- irregular span - N = 125 - a = 0.12 - b = 0.95 - test_gridpoints = grid_points(s, N, 1, [a, b]) - - points_in_span = floor(b * base^(L / 2)) - ceil(a * base^(L / 2)) + 1 - N_gridpoints = Int(floor(points_in_span / ceil(points_in_span / N))) + 1 - - @test length(test_gridpoints) == N_gridpoints - @test test_gridpoints[1] >= a - @test test_gridpoints[end] < b - internal = (test_gridpoints[2] - test_gridpoints[1]) - left = (test_gridpoints[1] - a) - right = (b - test_gridpoints[end]) - @test internal >= left && internal >= right - - #second set - N = 32 - a = 0.25 - b = 0.5 - test2 = grid_points(s, N, 1, [a, b]) - @test length(test2) == N - @test test2[1] >= a - @test test2[end] < b - internal = (test2[2] - test2[1]) - left = (test2[1] - a) - right = (b - test2[end]) - @test internal >= left && internal >= right - - #third set - test3 = grid_points(s, 1) - @test length(test3) == 256 - @test test3[1] >= 0 - @test test3[end] < 1 - internal = (test3[2] - test3[1]) - left = (test3[1] - a) - right = (b - test3[end]) - @test internal >= left && internal >= right - - #test the rand_p() function to see if it succeeds - rng = Random.Xoshiro(42) - rand_gridpoint1 = rand_p(rng, s) - rand_gridpoint2 = rand_p(rng, s, 1) - default_rng_gridpoint1 = rand_p(s) - default_rng_gridpoint2 = rand_p(s, 1) - - #fourth set -- very large L - L = 140 - base = 2 - g = named_comb_tree((2, L ÷ 2)) - s = continuous_siteinds(g; map_dimension=2) - n_grid = 16 - @test length(grid_points(s, n_grid, 1)) == n_grid - end end From f03c5181cf181c28764db16e685669ffa814128c Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Thu, 31 Oct 2024 23:51:09 -0700 Subject: [PATCH 15/31] formatting --- test/test_indexmaps.jl | 1 - 1 file changed, 1 deletion(-) diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index f690c27..4344833 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -69,5 +69,4 @@ Random.seed!(1234) xyzvals_approx = calculate_p(s, ind_to_ind_value_map, [i for i in 1:dimension(s)]) xyzvals ≈ xyzvals_approx end - end From bd4e0d42c954ebf6f575db262de3eb52c52a13fc Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Mon, 4 Nov 2024 15:24:00 -0800 Subject: [PATCH 16/31] added back grid_points tests, made naming of args more consistent, cleaned up code a bit --- Project.toml | 2 - src/interpolation_functions.jl | 84 ++++++++++++++-------------------- test/test_indexmaps.jl | 62 +++++++++++++++++++++++++ 3 files changed, 97 insertions(+), 51 deletions(-) diff --git a/Project.toml b/Project.toml index 4b560d5..014c6e0 100644 --- a/Project.toml +++ b/Project.toml @@ -6,13 +6,11 @@ version = "0.1.1" [deps] ApproxFun = "28f2ccd6-bb30-5033-b560-165f7b14dc2f" Dictionaries = "85a47980-9c8c-11e8-2b9f-f7ca1fa99fb4" -FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549" Glob = "c27321d9-0574-5035-807b-f59d2c89b15c" GraphRecipes = "bd48cda9-67a9-57be-86fa-5b3c104eda73" Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6" ITensorNetworks = "2919e153-833c-4bdc-8836-1ea460a35fc7" ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5" -Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0" Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59" NamedGraphs = "678767b0-92e7-4007-89e4-4527a8725b19" Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl index 149c2f2..66b0659 100644 --- a/src/interpolation_functions.jl +++ b/src/interpolation_functions.jl @@ -1,15 +1,15 @@ using ApproxFun: Interval, Fourier, Chebyshev, Fun, ProductFun, coefficients, chop, ncoefficients -using Interpolations: LinearInterpolation, Line +using Interpolations: LinearInterpolation, Line, CubicSplineInterpolation """ Helper function for fourier_itensornetwork and fourier_2D_itensornetwork """ -function fourier_term(s::IndsNetworkMap, j::Integer, d::Integer) +function fourier_term(s::IndsNetworkMap, j::Integer, dim::Integer) if j == 1 return const_itn(s) elseif j % 2 == 0 - return sin_itn(s; k=j * π, dim=d) + return sin_itn(s; k=j * π, dim) else - return cos_itn(s; k=(j - 1) * π, dim=d) + return cos_itn(s; k=(j - 1) * π, dim) end end @@ -17,7 +17,7 @@ end + ∑_{k=1}^{n} coeffs[2k+1]*cos(2kπx) """ function fourier_itensornetwork( s::IndsNetworkMap, - coeffs::Vector{<:Union{AbstractFloat,Complex{<:AbstractFloat}}}; + coeffs::Vector{<:Number}; dim::Int=1, min_threshold=1e-15, cutoff=1e-16, @@ -27,7 +27,7 @@ function fourier_itensornetwork( throw("coeffs must be nonempty") end - ψ = coeffs[1] * const_itn(s) + ψ = coeffs[1] * fourier_term(s, 1, dim) for i in 2:n if abs(coeffs[i]) > min_threshold ψ += coeffs[i] * fourier_term(s, i, dim) @@ -40,7 +40,7 @@ end """ Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are sines/cosines. """ function fourier_2D_itensornetwork( s::IndsNetworkMap, - coeffs::Matrix{<:Union{AbstractFloat,Complex{<:AbstractFloat}}}; + coeffs::Matrix{<:Number}; dims::Vector{Int}=[1, 2], min_threshold=1e-15, cutoff=1e-16, @@ -67,7 +67,7 @@ end where T_k(x) is the k-th Chebyshev polynomial. """ function chebyshev_itensornetwork( s::IndsNetworkMap, - coeffs::Vector{<:Union{AbstractFloat,Complex{<:AbstractFloat}}}; + coeffs::Vector{<:Number}; dim::Int=1, cutoff=1e-16, ) @@ -95,7 +95,7 @@ end """ Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are chebyshev polynomials """ function chebyshev_2D_itensornetwork( s::IndsNetworkMap, - coeffs::Matrix{<:Union{AbstractFloat,Complex{<:AbstractFloat}}}; + coeffs::Matrix{<:Number}; dims::Vector{Int}=[1, 2], cutoff=1e-16, ) @@ -172,26 +172,26 @@ function greatest_n_2d(coeffs_matrix, n) end """ - function_itensornetwork(s,f, cutoff=1e-3, max_coeffs=100, mode="fourier", by_mag=true) + function_itensornetwork(s,f, chop_level=1e-3, max_coeffs=100, mode="fourier", by_mag=true, cutoff=1e-16) Takes in a function `f` as a black box, outputs a tensor network approximation using Fourier or Chebyshev series. Supports 1D or 2D functions. #Arguments - `s`: IndsNetworkMap - `f`: a real-valued function on domain [0,1] or [0,1]⊗[0,1] which can be given as a black box - - `cutoff`: (default=1e-3) specifies at what value should the fourier/chebyshev coefficients be truncated below + - `chop_level`: (default=1e-3) specifies at what level of precision should the fourier/chebyshev coefficients be chopped off at - `max_coeffs`: the maximum number of coefficients allowed in 1D. In 2D, it is the maximum degree of a coefficient in each dimension - `mode`: ["fourier", "chebyshev"] "fourier" uses a fourier basis and "chebyshev" uses a chebyshev polynomial basis - `by_mag`: boolean. if false, will use the `max_coeffs` coefficients of lowest degree. if true, will use the `max_coeffs` coefficients of greatest absolute magnitude. - - `trunc_level`: what cutoff the periodic truncation is done at + - `cutoff`: (default=1e-16) at what cutoff the repeated calls to truncate() are performed at """ function function_itensornetwork( s::IndsNetworkMap, f::Function; - cutoff::Float64=1e-3, + chop_level::Float64=1e-3, max_coeffs::Integer=100, mode="fourier", by_mag=false, - trunc_level=1e-16, + cutoff=1e-16, ) #get the number of inputs to f @@ -204,23 +204,23 @@ function function_itensornetwork( if mode == "fourier" S = Fourier(Interval(0.0, 1.0)) f_fourier = Fun(f, S) - a = chop(f_fourier, cutoff) + a = chop(f_fourier, chop_level) if by_mag cf = greatest_n(coefficients(a), max_coeffs) else cf = ncoefficients(a) > max_coeffs ? coefficients(a)[1:max_coeffs] : coefficients(a) end - ψ = fourier_itensornetwork(s, cf; cutoff=trunc_level) + ψ = fourier_itensornetwork(s, cf; cutoff) elseif mode == "chebyshev" T = Chebyshev(Interval(0.0, 1.0)) f_chebyshev = Fun(f, T) - a = chop(f_chebyshev, cutoff) + a = chop(f_chebyshev, chop_level) if by_mag cf = greatest_n(coefficients(a), max_coeffs) else cf = ncoefficients(a) > max_coeffs ? coefficients(a)[1:max_coeffs] : coefficients(a) end - ψ = chebyshev_itensornetwork(s, cf; cutoff=trunc_level) + ψ = chebyshev_itensornetwork(s, cf; cutoff) else throw("mode $mode not recognized") end @@ -230,7 +230,7 @@ function function_itensornetwork( elseif num_inputs == 2 if mode == "fourier" S = Fourier(Interval(0.0, 1.0))^2 - f_fourier = ProductFun(f, S; tol=cutoff) + f_fourier = ProductFun(f, S; tol=chop_level) if by_mag cf = greatest_n_2d(coefficients(f_fourier), max_coeffs) else @@ -238,10 +238,10 @@ function function_itensornetwork( b = min(max_coeffs, size(coefficients(f_fourier))[2]) cf = coefficients(f_fourier)[1:a, 1:b] end - ψ = fourier_2D_itensornetwork(s, cf; dims=[1, 2], cutoff=trunc_level) + ψ = fourier_2D_itensornetwork(s, cf; dims=[1, 2], cutoff) elseif mode == "chebyshev" T = Chebyshev(Interval(0.0, 1.0))^2 - f_chebyshev = ProductFun(f, T; tol=cutoff) + f_chebyshev = ProductFun(f, T; tol=chop_level) if by_mag cf = greatest_n_2d(coefficients(f_chebyshev), max_coeffs) else @@ -249,7 +249,7 @@ function function_itensornetwork( b = min(max_coeffs, size(coefficients(f_chebyshev))[2]) cf = coefficients(f_chebyshev)[1:a, 1:b] end - ψ = chebyshev_2D_itensornetwork(s, cf; dims=[1, 2], cutoff=trunc_level) + ψ = chebyshev_2D_itensornetwork(s, cf; dims=[1, 2], cutoff) else throw("mode $mode not recognized") end @@ -265,37 +265,23 @@ end #Arguments - `s`: IndsNetworkMap - `data`: a real-valued vector or matrix of data points - - `eval_pts`: optional, where the data is located. by default it will the data as evenly spaced over [0,1] or [0,1]⊗[0,1], depending on dimension of the data. - - other kwargs are inherited from `function_itensornetwork` + - `domain`: optional argument, specifies at what coordinates the data is located. Must match the shape of `data`. If left unspecified, data is treated as evenly spaced over [0,1]/[0,1]⊗[0,1]. + - `interpolation_mode`: Taken from Interpolations.jl. By default is `LinearInterpolation`, alternatively can be `CubicSplineInterpolation`. + - all other kwargs are inherited from `function_itensornetwork` """ -function data_itensornetwork(s::IndsNetworkMap, data, eval_pts=nothing; kwargs...) +function data_itensornetwork(s::IndsNetworkMap, data, domain=nothing, interpolation_mode=LinearInterpolation; kwargs...) dimensionality = length(size(data)) - - if dimensionality == 1 - #if no eval_pts are given, assumes that the data is evenly spaced across [0,1] - if eval_pts == nothing - eval_pts = grid_points(s, length(data), 1; exact_grid=false) - end - if length(eval_pts) != length(data) - throw("length of data and eval_pts do not match!") - end - f = LinearInterpolation(eval_pts, data; extrapolation_bc=Line()) - g = (x) -> f(x) #make a function g that is defined as f - return function_itensornetwork(s, g; kwargs...) - elseif dimensionality == 2 - if eval_pts == nothing - eval_pts_x = grid_points(s, size(data)[1], 1; exact_grid=false) - eval_pts_y = grid_points(s, size(data)[2], 2; exact_grid=false) - eval_pts = (eval_pts_x, eval_pts_y) - end - if length(eval_pts[1]) * length(eval_pts[2]) != length(data) - throw("length of data and eval_pts do not match!") - end - f = LinearInterpolation(eval_pts, data; extrapolation_bc=Line()) - g = (x, y) -> f(x, y) #make a function g that is defined identically to f - return function_itensornetwork(s, g; kwargs...) + if isnothing(domain) + domain = Tuple([grid_points(s, size(data)[i], i; exact_grid=false) for i in 1:dimensionality]) + end + if map(length, domain) != size(data) + throw("shape of data and domain do not match!") end + # Specifies how the function should be defined between data points + f = interpolation_mode(domain, data; extrapolation_bc=Line()) + g = x... -> f(x...) + return function_itensornetwork(s, g; kwargs...) end const fourier_itn = fourier_itensornetwork diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 4344833..79c05cb 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -69,4 +69,66 @@ Random.seed!(1234) xyzvals_approx = calculate_p(s, ind_to_ind_value_map, [i for i in 1:dimension(s)]) xyzvals ≈ xyzvals_approx end + + @testset "test grid_points" begin + L = 16 + base = 2 + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + + #first set -- irregular span + N = 125 + a = 0.12 + b = 0.95 + test_gridpoints = grid_points(s, N, 1, [a, b]) + + points_in_span = floor(b * base^(L / 2)) - ceil(a * base^(L / 2)) + 1 + N_gridpoints = Int(floor(points_in_span / ceil(points_in_span / N))) + 1 + + @test length(test_gridpoints) == N_gridpoints + @test test_gridpoints[1] >= a + @test test_gridpoints[end] < b + internal = (test_gridpoints[2] - test_gridpoints[1]) + left = (test_gridpoints[1] - a) + right = (b - test_gridpoints[end]) + @test internal >= left && internal >= right + + #second set + N = 32 + a = 0.25 + b = 0.5 + test2 = grid_points(s, N, 1, [a, b]) + @test length(test2) == N + @test test2[1] >= a + @test test2[end] < b + internal = (test2[2] - test2[1]) + left = (test2[1] - a) + right = (b - test2[end]) + @test internal >= left && internal >= right + + #third set + test3 = grid_points(s, 1) + @test length(test3) == 256 + @test test3[1] >= 0 + @test test3[end] < 1 + internal = (test3[2] - test3[1]) + left = (test3[1] - a) + right = (b - test3[end]) + @test internal >= left && internal >= right + + #test the rand_p() function to see if it succeeds + rng = Random.Xoshiro(42) + rand_gridpoint1 = rand_p(rng, s) + rand_gridpoint2 = rand_p(rng, s, 1) + default_rng_gridpoint1 = rand_p(s) + default_rng_gridpoint2 = rand_p(s, 1) + + #fourth set -- very large L + L = 140 + base = 2 + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + n_grid = 16 + @test length(grid_points(s, n_grid, 1)) == n_grid + end end From 050cb3e493a48b4b88a4594c6faf543afcd2240e Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Mon, 4 Nov 2024 23:43:09 -0800 Subject: [PATCH 17/31] added functional grid_points and rand_p functions with passing tests --- Project.toml | 1 - src/IndexMaps/abstractindexmap.jl | 10 ++- src/IndexMaps/complexindexmap.jl | 12 ++++ src/IndexMaps/realindexmap.jl | 111 ++++++++++++++++++++++++++++-- src/interpolation_functions.jl | 2 +- test/test_indexmaps.jl | 7 +- 6 files changed, 131 insertions(+), 12 deletions(-) diff --git a/Project.toml b/Project.toml index 014c6e0..11edff5 100644 --- a/Project.toml +++ b/Project.toml @@ -7,7 +7,6 @@ version = "0.1.1" ApproxFun = "28f2ccd6-bb30-5033-b560-165f7b14dc2f" Dictionaries = "85a47980-9c8c-11e8-2b9f-f7ca1fa99fb4" Glob = "c27321d9-0574-5035-807b-f59d2c89b15c" -GraphRecipes = "bd48cda9-67a9-57be-86fa-5b3c104eda73" Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6" ITensorNetworks = "2919e153-833c-4bdc-8836-1ea460a35fc7" ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5" diff --git a/src/IndexMaps/abstractindexmap.jl b/src/IndexMaps/abstractindexmap.jl index e71bb85..f118457 100644 --- a/src/IndexMaps/abstractindexmap.jl +++ b/src/IndexMaps/abstractindexmap.jl @@ -2,7 +2,7 @@ using Base: Base using Dictionaries: Dictionary, set! using ITensors: ITensors, Index, dim using ITensorNetworks: IndsNetwork, vertex_data - +using Random: AbstractRNG, default_rng abstract type AbstractIndexMap{VB,VD} end #These functions need to be defined on the concrete type for implementation @@ -17,7 +17,7 @@ function calculate_ind_values( ) return not_implemented() end -grid_points(imap::AbstractIndexMap, N::Int, d::Int) = not_implemented() + rem_index(imap::AbstractIndexMap, ind::Index) = not_implemented() dimensions(imap::AbstractIndexMap) = Int64.(unique(collect(values(index_dimension(imap))))) @@ -104,3 +104,9 @@ function grid_points(imap::AbstractIndexMap, d::Int) L = length(dimension_inds(imap, d)) return grid_points(imap, base^L, d) end + +function rand_p(rng::AbstractRNG, imap::AbstractIndexMap) + return [rand_p(rng, imap, i) for i in 1:dimension(imap)] +end + +rand_p(imap::AbstractIndexMap, args...) = rand_p(default_rng(), imap, args...) \ No newline at end of file diff --git a/src/IndexMaps/complexindexmap.jl b/src/IndexMaps/complexindexmap.jl index eda4bc2..f1dd2a8 100644 --- a/src/IndexMaps/complexindexmap.jl +++ b/src/IndexMaps/complexindexmap.jl @@ -2,6 +2,7 @@ using Base: Base using Dictionaries: Dictionaries, Dictionary, set! using ITensors: ITensors, Index, dim, hastags using ITensorNetworks: IndsNetwork, vertex_data +using Random: AbstractRNG struct ComplexIndexMap{VB,VD,VR} <: AbstractIndexMap{VB,VD} index_digit::VB @@ -142,3 +143,14 @@ function grid_points(imap::ComplexIndexMap, N::Int, d::Int) ] return filter(x -> real(x) < 1 && imag(x) < 1, grid_points) end + +""" + Picks a random grid point from `imap` given a dimension +""" +function rand_p(rng::AbstractRNG, imap::ComplexIndexMap, d::Integer) + dims = dim.(dimension_inds(imap, d)) + @assert all(y -> y == first(dims), dims) + base = float(first(dims)) + Lre, Lim = length(real_indices(imap, d)), length(imag_indices(imap, d)) + return rand(rng, 0:(base^Lre - 1)) / base^Lre + im * rand(rng, 0:(base^Lim - 1)) / base^Lim +end diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index 51063e9..a23a807 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -2,6 +2,7 @@ using Base: Base using Dictionaries: Dictionaries, Dictionary, set! using ITensors: ITensors, Index, dim using ITensorNetworks: IndsNetwork, vertex_data +using Random: AbstractRNG struct RealIndexMap{VB,VD} <: AbstractIndexMap{VB,VD} index_digit::VB @@ -75,12 +76,112 @@ function calculate_ind_values(imap::RealIndexMap, xs::Vector, dims::Vector{Int}) return ind_to_ind_value_map end -function grid_points(imap::RealIndexMap, N::Int, d::Int) +""" + grid_points(imap, N, d, span; exact_grid=true, enforced=[]) + + Gives `N` grid points from a given dimension of `imap` within a specified range. + + # Arguments + - `imap::RealIndexMap`: An IndexMap specifying the structure of the TN being used + - `N::Int`: The number of grid points requested. + - `d::Int` The index of the dimension of `imap` requested + - `span::AbstractVector{<:Number}`: A two element number vector [a,b] with 0≤a= span[2] || span[1] < 0 || span[2] > 1 + throw( + "expected a two-element vector [a,b] with 0≤a y == first(dims), dims) + base = first(dims) + L = length(dimension_inds(imap, d)) + + if !exact_grid + grid_points = range(span[1], span[2] - (span[2] - span[1]) / N; length=N) + else #exact_grid = true + if span[1] == 0 && span[2] == 1 + inv_step = min(Int(floor(log(base, N))), L) + if !(log(base, N) ≈ inv_step) + @warn "rounding $N down to $(Int(base^inv_step)) exact gridpoints!" + end + # now 1/inv_step should provide the step + grid_points = collect(span[1]:(1 / base^inv_step):span[2])[1:(end - 1)] + + else + + #get a count of the number of gridpoints within the span + points_in_span = floor(span[end] * base^L) - ceil(span[1] * base^L) + 1 + #TODO: figure out a way to calculate this without exponentiating to the power of L + + #exclude the endpoint in the count + if floor(span[end] * base^L) == span[end] * base^L + points_in_span = points_in_span - 1 + end + + if points_in_span <= 0 + @warn "No exact gridpoints found in this span!" + grid_points = [] + else + oldN = N + stepsize = ceil(points_in_span / N) + N = Int(floor(points_in_span / stepsize)) + 1 + startval = ceil(span[1] * base^L) / base^L #startval is the smallest grid point ≥ span[1] + + if startval + (N - 1) * stepsize / base^L >= span[2] + N = N - 1 + end + + if N < oldN + @warn "rounding $oldN down to $N exact gridpoints to maintain equal spacing." + end + + grid_points = [startval + i * (stepsize / base^L) for i in 0:(N - 1)] + end + end + end + + #add enforced points in naively + for point in enforced + if point >= span[2] || point < span[1] + @warn "enforced point $point outside of span $span, not including it" + continue + end + nearest_idx = searchsortedfirst(grid_points, point) + if nearest_idx > length(grid_points) || grid_points[nearest_idx] != point + insert!(grid_points, nearest_idx, point) + end + end + + return grid_points +end + +function grid_points( + imap::RealIndexMap, d::Int; kwargs... +) dims = dim.(dimension_inds(imap, d)) @assert all(y -> y == first(dims), dims) - base = float(first(dims)) + base = dims[d] L = length(dimension_inds(imap, d)) - a = round(base^L / N) - grid_points = [i * (a / base^L) for i in 0:(N + 1)] - return filter(x -> x < 1, grid_points) + return grid_points(imap, base^L, d; kwargs...) end + + + +""" + Picks a random grid point from `imap` given a dimension +""" +function rand_p(rng::AbstractRNG, imap::RealIndexMap, d::Integer) + dims = dim.(dimension_inds(imap, d)) + @assert all(y -> y == first(dims), dims) + base = dims[d] + L = length(dimension_inds(imap, d)) + return rand(rng, 0:(base^L - 1)) / base^L +end \ No newline at end of file diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl index 66b0659..1676f33 100644 --- a/src/interpolation_functions.jl +++ b/src/interpolation_functions.jl @@ -280,7 +280,7 @@ function data_itensornetwork(s::IndsNetworkMap, data, domain=nothing, interpolat end # Specifies how the function should be defined between data points f = interpolation_mode(domain, data; extrapolation_bc=Line()) - g = x... -> f(x...) + g = (x...) -> f(x...) return function_itensornetwork(s, g; kwargs...) end diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 79c05cb..6064bc3 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -2,7 +2,7 @@ using Test using ITensorNumericalAnalysis using NamedGraphs: vertices -using NamedGraphs.NamedGraphGenerators: named_grid +using NamedGraphs.NamedGraphGenerators: named_grid, named_comb_tree using NamedGraphs.GraphsExtensions: is_tree using ITensors: siteinds, inds using Dictionaries: Dictionary @@ -80,7 +80,8 @@ Random.seed!(1234) N = 125 a = 0.12 b = 0.95 - test_gridpoints = grid_points(s, N, 1, [a, b]) + + test_gridpoints = grid_points(s, N, 1, span=[a, b]) points_in_span = floor(b * base^(L / 2)) - ceil(a * base^(L / 2)) + 1 N_gridpoints = Int(floor(points_in_span / ceil(points_in_span / N))) + 1 @@ -97,7 +98,7 @@ Random.seed!(1234) N = 32 a = 0.25 b = 0.5 - test2 = grid_points(s, N, 1, [a, b]) + test2 = grid_points(s, N, 1; span=[a, b]) @test length(test2) == N @test test2[1] >= a @test test2[end] < b From bac29f1b9cc8c4cf7827ea1e4fab90c27a1ad79e Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Mon, 4 Nov 2024 23:44:09 -0800 Subject: [PATCH 18/31] formatting --- src/IndexMaps/abstractindexmap.jl | 2 +- src/IndexMaps/complexindexmap.jl | 3 ++- src/IndexMaps/realindexmap.jl | 15 ++++++++------- src/interpolation_functions.jl | 26 ++++++++++---------------- test/test_indexmaps.jl | 16 ++++++++-------- 5 files changed, 29 insertions(+), 33 deletions(-) diff --git a/src/IndexMaps/abstractindexmap.jl b/src/IndexMaps/abstractindexmap.jl index f118457..927b2a8 100644 --- a/src/IndexMaps/abstractindexmap.jl +++ b/src/IndexMaps/abstractindexmap.jl @@ -109,4 +109,4 @@ function rand_p(rng::AbstractRNG, imap::AbstractIndexMap) return [rand_p(rng, imap, i) for i in 1:dimension(imap)] end -rand_p(imap::AbstractIndexMap, args...) = rand_p(default_rng(), imap, args...) \ No newline at end of file +rand_p(imap::AbstractIndexMap, args...) = rand_p(default_rng(), imap, args...) diff --git a/src/IndexMaps/complexindexmap.jl b/src/IndexMaps/complexindexmap.jl index f1dd2a8..1c75f20 100644 --- a/src/IndexMaps/complexindexmap.jl +++ b/src/IndexMaps/complexindexmap.jl @@ -152,5 +152,6 @@ function rand_p(rng::AbstractRNG, imap::ComplexIndexMap, d::Integer) @assert all(y -> y == first(dims), dims) base = float(first(dims)) Lre, Lim = length(real_indices(imap, d)), length(imag_indices(imap, d)) - return rand(rng, 0:(base^Lre - 1)) / base^Lre + im * rand(rng, 0:(base^Lim - 1)) / base^Lim + return rand(rng, 0:(base^Lre - 1)) / base^Lre + + im * rand(rng, 0:(base^Lim - 1)) / base^Lim end diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index a23a807..8e9fe82 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -91,7 +91,12 @@ end - `enforced::AbstractVector{<:Number}`: A list of points that we want to enforce to show up in the grid. """ function grid_points( - imap::RealIndexMap, N::Int, d::Int; span::AbstractVector{<:Number}=[0,1], exact_grid::Bool=true, enforced=[] + imap::RealIndexMap, + N::Int, + d::Int; + span::AbstractVector{<:Number}=[0, 1], + exact_grid::Bool=true, + enforced=[], ) if length(span) != 2 || span[1] >= span[2] || span[1] < 0 || span[2] > 1 throw( @@ -163,9 +168,7 @@ function grid_points( return grid_points end -function grid_points( - imap::RealIndexMap, d::Int; kwargs... -) +function grid_points(imap::RealIndexMap, d::Int; kwargs...) dims = dim.(dimension_inds(imap, d)) @assert all(y -> y == first(dims), dims) base = dims[d] @@ -173,8 +176,6 @@ function grid_points( return grid_points(imap, base^L, d; kwargs...) end - - """ Picks a random grid point from `imap` given a dimension """ @@ -184,4 +185,4 @@ function rand_p(rng::AbstractRNG, imap::RealIndexMap, d::Integer) base = dims[d] L = length(dimension_inds(imap, d)) return rand(rng, 0:(base^L - 1)) / base^L -end \ No newline at end of file +end diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl index 1676f33..98118f1 100644 --- a/src/interpolation_functions.jl +++ b/src/interpolation_functions.jl @@ -16,11 +16,7 @@ end """ Build the function f(x) = coeffs[1] + ∑_{k=1}^{n} coeffs[2k]*sin(2kπx) + ∑_{k=1}^{n} coeffs[2k+1]*cos(2kπx) """ function fourier_itensornetwork( - s::IndsNetworkMap, - coeffs::Vector{<:Number}; - dim::Int=1, - min_threshold=1e-15, - cutoff=1e-16, + s::IndsNetworkMap, coeffs::Vector{<:Number}; dim::Int=1, min_threshold=1e-15, cutoff=1e-16 ) n = length(coeffs) if n < 1 @@ -66,10 +62,7 @@ end """ Build the function f(x) = ∑_{k=1}^n coeffs[k] * T_k(x) where T_k(x) is the k-th Chebyshev polynomial. """ function chebyshev_itensornetwork( - s::IndsNetworkMap, - coeffs::Vector{<:Number}; - dim::Int=1, - cutoff=1e-16, + s::IndsNetworkMap, coeffs::Vector{<:Number}; dim::Int=1, cutoff=1e-16 ) n = length(coeffs) if n <= 0 @@ -94,10 +87,7 @@ end """ Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are chebyshev polynomials """ function chebyshev_2D_itensornetwork( - s::IndsNetworkMap, - coeffs::Matrix{<:Number}; - dims::Vector{Int}=[1, 2], - cutoff=1e-16, + s::IndsNetworkMap, coeffs::Matrix{<:Number}; dims::Vector{Int}=[1, 2], cutoff=1e-16 ) n = size(coeffs)[1] m = size(coeffs)[2] @@ -270,16 +260,20 @@ end - all other kwargs are inherited from `function_itensornetwork` """ -function data_itensornetwork(s::IndsNetworkMap, data, domain=nothing, interpolation_mode=LinearInterpolation; kwargs...) +function data_itensornetwork( + s::IndsNetworkMap, data, domain=nothing, interpolation_mode=LinearInterpolation; kwargs... +) dimensionality = length(size(data)) if isnothing(domain) - domain = Tuple([grid_points(s, size(data)[i], i; exact_grid=false) for i in 1:dimensionality]) + domain = Tuple([ + grid_points(s, size(data)[i], i; exact_grid=false) for i in 1:dimensionality + ]) end if map(length, domain) != size(data) throw("shape of data and domain do not match!") end # Specifies how the function should be defined between data points - f = interpolation_mode(domain, data; extrapolation_bc=Line()) + f = interpolation_mode(domain, data; extrapolation_bc=Line()) g = (x...) -> f(x...) return function_itensornetwork(s, g; kwargs...) end diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 6064bc3..424d7f8 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -75,17 +75,17 @@ Random.seed!(1234) base = 2 g = named_comb_tree((2, L ÷ 2)) s = continuous_siteinds(g; map_dimension=2) - + #first set -- irregular span N = 125 a = 0.12 b = 0.95 - test_gridpoints = grid_points(s, N, 1, span=[a, b]) - + test_gridpoints = grid_points(s, N, 1; span=[a, b]) + points_in_span = floor(b * base^(L / 2)) - ceil(a * base^(L / 2)) + 1 N_gridpoints = Int(floor(points_in_span / ceil(points_in_span / N))) + 1 - + @test length(test_gridpoints) == N_gridpoints @test test_gridpoints[1] >= a @test test_gridpoints[end] < b @@ -93,7 +93,7 @@ Random.seed!(1234) left = (test_gridpoints[1] - a) right = (b - test_gridpoints[end]) @test internal >= left && internal >= right - + #second set N = 32 a = 0.25 @@ -106,7 +106,7 @@ Random.seed!(1234) left = (test2[1] - a) right = (b - test2[end]) @test internal >= left && internal >= right - + #third set test3 = grid_points(s, 1) @test length(test3) == 256 @@ -116,14 +116,14 @@ Random.seed!(1234) left = (test3[1] - a) right = (b - test3[end]) @test internal >= left && internal >= right - + #test the rand_p() function to see if it succeeds rng = Random.Xoshiro(42) rand_gridpoint1 = rand_p(rng, s) rand_gridpoint2 = rand_p(rng, s, 1) default_rng_gridpoint1 = rand_p(s) default_rng_gridpoint2 = rand_p(s, 1) - + #fourth set -- very large L L = 140 base = 2 From 3e37e3253621caf1d247aee0d709c1e1bde69a55 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Thu, 7 Nov 2024 08:19:48 -0800 Subject: [PATCH 19/31] add test cases for interpolation_functions --- examples/2D_function_into_ITN.jl | 4 +- src/IndexMaps/realindexmap.jl | 2 + src/interpolation_functions.jl | 14 ++++++- test/test_examples.jl | 5 ++- test/test_interpolations.jl | 68 ++++++++++++++++++++++++++++++++ 5 files changed, 88 insertions(+), 5 deletions(-) create mode 100644 test/test_interpolations.jl diff --git a/examples/2D_function_into_ITN.jl b/examples/2D_function_into_ITN.jl index fe11064..30d0145 100644 --- a/examples/2D_function_into_ITN.jl +++ b/examples/2D_function_into_ITN.jl @@ -25,8 +25,8 @@ y_vals = grid_points(s, length(x_vals), 2) f(x, y) = exp(-((x - 0.5)^2 + (y - 0.5)^2) / 0.05) -ψ_f = function_itn(s, f; mode="fourier", cutoff=1e-3, max_coeffs=400, by_mag=true) -ψ_c = function_itn(s, f; mode="chebyshev", cutoff=1e-3, max_coeffs=400, by_mag=true) +ψ_f = function_itn(s, f; mode="fourier", chop_level=1e-3, max_coeffs=400, by_mag=true) +ψ_c = function_itn(s, f; mode="chebyshev", chop_level=1e-3, max_coeffs=400, by_mag=true) ψ_f = truncate(ψ_f; cutoff=1e-16) ψ_c = truncate(ψ_c; cutoff=1e-16) diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index 8e9fe82..d0475e2 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -176,6 +176,8 @@ function grid_points(imap::RealIndexMap, d::Int; kwargs...) return grid_points(imap, base^L, d; kwargs...) end +grid_points(imap::RealIndexMap; kwargs...) = grid_points(imap, 1; kwargs...) + """ Picks a random grid point from `imap` given a dimension """ diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl index 98118f1..b924b98 100644 --- a/src/interpolation_functions.jl +++ b/src/interpolation_functions.jl @@ -264,17 +264,27 @@ function data_itensornetwork( s::IndsNetworkMap, data, domain=nothing, interpolation_mode=LinearInterpolation; kwargs... ) dimensionality = length(size(data)) + if dimensionality > 2 + throw("cannot handle dimensionality > 2") + end + if isnothing(domain) domain = Tuple([ grid_points(s, size(data)[i], i; exact_grid=false) for i in 1:dimensionality ]) end - if map(length, domain) != size(data) + if dimensionality == 1 && length(domain) != length(data) || + dimensionality > 1 && map(length, domain) != size(data) throw("shape of data and domain do not match!") end # Specifies how the function should be defined between data points f = interpolation_mode(domain, data; extrapolation_bc=Line()) - g = (x...) -> f(x...) + + if dimensionality == 1 + g = (x) -> f(x) + elseif dimensionality == 2 + g = (x, y) -> f(x, y) + end return function_itensornetwork(s, g; kwargs...) end diff --git a/test/test_examples.jl b/test/test_examples.jl index a676cdf..6ec7622 100644 --- a/test/test_examples.jl +++ b/test/test_examples.jl @@ -4,7 +4,10 @@ using Test: @testset @testset "Test examples" begin example_files = [ - "2d_laplace_solver.jl", "construct_multi_dimensional_function.jl", "fredholm_solver.jl" + "2d_laplace_solver.jl", + "construct_multi_dimensional_function.jl", + "fredholm_solver.jl", + "2D_function_into_ITN.jl", ] @testset "Test $example_file" for example_file in example_files include(joinpath(pkgdir(ITensorNumericalAnalysis), "examples", example_file)) diff --git a/test/test_interpolations.jl b/test/test_interpolations.jl new file mode 100644 index 0000000..4157c89 --- /dev/null +++ b/test/test_interpolations.jl @@ -0,0 +1,68 @@ +using Test +using ITensorNumericalAnalysis +using NamedGraphs.NamedGraphGenerators: named_comb_tree +using Plots +@testset "test interpolations" begin + @testset "interpolate 1D function" begin + L = 10 + g = named_comb_tree((1, L)) + s = continuous_siteinds(g) + f1(x) = 10x^4 - 5x^3 - 20x^2 + 3x + 10 + ψ_c = function_itn(s, f1; mode="chebyshev", chop_level=1e-5) + ψ_c = truncate(ψ_c; cutoff=1e-16) + x = 0.375 + a = f1(x) + b = real(ITensorNumericalAnalysis.evaluate(ψ_c, [x])) + ε = 0.0001 #numerical precision limit + @test abs(a - b) <= ε #test that they evaluate to close to the same point + end + + @testset "interpolate 2D function" begin + L = 12 + #comb tree + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + f2(x, y) = exp(-((x - 0.5)^2 + (y - 0.5)^2) / 0.05) + ψ_c = function_itn(s, f2; mode="chebyshev", chop_level=1e-5) + ψ_c = truncate(ψ_c; cutoff=1e-16) + x, y = 0.375, 0.125 + a = f2(x, y) + b = real(ITensorNumericalAnalysis.evaluate(ψ_c, [x, y])) + ε = 0.0001 #numerical precision limit + @test abs(a - b) <= ε #test that they evaluate to close to the same point + end + + @testset "interpolate 1D data" begin + L = 10 + g = named_comb_tree((1, L)) + s = continuous_siteinds(g) + x_vals = collect(range(0.0, 1.0; length=200)) + f3(x) = 10 * x^4 - 5 * x^3 - 20 * x^2 + 3 * x + 10 + data = [f3(x) for x in x_vals] + ψ_c = data_itn(s, data, x_vals; mode="chebyshev", chop_level=1e-5) + ψ_c = truncate(ψ_c; cutoff=1e-16) + x = 0.375 + a = f3(x) + b = real(ITensorNumericalAnalysis.evaluate(ψ_c, [x])) + ε = 0.0001 #numerical precision limit + @test abs(a - b) <= ε #test that they evaluate to close to the same point + end + + @testset "interpolate 2D data" begin + L = 12 + #comb tree + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + f4(x, y) = exp(-((x - 0.5)^2 + (y - 0.5)^2) / 0.05) + x_vals, y_vals = collect(range(0.0, 1.0; length=200)), + collect(range(0.0, 1.0; length=200)) + data = [f4(x, y) for x in x_vals, y in y_vals] + ψ_c = data_itn(s, data, (x_vals, y_vals); mode="chebyshev", chop_level=1e-5) + ψ_c = truncate(ψ_c; cutoff=1e-16) + x, y = 0.375, 0.125 + a = f4(x, y) + b = real(ITensorNumericalAnalysis.evaluate(ψ_c, [x, y])) + ε = 0.0001 #numerical precision limit + @test abs(a - b) <= ε #test that they evaluate to close to the same point + end +end From 554100b8f249675086f955ad3a381eb3927d2a51 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Thu, 7 Nov 2024 08:49:08 -0800 Subject: [PATCH 20/31] added dimension specification inside interpolation_functions and made rand_p robust to big L --- src/IndexMaps/complexindexmap.jl | 4 ++-- src/IndexMaps/realindexmap.jl | 2 +- src/interpolation_functions.jl | 22 ++++++++++------------ test/test_indexmaps.jl | 14 +++++++------- 4 files changed, 20 insertions(+), 22 deletions(-) diff --git a/src/IndexMaps/complexindexmap.jl b/src/IndexMaps/complexindexmap.jl index 1c75f20..d197667 100644 --- a/src/IndexMaps/complexindexmap.jl +++ b/src/IndexMaps/complexindexmap.jl @@ -152,6 +152,6 @@ function rand_p(rng::AbstractRNG, imap::ComplexIndexMap, d::Integer) @assert all(y -> y == first(dims), dims) base = float(first(dims)) Lre, Lim = length(real_indices(imap, d)), length(imag_indices(imap, d)) - return rand(rng, 0:(base^Lre - 1)) / base^Lre + - im * rand(rng, 0:(base^Lim - 1)) / base^Lim + return rand(rng, 0:(big(base)^Lre - 1)) / big(base)^Lre + + im * rand(rng, 0:(big(base)^Lim - 1)) / big(base)^Lim end diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index d0475e2..c9d85fc 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -186,5 +186,5 @@ function rand_p(rng::AbstractRNG, imap::RealIndexMap, d::Integer) @assert all(y -> y == first(dims), dims) base = dims[d] L = length(dimension_inds(imap, d)) - return rand(rng, 0:(base^L - 1)) / base^L + return rand(rng, 0:(big(base)^L - 1)) / big(base)^L end diff --git a/src/interpolation_functions.jl b/src/interpolation_functions.jl index b924b98..a6b37b4 100644 --- a/src/interpolation_functions.jl +++ b/src/interpolation_functions.jl @@ -4,9 +4,7 @@ using Interpolations: LinearInterpolation, Line, CubicSplineInterpolation """ Helper function for fourier_itensornetwork and fourier_2D_itensornetwork """ function fourier_term(s::IndsNetworkMap, j::Integer, dim::Integer) - if j == 1 - return const_itn(s) - elseif j % 2 == 0 + if j % 2 == 0 return sin_itn(s; k=j * π, dim) else return cos_itn(s; k=(j - 1) * π, dim) @@ -47,7 +45,7 @@ function fourier_2D_itensornetwork( throw("coeffs must be nonempty") end - ψ = const_itn(s; c=0) + ψ = poly_itn(s, [0]; dim=dims[1]) for j in 1:n for k in 1:m if abs(coeffs[j, k]) > min_threshold @@ -72,13 +70,13 @@ function chebyshev_itensornetwork( end #Clenshaw Evaluation method - uses idea from https://arxiv.org/pdf/2407.09609 - y_n = const_itn(s; c=0) - y_n1 = const_itn(s; c=0) + y_n = poly_itn(s, [0]; dim) #const_itn(s; c=0) + y_n1 = poly_itn(s, [0]; dim) #const_itn(s; c=0) # y_n-1 = c_n-1 - y_n+1 + (4x-2) * y_n for d in n:-1:1 old_y_n = truncate(y_n; cutoff) - y_n = coeffs[d] * const_itn(s) + (-1) * y_n1 + poly_itn(s, [-2, 4]; dim) * old_y_n + y_n = poly_itn(s, [coeffs[d]]; dim) + (-1) * y_n1 + poly_itn(s, [-2, 4]; dim) * old_y_n y_n1 = old_y_n end @@ -96,18 +94,18 @@ function chebyshev_2D_itensornetwork( end #Clenshaw Evaluation method - uses idea from https://arxiv.org/pdf/2407.09609 - y_n = const_itn(s; c=0) - y_n1 = const_itn(s; c=0) + y_n = poly_itn(s, [0]; dim=dims[2]) #const_itn(s; c=0) # + y_n1 = poly_itn(s, [0]; dim=dims[2]) #const_itn(s; c=0) # for j in m:-1:1 #determine the weighted sum of chebyshev polynomials of x - x_n = const_itn(s; c=0) - x_n1 = const_itn(s; c=0) + x_n = poly_itn(s, [0]; dim=dims[1]) #const_itn(s; c=0) # + x_n1 = poly_itn(s, [0]; dim=dims[1]) #const_itn(s; c=0) # for i in n:-1:1 # x_n-1 = c_n-1 - x_n+1 + (4x-2) * x_n old_x_n = truncate(x_n; cutoff) x_n = - coeffs[i, j] * const_itn(s) + + poly_itn(s, [coeffs[i, j]]; dim=dims[1]) + #coeffs[i, j] * const_itn(s) + # (-1) * x_n1 + poly_itn(s, [-2, 4]; dim=dims[1]) * old_x_n x_n1 = old_x_n diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 424d7f8..7dfb5e9 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -117,13 +117,6 @@ Random.seed!(1234) right = (b - test3[end]) @test internal >= left && internal >= right - #test the rand_p() function to see if it succeeds - rng = Random.Xoshiro(42) - rand_gridpoint1 = rand_p(rng, s) - rand_gridpoint2 = rand_p(rng, s, 1) - default_rng_gridpoint1 = rand_p(s) - default_rng_gridpoint2 = rand_p(s, 1) - #fourth set -- very large L L = 140 base = 2 @@ -131,5 +124,12 @@ Random.seed!(1234) s = continuous_siteinds(g; map_dimension=2) n_grid = 16 @test length(grid_points(s, n_grid, 1)) == n_grid + + #test the rand_p() function to see if it succeeds on large L + rng = Random.Xoshiro(42) + rand_gridpoint1 = rand_p(rng, s) + rand_gridpoint2 = rand_p(rng, s, 1) + default_rng_gridpoint1 = rand_p(s) + default_rng_gridpoint2 = rand_p(s, 1) end end From 28ad64da799979080a242cd40010ce6b1ab3612c Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Fri, 8 Nov 2024 08:38:02 -0800 Subject: [PATCH 21/31] removed interpolation changes --- Project.toml | 4 - examples/2D_function_into_ITN.jl | 64 ------- src/ITensorNumericalAnalysis.jl | 9 +- src/interpolation_functions.jl | 292 ------------------------------- test/test_examples.jl | 3 +- test/test_interpolations.jl | 68 ------- 6 files changed, 2 insertions(+), 438 deletions(-) delete mode 100644 examples/2D_function_into_ITN.jl delete mode 100644 src/interpolation_functions.jl delete mode 100644 test/test_interpolations.jl diff --git a/Project.toml b/Project.toml index 11edff5..2209623 100644 --- a/Project.toml +++ b/Project.toml @@ -4,26 +4,22 @@ authors = ["Joseph Tindall ", "Ryan Levy min_threshold - ψ += coeffs[i] * fourier_term(s, i, dim) - ψ = truncate(ψ; cutoff) - end - end - return ψ -end - -""" Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are sines/cosines. """ -function fourier_2D_itensornetwork( - s::IndsNetworkMap, - coeffs::Matrix{<:Number}; - dims::Vector{Int}=[1, 2], - min_threshold=1e-15, - cutoff=1e-16, -) - n = size(coeffs)[1] - m = size(coeffs)[2] - if n < 1 || m < 1 - throw("coeffs must be nonempty") - end - - ψ = poly_itn(s, [0]; dim=dims[1]) - for j in 1:n - for k in 1:m - if abs(coeffs[j, k]) > min_threshold - ψ += coeffs[j, k] * fourier_term(s, j, dims[1]) * fourier_term(s, k, dims[2]) - ψ = truncate(ψ; cutoff) - end - end - end - return ψ -end - -""" Build the function f(x) = ∑_{k=1}^n coeffs[k] * T_k(x) - where T_k(x) is the k-th Chebyshev polynomial. """ -function chebyshev_itensornetwork( - s::IndsNetworkMap, coeffs::Vector{<:Number}; dim::Int=1, cutoff=1e-16 -) - n = length(coeffs) - if n <= 0 - throw("coeffs must be nonempty") - elseif n == 1 - return coeffs[1] * const_itn(s) - end - - #Clenshaw Evaluation method - uses idea from https://arxiv.org/pdf/2407.09609 - y_n = poly_itn(s, [0]; dim) #const_itn(s; c=0) - y_n1 = poly_itn(s, [0]; dim) #const_itn(s; c=0) - - # y_n-1 = c_n-1 - y_n+1 + (4x-2) * y_n - for d in n:-1:1 - old_y_n = truncate(y_n; cutoff) - y_n = poly_itn(s, [coeffs[d]]; dim) + (-1) * y_n1 + poly_itn(s, [-2, 4]; dim) * old_y_n - y_n1 = old_y_n - end - - return truncate(y_n + poly_itn(s, [1, -2]; dim) * y_n1; cutoff) -end - -""" Build the function f(x,y) = ∑_{j=1}^n ∑_{k=1}^n coeffs[j, k]*ϕ_j(x)*ϕ_k(y) where ϕ_j and ϕ_k are chebyshev polynomials """ -function chebyshev_2D_itensornetwork( - s::IndsNetworkMap, coeffs::Matrix{<:Number}; dims::Vector{Int}=[1, 2], cutoff=1e-16 -) - n = size(coeffs)[1] - m = size(coeffs)[2] - if n < 1 || m < 1 - throw("coeffs must be nonempty") - end - - #Clenshaw Evaluation method - uses idea from https://arxiv.org/pdf/2407.09609 - y_n = poly_itn(s, [0]; dim=dims[2]) #const_itn(s; c=0) # - y_n1 = poly_itn(s, [0]; dim=dims[2]) #const_itn(s; c=0) # - - for j in m:-1:1 - #determine the weighted sum of chebyshev polynomials of x - x_n = poly_itn(s, [0]; dim=dims[1]) #const_itn(s; c=0) # - x_n1 = poly_itn(s, [0]; dim=dims[1]) #const_itn(s; c=0) # - for i in n:-1:1 - # x_n-1 = c_n-1 - x_n+1 + (4x-2) * x_n - old_x_n = truncate(x_n; cutoff) - x_n = - poly_itn(s, [coeffs[i, j]]; dim=dims[1]) + #coeffs[i, j] * const_itn(s) + # - (-1) * x_n1 + - poly_itn(s, [-2, 4]; dim=dims[1]) * old_x_n - x_n1 = old_x_n - end - coeff_j = truncate(x_n + poly_itn(s, [1, -2]; dim=dims[1]) * x_n1; cutoff) - - # y_n-1 = c_n-1 - y_n+1 + (4y-2) * y_n - old_y_n = truncate(y_n; cutoff) - y_n = coeff_j + (-1) * y_n1 + poly_itn(s, [-2, 4]; dim=dims[2]) * old_y_n - y_n1 = old_y_n - end - - return truncate(y_n + poly_itn(s, [1, -2]; dim=dims[2]) * y_n1; cutoff) -end - -""" Helper function for function_itensornetwork (1D case) """ -function greatest_n(coeffs, n) - if n < 1 - throw("n must be greater than 0") - end - sorted_indices = sortperm(coeffs; by=abs, rev=true) - top_n_indices = sorted_indices[1:min(n, length(coeffs))] - output = zeros(eltype(coeffs), length(coeffs)) - output[top_n_indices] = coeffs[top_n_indices] - last_non_zero = findlast(output .!= 0) - if isempty(last_non_zero) - return [] - end - return output[1:last_non_zero] -end - -""" Helper function for function_itensornetwork (2D case) """ -function greatest_n_2d(coeffs_matrix, n) - if n < 1 - throw("n must be greater than 0") - end - dims = size(coeffs_matrix) - coeffs = vec(coeffs_matrix) - sorted_indices = sortperm(coeffs; by=abs, rev=true) - top_n_indices = sorted_indices[1:min(n, length(coeffs))] - output = zeros(eltype(coeffs), length(coeffs)) - output[top_n_indices] = coeffs[top_n_indices] - matrix = reshape(output, dims) - last_row, last_col = size(matrix) - while last_row > 0 && all(matrix[last_row, :] .== 0) - last_row -= 1 - end - while last_col > 0 && all(matrix[:, last_col] .== 0) - last_col -= 1 - end - return matrix[1:last_row, 1:last_col] -end - -""" - function_itensornetwork(s,f, chop_level=1e-3, max_coeffs=100, mode="fourier", by_mag=true, cutoff=1e-16) - Takes in a function `f` as a black box, outputs a tensor network approximation using Fourier or Chebyshev series. Supports 1D or 2D functions. - - #Arguments - - `s`: IndsNetworkMap - - `f`: a real-valued function on domain [0,1] or [0,1]⊗[0,1] which can be given as a black box - - `chop_level`: (default=1e-3) specifies at what level of precision should the fourier/chebyshev coefficients be chopped off at - - `max_coeffs`: the maximum number of coefficients allowed in 1D. In 2D, it is the maximum degree of a coefficient in each dimension - - `mode`: ["fourier", "chebyshev"] "fourier" uses a fourier basis and "chebyshev" uses a chebyshev polynomial basis - - `by_mag`: boolean. if false, will use the `max_coeffs` coefficients of lowest degree. if true, will use the `max_coeffs` coefficients of greatest absolute magnitude. - - `cutoff`: (default=1e-16) at what cutoff the repeated calls to truncate() are performed at -""" -function function_itensornetwork( - s::IndsNetworkMap, - f::Function; - chop_level::Float64=1e-3, - max_coeffs::Integer=100, - mode="fourier", - by_mag=false, - cutoff=1e-16, -) - - #get the number of inputs to f - method_list = methods(f).ms - arg_counts = [length(m.sig.parameters) - 1 for m in method_list] - num_inputs = arg_counts[1] - - """ 1D functions """ - if num_inputs == 1 - if mode == "fourier" - S = Fourier(Interval(0.0, 1.0)) - f_fourier = Fun(f, S) - a = chop(f_fourier, chop_level) - if by_mag - cf = greatest_n(coefficients(a), max_coeffs) - else - cf = ncoefficients(a) > max_coeffs ? coefficients(a)[1:max_coeffs] : coefficients(a) - end - ψ = fourier_itensornetwork(s, cf; cutoff) - elseif mode == "chebyshev" - T = Chebyshev(Interval(0.0, 1.0)) - f_chebyshev = Fun(f, T) - a = chop(f_chebyshev, chop_level) - if by_mag - cf = greatest_n(coefficients(a), max_coeffs) - else - cf = ncoefficients(a) > max_coeffs ? coefficients(a)[1:max_coeffs] : coefficients(a) - end - ψ = chebyshev_itensornetwork(s, cf; cutoff) - else - throw("mode $mode not recognized") - end - return ψ - - """ 2D functions """ - elseif num_inputs == 2 - if mode == "fourier" - S = Fourier(Interval(0.0, 1.0))^2 - f_fourier = ProductFun(f, S; tol=chop_level) - if by_mag - cf = greatest_n_2d(coefficients(f_fourier), max_coeffs) - else - a = min(max_coeffs, size(coefficients(f_fourier))[1]) - b = min(max_coeffs, size(coefficients(f_fourier))[2]) - cf = coefficients(f_fourier)[1:a, 1:b] - end - ψ = fourier_2D_itensornetwork(s, cf; dims=[1, 2], cutoff) - elseif mode == "chebyshev" - T = Chebyshev(Interval(0.0, 1.0))^2 - f_chebyshev = ProductFun(f, T; tol=chop_level) - if by_mag - cf = greatest_n_2d(coefficients(f_chebyshev), max_coeffs) - else - a = min(max_coeffs, size(coefficients(f_chebyshev))[1]) - b = min(max_coeffs, size(coefficients(f_chebyshev))[2]) - cf = coefficients(f_chebyshev)[1:a, 1:b] - end - ψ = chebyshev_2D_itensornetwork(s, cf; dims=[1, 2], cutoff) - else - throw("mode $mode not recognized") - end - return ψ - else - throw("functions with $num_inputs inputs not supported.") - end -end - -""" - data_itensornetwork converts a list of numerical datapoints into an ITN by first converting it into a function. Can be 1D or 2D data. - - #Arguments - - `s`: IndsNetworkMap - - `data`: a real-valued vector or matrix of data points - - `domain`: optional argument, specifies at what coordinates the data is located. Must match the shape of `data`. If left unspecified, data is treated as evenly spaced over [0,1]/[0,1]⊗[0,1]. - - `interpolation_mode`: Taken from Interpolations.jl. By default is `LinearInterpolation`, alternatively can be `CubicSplineInterpolation`. - - all other kwargs are inherited from `function_itensornetwork` - -""" -function data_itensornetwork( - s::IndsNetworkMap, data, domain=nothing, interpolation_mode=LinearInterpolation; kwargs... -) - dimensionality = length(size(data)) - if dimensionality > 2 - throw("cannot handle dimensionality > 2") - end - - if isnothing(domain) - domain = Tuple([ - grid_points(s, size(data)[i], i; exact_grid=false) for i in 1:dimensionality - ]) - end - if dimensionality == 1 && length(domain) != length(data) || - dimensionality > 1 && map(length, domain) != size(data) - throw("shape of data and domain do not match!") - end - # Specifies how the function should be defined between data points - f = interpolation_mode(domain, data; extrapolation_bc=Line()) - - if dimensionality == 1 - g = (x) -> f(x) - elseif dimensionality == 2 - g = (x, y) -> f(x, y) - end - return function_itensornetwork(s, g; kwargs...) -end - -const fourier_itn = fourier_itensornetwork -const chebyshev_itn = chebyshev_itensornetwork -const function_itn = function_itensornetwork -const data_itn = data_itensornetwork diff --git a/test/test_examples.jl b/test/test_examples.jl index 6ec7622..21a8e0c 100644 --- a/test/test_examples.jl +++ b/test/test_examples.jl @@ -6,8 +6,7 @@ using Test: @testset example_files = [ "2d_laplace_solver.jl", "construct_multi_dimensional_function.jl", - "fredholm_solver.jl", - "2D_function_into_ITN.jl", + "fredholm_solver.jl" ] @testset "Test $example_file" for example_file in example_files include(joinpath(pkgdir(ITensorNumericalAnalysis), "examples", example_file)) diff --git a/test/test_interpolations.jl b/test/test_interpolations.jl deleted file mode 100644 index 4157c89..0000000 --- a/test/test_interpolations.jl +++ /dev/null @@ -1,68 +0,0 @@ -using Test -using ITensorNumericalAnalysis -using NamedGraphs.NamedGraphGenerators: named_comb_tree -using Plots -@testset "test interpolations" begin - @testset "interpolate 1D function" begin - L = 10 - g = named_comb_tree((1, L)) - s = continuous_siteinds(g) - f1(x) = 10x^4 - 5x^3 - 20x^2 + 3x + 10 - ψ_c = function_itn(s, f1; mode="chebyshev", chop_level=1e-5) - ψ_c = truncate(ψ_c; cutoff=1e-16) - x = 0.375 - a = f1(x) - b = real(ITensorNumericalAnalysis.evaluate(ψ_c, [x])) - ε = 0.0001 #numerical precision limit - @test abs(a - b) <= ε #test that they evaluate to close to the same point - end - - @testset "interpolate 2D function" begin - L = 12 - #comb tree - g = named_comb_tree((2, L ÷ 2)) - s = continuous_siteinds(g; map_dimension=2) - f2(x, y) = exp(-((x - 0.5)^2 + (y - 0.5)^2) / 0.05) - ψ_c = function_itn(s, f2; mode="chebyshev", chop_level=1e-5) - ψ_c = truncate(ψ_c; cutoff=1e-16) - x, y = 0.375, 0.125 - a = f2(x, y) - b = real(ITensorNumericalAnalysis.evaluate(ψ_c, [x, y])) - ε = 0.0001 #numerical precision limit - @test abs(a - b) <= ε #test that they evaluate to close to the same point - end - - @testset "interpolate 1D data" begin - L = 10 - g = named_comb_tree((1, L)) - s = continuous_siteinds(g) - x_vals = collect(range(0.0, 1.0; length=200)) - f3(x) = 10 * x^4 - 5 * x^3 - 20 * x^2 + 3 * x + 10 - data = [f3(x) for x in x_vals] - ψ_c = data_itn(s, data, x_vals; mode="chebyshev", chop_level=1e-5) - ψ_c = truncate(ψ_c; cutoff=1e-16) - x = 0.375 - a = f3(x) - b = real(ITensorNumericalAnalysis.evaluate(ψ_c, [x])) - ε = 0.0001 #numerical precision limit - @test abs(a - b) <= ε #test that they evaluate to close to the same point - end - - @testset "interpolate 2D data" begin - L = 12 - #comb tree - g = named_comb_tree((2, L ÷ 2)) - s = continuous_siteinds(g; map_dimension=2) - f4(x, y) = exp(-((x - 0.5)^2 + (y - 0.5)^2) / 0.05) - x_vals, y_vals = collect(range(0.0, 1.0; length=200)), - collect(range(0.0, 1.0; length=200)) - data = [f4(x, y) for x in x_vals, y in y_vals] - ψ_c = data_itn(s, data, (x_vals, y_vals); mode="chebyshev", chop_level=1e-5) - ψ_c = truncate(ψ_c; cutoff=1e-16) - x, y = 0.375, 0.125 - a = f4(x, y) - b = real(ITensorNumericalAnalysis.evaluate(ψ_c, [x, y])) - ε = 0.0001 #numerical precision limit - @test abs(a - b) <= ε #test that they evaluate to close to the same point - end -end From fd31bb2ed74689a7d57b138a1e5a4f8219db6db7 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Fri, 8 Nov 2024 08:58:46 -0800 Subject: [PATCH 22/31] add GraphRecipes dep --- Project.toml | 1 + 1 file changed, 1 insertion(+) diff --git a/Project.toml b/Project.toml index 2209623..8fe28cb 100644 --- a/Project.toml +++ b/Project.toml @@ -6,6 +6,7 @@ version = "0.1.1" [deps] Dictionaries = "85a47980-9c8c-11e8-2b9f-f7ca1fa99fb4" Glob = "c27321d9-0574-5035-807b-f59d2c89b15c" +GraphRecipes = "bd48cda9-67a9-57be-86fa-5b3c104eda73" Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6" ITensorNetworks = "2919e153-833c-4bdc-8836-1ea460a35fc7" ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5" From 108d3aba82dc7895478250e7f9fe8d788ea031ab Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Fri, 8 Nov 2024 09:00:17 -0800 Subject: [PATCH 23/31] formatting --- src/ITensorNumericalAnalysis.jl | 9 +-------- test/test_examples.jl | 4 +--- 2 files changed, 2 insertions(+), 11 deletions(-) diff --git a/src/ITensorNumericalAnalysis.jl b/src/ITensorNumericalAnalysis.jl index a5eda32..4df1a0a 100644 --- a/src/ITensorNumericalAnalysis.jl +++ b/src/ITensorNumericalAnalysis.jl @@ -62,14 +62,7 @@ export const_itensornetwork, map_to_zeros, const_plane_op export const_itn, - poly_itn, - cosh_itn, - sinh_itn, - tanh_itn, - exp_itn, - sin_itn, - cos_itn, - rand_itn + poly_itn, cosh_itn, sinh_itn, tanh_itn, exp_itn, sin_itn, cos_itn, rand_itn export evaluate export operate, operator_proj, multiply diff --git a/test/test_examples.jl b/test/test_examples.jl index 21a8e0c..a676cdf 100644 --- a/test/test_examples.jl +++ b/test/test_examples.jl @@ -4,9 +4,7 @@ using Test: @testset @testset "Test examples" begin example_files = [ - "2d_laplace_solver.jl", - "construct_multi_dimensional_function.jl", - "fredholm_solver.jl" + "2d_laplace_solver.jl", "construct_multi_dimensional_function.jl", "fredholm_solver.jl" ] @testset "Test $example_file" for example_file in example_files include(joinpath(pkgdir(ITensorNumericalAnalysis), "examples", example_file)) From 8e319c23708e4dfa968f4b8afe91abe3b6269e77 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Wed, 13 Nov 2024 21:33:35 -0800 Subject: [PATCH 24/31] re-organize test sets for indexmaps --- test/test_indexmaps.jl | 51 +++++++++++++++++++++++++++++++++++------- 1 file changed, 43 insertions(+), 8 deletions(-) diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 7dfb5e9..64c895b 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -70,7 +70,11 @@ Random.seed!(1234) xyzvals ≈ xyzvals_approx end - @testset "test grid_points" begin +end + +@testset "grid_points tests" begin + + @testset "test grid_points irregular span" begin L = 16 base = 2 g = named_comb_tree((2, L ÷ 2)) @@ -93,6 +97,12 @@ Random.seed!(1234) left = (test_gridpoints[1] - a) right = (b - test_gridpoints[end]) @test internal >= left && internal >= right + end + + @testset "test grid_points spacing" begin + L = 16 + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) #second set N = 32 @@ -106,6 +116,14 @@ Random.seed!(1234) left = (test2[1] - a) right = (b - test2[end]) @test internal >= left && internal >= right + end + + @testset "test grid_points spacing 2" begin + L = 16 + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + a = 0.25 + b = 0.5 #third set test3 = grid_points(s, 1) @@ -116,7 +134,9 @@ Random.seed!(1234) left = (test3[1] - a) right = (b - test3[end]) @test internal >= left && internal >= right + end + @testset "test grid_points high precision" begin #fourth set -- very large L L = 140 base = 2 @@ -124,12 +144,27 @@ Random.seed!(1234) s = continuous_siteinds(g; map_dimension=2) n_grid = 16 @test length(grid_points(s, n_grid, 1)) == n_grid - - #test the rand_p() function to see if it succeeds on large L - rng = Random.Xoshiro(42) - rand_gridpoint1 = rand_p(rng, s) - rand_gridpoint2 = rand_p(rng, s, 1) - default_rng_gridpoint1 = rand_p(s) - default_rng_gridpoint2 = rand_p(s, 1) end end + +@testset "test rand_p" begin + #test the rand_p() function to see if it succeeds on large L + L = 140 + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + ψ = cos_itn(s; dim=1) * cos_itn(s; dim=2) + + #test the use of seedeed randomness + rng = Random.Xoshiro(42) + rand_gridpoint1 = rand_p(rng, s) + rand_gridpoint2 = rand_p(rng, s, 1) + x = real(ITensorNumericalAnalysis.evaluate(ψ, rand_gridpoint1)) + @test x >= -1 && x <= 1 # check to make sure ψ can be evaluated at these points + + #test the use of default rng + default_rng_gridpoint1 = rand_p(s) + default_rng_gridpoint2 = rand_p(s, 1) + y = real(ITensorNumericalAnalysis.evaluate(ψ, default_rng_gridpoint1)) + @test y >= -1 && y <= 1 # check to make sure ψ can be evaluated at these points + +end From f81e4bc9f0ea966682040c14bf2599c15fc0c0b6 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Wed, 13 Nov 2024 21:50:51 -0800 Subject: [PATCH 25/31] multi-dimensional grid_points --- src/IndexMaps/realindexmap.jl | 30 ++++++++++++++++++++---------- 1 file changed, 20 insertions(+), 10 deletions(-) diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index c9d85fc..9a9ca03 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -153,16 +153,9 @@ function grid_points( end end - #add enforced points in naively - for point in enforced - if point >= span[2] || point < span[1] - @warn "enforced point $point outside of span $span, not including it" - continue - end - nearest_idx = searchsortedfirst(grid_points, point) - if nearest_idx > length(grid_points) || grid_points[nearest_idx] != point - insert!(grid_points, nearest_idx, point) - end + #add enforced points + if !isempty(enforced) + grid_points = sort(vcat(grid_points, enforced_points)) end return grid_points @@ -178,6 +171,23 @@ end grid_points(imap::RealIndexMap; kwargs...) = grid_points(imap, 1; kwargs...) +#multi-dimensional grid_points +function grid_points(imap::RealIndexMap, Ns::Vector{Int}, dims::Vector{Int}; kwargs...) + if length(Ns) != length(dims) + @throw "length of Ns and dims do not match!" + end + coords = [grid_points(imap, pair[1], pair[2]; kwargs...) for pair in zip(Ns, dims)] + gp = Base.Iterators.product(coords...) + return [collect(point) for point in gp] +end + +function grid_points(imap::RealIndexMap, dims::Vector{Int}; kwargs...) + coords = [grid_points(imap, d; kwargs...) for d in dims] + gp = Base.Iterators.product(coords...) + return [collect(point) for point in gp] +end + + """ Picks a random grid point from `imap` given a dimension """ From 3923d7528f57b3ba4db7bb890aa6afb79a635277 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Wed, 13 Nov 2024 22:48:20 -0800 Subject: [PATCH 26/31] simplify grid_points exact_grid condition significantly --- src/IndexMaps/realindexmap.jl | 64 +++++++++++------------------------ test/test_indexmaps.jl | 10 +----- 2 files changed, 20 insertions(+), 54 deletions(-) diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index 9a9ca03..d59d288 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -103,64 +103,38 @@ function grid_points( "expected a two-element vector [a,b] with 0≤a y == first(dims), dims) base = first(dims) L = length(dimension_inds(imap, d)) - if !exact_grid - grid_points = range(span[1], span[2] - (span[2] - span[1]) / N; length=N) - else #exact_grid = true - if span[1] == 0 && span[2] == 1 - inv_step = min(Int(floor(log(base, N))), L) - if !(log(base, N) ≈ inv_step) - @warn "rounding $N down to $(Int(base^inv_step)) exact gridpoints!" - end - # now 1/inv_step should provide the step - grid_points = collect(span[1]:(1 / base^inv_step):span[2])[1:(end - 1)] - - else - - #get a count of the number of gridpoints within the span - points_in_span = floor(span[end] * base^L) - ceil(span[1] * base^L) + 1 - #TODO: figure out a way to calculate this without exponentiating to the power of L - - #exclude the endpoint in the count - if floor(span[end] * base^L) == span[end] * base^L - points_in_span = points_in_span - 1 - end - - if points_in_span <= 0 - @warn "No exact gridpoints found in this span!" - grid_points = [] - else - oldN = N - stepsize = ceil(points_in_span / N) - N = Int(floor(points_in_span / stepsize)) + 1 - startval = ceil(span[1] * base^L) / base^L #startval is the smallest grid point ≥ span[1] - - if startval + (N - 1) * stepsize / base^L >= span[2] - N = N - 1 - end - - if N < oldN - @warn "rounding $oldN down to $N exact gridpoints to maintain equal spacing." - end - - grid_points = [startval + i * (stepsize / base^L) for i in 0:(N - 1)] - end + # generate grid_points within the span (exclusive of right endpoint) + grid_points = collect(range(span[1], span[2] - (span[2] - span[1]) / N; length=N)) + if exact_grid + for (i, point) in enumerate(grid_points) + grid_points[i] = round_to_nearest_exact_point(point, L) end + # define lambda function + # round_near = point -> round_to_nearest_exact_point(point, L) + # grid_points = map(round_near, grid_points) + grid_points = unique(grid_points) end - #add enforced points + # add enforced points if !isempty(enforced) - grid_points = sort(vcat(grid_points, enforced_points)) + grid_points = sort(unique(vcat(grid_points, enforced_points))) end return grid_points end +function round_to_nearest_exact_point(point::Number, L::Int) + if point < 0 || point >= 1 + throw("Input point must be between 0 and 1") + end + return round(point * 2.0^L) / 2.0^L +end + function grid_points(imap::RealIndexMap, d::Int; kwargs...) dims = dim.(dimension_inds(imap, d)) @assert all(y -> y == first(dims), dims) @@ -174,7 +148,7 @@ grid_points(imap::RealIndexMap; kwargs...) = grid_points(imap, 1; kwargs...) #multi-dimensional grid_points function grid_points(imap::RealIndexMap, Ns::Vector{Int}, dims::Vector{Int}; kwargs...) if length(Ns) != length(dims) - @throw "length of Ns and dims do not match!" + throw("length of Ns and dims do not match!") end coords = [grid_points(imap, pair[1], pair[2]; kwargs...) for pair in zip(Ns, dims)] gp = Base.Iterators.product(coords...) diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 64c895b..757b248 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -86,17 +86,9 @@ end b = 0.95 test_gridpoints = grid_points(s, N, 1; span=[a, b]) - - points_in_span = floor(b * base^(L / 2)) - ceil(a * base^(L / 2)) + 1 - N_gridpoints = Int(floor(points_in_span / ceil(points_in_span / N))) + 1 - - @test length(test_gridpoints) == N_gridpoints + @test length(test_gridpoints) == N @test test_gridpoints[1] >= a @test test_gridpoints[end] < b - internal = (test_gridpoints[2] - test_gridpoints[1]) - left = (test_gridpoints[1] - a) - right = (b - test_gridpoints[end]) - @test internal >= left && internal >= right end @testset "test grid_points spacing" begin From ddbdc33b4a742fc9967d8bebeea874df5f679fd2 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Wed, 13 Nov 2024 22:49:22 -0800 Subject: [PATCH 27/31] formatting --- src/IndexMaps/realindexmap.jl | 1 - test/test_indexmaps.jl | 3 --- 2 files changed, 4 deletions(-) diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index d59d288..c68a561 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -161,7 +161,6 @@ function grid_points(imap::RealIndexMap, dims::Vector{Int}; kwargs...) return [collect(point) for point in gp] end - """ Picks a random grid point from `imap` given a dimension """ diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 757b248..7950c0d 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -69,11 +69,9 @@ Random.seed!(1234) xyzvals_approx = calculate_p(s, ind_to_ind_value_map, [i for i in 1:dimension(s)]) xyzvals ≈ xyzvals_approx end - end @testset "grid_points tests" begin - @testset "test grid_points irregular span" begin L = 16 base = 2 @@ -158,5 +156,4 @@ end default_rng_gridpoint2 = rand_p(s, 1) y = real(ITensorNumericalAnalysis.evaluate(ψ, default_rng_gridpoint1)) @test y >= -1 && y <= 1 # check to make sure ψ can be evaluated at these points - end From 57433145f0bddac543177a01896e3ddaa94f1cbb Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Wed, 15 Jan 2025 00:14:21 -0800 Subject: [PATCH 28/31] clean up grid_points and rand_p and their tests --- src/IndexMaps/realindexmap.jl | 27 ++++++-------- test/test_indexmaps.jl | 70 +++++++++++++++++++++++++---------- 2 files changed, 62 insertions(+), 35 deletions(-) diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index c68a561..63781b2 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -110,13 +110,10 @@ function grid_points( # generate grid_points within the span (exclusive of right endpoint) grid_points = collect(range(span[1], span[2] - (span[2] - span[1]) / N; length=N)) + + # if exact_grid is true, round to exact gridpoints if exact_grid - for (i, point) in enumerate(grid_points) - grid_points[i] = round_to_nearest_exact_point(point, L) - end - # define lambda function - # round_near = point -> round_to_nearest_exact_point(point, L) - # grid_points = map(round_near, grid_points) + grid_points = round_to_nearest_exact_point.(grid_points, (L,)) grid_points = unique(grid_points) end @@ -128,12 +125,8 @@ function grid_points( return grid_points end -function round_to_nearest_exact_point(point::Number, L::Int) - if point < 0 || point >= 1 - throw("Input point must be between 0 and 1") - end - return round(point * 2.0^L) / 2.0^L -end +round_to_nearest_exact_point(point::Number, L::Int) = round(point * 2.0^min(63,L)) / 2.0^min(63,L) +#TODO: avoid using 2.0^min(63,L) to prevent overflow function grid_points(imap::RealIndexMap, d::Int; kwargs...) dims = dim.(dimension_inds(imap, d)) @@ -152,13 +145,13 @@ function grid_points(imap::RealIndexMap, Ns::Vector{Int}, dims::Vector{Int}; kwa end coords = [grid_points(imap, pair[1], pair[2]; kwargs...) for pair in zip(Ns, dims)] gp = Base.Iterators.product(coords...) - return [collect(point) for point in gp] + return collect.(gp) end function grid_points(imap::RealIndexMap, dims::Vector{Int}; kwargs...) coords = [grid_points(imap, d; kwargs...) for d in dims] gp = Base.Iterators.product(coords...) - return [collect(point) for point in gp] + return collect.(gp) end """ @@ -169,5 +162,9 @@ function rand_p(rng::AbstractRNG, imap::RealIndexMap, d::Integer) @assert all(y -> y == first(dims), dims) base = dims[d] L = length(dimension_inds(imap, d)) - return rand(rng, 0:(big(base)^L - 1)) / big(base)^L + if L > 63 + return rand(rng, 0:(big(base)^L - 1)) / big(base)^L + else + return rand(rng, 0:(base^L - 1)) / base^L + end end diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 7950c0d..db010b1 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -83,6 +83,7 @@ end a = 0.12 b = 0.95 + # test that giving an irregular span still works and it obeys the constraints test_gridpoints = grid_points(s, N, 1; span=[a, b]) @test length(test_gridpoints) == N @test test_gridpoints[1] >= a @@ -102,28 +103,31 @@ end @test length(test2) == N @test test2[1] >= a @test test2[end] < b - internal = (test2[2] - test2[1]) - left = (test2[1] - a) - right = (b - test2[end]) - @test internal >= left && internal >= right + + # test that the spacing between all points is the same + spacing_equal = true + gap = (test2[2] - test2[1]) + for i in 2:(N-1) + if !(test2[i+1] - test2[i] ≈ gap) + spacing_equal = false + end + end + @test spacing_equal end - @testset "test grid_points spacing 2" begin + @testset "test grid_points exact_grid" begin L = 16 g = named_comb_tree((2, L ÷ 2)) s = continuous_siteinds(g; map_dimension=2) a = 0.25 - b = 0.5 + b = 0.6 + + test3 = grid_points(s, 1, span=[a,b], exact_grid=true) - #third set - test3 = grid_points(s, 1) - @test length(test3) == 256 - @test test3[1] >= 0 - @test test3[end] < 1 - internal = (test3[2] - test3[1]) - left = (test3[1] - a) - right = (b - test3[end]) - @test internal >= left && internal >= right + # tests that the number of points generated matches the number of exact gridpoints that fall in the range [a,b). + @test length(test3) == round(b*2^(L÷2)-0.5) - round(a*2^(L÷2)) + 1 + @test test3[1] >= a + @test test3[end] < b end @testset "test grid_points high precision" begin @@ -146,14 +150,40 @@ end #test the use of seedeed randomness rng = Random.Xoshiro(42) - rand_gridpoint1 = rand_p(rng, s) - rand_gridpoint2 = rand_p(rng, s, 1) - x = real(ITensorNumericalAnalysis.evaluate(ψ, rand_gridpoint1)) - @test x >= -1 && x <= 1 # check to make sure ψ can be evaluated at these points + rand_gridpoint = rand_p(rng, s) + x1 = real(ITensorNumericalAnalysis.evaluate(ψ, rand_gridpoint)) + @test x1 >= -1 && x1 <= 1 # check to make sure ψ can be evaluated at these points + + rand_gridpoint1 = rand_p(rng, s, 1) + rand_gridpoint2 = rand_p(rng, s, 2) + x2 = real(ITensorNumericalAnalysis.evaluate(ψ, [rand_gridpoint1, rand_gridpoint2])) + @test x2 >= -1 && x2 <= 1 # check to make sure ψ can be evaluated at these points + + #test the use of default rng + default_rng_gridpoint1 = rand_p(s) + y = real(ITensorNumericalAnalysis.evaluate(ψ, default_rng_gridpoint1)) + @test y >= -1 && y <= 1 # check to make sure ψ can be evaluated at these points + # same things but with smaller L as well + L = 12 + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + ψ = cos_itn(s; dim=1) * cos_itn(s; dim=2) + + #test the use of seedeed randomness + rng = Random.Xoshiro(42) + rand_gridpoint = rand_p(rng, s) + x1 = real(ITensorNumericalAnalysis.evaluate(ψ, rand_gridpoint)) + @test x1 >= -1 && x1 <= 1 # check to make sure ψ can be evaluated at these points + + rand_gridpoint1 = rand_p(rng, s, 1) + rand_gridpoint2 = rand_p(rng, s, 2) + x2 = real(ITensorNumericalAnalysis.evaluate(ψ, [rand_gridpoint1, rand_gridpoint2])) + @test x2 >= -1 && x2 <= 1 # check to make sure ψ can be evaluated at these points + #test the use of default rng default_rng_gridpoint1 = rand_p(s) - default_rng_gridpoint2 = rand_p(s, 1) y = real(ITensorNumericalAnalysis.evaluate(ψ, default_rng_gridpoint1)) @test y >= -1 && y <= 1 # check to make sure ψ can be evaluated at these points + end From f94255723349e787d859bcec984c708ed459c129 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Wed, 15 Jan 2025 00:15:11 -0800 Subject: [PATCH 29/31] formatting --- src/IndexMaps/realindexmap.jl | 4 +++- test/test_indexmaps.jl | 15 +++++++-------- 2 files changed, 10 insertions(+), 9 deletions(-) diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index 63781b2..0f8f65d 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -125,7 +125,9 @@ function grid_points( return grid_points end -round_to_nearest_exact_point(point::Number, L::Int) = round(point * 2.0^min(63,L)) / 2.0^min(63,L) +function round_to_nearest_exact_point(point::Number, L::Int) + return round(point * 2.0^min(63, L)) / 2.0^min(63, L) +end #TODO: avoid using 2.0^min(63,L) to prevent overflow function grid_points(imap::RealIndexMap, d::Int; kwargs...) diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index db010b1..77baa91 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -103,12 +103,12 @@ end @test length(test2) == N @test test2[1] >= a @test test2[end] < b - + # test that the spacing between all points is the same spacing_equal = true gap = (test2[2] - test2[1]) - for i in 2:(N-1) - if !(test2[i+1] - test2[i] ≈ gap) + for i in 2:(N - 1) + if !(test2[i + 1] - test2[i] ≈ gap) spacing_equal = false end end @@ -122,10 +122,10 @@ end a = 0.25 b = 0.6 - test3 = grid_points(s, 1, span=[a,b], exact_grid=true) + test3 = grid_points(s, 1; span=[a, b], exact_grid=true) # tests that the number of points generated matches the number of exact gridpoints that fall in the range [a,b). - @test length(test3) == round(b*2^(L÷2)-0.5) - round(a*2^(L÷2)) + 1 + @test length(test3) == round(b * 2^(L ÷ 2) - 0.5) - round(a * 2^(L ÷ 2)) + 1 @test test3[1] >= a @test test3[end] < b end @@ -158,7 +158,7 @@ end rand_gridpoint2 = rand_p(rng, s, 2) x2 = real(ITensorNumericalAnalysis.evaluate(ψ, [rand_gridpoint1, rand_gridpoint2])) @test x2 >= -1 && x2 <= 1 # check to make sure ψ can be evaluated at these points - + #test the use of default rng default_rng_gridpoint1 = rand_p(s) y = real(ITensorNumericalAnalysis.evaluate(ψ, default_rng_gridpoint1)) @@ -180,10 +180,9 @@ end rand_gridpoint2 = rand_p(rng, s, 2) x2 = real(ITensorNumericalAnalysis.evaluate(ψ, [rand_gridpoint1, rand_gridpoint2])) @test x2 >= -1 && x2 <= 1 # check to make sure ψ can be evaluated at these points - + #test the use of default rng default_rng_gridpoint1 = rand_p(s) y = real(ITensorNumericalAnalysis.evaluate(ψ, default_rng_gridpoint1)) @test y >= -1 && y <= 1 # check to make sure ψ can be evaluated at these points - end From e1572420346c310615fe4796abb81d7a84047909 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Wed, 15 Jan 2025 08:50:12 -0800 Subject: [PATCH 30/31] generalize round_to_nearest_exact_point and added complexindexmap rand_p test --- src/IndexMaps/complexindexmap.jl | 10 +-- src/IndexMaps/realindexmap.jl | 6 +- test/test_indexmaps.jl | 103 ++++++++++++++++++------------- 3 files changed, 69 insertions(+), 50 deletions(-) diff --git a/src/IndexMaps/complexindexmap.jl b/src/IndexMaps/complexindexmap.jl index d197667..e6d10f0 100644 --- a/src/IndexMaps/complexindexmap.jl +++ b/src/IndexMaps/complexindexmap.jl @@ -136,7 +136,7 @@ function grid_points(imap::ComplexIndexMap, N::Int, d::Int) dims = dim.(dimension_inds(imap, d)) @assert all(y -> y == first(dims), dims) base = float(first(dims)) - Lre, Lim = length(real_indices(imap, d)), length(imag_indices(imap, d)) + Lre, Lim = length(real_indices(imap, d)), length(imaginary_indices(imap, d)) are, aim = round(base^Lre / N), round(base^Lim / N) grid_points = [ i * (are / base^Lre) + im * j * (aim / base^Lim) for i in 0:(N + 1) for j in 0:(N + 1) @@ -151,7 +151,9 @@ function rand_p(rng::AbstractRNG, imap::ComplexIndexMap, d::Integer) dims = dim.(dimension_inds(imap, d)) @assert all(y -> y == first(dims), dims) base = float(first(dims)) - Lre, Lim = length(real_indices(imap, d)), length(imag_indices(imap, d)) - return rand(rng, 0:(big(base)^Lre - 1)) / big(base)^Lre + - im * rand(rng, 0:(big(base)^Lim - 1)) / big(base)^Lim + Lre, Lim = length(real_indices(imap, d)), length(imaginary_indices(imap, d)) + + real_part = Lre > 63 ? rand(rng, 0:(big(base)^Lre - 1)) / big(base)^Lre : rand(rng, 0:(base^Lre - 1)) / base^Lre + imag_part = Lim > 63 ? im * rand(rng, 0:(big(base)^Lim - 1)) / big(base)^Lim : im * rand(rng, 0:(base^Lim - 1)) / base^Lim + return real_part + imag_part end diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index 0f8f65d..2e1ca7a 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -113,7 +113,7 @@ function grid_points( # if exact_grid is true, round to exact gridpoints if exact_grid - grid_points = round_to_nearest_exact_point.(grid_points, (L,)) + grid_points = round_to_nearest_exact_point.(grid_points, (L,), (base,)) grid_points = unique(grid_points) end @@ -125,8 +125,8 @@ function grid_points( return grid_points end -function round_to_nearest_exact_point(point::Number, L::Int) - return round(point * 2.0^min(63, L)) / 2.0^min(63, L) +function round_to_nearest_exact_point(point::Number, L::Int, base::Int = 2) + return round(point * Float64(base)^min(63, L)) / Float64(base)^min(63, L) end #TODO: avoid using 2.0^min(63,L) to prevent overflow diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 77baa91..97f746c 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -142,47 +142,64 @@ end end @testset "test rand_p" begin - #test the rand_p() function to see if it succeeds on large L - L = 140 - g = named_comb_tree((2, L ÷ 2)) - s = continuous_siteinds(g; map_dimension=2) - ψ = cos_itn(s; dim=1) * cos_itn(s; dim=2) - - #test the use of seedeed randomness - rng = Random.Xoshiro(42) - rand_gridpoint = rand_p(rng, s) - x1 = real(ITensorNumericalAnalysis.evaluate(ψ, rand_gridpoint)) - @test x1 >= -1 && x1 <= 1 # check to make sure ψ can be evaluated at these points - - rand_gridpoint1 = rand_p(rng, s, 1) - rand_gridpoint2 = rand_p(rng, s, 2) - x2 = real(ITensorNumericalAnalysis.evaluate(ψ, [rand_gridpoint1, rand_gridpoint2])) - @test x2 >= -1 && x2 <= 1 # check to make sure ψ can be evaluated at these points - - #test the use of default rng - default_rng_gridpoint1 = rand_p(s) - y = real(ITensorNumericalAnalysis.evaluate(ψ, default_rng_gridpoint1)) - @test y >= -1 && y <= 1 # check to make sure ψ can be evaluated at these points - - # same things but with smaller L as well - L = 12 - g = named_comb_tree((2, L ÷ 2)) - s = continuous_siteinds(g; map_dimension=2) - ψ = cos_itn(s; dim=1) * cos_itn(s; dim=2) - - #test the use of seedeed randomness - rng = Random.Xoshiro(42) - rand_gridpoint = rand_p(rng, s) - x1 = real(ITensorNumericalAnalysis.evaluate(ψ, rand_gridpoint)) - @test x1 >= -1 && x1 <= 1 # check to make sure ψ can be evaluated at these points - - rand_gridpoint1 = rand_p(rng, s, 1) - rand_gridpoint2 = rand_p(rng, s, 2) - x2 = real(ITensorNumericalAnalysis.evaluate(ψ, [rand_gridpoint1, rand_gridpoint2])) - @test x2 >= -1 && x2 <= 1 # check to make sure ψ can be evaluated at these points - - #test the use of default rng - default_rng_gridpoint1 = rand_p(s) - y = real(ITensorNumericalAnalysis.evaluate(ψ, default_rng_gridpoint1)) - @test y >= -1 && y <= 1 # check to make sure ψ can be evaluated at these points + @testset "test rand_p for realindexmaps" begin + #test the rand_p() function to see if it succeeds on large L + L = 140 + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + ψ = cos_itn(s; dim=1) * cos_itn(s; dim=2) + + #test the use of seedeed randomness + rng = Random.Xoshiro(42) + rand_gridpoint = rand_p(rng, s) + x1 = real(ITensorNumericalAnalysis.evaluate(ψ, rand_gridpoint)) + @test x1 >= -1 && x1 <= 1 # check to make sure ψ can be evaluated at these points + + rand_gridpoint1 = rand_p(rng, s, 1) + rand_gridpoint2 = rand_p(rng, s, 2) + x2 = real(ITensorNumericalAnalysis.evaluate(ψ, [rand_gridpoint1, rand_gridpoint2])) + @test x2 >= -1 && x2 <= 1 # check to make sure ψ can be evaluated at these points + + #test the use of default rng + default_rng_gridpoint1 = rand_p(s) + y = real(ITensorNumericalAnalysis.evaluate(ψ, default_rng_gridpoint1)) + @test y >= -1 && y <= 1 # check to make sure ψ can be evaluated at these points + + # same things but with smaller L as well + L = 12 + g = named_comb_tree((2, L ÷ 2)) + s = continuous_siteinds(g; map_dimension=2) + ψ = cos_itn(s; dim=1) * cos_itn(s; dim=2) + + #test the use of seedeed randomness + rng = Random.Xoshiro(42) + rand_gridpoint = rand_p(rng, s) + x1 = real(ITensorNumericalAnalysis.evaluate(ψ, rand_gridpoint)) + @test x1 >= -1 && x1 <= 1 # check to make sure ψ can be evaluated at these points + + rand_gridpoint1 = rand_p(rng, s, 1) + rand_gridpoint2 = rand_p(rng, s, 2) + x2 = real(ITensorNumericalAnalysis.evaluate(ψ, [rand_gridpoint1, rand_gridpoint2])) + @test x2 >= -1 && x2 <= 1 # check to make sure ψ can be evaluated at these points + + #test the use of default rng + default_rng_gridpoint1 = rand_p(s) + y = real(ITensorNumericalAnalysis.evaluate(ψ, default_rng_gridpoint1)) + @test y >= -1 && y <= 1 # check to make sure ψ can be evaluated at these points + end + + @testset "test rand_p for complexindexmaps" begin + L = 16 + g = named_comb_tree((2,L÷2)) + vs = collect(vertices(g)) + split = div(length(vs), 2) + real_vs = [vs[1:split]] + imag_vs = [vs[split+1:end]] + s = complex_continuous_siteinds(g, real_vs, imag_vs) + ψ = poly_itn(s, [0, 0, 1]) + + rand_gridpoint = rand_p(s) + x = ITensorNumericalAnalysis.evaluate(ψ, rand_gridpoint) + @test real(x) >= -1 && real(x) <= 1 && imag(x) >= -1 && imag(x) <= 1 + end end From 1b64e1245f87b8b39f8d1f692b376c9439e519d7 Mon Sep 17 00:00:00 2001 From: Ryan Anselm Date: Wed, 15 Jan 2025 08:50:38 -0800 Subject: [PATCH 31/31] formatting --- src/IndexMaps/complexindexmap.jl | 12 ++++++++++-- src/IndexMaps/realindexmap.jl | 2 +- test/test_indexmaps.jl | 4 ++-- 3 files changed, 13 insertions(+), 5 deletions(-) diff --git a/src/IndexMaps/complexindexmap.jl b/src/IndexMaps/complexindexmap.jl index e6d10f0..f697ae4 100644 --- a/src/IndexMaps/complexindexmap.jl +++ b/src/IndexMaps/complexindexmap.jl @@ -153,7 +153,15 @@ function rand_p(rng::AbstractRNG, imap::ComplexIndexMap, d::Integer) base = float(first(dims)) Lre, Lim = length(real_indices(imap, d)), length(imaginary_indices(imap, d)) - real_part = Lre > 63 ? rand(rng, 0:(big(base)^Lre - 1)) / big(base)^Lre : rand(rng, 0:(base^Lre - 1)) / base^Lre - imag_part = Lim > 63 ? im * rand(rng, 0:(big(base)^Lim - 1)) / big(base)^Lim : im * rand(rng, 0:(base^Lim - 1)) / base^Lim + real_part = if Lre > 63 + rand(rng, 0:(big(base)^Lre - 1)) / big(base)^Lre + else + rand(rng, 0:(base^Lre - 1)) / base^Lre + end + imag_part = if Lim > 63 + im * rand(rng, 0:(big(base)^Lim - 1)) / big(base)^Lim + else + im * rand(rng, 0:(base^Lim - 1)) / base^Lim + end return real_part + imag_part end diff --git a/src/IndexMaps/realindexmap.jl b/src/IndexMaps/realindexmap.jl index 2e1ca7a..2516591 100644 --- a/src/IndexMaps/realindexmap.jl +++ b/src/IndexMaps/realindexmap.jl @@ -125,7 +125,7 @@ function grid_points( return grid_points end -function round_to_nearest_exact_point(point::Number, L::Int, base::Int = 2) +function round_to_nearest_exact_point(point::Number, L::Int, base::Int=2) return round(point * Float64(base)^min(63, L)) / Float64(base)^min(63, L) end #TODO: avoid using 2.0^min(63,L) to prevent overflow diff --git a/test/test_indexmaps.jl b/test/test_indexmaps.jl index 97f746c..3c17745 100644 --- a/test/test_indexmaps.jl +++ b/test/test_indexmaps.jl @@ -190,11 +190,11 @@ end @testset "test rand_p for complexindexmaps" begin L = 16 - g = named_comb_tree((2,L÷2)) + g = named_comb_tree((2, L ÷ 2)) vs = collect(vertices(g)) split = div(length(vs), 2) real_vs = [vs[1:split]] - imag_vs = [vs[split+1:end]] + imag_vs = [vs[(split + 1):end]] s = complex_continuous_siteinds(g, real_vs, imag_vs) ψ = poly_itn(s, [0, 0, 1])